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diff --git a/PV_prediction/ML_V2.ipynb b/PV_prediction/ML_V2.ipynb
index a8c28e3..cadeaba 100644
--- a/PV_prediction/ML_V2.ipynb
+++ b/PV_prediction/ML_V2.ipynb
@@ -1,10668 +1,15147 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+ "/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" from ._conv import register_converters as _register_converters\n"
]
}
],
"source": [
"import pandas as pd\n",
"import xarray as xr\n",
"import numpy as np\n",
"import itertools\n",
"\n",
"from rooftop_handling import link_rooftops_with_pixels\n",
"import util\n",
"\n",
"from sklearn import tree\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.neighbors import KNeighborsRegressor\n",
"from sklearn.neural_network import MLPRegressor\n",
"from sklearn.svm import SVR\n",
"from sklearn.metrics import mean_squared_error as mse\n",
"from sklearn.metrics import mean_absolute_error as mae\n",
"from sklearn.metrics import r2_score as r2\n",
"from sklearn.model_selection import cross_val_predict\n",
"from sklearn.preprocessing import Normalizer\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.base import clone\n",
"from ELM_ensemble import ELM_Ensemble\n",
"from scipy.stats import describe\n",
"from uncertainty import Uncertainty\n",
"\n",
"import os\n",
"import time\n",
"\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.colors import LinearSegmentedColormap"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"colorsRGB = [(47,111,191),\n",
" (51,148,190),\n",
" (65,195,153),\n",
" (105,219,77),\n",
" (183,233,81),\n",
" (249,239,88),\n",
" (250,201,53),\n",
" (246,135,26),\n",
" (220,82,7),\n",
" (193,31,4)]\n",
"colors = []\n",
"for row in colorsRGB:\n",
" colors.append(tuple([i/255.0 for i in row]))\n",
" \n",
"cm_PV = LinearSegmentedColormap.from_list('radiation', colors, N=500)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def rescale(vector, training):\n",
" return (vector * training.std()) + training.mean()\n",
"\n",
"def normalize(vector, training):\n",
" return (vector - training.mean()) / training.std()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def notnan( x ):\n",
" return x[~np.isnan(x)]\n",
"\n",
"# ERROR MEASUREMENTS\n",
"error = {\n",
" 'MSE' : lambda y, t: mse(t,y),\n",
" 'RMSE': lambda y, t: np.sqrt(mse(t,y)),\n",
" 'MAE' : lambda y, t: mae(t,y),\n",
" 'MAEP': lambda y, t: mae(np.ones(len(y)), notnan(y/t)),\n",
" 'MBE' : lambda y, t: np.mean(t - y),\n",
" 'MBEP': lambda y, t: np.mean(1 - notnan(y/t)),\n",
" 'R2' : lambda y, t: r2(t,y)\n",
"}\n",
"\n",
"def get_errors(true, pred, label = ''):\n",
" # create a pandas series with errors and print them\n",
" true = true.reshape((-1,1))\n",
" pred = pred.reshape((-1,1))\n",
" \n",
" err_series = pd.Series(data = np.zeros(len(error)), index = error.keys())\n",
" for key, val in error.items():\n",
" print('%s %s: %f' %(label, key, val(pred, true)))\n",
" err_series[ key ] = val(pred, true)\n",
" \n",
" return err_series"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def shp( vector ):\n",
"# check shape of vector and reshape it to one dimension if it is a one-dimensional vector\n",
" if len( label_name ) == 1:\n",
" return vector.reshape((-1,1))\n",
" else:\n",
" return vector "
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def compute_residuals( prediction, target, model_std):\n",
" residuals = ( prediction - target )**2 - model_std**2\n",
" return np.sqrt( np.maximum(residuals, 0) ) "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
- "path = '/Volumes/Seagate Backup Plus Drive/DOKUMENTE/EPFL/data/Results/PV_w_uncertainty/pv_prediction/'"
+ "# path = '/Volumes/Seagate Backup Plus Drive/DOKUMENTE/EPFL/data/Results/PV_w_uncertainty/pv_prediction/'\n",
+ "path = '/work/hyenergy/output/solar_potential/technical_potential/predict_pv'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load data"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:472: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
+ "/home/walch/miniconda3/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:569: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" mask |= (ar1 == a)\n"
]
}
],
"source": [
"features = pd.read_csv(os.path.join(path, 'features_v2.csv'), index_col = 0)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:472: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
- " mask |= (ar1 == a)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"targets = pd.read_csv(os.path.join(path, 'targets_v2.csv'), index_col = 0)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/numpy/lib/arraysetops.py:472: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
- " mask |= (ar1 == a)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"communes = pd.read_csv(os.path.join(path, 'data_all.csv'), index_col = 0,\n",
" usecols = ['DF_UID', 'Kanton', 'Commune_ID', 'XCOORD', 'YCOORD', 'FLAECHE', 'GWR_EGID'])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"data = pd.concat([features, targets, communes], axis = 1).dropna()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>SIS</th>\n",
" <th>SISDIR</th>\n",
" <th>DHI</th>\n",
" <th>SVF</th>\n",
" <th>illumination</th>\n",
" <th>horizon_S</th>\n",
" <th>horizon_E</th>\n",
" <th>horizon_NEE</th>\n",
" <th>...</th>\n",
" <th>horizon_SSE</th>\n",
" <th>horizon_SEE</th>\n",
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" <th>PV_kWh_m2</th>\n",
" <th>FLAECHE</th>\n",
" <th>XCOORD</th>\n",
" <th>YCOORD</th>\n",
" <th>GWR_EGID</th>\n",
" <th>Kanton</th>\n",
" <th>Commune_ID</th>\n",
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" <td>0.706426</td>\n",
" <td>0.738014</td>\n",
" <td>12.730241</td>\n",
" <td>21.675634</td>\n",
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],
"text/plain": [
" NEIGUNG AUSRICHTUNG SIS SISDIR DHI SVF \\\n",
"DF_UID \n",
"5343176 16 -17.0 1350.071526 846.491412 503.587476 0.718741 \n",
"5343175 17 163.0 1350.071526 846.491412 503.587476 0.759114 \n",
"5343177 25 -59.0 1350.071526 846.491412 503.587476 0.706426 \n",
"5343178 24 121.0 1350.071526 846.491412 503.587476 0.643597 \n",
"5343214 11 168.0 1350.071526 846.491412 503.587476 0.598916 \n",
"\n",
- " illumination horizon_S horizon_E horizon_NEE ... horizon_SSE \\\n",
- "DF_UID ... \n",
- "5343176 0.811781 6.092388 14.689941 17.452604 ... 8.197643 \n",
- "5343175 0.804061 11.788798 16.118021 15.847362 ... 13.261172 \n",
- "5343177 0.738014 12.730241 21.675634 21.338327 ... 13.979061 \n",
- "5343178 0.654795 16.819239 18.360150 19.976019 ... 12.246127 \n",
- "5343214 0.448989 43.407631 15.740415 5.747942 ... 44.075201 \n",
+ " illumination horizon_S horizon_E horizon_NEE ... \\\n",
+ "DF_UID ... \n",
+ "5343176 0.811781 6.092388 14.689941 17.452604 ... \n",
+ "5343175 0.804061 11.788798 16.118021 15.847362 ... \n",
+ "5343177 0.738014 12.730241 21.675634 21.338327 ... \n",
+ "5343178 0.654795 16.819239 18.360150 19.976019 ... \n",
+ "5343214 0.448989 43.407631 15.740415 5.747942 ... \n",
"\n",
- " horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE XCOORD \\\n",
+ " horizon_SSE horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE \\\n",
"DF_UID \n",
- "5343176 9.963911 1548 210.528 108.129956 722110.3750 \n",
- "5343175 13.841580 1114 151.504 110.595071 722108.1875 \n",
- "5343177 15.757084 545 74.120 20.512037 722494.3125 \n",
- "5343178 15.541741 598 81.328 20.850745 722491.9375 \n",
- "5343214 35.429473 1032 140.352 168.164462 722125.8125 \n",
- "\n",
- " YCOORD GWR_EGID Kanton Commune_ID \n",
- "DF_UID \n",
- "5343176 75509.609375 11157515.0 TI 5250.0 \n",
- "5343175 75516.570312 11157515.0 TI 5250.0 \n",
- "5343177 75592.125000 11103162.0 TI 5250.0 \n",
- "5343178 75593.523438 11103162.0 TI 5250.0 \n",
- "5343214 75788.093750 11157513.0 TI 5250.0 \n",
+ "5343176 8.197643 9.963911 1548 210.528 108.129956 \n",
+ "5343175 13.261172 13.841580 1114 151.504 110.595071 \n",
+ "5343177 13.979061 15.757084 545 74.120 20.512037 \n",
+ "5343178 12.246127 15.541741 598 81.328 20.850745 \n",
+ "5343214 44.075201 35.429473 1032 140.352 168.164462 \n",
+ "\n",
+ " XCOORD YCOORD GWR_EGID Kanton Commune_ID \n",
+ "DF_UID \n",
+ "5343176 722110.3750 75509.609375 11157515.0 TI 5250.0 \n",
+ "5343175 722108.1875 75516.570312 11157515.0 TI 5250.0 \n",
+ "5343177 722494.3125 75592.125000 11103162.0 TI 5250.0 \n",
+ "5343178 722491.9375 75593.523438 11103162.0 TI 5250.0 \n",
+ "5343214 722125.8125 75788.093750 11157513.0 TI 5250.0 \n",
"\n",
"[5 rows x 24 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
- "workdir = '/Users/alinawalch/Documents/EPFL/data/interactive_visualisation'\n",
+ "# workdir = '/Users/alinawalch/Documents/EPFL/data/interactive_visualisation'\n",
+ "workdir = '/work/hyenergy/raw/Surface_data/swissBOUNDARIES3D/BOUNDARIES_2019/DATEN/swissBOUNDARIES3D/SHAPEFILE_LV03_LN02'\n",
"commune_data = pd.read_csv(os.path.join(workdir, 'swissBOUNDARIES3D_1_3_TLM_HOHEITSGEBIET_data.csv'))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Part 1: Define features & normalize"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"label_name = ['MSTRAHLUNG']\n",
"identifier = 'DF_UID'\n",
"\n",
"all_features = features.columns\n",
"# feature_labels = ['Roof tilt', 'Roof aspect', 'Annual GHI', 'Horizon (S)', 'Horizon (E)', 'Horizon (W)']\n",
"\n",
"feature_names = ['SIS', 'horizon_SEE', 'horizon_SWW', 'horizon_S', 'NEIGUNG', 'AUSRICHTUNG']\n",
"\n",
"feature_labels = ['Annual GHI', 'Horizon SEE (120°)', 'Horizon SWW (240°)', 'Horizon S (180°)', \n",
" 'Roof tilt', 'Roof aspect', ]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"def get_data( data, feature_names, label_name ):\n",
" X = data.loc[ : , feature_names ].values\n",
" T = data.loc[ : , label_name ].values.reshape((-1,))\n",
"\n",
" norm = Normalizer()\n",
" x = norm.fit_transform(X)\n",
" t = normalize(T, T)\n",
" \n",
" return x, t, X, T"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"def get_mse( x, t, model, cv = 5, print_time = True ):\n",
" \n",
" est = set_estimators()[ model ]\n",
"\n",
" # normalized cross-validation\n",
" tt = time.time()\n",
" y = cross_val_predict(est, x, t, n_jobs = -1) # cannot use n_jobs = -1 as not all are scikit-learn estimators\n",
" cv_time = time.time()-tt\n",
" if print_time : \n",
" print('Crossvalidation time: %.3fs' %cv_time)\n",
"\n",
" # Y = rescale(y, T)\n",
" return mse(t, y), 0, cv_time # mse(t, y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Part 2: Get train and test areas"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Part 2.1: Choose training areas and testing areas (based on Cantons)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#'/work/hyenergy/output/solar_potential/technical_potential/interactive_visualisation'\n",
"workdir = '/Users/alinawalch/Documents/EPFL/data/interactive_visualisation'\n",
"communes = gpd.read_file(os.path.join(workdir, 'swissBOUNDARIES3D_1_3_TLM_HOHEITSGEBIET.shp'))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
- "COMMUNE_FP = '/Users/alinawalch/Documents/EPFL/data/GWR/GDEListe_20150101.txt'\n",
+ "# COMMUNE_FP = '/Users/alinawalch/Documents/EPFL/data/GWR/GDEListe_20150101.txt'\n",
+ "COMMUNE_FP = '/work/hyenergy/raw/GWR_Reg-BL/GDEListe_20150101.txt'\n",
"commune_info = pd.read_csv( COMMUNE_FP, sep = '\\t', encoding = 'cp1250' )"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>GDEKT</th>\n",
" <th>GDEBZNR</th>\n",
" <th>GDENR</th>\n",
" <th>GDENAME</th>\n",
" <th>GDENAMK</th>\n",
" <th>GDEBZNA</th>\n",
" <th>GDEKTNA</th>\n",
" <th>GDEMUTDAT</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2058</th>\n",
" <td>VS</td>\n",
" <td>2302.0</td>\n",
" <td>6021.0</td>\n",
" <td>Ardon</td>\n",
" <td>Ardon</td>\n",
" <td>District de Conthey</td>\n",
" <td>Valais / Wallis</td>\n",
" <td>01.01.1960</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2059</th>\n",
" <td>VS</td>\n",
" <td>2302.0</td>\n",
" <td>6022.0</td>\n",
" <td>Chamoson</td>\n",
" <td>Chamoson</td>\n",
" <td>District de Conthey</td>\n",
" <td>Valais / Wallis</td>\n",
" <td>01.01.1960</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2060</th>\n",
" <td>VS</td>\n",
" <td>2302.0</td>\n",
" <td>6023.0</td>\n",
" <td>Conthey</td>\n",
" <td>Conthey</td>\n",
" <td>District de Conthey</td>\n",
" <td>Valais / Wallis</td>\n",
" <td>01.01.1960</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2061</th>\n",
" <td>VS</td>\n",
" <td>2302.0</td>\n",
" <td>6024.0</td>\n",
" <td>Nendaz</td>\n",
" <td>Nendaz</td>\n",
" <td>District de Conthey</td>\n",
" <td>Valais / Wallis</td>\n",
" <td>01.01.1960</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2062</th>\n",
" <td>VS</td>\n",
" <td>2302.0</td>\n",
" <td>6025.0</td>\n",
" <td>Vétroz</td>\n",
" <td>Vétroz</td>\n",
" <td>District de Conthey</td>\n",
" <td>Valais / Wallis</td>\n",
" <td>01.01.1960</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" GDEKT GDEBZNR GDENR GDENAME GDENAMK GDEBZNA \\\n",
"2058 VS 2302.0 6021.0 Ardon Ardon District de Conthey \n",
"2059 VS 2302.0 6022.0 Chamoson Chamoson District de Conthey \n",
"2060 VS 2302.0 6023.0 Conthey Conthey District de Conthey \n",
"2061 VS 2302.0 6024.0 Nendaz Nendaz District de Conthey \n",
"2062 VS 2302.0 6025.0 Vétroz Vétroz District de Conthey \n",
"\n",
" GDEKTNA GDEMUTDAT \n",
"2058 Valais / Wallis 01.01.1960 \n",
"2059 Valais / Wallis 01.01.1960 \n",
"2060 Valais / Wallis 01.01.1960 \n",
"2061 Valais / Wallis 01.01.1960 \n",
"2062 Valais / Wallis 01.01.1960 "
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# find french-speaking communes in Valais based on the start of their district name ('District' and not 'Bezirk')\n",
"districts_valais = commune_info[ commune_info.GDEKT == 'VS' ]\n",
"french_communes = [bzg[0:8] == 'District' for bzg in districts_valais.GDEBZNA.values]\n",
"districts_valais[french_communes].head()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"french_cantons = ['NE', 'JU', 'VD', 'GE', 'FR'] # plus french communes in Valais; considering FR even though bilangue"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"training_data = data[(data.Kanton.isin( french_cantons )) \\\n",
" | (data.Commune_ID.isin( districts_valais[french_communes].GDENR.values )) ]\n",
"training_data = training_data.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
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"text/plain": [
" NEIGUNG AUSRICHTUNG SIS SISDIR DHI SVF \\\n",
"DF_UID \n",
"9449166 0 0.0 1552.478067 900.636293 651.867345 0.794826 \n",
"9449168 27 7.0 1552.478067 900.636293 651.867345 0.755589 \n",
"9449167 25 -173.0 1552.478067 900.636293 651.867345 0.764098 \n",
"9449170 34 22.0 1552.478067 900.636293 651.867345 0.803094 \n",
"9449157 33 22.0 1552.478067 900.636293 651.867345 0.785625 \n",
"\n",
- " illumination horizon_S horizon_E horizon_NEE ... horizon_SSE \\\n",
- "DF_UID ... \n",
- "9449166 0.816486 19.170645 8.315230 8.125061 ... 27.173886 \n",
- "9449168 0.728311 30.907117 4.143541 1.431431 ... 29.991368 \n",
- "9449167 0.753425 30.548385 3.495298 0.715425 ... 28.331859 \n",
- "9449170 0.886675 21.041524 2.523374 2.499965 ... 21.660933 \n",
- "9449157 0.873858 17.481223 8.517506 8.390612 ... 20.984736 \n",
+ " illumination horizon_S horizon_E horizon_NEE ... \\\n",
+ "DF_UID ... \n",
+ "9449166 0.816486 19.170645 8.315230 8.125061 ... \n",
+ "9449168 0.728311 30.907117 4.143541 1.431431 ... \n",
+ "9449167 0.753425 30.548385 3.495298 0.715425 ... \n",
+ "9449170 0.886675 21.041524 2.523374 2.499965 ... \n",
+ "9449157 0.873858 17.481223 8.517506 8.390612 ... \n",
"\n",
- " horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE XCOORD \\\n",
+ " horizon_SSE horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE \\\n",
"DF_UID \n",
- "9449166 19.419470 1418 192.848 113.600622 579172.9375 \n",
- "9449168 17.834692 1577 214.472 32.135801 579235.2500 \n",
- "9449167 15.277346 1086 147.696 33.816775 579235.6875 \n",
- "9449170 6.787898 1572 213.792 162.651604 579209.9375 \n",
- "9449157 10.082763 1630 221.680 175.680874 579190.1875 \n",
- "\n",
- " YCOORD GWR_EGID Kanton Commune_ID \n",
- "DF_UID \n",
- "9449166 79689.500000 902671.0 VS 6032.0 \n",
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+ "9449170 21.660933 6.787898 1572 213.792 162.651604 \n",
+ "9449157 20.984736 10.082763 1630 221.680 175.680874 \n",
+ "\n",
+ " XCOORD YCOORD GWR_EGID Kanton Commune_ID \n",
+ "DF_UID \n",
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+ "9449168 579235.2500 79689.906250 902671.0 VS 6032.0 \n",
+ "9449167 579235.6875 79693.085938 902671.0 VS 6032.0 \n",
+ "9449170 579209.9375 79712.953125 902671.0 VS 6032.0 \n",
+ "9449157 579190.1875 79714.609375 902671.0 VS 6032.0 \n",
"\n",
"[5 rows x 24 columns]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"training_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1909876"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(training_data)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"testing_data = data[ np.logical_not(data.index.isin( training_data.index.values )) ]\n",
"testing_data = testing_data.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6672012"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(testing_data)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"scrolled": true
},
"outputs": [
{
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" <tr>\n",
" <th>5343177</th>\n",
" <td>25</td>\n",
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" <td>545</td>\n",
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" <td>20.512037</td>\n",
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" <tr>\n",
" <th>5343178</th>\n",
" <td>24</td>\n",
" <td>121.0</td>\n",
" <td>1350.071526</td>\n",
" <td>846.491412</td>\n",
" <td>503.587476</td>\n",
" <td>0.643597</td>\n",
" <td>0.654795</td>\n",
" <td>16.819239</td>\n",
" <td>18.360150</td>\n",
" <td>19.976019</td>\n",
" <td>...</td>\n",
" <td>12.246127</td>\n",
" <td>15.541741</td>\n",
" <td>598</td>\n",
" <td>81.328</td>\n",
" <td>20.850745</td>\n",
" <td>722491.9375</td>\n",
" <td>75593.523438</td>\n",
" <td>11103162.0</td>\n",
" <td>TI</td>\n",
" <td>5250.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5343214</th>\n",
" <td>11</td>\n",
" <td>168.0</td>\n",
" <td>1350.071526</td>\n",
" <td>846.491412</td>\n",
" <td>503.587476</td>\n",
" <td>0.598916</td>\n",
" <td>0.448989</td>\n",
" <td>43.407631</td>\n",
" <td>15.740415</td>\n",
" <td>5.747942</td>\n",
" <td>...</td>\n",
" <td>44.075201</td>\n",
" <td>35.429473</td>\n",
" <td>1032</td>\n",
" <td>140.352</td>\n",
" <td>168.164462</td>\n",
" <td>722125.8125</td>\n",
" <td>75788.093750</td>\n",
" <td>11157513.0</td>\n",
" <td>TI</td>\n",
" <td>5250.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 24 columns</p>\n",
"</div>"
],
"text/plain": [
" NEIGUNG AUSRICHTUNG SIS SISDIR DHI SVF \\\n",
"DF_UID \n",
"5343176 16 -17.0 1350.071526 846.491412 503.587476 0.718741 \n",
"5343175 17 163.0 1350.071526 846.491412 503.587476 0.759114 \n",
"5343177 25 -59.0 1350.071526 846.491412 503.587476 0.706426 \n",
"5343178 24 121.0 1350.071526 846.491412 503.587476 0.643597 \n",
"5343214 11 168.0 1350.071526 846.491412 503.587476 0.598916 \n",
"\n",
- " illumination horizon_S horizon_E horizon_NEE ... horizon_SSE \\\n",
- "DF_UID ... \n",
- "5343176 0.811781 6.092388 14.689941 17.452604 ... 8.197643 \n",
- "5343175 0.804061 11.788798 16.118021 15.847362 ... 13.261172 \n",
- "5343177 0.738014 12.730241 21.675634 21.338327 ... 13.979061 \n",
- "5343178 0.654795 16.819239 18.360150 19.976019 ... 12.246127 \n",
- "5343214 0.448989 43.407631 15.740415 5.747942 ... 44.075201 \n",
+ " illumination horizon_S horizon_E horizon_NEE ... \\\n",
+ "DF_UID ... \n",
+ "5343176 0.811781 6.092388 14.689941 17.452604 ... \n",
+ "5343175 0.804061 11.788798 16.118021 15.847362 ... \n",
+ "5343177 0.738014 12.730241 21.675634 21.338327 ... \n",
+ "5343178 0.654795 16.819239 18.360150 19.976019 ... \n",
+ "5343214 0.448989 43.407631 15.740415 5.747942 ... \n",
"\n",
- " horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE XCOORD \\\n",
+ " horizon_SSE horizon_SEE MSTRAHLUNG PV_kWh_m2 FLAECHE \\\n",
"DF_UID \n",
- "5343176 9.963911 1548 210.528 108.129956 722110.3750 \n",
- "5343175 13.841580 1114 151.504 110.595071 722108.1875 \n",
- "5343177 15.757084 545 74.120 20.512037 722494.3125 \n",
- "5343178 15.541741 598 81.328 20.850745 722491.9375 \n",
- "5343214 35.429473 1032 140.352 168.164462 722125.8125 \n",
- "\n",
- " YCOORD GWR_EGID Kanton Commune_ID \n",
- "DF_UID \n",
- "5343176 75509.609375 11157515.0 TI 5250.0 \n",
- "5343175 75516.570312 11157515.0 TI 5250.0 \n",
- "5343177 75592.125000 11103162.0 TI 5250.0 \n",
- "5343178 75593.523438 11103162.0 TI 5250.0 \n",
- "5343214 75788.093750 11157513.0 TI 5250.0 \n",
+ "5343176 8.197643 9.963911 1548 210.528 108.129956 \n",
+ "5343175 13.261172 13.841580 1114 151.504 110.595071 \n",
+ "5343177 13.979061 15.757084 545 74.120 20.512037 \n",
+ "5343178 12.246127 15.541741 598 81.328 20.850745 \n",
+ "5343214 44.075201 35.429473 1032 140.352 168.164462 \n",
+ "\n",
+ " XCOORD YCOORD GWR_EGID Kanton Commune_ID \n",
+ "DF_UID \n",
+ "5343176 722110.3750 75509.609375 11157515.0 TI 5250.0 \n",
+ "5343175 722108.1875 75516.570312 11157515.0 TI 5250.0 \n",
+ "5343177 722494.3125 75592.125000 11103162.0 TI 5250.0 \n",
+ "5343178 722491.9375 75593.523438 11103162.0 TI 5250.0 \n",
+ "5343214 722125.8125 75788.093750 11157513.0 TI 5250.0 \n",
"\n",
"[5 rows x 24 columns]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"testing_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get cities"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"cities = ['Luzern', 'Zürich', 'Basel', 'Lugano', 'Interlaken', 'Davos']"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"city_data = {}\n",
"for name in cities:\n",
" city_data[name] = testing_data[ testing_data.Commune_ID.isin( \n",
" commune_info[ commune_info.GDENAME == name].GDENR.values) ].dropna()"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"city_coords = pd.DataFrame(data = [], columns = ['XCOORD', 'YCOORD'])\n",
"\n",
"for name, data in city_data.items():\n",
" city_coords = city_coords.append( pd.DataFrame(data = data[['XCOORD', 'YCOORD']].mean(), \n",
" index = ['XCOORD', 'YCOORD'], columns = [ name ]).T)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>XCOORD</th>\n",
" <th>YCOORD</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Luzern</th>\n",
" <td>665624.955697</td>\n",
" <td>211666.076867</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Zürich</th>\n",
" <td>682773.044850</td>\n",
" <td>248311.436652</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Basel</th>\n",
" <td>611299.379711</td>\n",
" <td>267349.846960</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Lugano</th>\n",
" <td>718420.536632</td>\n",
" <td>97348.639209</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Interlaken</th>\n",
" <td>632237.358008</td>\n",
" <td>170485.718042</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Davos</th>\n",
" <td>781587.456246</td>\n",
" <td>183569.663515</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" XCOORD YCOORD\n",
"Luzern 665624.955697 211666.076867\n",
"Zürich 682773.044850 248311.436652\n",
"Basel 611299.379711 267349.846960\n",
"Lugano 718420.536632 97348.639209\n",
"Interlaken 632237.358008 170485.718042\n",
"Davos 781587.456246 183569.663515"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"city_coords"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot locations of train and test data with cities"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Luzern', 'Zürich', 'Basel', 'Lugano', 'Interlaken', 'Davos'], dtype='object')"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"city_coords.index"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
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"/* Put everything inside the global mpl namespace */\n",
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" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
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"\n",
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"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
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"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
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"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
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" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
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"\n",
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" },\n",
" resize: function(event, ui) {\n",
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" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
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"\n",
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"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
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" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
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" });\n",
"\n",
" canvas_div.append(canvas);\n",
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"\n",
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" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
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"\n",
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" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
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" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
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"\n",
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" canvas_div.focus();\n",
" }\n",
"\n",
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"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
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" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
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" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
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" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
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" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
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" nav_element.append(status_bar);\n",
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"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
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" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
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" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"trn = training_data.sample(100000)\n",
"tst = testing_data.sample(1000000)\n",
"\n",
"DIST = 5000\n",
"XMAX = tst.XCOORD.max()\n",
"XMIN = trn.XCOORD.min()\n",
"\n",
"YMAX = tst.YCOORD.max()\n",
"YMIN = tst.YCOORD.min()\n",
"\n",
"plt.figure()\n",
"plt.scatter(trn.XCOORD, trn.YCOORD, s = 0.5, c = 'C0', label = 'training data')\n",
"plt.scatter(tst.XCOORD, tst.YCOORD, s = 0.5, c = 'C1', label = 'test data')\n",
"plt.scatter(city_coords.XCOORD, city_coords.YCOORD, s = 50, c = 'g', label = '')\n",
"\n",
"for city in city_coords.index:\n",
" plt.text(city_coords.loc[city].XCOORD + DIST, city_coords.loc[city].YCOORD, city, \n",
" fontsize = 12)\n",
"\n",
"plt.axis('equal')\n",
"plt.axis('off')\n",
"\n",
"plt.xlim((XMIN, XMAX))\n",
"plt.ylim((YMIN, YMAX))\n",
"\n",
"plt.legend(markerscale=5)\n",
"plt.tight_layout()\n",
"# plt.savefig('train_test_w_cities.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Part 3: Define ML models"
]
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 159,
"metadata": {},
"outputs": [],
"source": [
"# ML MODEL PARAMETERS\n",
"n_est = 500\n",
"n_samples_leaf = 3\n",
"RF_features = 3\n",
"ELM_nodes = 45\n",
"ELM_est = 25\n",
"MLP_layers = (100, 20,) # WORKS RESONABLY WELL\n",
- "SVM_paramC = 1\n",
- "SVM_gamma = 500\n",
+ "SVM_paramC = 5\n",
+ "SVM_gamma = 200\n",
"knn_neighbors = 17\n",
"\n",
"k_CV = 5\n",
"\n",
"# DEFINITION OF ESTIMATORS\n",
"def set_estimators():\n",
" estimator = {\n",
" 'LIN': LinearRegression( n_jobs = -1 ),\n",
" 'KNN': KNeighborsRegressor( n_neighbors = knn_neighbors, n_jobs = -1 ),\n",
" 'ELM' : ELM_Ensemble( n_estimators = ELM_est, n_nodes = ELM_nodes),\n",
" 'RF' : RandomForestRegressor( n_estimators = n_est, min_samples_leaf = n_samples_leaf, max_features = RF_features, n_jobs = -1 ),\n",
"# 'MLP': MLPRegressor( hidden_layer_sizes = MLP_layers ),\n",
" 'SVM': SVR( C = SVM_paramC, kernel = 'rbf', gamma = SVM_gamma ),\n",
"# 'RF_unc' : Uncertainty( RandomForestRegressor( n_estimators = n_est, min_samples_leaf = n_samples_leaf, n_jobs = -1 ) ),\n",
"# 'ELM_unc': Uncertainty( ELM_Ensemble( n_estimators = ELM_est, n_nodes = ELM_nodes) )\n",
" }\n",
" return estimator\n",
"\n",
"# 'XGB': XGBRegressor( n_estimators = n_est, max_depth = tree_depth, n_jobs = -1 ),"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Check RMSE score"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# choose model with which to perform the feature selection\n",
"model = 'RF'\n",
"training = training_data.sample(100000)\n",
"\n",
"MSE = pd.DataFrame(data = [], columns = ['mse', 'mse_norm', 'cv_time'])\n",
"N = len(feature_names)\n",
"\n",
"# get all all features\n",
"x, t, X, T = get_data( training, feature_names, label_name)\n",
"mse_df = pd.DataFrame(data = np.zeros((len(feature_names), 3)), \n",
" index = feature_names, columns = ['mse', 'mse_norm', 'cv_time'])\n",
"mse_df.loc['all', :] = get_mse( x, t, X, T, model )\n",
"MSE = MSE.append(mse_df.loc['all',:])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.sqrt(MSE)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# PERFORM MODEL TRAINING"
]
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 169,
"metadata": {},
"outputs": [],
"source": [
- "training = training_data.sample(10000)\n",
+ "training = training_data.sample(1000)\n",
"x, t, X, T = get_data( training, feature_names, label_name)"
]
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 170,
"metadata": {},
"outputs": [],
"source": [
- "testing = testing_data.sample(10000)\n",
+ "testing = testing_data.sample(100000)\n",
"x_tst, t_tst, X_tst, T_tst = get_data( testing, feature_names, label_name)"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Train with 1k samples"
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 174,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Testing LIN\n",
- "Training time: 0.055s\n",
- "LIN MSE: 25098.747022\n",
- "LIN RMSE: 158.425841\n",
- "LIN MAE: 116.309859\n",
- "LIN MAEP: 0.144816\n",
- "LIN MBE: -57.931698\n",
- "LIN MBEP: -0.090166\n",
- "LIN R2: 0.542737\n",
- "Prediction time: 0.013s\n",
+ "Training time: 0.002s\n",
+ "LIN MSE: 23783.918182\n",
+ "LIN RMSE: 154.220356\n",
+ "LIN MAE: 112.957959\n",
+ "LIN MAEP: 0.139287\n",
+ "LIN MBE: -53.545046\n",
+ "LIN MBEP: -0.085440\n",
+ "LIN R2: 0.566333\n",
+ "Prediction time: 0.149s\n",
"Testing KNN\n",
- "Training time: 0.012s\n",
- "KNN MSE: 14575.417645\n",
- "KNN RMSE: 120.728694\n",
- "KNN MAE: 83.222771\n",
- "KNN MAEP: 0.103548\n",
- "KNN MBE: -59.695535\n",
- "KNN MBEP: -0.082560\n",
- "KNN R2: 0.734457\n",
- "Prediction time: 0.134s\n",
+ "Training time: 0.001s\n",
+ "KNN MSE: 18036.501312\n",
+ "KNN RMSE: 134.300042\n",
+ "KNN MAE: 96.160955\n",
+ "KNN MAEP: 0.119556\n",
+ "KNN MBE: -74.634360\n",
+ "KNN MBEP: -0.101056\n",
+ "KNN R2: 0.671129\n",
+ "Prediction time: 4.237s\n",
"Testing ELM\n",
- "Training time: 0.323s\n",
- "ELM MSE: 14870.709539\n",
- "ELM RMSE: 121.945519\n",
- "ELM MAE: 83.957663\n",
- "ELM MAEP: 0.105279\n",
- "ELM MBE: -35.760251\n",
- "ELM MBEP: -0.050804\n",
- "ELM R2: 0.729077\n",
- "Prediction time: 0.151s\n",
+ "Training time: 2.165s\n",
+ "ELM MSE: 14398.281828\n",
+ "ELM RMSE: 119.992841\n",
+ "ELM MAE: 83.765236\n",
+ "ELM MAEP: 0.102963\n",
+ "ELM MBE: -37.410857\n",
+ "ELM MBEP: -0.049222\n",
+ "ELM R2: 0.737467\n",
+ "Prediction time: 4.461s\n",
"Testing RF\n",
- "Training time: 4.878s\n",
- "RF MSE: 13086.314055\n",
- "RF RMSE: 114.395428\n",
- "RF MAE: 77.190260\n",
- "RF MAEP: 0.095846\n",
- "RF MBE: -40.101319\n",
- "RF MBEP: -0.060314\n",
- "RF R2: 0.761586\n",
- "Prediction time: 0.314s\n",
+ "Training time: 1.537s\n",
+ "RF MSE: 13653.840310\n",
+ "RF RMSE: 116.849648\n",
+ "RF MAE: 80.052971\n",
+ "RF MAEP: 0.104255\n",
+ "RF MBE: -37.128476\n",
+ "RF MBEP: -0.069705\n",
+ "RF R2: 0.751041\n",
+ "Prediction time: 3.712s\n",
"Testing SVM\n",
- "Training time: 2.401s\n",
- "SVM MSE: 13477.339763\n",
- "SVM RMSE: 116.091945\n",
- "SVM MAE: 79.157336\n",
- "SVM MAEP: 0.096642\n",
- "SVM MBE: -46.957775\n",
- "SVM MBEP: -0.064411\n",
- "SVM R2: 0.754462\n",
- "Prediction time: 1.128s\n"
+ "Training time: 0.052s\n",
+ "SVM MSE: 12933.380941\n",
+ "SVM RMSE: 113.725023\n",
+ "SVM MAE: 78.979292\n",
+ "SVM MAEP: 0.094706\n",
+ "SVM MBE: -45.913064\n",
+ "SVM MBEP: -0.061326\n",
+ "SVM R2: 0.764178\n",
+ "Prediction time: 2.110s\n"
]
}
],
"source": [
+ "training = training_data.sample(1000)\n",
+ "x, t, X, T = get_data( training, feature_names, label_name)\n",
+ "\n",
"# names = ['RF']\n",
"# for name in names:\n",
"# est = set_estimators()[name]\n",
"for name, est in (set_estimators()).items():\n",
" print('Testing %s' %name)\n",
" tt = time.time()\n",
"\n",
- " est.fit(x, t)\n",
- " \n",
- " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " if name == 'RF':\n",
+ " est.fit(X, T)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time()\n",
+ " Y_tst = est.predict(X_tst)\n",
+ " \n",
+ " else:\n",
+ " est.fit(x, t)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time() \n",
+ " y_tst = est.predict(x_tst)\n",
+ " Y_tst = rescale(y_tst, T)\n",
+ "\n",
+ " pred_err = get_errors( shp(T_tst), shp(Y_tst), name )\n",
+ "\n",
+ " print('Prediction time: %.3fs' %(time.time()-tt))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Train with 10k samples"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 175,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Testing LIN\n",
+ "Training time: 0.054s\n",
+ "LIN MSE: 24480.316694\n",
+ "LIN RMSE: 156.461870\n",
+ "LIN MAE: 115.865296\n",
+ "LIN MAEP: 0.141440\n",
+ "LIN MBE: -58.208685\n",
+ "LIN MBEP: -0.087344\n",
+ "LIN R2: 0.553635\n",
+ "Prediction time: 0.097s\n",
+ "Testing KNN\n",
+ "Training time: 0.005s\n",
+ "KNN MSE: 14464.805151\n",
+ "KNN RMSE: 120.269718\n",
+ "KNN MAE: 83.825904\n",
+ "KNN MAEP: 0.101716\n",
+ "KNN MBE: -60.812275\n",
+ "KNN MBEP: -0.081115\n",
+ "KNN R2: 0.736254\n",
+ "Prediction time: 13.143s\n",
+ "Testing ELM\n",
+ "Training time: 11.351s\n",
+ "ELM MSE: 13715.809926\n",
+ "ELM RMSE: 117.114516\n",
+ "ELM MAE: 82.055596\n",
+ "ELM MAEP: 0.099404\n",
+ "ELM MBE: -41.600571\n",
+ "ELM MBEP: -0.053772\n",
+ "ELM R2: 0.749911\n",
+ "Prediction time: 4.345s\n",
+ "Testing RF\n",
+ "Training time: 11.359s\n",
+ "RF MSE: 10023.226545\n",
+ "RF RMSE: 100.116065\n",
+ "RF MAE: 64.214906\n",
+ "RF MAEP: 0.084092\n",
+ "RF MBE: -25.099019\n",
+ "RF MBEP: -0.051259\n",
+ "RF R2: 0.817240\n",
+ "Prediction time: 5.813s\n",
+ "Testing SVM\n",
+ "Training time: 3.860s\n",
+ "SVM MSE: 13406.938688\n",
+ "SVM RMSE: 115.788336\n",
+ "SVM MAE: 80.636103\n",
+ "SVM MAEP: 0.094644\n",
+ "SVM MBE: -48.514743\n",
+ "SVM MBEP: -0.061425\n",
+ "SVM R2: 0.755543\n",
+ "Prediction time: 20.292s\n"
+ ]
+ }
+ ],
+ "source": [
+ "training = training_data.sample(10000)\n",
+ "x, t, X, T = get_data( training, feature_names, label_name)\n",
+ "\n",
+ "# names = ['RF']\n",
+ "# for name in names:\n",
+ "# est = set_estimators()[name]\n",
+ "for name, est in (set_estimators()).items():\n",
+ " print('Testing %s' %name)\n",
" tt = time.time()\n",
- " \n",
- " y_tst = est.predict(x_tst)\n",
- " Y_tst = rescale(y_tst, T)\n",
- " \n",
+ "\n",
+ " if name == 'RF':\n",
+ " est.fit(X, T)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time()\n",
+ " Y_tst = est.predict(X_tst)\n",
+ " \n",
+ " else:\n",
+ " est.fit(x, t)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time() \n",
+ " y_tst = est.predict(x_tst)\n",
+ " Y_tst = rescale(y_tst, T)\n",
+ "\n",
" pred_err = get_errors( shp(T_tst), shp(Y_tst), name )\n",
"\n",
" print('Prediction time: %.3fs' %(time.time()-tt))"
]
},
{
"cell_type": "markdown",
"metadata": {},
+ "source": [
+ "### Train with 100k samples"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Testing LIN\n",
+ "Training time: 0.383s\n",
+ "LIN MSE: 24472.805872\n",
+ "LIN RMSE: 156.437866\n",
+ "LIN MAE: 115.616655\n",
+ "LIN MAEP: 0.141513\n",
+ "LIN MBE: -58.201560\n",
+ "LIN MBEP: -0.087648\n",
+ "LIN R2: 0.553772\n",
+ "Prediction time: 0.107s\n",
+ "Testing KNN\n",
+ "Training time: 0.176s\n",
+ "KNN MSE: 12979.745631\n",
+ "KNN RMSE: 113.928687\n",
+ "KNN MAE: 77.681210\n",
+ "KNN MAEP: 0.093053\n",
+ "KNN MBE: -48.567064\n",
+ "KNN MBEP: -0.065647\n",
+ "KNN R2: 0.763332\n",
+ "Prediction time: 27.063s\n",
+ "Testing ELM\n",
+ "Training time: 132.058s\n",
+ "ELM MSE: 13726.753560\n",
+ "ELM RMSE: 117.161229\n",
+ "ELM MAE: 82.091841\n",
+ "ELM MAEP: 0.099962\n",
+ "ELM MBE: -39.033537\n",
+ "ELM MBEP: -0.050839\n",
+ "ELM R2: 0.749712\n",
+ "Prediction time: 4.695s\n",
+ "Testing RF\n",
+ "Training time: 150.906s\n",
+ "RF MSE: 8865.486913\n",
+ "RF RMSE: 94.156715\n",
+ "RF MAE: 58.102606\n",
+ "RF MAEP: 0.076116\n",
+ "RF MBE: -15.740714\n",
+ "RF MBEP: -0.039334\n",
+ "RF R2: 0.838350\n",
+ "Prediction time: 10.920s\n",
+ "Testing SVM\n"
+ ]
+ }
+ ],
+ "source": [
+ " training = training_data.sample(100000)\n",
+ "x, t, X, T = get_data( training, feature_names, label_name)\n",
+ "\n",
+ "# names = ['RF']\n",
+ "# for name in names:\n",
+ "# est = set_estimators()[name]\n",
+ "for name, est in (set_estimators()).items():\n",
+ " print('Testing %s' %name)\n",
+ " tt = time.time()\n",
+ "\n",
+ " if name == 'RF':\n",
+ " est.fit(X, T)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time()\n",
+ " Y_tst = est.predict(X_tst)\n",
+ " \n",
+ " else:\n",
+ " est.fit(x, t)\n",
+ " print('Training time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time() \n",
+ " y_tst = est.predict(x_tst)\n",
+ " Y_tst = rescale(y_tst, T)\n",
+ "\n",
+ " pred_err = get_errors( shp(T_tst), shp(Y_tst), name )\n",
+ "\n",
+ " print('Prediction time: %.3fs' %(time.time()-tt))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
"source": [
"### RF and LIN are OK!\n",
"RF gives very good performance if X, T are used (no normalization)\n",
"LIN is in all cases not great, but functions as a reference model\n",
"\n",
"--> **for the other models, we should check different types of normalization, and with and without normalization**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### TUNING FOR KNN"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"training = training_data.sample(100000)\n",
"x, t, X, T = get_data( training, feature_names, label_name)"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"n_neighbors = 1\n",
"KNN (unscaled) MSE: 17936.489860\n",
"KNN (unscaled) RMSE: 133.927181\n",
"KNN (unscaled) MAE: 79.814240\n",
"KNN (unscaled) MAEP: 0.101270\n",
"KNN (unscaled) MBE: -7.217900\n",
"KNN (unscaled) MBEP: -0.038601\n",
"KNN (unscaled) R2: 0.712287\n",
"Crossvalidation time: 1.064s\n",
"KNN (scaled) MSE: 19677.763360\n",
"KNN (scaled) RMSE: 140.277451\n",
"KNN (scaled) MAE: 89.346540\n",
"KNN (scaled) MAEP: 0.106728\n",
"KNN (scaled) MBE: -3.728060\n",
"KNN (scaled) MBEP: -0.034882\n",
"KNN (scaled) R2: 0.684356\n",
"Crossvalidation time: 0.886s\n",
"\n",
"n_neighbors = 3\n",
"KNN (unscaled) MSE: 12194.562456\n",
"KNN (unscaled) RMSE: 110.428993\n",
"KNN (unscaled) MAE: 66.508287\n",
"KNN (unscaled) MAEP: 0.088468\n",
"KNN (unscaled) MBE: -9.034973\n",
"KNN (unscaled) MBEP: -0.040306\n",
"KNN (unscaled) R2: 0.804391\n",
"Crossvalidation time: 1.561s\n",
"KNN (scaled) MSE: 13216.161858\n",
"KNN (scaled) RMSE: 114.961567\n",
"KNN (scaled) MAE: 73.633820\n",
"KNN (scaled) MAEP: 0.092077\n",
"KNN (scaled) MBE: -4.446187\n",
"KNN (scaled) MBEP: -0.035396\n",
"KNN (scaled) R2: 0.788004\n",
"Crossvalidation time: 1.248s\n",
"\n",
"n_neighbors = 5\n",
"KNN (unscaled) MSE: 11099.403854\n",
"KNN (unscaled) RMSE: 105.353708\n",
"KNN (unscaled) MAE: 63.260656\n",
"KNN (unscaled) MAEP: 0.085720\n",
"KNN (unscaled) MBE: -10.136920\n",
"KNN (unscaled) MBEP: -0.041689\n",
"KNN (unscaled) R2: 0.821958\n",
"Crossvalidation time: 1.475s\n",
"KNN (scaled) MSE: 11955.351578\n",
"KNN (scaled) RMSE: 109.340530\n",
"KNN (scaled) MAE: 69.773316\n",
"KNN (scaled) MAEP: 0.088403\n",
"KNN (scaled) MBE: -5.201756\n",
"KNN (scaled) MBEP: -0.035990\n",
"KNN (scaled) R2: 0.808228\n",
"Crossvalidation time: 1.315s\n",
"\n",
"n_neighbors = 7\n",
"KNN (unscaled) MSE: 10706.984887\n",
"KNN (unscaled) RMSE: 103.474562\n",
"KNN (unscaled) MAE: 61.927021\n",
"KNN (unscaled) MAEP: 0.084790\n",
"KNN (unscaled) MBE: -10.867441\n",
"KNN (unscaled) MBEP: -0.042730\n",
"KNN (unscaled) R2: 0.828253\n",
"Crossvalidation time: 1.455s\n",
"KNN (scaled) MSE: 11392.805628\n",
"KNN (scaled) RMSE: 106.737086\n",
"KNN (scaled) MAE: 67.816767\n",
"KNN (scaled) MAEP: 0.086936\n",
"KNN (scaled) MBE: -5.736339\n",
"KNN (scaled) MBEP: -0.036814\n",
"KNN (scaled) R2: 0.817252\n",
"Crossvalidation time: 1.308s\n",
"\n",
"n_neighbors = 9\n",
"KNN (unscaled) MSE: 10543.600396\n",
"KNN (unscaled) RMSE: 102.682035\n",
"KNN (unscaled) MAE: 61.310733\n",
"KNN (unscaled) MAEP: 0.084391\n",
"KNN (unscaled) MBE: -11.532802\n",
"KNN (unscaled) MBEP: -0.043543\n",
"KNN (unscaled) R2: 0.830874\n",
"Crossvalidation time: 1.907s\n",
"KNN (scaled) MSE: 11132.352721\n",
"KNN (scaled) RMSE: 105.509965\n",
"KNN (scaled) MAE: 66.778321\n",
"KNN (scaled) MAEP: 0.086262\n",
"KNN (scaled) MBE: -6.243303\n",
"KNN (scaled) MBEP: -0.037596\n",
"KNN (scaled) R2: 0.821430\n",
"Crossvalidation time: 1.521s\n",
"\n",
"n_neighbors = 11\n",
"KNN (unscaled) MSE: 10452.999561\n",
"KNN (unscaled) RMSE: 102.239912\n",
"KNN (unscaled) MAE: 60.969124\n",
"KNN (unscaled) MAEP: 0.084270\n",
"KNN (unscaled) MBE: -12.089491\n",
"KNN (unscaled) MBEP: -0.044278\n",
"KNN (unscaled) R2: 0.832327\n",
"Crossvalidation time: 1.902s\n",
"KNN (scaled) MSE: 10975.228516\n",
"KNN (scaled) RMSE: 104.762725\n",
"KNN (scaled) MAE: 66.118878\n",
"KNN (scaled) MAEP: 0.085953\n",
"KNN (scaled) MBE: -6.554885\n",
"KNN (scaled) MBEP: -0.038208\n",
"KNN (scaled) R2: 0.823950\n",
"Crossvalidation time: 1.777s\n",
"\n",
"n_neighbors = 13\n",
"KNN (unscaled) MSE: 10416.797665\n",
"KNN (unscaled) RMSE: 102.062714\n",
"KNN (unscaled) MAE: 60.869478\n",
"KNN (unscaled) MAEP: 0.084387\n",
"KNN (unscaled) MBE: -12.464251\n",
"KNN (unscaled) MBEP: -0.044863\n",
"KNN (unscaled) R2: 0.832908\n",
"Crossvalidation time: 1.873s\n",
"KNN (scaled) MSE: 10864.128870\n",
"KNN (scaled) RMSE: 104.231132\n",
"KNN (scaled) MAE: 65.653434\n",
"KNN (scaled) MAEP: 0.085656\n",
"KNN (scaled) MBE: -6.987180\n",
"KNN (scaled) MBEP: -0.038707\n",
"KNN (scaled) R2: 0.825732\n",
"Crossvalidation time: 1.541s\n",
"\n",
"n_neighbors = 15\n",
"KNN (unscaled) MSE: 10407.979269\n",
"KNN (unscaled) RMSE: 102.019504\n",
"KNN (unscaled) MAE: 60.828119\n",
"KNN (unscaled) MAEP: 0.084519\n",
"KNN (unscaled) MBE: -12.905059\n",
"KNN (unscaled) MBEP: -0.045440\n",
"KNN (unscaled) R2: 0.833049\n",
"Crossvalidation time: 2.093s\n",
"KNN (scaled) MSE: 10790.107915\n",
"KNN (scaled) RMSE: 103.875444\n",
"KNN (scaled) MAE: 65.374872\n",
"KNN (scaled) MAEP: 0.085386\n",
"KNN (scaled) MBE: -7.334755\n",
"KNN (scaled) MBEP: -0.039021\n",
"KNN (scaled) R2: 0.826920\n",
"Crossvalidation time: 2.058s\n",
"\n",
"n_neighbors = 17\n",
"KNN (unscaled) MSE: 10404.359819\n",
"KNN (unscaled) RMSE: 102.001764\n",
"KNN (unscaled) MAE: 60.840614\n",
"KNN (unscaled) MAEP: 0.084702\n",
"KNN (unscaled) MBE: -13.303973\n",
"KNN (unscaled) MBEP: -0.045989\n",
"KNN (unscaled) R2: 0.833107\n",
"Crossvalidation time: 2.429s\n",
"KNN (scaled) MSE: 10750.128628\n",
"KNN (scaled) RMSE: 103.682827\n",
"KNN (scaled) MAE: 65.155901\n",
"KNN (scaled) MAEP: 0.085283\n",
"KNN (scaled) MBE: -7.616437\n",
"KNN (scaled) MBEP: -0.039390\n",
"KNN (scaled) R2: 0.827561\n",
"Crossvalidation time: 2.059s\n",
"\n",
"n_neighbors = 19\n",
"KNN (unscaled) MSE: 10411.482554\n",
"KNN (unscaled) RMSE: 102.036673\n",
"KNN (unscaled) MAE: 60.892743\n",
"KNN (unscaled) MAEP: 0.084887\n",
"KNN (unscaled) MBE: -13.650136\n",
"KNN (unscaled) MBEP: -0.046457\n",
"KNN (unscaled) R2: 0.832993\n",
"Crossvalidation time: 2.417s\n",
"KNN (scaled) MSE: 10714.865824\n",
"KNN (scaled) RMSE: 103.512636\n",
"KNN (scaled) MAE: 65.020369\n",
"KNN (scaled) MAEP: 0.085191\n",
"KNN (scaled) MBE: -7.860828\n",
"KNN (scaled) MBEP: -0.039656\n",
"KNN (scaled) R2: 0.828127\n",
"Crossvalidation time: 1.982s\n",
"\n",
"n_neighbors = 21\n",
"KNN (unscaled) MSE: 10433.962500\n",
"KNN (unscaled) RMSE: 102.146769\n",
"KNN (unscaled) MAE: 61.001188\n",
"KNN (unscaled) MAEP: 0.085100\n",
"KNN (unscaled) MBE: -13.958888\n",
"KNN (unscaled) MBEP: -0.046864\n",
"KNN (unscaled) R2: 0.832632\n",
"Crossvalidation time: 2.334s\n",
"KNN (scaled) MSE: 10702.347523\n",
"KNN (scaled) RMSE: 103.452151\n",
"KNN (scaled) MAE: 64.922793\n",
"KNN (scaled) MAEP: 0.085117\n",
"KNN (scaled) MBE: -8.073680\n",
"KNN (scaled) MBEP: -0.039885\n",
"KNN (scaled) R2: 0.828327\n",
"Crossvalidation time: 2.069s\n",
"\n",
"n_neighbors = 23\n",
"KNN (unscaled) MSE: 10456.314662\n",
"KNN (unscaled) RMSE: 102.256123\n",
"KNN (unscaled) MAE: 61.089005\n",
"KNN (unscaled) MAEP: 0.085257\n",
"KNN (unscaled) MBE: -14.256716\n",
"KNN (unscaled) MBEP: -0.047223\n",
"KNN (unscaled) R2: 0.832274\n",
"Crossvalidation time: 2.111s\n",
"KNN (scaled) MSE: 10689.113724\n",
"KNN (scaled) RMSE: 103.388170\n",
"KNN (scaled) MAE: 64.859814\n",
"KNN (scaled) MAEP: 0.085216\n",
"KNN (scaled) MBE: -8.331738\n",
"KNN (scaled) MBEP: -0.040285\n",
"KNN (scaled) R2: 0.828540\n",
"Crossvalidation time: 1.861s\n",
"\n",
"n_neighbors = 25\n",
"KNN (unscaled) MSE: 10490.688473\n",
"KNN (unscaled) RMSE: 102.424062\n",
"KNN (unscaled) MAE: 61.211516\n",
"KNN (unscaled) MAEP: 0.085473\n",
"KNN (unscaled) MBE: -14.551115\n",
"KNN (unscaled) MBEP: -0.047607\n",
"KNN (unscaled) R2: 0.831723\n",
"Crossvalidation time: 2.406s\n",
"KNN (scaled) MSE: 10680.215304\n",
"KNN (scaled) RMSE: 103.345127\n",
"KNN (scaled) MAE: 64.826315\n",
"KNN (scaled) MAEP: 0.085263\n",
"KNN (scaled) MBE: -8.536103\n",
"KNN (scaled) MBEP: -0.040559\n",
"KNN (scaled) R2: 0.828682\n",
"Crossvalidation time: 1.847s\n",
"\n",
"n_neighbors = 27\n",
"KNN (unscaled) MSE: 10519.643905\n",
"KNN (unscaled) RMSE: 102.565315\n",
"KNN (unscaled) MAE: 61.336524\n",
"KNN (unscaled) MAEP: 0.085675\n",
"KNN (unscaled) MBE: -14.801919\n",
"KNN (unscaled) MBEP: -0.047934\n",
"KNN (unscaled) R2: 0.831258\n",
"Crossvalidation time: 2.415s\n",
"KNN (scaled) MSE: 10680.828484\n",
"KNN (scaled) RMSE: 103.348094\n",
"KNN (scaled) MAE: 64.814751\n",
"KNN (scaled) MAEP: 0.085333\n",
"KNN (scaled) MBE: -8.750767\n",
"KNN (scaled) MBEP: -0.040840\n",
"KNN (scaled) R2: 0.828673\n",
"Crossvalidation time: 2.183s\n",
"\n",
"n_neighbors = 29\n",
"KNN (unscaled) MSE: 10551.474020\n",
"KNN (unscaled) RMSE: 102.720368\n",
"KNN (unscaled) MAE: 61.473164\n",
"KNN (unscaled) MAEP: 0.085902\n",
"KNN (unscaled) MBE: -15.027471\n",
"KNN (unscaled) MBEP: -0.048254\n",
"KNN (unscaled) R2: 0.830748\n",
"Crossvalidation time: 2.451s\n",
"KNN (scaled) MSE: 10674.096961\n",
"KNN (scaled) RMSE: 103.315521\n",
"KNN (scaled) MAE: 64.801763\n",
"KNN (scaled) MAEP: 0.085344\n",
"KNN (scaled) MBE: -8.936027\n",
"KNN (scaled) MBEP: -0.041038\n",
"KNN (scaled) R2: 0.828781\n",
"Crossvalidation time: 2.173s\n",
"\n",
"n_neighbors = 31\n",
"KNN (unscaled) MSE: 10586.091853\n",
"KNN (unscaled) RMSE: 102.888735\n",
"KNN (unscaled) MAE: 61.617209\n",
"KNN (unscaled) MAEP: 0.086129\n",
"KNN (unscaled) MBE: -15.234382\n",
"KNN (unscaled) MBEP: -0.048546\n",
"KNN (unscaled) R2: 0.830192\n",
"Crossvalidation time: 2.425s\n",
"KNN (scaled) MSE: 10676.314566\n",
"KNN (scaled) RMSE: 103.326253\n",
"KNN (scaled) MAE: 64.810894\n",
"KNN (scaled) MAEP: 0.085346\n",
"KNN (scaled) MBE: -9.148932\n",
"KNN (scaled) MBEP: -0.041235\n",
"KNN (scaled) R2: 0.828745\n",
"Crossvalidation time: 2.157s\n",
"\n",
"n_neighbors = 33\n",
"KNN (unscaled) MSE: 10617.628360\n",
"KNN (unscaled) RMSE: 103.041877\n",
"KNN (unscaled) MAE: 61.770765\n",
"KNN (unscaled) MAEP: 0.086325\n",
"KNN (unscaled) MBE: -15.443332\n",
"KNN (unscaled) MBEP: -0.048802\n",
"KNN (unscaled) R2: 0.829686\n",
"Crossvalidation time: 2.740s\n",
"KNN (scaled) MSE: 10673.333494\n",
"KNN (scaled) RMSE: 103.311826\n",
"KNN (scaled) MAE: 64.812968\n",
"KNN (scaled) MAEP: 0.085358\n",
"KNN (scaled) MBE: -9.315893\n",
"KNN (scaled) MBEP: -0.041402\n",
"KNN (scaled) R2: 0.828793\n",
"Crossvalidation time: 2.177s\n",
"\n",
"n_neighbors = 35\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"KNN (unscaled) MSE: 10640.251149\n",
"KNN (unscaled) RMSE: 103.151593\n",
"KNN (unscaled) MAE: 61.863727\n",
"KNN (unscaled) MAEP: 0.086469\n",
"KNN (unscaled) MBE: -15.634464\n",
"KNN (unscaled) MBEP: -0.049046\n",
"KNN (unscaled) R2: 0.829323\n",
"Crossvalidation time: 2.791s\n",
"KNN (scaled) MSE: 10682.688526\n",
"KNN (scaled) RMSE: 103.357092\n",
"KNN (scaled) MAE: 64.838960\n",
"KNN (scaled) MAEP: 0.085460\n",
"KNN (scaled) MBE: -9.495607\n",
"KNN (scaled) MBEP: -0.041644\n",
"KNN (scaled) R2: 0.828643\n",
"Crossvalidation time: 3.275s\n",
"\n",
"n_neighbors = 37\n",
"KNN (unscaled) MSE: 10670.352017\n",
"KNN (unscaled) RMSE: 103.297396\n",
"KNN (unscaled) MAE: 61.992450\n",
"KNN (unscaled) MAEP: 0.086629\n",
"KNN (unscaled) MBE: -15.831509\n",
"KNN (unscaled) MBEP: -0.049273\n",
"KNN (unscaled) R2: 0.828841\n",
"Crossvalidation time: 3.495s\n",
"KNN (scaled) MSE: 10684.478958\n",
"KNN (scaled) RMSE: 103.365753\n",
"KNN (scaled) MAE: 64.850631\n",
"KNN (scaled) MAEP: 0.085538\n",
"KNN (scaled) MBE: -9.651181\n",
"KNN (scaled) MBEP: -0.041856\n",
"KNN (scaled) R2: 0.828614\n",
"Crossvalidation time: 3.192s\n",
"\n",
"n_neighbors = 39\n",
"KNN (unscaled) MSE: 10707.069588\n",
"KNN (unscaled) RMSE: 103.474971\n",
"KNN (unscaled) MAE: 62.144333\n",
"KNN (unscaled) MAEP: 0.086804\n",
"KNN (unscaled) MBE: -16.008472\n",
"KNN (unscaled) MBEP: -0.049477\n",
"KNN (unscaled) R2: 0.828252\n",
"Crossvalidation time: 3.382s\n",
"KNN (scaled) MSE: 10698.132130\n",
"KNN (scaled) RMSE: 103.431775\n",
"KNN (scaled) MAE: 64.876131\n",
"KNN (scaled) MAEP: 0.085602\n",
"KNN (scaled) MBE: -9.795402\n",
"KNN (scaled) MBEP: -0.042030\n",
"KNN (scaled) R2: 0.828395\n",
"Crossvalidation time: 2.953s\n",
"\n",
"n_neighbors = 41\n",
"KNN (unscaled) MSE: 10738.284487\n",
"KNN (unscaled) RMSE: 103.625694\n",
"KNN (unscaled) MAE: 62.267558\n",
"KNN (unscaled) MAEP: 0.086970\n",
"KNN (unscaled) MBE: -16.181061\n",
"KNN (unscaled) MBEP: -0.049694\n",
"KNN (unscaled) R2: 0.827751\n",
"Crossvalidation time: 3.657s\n",
"KNN (scaled) MSE: 10701.172923\n",
"KNN (scaled) RMSE: 103.446474\n",
"KNN (scaled) MAE: 64.889298\n",
"KNN (scaled) MAEP: 0.085593\n",
"KNN (scaled) MBE: -9.947980\n",
"KNN (scaled) MBEP: -0.042149\n",
"KNN (scaled) R2: 0.828346\n",
"Crossvalidation time: 2.614s\n",
"\n",
"n_neighbors = 43\n",
"KNN (unscaled) MSE: 10769.089157\n",
"KNN (unscaled) RMSE: 103.774222\n",
"KNN (unscaled) MAE: 62.383713\n",
"KNN (unscaled) MAEP: 0.087140\n",
"KNN (unscaled) MBE: -16.344613\n",
"KNN (unscaled) MBEP: -0.049912\n",
"KNN (unscaled) R2: 0.827257\n",
"Crossvalidation time: 3.098s\n",
"KNN (scaled) MSE: 10710.505596\n",
"KNN (scaled) RMSE: 103.491573\n",
"KNN (scaled) MAE: 64.906860\n",
"KNN (scaled) MAEP: 0.085667\n",
"KNN (scaled) MBE: -10.090464\n",
"KNN (scaled) MBEP: -0.042341\n",
"KNN (scaled) R2: 0.828197\n",
"Crossvalidation time: 3.004s\n",
"\n",
"n_neighbors = 45\n",
"KNN (unscaled) MSE: 10797.895615\n",
"KNN (unscaled) RMSE: 103.912923\n",
"KNN (unscaled) MAE: 62.504908\n",
"KNN (unscaled) MAEP: 0.087299\n",
"KNN (unscaled) MBE: -16.491526\n",
"KNN (unscaled) MBEP: -0.050103\n",
"KNN (unscaled) R2: 0.826795\n",
"Crossvalidation time: 3.261s\n",
"KNN (scaled) MSE: 10719.709235\n",
"KNN (scaled) RMSE: 103.536029\n",
"KNN (scaled) MAE: 64.941426\n",
"KNN (scaled) MAEP: 0.085751\n",
"KNN (scaled) MBE: -10.221365\n",
"KNN (scaled) MBEP: -0.042518\n",
"KNN (scaled) R2: 0.828049\n",
"Crossvalidation time: 3.044s\n",
"\n",
"n_neighbors = 47\n",
"KNN (unscaled) MSE: 10825.161872\n",
"KNN (unscaled) RMSE: 104.044038\n",
"KNN (unscaled) MAE: 62.623741\n",
"KNN (unscaled) MAEP: 0.087450\n",
"KNN (unscaled) MBE: -16.631150\n",
"KNN (unscaled) MBEP: -0.050279\n",
"KNN (unscaled) R2: 0.826357\n",
"Crossvalidation time: 4.019s\n",
"KNN (scaled) MSE: 10732.175078\n",
"KNN (scaled) RMSE: 103.596212\n",
"KNN (scaled) MAE: 64.975693\n",
"KNN (scaled) MAEP: 0.085834\n",
"KNN (scaled) MBE: -10.364926\n",
"KNN (scaled) MBEP: -0.042703\n",
"KNN (scaled) R2: 0.827849\n",
"Crossvalidation time: 3.649s\n",
"\n",
"n_neighbors = 49\n",
"KNN (unscaled) MSE: 10857.319148\n",
"KNN (unscaled) RMSE: 104.198460\n",
"KNN (unscaled) MAE: 62.749351\n",
"KNN (unscaled) MAEP: 0.087658\n",
"KNN (unscaled) MBE: -16.774707\n",
"KNN (unscaled) MBEP: -0.050514\n",
"KNN (unscaled) R2: 0.825842\n",
"Crossvalidation time: 4.230s\n",
"KNN (scaled) MSE: 10742.371567\n",
"KNN (scaled) RMSE: 103.645413\n",
"KNN (scaled) MAE: 65.008273\n",
"KNN (scaled) MAEP: 0.085902\n",
"KNN (scaled) MBE: -10.489409\n",
"KNN (scaled) MBEP: -0.042856\n",
"KNN (scaled) R2: 0.827685\n",
"Crossvalidation time: 3.441s\n"
]
}
],
"source": [
"name = 'KNN'\n",
"knn_tuning = pd.DataFrame(data = [], columns = ['unscaled', 'scaled'])\n",
"\n",
"for n_neighbors in range(1,51, 2):\n",
" print('\\nn_neighbors = %d' %n_neighbors)\n",
" tt = time.time()\n",
"\n",
" est = KNeighborsRegressor( n_neighbors = n_neighbors, n_jobs = -1 )\n",
" Y = cross_val_predict(est, X, T)\n",
" unscaled_err = get_errors( shp(T), shp(Y), 'KNN (unscaled)' )\n",
" \n",
" print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
" tt = time.time()\n",
" \n",
" est = KNeighborsRegressor( n_neighbors = n_neighbors, n_jobs = -1 )\n",
" Y = cross_val_predict(est, x, T)\n",
" scaled_err = get_errors( shp(T), shp(Y), 'KNN (scaled)' )\n",
" \n",
" print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
" \n",
" knn_tuning = knn_tuning.append( pd.DataFrame(data = [[unscaled_err.RMSE, scaled_err.RMSE]], \n",
" columns = ['unscaled', 'scaled'], index = [n_neighbors]) )"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unscaled</th>\n",
" <th>scaled</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>133.927181</td>\n",
" <td>140.277451</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>116.318220</td>\n",
" <td>121.763431</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>110.428993</td>\n",
" <td>114.961567</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>107.106472</td>\n",
" <td>111.392788</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>105.353708</td>\n",
" <td>109.340530</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>104.148116</td>\n",
" <td>107.898006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>103.474562</td>\n",
" <td>106.737086</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>103.000060</td>\n",
" <td>106.043608</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>102.682035</td>\n",
" <td>105.509965</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>102.407954</td>\n",
" <td>105.045268</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>102.239912</td>\n",
" <td>104.762725</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>102.148309</td>\n",
" <td>104.457737</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>102.062714</td>\n",
" <td>104.231132</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>101.991796</td>\n",
" <td>104.074468</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>102.019504</td>\n",
" <td>103.875444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>102.003360</td>\n",
" <td>103.749668</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>102.001764</td>\n",
" <td>103.682827</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>102.015503</td>\n",
" <td>103.582393</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>102.036673</td>\n",
" <td>103.512636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>102.082279</td>\n",
" <td>103.468825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>102.146769</td>\n",
" <td>103.452151</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>102.204693</td>\n",
" <td>103.388752</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>102.256123</td>\n",
" <td>103.388170</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>102.342830</td>\n",
" <td>103.339980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>102.424062</td>\n",
" <td>103.345127</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>102.477265</td>\n",
" <td>103.340534</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>102.565315</td>\n",
" <td>103.348094</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>102.628012</td>\n",
" <td>103.343503</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>102.720368</td>\n",
" <td>103.315521</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>102.808029</td>\n",
" <td>103.318041</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" unscaled scaled\n",
"1 133.927181 140.277451\n",
"2 116.318220 121.763431\n",
"3 110.428993 114.961567\n",
"4 107.106472 111.392788\n",
"5 105.353708 109.340530\n",
"6 104.148116 107.898006\n",
"7 103.474562 106.737086\n",
"8 103.000060 106.043608\n",
"9 102.682035 105.509965\n",
"10 102.407954 105.045268\n",
"11 102.239912 104.762725\n",
"12 102.148309 104.457737\n",
"13 102.062714 104.231132\n",
"14 101.991796 104.074468\n",
"15 102.019504 103.875444\n",
"16 102.003360 103.749668\n",
"17 102.001764 103.682827\n",
"18 102.015503 103.582393\n",
"19 102.036673 103.512636\n",
"20 102.082279 103.468825\n",
"21 102.146769 103.452151\n",
"22 102.204693 103.388752\n",
"23 102.256123 103.388170\n",
"24 102.342830 103.339980\n",
"25 102.424062 103.345127\n",
"26 102.477265 103.340534\n",
"27 102.565315 103.348094\n",
"28 102.628012 103.343503\n",
"29 102.720368 103.315521\n",
"30 102.808029 103.318041"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"knn_tuning"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [],
"source": [
"knn_tuning.to_csv('KNN_tuning.csv')"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"unscaled 17\n",
"scaled 33\n",
"dtype: int64"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"knn_tuning.idxmin()"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"data": {
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" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"knn_tuning.unscaled.plot(lw = 2, label = 'RMSE for KNN')\n",
"plt.xlabel('Number of neighbors')\n",
"plt.ylabel('RMSE (in $kWh/m^2$)')\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.tight_layout()\n",
"plt.savefig('KNN_tuning.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tuning ELM"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"training = training_data.sample(100000)\n",
"x, t, X, T = get_data( training, feature_names, label_name)"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"ELM nodes = 50\n",
"ELM (unscaled) MSE: 10900.260481\n",
"ELM (unscaled) RMSE: 104.404313\n",
"ELM (unscaled) MAE: 66.563815\n",
"ELM (unscaled) MAEP: 0.083317\n",
"ELM (unscaled) MBE: -0.009370\n",
"ELM (unscaled) MBEP: -0.028423\n",
"ELM (unscaled) R2: 0.826046\n",
"Crossvalidation time: 8.801s\n",
"ELM (scaled) MSE: 10893.756707\n",
"ELM (scaled) RMSE: 104.373161\n",
"ELM (scaled) MAE: 66.552260\n",
"ELM (scaled) MAEP: 0.083305\n",
"ELM (scaled) MBE: -0.028816\n",
"ELM (scaled) MBEP: -0.028458\n",
"ELM (scaled) R2: 0.826149\n",
"Crossvalidation time: 8.094s\n"
]
}
],
"source": [
"name = 'ELM'\n",
"ELM_est = 25\n",
"#elm_tuning = pd.DataFrame(data = [], columns = ['unscaled_target', 'scaled_target'])\n",
"\n",
"for ELM_nodes in [50]:\n",
" print('\\nELM nodes = %d' %ELM_nodes)\n",
" tt = time.time()\n",
"\n",
" est = ELM_Ensemble( n_estimators = ELM_est, n_nodes = ELM_nodes )\n",
" Y = cross_val_predict(est, x, T)\n",
" unscaled_err = get_errors( shp(T), shp(Y), 'ELM (unscaled)' )\n",
" \n",
" print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
" tt = time.time()\n",
" \n",
" est = ELM_Ensemble( n_estimators = ELM_est, n_nodes = ELM_nodes )\n",
" y = cross_val_predict(est, x, t)\n",
" Y = rescale(y, T)\n",
" scaled_err = get_errors( shp(T), shp(Y), 'ELM (scaled)' )\n",
" \n",
" print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
" \n",
" if (unscaled_err.RMSE > 200) & (ELM_nodes > 20): break\n",
" \n",
" #elm_tuning = elm_tuning.append( pd.DataFrame(data = [[unscaled_err.RMSE, scaled_err.RMSE]], \n",
" #columns = ['unscaled_target', 'scaled_target'], index = [ELM_nodes]) )"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
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" <th></th>\n",
" <th>unscaled_target</th>\n",
" <th>scaled_target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>252.056856</td>\n",
" <td>250.313907</td>\n",
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" <th>6</th>\n",
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" <td>163.030005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>143.353876</td>\n",
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" <td>121.154071</td>\n",
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" <tr>\n",
" <th>41</th>\n",
" <td>105.774135</td>\n",
" <td>106.085332</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>104.854574</td>\n",
" <td>104.940364</td>\n",
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" <tr>\n",
" <th>51</th>\n",
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" <th>56</th>\n",
" <td>103.623092</td>\n",
" <td>103.828793</td>\n",
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" <td>103.281091</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>104.027258</td>\n",
" <td>103.132682</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>103.298952</td>\n",
" <td>103.221512</td>\n",
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" <tr>\n",
" <th>76</th>\n",
" <td>103.216895</td>\n",
" <td>103.139736</td>\n",
" </tr>\n",
" <tr>\n",
" <th>81</th>\n",
" <td>103.096608</td>\n",
" <td>103.087989</td>\n",
" </tr>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>103.031711</td>\n",
" <td>103.017617</td>\n",
" </tr>\n",
" <tr>\n",
" <th>91</th>\n",
" <td>103.022977</td>\n",
" <td>102.760905</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>102.942882</td>\n",
" <td>102.889443</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" unscaled_target scaled_target\n",
"1 252.056856 250.313907\n",
"6 158.953529 163.030005\n",
"11 143.353876 143.447775\n",
"16 133.347560 133.440524\n",
"21 120.861807 121.154071\n",
"26 111.439309 113.364057\n",
"31 108.308805 108.561483\n",
"36 107.089450 107.018143\n",
"41 105.774135 106.085332\n",
"46 104.854574 104.940364\n",
"51 104.366426 104.161843\n",
"56 103.623092 103.828793\n",
"61 103.364507 103.281091\n",
"66 104.027258 103.132682\n",
"71 103.298952 103.221512\n",
"76 103.216895 103.139736\n",
"81 103.096608 103.087989\n",
"86 103.031711 103.017617\n",
"91 103.022977 102.760905\n",
"96 102.942882 102.889443"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"elm_tuning"
]
},
{
"cell_type": "code",
"execution_count": 129,
"metadata": {},
"outputs": [],
"source": [
"elm_tuning.to_csv('ELM_tuning_n25.csv')"
]
},
{
"cell_type": "code",
"execution_count": 121,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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hMdcIeJroi8Smu2iGaCEli99rdufcjSO37hxA6lTp/Z4H58/dXNZexFgLuXjTf2W9Arpjfj9lnQIPVtIp8qNrFwm5l2SaGIviBId4liyZAk2btwojv1ToiP7dAcUHbt33bLuSQDSHgn354KoLG3+pdvi478jSZ/R3g1PT/vQMsTFyAiM+SPmNvnqWaPQJn9UEKHIrjICjICKCIRG3kPzva8I1xaXmoTI0GR+uUkvXtASIX2ReHpmzK/KuTAjwAhYggCdTqc/3OiScTr34J5otZMOsGonAHv16iXubaJj9HSqzZXoaPtnn30W5+JOmg2kzbG06ZZOj/myBJzYDOD9kGSoOmKdcKFWoYz45oXylgQCV+ofAlrMGvkHUdCU1oJLngEMmnhkR2MQ4BlA+ZHAM4BumFKAkfijPX0k5mj/n3silUzLsu6JLvUcN26cuHmdxKLrEMipU6fEARFKdGkobZKlZ3qMTKW67wGkpYsiA5bj3sMoFMySCr/0qS0/CrhGvxHQYt+Y3ygFRwVacGnDPYAqsM37xlRgQY4PzKUcHN1r4T2AbmjQKS1adqVDHO53/6VNmzb2uH98CuIvAbuugaEneEaOHCluf6eTU3RPoC/XwJBgrDd6LY5cvIUUYaHY/2Fj3ssivx/4XaMWosFvlIKjAi24ZAEYHMHIXsYiwAJQfjCwAHTDlMScp0R3N5GI85TiC0DKQxdBk5iMfxE0HQQxktxnAEkAdvxmKzb8HTPzuPODBsiYylg9RmxxHjkIaCEa5EClfC1acMkCUPk4ZAfjIsACUH5EsACUj6nfNcYXgO/N24tZ206Kehf2rI5SOdP5bYMrkIuAFqJBLmTK1qYFlywAlY0/dswzAiwA5UcGC0D5mPpdY3wBOGHNYYxccUjUO/G5cmhaMmZvISd1ENBCNKgDt6WeaMFl5ANg75wYHEu1AULD/MI0WC+C9qvRXNhWBFgAyoebBaB8TP2uMb4AXLDrNN6YvVvU+8ETRfFyzfx+2+AK5CKghWiQC5mytTGX5qlhAWgeMy5hDgEWgObwMpKbBaARlGzOE18Abj92Bc9+uVl40blaXgxuWdxmj9icNwRYNHhDKHg+Zy7Nc8UC0DxmXMIcAiQAn3/+edy6dUsc1Ewo0Q0e9OIWPeJAT/QZTQcPHhR7/Xfv3o0iRYqI/3pL9LgDXQ9Hby1Tojt96Qo5I2W91W32c9fzgnRPMb0ZbSSxADSCks154gvAs9fvoOrw1cKLBkWzYnKnCjZ7xOa8IcCiwRtCwfO5FlzSU3D//BpDSoH6QGjMZfO+pmAVgPSFT1/e3t7J9RUXmeWMigv3hwXokCJd0E2CiN4npou6XalOnTrivWJ61vTdd9+N42qzZs3ElWaDBg0SooYSvXHcv39/UYZut6BXIsqXLy9uu3j88cdFnoQOUib2vrFRjEgA0qXFdDUaPa1KidpAYmfs2LGx1fgqANu2bSuueZsyZYp46CFjxoxeXWMB6BWimLgItpdAjDXLmlzxBWBkVDQKf7AMD6OiUTRbGix7vaY1hrlWnxHQQjT4jE5wFdSCSz4EIoLSqQJw7ty5+OWXX0Ci6Z9//gG9bJUyZUps3hyzkuQSTyTqUqRIgUOHYvaYUzpz5gzy588vRBY9bUoCkF6MKFq0qJgZGzBggLjjlu66Xbp0qbjirGLFirECkG7NaNKkSZxOTzNx/j4R6GkJWKYArFChAp544gmPr3IlNIL5KwDp7mG6Oo5e0vE38QygvwgqUj6+ACS3an6yGiev3EHq5Emxb3BjRTxlN1wIaCEaNKFbCy5ZABoSgHSlFz0O8Ouvv4oXn0jY0H2udM8rPZFFImnbtm1iJoy+zGnWqECBAti+fbuon2a++vTpg7Nnz4p/nz59Wvyb3oqn+mrUqCEeEqA3lCnR7NXbb7+NP//8U7wpXrx4cXE37Zo1a9ClS5c4PTCh68k8zRSSz717947zrBeJp2LFimHOnDliSbV69eqi/o8//hhbtmwR15mRuKP6aEmzbNmy4t3YPHli3pD2lDxdi5bYsEFPq/71119YtGiRyEYzeW+++SYWL14sxBglupOXMHvllVfiLAGTeP/222/jVH/06FHhI814kgB+5513sH//fjFLSHi53+/rXjD+zCXNfBI+8ZeSXTiQHeLMrAB0zU4uX75czKbu3btXPBubO3du0UbCnZa4SWzTzGyDBg1i3SR7JMgPHz6MH3/8EenTp8cHH3wgfkcpvgAkwdytWzcxY0vv1HvijZeAFfxS8yQA2329GVuOXBHe7h3cCGmS+3dqT8FmB7VLWoiGoGbIuPNacGmXACQ7CaqFUCAs+X+fJpo3BAhL4T1veMo41rwdHEhsBpAEHQk7mjkjYUJvpdL9rrQESV/klOhzei+VhMyePXuEYKAv8IsXL4pXn+gLmITiDz/8AHpblYQIPRtK+8Zo1mfYsGHYuXOnEAIkCGlZlYTOq6++KmbdSFxSnZkzZxYzbyQcSNhQSuiBgvgCkF6wat++PTZs2CB8ofZQcs2eUTvJ58mTJ4vf03LuJ598IoSfSwCScCWRQr8n30NDQz2yalYAkvDr2LGjWFKm9j/55JPYuHGjELtki3yn2cYDBw4Iv9z3AFJbmjZtihIlSuDDDz8U/hBO1E7CrHLlyhgxYoT4HeFJM22bNm3y6DfZIbFFAr9v375iCXjHjh2WCcBSpUph1KhRYqaVZkdpNpXEX7Vq1cRMKQnb0aNHi5lZwp0SCcAbN25g6NChaNSoEWiWl0Qk/bFAM7PuApCEPcUlzf6SwMySJYvHdrMANP69YFtOTwKw7497MHfnKeEDLQHTUjAndRDQQjSoA7elnmjBpV0CcHDahLkq1Ah47sf/Pv8oG/Dgtuf8eWoAXZb899kn+YHblx/NO/i6NAFIsyYkMGi2x7V3jmaTaFaOhBkte7rPYNFMHokXWlalL2naR0czTjSjRQKE9paRqCEx45pxIpFHAoD2INISJM0gkrisXfvRJz/N7AEk+7S0SwL4zp07AhOaASQfXcklAF988UUxE0mzlCRGn332WSFIqH0uAUhlJkyYIGYnSfyRrySynnvuOSFiXInaRQImvkAkgeuez5XffRa1XLlyQqyRAJs3b57AmGZQCT8SaJ4OgSS2BExCuX79+sIULVXTjCJhkdBSNIlz9/Z62ksoawaQ+G7VqlWi4xjF2WuvvYaePXvGCkD642HGjBni3yTcaX/nkCFDRHy5BCAJYPodtXXJkiXiD4WEEgtAS79KfKvckwD8dNVfGPfr36LCSS9UQMNiWX2rnEtZgoAWosES5NSrVAsuWQCKwEtsBvCzzz7Dp59+KgSge6KlNxJSL7zwgli6dM1gPfPMM0JwkACk2T0SLjR7RaKRlvRoH95XX331iAChmUESV/RlTzNfJHoaNmwoZqTatGkT+6a8GQFIy7oLFy7EvXv3xPIuLRmSMKCZrfgCkGY3aSaTBCItNdMsJM1OxRdEVI5moCjP1q1bRdv//vtvYYf8pUQCcOLEiXGWLun3tPxIS9qekmsW1dVmmvUiYUMHMkgM0iGd2bNnmxaAFy5cEIKSEp2MJYF5/Pjx2Bm1+L7YKQBJYOfIkSPWBZqBJdFGS9+0B5Nmm0nA0R8Y9EcDJZoBpBjq169fbLnSpUvj6aefxsCBA2MFYM6cOUE/tG0hIiIi0QGWBaB63z/wJADn7DiJt+fuFd4OblEMnavnU9BzfV3SQjRoQq8WXNolAIN4CZhEHv2QoHNPNGNHe+pI+LlmsEgQ0WwhzRrRshvto3v99dfFcun58+dFcRJ4v//+O77//vtHehIJFddMDYkVWuolgbVv3z6xf6tKlSqGrxjxJBRJWJKocM0ekQPus2ckQGnZkcQqzbzREqInAejuOM1ANW7cWIhM2mfmEoDz588XM2lGk2sWlZY1169fL8QqiTV3DAk7szOA7tfAxJ+58+Rb/PaSLzQTS8vTJPop0d7OSpUqiT8K/NkDGP+KGtpaQEu1JLwLFiwoZm/pDwriyHXCmexRPNGPK7n77JoBpD2B3333nYifevXqsQA0Goiq5PMkAH/75xI6TNoqXHylZj70f6KYKu6yHwC0EA2aMK0Fl3YJwADHjD97ABNbAiYhQMuglGgGq2TJkmKZkcQezVjRDBZ9gVMs0WwcpUmTJolDCfRFTfsDjaSqVauKpViajSRBRLODJAoTS54EIIlY2kNH4o7EVXwBSIIke/bsoBkl2otGyZsApDw0a/jbb7+J/XK+CkDXLCotKdOsJ81y0ewp+USilPa4kSD1JABJNNIyOwlyVzKydGtEANJSPdl12XdxSAJLtgCk+KHZXtrnSenmzZtiFo9mqM0KQPoDgmZ733vvPbEE7Gk7gav9PANopBfanMeTADxx+TZqjVwjPGlW8jF88Vx5m71ic4khoIVo0CQEtOCSnoLbOS2G0fKdtX0Kjr5gaVmQlnrdE53upX1/JO5o2dT9EAj923UIhMrQDBbNFNIBBpq9okQnZkmokXCj2R1KrkMgtPRHhxboC55O2tJ+N1rWo7j7+uuv0bJlSyHGaCmUDm/QQRGaAaPTwCQ+aJ8hlaXDKMmSJXukVya0VExLhTRbR8uMlOLvnyPhSsu0rkMi7gKQZtDoZCzNepIoCg8PF7N+NMtJotYlXGgJ2NM1MOSrq974DrtmUaksHaShvW+0bE3+Eg+0lEvJkwAkPMg3EtnEC+WnmTtvp3eNCEDig0500+wrcUDL3cQ18SJbAFLs0B8GhB3hQHhSjNH+TF8EoOtuRKqH7nOkPZ6eEgtABb/UPAnA+w+jUHjAMkRHA6VypsXCnp4JVbA5WrikhWjQgkmezfWF5mC+CDr+VSLU/k6dOokrPhK7BsaFEwmqFi1a4PPPPxezV5RomY5E4R9//CEEjSvRYQYSTDRbSPvpSAzSvkFa+qM9X7SZn5aTL1++LPb+kR8kvOiELIk3OnRBe7tIrJm5Bobs00wdXfVCM3x0QtbTAQp37t0FIO3Ho4Mlq1evFkKFRAotSZJ/NFtH/lFK6CJoT5dNu9ui2VTCmmZQqQ7XRdMkAl2i2pMApCtkyAcSjoSf+zUw/i4Bk390apjEN4k/momlGU86JCNbABKmJPaIG9qDSTFC7Xa/5NroErD7SyBjxowRWwdoSwGdMI6fWAD6MtpZXMaTACSTVYf/irPX7yJjynDsHBCz6ZaTGgiwAFSDBxleMJfmUQxWAWi+pVwiUAh4W84PlF/BbJcFoILsJSQAn5n4G3Ycvyo8PvBhE6QI93wXk4JNcrxLLBqcQ7EWXEZFAsd/iyEtTzUgxL+xhAWgc+Jf1ZawAJTPDAtA+Zj6XWNCAvD1H3bh591nRP2/9KmFgllS+22LK5CDgBaiQQ5UyteiBZd8CET5OGQH4yLAAlB+RLAAlI+p3zUmJABHrjiICWv+EfVP61IRdQp7vt3bbwe4AtMIaCEaTKMSnAW04JIFYHAGp8ZeswCUTz4LQPmY+l1jQgJw5tYTeH9+zBUAHz1ZAs9VTvhNRr+d4ApMIaCFaDCFSPBm1oJLFoDBG6Caes4CUD7xLADlY+p3jQkJwHV/XUSnKdtE/a/VKYB3mhTx2xZXIAcBLUSDHKiUr0ULLlkAKh+H7GBcBFgAyo8IFoDyMfW7xoQE4OELN9FgTMyN6y1LZ8dn7cv6bYsrkIOAFqJBDlTK16IFlxYJQHryy9vzU3YGAIsGO9G21hZzKR9fupuS7sHMly/fI08UJqRDfPEiSTS9G8PJEAIJAX/3QSSKDFgu6iifJz1+eu3Re30MGeBM0hHQQjRIR03NCrXgUrIApC9nuistNDRUvL9KFwUndCecnayTX/SqAl0S7Lqrzk77bEseAsylPCxJjt2/fx8XL15EZGQkChUq9Ej/YAEoD29TNSUGfIVhq3Dp5n08liY5trxf31S9nNk6BLQQDdbBp1TNWnApWQASgfSFcvbsWfHihSqJvujogmB6W1UFQaoKLsHoB3MpnzWaracLx8+GWksAACAASURBVOkPtviJBaB8vA3VmBjwrT7fiD2nriNJEuDQ0KYITxpzAzunwCKghWgILMS2WdeCy4f3ga0TYzCt/BqQ9NEvAF8Apy/phw8filkFFRJxSU+D1apVSzxzxil4EWAu5XJHs/VJkyZN8A8jFoBy8TZcW2LA9/j+dyzZd1bUta5fHeTJmNJwvZzROgS0EA3WwadUzcylUnT45Qxz6Rd8ShVmLu2lgwWgvXjHWksM+I+XHsDX64+IvDNfroxqBTMFyEs2644AD07OiQfmkrl0DgLOaQn3S3u5ZAFoL96GBOC3vx3DoIV/iryfPF0KbSrmCpCXbJYFoDNjQIsvGnoK7uzuGAKzlfH7KThVI0ELLlUFX7JfzKVkQL1UxwLQXrwNCcBfD5zHS9/uEHl71y+EPg0fD5CXbJYFoDNjQIsvGgsOgagYDVpwqSLwFvjEXFoAaiJVsgC0F29DAvDguX/RZOwGkffpcjkxuk3pAHnJZlkAOjMGtPiiYQHozOB1cKu06JcK8ccCMEBkJAb8jbsPUHLwSuFZ5XwZMLtb1QB5yWZZADozBrT4omEB6MzgdXCrtOiXCvHHAjBAZHgDvtTgFfj37kPkTJ8CG9+pFyAv2SwLQGfGgBZfNCwAnRm8Dm6VFv1SIf686RAzrvJLICbQ8gZ8s3EbsP/sv0gakgSHhjVFaEgSE7VzVisQ4MHJClQDU6cWXLIADExwsVWfEdCiX/qMjvyC3nSIGYssAE2g5Q34V6bvwKr950WNv71bD9nTpTBRO2e1AgEenKxANTB1asElC8DABBdb9RkBLfqlz+jIL+hNh5ixyALQBFregB+88E9M++2YqHFOt6qolC+Dido5qxUI8OBkBaqBqVMLLlkABia42KrPCGjRL31GR35BbzrEjEUWgCbQ8gb85A1HMGzJAVHjp21L48myOU3UzlmtQIAHJytQDUydWnBJT8FtGB0DcM23pD0FFxjGEraqBZeqgW6RP8ylRcAmUK03HWLGGxaAJtDyBvzyP87i1e9+FzX2bfQ4etYrZKJ2zmoFAjw4WYFqYOpkLgODuxVWmUsrUA1Mncylvbh70yFmvGEBaAItb8DvO3UdLT7fKGpsVzEX/u/pUiZq56xWIMCDkxWoBqZO5jIwuFthlbm0AtXA1Mlc2ou7Nx1ixhsWgCbQ8gb81Vv3UXboKlFjzUKZMOOlyiZq56xWIMCDkxWoBqZOLbiMigIuHYoBOFNhICQkMGBbbFULLi3GUJXqmUt7mfCmQ8x4wwLQBFregI+OjkbxQStw+34k8mdKidV965ionbNagQAPTlagGpg6teCSD4EEJrjYqs8IaNEvfUZHfkFvOsSMRRaAJtAyAnzDMevw94WbCE8agoMfNkEI3wVoAmH5WXlwko9poGrUgksWgIEKL7brIwJa9EsfsbGimBEdYtQuC0CjSAEwAnyXqduw5tBFUeu2/vWRJXVyExY4q2wEeHCSjWjg6tOCSxaAgQswtuwTAlr0S5+QsaaQER1i1HJQCMDhw4dj3rx5OHjwIFKkSIFq1aphxIgRKFy4sGjnlStXMGjQIKxcuRInT55EpkyZ0Lp1awwdOhRp06aNxeLEiRPo0aMHVq9eLerp0KEDRo0ahfDwcEN4GQH+gwX78N2WE6K++d2roWzu9Ibq5kzWIMCDkzW4BqJWLbhkARiI0GKbfiCgRb/0Ax/ZRY3oEKM2g0IANmnSBO3atUPFihXx8OFD9O/fH/v27cP+/fuRMmVK/PHHH0IAdu7cGcWKFcPx48fx6quvolSpUpg7d67AIjIyEmXKlEHmzJkxevRoXL58GZ06dcJTTz2F8ePHG8LLCPAT1/6DEcsPivo+71AWzUtlN1Q3Z7IGAR6crME1ELVqwSULwECEFtv0AwEt+qUf+MguakSHGLUZFAIwfmMuXryILFmyYN26dahVq5bHtv744494/vnncevWLSRNmhTLli1D8+bNxQxh9uwxouyHH34QovHChQtIkyaNV8yMAL9wzxn0nrVL1PVu0yJ4tXYBr/VyBusQ4MHJOmztrlkLLlkA2h1WbM9PBLTol35iJLO4ER1i1F5QCsDDhw+jUKFCYhawRIkSHts6efJkvPfeeyCxSGngwIH4+eefsWfPntj8V69eRYYMGcSScN26dR+p5969e6AfVyLgc+XKhUuXLiUoGHedvIY2X28TRZ6rlAuDWxQ1ygXnswABGpxWrVqFhg0bIiwszAILXKVdCGjB5f1bCBuZR0D6oN9xIDylXfDaakcLLm1FNHDGmEt7sScdQtvcrl+/bmjiKjHvgk4A0lUrrVq1Aom3DRs2eGwbLe+WK1cOHTt2xLBhw0Serl274tixY2KfoHtKliwZpk2bhvbt2z9S1+DBgzFkyJBHfj9z5kxERER4tH39PjBwZ1LxWbF0UehWNMre6GBrjAAjELQIJIl6iKJnfxT+H8j2LKJDYsYSTowAI8AIEAK3b98W5xe0FIB0iGPJkiXYuHEjcuZ89K1dUseNGjVC+vTpsXDhwthZHxKAtDdwxYoVcaKIDoBMnz5d7DGMn3yZAYyKikaJD3/Bg8hoFMqSEkt7VeeoDSAC/NdpAMGXbJq5lAxoAKtjLgMIvmTTzKVkQL1Up+0MYK9evbBgwQKsX78e+fLlewSmGzduoHHjxmJ2bvHixUie/L8rWHxZAo5vwOjae91Ra3H00i2kDA/FH0MaI0mSJPZGCFuLRYD3pzgnGJhL5tI5CDinJdwv7eXSqA4x4lVQLAHTsi+Jv/nz52Pt2rVi/58ncUbij5Z0ly5d+sgSresQyKlTp5AtWzZRfPbs2eIksMxDIFTv85O3YuPhS8LG7oENkS7C2DUzRgjjPOYQ4MHJHF4q59aCS3oK7vrJGBrS5uKn4FQOSPZNIKBFv1SIa+0EYPfu3UH77ugQh+vuPzE+pk0r7vOjmT/a5E9r4yQS6WoYV6JrX0JDQ2OvgcmaNStGjhwp7g6kE8B0X6DMa2DI7jtz92L2jphBfHGvGiiR47+7CBWKIy1c4cHJOTRrwSWfAnZOwGrSEi36pUJcaicAE1pCnTp1qhBxNCvo6RQvcXb06FHkzZtX0EcXQZOYjH8RNM0aGklGgR//698YveovUeWXz5dHkxKPGame81iAAA9OFoAaoCq14JIFYICii836ioAW/dJXcCwoZ1SHGDEdFEvARhpiRx6jwM/7/RT6zIm5bmZA82J4qcaj+xXt8Jdt8PKEk2JAiy8aFoBOClkt2qJFv1SISaM6xIjLLACNoPS/PEaB33rkMtp+vUWUerF6PgxsUcyEFc4qEwEenGSiGdi6tOCSBWBgg4ytm0ZAi35pGhXrChjVIUY8YAFoBCWTAvD0tTuo/n+rRalGxbLi6xcqmLDCWWUiwIOTTDQDW5cWXLIADGyQsXXTCGjRL02jYl0BFoDWYZtozUaBfxgZhcIDliMyKhrFs6fBkt41A+Qxm+XByTkxoAWXLACdE7CatESLfqkQl0Z1iBGXeQbQCEomZwApO80A0kxguogw7B7YyIQVzioTAR6cZKIZ2Lq04JIFYGCDjK2bRkCLfmkaFesKsAC0DlspM4BUSZuvNmPb0SuiProMOlUyftIpELTx4BQI1K2xqQWXD+8BK96PAbDxx0BSYzcUWIO4dbVqwaV18ClVM3NpLx0sAO3FO9aaGeD7zNmNeb+fFmVXvFELhR9LHSCv9TbLg5Nz+GcumUvnIOCclnC/tJdLMzrEm2e8BOwNIbfPzQA/ZuUhfLb6sCg9pXMF1CuS1YQlzioLAR6cZCEZ+HqYy8BzIMsD5lIWkoGvh7m0lwMzOsSbZywAvSHkowCcvf0E3vlpnyj9YavieKFqzGXUnOxFgAcne/G20poWXEZHA7cvx8AYkRFw6DviWnBpZWdQqG7m0l4yWADai3esNTPAbzp8Cc9N3irKdquVH+81Kxogr/U2y4OTc/jXgks+BOKcgNWkJVr0S4W4NKNDvLnNM4DeEPJxBvDYpVuoM2qtKP1EqWyY0KGcCUucVRYCPDjJQjLw9WjBJQvAwAcae2AKAS36pSlErM3MAtBafBOs3Qzw9x5GovAHy0VdZXKlw4Ie1QPktd5meXByDv9acMkC0DkBq0lLtOiXCnFpRod4c5tnAL0h5OMMIBWr/PEvOP/vPWRKlQw7PmhgwhJnlYUAD06ykAx8PVpwyQIw8IHGHphCQIt+aQoRazOzALQWXykzgFTJU19swu8nron6Dg5tguRhoQHyXF+zPDg5h3stuGQB6JyA1aQlWvRLhbhkARggMswC32vWLizac0Z4u/qt2sifOVWAPNfXLA9OzuFeCy5ZADonYDVpiRb9UiEuzeqQxFznJWATxJoF/v+WHcSX6/4RFqa/WAm1Hs9swhpnlYEAD04yUFSjDi24ZAGoRrCxF4YR0KJfGkbD+oxmdQgLQEmcmAX+uy3H8cGCP4T14U+VRPtKuSV5wtUYRYAHJ6NIqZ9PCy7pKbhFb8SQ0WIsPwWnflhq76EW/VIhls3qEBaAksgzC/yaQxfQZep2Yb1n3YLo27iwJE+4GqMI8OBkFCn18zGX6nNk1EPm0ihS6udjLu3lyKwOYQEoiR+zwP99/gYafrpeWG9dJjvGtisryROuxigCPDgZRUr9fMyl+hwZ9ZC5NIqU+vmYS3s5MqtDWABK4scs8LfvP0SxgSuE9Yp50+PHV6tJ8oSrMYoAD05GkVI/nxZc0lNwD27HkBEWwU/BqR+W2nuoRb9UiGWzOoQFoCTyfAG+3NBVuHLrPrKnTY7f3qsvyROuxigCPDgZRUr9fFpwyYdA1A9E9jAOAlr0S4U490WHJOQ+nwI2QawvwLcYvxH7Tl9HSBLg0LCmCAsNMWGRs/qLAA9O/iKoTnktuGQBqE7AsSeGENCiXxpCwp5MvugQFoASuPEF+Ne+24llf5wT1je8XRe5MkRI8ISrMIoAD05GkVI/nxZcsgBUPxDZQ54BDGAM+KJDWABKIMwX4Ict3o/JG48K67NeqYKqBTJK8ISrMIqAFqLBKBhBnk8LLlkABnmU6ue+Fv1SIVp90SEsACUQ6AvwUzcdxZBF+4X1Uc+WxjPlc0rwhKswigAPTkaRUj+fFlyyAFQ/ENlDngEMYAz4okNYAEogzBfgV+0/j1em7xDW32hQCG80eFyCJ1yFUQS0EA1GwQjyfFpwyQIwyKNUP/e16JcK0eqLDmEBKIFAX4Dff+ZfNPtsg7D+bPmcGPlsaQmecBVGEeDByShS6ufTgksWgOoHInvIM4ABjAFfdAgLQAmE+QL89TsPUHrISmG9WoGMmPlKFQmecBVGEdBCNBgFI8jzacHlg7vA/K4xTD35NRCWPMhZ8+y+Flw6krlHG8Vc2ku0LzqEBaAEjnwFvuSgFbhx7yFyZ4jA+rfrSvCEqzCKAA9ORpFSPx9zqT5HRj1kLo0ipX4+5tJejnzVIZ685HsATXDnK/BNxq7HwXM3EBaaBIeGNkUIXQrIyRYEeHCyBWZbjDCXtsBsixHm0haYbTHCXNoCc6wRX3UIC0A/efIV+Je/3Y5fDlwQ1re8Vx+PpXXmso6f8FpSnAcnS2ANSKXMZUBgt8Qoc2kJrAGplLm0F3ZfdQgLQD958hX4QT//gW83HxfWf3qtKsrnyeCnJ1zcKAI8OBlFSv18WnDJh0DUD0T2MA4CWvRLhTj3VYewAPSTRF+Bn7T+CD5aekBYH9euDFqVyeGnJ1zcKAI8OBlFSv18WnDJAlD9QGQPWQAGMAZ81SEsAP0kzVfgl+47i+7f/y6s92tcGD3qFvTTEy5uFAEtRINRMII8nxZcsgAM8ijVz30t+qVCtPqqQ1gA+kmir8DvOXkNrSZsEtY7VM6Nj58s6acnXNwoAjw4GUVK/XxacMkCUP1AZA95BjCAMeCrDmEB6CdpvgJ/+eY9lB/2i7Be6/HMmP5iJT894eJGEdBCNBgFI8jzacElC8Agj1L93NeiXypEq686hAWgnyT6Cnx0dDSKDlyOuw+iUCBzSvz6Vh0/PeHiRhHgwckoUurn04JLFoDqByJ7yDOAAYwBX3UIC0A/SfMH+Pqj1+Kfi7eQPCwEBz5sgiRJ+C5AP+kwVFwL0WAIieDPpAWXLACDP1A1a4EW/VIhTv3RIfGbwRdBmyDWH+A7TdmGdX9dFNZ2fNAAmVIlM2GZs/qKAA9OviKnXjktuKSn4OZ0jAG/zQx+Ck69MGSP4iGgRb9UiHV/dAgLQD+I9Af49+fvw8ytJ4T1n3tUR+lc6fzwhIsaRYAHJ6NIqZ+PuVSfI6MeMpdGkVI/H3NpL0f+6JCgFIDDhw/HvHnzcPDgQaRIkQLVqlXDiBEjULhw4dj23Lt3D3379sWsWbNw584d1K9fH1988QVy5swZm+fEiRPo0aMHVq9eLerp0KEDRo0ahfDwcEMM+gP8hDWHMXLFIWHni+fKoVnJbIZscib/EODByT/8VCrNXKrEhn++MJf+4adSaebSXjb80SFBKQCbNGmCdu3aoWLFinj48CH69++Pffv2Yf/+/UiZMqVo02uvvYZFixZh2rRpyJgxI9566y1cuXIFO3fuRGhoKCIjI1GmTBlkzpwZo0ePxuXLl9GpUyc89dRTGD9+vCEG/QH+592n8foPu4Wd/s2K4pVa+Q3Z5Ez+IcCDk3/4qVSauVSJDf98YS79w0+l0sylvWz4o0OCUgDGd/rixYvIkiUL1q1bh1q1auH69etC2M2YMQNt27YV2c+cOYNcuXJh6dKlaNy4MZYtW4bmzZvj5MmTyJ49u8jzww8/oHPnzrhw4QLSpEnjlUV/gN95/AqenrhZ2OhUNQ+GtCrh1R5n8B8BHpz8x1CVGrTgkg6BjPzfRfH9DgPhMX/gOi1pwaXTSEugPcylvUT7o0McIQAPHz6MQoUKiVnAEiVKiCVdWvKlGb/06dPHtrF06dJo3bo1hgwZgoEDB+Lnn3/Gnj17Yj+/evUqMmTIIMrXrVvXK4v+AH/u+l1UGf6rsNGgaBZM7lTRqz3O4D8CPDj5j6EqNWjBJZ8CViXc2A+DCGjRLw1iYUc2f3RI0AtAulOvVatWIPG2YcMG0Z6ZM2eiS5cuoH2A7qlRo0bIly8fvvrqK3Tt2hXHjh3DypUr4+RJliyZWDZu3779I9xRfe51EvA0q3jp0iVDM4buFUZFRaPEh7/gQWQ0imRNhUU9q9kRK9rboMFp1apVaNiwIcLCwrTHI5gB0ILL+7cQNjKPoOlBv+OOngHkfhnMvfE/37XolwpRRTokU6ZMYuXTyMplYq4H3TUwdIhjyZIl2LhxY+wBj4QEIH3pFyhQAF9++aUQgMePH8eKFSvi4EEHQKZPny72GMZPgwcPFrOH8RPZi4iIMB0SQ38PxaV7SZA8NBojKkWaLs8FGAFGwNkIhEbeQ/O9r4hGLi41CZGhfF2Usxnn1jEC5hC4ffu2OMCqnQDs1asXFixYgPXr14uZPVeyaglY5gwg+frC1B3YfOSKcHvn+3WRJgXPSJkLffO5+a9T85ipWkILLnkGUNXwY78SQECLfqkQ+9rNANKyL4m/+fPnY+3atWL/n3tyHQL57rvv0KZNG/HR2bNnxQxh/EMgp06dQrZsMVewzJ49W5wEtuMQCNnr9+Me/LjzlLC9tHdNFMvu/eCJQnEXlK7w/pSgpM2j01pwyXsAnROwmrREi36pEJfa7QHs3r272OdHhzjc7/5LmzatuM+PEl0Ds3jxYrGfjw520J2AdNVL/GtgsmbNipEjR4oDI3QCmA6J2HENDPk47pe/8ekvfwl/v+5YHo2KP6ZQWDnTFR6cnMOrFlyyAHROwGrSEi36pUJcaicAE3o3d+rUqULEUbp79y769esnhKL7RdB0aMOV6CJoEpPxL4KmgyBGkr/Az915Cn1/jDmFPKhFMXSp/t8ythH7nMc8Ajw4mcdM1RJacPngDvDdMzEUPD8XCIv5A9dpSQsunUZaAu1hLu0l2l8d4u5t0B0CsRfquNb8BX7zP5fRftIWUenLNfLhg+bFAtkcLWzz4OQcmplL5tI5CDinJdwv7eXSXx3CAtBHvvwF/uSV26j5yRphvWmJxzDx+fI+esLFjCLAg5NRpNTPx1yqz5FRD5lLo0ipn4+5tJcjf3UIC0Af+fIX+AeRUSj8wTJERQMlc6TFol41fPSEixlFgAcno0ipn4+5VJ8jox4yl0aRUj8fc2kvR/7qEBaAPvIlA/hqw3/Fmet3kSFlOH4f0NBHT7iYUQR4cDKKlPr5tOCSDoGMLRlDxhv7HH0RNN3Q0KxZM76gXf2ul6iHWvRLhTiSoUNczeE9gCaIlQH8s1/+hu3Hrgqr+z9sjIjwpCY84KxmEeDBySxi6ubXgks+BaxuALJnHhHQol8qxL0MHcIC0AdCZQD/5uzdmL/rtLC+6s1aKJQ1tQ+ecBGjCPDgZBQp9fNpwSULQPUDkT2Mg4AW/VIhzmXoEBaAPhAqA/hRKw7h8zWHhfWpXSqibuEsPnjCRYwiwIOTUaTUz6cFlywA1Q9E9pAFYABjQIYOsVwA0mB97tw50Lt1mTNnFpczB3uSAfysbSfw3rx9AophrUvg+SoxD79zsgYBLUSDNdApV6sWXLIAVC7u2KHEEdCiXyoUBDJ0iCUC8ObNm/j+++8xa9YsbNu2DfSWrivRs2yNGjVC165dUbFiRYXgNO6KDOA3/H0RHb/ZJoy+WrsA3m1axLgDnNM0Ajw4mYZM2QJacMkCUNn4Y8c8I6BFv1SIfBk6RLoA/PTTT/HRRx8hb968aNmyJSpVqoQcOXKIp9ro2bU//vgDGzZsEO/5VqlSRTy/Fv9NX4Uw9uiKDOCPXLyJeqPXifpblM6O8e3Lqt7soPaPB6egpi+O81pwyQLQOQGrSUu06JcKcSlDh0gXgM8++ywGDhyIkiX/d4VBAoDRrOA333yD8PBwvPzyywrB6t0VGcDffRCJIgOWC2PlcqfDvO7VvRvmHD4jwIOTz9ApV1ALLukpuKlNY7DvsoyfglMuCtmh+Aho0S8Vol2GDpEuABXCxzJXZAFf8aNfcPHGPWRNkwxb329gmb9cMcCDk3OigLlkLp2DgHNawv3SXi5l6RDymu8BNMGdLOBbT9iE3SevCcuHhjVBsqShJrzgrGYQ4MHJDFpq52Uu1ebHjHfMpRm01M7LXNrLjywdIk0A3rlzR+zzoz1/7unPP/9E8eLF7UXHQmuygO8x83cs2XtWeLq2bx3kzZTSQq/1rpoHJ+fwz1wyl85BwDkt4X5pL5eydIgUATh37ly8+eab4pqX6OhoTJo0CZUrVxaIlCtXDr///ru96FhoTRbww5cewFfrjwhPv3+5MqoXzGSh13pXzYOTc/jXgsv7t4EJMeMnemwFwiOcQ6BbS7Tg0pHMPdoo5tJeomXpECkCsEyZMli1apW462/Hjh3o1KkT+vfvjw4dOqBs2bLYtWuXvehYaE0W8DM2H8OAn/8Uno54uiTaVsxtodd6V82Dk3P414JLPgXsnIDVpCVa9EuFuJSlQ6QIQFripaVeV7p8+TKeeuop1K9fHwsWLOAZQA+Bs/rgebw4bYf4pHe9gujTqLBC4eUsV3hwcg6fWnDJAtA5AatJS7TolwpxqZQArFu3LsaNG4dSpUrFQnT//n0xE/jjjz/i4cOHCkHnnyuygD907gYaj10vnHmqXA6MaVPGP8e4dIII8ODknODQgksWgM4JWE1aokW/VIhLWTpEygzgqVOnkDRpUjz22GOPQLRp0yZUr+6ce+5kAX/z3kOUGLRC4FUpXwbM6VZVofBylis8ODmHTy24ZAHonIDVpCVa9EuFuJSlQ6QIQIVwsdwVmcCX+XAlrt1+gBzpUmDTu/Us911XAzw4OYd5LbhkAeicgNWkJVr0S4W4lKlDLLkH8Nq1a+K1j3PnziFfvnyggyKlS5dGypTBfd2JTOCf+GwD/jzzL0JDkuDQ0CZIGhqiUIg5xxUenJjLoEKABWBQ0cXO8mX7dseATB1iiQCsV68e9u3bh4oVK+LEiRP466+/EBUVhfz58wsxOGfOHLsxk2JPJvDdZuzAij/PC79oBpBmAjnJR4AFoHxMA1WjFlzSNTCT6sZA/MoavgYmUMHGdg0joEW/NIyG9Rll6hBLBCDN9K1btw4VKlQQaND7v3RSeM+ePeJn7Nix1qNkgQWZwH+4aD+mbDoqvJzdtQoq589ogcdcJQ9OzokB5pK5dA4CzmkJ90t7uZSpQywRgHQR9MSJE8VF0E5KMoH/ZuNRDF28X8Azpk1pPFUup5OgUqYtPDgpQ4XfjjCXfkOoTAXMpTJU+O0Ic+k3hKYqkKlDLBGAa9euxciRI/HTTz8hefLkphqncmaZwK/48xy6zdgpmvtWw8fRq34hlZsetL7x4BS01D3iOHPJXDoHAee0hPulvVzK1CGWCMDjx4+jY8eOOHnyJNq3by+ehqNXQXLnDu4XL2QC/8fp62g+fqOInLYVcmHEM//do2hvODnbGg9OzuFXCy55D6BzAlaTlmjRLxXiUqYOsUQA0t4/ehGELommQyC7d+/G1atXkS5dOnEaePXq1QrBadwVmcBfu30fZT5cJYzXKJgJ3738v/c/jbvDOQ0gwIOTAZCCJIsWXPIp4CCJRnbThYAW/VIhumXqEEsEYEREBLZs2RLndRASgvQuMInBQYMGKQSncVdkAh8dHS0ug751PxL5MqXEmr51jDvCOQ0jwIOTYaiUz6gFlywAlY9DdjAuAlr0S4VIl6lDLBGAtWvXxvDhw1GtWjWFYPPfFZnAkzeNP12PQ+dvIDw0BAeHNkFISBL/neQa4iDAg5NzAkILLlkAOidgNWmJFv1SIS5l6hBLBOD8+fPFKeDZs2cjffr0CkHnnysygSdPXpy2HasPXhBObXu/PrKkcc6BGf+QlleaByd5WAa6Ji24ZAEY6DBj+yYR0KJf20DFLwAAIABJREFUmsTEyuwydYglAjAkJOZViwwZMqBly5aoUqWKOARSqlQpJEuWzEpsLK1bJvDk6IAFf2DGluPC53ndq6FcbueIZUuJMFE5D04mwFI8qxZcsgBUPArZvfgIaNEvFaJdpg6xRADSKWDa60eXPrv+e+zYMYSGhqJIkSLYu3evQnAad0Um8GT1q3X/YPiyg8KB8e3LokXp7Mad4ZyGEODByRBMQZFJCy5ZAAZFLLKT/yGgRb9UiHCZOsQSAegJqxs3bggxSOKvR48eCsFp3BWZwJPVxXvPoOfMXcKBd5oUwWt1Chh3hnMaQoAHJ0MwBUUmLbika2Am/O9GgB5b+Sm4oIhMvZ3Uol8qRLFMHSJVAL7//vto3bo1KlWqpBBc8lyRCTx5tevEVTz5xW/Cweer5Maw1iXlOcs1CQR4cHJOIDCXzKVzEHBOS7hf2sulTB0iVQB26dIFS5YsEUu9LVq0QKtWrdCgQYOg3vfnTq1M4KneizfuoeJHvwgTdQtnxtQuzhTO9naPuNZ4cAok+nJtM5dy8QxkbcxlINGXa5u5lIunt9pk6hCpApAcp/vtNm7ciEWLFmHhwoU4ffo0GjZsKA6DNG/eHJkyZfLWPmU/lwm8C6siA5bj3sMoFMqSCqv61Fa27cHqGA9Owcrco34zl8ylcxBwTku4X9rLpUwdIl0AxofiwIEDQgz+/PPP2LFjh3gWjsQgPRGXI0cOe5Hz05pM4F2u1Bu1Fkcu3UJEeCj+HNIYSZLwXYB+0hSnOA9OMtEMbF1acPngDjC1aQzQXZYBYSkCC7pF1rXg0iLsVKuWubSXEZk6xHIB6A7NxYsXxawg/dSsWRN9+/a1Fzk/rckE3uVKx2+2YsPfl8Q/dw1oiPQpw/30kou7I8CDk3PiQQsu+RSwcwJWk5Zo0S8V4lKmDrFVACqEoU+uyATe5cB78/Zi1raT4p+LetZAyZxpffKNC3lGgAcn50SGFlyyAHROwGrSEi36pUJcytQhlgjA7du349133wXN+BUsWBBlypSJ/cmdO7dCUJpzRSbwLsufr/4bo1b+Jf755fPl0KRENnNOce5EEeDByTkBogWXLACdE7CatESLfqkQlzJ1iCUCkC57JqFHV8IcOXIEu3btEncAXr16VTwNd/nyZdNwrl+/HiNHjsTOnTtx9uxZ0HNzVL8r3bx5U4jOBQsWiPrz5s2L3r1747XXXovNc+/ePbHsPGvWLNy5cwf169fHF198gZw5cxryRybwLoPzd53Cm7P3iH9+8ERRvFwzvyFfOJMxBHhwMoZTMOTSgksWgMEQiuyjGwJa9EuFGJepQywRgClTphQXPhcoEPdiY9cLIXQ9jNm0bNkybNq0CeXKlcPTTz/9iAB85ZVXsGbNGkyePFmIv5UrV6J79+746aefxHU0lEgM0oGUadOmIWPGjHjrrbdw5coVISrp6hpvSSbwLlvbj13Bs19uFv/sUj0vBrUo7s0N/twEAjw4mQBL8axacMkCUPEoZPfiI6BFv1SIdpk6xBIB2KhRI9Cl0HXq1LEENjopG38GsESJEmjbti0GDBgQa7N8+fJo1qwZhg4diuvXryNz5syYMWOGyEfpzJkzyJUrF5YuXYrGjRt79VUm8C5jZ67dQbX/Wy3+2bBYVkx6oYJXPziDcQR4cDKOleo5teCSBaDqYcj+xUNAi36pEOsydYg0AUizbKVLlxY/JNA+//xz/Pjjj2KmTXbyJABfffVVMZNHS8DZs2fH2rVrxXUzNHNYo0YNrF69Wiz50owfLUO7EvlLS8lDhgzx6qZM4F3GIqOiUfiDZXgYFY1i2dJg6es1vfrBGYwjwIOTcaxUz6kFlyQAx/7vRaA39gHhKVWnxSf/tODSJ2SCrxBzaS9nMnWINAFIe+ton9+ePXti9/hlyJBBLL9WrVoVZcuWRcmSJREe7v81J54E4P3790HLwNOnT0fSpEkREhIiloM7duwo2Jk5cybopRLaB+ieaLYyX758+Oqrrx5hkfK65yfgacbw0qVLSJMmjTTW647ZgFNX7yBtiqTY8X49afVyRTFPwa1atUpcRh4WFsaQBDECzGUQk+dh1oj7pTP45H5pL4+kQ+hBDVrV9FeHSBOABAGJMBJ4p06dEmLQ/efo0aNinx0dEKH9gf4kTwJw1KhRmDRpEui/efLkAR0aee+998RSMT1Hl5AAJGFAexW//PLLR1waPHiwx5lBqisiIsKfJsQpO/7PEBz+N0T8bkTFh0ieVFrVXBEjwAgwAowAI8AIOASB27dvo0OHDuoJwGzZsqFnz57i8IX7MivhTqd06TQwib8ePXr4RUV8AUgnetOmTSvE3hNPPBFb98svvyzE6PLly31aArZrBvDteX9g/q4zwu/FPaqi8GOp/cKHC/+HAP916pxoYC6ZS+cg4JyWcL+0l0tlZwA//fRTjB8/HhcuXECnTp3w5ptvinsAZaf4AtC1Jk6HOZo2/d8zSgC6desGmnmkE8GuQyDfffcd2rRpI1yi62ToCphAHgIhPz5d9RfG/fq38OmbThVQv2hW2ZBpWx/vT3EO9VpwSU/BffdMDGnPz+Wn4JwTvo5tiRb9UiH2lNwD6MInKipKXL1CYnDbtm1o0aKFuHuvevXqfkFIM4iHDx8WddB+wjFjxqBu3bqgfYZ05yCdOKa9eXT4hJaA161bJ659oXyuuwDpv4sXLxbXwFA58ovuDAzkNTDUnjk7TuLtuTHL4kNaFkenann9wooLx50BJIFPp8F5D2BwR4YWXzR8Cji4g1RD77XolwrxqrQAdMdpy5YtGD16tDiZS/f3keCiO/zogIbZRKd6SfDFTzTTSILu3LlzYs8fzfbRSV8SgV27dhWzkDRjSOnu3bvo16+f2A/ofhE0HewwkmQC727vt8OX0GHyVvGrrrXy4/1mRY24w3kMIMCDkwGQgiSLFlyyAAySaGQ3XQho0S8VolumDpF6CCQhjOgC6HHjxmHKlCli5o1eBwnGJBN49/Yfv3wLtUeuFb96omQ2THiuXDDCo6TPPDgpSYtPTmnBJQtAn2KDCwUOAS36ZeDgfcSyTB0iVQD2799f7LXz9HPt2jXcuHED0dHRiIyMVAhO467IBN7d6v2HUSg8YBmio4HSudLh5x7+LZcbb5Hzc/Lg5ByOteCSBaBzAlaTlmjRLxXiUqYOkSoAaWk3efLk6Ny5M4oWLSpO5tI9NfTj+n/6b5YsWRSC07grMoGPb7XKx7/i3L93kSlVOHZ80NC4U5wzUQR4cHJOgGjBJQtA5wSsJi3Rol8qxKVMHSJVANJrG3To4pdffkG7du3Enj96os0pSSbw8TF5euJv2Hn8qvj1waFNkDzM+9vETsHVynbw4GQluvbWrQWXLADtDSq25jcCWvRLv1GSV4FMHSJVALqaeOjQISEE6cqVmjVrioMX9AxbsCeZwMfH4vUfduHn3TF3Af76Vm0UyJwq2OFSwn8enJSgQYoTWnBJAnDk/67O6neYn4KTEjlciZUIaNEvrQTQZN0ydYglAtDVnosXL2LChAnilQ26JJpmBGlmkF4ECcYkE/j47f9k+UF8sfYf8etvX6yE2o9nDkaIlPOZByflKPHZIebSZ+iUK8hcKkeJzw4xlz5D51NBmTrEUgHoat3Vq1fF/Xxjx45FqlSpQKeCgzHJBD5++7/fehz95/8hfv3xkyXRoXLuYIRIOZ95cFKOEp8dYi59hk65gsylcpT47BBz6TN0PhWUqUOkCsDWrVvHngAmJ+k0MP334cOH4vQvJbqTj08BP8r7ur8uotOUbeKDHnULoF/jIj4FBxeKiwAPTs6JCOaSuXQOAs5pCfdLe7lUVgDS6d906dKJHzrt6/5f9//PmDGjvYhJsiYT+PguHb5wEw3GrBO/blUmO8a1KyvJa72r4cHJOfxrweWDu8CcjjGktZkBhCV3DoFuLdGCS0cy92ijmEt7iZapQ6TOALpgOH/+PLJmdd57tjKBjx8yd+5HoujA5eLXFfKkx9zXqtkbVQ61xoOTc4jVgks+BeycgNWkJVr0S4W4lKlDLBGANWrUAD3dljRp0kdgo+VgT79XCN8EXZEJvCcjFYatwqWb95EtbXJsfi/4T02rwCkPTiqwIMcHLbhkASgnWLgW2xDQol/ahqZ3QzJ1iCUCsEWLFsiZMycmTpwYpzWXL18WbwGTOAzGJBN4T+1v9flG7Dl1HSFJ6C7ApghPav7N5GDE1UqfeXCyEl1769aCSxaA9gYVW/MbAS36pd8oyatApg6xRADSs2+VKlXC22+/jZdfflm0/MCBA2jevDmKFy+OhQsXykPDxppkAu/J7e7f78TSfefER+v71UXujBE2ts6Zpnhwcg6vWnDJAtA5AatJS7TolwpxKVOHWCIACat9+/ahdu3aWLZsGegaGLr/r2vXrhgxYoQ4CRyMSSbwntr/0ZL9mLThqPho5iuVUa1ApmCESSmfeXBSig6/nNGCSxaAfsUIF7YfAS36pf2wJmhRpg6RJgBbtWqFMmXKoGzZsuK/efPmxaxZs9CrVy/cvXtXXAjdqVMnhWA074pM4D1Z//a3Yxi08E/x0chnSuHZCrnMO8kl4iDAg5NzAkILLlkAOidgNWmJFv1SIS5l6hBpApBe+di9ezf27NkD2utH176ULl0ae/fuxTPPPIPu3bujWLFiCAsLUwhKc67IBN6T5V/2n8fL03eIj16vXwhvNnzcnIOc+xEEeHByTlBowSULQOcErCYt0aJfKsSlTB0iTQC643Pq1CkhBt1/jh49Kk7/FilSRIjEYEwygffU/gNn/0XTcRvER8+Uz4lRz5YORpiU8pkHJ6Xo8MsZ5tIv+JQqzFwqRYdfzjCXfsFnurBMHWKJAPTUops3b2LXrl1iRrBHjx6mG61CAZnAe2rPv3cfoNTgleKjqvkzYlbXKio0O6h94MEpqOmL4zxzyVw6BwHntIT7pb1cytQhtglAeyGyxppM4BPysNTgFfj37kPkypACG96uZ01DNKqVByfnkM1cMpfOQcA5LeF+aS+XMnUIC0AT3MkEPiGztARMS8FJQ5Lg0LCmCKVLATn5jAAPTj5Dp1xBLbikp+Dmd43B/smv+Sk45aKQHYqPgBb9UiHaZeoQFoAmiJUJfEJmX5m+A6v2nxcfb36vHrKlTWHCQ87Kg5NzY0CLLxo+BOLcAHZoy7TolwpxJ1OHsAA0QaxM4BMyO3jhn5j22zHx8dxXq6JC3gwmPOSsLACdGwNafNGwAHRuADu0ZVr0S4W4k6lDWACaIFYm8AmZnbzhCIYtOSA+Htu2DFqXzWHCQ87KAtC5MaDFFw0LQOcGsENbpkW/VIg7mTqEBaAJYmUCn5DZZfvO4rXvfxcf92tcGD3qFjThIWdlAejcGNDii4YFoHMD2KEt06JfKsSdTB1imQD89ddfQT8XLlxAVFRUHPimTJmiEJzGXZEJfEJW9526jhafbxQft6+UG8OfKmncQc75CAI8ODknKLTgkgWgcwJWk5Zo0S8V4lKmDrFEAA4ZMgQffvghKlSogGzZsj3y9u/8+fMVgtO4KzKBT8jqlVv3UW7oKvFxzUKZMOOlysYd5JwsAB0cA1p80bAAdHAEO7NpWvRLhaiTqUMsEYAk+j755BN07NhRIdj8d0Um8Al5Ex0djWIDV+DOg0jkz5wSq9+q47/jGtfAg5NzyNeCSxaAzglYTVqiRb9UiEuZOsQSAZgxY0Zs27YNBQoUUAg2/12RCXxi3jQcsw5/X7iJZElDcHBok0dmUP1viT418ODkHK614DI6GnhwO4a0sAggiTPvAdWCS+d0vURbwlzaS7RMHWKJAHznnXeQKlUqDBgwwF5kLLYmE/jEXO08dRvWHroosmzv3wCZUyezuGXOrZ4HJ+dwy1wyl85BwDkt4X5pL5cydYglAvD111/H9OnTUapUKfETFhYWB6ExY8bYi5gkazKBT8yl/vP34futJ0SWBT2qo0yudJJaoF81PDg5h3Pmkrl0DgLOaQn3S3u5lKlDLBGAdevWTRSRNWvW2IuYJGsygU/MpYlr/8GI5QdFlgkdyuGJUtkktUC/anhwcg7nWnD58B6w6I0Y0lqMBZI6c/ZfCy6d0/USbQlzaS/RMnWIJQLQXjjssyYT+MS8XrjnDHrP2iWyvN+sCLrWctZeSvsYA3hwshNta21pwSUfArE2iLh26Qho0S+lo+Z7hTJ1iDQB2KdPHwwdOhQpU6YE/X9CKUmSJBg9erTvrQ9gSZnAJ9aMncev4umJv4ksL1TNgw9blQhgq4PbNA9Owc2fu/dacMkC0DkBq0lLtOiXCnEpU4dIE4C07Ev3+6VLlw6JLQGTAFy9erVCcBp3RSbwiVm98O9dVPr4V5GlfpEs+KZzReNOcs44CPDg5JyA0IJLFoDOCVhNWqJFv1SIS5k6RJoAVAgfy1yRCXxiTkZFRaPIgOW4HxmFIo+lxvI3alnWJqdXzIOTcxjWgksWgM4JWE1aokW/VIhLmTqEBaAJYmUC781snZFrcOzybaRKlhT7BjfiuwC9AZbA5zw4+QicgsW04JIFoIKRxy4lhoAW/VKhEJCpQ6QJwBMnTiB37tyGYTp9+jRy5MhhOL8KGWUC7609z03egk2HL4tsewY2QtqIuFfpeCvPn8cgwIOTcyJBCy5ZADonYDVpiRb9UiEuZeoQaQIwa9asaNmyJV555RVUqlTJI1zXr1/HnDlzMG7cOHTr1g29evVSCFbvrsgE3pu1d+buxewdJ0W2Jb1roHj2tN6K8OceEODByTlhoQWXLACdE7CatESLfqkQlzJ1iDQBeOXKFXz88ceYMmWKuPi5QoUKyJ49O5InT46rV69i//79+PPPP8XvP/jgAzRt2lQhSI25IhN4bxY/+/VvjFn1l8j2VcfyaFz8MW9F+HMWgI6OAS2+aOgpuNsxM/+IyMhPwTk6op3ROC36pUJUydQh0gSgC5+7d+9i6dKl2LBhA44dO4Y7d+4gU6ZMKFu2LBo3bowSJYL3ShOZwHuLp592nsJbP+4R2QY2L4YXa+TzVoQ/ZwHo6BjgLxrn0MtcMpfOQcDelsjUIdIFoL1Q2GtNJvDePN965DLafr1FZHupRj4MaF7MWxH+nAWgo2OARYNz6GUumUvnIGBvS2TqkKARgOvXr8fIkSOxc+dOnD17Vtw52Lp16zjIHzhwAO+88w7WrVuHqKgoFC9eXOw5dB1OuXfvHvr27YtZs2aJmcn69evjiy++QM6cOQ0xKBN4bwZPXb2NGiNinsxrUvwxfNmxvLci/DkLQEfHgBaigZ6CW/F+DI+NP+an4Bwd0c5onBb9UiGqZOqQoBGAy5Ytw6ZNm1CuXDk8/fTTjwjAf/75Rxw+eemll9C+fXukTZsWJAgrVqyILFmyCPpee+01LFq0CNOmTUPGjBnx1ltvgfYukqgMDQ31SrFM4L0ZexgZhcIDliMyKholcqTB4l41vRXhz1kAOjoGtPii4UMgjo5hJzZOi36pEHEydUjQCEB3/Ok1kfgzgO3atROHT2bMmOGRKjqBnDlzZvF527ZtRZ4zZ84gV65cYs8i7U/0lmQC780WfV79/1bj9LU7SB8Rhl0DGxkpwnniIcCDk3NCQgsuWQA6J2A1aYkW/VIhLmXqEEcIQFrupRm/t99+Gxs3bsSuXbuQL18+vPfee7HLxPT8HC350oxf+vTpY+ksXbq0yDNkyJBHKKYlY/pxJQKeBOOlS5eQJk0ay0Oiwzfbsf3YVWFn9wf1kDJZUsttOs0ADU6rVq1Cw4YNxR8InIIXAS24vH8LYSPzCJIe9DsOhKcMXsIS8VwLLh3J3KONYi7tJZp0CB2spUktf3WIIwTguXPnkC1bNkRERGDYsGHiLeLly5fj/fffx5o1a1C7dm3MnDkTXbp0iSPoiLZGjRoJsfjVV189wuLgwYM9CkOqi2xZnb77OwTbL4UIM++Wfohs1pu0uklcPyPACCSCQGjkPTTf+4rIsbjUJESGJmO8GAFGgBGIReD27dvo0KGDegKwWbNm4oAFzcZR+uijj9CjRw+kS5dO/Pvy5cuoWbOmuBPQnxR/CZiWculVEdr7R+LMlehi6pQpUwqfEhKANDNUoEABfPnll4+4FOgZwLG/HsaEtUeEX5M6lkWdxzP7A5uWZfmvU+fQrgWXPAPonIDVpCVa9EuFuFR2BpAOUtAJXdehC5qe3L17N/Lnzy/gO3/+vLgcOjIy0i844wvA+/fvC6E3aNAgccm0K9GJYFoSpsMjviwBx3dS5tq7EQBmbz+Bd37aJ7L2rFsQfRsXNlKM87ghwPtTnBMOWnDJewCdE7CatESLfqkQlzJ1iNQl4JCQENByrEsApk6dGnv27LFcABI31apVEzN57odAnnzySaRIkULM/rkOgXz33Xdo06aNoJPEKl0Bo+ohkMMXbqDhp+tBjwMkDUmCua9VQ5lcMbOpnIwhwIOTMZyCIZcWXLIADIZQZB/5j+yAxYCWAvDmzZs4fPiwAJ1eFRkzZozY65chQwZxzx+dCqbTvRMmTIjdA/jGG29g7dq1qFGjhihH18AsXrxYXAND5ehOQFqWVvEaGFd0fbL8IL5Y+4/4Z+4MEeJd4NTJ+TCD0d6nhWgwCkaQ59OCy6go4HrMG+BImwsIidkD7LSkBZdOIy2B9jCX9hKtrACkJWCaAaTrVijRDODevXvFIQtK/iwBk5AjwRc/derUSQg6SvQO8fDhw3Hq1CkULlxYHOBo1apVbBF6pq5fv35iRtD9Img62WskyQTeiD3K8yAyCm2+2oxdJ66JIi1LZ8e4dmVAy+CcvCPAg5N3jIIlB3MZLEx595O59I5RsORgLu1lSqYOkb4E3LRpUyRLFnNyjS5drlevntifR4kOVdDpXH/3ANoL93/WZAJvpg0nr9xGs3EbcOPeQ1Hsk2dKoU0FY6LVjB0n5uXByTmsMpfMpXMQcE5LuF/ay6VMHSJVANI1K0bS1KlTjWRTLo9M4M02bvHeM+g5c5coliIsFIt61UDBLKnMVqNdfh6cnEO5Flw+vA+s/jCGtHoDgaThziHQrSVacOlI5h5tFHNpL9EydYhUAWgvDPZbkwm8L96/+9Ne/LA9Zn9Q0WxpML97NSQP8/6EnS+2nFKGByenMAlowSUfAnFOwGrSEi36pUJcytQhLABNECsTeBNmY7PeuR+JFp9vxOELN8XvOlfLi8Eti/tSlTZleHByDtVacMkC0DkBq0lLtOiXCnEpU4dIFYBbt24VT63RPkBXmj59urif79atW+LJtfHjx8fuEVQIU0OuyATekEEPmQ6c/RetJmzC/YdR4tPJL1RAg2JZfa3O8eV4cHIOxVpwyQLQOQGrSUu06JcKcSlTh0gVgCT86tSpA7qAmdK+fftQrlw5dO7cGUWLFsXIkSPRrVs30BNrwZhkAu9P+6dvPoaBP/8pqkgfEYZlr9fCY2mT+1OlY8vy4OQcarXgkgWgcwJWk5Zo0S8V4lKmDpEqAOk9Xjr5W6FCBQFX//79sW7dOvEaB6Uff/xRzAb6+xRcoLiQCbw/bYiOjka3GTuxcv95UU3lfBkw85UqCA3hq2Hi48qDkz+RplZZLbhkAahW0LE3XhHQol96RcG+DDJ1iFQBmDx5cvz9999w3atHFzA3adIk9nm2Y8eOoWTJkrhx44Z9aEm0JBN4f926dvs+mo7bgLPX74qq+jR8HL3rF/K3WseV58HJOZRqwSULQOcErCYt0aJfKsSlTB0iVQDmyZNHPMVWq1Yt0Pu86dKlEzOC9evXF/DRknDt2rXFPsFgTDKBl9H+bUevoN3XmxEVDdDk35xuVVEhbwYZVTumDh6cHEMlnwJ2DpV6cOkgvhJrCo+x9hItU4dIFYC0v49E3ogRI7BgwQJ8++23OHPmDMLDY+6y+v777zF27Fhs377dXsQkWZMJvCSXMPaXvzD2l79FdTnSpcDS3jWRNoKfinPhy4OTrEgLfD1acElPwV06FAN2psL8FFzgw4498IKAFv1SoSiQqUOkCsCLFy/iqaeewqZNm5AqVSohAJ988slY6GgmsEqVKvjoo48UgtO4KzKBN2418ZyRUdFoP2kLaDaQUpPij2Hi8+X4qbj/wcaDk6xIC3w9zGXgOZDlAXMpC8nA18Nc2suBTB0iVQC6YLh+/boQgPQ2sHuipV/6vWtG0F7Y/LcmE3j/vfmvhjPX7oj9gNfvPBC/HNa6BJ6vkkemiaCtiwenoKXuEceZS+bSOQg4pyXcL+3lUqYOsUQA2guHfdZkAi/b65V/nkPXGTtFtcmShmBhzxoo/Fhq2WaCrj4enIKOsgQd1oJLegpuw+gYDGq+xU/BOSd8HdsSLfqlQuzJ1CFSBeCLL75oCKYpU6YYyqdaJpnAW9G2gT//gembj4uqH8+aCj/3qIEU4Xo/FceDkxWRFpg6teCSTwEHJrjYqs8IaNEvfUZHfkGZOkSqAAwJCQGdBC5btizorrqE0vz58+WjYkONMoG3wt27DyLResImHDwXc81Oh8q58fGTJa0wFTR18uAUNFR5dVQLLlkAeo0DzqAWAlr0S4Ugl6lDpArA7t2744cffkDu3LlBs4HPP/88MmRwzrUkMoG3Kp4OX7iBFuM34c6DSGFi4nPl0LRkNqvMKV8vD07KU2TYQS24ZAFoOB44oxoIaNEv1YBaeCFTh0gVgOTcvXv3MG/ePNAy72+//YYnnngCL730Eho1ahT0J1NlAm9lPM3efgLv/LRPmEiTPCmWvl4TOdNHWGlS2bp5cFKWGtOOacElC0DTccEFAouAFv0ysBDHsS5Th0gXgO6eHj9+HNOmTcP06dPFxZ/0BBydAg7WJBN4KzGg5fees3Zhyd6zwkz5POkxu2sVJA0NsdKsknXz4KQkLT45pQWXLAB9ig0uFDgEtOiXgYP3EcsydYilAvDEiRNCANIPvQxy8OA5JpSxAAAgAElEQVRBFoA2BdK/dx+g2bgNOHX1jrDYs25B9G1c2Cbr6pjhwUkdLvz1RAsuWQD6GyZc3mYEtOiXNmOamDmlBaD7EvDGjRvRvHlzdOnSRbwJTIdEgjnJBN4OHH4/cRXPfrkZdFl0kiTA9y9XRrUCmewwrYwNHpyUocJvR7TgkgWg33HCFdiLgBb90l5IE7UmU4dInQF0PwRCoo8OgWTMmFEh6PxzRSbw/nlivPQXaw/jk+UxT0tlTZMMy16vhQwpY57m0yHx4OQclrXgMioSOLs7hrRsZYAQZ17jpAWXzul6ibaEubSXaJk6RKoApBk+OgFM18AkoSmnBBIdEgnGJBN4u9ofFRWNF6Zsw8bDl4TJ+kWyYHKnCkF/IMcofjw4GUVK/XzMpfocGfWQuTSKlPr5mEt7OZKpQ6QKwM6dOxsSFlOnTrUXMUnWZAIvySVD1Vz49654Ku7yrfsi/8DmxfBijXyGygZ7Jh6cgp3B//xnLplL5yDgnJZwv7SXS5k6RKoANALD6dOnkSNHDiNZlcsjE3i7G7fm0AV0mbpdmA0PDcG87tVQIkdau92w3R4PTrZDbplBLbikp+C2TozBsPJr/BScZdHEFctCQIt+KQssCfXI1CG2CcBz587h448/xqRJk3DnTszJ1GBLMoEPRNuHLd6PyRuPCtP5M6XEol41kDJZ0kC4YptNHpxsg9pyQ1pwyYdALI8jNiAXAS36pVzI/KpNpg6RKgCvXbuGHj16YOXKlQgLC8O7776Lnj17YvDgwRg1ahSKFy+OPn36oH379n4BEKjCMoEPRBvuP4zC0xN/w77T14X5Z8rnxKhnSwfCFdts8uBkG9SWG9KCSxaAlscRG5CLgBb9Ui5kftUmU4dIFYB0CnjRokVo27Ytli9fjgMHDqBx48a4e/cuBg0ahNq1a/vV8EAXlgl8oNpy7NItPPHZBty6H/NU3Lh2ZdCqTHAuyRvBkAcnIygFRx4tuGQBGBzByF7GIqBFv1SIb5k6RKoAzJMnD7755hs0aNAAR44cQcGCBdG7d2+MHTtWIfh8d0Um8L574X/J+btO4c3Ze0RFqZIlxZLeNZAnY0r/K1awBh6cFCTFR5e04JIFoI/RwcUChYAW/TJQ4HqwK1OHSBWAtOxLz79lz55duB0REYFt27ahRIkSCsHnuysygffdCzkl+8zZjXm/nxaVlcqZFnNfrYbwpMF9UbcnZHhwkhMvKtSiBZcsAFUINfbBBAJa9EsTeFidVaYOkSoAQ0NDQYc9MmfOLDBInTo19u7di3z5nHHliEzgrQ4Sb/XfvPcQzT/bgGOXb4usXWvlx/vNinorFnSf8+AUdJQl6LAWXLIAdE7AatISLfqlQlzK1CFSBSBdBN20aVMkS5ZMwEX7AevVq4eUKeMuL/JF0GpE075T1/HUxE14EBktHPr2xUqo/XiMeHdK4sHJKUwCWnDJAtA5AatJS7TolwpxqawApOffjCS+CNoISvbkmbzhCIYtOSCMZUoVjqWv10SW1MntMW6DFR6cbADZJhNacElPwR3/LQbRPNX4KTibYovN+I6AFv3Sd3ikl1RWAEpvqWIVygRelaZFR0fjxWnbsebQReFSzUKZ8G2XSggJSfgpP1V8N+IHD05GUAqOPMxlcPBkxEvm0ghKwZGHubSXJ5k6ROoSsL0w2G9NJvD2e5+wxcs374mn4i7cuCcyvdu0CF6tXUAlF332hQcnn6FTriBzqRwlPjvEXPoMnXIFmUt7KZGpQ1gAmuBOJvAmzNqS9bfDl/DcN1sRHQ0kDUmCH1+tirK509ti20ojPDhZia69dWvBZeQDYOe0GGDLdwZCw+wF2SZrWnBpE5aBNsNc2suATB3CAtAEdzKBN2HWtqwjVxzEhDX/CHs50qXA9y9XRt5MwX0/IA9OtoWP5Ya04JIPgVgeR2xALgJa9Eu5kPlVm0wdwgLQBBUygTdh1rasDyKj0Oarzdh14pqwmSFlOL7pVCGoZwJ5cLItfCw3pAWXLAAtjyM2IBcBLfqlXMj8qk2mDmEBaIIKmcCbMGtr1vP/3sUL32zDofM3hN3kYSH4rF1ZNCr+mK1+yDLGg5MsJANfjxZcsgAMfKCxB6YQ0KJfmkLE2swydQgLQBNcyQTehFnbs16/8wCvztiJzUcuC9tJkgBDWhbHC1Xz2u6LvwZ5cPIXQXXKa8ElC0B1Ao49MYSAFv3SEBL2ZJKpQ1gAmuBMJvAmzAYk6/2HUXh77h4s2H0m1n63WvnxTpMiQXVFDA9OAQkfS4xqwSULQEtihyu1DgEt+qV18JmuWaYOCRoBuH79eowcORI7d+7E2bNnMX/+fLRu3dojeN26dcPXX3+NTz/9FG+88UZsnqtXr6J3795YuHCh+F3Lli0xfvx4pEuXzhAJMoE3ZDDAmeiOwFErD8UeDCF3mpfKhlHPlkbysNAAe2fMPA9OxnAKhlxacMkCMBhCkX10Q0CLfqkQ4zJ1SNAIwGXLlmHTpk0oV64cnn766QQF4IIFCzB48GBcvHgR/fr1iyMA6Zm6U6dOCXFIqWvXrsibN694ss5Ikgm8EXuq5Jm59QQ+WLAPUTEvxqFSvgz4umN5pIsIV8XFBP3gwUl5igw7qAWXLAANxwNnVAMBLfqlGlALL2TqkKARgO74J0mSxKMAPH36NCpXrowVK1bgiSeeEOLPNQN44MABFCtWDFu2bBF5KNH/V61aFQcPHkThwoW9UiwTeK/GFMuw+uB59Ph+F+48iBSeFcySCtO6VETO9BGKeRrXHR6clKbHlHNacBn5EPjn1xhcCtQHQpOawihYMmvBZbCQ4aefzKWfAJosLlOHOEYARkVFoUGDBmjVqhVef/11MbPnLgCnTJmCPn364Nq1mCtOXImWf2mp2Mg7xjKBN8m5Etn3nromno27dPO+8Cdz6mSY2rkiSuRIq4R/npzgwUlZakw7xlyahkzZAszl/7d3HmBWFecb/7YX2F1YOkgTKSIiTRArJIAtKoqCoohIwKiRIDZQYyBR1PAPkIgRUCmGoIkFK2KJIgYEKUFROihSpeyysCzb9/98c/dc7jbunXvmnjP3zHueZ5+9ZWa+md87Z/bdmTPnaCuNdMWgpTQyWxlU+hDPGMCnn36aPv/8czH7xzOElQ3g5MmTad68ebR169YK8Nu1ayfM34QJE6qIUlBQQPxjHQy+efPmdPjwYUpPT7clYrRm3p2dR79+ZR3tPJwnmpCaGEd/G9KZLmvXQMsm8eD0ySefUP/+/SkhwZtPVdASfAQqBS0jANWlIqGlS+AjEBZaRgDqaYpkH1K/fn3Kycmx7UM8YQB5Ywgv+a5bt46aNm0q0FVnAOfPn09btmypgLZt27Y0cuRIGj9+fBXkfC3hpEmTqny+cOFCSk3Ve+kzkl3yRBHRi1vi6IfjMSJMLJXR4DNLqXej8osEIxkcZYOAhwnElBXTGVlfiRbuyexNZTHeXAL2sIRoGghElEBeXh4NHToUBtDaBTx9+nSxvBsbG+sHX1JSIt7zjN2PP/5I4SwBYwaw5n5cUFRCD775HS35/md/onv7nEm/+0UbMQOry4H/TnVRwn49jNCy8AQlTGkpYBU9tIsoMbofxViT6kZoab/LR0UJ0NJZmTADWGkTyJEjR8StYQKPyy+/nIYNGyaWd3mDh7UJZNWqVdSzZ0+RlF9fcMEF2AQSZv8tLS2jpxZvopf/+4O/hBu6NaNnbuhMifGnzHiYxSvJhutTlGDUohAjtMQuYC36GioROgEjzsvQcUQ8pZHXAObm5tL27dsF3K5du9LUqVOpb9++lJmZSS1atKgCvfISMCfg28Ds27ePZs2aJdLzbWBatmyJ28DY7LJz/vsD/emDjVRWvgJ88Vn16e+3daP0ZPevucPgZFNcjbIboSUMoEY9DlUJhYAR52UoIBxKY6QBXLp0qTB8lY/hw4eLzR2Vj+oMYFZWVpUbQc+YMQM3glbQcZd8t59+99p6KiguFaV1aJxG80b0pMYZyQpKD78IDE7hs9MtpxFawgDq1u1QnyAEjDgvNeoFRhpAHfirBK9De1TXYe2uLPr1/DWUnVckim6SkUxzR5xPHRq7t2Mag5Nqld0rzwgtYQDd62CIHBYBI87LsMhEJpNKHxKVu4AjgzV4qSrBB48WnSl2HsqlO+aupp+yfLeJSUuKp5nDutNFZ9V3pUEYnFzBHpGgRmgJAxiRvoNCI0fAiPMycvikS1bpQ2AAJfCrBC8RNuqSHs4toJHzVtM3e3JE3RPiYujZQZ3phm5nON4WDE6OI49YQCO0hAGMWP9BwZEhYMR5GRl0YZWq0ofAAEpIoBK8RNioTJpXWExjXv0ffbrpoL/+D13enu7p4+xtYjA4RWX3qbbSRmjJj4LbXP5s8g7X4FFw3um+nm2JEeelRuqp9CEwgBLCqgQvETZqk5aUltEf3v2OFqz8yd+GW3q2oD9ddw7FxzlzmxgMTlHbfapUHFpCS+8Q8E5LcF46q6VKHwIDKKGdSvASYaM6aVlZGc38Yic9u2Szvx192zegGUO7Ua2kyD/lAINTVHefCpWHltDSOwS80xKcl85qqdKHwABKaKcSvERYTyR9Z/1eeuj1b6mwxHebmHObZdDLd/SghmmRvU0MBidPdB/RCCO0xBKwdzqsIS0x4rzUSEuVPgQGUEJYleAlwnom6cqdR2j0K2voWH6xaNMZdVPEvQLPalg7Ym3E4BQxtI4XbISW2ATieL9CQHsEjDgv7SFSmlulD4EBlJBGJXiJsJ5KuvXn43THnK9pX06+aFdGSgK9eHsP6tk6MyLtxOAUEayuFGqEljCArvQtBA2fgBHnZfh4lOdU6UNgACXkUQleIqznkv58LJ9GzF1NG/cfE23j5wZPG9yFru7cRHlbMTgpR+pagUZoCQPoWv9C4PAIGHFehocmIrlU+hAYQAmJVIKXCOvJpLkFxXTPP9fRsq2H/O3743Xn0O29WyltLwYnpThdLcwILWEAXe1jCC5PwIjzUh5LxHKo9CEwgBIyqQQvEdazSYtKSumxRRvo32v2+Ns4fUgXGti1mbI2Y3BShtL1gozQEgbQ9X6GCsgRMOK8lEMS0dQqfQgMoIRUKsFLhPV0Ur5NzJSPttDfl+4Q7YyPjaEXh/egvu0bKmk3BiclGLUoxAgtYQC16GuoROgEjDgvQ8cR8ZQqfQgMoIRcKsFLhPV8UjaBj7/9Hf1zle+G0SkJcbRwVC/q2qKu7bZjcLKNUJsCjNASBlCb/oaKhEbAiPMyNBSOpFLpQ2AAJSRTCV4irBFJ+akh9726jhZvOCDaWyc1gd74TW86q2GarfZjcLKFT6vMRmhZUkT07b993DsPJopL0EoDVZUxQktVsDQvB1o6K5BKHwIDKKGdSvASYY1JWlBcInYHr9hxRLS5SUYyvXn3hdS0TkrYDDA4hY1Ou4zQUjtJwq4QtAwbnXYZoaWzkqj0ITCAEtqpBC8R1qikx/OL6JYXV9J3e323iOGbRL9+V2+qWysxLA4YnMLCpmUmaKmlLGFVClqGhU3LTNDSWVlU+hAYQAntVIKXCGtc0kPHC+immSvoxyN5ou1dmtcR1wSmJso/OxiDk3e6jxFa8qPgdvzHJ1qbXxLFyff5aFDcCC2jQQgFdYSWCiBKFKHSh8AAugReIqyRSXdn5dENL6wgNoN8XNauAb00vAclxMVK8cDgJIVL68RGaIlNIFr3QVSuKgEjzkuNhIcBdEkMleBdakJUhd247xgNmfUVHS/wPTt4YJemNHVwF4qNjQm5HRicQkalfUIjtIQB1L4fooIVCRhxXmokukofghlACWFVgpcIa3TSVTuP0LA5X1NhcangMPLi1vT41WdTTExoJhCDk3e6jxFawgB6p8Ma0hIjzkuNtFTpQ2AAJYRVCV4irPFJP/7+AP1mwVoqLfOheOSKDnR3nzYhccHgFBKmqEhkhJYwgFHRF1HJUwSMOC81ElylD4EBlBBWJXiJsEhKRP9a/RM98uYGP4s/D+pMg89vHpQNBqegiKImgRFawgBGTX9ERX0EjDgvNRJbpQ+BAZQQViV4ibBIWk7g+c+3i8fG8cGXAc4a1oP6d2x0Wj4YnLzTfYzQEgbQOx3WkJYYcV5qpKVKHwIDKCGsSvASYZG0nAA/Mu6P72+kuct/FJ8kxcfSP0b2op6tM2tkhMHJO93HCC1hAL3TYQ1piRHnpUZaqvQhMIASwqoELxEWSQMIlJaW0f3/Xk/vrN8nPk1Ljqd/39Wbzm6SXi0nDE7e6T5GaMmPgls7zyda9zvwKDjvdF/PtsSI81Ij9VT6EBhACWFVgpcIi6SVCPCO4F+/soaWbT0kvmmYliQeGdc8M7UKKwxO3uk+0BJaeoeAd1qC89JZLVX6EBhACe1UgpcIi6TVEMgrLKahL66i9buPim9b1UulN+6+kOrXTqqQGoOTd7oPtISW3iHgnZbgvHRWS5U+BAZQQjuV4CXCImkNBLJPFNKNM1fQjkMnRIpOzdLp1VEXUFpygj8HBifvdB8jtCwtIdq1widaywuJYuO8I2BAS4zQ0pPKVW0UtHRWaJU+BAZQQjuV4CXCIulpCOw9epJufGEF7c/JF6kubFOP5o44n5LifX84MTh5p/sYoSU2gXinwxrSEiPOS420VOlDYAAlhFUJXiIskgYhsO3n43TjzK8o52SRSHnVuY3puVu6UVxsDAygh3qPEX9oYAA91GPNaIoR56VGUqr0ITCAEsKqBC8RFklDILB2Vzbd+tJKyi/yPTLutgta0J+u60TFxcW0ePFiuuqqqygh4dTScAhFIolmBIz4QwMDqFmvQ3WCETDivAwGwcHvVfoQGEAJ4VSClwiLpCES+HzzQbE7uKT8mXFj+7Wley9rDQMYIj/dkxnxhwYGUPduiPpVImDEeamR6ip9CAyghLAqwUuERVIJAm+t20Pj/v2NP8fEa86muoc3YAZQgqGuSY34QwMDqGv3Q71qIGDEeamR+ip9CAyghLAqwUuERVJJAi99uZOe/GCTyBUTQzS8bQk9NuxKLAFLctQtuRF/aGAAdet2qE8QAkaclxr1ApU+BAZQQliV4CXCImkYBJ75cDPN/GKHyBkXU0Zzhvegyzo0DqMkZNGFgBF/aGAAdeluqEeIBIw4L0Nk4UQylT4EBlBCMZXgJcIiaRgE+LnBD7/xLb2+do/IXSsxjl4b3ZvOPSMjjNKQRQcCRvyhKS4kWvWCD3evu4niE3VAr7wORmipnJqeBUJLZ3VR6UNgACW0UwleIiyShkmguKSURr+yhj7b4ntkXL1aieJpIa3r1wqzRGRzkwD+0LhJX21saKmWp5ulQUtn6av0ITCAEtqpBC8RFkltEDh2Ip8GTv+Udh6PEaWcUTdFPDe4UXqyjVKR1Q0C+EPjBvXIxISWkeHqRqnQ0lnqKn0IDKCEdirBS4RFUhsEeHB6493FNHdXHdp6MFeU1KFxGv3rrt6UkYL7AtpA63hWI/7Q8KPg9q/3sW3SBY+Cc7yXIaAsASPOS1koEUyv0ofAAEoIpRK8RFgktUHAGpy6X/wLGvLiauJHx/HRs1UmvTKyJyUnePNZqzaQaZvViD802ASibf9DxaonYMR5qZH4Kn1I1BjAZcuW0ZQpU2jt2rW0f/9+WrRoEQ0cOFDIwh3w8ccfFzf83blzJ2VkZFC/fv3omWeeoaZNm/qly87OpjFjxtC7774rPrv22mvpueeeozp16oQkr0rwIQVEItsEAgen3UcLxCPjsk4UinL7nd2IZt7WjeLjYm3HQQGRJ2DEHxoYwMh3JERQSsCI81IpMXuFqfQhUWMAP/zwQ1q+fDl169aNBg0aVMEA5uTk0I033kijRo2i8847j9jojR07VjwGbM2aNX7aV155Je3Zs4dmz54tPhs9ejS1atWK3nvvvZAUUQk+pIBIZJtA5cHp2z1H6ZbZK+lEYYko+5K29WnG0G5YDrZNOvIFGPGHBgYw8h0JEZQSMOK8VErMXmEqfUjUGMBAZDExMRUMYHU4V69eTT179qRdu3ZRixYtaNOmTdSxY0dauXIl9erVS2Th171796bNmzdT+/btg6qiEnzQYEighEB1g9N/tx2mO+etpsIS33ODz2xQi166vQed2aC2kpgoJDIEjPhDAwMYmc6DUiNGwIjzMmL05AtW6UM8awA//fRTGjBgAB09epTS09Npzpw5NG7cOPE+8ODl32nTptGIESOqKFFQUED8Yx0Mvnnz5nT48GFRJg79CfDg9Mknn1D//v0rPAnk6x+z6LevfkPZeUWiEenJ8fTXIefRxWfV079RhtawJi09haPwBCVMaSmaVPTQLqJEb96yyAgtPdUxa24MtHRWaPYh9evXJ175tOtDPGkA8/Pz6eKLL6YOHTrQggULhDqTJ0+mefPm0datWyuo1a5dO2H+JkyYUEXFiRMn0qRJk6p8vnDhQkpNTXVWdURTTuBIPtHszXF04KTvFjGxVEbXtyqlSxqXiUfI4QABpwnElRTQr74dJcK+3/lFKolLcroKiAcCIKAxgby8PBo6dCgMoLUJJFAr/m/kpptuop9++omWLl3qd8hsAOfPn09btmypIG3btm1p5MiRNH78+CqSYwZQ47MgxKoF++/0eH4xPfjGBv/NornYm88/g564ugMlYHNIiJSdSRZMS2dqEeEomAGMMGAUr5qAEeelamg2ysMMYA3XAHJHHDx4sNgJ/Nlnn1G9eqeW88JZAq6skcq1dxv6I6sEgVCuTykpLaP/+3gLvbDU9+xgPnq1zqQXbutOmbW8+SguCYTaJA1FS20qG25F+FFwX/7Fl/uSB/AouHA5Ip9jBIw4Lx2jGTyQSh/imSVgy/xt27aNPv/8c2rQoEEFktYmkFWrVonNIXzw6wsuuACbQIL3uahNITM4vbVuD41/c4N/c0jzzBR6efj51K5RWtS230sVl9HSS+32YlugpXdUhZbOammkAczNzaXt27cL0l27dqWpU6dS3759KTMzU9zrj28Ns27dOnr//fepUaNGfkX4+8RE3ywO3wZm3759NGvWLPGebwPTsmVL3AbG2f7raDTZwWndT9k0+pW1dDjXt/mndlI8/fXmLvTLs0/1KUcbgGB+ArJaAp2+BKClvtrI1gxayhKzl95IA8jX87Hhq3wMHz6ceLNG69atq6XKs4F9+vQR32VlZVW5EfSMGTNwI2h7/VHr3OEMTvuOnqRRr6yh7/cdE23jDSHjr+hAoy89k/gWRDjcIRCOlu7U1EbU0lKiw+XXKddvTxTrzZuUG6GljW4QTVmhpbNqGWkAnUVcfTSV4HVojwl1CHdwyisspgdf/4YWbzjgx3RDt2Y0+fpz8fg4lzpOuFq6VN3wwuI+gOFxQy7XCBhxXrpGt2pglT4kKq8BdEsLleDdaoNpce0MTqWlZfS3z7bR9E+3+bF1a1GHZg7rTg3Tkk1D6Xp77WjpeuVDrQAMYKikkE4TAkacl5qw5mqo9CEwgBLCqgQvERZJbRBQMTh98O1+euD19ZRf5HtySNOMZJp9ew/q1CzDRs2QVZaACi1lYzqeHgbQceQIaI+AEeelPURKc6v0ITCAEtKoBC8RFkltEFA1OH23N0dcF7g/J1/UJiUhjqYOPo+uPLeJjdohqwwBVVrKxHQ8LQyg48gR0B4BI85Le4iU5lbpQ2AAJaRRCV4iLJLaIKBycDp4LJ9G/2Mtrd996nGC9/drR2N+eRY2h9jQKNSsKrUMNabj6WAAHUeOgPYIGHFe2kOkNLdKHwIDKCGNSvASYZHUBgHVg1N+UQk9+tYGeut/e/21urpzE/q/G8+jlMQ4GzVF1mAEVGsZLJ4r38MAuoIdQcMnYMR5GT4e5TlV+hAYQAl5VIKXCIukNghEYnAqKyujWct20rNLNlNZma9y5zbLoBdv70GNM7A5xIZcp80aCS0jVdewy4UBDBsdMrpDwIjz0h201UZV6UNgACWEVQleIiyS2iAQycHp040/0+9e+x+dKCwRNWyQlkSzh3Wnri3q2qgxstZEIJJaakOdHwX32R991fnFE3gUnDbCoCJGn5caya/Sh8AASgirErxEWCS1QSDSpmHLgeM0cv5q2pN9UtQyMT6W/jyoMw3s2sxGrZG1OgKR1hLUnSMALZ1jHelI0DLShCuWr9KHwABKaKcSvERYJLVBwInBKetEIf1mwVr6+ocsf03v6dOGHhzQnmJj8eQQG/JVyOqElqrqinJOTwBaeqeHQEtntVTpQ2AAJbRTCV4iLJLaIODU4FRYXEpPvPMdvbZ6t7+2/Ts2omlDuojnCeOwT8ApLe3X1EYJ/Ci4nPI+lNEcj4KzgRJZnSFgxHnpDMqQoqj0ITCAISH3JVIJXiIsktog4OTgxJtD5q34kf70/kYqLd8c0qFxmtgc0jwz1UYrkJUJOKmla8SxCcQ19AgcHgEjzsvw0EQkl0ofAgMoIZFK8BJhkdQGATcGp2VbD9G9C9fR8fxiUfPMWok087bu1LN1po2WIKsbWjpOHQbQceQIaI+AEeelPURKc6v0ITCAEtKoBC8RFkltEHBrcNpxKJdGzV9DOw+fELVPiIuhJwd2oiHnt7DRGrOzuqWlo9RhAB3FjWD2CRhxXtrHpKwElT4EBlBCFpXgJcIiqQ0Cbg5OOXlF9NtX19GX2w77W3BDt2Z0Teem1OvMTEpNxLWBMtK6qaVMPW2lhQG0hQ+ZnSdgxHnpPNYaI6r0ITCAEsKqBC8RFkltEHB7cCouKaUnP9gkrg0MPBLjYql7y7p0absGdEnb+tSxSTp2DAfR2W0tbXTD0LPCAIbOCim1IGDEeakFaV8lVPoQGEAJYVWClwiLpDYI6DI4vfr1TzTpve8pv6i02tbUr51IF59Vny5p24AuaVefGqbhiSKVQemipY3uGDwrDGBwRkihFQEjzkuNiKv0ITCAEsKqBC8RFkltENE2vtIAACAASURBVNBpcDqWX0Qrth+hL7cdomXbDtHuLN/No6s7ePcwzw5e2rYB9WhVl5IT8JxhnbS00SVPnxUGMGJoUXBkCBhxXkYGXVilqvQhMIASEqgELxEWSW0Q0HVw4lvG7DqSJ4zgsq2H6asdh/2PlKvc3KT4WOp1Zj26tG19YQrbNqxNMTHm3WBaVy1tdM+qWYsLiD561Pf55ZOJ4pOUFq9LYUZoqQvsCNcDWkYYcKXiVfoQGEAJ7VSClwiLpDYIRMvgVFRSSut2ZYsNI2wKN+zNobLyewlWbn7j9GRx3eAl7RqIZWO+zYwJR7RoaYIWdtsILe0S1Cc/tHRWC5U+BAZQQjuV4CXCIqkNAtE6OPHj5ZZvP0x8T0E2hQeO5VdLgScCz22WIQwhLxd3bVFXPI/Yi0e0aulFLey2CVraJahPfmjprBYqfQgMoIR2KsFLhEVSGwS8MDjxcvG2g7l+M7jqhyM1biaplRhHvdvUK99d3IBa1Uv1zHKxF7QM2pV52jfviC9Zaj0ijy71G6FlULG9kQBaOqujSh8CAyihnUrwEmGR1AYBLw5O+UUltObH7PLrBw/R5gPHayR0Rt0UatOgNvGyceOMgJ/0ZGqSkUwZKQlRYxC9qGUV4bAJxMbZjqxuEDDivHQDbA0xVfoQGEAJYVWClwiLpDYImDA4HTyWL5aJeXcx/z5yojBkYrzBRBjDQIPIrwPeN6idRPFx7i8rm6AlwQCG3HeRUA8CRpyXeqAWtVDpQ2AAJYRVCV4iLJLaIGDa4FRaWkYb9x/zbSbZeojW/ZRNBcXV33swVKyxMUQN0pKocUYKNU5PKjeHKdQ4g1/zb59hTEmM7K1qjNASBjDUbol0mhAw4rzUhDUMoItCwAC6CD/M0KYPTnz9IG8o4U0kB3Lyxe+fc/Jpf/lr67Pj+cVhEj6VjZeTrZnDpnVSqGlGMonf4se3/JwUH75JNEJLGEDb/RAFOEvAiPPSWaSnjabSh2AGUEJYleAlwiKpDQIYnEKDd6Kg+JRJrGQOLZN4OLegxlvThBaFqH7tJGpWx2cMm2T4jKHfJGYki+9jecqxmsMILWEAQ+1KSKcJASPOS01YYwbQRSFgAF2EH2ZoDE5hgqvOgJWU0sHjBb6ZRL9JPEkHjvFn/JtnFwuosCT8JeeEuBhhDHmDSjM2iZZBzEihhrXj6btVX9IN115FCQkJ6hqmU0kwgDqpgbqEQABjbAiQFCZR6UMwAyghjErwEmGR1AYBDE424IWRlZeceRPK/qP5tPfoSdqfc5L2HeWffNpX/ppNZE03uQ4lZO2k+ErmMJkapidTZmoiZdZOpHq1EqlurURKS4qPmh3O/nbDAIbSBZBGIwIYY50VQ6UPgQGU0E4leImwSGqDAAYnG/AilLWwuJR+PpYvjCFfi3jKKPo+459jCq5JTIyLpbq1EqhuaiLVq51ImbWSKDM1wfeb37NhrOX7jtPUTU1wf7czPwruvbE+8tdMx6PgItQHUaw6Ahhj1bEMpSSVPgQGMBTi5WlUgpcIi6Q2CGBwsgHPxay5BcW0/+jJcnPoM4Z7svPoux17qCC+Fh2wudRcXdP4nsu8kcUyhmwOq/upVytJGEueieSdz2w0TXw2s53ugfPSDj298kJLZ/VQ6UNgACW0UwleIiyS2iCAwckGPM2yBmoZFxfvW2ouX1Y+lFtIWbmFlJ1XKD7POlFAWSeKyn8XUlFJDQ9WVtDGuNgYSk2IE2YwNZF/x4vf4nVCNZ/xd+Jzn4H05fG9D8zD75MTvGkucV4q6HiaFAEtnRVCpQ+BAZTQTiV4ibBIaoMABicb8DTLGq6WfF0izyjy7XDYHGaX/+b3ga/5vfXD6d05yiiFCkTok5QkZhYtE8mGMD0lXsxS8k96cvlv633571Pfc/oEStDgJt6VWYarZSQ04Xtn1rTzPBLxvFamTlp6jW117VHpQ2AAJXqMSvASYZHUBgEMTjbgaZbVSS0Likso+0QRHTlR4P8daBh5pvFEQQmdLCyhvKJiyissf13+O9yd0CmUT5uS7xTkz86fQycp2bYK/HxoYRjLfyobyAw2lamnDKWVln8nJ4R/38bTVVyFlmzsTxaVEN/D8nh+kbhuNFe89r0P/LzCZwW+76y0rBUzEnz8ptpnnvk9//YZbp/59qcTzOLFpQAmXwKgQkvbndygAlT6EBhAiY6jErxEWCS1QQCDkw14mmWNJi2LS0opr+iUKcwrLPaZxfKfk0X8vpT8n5enLco/Tk9tvFyQv6PxO5RdkkAnC30Gk+/VyCanpDRyy9mVJedbMvIMIl/nmBAfS/GxMb738bHEt+zh1/yYwMTy1/ze9+P7zpe2PF0slxEjyoqlMtq5fSt16ng2JSf6Zik5T3xcjGhroGFjo8bt9pu6AANX7CCLmk4HZlTZPFoztIHm0TLgbCp5qT82JoY4L5tHvv7Ues+/+T1/zt9b733fxxDfJVP8jj2Vhz+tqYxIn8bRdF5GmoUT5av0ITCAEoqpBC8RFkltEMDgZAOeZlmN0DLIbWB41utEYQnlnCyinDye9SryvT5ZRMfKf/zv84v931nf230soGZdIqzq8DWbaeUzd2nJCcTPw+Ylf8Evv4jyi8K/j2VYFYpwJstECgMZSxRXbiR52ZtZWN/7Xgek4e8rpLUMpy8ff+cznURZRw5TwwYNxD8D/nLKy7LMqWVoLQPLTtYytJZ5tYyv3+SWp2FEp4xwuWmmQPNMbIF9xrk6nvxFNUf1n3K51Yvis98VD5+Jtwx7RdMeaOKrM/u+761/BKw2BpRR3ka/hrFEeSdy6ZoeZ1FOTg6lp6fb6j0wgBL4YAAlYGmS1AjToAnrSFfDCC0jfB/A/KISv9GxjKLPHJ4yi2yErO84fWFJGRWVlBLPavJmGl4y5fdFxaVUVFpGfFsfpw6eJWTTxgZO/CRZr32/eUmWv69tfV+e1vqc0/A1ladbsuXlf+ZhmWuLB89CWiabv7OY+V6Xm3CHZ2id4o44+hAoLcij3dMHwwA6LQkMoNPE7cczwjTYxxQVJRihZYQNYCSE5llJXpa2zKFlFNkkWmax2DKObBpLyuhkYSGt+noNde7SlUoptkI6Nmg+gxdg9Mpf82ydztfbWTO01myib5bWZxyF0S6fsfXNMpZRaSlRaVkZ8Uo25+XXvMDP78Vr/qw8DX/uS1NNniqfWfl9eUoCyuFyWS8ux/ebY5Sn4XLKX/N3fMN2/s35LZ01WHWPRDeOmjJhAF2SCgbQJfA2whphGmzwiaasRmgZhQYwnD5khJbhgImCPIEmlM1hQWEhLfnoY+rXrz/FxsX7zGa54WQ7a5lbNpP8c8rk+gwml+czt6dMK6fhw2eCT+URacX7U/lEWuszUdKpo7onDlV3BS2XW/mo9krbSh9yzQPrc8rIV6zzKR4Bxj6gvYFMK3MQZVpxSssoLzeXxg/shhlAp88VGECniduPhz809hnqUoIRWsIA6tLdUI8QCRhxXobIwolkKn1I1FwDuGzZMpoyZQqtXbuW9u/fT4sWLaKBAwf6ebODnjRpEs2ePZuys7OpV69e9Pzzz9M555zjT8Ofjxkzht59913x2bXXXkvPPfcc1alTJyTdVIIPKSAS2SaAwck2Qm0KMELLonyiRaN9zK+fTZRg/zYw2ggYUBEjtNQRfATqBC0jAPU0Rar0IVFjAD/88ENavnw5devWjQYNGlTFAD777LP01FNP0bx586hdu3b05JNPEpvGLVu2UFpamsB55ZVX0p49e4RJ5GP06NHUqlUreu+990JSUCX4kAIikW0CGJxsI9SmAGipjRS2KwItbSPUpgBo6awUKn1I1BjAQMR8EXDgDCDP/jVt2pTGjh1LjzzyiEhaUFBAjRo1IjaGd911F23atIk6duxIK1euFLODfPDr3r170+bNm6l9+/ZBVVQJPmgwJFBCAIOTEoxaFAIttZBBSSWgpRKMWhQCLZ2VQaUP8YQB3LlzJ7Vp04bWrVtHXbt29atx3XXXieXd+fPn05w5c2jcuHF09OjRCmrx99OmTaMRI0YEVVEl+KDBkEAJAQxOSjBqUQi01EIGJZWAlkowalEItHRWBpU+xBMGcMWKFXTRRRfR3r17xUygdfAS765du+ijjz6iyZMni+XhrVu3VlCLl4vZ/E2YMKGKijyLyD/WweCbN29Ohw8ftn0DRme7jLnReHD65JNPqH///pSQkGAuCA+03AgtC09QwpSWQq2ih3YRJdbygHJVm2CElp5UDlq6LSv7kPr165u7C7jyErBlAPft20dNmjTx6zNq1CjavXs3LVmyRBhAngnkawIDj7Zt29LIkSNp/PjxVXSdOHGi2FhS+Vi4cCGlpqa63Q8QHwRAwGME4koK6FffjhKter/zi1QSl+SxFqI5IAACdgjk5eXR0KFDYQCtXcCRWgLGDKCdbqpHXsw06KGDiloYoSVmAFV0FZThIAEjzksHeQYLhRnAGjaB3H///fTwww8LfoWFhdSwYcMqm0BWrVpFPXv2FGn49QUXXIBNIMF6XBR/j+tToli8SlU3QkvcB9A7HdaQlhhxXmqkpZHXAObm5tL27duFDLzRY+rUqdS3b1/KzMykFi1aCKP39NNP09y5c4mXdXnJd+nSpVVuA8PLxLNmzRLl8DWCLVu2xG1gNOrcqquCwUk1UffKM0JLGED3Ohgih0XAiPMyLDKRyWSkAWQzx4av8jF8+HCxucO6ETSbu8AbQXfq1MmfJSsrq8qNoGfMmIEbQUemn2pRKgYnLWRQUgkjtIQBVNJXUIhzBIw4L53DGTSSkQYwKBUHEqgE70B1EYJ3UhYV0eLFi+mqq67CLuAo7xFGaAkDGOW91LzqG3FeaiSrSh8SlbeBcUsLleDdaoNpcTE4eUdxI7TkR8H9e5hPtMH/wKPgvNN9PdsSI85LjdRT6UNgACWEVQleIiyS2iCAwckGPM2yQkvNBLFRHWhpA55mWaGls4Ko9CEwgBLaqQQvERZJbRDA4GQDnmZZoaVmgtioDrS0AU+zrNDSWUFU+hAYQAntVIKXCIukNghgcLIBT7Os0FIzQWxUB1ragKdZVmjprCAqfQgMoIR2KsFLhEVSGwQwONmAp1lWI7TkTSBTzvKRf2i7px8Fh81Zmp1gYVbHiPMyTDaRyKbSh8AASiikErxEWCS1QQCDkw14mmU1QkvsAtas16E6wQgYcV4Gg+Dg9yp9CAyghHAqwUuERVIbBDA42YCnWVYjtIQB1KzXoTrBCBhxXgaD4OD3Kn0IDKCEcCrBS4RFUhsEMDjZgKdZViO0hAHUrNehOsEIGHFeBoPg4PcqfQgMoIRwKsFLhEVSGwQwONmAp1lWI7SEAdSs16E6wQgYcV4Gg+Dg9yp9CAyghHAqwUuERVIbBDA42YCnWVYjtIQB1KzXoTrBCBhxXgaD4OD3Kn0IDKCEcCrBS4RFUhsEMDjZgKdZViO0hAHUrNehOsEIGHFeBoPg4PcqfQgMoIRwKsFLhEVSGwQwONmAp1lWI7QsOkm04EYf+dveIEpI0UwFNdUxQks1qLQvBVo6K5FKHwIDKKGdSvASYZHUBgEMTjbgaZYVWmomiI3qQEsb8DTLCi2dFUSlD4EBlNBOJXiJsEhqgwAGJxvwNMsKLTUTxEZ1oKUNeJplhZbOCqLSh8AASminErxEWCS1QQCDkw14mmWFlpoJYqM60NIGPM2yQktnBVHpQ2AAJbRTCV4iLJLaIIDByQY8zbIaoSVvApl+ro/82A14FJxmfRDVqUrAiPNSI+FV+hAYQAlhVYKXCIukNghgcLIBT7OsRmiJXcCa9TpUJxgBI87LYBAc/F6lD4EBlBBOJXiJsEhqgwAGJxvwNMtqhJYwgJr1OlQnGAEjzstgEBz8XqUPgQGUEC4nJ4fq1KlDu3fvpvT0dImcSOoWAR6cPv74YxowYAAlJCS4VQ3EVUDACC3ZAP6lvY/WA1s8vQSM81LBSaFBEUaclxpwtqrABrB58+Z09OhRysjIsFUzGEAJfHv27BHgcYAACIAACIAACICAWwR4IuqMM86wFR4GUAJfaWkp7du3j9LS0igmJkYiJ5K6RcD6bwmztm4poC4utFTH0u2SoKXbCqiLDy3VsQylpLKyMjp+/Dg1bdqUYmNjQ8lSYxoYQFv4kFl3Aiqvl9C9rV6vH7T0jsLQElp6h0D0tgQGMHq1Q81DIIA/NCFAipIk0DJKhAqhmtAyBEhRkgRaRolQ1VQTBjB6tUPNQyCAwSkESFGSBFpGiVAhVBNahgApSpJAyygRCgYweoVCzcMjUFBQQE8//TRNmDCBkpKSwisEubQgAC21kEFJJaClEoxaFAIttZAhrEpgBjAsbMgEAiAAAiAAAiAAAtFLAAYwerVDzUEABEAABEAABEAgLAIwgGFhQyYQAAEQAAEQAAEQiF4CMIDRqx1qDgIgAAIgAAIgAAJhEYABDAsbMulGgDd6vPXWW7R582ZKSUmhCy+8kJ599llq3778sVpExBcrP/jgg/Tqq6/SyZMn6Ze//CX9/e9/t303dd1YeKk+rOujjz5Kv/vd72j69OmiadAxehTeu3cvPfLII/Thhx+Kc65du3b08ssvU/fu3UUj+Ka2kyZNotmzZ1N2djb16tWLnn/+eTrnnHOip5EG1LS4uJgmTpxI//znP+nAgQPUpEkTuuOOO+jxxx/334wYWkZfR4ABjD7NUONqCFxxxRV088030/nnn088WD322GO0YcMG2rhxI9WqVUvkuPvuu+m9996jefPmUb169eiBBx6grKwsWrt2LcXFxYGrZgRWr15NgwcPFs/d7tu3r98AQkfNhKqhOmzounbtKrRjzRo2bEg7duygVq1aUZs2bUQu/iftqaeeEuckm8Mnn3ySli1bRlu2bBFPXMKhBwHWaNq0aTR//nxhztesWUMjRowQevE/Z9BSD51kawEDKEsM6aOCwKFDh8QfnC+++IIuvfRSysnJoQYNGtA//vEPGjJkiGgDP9aPn+28ePFiuvzyy6OiXaZUMjc3l7p16yZmaPmPTJcuXYQBhI7R0wPGjx9Py5cvpy+//LLaSvOMET/OauzYsWKWkA+e3W3UqJEwhnfddVf0NNbjNf3Vr34ldOHZW+sYNGgQpaamijEVWkZnB4ABjE7dUOsgBLZv305t27YVs4CdOnWizz77TCz58oxf3bp1/bnPO+88GjhwoFiGwqEPgeHDh1NmZqaYdejTp4/fAEJHfTQKVpOOHTuKf6z27Nkj/hFr1qwZ3XPPPTRq1CiRdefOnWImcN26dWKm0Dquu+46qlOnjphtwqEHgWeeeYZmzpxJH3/8sZip/eabb2jAgAHin7JbbrkFWuohk3QtYAClkSGD7gT4v1H+I8JLUNbsw8KFC8WSBc8wBB48iLVu3ZpmzZqle7OMqd9rr70mlgV5CTg5ObmCAYSO0dMNWDs+xo0bRzfddBN9/fXXYraPz7Xbb7+dVqxYQRdddBHxdYI8E2gdo0ePpl27dtFHH30UPY31eE15TOVrcXlmli+XKSkpEeco32CfD2gZnR0ABjA6dUOtT0Pg3nvvpQ8++ID++9//+jd41GQc+vfvL2Yh+L9bHO4T2L17N/Xo0UPMNPDsLB+BM4DQ0X2NQq1BYmKi0JLNgXWMGTNGGPuvvvrKbxr4UgzeVGAdPEPI/WDJkiWhhkK6CBPgf8oeeughmjJlirgGcP369cLMT506lXi23jKA0DLCQiguHgZQMVAU5y6B++67j95++21xITnP7FkHlg7d1SXU6Kzd9ddfX2FTDs82xMTEiN2GPCvUr18/LOWHCtTFdC1btiT+B+ull17y1+KFF14Q13TyrB+WgF0URzI0XyvN13TyP9fWwTouWLBA3HkBWkoC1SQ5DKAmQqAa9gjwEgWbv0WLFtHSpUvF9X+Bh7V5gAcs3lnKx/79+8UMITaB2GOvMvfx48fF8l/gwUv3HTp0EBsF+A8Rb+aBjiqpR6asoUOHipm8wE0g999/P61atUrMGFkbB/izhx9+WFSisLBQbN7CJpDIaBJuqXzXBDZ8vJvbOvgWTXPnzqWtW7dCy3DBupwPBtBlARBeDQG+uJyXB995550K9/7LyMgQ9wXkgwev999/X9xygjcY8D0Bjxw5gtvAqJEgYqUELgFDx4hhVl4wL/Xy/Th5gxX/08XXAPLyLt/z79ZbbxXx2OhZRoL/aZs8ebL4Bw63gVEuh60C+Z5/n376qbh+k5eA//e//xFfq3nnnXcKDaGlLbyuZYYBdA09AqskwEuE1R38HyoPXnzk5+eL61jYKAbeCJpnlXDoS6CyAYSO+mpVuWb8DxdvFNi2bZu4JIM3hFi7gDmtdfNgNhaBN4Lmnfs49CHAM/O///3vxQrLwYMHxaYd3v37xBNPEF/rCS310UqmJjCAMrSQFgRAAARAAARAAAQ8QAAG0AMiogkgAAIgAAIgAAIgIEMABlCGFtKCAAiAAAiAAAiAgAcIwAB6QEQ0AQRAAARAAARAAARkCMAAytBCWhAAARAAARAAARDwAAEYQA+IiCaAAAiAAAiAAAiAgAwBGEAZWkgLAiAAAiAAAiAAAh4gAAPoARHRBBAAARAAARAAARCQIQADKEMLaUEABEAABEAABEDAAwRgAD0gIpoAAiAQnMCPP/4onkbBj7Hq0qVL8AwOpNi8ebN4Us369evF8475Nw4QAAEQcIIADKATlBEDBEBAGJ358+eLZ7+OHz/eT+Ttt9+m66+/XjwWLJKHjgZwyJAhdPjwYZozZw7Vrl2b6tWrF0kEKBsEQAAE/ARgANEZQAAEHCHABvBf//oXJScn086dO6lu3boibrQbwMLCQv/zUGVB9ujRg66++mqaNGmSbNaIp7fTrohXDgFAAARsE4ABtI0QBYAACIRCgA3gkSNHaPv27XTNNdfQn//852oN4MSJE4UpDFwOnT59OvEPz+LxwWUdPXqUevbsSX/961+poKCA7r//fnrsscdowoQJ9PLLL1Nqair98Y9/pDvvvFPksWYAX331Vfrb3/5G69atozZt2tDzzz9Pffr08Tdh48aN9OCDD9KyZcuoVq1aNGDAAJo2bRrVr19fpOG0nTp1EqbvlVdeoXPOOYe++OKLKghKS0vpySefpNmzZ9OhQ4fo7LPPpmeeeYauuOIKkTYmJqZCnj/84Q/Eba98cLzOnTsL4/zSSy+JuL/5zW8qpM3JyaGHHnpIcMvPzyc2llzn8847rwIv/t46xo4dKxgvXbr0tO366aef6L777qP//Oc/FBsbK+r/3HPPUaNGjUQ+S68HHniAfv/731N2djZdeeWV9OKLL1JaWppI88YbbwiTy9qzLl27dqV33nlH8MUBAiDgDgEYQHe4IyoIGEfAMm3Dhw+noUOH0rZt2+iMM86oMgMYqgF866236PbbbxfmZPny5TRy5Ei6/PLL6dJLL6WbbrpJzDayAdyxYwc1b97cbwA5JpvJjh070tSpU0W6H374QSy/7t+/X5itUaNGibJPnjxJjzzyCBUXF9Nnn33mN0pr166lu+++W8TkpWu+fq/ywQaM2zJr1ixheHiZlz/7/vvvqW3btnTgwAHq16+fMFRsOHkJmH+qM4B83eK4ceMEt6+++koY4I8++oj69+8v4l9yySWUmZlJTzzxBGVkZIiY8+bNo61bt4rPLfbBDGDldrVv3566d+8ujBozYw733HOPMHaWceQ2/uUvfxFGmU0eG8DBgwcL4/3UU08Jpi1atBCGn5f6jx8/Tl9++aXgW117jTsx0GAQcIkADKBL4BEWBEwjEGhCevfuLQwYz9RVXgIO1QCyAeGlZJ6V4oNNWMOGDcXMHR8lJSXCDPGs2c033+w3gDwLx6aODzY0vDGETeTDDz8sDNSqVauEubKOPXv2CAO5ZcsWateunZgB5Bk3NmWnO5o1a0b33nsvPfroo/5kPGN5/vnni1lHPngzysCBA6ud+bMycTxuC5sm6+ByfvGLX4gZRTambKwOHjxISUlJ/jRnnXWWaNPo0aNDNoCV2/XJJ5+I2Tw2yMyAD54h5VnPr7/+WrSF9ZoyZYowtNaMH8dlHVauXClmWtlE8gxsy5YtTev2aC8IaEsABlBbaVAxEPAWgUADyOaADcy3334rZqkCN4GEagB5WfWDDz7wQ7rsssvE0qxlrvgLNhy8NDlmzBi/AeTlWp4ltA6OXadOHZo7d664Ho9NDy+zBh4nTpygxYsXCzPEhoxn8HiJs6bj2LFjwnyySeV6WQcvU3/zzTf+2cRQDSAbrsB2XXfddWLGkmcV2XzxppqUlJQK1eHZS55ZfPbZZ0M2gJXbxUvlPGvJBjDw4Os3eemdZ/FYr9dff13MbFoH5+FlYjbobF55ZpYNI//mmcIbb7zRfw2ot3o5WgMC0UMABjB6tEJNQSCqCVRehmSzlZCQIMxJoAHkZds333xTGCXrYJPDBqjyNYCBS5pszNhQ8VKldbRq1Yr4Wjf+sa4BrM4AsqFhM8UGj69RY9NU+WjSpIlYCq0uTuW0lgGsHIvrsWHDBnE9HR+hGsDK7eJZQzatvMzLdWWzZS3JBtaF0/C1i7wcy9df8nV31sGzk2zaAq8BrByHTR7/sJGrXC7HHDZsmP8awNNds8nL1CtWrKCPP/6YFi1aJGYLeaaVZ19xgAAIuEMABtAd7ogKAsYRqGwA2Qix4eAZOjZ41m1gXnjhBWEq2CRYGyVuvfVWcZ2fCgPIhomXKPngJeAzzzyTfvvb34rPeBMJm8/vvvuO4uPjq9UoFAPIGWtaAubl2xkzZigzgNYyLW+wYMNb3cFL3p9//rmYhbOOiy66SBjw0xnA0y0Br169Wmw2CWXGNrBOPCPIM7N8TSP/4AABEHCHAAygO9wRFQSMI1DdRgReQuTlQ965ahnATZs2iWvM+H6BvFS4ZMkSsbs0PT1diQHknfCf3gAAAptJREFUDQk8S8i7cnmpcuHChWKJk2fK9u3bJ0wpL9vyrlr+jI3Va6+9JpZ84+LiQpoBZHE5Bu/s5V3AXCYvMfOmE2sTCKdRMQPI3HhJmzdXsLnljRvcDl6y5plCNml8TSPPbvKMIV9/uWDBAlE/3pxyOgPIZfP1e7xZI3ATCL8P3ARyul3bPNPHM5689MvXaPL72267TVz7yXXCAQIg4A4BGEB3uCMqCBhHoDoDuGvXLmFY+DYugTeCnjlzJk2ePJmysrJo0KBBIg0bKRUzgGz4eFmTN3HwbWB4No6vR7QO3p1szZhxvXi2infqsnnjGclQZwADbwPDGzR400vgbWBUGUAuh82fNXvJ10Y2btxYmEI20dbmDTajvDuYzTYvCRcVFYnl6NMZQC471NvA1LQEzIaer33kzSC8NM48edMNz7riAAEQcI8ADKB77BEZBEAABEAABEAABFwhAAPoCnYEBQEQAAEQAAEQAAH3CMAAuscekUEABEAABEAABEDAFQIwgK5gR1AQAAEQAAEQAAEQcI8ADKB77BEZBEAABEAABEAABFwhAAPoCnYEBQEQAAEQAAEQAAH3CMAAuscekUEABEAABEAABEDAFQIwgK5gR1AQAAEQAAEQAAEQcI8ADKB77BEZBEAABEAABEAABFwhAAPoCnYEBQEQAAEQAAEQAAH3CMAAuscekUEABEAABEAABEDAFQIwgK5gR1AQAAEQAAEQAAEQcI8ADKB77BEZBEAABEAABEAABFwhAAPoCnYEBQEQAAEQAAEQAAH3CMAAuscekUEABEAABEAABEDAFQIwgK5gR1AQAAEQAAEQAAEQcI8ADKB77BEZBEAABEAABEAABFwhAAPoCnYEBQEQAAEQAAEQAAH3CPw/prMmHsaWAcYAAAAASUVORK5CYII=\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"elm_tuning.unscaled_target.plot(lw = 2, label = 'RMSE for ELM')\n",
"plt.plot([50, 50], [0, 300], '--', label = 'Lowest RMSE with full rank')\n",
"plt.xlabel('Number of neurons')\n",
"plt.ylabel('RMSE (in $kWh/m^2$)')\n",
"plt.ylim((90, 250))\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.tight_layout()\n",
"plt.savefig('ELM_tuning.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tuning SVM"
]
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 134,
"metadata": {},
"outputs": [],
"source": [
- "training = training_data.sample(10000)\n",
+ "training = training_data.sample(1000)\n",
"x, t, X, T = get_data( training, feature_names, label_name)"
]
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": 135,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
- "SVM C = 0.100000\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 20257.683947\n",
+ "SVM (scaled) RMSE: 142.329491\n",
+ "SVM (scaled) MAE: 100.803742\n",
+ "SVM (scaled) MAEP: 0.121330\n",
+ "SVM (scaled) MBE: -13.588861\n",
+ "SVM (scaled) MBEP: -0.051479\n",
+ "SVM (scaled) R2: 0.680607\n",
+ "Crossvalidation time: 18.183s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 15193.700803\n",
+ "SVM (scaled) RMSE: 123.262731\n",
+ "SVM (scaled) MAE: 83.405053\n",
+ "SVM (scaled) MAEP: 0.102458\n",
+ "SVM (scaled) MBE: -12.101577\n",
+ "SVM (scaled) MBEP: -0.046295\n",
+ "SVM (scaled) R2: 0.760448\n",
+ "Crossvalidation time: 19.089s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11746.300776\n",
+ "SVM (scaled) RMSE: 108.380352\n",
+ "SVM (scaled) MAE: 67.392852\n",
+ "SVM (scaled) MAEP: 0.085151\n",
+ "SVM (scaled) MBE: -12.211091\n",
+ "SVM (scaled) MBEP: -0.041217\n",
+ "SVM (scaled) R2: 0.814802\n",
+ "Crossvalidation time: 17.983s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11410.437945\n",
+ "SVM (scaled) RMSE: 106.819651\n",
+ "SVM (scaled) MAE: 65.866525\n",
+ "SVM (scaled) MAEP: 0.083401\n",
+ "SVM (scaled) MBE: -12.158720\n",
+ "SVM (scaled) MBEP: -0.040521\n",
+ "SVM (scaled) R2: 0.820097\n",
+ "Crossvalidation time: 17.730s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 11218.841350\n",
+ "SVM (scaled) RMSE: 105.919032\n",
+ "SVM (scaled) MAE: 65.024270\n",
+ "SVM (scaled) MAEP: 0.082461\n",
+ "SVM (scaled) MBE: -12.778295\n",
+ "SVM (scaled) MBEP: -0.040685\n",
+ "SVM (scaled) R2: 0.823118\n",
+ "Crossvalidation time: 17.990s\n",
"\n",
+ "SVM C = 1.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 61436.965206\n",
- "SVM (unscaled) RMSE: 247.864812\n",
- "SVM (unscaled) MAE: 204.182984\n",
- "SVM (unscaled) MAEP: 0.218677\n",
- "SVM (unscaled) MBE: -15.214545\n",
- "SVM (unscaled) MBEP: -0.086046\n",
- "SVM (unscaled) R2: -0.002035\n",
- "Crossvalidation time: 10.509s\n",
- "SVM (unscaled) MSE: 61470.668914\n",
- "SVM (unscaled) RMSE: 247.932791\n",
- "SVM (unscaled) MAE: 204.226638\n",
- "SVM (unscaled) MAEP: 0.218716\n",
- "SVM (unscaled) MBE: -15.200682\n",
- "SVM (unscaled) MBEP: -0.086048\n",
- "SVM (unscaled) R2: -0.002585\n",
- "Crossvalidation time: 10.907s\n",
- "SVM (scaled) MSE: 46564.437726\n",
- "SVM (scaled) RMSE: 215.787946\n",
- "SVM (scaled) MAE: 175.139796\n",
- "SVM (scaled) MAEP: 0.189158\n",
- "SVM (scaled) MBE: -10.193433\n",
- "SVM (scaled) MBEP: -0.073432\n",
- "SVM (scaled) R2: 0.240535\n",
- "Crossvalidation time: 10.953s\n",
- "\n",
- "SVM C = 0.200000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10955.732551\n",
+ "SVM (scaled) RMSE: 104.669635\n",
+ "SVM (scaled) MAE: 64.196585\n",
+ "SVM (scaled) MAEP: 0.081341\n",
+ "SVM (scaled) MBE: -12.761114\n",
+ "SVM (scaled) MBEP: -0.040025\n",
+ "SVM (scaled) R2: 0.827266\n",
+ "Crossvalidation time: 18.211s\n",
"\n",
+ "SVM C = 1.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 61327.417238\n",
- "SVM (unscaled) RMSE: 247.643730\n",
- "SVM (unscaled) MAE: 203.993537\n",
- "SVM (unscaled) MAEP: 0.218524\n",
- "SVM (unscaled) MBE: -15.385638\n",
- "SVM (unscaled) MBEP: -0.086150\n",
- "SVM (unscaled) R2: -0.000248\n",
- "Crossvalidation time: 10.365s\n",
- "SVM (unscaled) MSE: 61391.360933\n",
- "SVM (unscaled) RMSE: 247.772801\n",
- "SVM (unscaled) MAE: 204.076159\n",
- "SVM (unscaled) MAEP: 0.218590\n",
- "SVM (unscaled) MBE: -15.314538\n",
- "SVM (unscaled) MBEP: -0.086114\n",
- "SVM (unscaled) R2: -0.001291\n",
- "Crossvalidation time: 10.875s\n",
- "SVM (scaled) MSE: 37741.623404\n",
- "SVM (scaled) RMSE: 194.272035\n",
- "SVM (scaled) MAE: 155.043688\n",
- "SVM (scaled) MAEP: 0.168939\n",
- "SVM (scaled) MBE: -8.602787\n",
- "SVM (scaled) MBEP: -0.066009\n",
- "SVM (scaled) R2: 0.384435\n",
- "Crossvalidation time: 10.974s\n",
- "\n",
- "SVM C = 0.500000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10871.185745\n",
+ "SVM (scaled) RMSE: 104.264979\n",
+ "SVM (scaled) MAE: 63.729139\n",
+ "SVM (scaled) MAEP: 0.080857\n",
+ "SVM (scaled) MBE: -12.595900\n",
+ "SVM (scaled) MBEP: -0.039674\n",
+ "SVM (scaled) R2: 0.828599\n",
+ "Crossvalidation time: 18.925s\n",
"\n",
+ "SVM C = 1.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 60987.196189\n",
- "SVM (unscaled) RMSE: 246.955859\n",
- "SVM (unscaled) MAE: 203.425600\n",
- "SVM (unscaled) MAEP: 0.217960\n",
- "SVM (unscaled) MBE: -15.313219\n",
- "SVM (unscaled) MBEP: -0.085922\n",
- "SVM (unscaled) R2: 0.005301\n",
- "Crossvalidation time: 10.394s\n",
- "SVM (unscaled) MSE: 61145.928450\n",
- "SVM (unscaled) RMSE: 247.277028\n",
- "SVM (unscaled) MAE: 203.629148\n",
- "SVM (unscaled) MAEP: 0.218144\n",
- "SVM (unscaled) MBE: -15.265690\n",
- "SVM (unscaled) MBEP: -0.085952\n",
- "SVM (unscaled) R2: 0.002712\n",
- "Crossvalidation time: 11.727s\n",
- "SVM (scaled) MSE: 27946.209594\n",
- "SVM (scaled) RMSE: 167.171198\n",
- "SVM (scaled) MAE: 128.833987\n",
- "SVM (scaled) MAEP: 0.143014\n",
- "SVM (scaled) MBE: -9.551294\n",
- "SVM (scaled) MBEP: -0.057664\n",
- "SVM (scaled) R2: 0.544198\n",
- "Crossvalidation time: 11.652s\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 10900.085283\n",
+ "SVM (scaled) RMSE: 104.403474\n",
+ "SVM (scaled) MAE: 63.815915\n",
+ "SVM (scaled) MAEP: 0.080894\n",
+ "SVM (scaled) MBE: -12.388687\n",
+ "SVM (scaled) MBEP: -0.039405\n",
+ "SVM (scaled) R2: 0.828144\n",
+ "Crossvalidation time: 19.250s\n",
"\n",
"SVM C = 1.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 10997.590351\n",
+ "SVM (scaled) RMSE: 104.869397\n",
+ "SVM (scaled) MAE: 64.068174\n",
+ "SVM (scaled) MAEP: 0.081323\n",
+ "SVM (scaled) MBE: -12.164438\n",
+ "SVM (scaled) MBEP: -0.039380\n",
+ "SVM (scaled) R2: 0.826606\n",
+ "Crossvalidation time: 20.219s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 18756.129847\n",
+ "SVM (scaled) RMSE: 136.953021\n",
+ "SVM (scaled) MAE: 96.394078\n",
+ "SVM (scaled) MAEP: 0.116256\n",
+ "SVM (scaled) MBE: -12.296302\n",
+ "SVM (scaled) MBEP: -0.049013\n",
+ "SVM (scaled) R2: 0.704281\n",
+ "Crossvalidation time: 18.101s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 13449.226202\n",
+ "SVM (scaled) RMSE: 115.970799\n",
+ "SVM (scaled) MAE: 75.881400\n",
+ "SVM (scaled) MAEP: 0.094216\n",
+ "SVM (scaled) MBE: -11.562613\n",
+ "SVM (scaled) MBEP: -0.043459\n",
+ "SVM (scaled) R2: 0.787952\n",
+ "Crossvalidation time: 18.108s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11489.376738\n",
+ "SVM (scaled) RMSE: 107.188510\n",
+ "SVM (scaled) MAE: 66.243476\n",
+ "SVM (scaled) MAEP: 0.083769\n",
+ "SVM (scaled) MBE: -12.019165\n",
+ "SVM (scaled) MBEP: -0.040263\n",
+ "SVM (scaled) R2: 0.818852\n",
+ "Crossvalidation time: 18.338s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11261.467602\n",
+ "SVM (scaled) RMSE: 106.120062\n",
+ "SVM (scaled) MAE: 65.210966\n",
+ "SVM (scaled) MAEP: 0.082578\n",
+ "SVM (scaled) MBE: -12.348857\n",
+ "SVM (scaled) MBEP: -0.040116\n",
+ "SVM (scaled) R2: 0.822446\n",
+ "Crossvalidation time: 18.478s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 11114.131903\n",
+ "SVM (scaled) RMSE: 105.423583\n",
+ "SVM (scaled) MAE: 64.690053\n",
+ "SVM (scaled) MAEP: 0.081927\n",
+ "SVM (scaled) MBE: -12.662760\n",
+ "SVM (scaled) MBEP: -0.040075\n",
+ "SVM (scaled) R2: 0.824769\n",
+ "Crossvalidation time: 18.350s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10880.251537\n",
+ "SVM (scaled) RMSE: 104.308444\n",
+ "SVM (scaled) MAE: 63.914490\n",
+ "SVM (scaled) MAEP: 0.080816\n",
+ "SVM (scaled) MBE: -12.406063\n",
+ "SVM (scaled) MBEP: -0.039243\n",
+ "SVM (scaled) R2: 0.828456\n",
+ "Crossvalidation time: 18.815s\n",
"\n",
+ "SVM C = 2.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 60456.260746\n",
- "SVM (unscaled) RMSE: 245.878549\n",
- "SVM (unscaled) MAE: 202.548556\n",
- "SVM (unscaled) MAEP: 0.217044\n",
- "SVM (unscaled) MBE: -15.021369\n",
- "SVM (unscaled) MBEP: -0.085392\n",
- "SVM (unscaled) R2: 0.013960\n",
- "Crossvalidation time: 10.457s\n",
- "SVM (unscaled) MSE: 60736.896209\n",
- "SVM (unscaled) RMSE: 246.448567\n",
- "SVM (unscaled) MAE: 202.901081\n",
- "SVM (unscaled) MAEP: 0.217341\n",
- "SVM (unscaled) MBE: -14.767711\n",
- "SVM (unscaled) MBEP: -0.085301\n",
- "SVM (unscaled) R2: 0.009383\n",
- "Crossvalidation time: 11.069s\n",
- "SVM (scaled) MSE: 24246.604572\n",
- "SVM (scaled) RMSE: 155.713213\n",
- "SVM (scaled) MAE: 117.318844\n",
- "SVM (scaled) MAEP: 0.131952\n",
- "SVM (scaled) MBE: -10.869037\n",
- "SVM (scaled) MBEP: -0.053569\n",
- "SVM (scaled) R2: 0.604539\n",
- "Crossvalidation time: 10.629s\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10896.508972\n",
+ "SVM (scaled) RMSE: 104.386345\n",
+ "SVM (scaled) MAE: 63.778081\n",
+ "SVM (scaled) MAEP: 0.080708\n",
+ "SVM (scaled) MBE: -12.424258\n",
+ "SVM (scaled) MBEP: -0.039168\n",
+ "SVM (scaled) R2: 0.828200\n",
+ "Crossvalidation time: 19.913s\n",
"\n",
"SVM C = 2.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 10949.589861\n",
+ "SVM (scaled) RMSE: 104.640288\n",
+ "SVM (scaled) MAE: 63.921499\n",
+ "SVM (scaled) MAEP: 0.080892\n",
+ "SVM (scaled) MBE: -12.261219\n",
+ "SVM (scaled) MBEP: -0.039032\n",
+ "SVM (scaled) R2: 0.827363\n",
+ "Crossvalidation time: 21.399s\n",
"\n",
+ "SVM C = 2.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 59486.386250\n",
- "SVM (unscaled) RMSE: 243.898311\n",
- "SVM (unscaled) MAE: 200.880797\n",
- "SVM (unscaled) MAEP: 0.215426\n",
- "SVM (unscaled) MBE: -15.075986\n",
- "SVM (unscaled) MBEP: -0.084956\n",
- "SVM (unscaled) R2: 0.029779\n",
- "Crossvalidation time: 10.326s\n",
- "SVM (unscaled) MSE: 59978.894363\n",
- "SVM (unscaled) RMSE: 244.905889\n",
- "SVM (unscaled) MAE: 201.512778\n",
- "SVM (unscaled) MAEP: 0.215932\n",
- "SVM (unscaled) MBE: -14.511767\n",
- "SVM (unscaled) MBEP: -0.084692\n",
- "SVM (unscaled) R2: 0.021746\n",
- "Crossvalidation time: 10.869s\n",
- "SVM (scaled) MSE: 22623.887531\n",
- "SVM (scaled) RMSE: 150.412392\n",
- "SVM (scaled) MAE: 111.792388\n",
- "SVM (scaled) MAEP: 0.126747\n",
- "SVM (scaled) MBE: -11.389050\n",
- "SVM (scaled) MBEP: -0.050423\n",
- "SVM (scaled) R2: 0.631005\n",
- "Crossvalidation time: 10.877s\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11103.099060\n",
+ "SVM (scaled) RMSE: 105.371244\n",
+ "SVM (scaled) MAE: 64.327001\n",
+ "SVM (scaled) MAEP: 0.081441\n",
+ "SVM (scaled) MBE: -12.082502\n",
+ "SVM (scaled) MBEP: -0.038945\n",
+ "SVM (scaled) R2: 0.824943\n",
+ "Crossvalidation time: 22.483s\n",
"\n",
"SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 16002.534898\n",
+ "SVM (scaled) RMSE: 126.501126\n",
+ "SVM (scaled) MAE: 87.091312\n",
+ "SVM (scaled) MAEP: 0.105966\n",
+ "SVM (scaled) MBE: -10.789220\n",
+ "SVM (scaled) MBEP: -0.045364\n",
+ "SVM (scaled) R2: 0.747696\n",
+ "Crossvalidation time: 18.660s\n",
"\n",
+ "SVM C = 5.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 57027.433679\n",
- "SVM (unscaled) RMSE: 238.804174\n",
- "SVM (unscaled) MAE: 196.552703\n",
- "SVM (unscaled) MAEP: 0.211139\n",
- "SVM (unscaled) MBE: -14.919381\n",
- "SVM (unscaled) MBEP: -0.083521\n",
- "SVM (unscaled) R2: 0.069884\n",
- "Crossvalidation time: 10.640s\n",
- "SVM (unscaled) MSE: 57838.471824\n",
- "SVM (unscaled) RMSE: 240.496303\n",
- "SVM (unscaled) MAE: 197.561252\n",
- "SVM (unscaled) MAEP: 0.211871\n",
- "SVM (unscaled) MBE: -13.556971\n",
- "SVM (unscaled) MBEP: -0.082739\n",
- "SVM (unscaled) R2: 0.056656\n",
- "Crossvalidation time: 11.192s\n",
- "SVM (scaled) MSE: 21896.345326\n",
- "SVM (scaled) RMSE: 147.974137\n",
- "SVM (scaled) MAE: 109.039236\n",
- "SVM (scaled) MAEP: 0.124304\n",
- "SVM (scaled) MBE: -11.341553\n",
- "SVM (scaled) MBEP: -0.047692\n",
- "SVM (scaled) R2: 0.642871\n",
- "Crossvalidation time: 11.964s\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 12319.303118\n",
+ "SVM (scaled) RMSE: 110.992356\n",
+ "SVM (scaled) MAE: 70.486338\n",
+ "SVM (scaled) MAEP: 0.088253\n",
+ "SVM (scaled) MBE: -10.934226\n",
+ "SVM (scaled) MBEP: -0.040516\n",
+ "SVM (scaled) R2: 0.805767\n",
+ "Crossvalidation time: 18.500s\n",
"\n",
- "SVM C = 10.000000\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11287.069099\n",
+ "SVM (scaled) RMSE: 106.240619\n",
+ "SVM (scaled) MAE: 65.350242\n",
+ "SVM (scaled) MAEP: 0.082644\n",
+ "SVM (scaled) MBE: -12.069043\n",
+ "SVM (scaled) MBEP: -0.039582\n",
+ "SVM (scaled) R2: 0.822042\n",
+ "Crossvalidation time: 19.377s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11144.603683\n",
+ "SVM (scaled) RMSE: 105.568005\n",
+ "SVM (scaled) MAE: 64.766358\n",
+ "SVM (scaled) MAEP: 0.081941\n",
+ "SVM (scaled) MBE: -12.425626\n",
+ "SVM (scaled) MBEP: -0.039652\n",
+ "SVM (scaled) R2: 0.824288\n",
+ "Crossvalidation time: 19.703s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 11015.898955\n",
+ "SVM (scaled) RMSE: 104.956653\n",
+ "SVM (scaled) MAE: 64.415911\n",
+ "SVM (scaled) MAEP: 0.081412\n",
+ "SVM (scaled) MBE: -12.371081\n",
+ "SVM (scaled) MBEP: -0.039261\n",
+ "SVM (scaled) R2: 0.826318\n",
+ "Crossvalidation time: 19.494s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10853.234413\n",
+ "SVM (scaled) RMSE: 104.178858\n",
+ "SVM (scaled) MAE: 63.757718\n",
+ "SVM (scaled) MAEP: 0.080568\n",
+ "SVM (scaled) MBE: -12.265108\n",
+ "SVM (scaled) MBEP: -0.038787\n",
+ "SVM (scaled) R2: 0.828882\n",
+ "Crossvalidation time: 20.875s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10978.580340\n",
+ "SVM (scaled) RMSE: 104.778721\n",
+ "SVM (scaled) MAE: 63.978085\n",
+ "SVM (scaled) MAEP: 0.080825\n",
+ "SVM (scaled) MBE: -12.291847\n",
+ "SVM (scaled) MBEP: -0.038792\n",
+ "SVM (scaled) R2: 0.826906\n",
+ "Crossvalidation time: 24.319s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11081.028008\n",
+ "SVM (scaled) RMSE: 105.266462\n",
+ "SVM (scaled) MAE: 64.200320\n",
+ "SVM (scaled) MAEP: 0.081169\n",
+ "SVM (scaled) MBE: -12.081926\n",
+ "SVM (scaled) MBEP: -0.038681\n",
+ "SVM (scaled) R2: 0.825291\n",
+ "Crossvalidation time: 25.846s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11330.884157\n",
+ "SVM (scaled) RMSE: 106.446626\n",
+ "SVM (scaled) MAE: 64.902558\n",
+ "SVM (scaled) MAEP: 0.082015\n",
+ "SVM (scaled) MBE: -11.788053\n",
+ "SVM (scaled) MBEP: -0.038528\n",
+ "SVM (scaled) R2: 0.821351\n",
+ "Crossvalidation time: 28.581s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 14934.388753\n",
+ "SVM (scaled) RMSE: 122.206337\n",
+ "SVM (scaled) MAE: 83.043542\n",
+ "SVM (scaled) MAEP: 0.101501\n",
+ "SVM (scaled) MBE: -10.289837\n",
+ "SVM (scaled) MBEP: -0.043728\n",
+ "SVM (scaled) R2: 0.764537\n",
+ "Crossvalidation time: 18.738s\n",
"\n",
+ "SVM C = 7.000000\n",
"SVM epsilon = 0.010000\n",
- "SVM (unscaled) MSE: 53578.587197\n",
- "SVM (unscaled) RMSE: 231.470489\n",
- "SVM (unscaled) MAE: 190.215329\n",
- "SVM (unscaled) MAEP: 0.204701\n",
- "SVM (unscaled) MBE: -13.965112\n",
- "SVM (unscaled) MBEP: -0.080750\n",
- "SVM (unscaled) R2: 0.126135\n",
- "Crossvalidation time: 11.559s\n",
- "SVM (unscaled) MSE: 54562.804033\n",
- "SVM (unscaled) RMSE: 233.586823\n",
- "SVM (unscaled) MAE: 191.321378\n",
- "SVM (unscaled) MAEP: 0.205600\n",
- "SVM (unscaled) MBE: -12.835586\n",
- "SVM (unscaled) MBEP: -0.080377\n",
- "SVM (unscaled) R2: 0.110082\n",
- "Crossvalidation time: 12.119s\n",
- "SVM (scaled) MSE: 21708.055177\n",
- "SVM (scaled) RMSE: 147.336537\n",
- "SVM (scaled) MAE: 108.228000\n",
- "SVM (scaled) MAEP: 0.123669\n",
- "SVM (scaled) MBE: -11.471268\n",
- "SVM (scaled) MBEP: -0.046681\n",
- "SVM (scaled) R2: 0.645942\n",
- "Crossvalidation time: 13.172s\n"
+ "SVM gamma = 20.000000\n"
]
- }
- ],
- "source": [
- "name = 'SVM'\n",
- "svm_tuning = pd.DataFrame(data = [], columns = ['unscaled', 'unscaled_target', 'scaled_target'])\n",
- "\n",
- "SVM_epsilon = 0.01\n",
- "for C in [0.1, 0.2, 0.5, 1, 2, 5, 10]:\n",
- " print('\\nSVM C = %f' %C)\n",
- " print('\\nSVM epsilon = %f' %SVM_epsilon)\n",
- " tt = time.time()\n",
- "\n",
- " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = 'scale')\n",
- " Y = cross_val_predict(est, X, T, cv = 5)\n",
- " ununscaled_err = get_errors( shp(T), shp(Y), 'SVM (unscaled)' )\n",
- " \n",
- " print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
- " tt = time.time()\n",
- "\n",
- " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = 'scale')\n",
- " Y = cross_val_predict(est, x, T, cv = 5)\n",
- " unscaled_err = get_errors( shp(T), shp(Y), 'SVM (unscaled)' )\n",
- " \n",
- " print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
- " tt = time.time()\n",
- " \n",
- " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = 'scale')\n",
- " y = cross_val_predict(est, x, t, cv = 5)\n",
- " Y = rescale(y, T)\n",
- " scaled_err = get_errors( shp(T), shp(Y), 'SVM (scaled)' )\n",
- " \n",
- " print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
- " \n",
- " svm_tuning = svm_tuning.append( pd.DataFrame(data = [[ununscaled_err.RMSE, unscaled_err.RMSE, scaled_err.RMSE]], \n",
- " columns = ['unscaled', 'unscaled_target', 'scaled_target'], \n",
- " index = [C]) )"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {},
- "outputs": [
+ },
{
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>unscaled</th>\n",
- " <th>unscaled_target</th>\n",
- " <th>scaled_target</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0.1</th>\n",
- " <td>247.865813</td>\n",
- " <td>247.933048</td>\n",
- " <td>216.000682</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>0.2</th>\n",
- " <td>247.642499</td>\n",
- " <td>247.773033</td>\n",
- " <td>194.446270</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>0.5</th>\n",
- " <td>246.957192</td>\n",
- " <td>247.275723</td>\n",
- " <td>167.589291</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1.0</th>\n",
- " <td>245.878745</td>\n",
- " <td>246.446937</td>\n",
- " <td>155.871316</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2.0</th>\n",
- " <td>243.899368</td>\n",
- " <td>244.907860</td>\n",
- " <td>150.359435</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5.0</th>\n",
- " <td>238.804532</td>\n",
- " <td>240.496598</td>\n",
- " <td>147.968116</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10.0</th>\n",
- " <td>231.471496</td>\n",
- " <td>233.585816</td>\n",
- " <td>147.285781</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "SVM (scaled) MSE: 12129.669095\n",
+ "SVM (scaled) RMSE: 110.134777\n",
+ "SVM (scaled) MAE: 69.492688\n",
+ "SVM (scaled) MAEP: 0.087226\n",
+ "SVM (scaled) MBE: -11.037482\n",
+ "SVM (scaled) MBEP: -0.040086\n",
+ "SVM (scaled) R2: 0.808757\n",
+ "Crossvalidation time: 18.214s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11236.100437\n",
+ "SVM (scaled) RMSE: 106.000474\n",
+ "SVM (scaled) MAE: 65.136989\n",
+ "SVM (scaled) MAEP: 0.082355\n",
+ "SVM (scaled) MBE: -12.159941\n",
+ "SVM (scaled) MBEP: -0.039473\n",
+ "SVM (scaled) R2: 0.822846\n",
+ "Crossvalidation time: 19.684s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11108.120925\n",
+ "SVM (scaled) RMSE: 105.395071\n",
+ "SVM (scaled) MAE: 64.667407\n",
+ "SVM (scaled) MAEP: 0.081771\n",
+ "SVM (scaled) MBE: -12.378668\n",
+ "SVM (scaled) MBEP: -0.039448\n",
+ "SVM (scaled) R2: 0.824864\n",
+ "Crossvalidation time: 19.683s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10989.908051\n",
+ "SVM (scaled) RMSE: 104.832762\n",
+ "SVM (scaled) MAE: 64.336489\n",
+ "SVM (scaled) MAEP: 0.081255\n",
+ "SVM (scaled) MBE: -12.301090\n",
+ "SVM (scaled) MBEP: -0.039055\n",
+ "SVM (scaled) R2: 0.826727\n",
+ "Crossvalidation time: 20.913s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10855.952581\n",
+ "SVM (scaled) RMSE: 104.191903\n",
+ "SVM (scaled) MAE: 63.750920\n",
+ "SVM (scaled) MAEP: 0.080572\n",
+ "SVM (scaled) MBE: -12.381558\n",
+ "SVM (scaled) MBEP: -0.038849\n",
+ "SVM (scaled) R2: 0.828839\n",
+ "Crossvalidation time: 21.698s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11006.280387\n",
+ "SVM (scaled) RMSE: 104.910821\n",
+ "SVM (scaled) MAE: 64.039671\n",
+ "SVM (scaled) MAEP: 0.080897\n",
+ "SVM (scaled) MBE: -12.190828\n",
+ "SVM (scaled) MBEP: -0.038677\n",
+ "SVM (scaled) R2: 0.826469\n",
+ "Crossvalidation time: 25.777s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11152.615175\n",
+ "SVM (scaled) RMSE: 105.605943\n",
+ "SVM (scaled) MAE: 64.374199\n",
+ "SVM (scaled) MAEP: 0.081394\n",
+ "SVM (scaled) MBE: -12.002048\n",
+ "SVM (scaled) MBEP: -0.038617\n",
+ "SVM (scaled) R2: 0.824162\n",
+ "Crossvalidation time: 28.799s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11464.371474\n",
+ "SVM (scaled) RMSE: 107.071805\n",
+ "SVM (scaled) MAE: 65.272678\n",
+ "SVM (scaled) MAEP: 0.082381\n",
+ "SVM (scaled) MBE: -11.589083\n",
+ "SVM (scaled) MBEP: -0.038318\n",
+ "SVM (scaled) R2: 0.819247\n",
+ "Crossvalidation time: 31.566s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 13978.946492\n",
+ "SVM (scaled) RMSE: 118.232595\n",
+ "SVM (scaled) MAE: 78.952758\n",
+ "SVM (scaled) MAEP: 0.097091\n",
+ "SVM (scaled) MBE: -10.224882\n",
+ "SVM (scaled) MBEP: -0.042507\n",
+ "SVM (scaled) R2: 0.779601\n",
+ "Crossvalidation time: 19.067s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11983.580063\n",
+ "SVM (scaled) RMSE: 109.469539\n",
+ "SVM (scaled) MAE: 68.722585\n",
+ "SVM (scaled) MAEP: 0.086436\n",
+ "SVM (scaled) MBE: -11.029818\n",
+ "SVM (scaled) MBEP: -0.039606\n",
+ "SVM (scaled) R2: 0.811061\n",
+ "Crossvalidation time: 19.229s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11193.517967\n",
+ "SVM (scaled) RMSE: 105.799423\n",
+ "SVM (scaled) MAE: 64.941255\n",
+ "SVM (scaled) MAEP: 0.082122\n",
+ "SVM (scaled) MBE: -12.328501\n",
+ "SVM (scaled) MBEP: -0.039508\n",
+ "SVM (scaled) R2: 0.823517\n",
+ "Crossvalidation time: 19.750s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11077.825807\n",
+ "SVM (scaled) RMSE: 105.251251\n",
+ "SVM (scaled) MAE: 64.586028\n",
+ "SVM (scaled) MAEP: 0.081621\n",
+ "SVM (scaled) MBE: -12.278741\n",
+ "SVM (scaled) MBEP: -0.039219\n",
+ "SVM (scaled) R2: 0.825341\n",
+ "Crossvalidation time: 20.556s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10955.084874\n",
+ "SVM (scaled) RMSE: 104.666541\n",
+ "SVM (scaled) MAE: 64.226135\n",
+ "SVM (scaled) MAEP: 0.081062\n",
+ "SVM (scaled) MBE: -12.097474\n",
+ "SVM (scaled) MBEP: -0.038725\n",
+ "SVM (scaled) R2: 0.827276\n",
+ "Crossvalidation time: 21.428s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10858.283754\n",
+ "SVM (scaled) RMSE: 104.203089\n",
+ "SVM (scaled) MAE: 63.731179\n",
+ "SVM (scaled) MAEP: 0.080561\n",
+ "SVM (scaled) MBE: -12.401180\n",
+ "SVM (scaled) MBEP: -0.038840\n",
+ "SVM (scaled) R2: 0.828803\n",
+ "Crossvalidation time: 23.484s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11046.318140\n",
+ "SVM (scaled) RMSE: 105.101466\n",
+ "SVM (scaled) MAE: 64.130753\n",
+ "SVM (scaled) MAEP: 0.081025\n",
+ "SVM (scaled) MBE: -12.141699\n",
+ "SVM (scaled) MBEP: -0.038638\n",
+ "SVM (scaled) R2: 0.825838\n",
+ "Crossvalidation time: 29.802s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11246.886531\n",
+ "SVM (scaled) RMSE: 106.051339\n",
+ "SVM (scaled) MAE: 64.627563\n",
+ "SVM (scaled) MAEP: 0.081683\n",
+ "SVM (scaled) MBE: -11.894048\n",
+ "SVM (scaled) MBEP: -0.038507\n",
+ "SVM (scaled) R2: 0.822676\n",
+ "Crossvalidation time: 32.396s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11634.989322\n",
+ "SVM (scaled) RMSE: 107.865608\n",
+ "SVM (scaled) MAE: 65.722988\n",
+ "SVM (scaled) MAEP: 0.082859\n",
+ "SVM (scaled) MBE: -11.392820\n",
+ "SVM (scaled) MBEP: -0.038101\n",
+ "SVM (scaled) R2: 0.816557\n",
+ "Crossvalidation time: 38.182s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12839.277351\n",
+ "SVM (scaled) RMSE: 113.310535\n",
+ "SVM (scaled) MAE: 73.470565\n",
+ "SVM (scaled) MAEP: 0.091257\n",
+ "SVM (scaled) MBE: -10.021826\n",
+ "SVM (scaled) MBEP: -0.040412\n",
+ "SVM (scaled) R2: 0.797569\n",
+ "Crossvalidation time: 19.364s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11778.742220\n",
+ "SVM (scaled) RMSE: 108.529914\n",
+ "SVM (scaled) MAE: 67.704185\n",
+ "SVM (scaled) MAEP: 0.085323\n",
+ "SVM (scaled) MBE: -11.054244\n",
+ "SVM (scaled) MBEP: -0.038931\n",
+ "SVM (scaled) R2: 0.814290\n",
+ "Crossvalidation time: 20.162s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11131.443253\n",
+ "SVM (scaled) RMSE: 105.505655\n",
+ "SVM (scaled) MAE: 64.736145\n",
+ "SVM (scaled) MAEP: 0.081800\n",
+ "SVM (scaled) MBE: -12.242910\n",
+ "SVM (scaled) MBEP: -0.039162\n",
+ "SVM (scaled) R2: 0.824496\n",
+ "Crossvalidation time: 22.115s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11029.249914\n",
+ "SVM (scaled) RMSE: 105.020236\n",
+ "SVM (scaled) MAE: 64.446006\n",
+ "SVM (scaled) MAEP: 0.081392\n",
+ "SVM (scaled) MBE: -12.148036\n",
+ "SVM (scaled) MBEP: -0.038886\n",
+ "SVM (scaled) R2: 0.826107\n",
+ "Crossvalidation time: 22.964s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10908.798791\n",
+ "SVM (scaled) RMSE: 104.445195\n",
+ "SVM (scaled) MAE: 64.032250\n",
+ "SVM (scaled) MAEP: 0.080822\n",
+ "SVM (scaled) MBE: -12.037425\n",
+ "SVM (scaled) MBEP: -0.038448\n",
+ "SVM (scaled) R2: 0.828006\n",
+ "Crossvalidation time: 24.270s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10888.380165\n",
+ "SVM (scaled) RMSE: 104.347401\n",
+ "SVM (scaled) MAE: 63.787025\n",
+ "SVM (scaled) MAEP: 0.080645\n",
+ "SVM (scaled) MBE: -12.434495\n",
+ "SVM (scaled) MBEP: -0.038844\n",
+ "SVM (scaled) R2: 0.828328\n",
+ "Crossvalidation time: 29.165s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11158.060278\n",
+ "SVM (scaled) RMSE: 105.631720\n",
+ "SVM (scaled) MAE: 64.403732\n",
+ "SVM (scaled) MAEP: 0.081389\n",
+ "SVM (scaled) MBE: -12.060488\n",
+ "SVM (scaled) MBEP: -0.038552\n",
+ "SVM (scaled) R2: 0.824076\n",
+ "Crossvalidation time: 40.546s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11497.285254\n",
+ "SVM (scaled) RMSE: 107.225395\n",
+ "SVM (scaled) MAE: 65.276674\n",
+ "SVM (scaled) MAEP: 0.082410\n",
+ "SVM (scaled) MBE: -11.727694\n",
+ "SVM (scaled) MBEP: -0.038319\n",
+ "SVM (scaled) R2: 0.818728\n",
+ "Crossvalidation time: 46.880s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 12041.443113\n",
+ "SVM (scaled) RMSE: 109.733510\n",
+ "SVM (scaled) MAE: 66.721403\n",
+ "SVM (scaled) MAEP: 0.083979\n",
+ "SVM (scaled) MBE: -11.108474\n",
+ "SVM (scaled) MBEP: -0.037808\n",
+ "SVM (scaled) R2: 0.810148\n",
+ "Crossvalidation time: 57.166s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12251.971792\n",
+ "SVM (scaled) RMSE: 110.688625\n",
+ "SVM (scaled) MAE: 70.204238\n",
+ "SVM (scaled) MAEP: 0.087902\n",
+ "SVM (scaled) MBE: -10.151526\n",
+ "SVM (scaled) MBEP: -0.038844\n",
+ "SVM (scaled) R2: 0.806829\n",
+ "Crossvalidation time: 21.472s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11549.455450\n",
+ "SVM (scaled) RMSE: 107.468393\n",
+ "SVM (scaled) MAE: 66.610685\n",
+ "SVM (scaled) MAEP: 0.084034\n",
+ "SVM (scaled) MBE: -11.031012\n",
+ "SVM (scaled) MBEP: -0.038309\n",
+ "SVM (scaled) R2: 0.817905\n",
+ "Crossvalidation time: 23.061s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "SVM (scaled) MSE: 11072.473790\n",
+ "SVM (scaled) RMSE: 105.225823\n",
+ "SVM (scaled) MAE: 64.577883\n",
+ "SVM (scaled) MAEP: 0.081607\n",
+ "SVM (scaled) MBE: -12.073269\n",
+ "SVM (scaled) MBEP: -0.038799\n",
+ "SVM (scaled) R2: 0.825426\n",
+ "Crossvalidation time: 26.658s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10957.190941\n",
+ "SVM (scaled) RMSE: 104.676602\n",
+ "SVM (scaled) MAE: 64.194169\n",
+ "SVM (scaled) MAEP: 0.081061\n",
+ "SVM (scaled) MBE: -11.952395\n",
+ "SVM (scaled) MBEP: -0.038376\n",
+ "SVM (scaled) R2: 0.827243\n",
+ "Crossvalidation time: 31.174s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10873.860407\n",
+ "SVM (scaled) RMSE: 104.277804\n",
+ "SVM (scaled) MAE: 63.886807\n",
+ "SVM (scaled) MAEP: 0.080758\n",
+ "SVM (scaled) MBE: -12.265702\n",
+ "SVM (scaled) MBEP: -0.038585\n",
+ "SVM (scaled) R2: 0.828557\n",
+ "Crossvalidation time: 34.215s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10964.361763\n",
+ "SVM (scaled) RMSE: 104.710848\n",
+ "SVM (scaled) MAE: 64.014650\n",
+ "SVM (scaled) MAEP: 0.080886\n",
+ "SVM (scaled) MBE: -12.420074\n",
+ "SVM (scaled) MBEP: -0.038763\n",
+ "SVM (scaled) R2: 0.827130\n",
+ "Crossvalidation time: 43.657s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11446.444435\n",
+ "SVM (scaled) RMSE: 106.988057\n",
+ "SVM (scaled) MAE: 65.126017\n",
+ "SVM (scaled) MAEP: 0.082268\n",
+ "SVM (scaled) MBE: -11.749879\n",
+ "SVM (scaled) MBEP: -0.038284\n",
+ "SVM (scaled) R2: 0.819529\n",
+ "Crossvalidation time: 71.328s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11985.079385\n",
+ "SVM (scaled) RMSE: 109.476387\n",
+ "SVM (scaled) MAE: 66.445264\n",
+ "SVM (scaled) MAEP: 0.083813\n",
+ "SVM (scaled) MBE: -11.330979\n",
+ "SVM (scaled) MBEP: -0.038016\n",
+ "SVM (scaled) R2: 0.811037\n",
+ "Crossvalidation time: 91.222s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 12866.107143\n",
+ "SVM (scaled) RMSE: 113.428864\n",
+ "SVM (scaled) MAE: 68.295084\n",
+ "SVM (scaled) MAEP: 0.085836\n",
+ "SVM (scaled) MBE: -10.607349\n",
+ "SVM (scaled) MBEP: -0.037510\n",
+ "SVM (scaled) R2: 0.797146\n",
+ "Crossvalidation time: 117.494s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12160.727321\n",
+ "SVM (scaled) RMSE: 110.275688\n",
+ "SVM (scaled) MAE: 69.625884\n",
+ "SVM (scaled) MAEP: 0.087366\n",
+ "SVM (scaled) MBE: -10.264861\n",
+ "SVM (scaled) MBEP: -0.038562\n",
+ "SVM (scaled) R2: 0.808268\n",
+ "Crossvalidation time: 24.074s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11468.539386\n",
+ "SVM (scaled) RMSE: 107.091267\n",
+ "SVM (scaled) MAE: 66.233570\n",
+ "SVM (scaled) MAEP: 0.083585\n",
+ "SVM (scaled) MBE: -11.107879\n",
+ "SVM (scaled) MBEP: -0.038277\n",
+ "SVM (scaled) R2: 0.819181\n",
+ "Crossvalidation time: 25.995s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11053.431671\n",
+ "SVM (scaled) RMSE: 105.135302\n",
+ "SVM (scaled) MAE: 64.525303\n",
+ "SVM (scaled) MAEP: 0.081530\n",
+ "SVM (scaled) MBE: -12.013512\n",
+ "SVM (scaled) MBEP: -0.038628\n",
+ "SVM (scaled) R2: 0.825726\n",
+ "Crossvalidation time: 31.432s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10931.674136\n",
+ "SVM (scaled) RMSE: 104.554647\n",
+ "SVM (scaled) MAE: 64.085255\n",
+ "SVM (scaled) MAEP: 0.080940\n",
+ "SVM (scaled) MBE: -11.974629\n",
+ "SVM (scaled) MBEP: -0.038337\n",
+ "SVM (scaled) R2: 0.827645\n",
+ "Crossvalidation time: 35.203s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10861.833773\n",
+ "SVM (scaled) RMSE: 104.220122\n",
+ "SVM (scaled) MAE: 63.840338\n",
+ "SVM (scaled) MAEP: 0.080723\n",
+ "SVM (scaled) MBE: -12.309372\n",
+ "SVM (scaled) MBEP: -0.038604\n",
+ "SVM (scaled) R2: 0.828747\n",
+ "Crossvalidation time: 40.663s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10986.631860\n",
+ "SVM (scaled) RMSE: 104.817135\n",
+ "SVM (scaled) MAE: 64.085593\n",
+ "SVM (scaled) MAEP: 0.080942\n",
+ "SVM (scaled) MBE: -12.357526\n",
+ "SVM (scaled) MBEP: -0.038685\n",
+ "SVM (scaled) R2: 0.826779\n",
+ "Crossvalidation time: 54.250s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11582.323742\n",
+ "SVM (scaled) RMSE: 107.621205\n",
+ "SVM (scaled) MAE: 65.446652\n",
+ "SVM (scaled) MAEP: 0.082679\n",
+ "SVM (scaled) MBE: -11.629362\n",
+ "SVM (scaled) MBEP: -0.038228\n",
+ "SVM (scaled) R2: 0.817387\n",
+ "Crossvalidation time: 89.637s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 12204.182541\n",
+ "SVM (scaled) RMSE: 110.472542\n",
+ "SVM (scaled) MAE: 66.920293\n",
+ "SVM (scaled) MAEP: 0.084390\n",
+ "SVM (scaled) MBE: -11.241513\n",
+ "SVM (scaled) MBEP: -0.037934\n",
+ "SVM (scaled) R2: 0.807582\n",
+ "Crossvalidation time: 115.106s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 13317.619253\n",
+ "SVM (scaled) RMSE: 115.401990\n",
+ "SVM (scaled) MAE: 69.094689\n",
+ "SVM (scaled) MAEP: 0.086857\n",
+ "SVM (scaled) MBE: -10.302672\n",
+ "SVM (scaled) MBEP: -0.037346\n",
+ "SVM (scaled) R2: 0.790027\n",
+ "Crossvalidation time: 156.138s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12084.074446\n",
+ "SVM (scaled) RMSE: 109.927587\n",
+ "SVM (scaled) MAE: 69.117692\n",
+ "SVM (scaled) MAEP: 0.086875\n",
+ "SVM (scaled) MBE: -10.537588\n",
+ "SVM (scaled) MBEP: -0.038451\n",
+ "SVM (scaled) R2: 0.809476\n",
+ "Crossvalidation time: 24.476s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11392.699653\n",
+ "SVM (scaled) RMSE: 106.736590\n",
+ "SVM (scaled) MAE: 65.897491\n",
+ "SVM (scaled) MAEP: 0.083195\n",
+ "SVM (scaled) MBE: -11.207495\n",
+ "SVM (scaled) MBEP: -0.038285\n",
+ "SVM (scaled) R2: 0.820377\n",
+ "Crossvalidation time: 28.507s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11025.459373\n",
+ "SVM (scaled) RMSE: 105.002187\n",
+ "SVM (scaled) MAE: 64.427025\n",
+ "SVM (scaled) MAEP: 0.081386\n",
+ "SVM (scaled) MBE: -12.015131\n",
+ "SVM (scaled) MBEP: -0.038515\n",
+ "SVM (scaled) R2: 0.826167\n",
+ "Crossvalidation time: 35.904s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10912.187161\n",
+ "SVM (scaled) RMSE: 104.461415\n",
+ "SVM (scaled) MAE: 64.001477\n",
+ "SVM (scaled) MAEP: 0.080868\n",
+ "SVM (scaled) MBE: -12.029018\n",
+ "SVM (scaled) MBEP: -0.038345\n",
+ "SVM (scaled) R2: 0.827953\n",
+ "Crossvalidation time: 40.844s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10854.523489\n",
+ "SVM (scaled) RMSE: 104.185044\n",
+ "SVM (scaled) MAE: 63.838218\n",
+ "SVM (scaled) MAEP: 0.080730\n",
+ "SVM (scaled) MBE: -12.348117\n",
+ "SVM (scaled) MBEP: -0.038628\n",
+ "SVM (scaled) R2: 0.828862\n",
+ "Crossvalidation time: 48.681s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 11014.925217\n",
+ "SVM (scaled) RMSE: 104.952014\n",
+ "SVM (scaled) MAE: 64.177831\n",
+ "SVM (scaled) MAEP: 0.081015\n",
+ "SVM (scaled) MBE: -12.299085\n",
+ "SVM (scaled) MBEP: -0.038619\n",
+ "SVM (scaled) R2: 0.826333\n",
+ "Crossvalidation time: 69.666s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11764.177295\n",
+ "SVM (scaled) RMSE: 108.462792\n",
+ "SVM (scaled) MAE: 65.851721\n",
+ "SVM (scaled) MAEP: 0.083256\n",
+ "SVM (scaled) MBE: -11.554232\n",
+ "SVM (scaled) MBEP: -0.038241\n",
+ "SVM (scaled) R2: 0.814520\n",
+ "Crossvalidation time: 130.173s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 12518.522405\n",
+ "SVM (scaled) RMSE: 111.886203\n",
+ "SVM (scaled) MAE: 67.472509\n",
+ "SVM (scaled) MAEP: 0.085078\n",
+ "SVM (scaled) MBE: -11.113887\n",
+ "SVM (scaled) MBEP: -0.037828\n",
+ "SVM (scaled) R2: 0.802626\n",
+ "Crossvalidation time: 159.096s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.010000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 13849.084554\n",
+ "SVM (scaled) RMSE: 117.682134\n",
+ "SVM (scaled) MAE: 69.977586\n",
+ "SVM (scaled) MAEP: 0.088176\n",
+ "SVM (scaled) MBE: -10.171039\n",
+ "SVM (scaled) MBEP: -0.037506\n",
+ "SVM (scaled) R2: 0.781648\n",
+ "Crossvalidation time: 231.256s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 20307.024475\n",
+ "SVM (scaled) RMSE: 142.502717\n",
+ "SVM (scaled) MAE: 100.961641\n",
+ "SVM (scaled) MAEP: 0.121548\n",
+ "SVM (scaled) MBE: -13.753743\n",
+ "SVM (scaled) MBEP: -0.051787\n",
+ "SVM (scaled) R2: 0.679829\n",
+ "Crossvalidation time: 15.881s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 15249.697176\n",
+ "SVM (scaled) RMSE: 123.489664\n",
+ "SVM (scaled) MAE: 83.875305\n",
+ "SVM (scaled) MAEP: 0.102811\n",
+ "SVM (scaled) MBE: -11.161683\n",
+ "SVM (scaled) MBEP: -0.045482\n",
+ "SVM (scaled) R2: 0.759565\n",
+ "Crossvalidation time: 15.070s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11742.052590\n",
+ "SVM (scaled) RMSE: 108.360752\n",
+ "SVM (scaled) MAE: 67.649580\n",
+ "SVM (scaled) MAEP: 0.085307\n",
+ "SVM (scaled) MBE: -10.884603\n",
+ "SVM (scaled) MBEP: -0.040064\n",
+ "SVM (scaled) R2: 0.814869\n",
+ "Crossvalidation time: 13.338s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "SVM (scaled) MSE: 11392.317593\n",
+ "SVM (scaled) RMSE: 106.734800\n",
+ "SVM (scaled) MAE: 65.960555\n",
+ "SVM (scaled) MAEP: 0.083441\n",
+ "SVM (scaled) MBE: -11.023122\n",
+ "SVM (scaled) MBEP: -0.039429\n",
+ "SVM (scaled) R2: 0.820383\n",
+ "Crossvalidation time: 13.075s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 11167.089480\n",
+ "SVM (scaled) RMSE: 105.674450\n",
+ "SVM (scaled) MAE: 65.076427\n",
+ "SVM (scaled) MAEP: 0.082439\n",
+ "SVM (scaled) MBE: -10.864001\n",
+ "SVM (scaled) MBEP: -0.038811\n",
+ "SVM (scaled) R2: 0.823934\n",
+ "Crossvalidation time: 13.103s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10895.791177\n",
+ "SVM (scaled) RMSE: 104.382907\n",
+ "SVM (scaled) MAE: 64.229407\n",
+ "SVM (scaled) MAEP: 0.081368\n",
+ "SVM (scaled) MBE: -10.577629\n",
+ "SVM (scaled) MBEP: -0.038022\n",
+ "SVM (scaled) R2: 0.828211\n",
+ "Crossvalidation time: 13.561s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10785.526112\n",
+ "SVM (scaled) RMSE: 103.853388\n",
+ "SVM (scaled) MAE: 63.778495\n",
+ "SVM (scaled) MAEP: 0.080803\n",
+ "SVM (scaled) MBE: -10.159342\n",
+ "SVM (scaled) MBEP: -0.037292\n",
+ "SVM (scaled) R2: 0.829950\n",
+ "Crossvalidation time: 13.907s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 10837.105742\n",
+ "SVM (scaled) RMSE: 104.101420\n",
+ "SVM (scaled) MAE: 63.862487\n",
+ "SVM (scaled) MAEP: 0.080983\n",
+ "SVM (scaled) MBE: -10.068455\n",
+ "SVM (scaled) MBEP: -0.037273\n",
+ "SVM (scaled) R2: 0.829136\n",
+ "Crossvalidation time: 14.675s\n",
+ "\n",
+ "SVM C = 1.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 10913.378448\n",
+ "SVM (scaled) RMSE: 104.467117\n",
+ "SVM (scaled) MAE: 63.955915\n",
+ "SVM (scaled) MAEP: 0.081242\n",
+ "SVM (scaled) MBE: -10.017158\n",
+ "SVM (scaled) MBEP: -0.037402\n",
+ "SVM (scaled) R2: 0.827934\n",
+ "Crossvalidation time: 14.865s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 18817.899665\n",
+ "SVM (scaled) RMSE: 137.178350\n",
+ "SVM (scaled) MAE: 96.554790\n",
+ "SVM (scaled) MAEP: 0.116435\n",
+ "SVM (scaled) MBE: -12.515686\n",
+ "SVM (scaled) MBEP: -0.049219\n",
+ "SVM (scaled) R2: 0.703307\n",
+ "Crossvalidation time: 16.645s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 13479.311195\n",
+ "SVM (scaled) RMSE: 116.100436\n",
+ "SVM (scaled) MAE: 76.363951\n",
+ "SVM (scaled) MAEP: 0.094553\n",
+ "SVM (scaled) MBE: -10.601742\n",
+ "SVM (scaled) MBEP: -0.042722\n",
+ "SVM (scaled) R2: 0.787478\n",
+ "Crossvalidation time: 15.034s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11469.134439\n",
+ "SVM (scaled) RMSE: 107.094045\n",
+ "SVM (scaled) MAE: 66.347006\n",
+ "SVM (scaled) MAEP: 0.083805\n",
+ "SVM (scaled) MBE: -10.917051\n",
+ "SVM (scaled) MBEP: -0.039176\n",
+ "SVM (scaled) R2: 0.819172\n",
+ "Crossvalidation time: 13.836s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11227.511855\n",
+ "SVM (scaled) RMSE: 105.959954\n",
+ "SVM (scaled) MAE: 65.283961\n",
+ "SVM (scaled) MAEP: 0.082599\n",
+ "SVM (scaled) MBE: -10.928408\n",
+ "SVM (scaled) MBEP: -0.038713\n",
+ "SVM (scaled) R2: 0.822981\n",
+ "Crossvalidation time: 14.242s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 11040.780735\n",
+ "SVM (scaled) RMSE: 105.075119\n",
+ "SVM (scaled) MAE: 64.669223\n",
+ "SVM (scaled) MAEP: 0.081825\n",
+ "SVM (scaled) MBE: -10.622488\n",
+ "SVM (scaled) MBEP: -0.038138\n",
+ "SVM (scaled) R2: 0.825925\n",
+ "Crossvalidation time: 13.922s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10828.114008\n",
+ "SVM (scaled) RMSE: 104.058224\n",
+ "SVM (scaled) MAE: 63.966787\n",
+ "SVM (scaled) MAEP: 0.080962\n",
+ "SVM (scaled) MBE: -10.518345\n",
+ "SVM (scaled) MBEP: -0.037607\n",
+ "SVM (scaled) R2: 0.829278\n",
+ "Crossvalidation time: 14.505s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10815.396121\n",
+ "SVM (scaled) RMSE: 103.997097\n",
+ "SVM (scaled) MAE: 63.828414\n",
+ "SVM (scaled) MAEP: 0.080742\n",
+ "SVM (scaled) MBE: -9.879050\n",
+ "SVM (scaled) MBEP: -0.036778\n",
+ "SVM (scaled) R2: 0.829479\n",
+ "Crossvalidation time: 15.547s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 10866.260550\n",
+ "SVM (scaled) RMSE: 104.241357\n",
+ "SVM (scaled) MAE: 63.860965\n",
+ "SVM (scaled) MAEP: 0.080830\n",
+ "SVM (scaled) MBE: -9.812377\n",
+ "SVM (scaled) MBEP: -0.036720\n",
+ "SVM (scaled) R2: 0.828677\n",
+ "Crossvalidation time: 16.125s\n",
+ "\n",
+ "SVM C = 2.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 10966.374548\n",
+ "SVM (scaled) RMSE: 104.720459\n",
+ "SVM (scaled) MAE: 64.043708\n",
+ "SVM (scaled) MAEP: 0.081079\n",
+ "SVM (scaled) MBE: -9.748340\n",
+ "SVM (scaled) MBEP: -0.036685\n",
+ "SVM (scaled) R2: 0.827098\n",
+ "Crossvalidation time: 16.855s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 16045.085837\n",
+ "SVM (scaled) RMSE: 126.669198\n",
+ "SVM (scaled) MAE: 87.393629\n",
+ "SVM (scaled) MAEP: 0.106196\n",
+ "SVM (scaled) MBE: -10.541027\n",
+ "SVM (scaled) MBEP: -0.045097\n",
+ "SVM (scaled) R2: 0.747025\n",
+ "Crossvalidation time: 16.550s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 12375.840897\n",
+ "SVM (scaled) RMSE: 111.246757\n",
+ "SVM (scaled) MAE: 71.000365\n",
+ "SVM (scaled) MAEP: 0.088688\n",
+ "SVM (scaled) MBE: -10.692465\n",
+ "SVM (scaled) MBEP: -0.040472\n",
+ "SVM (scaled) R2: 0.804876\n",
+ "Crossvalidation time: 14.696s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11250.573126\n",
+ "SVM (scaled) RMSE: 106.068719\n",
+ "SVM (scaled) MAE: 65.409722\n",
+ "SVM (scaled) MAEP: 0.082689\n",
+ "SVM (scaled) MBE: -10.733181\n",
+ "SVM (scaled) MBEP: -0.038280\n",
+ "SVM (scaled) R2: 0.822618\n",
+ "Crossvalidation time: 14.660s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11065.885956\n",
+ "SVM (scaled) RMSE: 105.194515\n",
+ "SVM (scaled) MAE: 64.738954\n",
+ "SVM (scaled) MAEP: 0.081815\n",
+ "SVM (scaled) MBE: -10.487173\n",
+ "SVM (scaled) MBEP: -0.037787\n",
+ "SVM (scaled) R2: 0.825529\n",
+ "Crossvalidation time: 14.456s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10935.759702\n",
+ "SVM (scaled) RMSE: 104.574183\n",
+ "SVM (scaled) MAE: 64.347953\n",
+ "SVM (scaled) MAEP: 0.081322\n",
+ "SVM (scaled) MBE: -10.494350\n",
+ "SVM (scaled) MBEP: -0.037558\n",
+ "SVM (scaled) R2: 0.827581\n",
+ "Crossvalidation time: 14.642s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10778.246657\n",
+ "SVM (scaled) RMSE: 103.818335\n",
+ "SVM (scaled) MAE: 63.778495\n",
+ "SVM (scaled) MAEP: 0.080576\n",
+ "SVM (scaled) MBE: -10.173227\n",
+ "SVM (scaled) MBEP: -0.036924\n",
+ "SVM (scaled) R2: 0.830064\n",
+ "Crossvalidation time: 16.023s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10863.659996\n",
+ "SVM (scaled) RMSE: 104.228883\n",
+ "SVM (scaled) MAE: 63.890321\n",
+ "SVM (scaled) MAEP: 0.080698\n",
+ "SVM (scaled) MBE: -9.823261\n",
+ "SVM (scaled) MBEP: -0.036470\n",
+ "SVM (scaled) R2: 0.828718\n",
+ "Crossvalidation time: 18.051s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 10967.483566\n",
+ "SVM (scaled) RMSE: 104.725754\n",
+ "SVM (scaled) MAE: 64.017529\n",
+ "SVM (scaled) MAEP: 0.080987\n",
+ "SVM (scaled) MBE: -9.655350\n",
+ "SVM (scaled) MBEP: -0.036472\n",
+ "SVM (scaled) R2: 0.827081\n",
+ "Crossvalidation time: 19.129s\n",
+ "\n",
+ "SVM C = 5.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11182.165096\n",
+ "SVM (scaled) RMSE: 105.745757\n",
+ "SVM (scaled) MAE: 64.582578\n",
+ "SVM (scaled) MAEP: 0.081634\n",
+ "SVM (scaled) MBE: -9.535967\n",
+ "SVM (scaled) MBEP: -0.036377\n",
+ "SVM (scaled) R2: 0.823696\n",
+ "Crossvalidation time: 20.867s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 15032.975530\n",
+ "SVM (scaled) RMSE: 122.609035\n",
+ "SVM (scaled) MAE: 83.574435\n",
+ "SVM (scaled) MAEP: 0.102033\n",
+ "SVM (scaled) MBE: -9.878080\n",
+ "SVM (scaled) MBEP: -0.043600\n",
+ "SVM (scaled) R2: 0.762982\n",
+ "Crossvalidation time: 16.195s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 12162.638287\n",
+ "SVM (scaled) RMSE: 110.284352\n",
+ "SVM (scaled) MAE: 69.873365\n",
+ "SVM (scaled) MAEP: 0.087532\n",
+ "SVM (scaled) MBE: -10.557505\n",
+ "SVM (scaled) MBEP: -0.039701\n",
+ "SVM (scaled) R2: 0.808237\n",
+ "Crossvalidation time: 13.767s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11179.165959\n",
+ "SVM (scaled) RMSE: 105.731575\n",
+ "SVM (scaled) MAE: 65.158755\n",
+ "SVM (scaled) MAEP: 0.082330\n",
+ "SVM (scaled) MBE: -10.549755\n",
+ "SVM (scaled) MBEP: -0.037898\n",
+ "SVM (scaled) R2: 0.823743\n",
+ "Crossvalidation time: 13.605s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 11032.806020\n",
+ "SVM (scaled) RMSE: 105.037165\n",
+ "SVM (scaled) MAE: 64.628273\n",
+ "SVM (scaled) MAEP: 0.081694\n",
+ "SVM (scaled) MBE: -10.542628\n",
+ "SVM (scaled) MBEP: -0.037747\n",
+ "SVM (scaled) R2: 0.826051\n",
+ "Crossvalidation time: 14.143s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "SVM (scaled) MSE: 10902.844117\n",
+ "SVM (scaled) RMSE: 104.416685\n",
+ "SVM (scaled) MAE: 64.237152\n",
+ "SVM (scaled) MAEP: 0.081148\n",
+ "SVM (scaled) MBE: -10.388831\n",
+ "SVM (scaled) MBEP: -0.037335\n",
+ "SVM (scaled) R2: 0.828100\n",
+ "Crossvalidation time: 14.373s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10772.236024\n",
+ "SVM (scaled) RMSE: 103.789383\n",
+ "SVM (scaled) MAE: 63.761719\n",
+ "SVM (scaled) MAEP: 0.080502\n",
+ "SVM (scaled) MBE: -10.063661\n",
+ "SVM (scaled) MBEP: -0.036708\n",
+ "SVM (scaled) R2: 0.830159\n",
+ "Crossvalidation time: 16.537s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10890.239851\n",
+ "SVM (scaled) RMSE: 104.356312\n",
+ "SVM (scaled) MAE: 63.946738\n",
+ "SVM (scaled) MAEP: 0.080768\n",
+ "SVM (scaled) MBE: -9.782195\n",
+ "SVM (scaled) MBEP: -0.036429\n",
+ "SVM (scaled) R2: 0.828299\n",
+ "Crossvalidation time: 21.054s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11023.854386\n",
+ "SVM (scaled) RMSE: 104.994545\n",
+ "SVM (scaled) MAE: 64.163619\n",
+ "SVM (scaled) MAEP: 0.081146\n",
+ "SVM (scaled) MBE: -9.571552\n",
+ "SVM (scaled) MBEP: -0.036367\n",
+ "SVM (scaled) R2: 0.826192\n",
+ "Crossvalidation time: 22.652s\n",
+ "\n",
+ "SVM C = 7.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11317.651213\n",
+ "SVM (scaled) RMSE: 106.384450\n",
+ "SVM (scaled) MAE: 64.948549\n",
+ "SVM (scaled) MAEP: 0.082049\n",
+ "SVM (scaled) MBE: -9.460930\n",
+ "SVM (scaled) MBEP: -0.036294\n",
+ "SVM (scaled) R2: 0.821560\n",
+ "Crossvalidation time: 25.370s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 14062.035871\n",
+ "SVM (scaled) RMSE: 118.583455\n",
+ "SVM (scaled) MAE: 79.611997\n",
+ "SVM (scaled) MAEP: 0.097658\n",
+ "SVM (scaled) MBE: -9.398804\n",
+ "SVM (scaled) MBEP: -0.041922\n",
+ "SVM (scaled) R2: 0.778291\n",
+ "Crossvalidation time: 17.411s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11987.717539\n",
+ "SVM (scaled) RMSE: 109.488436\n",
+ "SVM (scaled) MAE: 68.969488\n",
+ "SVM (scaled) MAEP: 0.086555\n",
+ "SVM (scaled) MBE: -10.405289\n",
+ "SVM (scaled) MBEP: -0.039019\n",
+ "SVM (scaled) R2: 0.810995\n",
+ "Crossvalidation time: 16.384s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11123.518503\n",
+ "SVM (scaled) RMSE: 105.468092\n",
+ "SVM (scaled) MAE: 64.948391\n",
+ "SVM (scaled) MAEP: 0.082044\n",
+ "SVM (scaled) MBE: -10.444227\n",
+ "SVM (scaled) MBEP: -0.037647\n",
+ "SVM (scaled) R2: 0.824621\n",
+ "Crossvalidation time: 16.153s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10992.280211\n",
+ "SVM (scaled) RMSE: 104.844076\n",
+ "SVM (scaled) MAE: 64.513112\n",
+ "SVM (scaled) MAEP: 0.081512\n",
+ "SVM (scaled) MBE: -10.476422\n",
+ "SVM (scaled) MBEP: -0.037552\n",
+ "SVM (scaled) R2: 0.826690\n",
+ "Crossvalidation time: 16.195s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10874.261446\n",
+ "SVM (scaled) RMSE: 104.279727\n",
+ "SVM (scaled) MAE: 64.132115\n",
+ "SVM (scaled) MAEP: 0.081006\n",
+ "SVM (scaled) MBE: -10.306060\n",
+ "SVM (scaled) MBEP: -0.037159\n",
+ "SVM (scaled) R2: 0.828551\n",
+ "Crossvalidation time: 16.883s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10771.550398\n",
+ "SVM (scaled) RMSE: 103.786080\n",
+ "SVM (scaled) MAE: 63.749605\n",
+ "SVM (scaled) MAEP: 0.080474\n",
+ "SVM (scaled) MBE: -9.961846\n",
+ "SVM (scaled) MBEP: -0.036546\n",
+ "SVM (scaled) R2: 0.830170\n",
+ "Crossvalidation time: 19.201s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 10924.557941\n",
+ "SVM (scaled) RMSE: 104.520610\n",
+ "SVM (scaled) MAE: 64.035449\n",
+ "SVM (scaled) MAEP: 0.080877\n",
+ "SVM (scaled) MBE: -9.733897\n",
+ "SVM (scaled) MBEP: -0.036397\n",
+ "SVM (scaled) R2: 0.827758\n",
+ "Crossvalidation time: 23.582s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11102.244251\n",
+ "SVM (scaled) RMSE: 105.367188\n",
+ "SVM (scaled) MAE: 64.342529\n",
+ "SVM (scaled) MAEP: 0.081310\n",
+ "SVM (scaled) MBE: -9.434421\n",
+ "SVM (scaled) MBEP: -0.036184\n",
+ "SVM (scaled) R2: 0.824956\n",
+ "Crossvalidation time: 25.100s\n",
+ "\n",
+ "SVM C = 10.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11483.042338\n",
+ "SVM (scaled) RMSE: 107.158958\n",
+ "SVM (scaled) MAE: 65.349748\n",
+ "SVM (scaled) MAEP: 0.082520\n",
+ "SVM (scaled) MBE: -9.380459\n",
+ "SVM (scaled) MBEP: -0.036221\n",
+ "SVM (scaled) R2: 0.818952\n",
+ "Crossvalidation time: 27.531s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12916.214920\n",
+ "SVM (scaled) RMSE: 113.649527\n",
+ "SVM (scaled) MAE: 74.090716\n",
+ "SVM (scaled) MAEP: 0.091768\n",
+ "SVM (scaled) MBE: -9.891285\n",
+ "SVM (scaled) MBEP: -0.040448\n",
+ "SVM (scaled) R2: 0.796356\n",
+ "Crossvalidation time: 15.942s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11766.479304\n",
+ "SVM (scaled) RMSE: 108.473404\n",
+ "SVM (scaled) MAE: 67.817723\n",
+ "SVM (scaled) MAEP: 0.085364\n",
+ "SVM (scaled) MBE: -10.382298\n",
+ "SVM (scaled) MBEP: -0.038269\n",
+ "SVM (scaled) R2: 0.814484\n",
+ "Crossvalidation time: 15.359s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 11043.130285\n",
+ "SVM (scaled) RMSE: 105.086299\n",
+ "SVM (scaled) MAE: 64.669423\n",
+ "SVM (scaled) MAEP: 0.081671\n",
+ "SVM (scaled) MBE: -10.262892\n",
+ "SVM (scaled) MBEP: -0.037300\n",
+ "SVM (scaled) R2: 0.825888\n",
+ "Crossvalidation time: 16.325s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10934.406553\n",
+ "SVM (scaled) RMSE: 104.567713\n",
+ "SVM (scaled) MAE: 64.328127\n",
+ "SVM (scaled) MAEP: 0.081216\n",
+ "SVM (scaled) MBE: -10.318254\n",
+ "SVM (scaled) MBEP: -0.037177\n",
+ "SVM (scaled) R2: 0.827602\n",
+ "Crossvalidation time: 17.317s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10825.896525\n",
+ "SVM (scaled) RMSE: 104.047569\n",
+ "SVM (scaled) MAE: 63.951895\n",
+ "SVM (scaled) MAEP: 0.080726\n",
+ "SVM (scaled) MBE: -10.156733\n",
+ "SVM (scaled) MBEP: -0.036858\n",
+ "SVM (scaled) R2: 0.829313\n",
+ "Crossvalidation time: 18.941s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10796.100525\n",
+ "SVM (scaled) RMSE: 103.904285\n",
+ "SVM (scaled) MAE: 63.799617\n",
+ "SVM (scaled) MAEP: 0.080540\n",
+ "SVM (scaled) MBE: -9.904966\n",
+ "SVM (scaled) MBEP: -0.036370\n",
+ "SVM (scaled) R2: 0.829783\n",
+ "Crossvalidation time: 21.776s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11062.876877\n",
+ "SVM (scaled) RMSE: 105.180211\n",
+ "SVM (scaled) MAE: 64.290901\n",
+ "SVM (scaled) MAEP: 0.081240\n",
+ "SVM (scaled) MBE: -9.540432\n",
+ "SVM (scaled) MBEP: -0.036271\n",
+ "SVM (scaled) R2: 0.825577\n",
+ "Crossvalidation time: 29.446s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11340.957519\n",
+ "SVM (scaled) RMSE: 106.493932\n",
+ "SVM (scaled) MAE: 64.951063\n",
+ "SVM (scaled) MAEP: 0.082028\n",
+ "SVM (scaled) MBE: -9.284026\n",
+ "SVM (scaled) MBEP: -0.035991\n",
+ "SVM (scaled) R2: 0.821193\n",
+ "Crossvalidation time: 34.156s\n",
+ "\n",
+ "SVM C = 20.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 11879.924463\n",
+ "SVM (scaled) RMSE: 108.995066\n",
+ "SVM (scaled) MAE: 66.263897\n",
+ "SVM (scaled) MAEP: 0.083541\n",
+ "SVM (scaled) MBE: -9.114376\n",
+ "SVM (scaled) MBEP: -0.035958\n",
+ "SVM (scaled) R2: 0.812695\n",
+ "Crossvalidation time: 43.081s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12279.293901\n",
+ "SVM (scaled) RMSE: 110.811975\n",
+ "SVM (scaled) MAE: 70.554522\n",
+ "SVM (scaled) MAEP: 0.088183\n",
+ "SVM (scaled) MBE: -10.088976\n",
+ "SVM (scaled) MBEP: -0.038832\n",
+ "SVM (scaled) R2: 0.806398\n",
+ "Crossvalidation time: 16.388s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11522.922860\n",
+ "SVM (scaled) RMSE: 107.344878\n",
+ "SVM (scaled) MAE: 66.681713\n",
+ "SVM (scaled) MAEP: 0.084077\n",
+ "SVM (scaled) MBE: -10.264338\n",
+ "SVM (scaled) MBEP: -0.037592\n",
+ "SVM (scaled) R2: 0.818324\n",
+ "Crossvalidation time: 16.726s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 10974.490755\n",
+ "SVM (scaled) RMSE: 104.759204\n",
+ "SVM (scaled) MAE: 64.441366\n",
+ "SVM (scaled) MAEP: 0.081407\n",
+ "SVM (scaled) MBE: -10.317032\n",
+ "SVM (scaled) MBEP: -0.037153\n",
+ "SVM (scaled) R2: 0.826970\n",
+ "Crossvalidation time: 19.152s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10865.080122\n",
+ "SVM (scaled) RMSE: 104.235695\n",
+ "SVM (scaled) MAE: 64.088529\n",
+ "SVM (scaled) MAEP: 0.080904\n",
+ "SVM (scaled) MBE: -10.110453\n",
+ "SVM (scaled) MBEP: -0.036776\n",
+ "SVM (scaled) R2: 0.828695\n",
+ "Crossvalidation time: 21.673s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10787.007252\n",
+ "SVM (scaled) RMSE: 103.860518\n",
+ "SVM (scaled) MAE: 63.841514\n",
+ "SVM (scaled) MAEP: 0.080554\n",
+ "SVM (scaled) MBE: -9.890666\n",
+ "SVM (scaled) MBEP: -0.036436\n",
+ "SVM (scaled) R2: 0.829926\n",
+ "Crossvalidation time: 24.062s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "SVM (scaled) MSE: 10840.248258\n",
+ "SVM (scaled) RMSE: 104.116513\n",
+ "SVM (scaled) MAE: 63.943106\n",
+ "SVM (scaled) MAEP: 0.080693\n",
+ "SVM (scaled) MBE: -9.794385\n",
+ "SVM (scaled) MBEP: -0.036205\n",
+ "SVM (scaled) R2: 0.829087\n",
+ "Crossvalidation time: 31.047s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11281.266509\n",
+ "SVM (scaled) RMSE: 106.213307\n",
+ "SVM (scaled) MAE: 64.870725\n",
+ "SVM (scaled) MAEP: 0.081912\n",
+ "SVM (scaled) MBE: -9.327964\n",
+ "SVM (scaled) MBEP: -0.035956\n",
+ "SVM (scaled) R2: 0.822134\n",
+ "Crossvalidation time: 53.531s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 11805.049921\n",
+ "SVM (scaled) RMSE: 108.651047\n",
+ "SVM (scaled) MAE: 66.021563\n",
+ "SVM (scaled) MAEP: 0.083434\n",
+ "SVM (scaled) MBE: -9.156888\n",
+ "SVM (scaled) MBEP: -0.036030\n",
+ "SVM (scaled) R2: 0.813875\n",
+ "Crossvalidation time: 65.179s\n",
+ "\n",
+ "SVM C = 50.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 12666.948816\n",
+ "SVM (scaled) RMSE: 112.547540\n",
+ "SVM (scaled) MAE: 67.767940\n",
+ "SVM (scaled) MAEP: 0.085423\n",
+ "SVM (scaled) MBE: -8.613697\n",
+ "SVM (scaled) MBEP: -0.035779\n",
+ "SVM (scaled) R2: 0.800286\n",
+ "Crossvalidation time: 86.382s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12172.011389\n",
+ "SVM (scaled) RMSE: 110.326839\n",
+ "SVM (scaled) MAE: 69.911192\n",
+ "SVM (scaled) MAEP: 0.087558\n",
+ "SVM (scaled) MBE: -10.066645\n",
+ "SVM (scaled) MBEP: -0.038443\n",
+ "SVM (scaled) R2: 0.808090\n",
+ "Crossvalidation time: 18.239s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11443.942715\n",
+ "SVM (scaled) RMSE: 106.976365\n",
+ "SVM (scaled) MAE: 66.329836\n",
+ "SVM (scaled) MAEP: 0.083675\n",
+ "SVM (scaled) MBE: -10.256958\n",
+ "SVM (scaled) MBEP: -0.037469\n",
+ "SVM (scaled) R2: 0.819569\n",
+ "Crossvalidation time: 18.532s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 10949.559443\n",
+ "SVM (scaled) RMSE: 104.640143\n",
+ "SVM (scaled) MAE: 64.379997\n",
+ "SVM (scaled) MAEP: 0.081304\n",
+ "SVM (scaled) MBE: -10.247675\n",
+ "SVM (scaled) MBEP: -0.037017\n",
+ "SVM (scaled) R2: 0.827363\n",
+ "Crossvalidation time: 22.836s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10840.568159\n",
+ "SVM (scaled) RMSE: 104.118049\n",
+ "SVM (scaled) MAE: 63.999670\n",
+ "SVM (scaled) MAEP: 0.080803\n",
+ "SVM (scaled) MBE: -10.009236\n",
+ "SVM (scaled) MBEP: -0.036624\n",
+ "SVM (scaled) R2: 0.829082\n",
+ "Crossvalidation time: 25.097s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10781.897108\n",
+ "SVM (scaled) RMSE: 103.835914\n",
+ "SVM (scaled) MAE: 63.818455\n",
+ "SVM (scaled) MAEP: 0.080553\n",
+ "SVM (scaled) MBE: -9.946328\n",
+ "SVM (scaled) MBEP: -0.036454\n",
+ "SVM (scaled) R2: 0.830007\n",
+ "Crossvalidation time: 30.340s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10862.361042\n",
+ "SVM (scaled) RMSE: 104.222651\n",
+ "SVM (scaled) MAE: 64.006754\n",
+ "SVM (scaled) MAEP: 0.080775\n",
+ "SVM (scaled) MBE: -9.782864\n",
+ "SVM (scaled) MBEP: -0.036222\n",
+ "SVM (scaled) R2: 0.828738\n",
+ "Crossvalidation time: 41.067s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11423.365235\n",
+ "SVM (scaled) RMSE: 106.880144\n",
+ "SVM (scaled) MAE: 65.186185\n",
+ "SVM (scaled) MAEP: 0.082339\n",
+ "SVM (scaled) MBE: -9.330777\n",
+ "SVM (scaled) MBEP: -0.035979\n",
+ "SVM (scaled) R2: 0.819893\n",
+ "Crossvalidation time: 71.186s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 12060.726055\n",
+ "SVM (scaled) RMSE: 109.821337\n",
+ "SVM (scaled) MAE: 66.522918\n",
+ "SVM (scaled) MAEP: 0.084111\n",
+ "SVM (scaled) MBE: -9.160439\n",
+ "SVM (scaled) MBEP: -0.036178\n",
+ "SVM (scaled) R2: 0.809844\n",
+ "Crossvalidation time: 89.224s\n",
+ "\n",
+ "SVM C = 70.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 13065.320025\n",
+ "SVM (scaled) RMSE: 114.303631\n",
+ "SVM (scaled) MAE: 68.417957\n",
+ "SVM (scaled) MAEP: 0.086360\n",
+ "SVM (scaled) MBE: -8.498086\n",
+ "SVM (scaled) MBEP: -0.035870\n",
+ "SVM (scaled) R2: 0.794005\n",
+ "Crossvalidation time: 114.653s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 10.000000\n",
+ "SVM (scaled) MSE: 12068.887102\n",
+ "SVM (scaled) RMSE: 109.858487\n",
+ "SVM (scaled) MAE: 69.314605\n",
+ "SVM (scaled) MAEP: 0.086941\n",
+ "SVM (scaled) MBE: -9.896917\n",
+ "SVM (scaled) MBEP: -0.037877\n",
+ "SVM (scaled) R2: 0.809716\n",
+ "Crossvalidation time: 17.971s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 20.000000\n",
+ "SVM (scaled) MSE: 11365.286438\n",
+ "SVM (scaled) RMSE: 106.608097\n",
+ "SVM (scaled) MAE: 65.990980\n",
+ "SVM (scaled) MAEP: 0.083288\n",
+ "SVM (scaled) MBE: -10.236784\n",
+ "SVM (scaled) MBEP: -0.037318\n",
+ "SVM (scaled) R2: 0.820809\n",
+ "Crossvalidation time: 19.859s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 50.000000\n",
+ "SVM (scaled) MSE: 10923.316447\n",
+ "SVM (scaled) RMSE: 104.514671\n",
+ "SVM (scaled) MAE: 64.283194\n",
+ "SVM (scaled) MAEP: 0.081201\n",
+ "SVM (scaled) MBE: -10.255503\n",
+ "SVM (scaled) MBEP: -0.036982\n",
+ "SVM (scaled) R2: 0.827777\n",
+ "Crossvalidation time: 25.813s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 70.000000\n",
+ "SVM (scaled) MSE: 10815.077454\n",
+ "SVM (scaled) RMSE: 103.995565\n",
+ "SVM (scaled) MAE: 63.921116\n",
+ "SVM (scaled) MAEP: 0.080694\n",
+ "SVM (scaled) MBE: -9.935495\n",
+ "SVM (scaled) MBEP: -0.036509\n",
+ "SVM (scaled) R2: 0.829484\n",
+ "Crossvalidation time: 28.104s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 100.000000\n",
+ "SVM (scaled) MSE: 10782.976938\n",
+ "SVM (scaled) RMSE: 103.841114\n",
+ "SVM (scaled) MAE: 63.830678\n",
+ "SVM (scaled) MAEP: 0.080607\n",
+ "SVM (scaled) MBE: -9.886186\n",
+ "SVM (scaled) MBEP: -0.036387\n",
+ "SVM (scaled) R2: 0.829990\n",
+ "Crossvalidation time: 33.360s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 200.000000\n",
+ "SVM (scaled) MSE: 10878.555987\n",
+ "SVM (scaled) RMSE: 104.300316\n",
+ "SVM (scaled) MAE: 64.068177\n",
+ "SVM (scaled) MAEP: 0.080837\n",
+ "SVM (scaled) MBE: -9.687263\n",
+ "SVM (scaled) MBEP: -0.036138\n",
+ "SVM (scaled) R2: 0.828483\n",
+ "Crossvalidation time: 48.447s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 500.000000\n",
+ "SVM (scaled) MSE: 11601.075669\n",
+ "SVM (scaled) RMSE: 107.708290\n",
+ "SVM (scaled) MAE: 65.591167\n",
+ "SVM (scaled) MAEP: 0.082884\n",
+ "SVM (scaled) MBE: -9.181940\n",
+ "SVM (scaled) MBEP: -0.035904\n",
+ "SVM (scaled) R2: 0.817091\n",
+ "Crossvalidation time: 100.223s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 700.000000\n",
+ "SVM (scaled) MSE: 12367.141411\n",
+ "SVM (scaled) RMSE: 111.207650\n",
+ "SVM (scaled) MAE: 67.066229\n",
+ "SVM (scaled) MAEP: 0.084827\n",
+ "SVM (scaled) MBE: -9.109264\n",
+ "SVM (scaled) MBEP: -0.036231\n",
+ "SVM (scaled) R2: 0.805013\n",
+ "Crossvalidation time: 119.214s\n",
+ "\n",
+ "SVM C = 100.000000\n",
+ "SVM epsilon = 0.100000\n",
+ "SVM gamma = 1000.000000\n",
+ "SVM (scaled) MSE: 13560.087904\n",
+ "SVM (scaled) RMSE: 116.447790\n",
+ "SVM (scaled) MAE: 69.264932\n",
+ "SVM (scaled) MAEP: 0.087524\n",
+ "SVM (scaled) MBE: -8.351864\n",
+ "SVM (scaled) MBEP: -0.035938\n",
+ "SVM (scaled) R2: 0.786205\n",
+ "Crossvalidation time: 154.301s\n"
+ ]
+ }
+ ],
+ "source": [
+ "name = 'SVM'\n",
+ "svm_tuning = pd.DataFrame(data = [], \n",
+ " columns = ['C', 'epsilon', 'gamma', 'scaled_target', 'time'])\n",
+ "\n",
+ "# SVM_gamma = 'scale'\n",
+ "# SVM_epsilon = 0.1\n",
+ "for SVM_epsilon in [0.01, 0.1]:\n",
+ " for C in [1, 2, 5, 7, 10, 20, 50, 70, 100]:\n",
+ " for SVM_gamma in [10, 20, 50, 70, 100, 200, 500, 700, 1000]: \n",
+ " print('\\nSVM C = %f' %C)\n",
+ " print('SVM epsilon = %f' %SVM_epsilon)\n",
+ " print('SVM gamma = %f' %SVM_gamma)\n",
+ " tt = time.time()\n",
+ "\n",
+ " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = SVM_gamma)\n",
+ " y = cross_val_predict(est, x, t, cv = 5)\n",
+ " Y = rescale(y, T)\n",
+ " scaled_err = get_errors( shp(T), shp(Y), 'SVM (scaled)' )\n",
+ "\n",
+ " cv_time = time.time()-tt\n",
+ " print('Crossvalidation time: %.3fs' %cv_time)\n",
+ "\n",
+ " svm_tuning = svm_tuning.append( pd.DataFrame(data = [[ C, SVM_epsilon, SVM_gamma, \n",
+ " scaled_err.RMSE, cv_time]], \n",
+ " columns = ['C', 'epsilon', 'gamma', \n",
+ " 'scaled_target', 'time']) )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 143,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "svm_tuning_xr = svm_tuning.set_index(['C', 'epsilon', 'gamma']).to_xarray()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 144,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.Dataset>\n",
+ "Dimensions: (C: 9, epsilon: 2, gamma: 9)\n",
+ "Coordinates:\n",
+ " * C (C) int64 1 2 5 7 10 20 50 70 100\n",
+ " * epsilon (epsilon) float64 0.01 0.1\n",
+ " * gamma (gamma) int64 10 20 50 70 100 200 500 700 1000\n",
+ "Data variables:\n",
+ " scaled_target (C, epsilon, gamma) float64 142.3 123.3 108.4 ... 111.2 116.4\n",
+ " time (C, epsilon, gamma) float64 18.18 19.09 17.98 ... 119.2 154.3"
+ ]
+ },
+ "execution_count": 144,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svm_tuning_xr"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 145,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "svm_tuning_xr.to_netcdf('svm_tuning_10k.nc')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.DataArray 'scaled_target' ()>\n",
+ "array(103.78608)"
+ ]
+ },
+ "execution_count": 146,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svm_tuning_xr.scaled_target.min()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 155,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.Dataset>\n",
+ "Dimensions: (C: 9, epsilon: 1, gamma: 4)\n",
+ "Coordinates:\n",
+ " * C (C) int64 1 2 5 7 10 20 50 70 100\n",
+ " * epsilon (epsilon) float64 0.1\n",
+ " * gamma (gamma) int64 70 100 200 500\n",
+ "Data variables:\n",
+ " scaled_target (C, epsilon, gamma) float64 nan nan nan ... 103.8 nan nan\n",
+ " time (C, epsilon, gamma) float64 nan nan nan ... 33.36 nan nan"
+ ]
+ },
+ "execution_count": 155,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svm_tuning_xr.where(svm_tuning_xr.scaled_target < 104, drop = True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 156,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([[[ nan, nan, nan, 103.85338758]],\n",
+ "\n",
+ " [[ nan, nan, nan, 103.9970967 ]],\n",
+ "\n",
+ " [[ nan, nan, 103.81833488, nan]],\n",
+ "\n",
+ " [[ nan, nan, 103.789383 , nan]],\n",
+ "\n",
+ " [[ nan, nan, 103.78607998, nan]],\n",
+ "\n",
+ " [[ nan, nan, 103.9042854 , nan]],\n",
+ "\n",
+ " [[ nan, 103.86051825, nan, nan]],\n",
+ "\n",
+ " [[ nan, 103.83591435, nan, nan]],\n",
+ "\n",
+ " [[103.99556459, 103.84111391, nan, nan]]])"
+ ]
+ },
+ "execution_count": 156,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "svm_tuning_xr.where(svm_tuning_xr.scaled_target < 104, drop = True).drop('epsilon').scaled_target.values"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 149,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "\n",
+ "mpl.get_websocket_type = function() {\n",
+ " if (typeof(WebSocket) !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert('Your browser does not have WebSocket support.' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.');\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = (this.ws.binaryType != undefined);\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById(\"mpl-warnings\");\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent = (\n",
+ " \"This browser does not support binary websocket messages. \" +\n",
+ " \"Performance may be slow.\");\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+ " fig.send_message(\"send_image_mode\", {});\n",
+ " if (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+ " }\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " }\n",
+ "\n",
+ " this.imageObj.onload = function() {\n",
+ " if (fig.image_mode == 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function() {\n",
+ " fig.ws.close();\n",
+ " }\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function() {\n",
+ " var titlebar = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus () {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items){\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ },
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+ "output_type": "display_data"
+ },
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\" width=\"640\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure()\n",
+ "svm_tuning_xr.scaled_target.attrs['long_name'] = 'RMSE ($kWh/m^2$)'\n",
+ "\n",
+ "svm_tuning_xr.scaled_target.isel(epsilon = i).plot(cmap = 'coolwarm') # vmin = 1.9, vmax = 2.4\n",
+ " \n",
+ "plt.xscale('log')\n",
+ "plt.xlim(5, 1e3)\n",
+ "plt.xlabel('Kernel coefficient ($\\gamma$)')\n",
+ "\n",
+ "plt.yscale('log')\n",
+ "plt.ylim(0.5, 1e2)\n",
+ "plt.ylabel('Error penalization term ($C$)')\n",
+ "\n",
+ "plt.title('')\n",
+ "plt.tight_layout()\n",
+ "plt.savefig('SVM_tuning_10k.png', dpi = 300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "\n",
+ "mpl.get_websocket_type = function() {\n",
+ " if (typeof(WebSocket) !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert('Your browser does not have WebSocket support.' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.');\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = (this.ws.binaryType != undefined);\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById(\"mpl-warnings\");\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent = (\n",
+ " \"This browser does not support binary websocket messages. \" +\n",
+ " \"Performance may be slow.\");\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+ " fig.send_message(\"send_image_mode\", {});\n",
+ " if (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+ " }\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " }\n",
+ "\n",
+ " this.imageObj.onload = function() {\n",
+ " if (fig.image_mode == 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function() {\n",
+ " fig.ws.close();\n",
+ " }\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function() {\n",
+ " var titlebar = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus () {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items){\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.figure(figsize = (10, 8))\n",
+ "for i in range(2):\n",
+ " plt.subplot(2,2,(2*i+1))\n",
+ " p1 = np.log10(svm_tuning_xr.scaled_target.isel(epsilon = i)).plot(vmax = 2.1) # vmin = 1.9, vmax = 2.4\n",
+ " plt.xscale('log')\n",
+ " plt.xlim(5, 1e3)\n",
+ "\n",
+ " plt.yscale('log')\n",
+ " plt.ylim(0.5, 1e2)\n",
+ "\n",
+ " plt.subplot(2,2, (2*i+2))\n",
+ " p2 = np.log10(svm_tuning_xr.time.isel(epsilon = i)).plot(cmap = 'RdBu_r') # vmin = -1.5, vmax = 1.5\n",
+ " plt.xscale('log')\n",
+ " plt.xlim(5, 1e3)\n",
+ "\n",
+ " plt.yscale('log')\n",
+ " plt.ylim(0.5, 1e2)\n",
+ " \n",
+ "plt.tight_layout()\n",
+ "plt.savefig('SVF_tuning_round2_10k.png', dpi = 300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 132,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "\n",
+ "mpl.get_websocket_type = function() {\n",
+ " if (typeof(WebSocket) !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert('Your browser does not have WebSocket support.' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.');\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = (this.ws.binaryType != undefined);\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById(\"mpl-warnings\");\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent = (\n",
+ " \"This browser does not support binary websocket messages. \" +\n",
+ " \"Performance may be slow.\");\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+ " fig.send_message(\"send_image_mode\", {});\n",
+ " if (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+ " }\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " }\n",
+ "\n",
+ " this.imageObj.onload = function() {\n",
+ " if (fig.image_mode == 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function() {\n",
+ " fig.ws.close();\n",
+ " }\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function() {\n",
+ " var titlebar = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus () {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option)\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function(type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function() {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0, 0, fig.canvas.width, fig.canvas.height);\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch(cursor)\n",
+ " {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message(\"ack\", {});\n",
+ "}\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = \"image/png\";\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig[\"handle_\" + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function(e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e)\n",
+ " e = window.event;\n",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\n",
+ "\n",
+ " return {\"x\": x, \"y\": y};\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys (original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object')\n",
+ " obj[key] = original[key]\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+ " var canvas_pos = mpl.findpos(event)\n",
+ "\n",
+ " if (name === 'button_press')\n",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function(event, name) {\n",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, {key: value,\n",
+ " guiEvent: simpleKeys(event)});\n",
+ " return false;\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+ " if (name == 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message(\"toolbar_button\", {name: name});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function() {\n",
+ " comm.close()\n",
+ " };\n",
+ " ws.send = function(m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function(msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data'])\n",
+ " });\n",
+ " return ws;\n",
+ "}\n",
+ "\n",
+ "mpl.mpl_figure_comm = function(comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element.get(0);\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error(\"Failed to find cell for figure\", id, fig);\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable()\n",
+ " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+ " fig.close_ws(fig, msg);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function() {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message(\"ack\", {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>')\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\n",
+ " for(var toolbar_ind in mpl.toolbar_items){\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('tabindex', 0)\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager)\n",
+ " manager = IPython.keyboard_manager;\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which == 13) {\n",
+ " this.canvas_div.blur();\n",
+ " event.shiftKey = false;\n",
+ " // Send a \"J\" for go to next cell\n",
+ " event.which = 74;\n",
+ " event.keyCode = 74;\n",
+ " manager.command_mode();\n",
+ " manager.handle_keydown(event);\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.find_output_cell = function(html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i=0; i<ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code'){\n",
+ " for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] == html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel != null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
],
"text/plain": [
- " unscaled unscaled_target scaled_target\n",
- "0.1 247.865813 247.933048 216.000682\n",
- "0.2 247.642499 247.773033 194.446270\n",
- "0.5 246.957192 247.275723 167.589291\n",
- "1.0 245.878745 246.446937 155.871316\n",
- "2.0 243.899368 244.907860 150.359435\n",
- "5.0 238.804532 240.496598 147.968116\n",
- "10.0 231.471496 233.585816 147.285781"
+ "<IPython.core.display.Javascript object>"
]
},
- "execution_count": 46,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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\" 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+ "text/plain": [
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+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
- "svm_tuning"
+ "plt.figure(figsize = (10, 8))\n",
+ "for i in range(2):\n",
+ " plt.subplot(2,2,(2*i+1))\n",
+ " p1 = np.log10(svm_tuning_xr.scaled_target.isel(epsilon = i)).plot(vmax = 2.1) # vmin = 1.9, vmax = 2.4\n",
+ " plt.xscale('log')\n",
+ " plt.xlim(5, 1e3)\n",
+ "\n",
+ " plt.yscale('log')\n",
+ " plt.ylim(0.5, 1e2)\n",
+ "\n",
+ " plt.subplot(2,2, (2*i+2))\n",
+ " p2 = np.log10(svm_tuning_xr.time.isel(epsilon = i)).plot() # vmin = -1.5, vmax = 1.5\n",
+ " plt.xscale('log')\n",
+ " plt.xlim(5, 1e3)\n",
+ "\n",
+ " plt.yscale('log')\n",
+ " plt.ylim(0.5, 1e2)\n",
+ " \n",
+ "plt.tight_layout()\n",
+ "plt.savefig('SVF_tuning_round2.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "# CURRENTLY NOT USED\n",
+ "tt = time.time()\n",
+ "\n",
+ " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = SVM_gamma)\n",
+ " Y = cross_val_predict(est, X, T, cv = 5)\n",
+ " ununscaled_err = get_errors( shp(T), shp(Y), 'SVM (unscaled)' )\n",
+ "\n",
+ " print('Crossvalidation time: %.3fs' %(time.time()-tt))\n",
+ " tt = time.time()\n",
+ "\n",
+ " est = SVR( C = C, kernel = 'rbf', epsilon = SVM_epsilon, gamma = SVM_gamma)\n",
+ " Y = cross_val_predict(est, x, T, cv = 5)\n",
+ " unscaled_err = get_errors( shp(T), shp(Y), 'SVM (unscaled)' )\n",
+ "\n",
+ " print('Crossvalidation time: %.3fs' %(time.time()-tt))"
+ ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot 2D histogram"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import LinearRegression\n",
"\n",
"min_val = max(T_tst.min(), Y_tst.min())\n",
"max_val = min(T_tst.max(), Y_tst.max())\n",
"\n",
"X_regr = Y_tst.reshape(-1, 1)\n",
"Y_regr = T_tst.reshape(-1, 1)\n",
"\n",
"LIN = LinearRegression( n_jobs = -1 )\n",
"LIN.fit( X_regr, Y_regr )\n",
"\n",
"x_regr = np.asarray([min_val, max_val]).reshape(-1, 1)\n",
"y_regr = LIN.predict( x_regr )\n",
"\n",
"R2 = LIN.score(X_regr, Y_regr)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"min_val = 500\n",
"max_val = 1700\n",
"\n",
"plt.figure()\n",
"\n",
"plt.hist2d( Y_tst, T_tst, bins=100, cmap = 'Oranges')\n",
"plt.plot([min_val,max_val],[min_val,max_val], c = 'grey', alpha= 0.7, lw = 0.7)\n",
"plt.plot(x_regr, y_regr, c = 'k', lw = 0.7, label = 'Regression line ($R^2 = %.2f$)' %R2)\n",
"# plt.plot([], [], c = 'grew', ls = '--', lw = 0.7, alpha = 0.7)\n",
"\n",
"plt.ylabel('Target ($kWh/m^2$)')\n",
"plt.xlabel('Prediction ($kWh/m^2$)')\n",
"# plt.title('Annual solar irradiation')\n",
"\n",
"plt.axis('equal')\n",
"plt.xlim((min_val, max_val))\n",
"plt.ylim((min_val, max_val))\n",
"\n",
"cbar = plt.colorbar()\n",
"cbar.set_label('# of values in bin')\n",
"\n",
"plt.legend()\n",
"plt.tight_layout()\n",
"plt.show()\n",
"# plt.savefig('Regression_1M.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Double-check feature importance"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# for standard estimators\n",
"n_features = X.shape[1]\n",
"importance = np.mean([tree.feature_importances_ for tree in RF.estimators_],axis=0)\n",
"std = np.std([tree.feature_importances_ for tree in RF.estimators_],axis=0)\n",
"ind = np.argsort(importance)[-n_features:]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(importance)\n",
"print(std)\n",
"print(ind)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.figure()\n",
"ax = plt.axes()\n",
"# plt.title(\"Feature Importance for RF (%dk features)\" %(X.shape[0]/1000)) # \\n Testing RMSE: %f ; , np.sqrt(mse(Y_te,T_te))\n",
"plt.barh(range(n_features),importance[ind],\n",
" color=\"C1\", xerr=std[ind], alpha=0.5, align=\"center\", capsize = 2)\n",
"plt.yticks(range(n_features), np.asarray(feature_labels)[ind])\n",
"plt.ylim([-1, len(ind)])\n",
"plt.xlabel('Feature importance')\n",
"plt.tight_layout()\n",
"plt.show()\n",
"# plt.savefig('Feature_importance_selFtrs_mean_10k.png', dpi=300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# ML with uncertainty"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"estimator = set_estimators()\n",
"RF_unc = Uncertainty( estimator['RF'] )\n",
"RF_unc.fit(X, T)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model variance not given\n",
"Estimating model variance ... \n",
"Fitting model ...\n",
"CPU time: 228.80 seconds\n",
"Wall clock time: 82.86 seconds\n"
]
}
],
"source": [
"# set residual estimator and fit \n",
"RF_unc.residuals.set_params( n_estimators = n_est )\n",
"\n",
"tt = util.Timer()\n",
"residuals = RF_unc.fit_residuals( X, T )\n",
"tt.stop()"
]
},
{
"cell_type": "code",
"execution_count": 204,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU time: 200.51 seconds\n",
"Wall clock time: 125.80 seconds\n"
]
},
{
"ename": "NameError",
"evalue": "name 'compute_residuals' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-204-4816131a1aa3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mtt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mRes_tst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompute_residuals\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mshp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mY_tst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mT_tst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmUnc_tst\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'compute_residuals' is not defined"
]
}
],
"source": [
"# get prediction, model uncertainty and data uncertainty\n",
"tt = util.Timer()\n",
"Y_tst, mUnc_tst = RF_unc.predict_model_uncertainty(X_tst)\n",
"dUnc_tst = RF_unc.predict_residuals(X_tst)\n",
"tt.stop()"
]
},
{
"cell_type": "code",
"execution_count": 208,
"metadata": {},
"outputs": [],
"source": [
"Res_tst = compute_residuals( shp(Y_tst), shp(T_tst), shp(mUnc_tst) )"
]
},
{
"cell_type": "code",
"execution_count": 213,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Prediction MSE: 8976.326644\n",
"Prediction RMSE: 94.743478\n",
"Prediction MAE: 58.576197\n",
"Prediction MAEP: 0.076631\n",
"Prediction MBE: -15.192731\n",
"Prediction MBEP: -0.038931\n",
"Prediction R2: 0.836498\n",
"\n",
"Residuals MSE: 4994.676687\n",
"Residuals RMSE: 70.673027\n",
"Residuals MAE: 40.612807\n",
"Residuals MAEP: 1.647667\n",
"Residuals MBE: 2.376570\n",
"Residuals MBEP: -0.149421\n",
"Residuals R2: -7.559683\n"
]
}
],
"source": [
"pred_err = get_errors( shp(T_tst), shp(Y_tst), 'Prediction' )\n",
"print('')\n",
"res_err = get_errors( shp(dUnc_tst), shp(Res_tst), 'Residuals' )"
]
},
{
"cell_type": "code",
"execution_count": 214,
"metadata": {},
"outputs": [],
"source": [
"# merge all test results into one dataframe\n",
"identifier = 'DF_UID'\n",
"identifiers = shp(testing.index.values)\n",
"test_results = pd.DataFrame( np.hstack([identifiers, shp(T_tst), shp(Y_tst), shp(mUnc_tst), shp(dUnc_tst) ]), \n",
" columns = ['DF_UID', 'target', 'prediction', 'model_std', 'data_std'])\n",
"test_results['total_std'] = np.sqrt(test_results.model_std ** 2 + test_results.data_std ** 2)\n",
"test_results['data_std_rel_to_total'] = test_results['total_std'] * test_results['data_std'] / ( test_results['data_std'] + test_results['model_std'] )\n",
"test_results['model_std_rel_to_total'] = test_results['total_std'] * test_results['model_std'] / ( test_results['data_std'] + test_results['model_std'] )"
]
},
{
"cell_type": "code",
"execution_count": 247,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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"\n",
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"\n",
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"\n",
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" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
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" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
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"\n",
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"\n",
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"\n",
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"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
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"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
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"\n",
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"\n",
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"\n",
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"\tthis.context.webkitBackingStorePixelRatio ||\n",
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"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
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"\n",
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"\n",
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"\n",
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"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
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"\n",
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" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
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" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"\n",
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" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
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},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# prepare sample for plotting\n",
"SAMPLE_LENGTH = 50\n",
"test_sample = test_results.sample( SAMPLE_LENGTH ).sort_values(by = 'prediction', ascending = False).reset_index()\n",
"\n",
"# plot results\n",
"plt.figure()\n",
"test_sample.prediction.plot( kind = 'bar', color = 'C0', width = 0.9, alpha = 0.3)\n",
"ticks, labels = plt.xticks( range(0, SAMPLE_LENGTH, 10), range(0, SAMPLE_LENGTH, 10))\n",
"\n",
"plt.errorbar( range(SAMPLE_LENGTH), test_sample.prediction, yerr = test_sample.total_std, \n",
" color = 'k', elinewidth = 1, capsize=1.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Data uncertainty')\n",
"\n",
"plt.errorbar( range(SAMPLE_LENGTH), test_sample.prediction, yerr = test_sample.model_std_rel_to_total, \n",
" color = 'r', elinewidth = 1, capsize=1.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Model uncertainty')\n",
"\n",
"\n",
"test_sample.target.plot( style = 'go', alpha = 0.5 )\n",
"# plt.title('Prediction and uncertainty of solar irradiation')\n",
"plt.legend(loc = 'upper right')\n",
"plt.xlabel('Sample (randomly selected)')\n",
"plt.ylabel('Prediction (in $kWh / m^2)$')\n",
"plt.xlim((-1, 50))\n",
"\n",
"plt.tight_layout()\n",
"# plt.savefig( os.path.join( 'pred_uncertainty_irrad_tst_new.png'), dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Tilt and aspect patterns for predicted values and uncertainty"
]
},
{
"cell_type": "code",
"execution_count": 266,
"metadata": {},
"outputs": [],
"source": [
"merged_results = test_results.merge(testing[['NEIGUNG', 'AUSRICHTUNG']], \n",
" left_on = 'DF_UID', right_index = True, how = 'left')"
]
},
{
"cell_type": "code",
"execution_count": 267,
"metadata": {},
"outputs": [],
"source": [
"merged_results['total_std_perc'] = merged_results.total_std / merged_results.prediction"
]
},
{
"cell_type": "code",
"execution_count": 268,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>target</th>\n",
" <th>prediction</th>\n",
" <th>model_std</th>\n",
" <th>data_std</th>\n",
" <th>total_std</th>\n",
" <th>data_std_rel_to_total</th>\n",
" <th>model_std_rel_to_total</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>total_std_perc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1001041.0</td>\n",
" <td>1124.0</td>\n",
" <td>1030.105617</td>\n",
" <td>142.829931</td>\n",
" <td>61.922971</td>\n",
" <td>155.675442</td>\n",
" <td>47.080583</td>\n",
" <td>108.594860</td>\n",
" <td>1</td>\n",
" <td>-51.0</td>\n",
" <td>0.151126</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>8720624.0</td>\n",
" <td>1431.0</td>\n",
" <td>1371.053704</td>\n",
" <td>59.213866</td>\n",
" <td>25.345624</td>\n",
" <td>64.410268</td>\n",
" <td>19.306153</td>\n",
" <td>45.104115</td>\n",
" <td>41</td>\n",
" <td>6.0</td>\n",
" <td>0.046979</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2671377.0</td>\n",
" <td>867.0</td>\n",
" <td>931.658432</td>\n",
" <td>75.201291</td>\n",
" <td>22.660883</td>\n",
" <td>78.541389</td>\n",
" <td>18.186978</td>\n",
" <td>60.354411</td>\n",
" <td>28</td>\n",
" <td>-128.0</td>\n",
" <td>0.084303</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>8826005.0</td>\n",
" <td>1337.0</td>\n",
" <td>1320.957118</td>\n",
" <td>70.414994</td>\n",
" <td>32.842632</td>\n",
" <td>77.697554</td>\n",
" <td>24.712869</td>\n",
" <td>52.984685</td>\n",
" <td>30</td>\n",
" <td>18.0</td>\n",
" <td>0.058819</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>3008353.0</td>\n",
" <td>1262.0</td>\n",
" <td>1206.295618</td>\n",
" <td>123.036708</td>\n",
" <td>48.113745</td>\n",
" <td>132.109666</td>\n",
" <td>37.138615</td>\n",
" <td>94.971051</td>\n",
" <td>41</td>\n",
" <td>-1.0</td>\n",
" <td>0.109517</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID target prediction model_std data_std total_std \\\n",
"0 1001041.0 1124.0 1030.105617 142.829931 61.922971 155.675442 \n",
"1 8720624.0 1431.0 1371.053704 59.213866 25.345624 64.410268 \n",
"2 2671377.0 867.0 931.658432 75.201291 22.660883 78.541389 \n",
"3 8826005.0 1337.0 1320.957118 70.414994 32.842632 77.697554 \n",
"4 3008353.0 1262.0 1206.295618 123.036708 48.113745 132.109666 \n",
"\n",
" data_std_rel_to_total model_std_rel_to_total NEIGUNG AUSRICHTUNG \\\n",
"0 47.080583 108.594860 1 -51.0 \n",
"1 19.306153 45.104115 41 6.0 \n",
"2 18.186978 60.354411 28 -128.0 \n",
"3 24.712869 52.984685 30 18.0 \n",
"4 37.138615 94.971051 41 -1.0 \n",
"\n",
" total_std_perc \n",
"0 0.151126 \n",
"1 0.046979 \n",
"2 0.084303 \n",
"3 0.058819 \n",
"4 0.109517 "
]
},
"execution_count": 268,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_results.head()"
]
},
{
"cell_type": "code",
"execution_count": 269,
"metadata": {},
"outputs": [],
"source": [
"# ADJUST FOR FLAT ROOFS\n",
"FLAT = -5.1\n",
"merged_results['tilt'] = merged_results.NEIGUNG\n",
"merged_results.loc[merged_results.NEIGUNG == 0, 'tilt'] = FLAT # NEEDED FOR PLOTTING"
]
},
{
"cell_type": "code",
"execution_count": 270,
"metadata": {},
"outputs": [],
"source": [
"ASP_ROUND = 10\n",
"TILT_ROUND = 10\n",
"merged_results['tilt_round'] = util.round_to_interval(merged_results.tilt, TILT_ROUND)\n",
"merged_results['aspect_round'] = util.round_to_interval(merged_results.AUSRICHTUNG, ASP_ROUND)"
]
},
{
"cell_type": "code",
"execution_count": 271,
"metadata": {},
"outputs": [],
"source": [
"results_mean = merged_results.groupby(['tilt_round', 'aspect_round']).mean()"
]
},
{
"cell_type": "code",
"execution_count": 276,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = results_mean['prediction']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Predicted annual $G_t$ (in $kWh/m^2$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('prediction_tilt_aspect.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 263,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = results_mean['target']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Target annual $G_t$ ($kWh/m^2$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('target_tilt_aspect.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 274,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = results_mean['total_std_perc'] * 100\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Relative uncertainty for $G_t$ (in %)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('total_std_perc_tilt_aspect.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 275,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<img 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = results_mean['total_std']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Uncertainty for $G_t$ (in $kWh/m^2$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('total_std_tilt_aspect.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predict for cities and compare potential"
]
},
{
"cell_type": "code",
"execution_count": 180,
"metadata": {},
"outputs": [],
"source": [
"x, t, X, T = get_data( training_data.sample(1e9), feature_names, label_name)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"estimator = set_estimators()\n",
"RF_unc = Uncertainty( estimator['RF'] )\n",
"RF_unc.fit(X, T)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model variance not given\n",
"Estimating model variance ... \n",
"Fitting model ...\n"
]
}
],
"source": [
"# set residual estimator and fit \n",
"RF_unc.residuals.set_params( n_estimators = n_est )\n",
"\n",
"tt = util.Timer()\n",
"residuals = RF_unc.fit_residuals( X, T )\n",
"tt.stop()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"city_pred = {}\n",
"for city in cities:\n",
" print(city)\n",
" # get prediction, model uncertainty and data uncertainty\n",
" x_tst, t_tst, X_tst, T_tst = get_data( city_data[city], feature_names, label_name)\n",
" \n",
" tt = util.Timer()\n",
" Y_tst, mUnc_tst = RF_unc.predict_model_uncertainty(X_tst)\n",
" dUnc_tst = RF_unc.predict_residuals(X_tst)\n",
" tt.stop()\n",
" \n",
" identifiers = shp(city_data[city].index.values)\n",
" test_results = pd.DataFrame( np.hstack([identifiers, shp(T_tst), shp(Y_tst), shp(mUnc_tst), shp(dUnc_tst) ]), \n",
" columns = ['DF_UID', 'target', 'prediction', 'model_std', 'data_std'])\n",
" \n",
" city_pred[city] = test_results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### SELECT SUITABLE ROOFS & APPLY SUITABILITY CRITERIA"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"GWR_cols = pd.read_csv('/Users/alinawalch/Documents/EPFL/data/GWR/Maske_EINZELD-GEB.csv').columns\n",
"GWR = pd.read_csv('/Users/alinawalch/Documents/EPFL/data/GWR/EPFL-150701-GEB.txt', usecols = ['EGID', 'GKAT'],\n",
" header = None, names = GWR_cols, sep = '\\t', encoding = 'cp1250' )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# merge all info\n",
"for city in cities:\n",
" city_pred[ city ] = city_pred[ city ].merge(city_data[ city ][['FLAECHE', 'NEIGUNG', 'AUSRICHTUNG', 'GWR_EGID']], \n",
" left_on = 'DF_UID', right_index = True, how = 'left')\n",
" \n",
" city_pred[ city ] = city_pred[ city ].merge(GWR, left_on = 'GWR_EGID', right_on = 'EGID', how = 'left') "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"city_pred[ city ].head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"city_suitable = {}\n",
"\n",
"for city in cities:\n",
" suited_roofs = city_pred[ city ][ (city_pred[ city ].FLAECHE >= 10) & (city_pred[ city ].target >= 1000) ]\n",
"\n",
" # define rules for roof categories\n",
" flat_roofs = suited_roofs.NEIGUNG <= 10\n",
" steep_roofs = suited_roofs.NEIGUNG > 10\n",
"\n",
" large_roofs = (suited_roofs.NEIGUNG <= 10) & (suited_roofs.FLAECHE >= 1000)\n",
" small_roofs = (suited_roofs.NEIGUNG <= 10) & (suited_roofs.FLAECHE < 1000)\n",
"\n",
" MFH = (suited_roofs.NEIGUNG <= 10) & (suited_roofs.GKAT == 1025)\n",
"\n",
" # compute untilization factor\n",
" suited_roofs['UF'] = 0\n",
" suited_roofs.loc[steep_roofs, 'UF'] = 0.7\n",
"\n",
" # for flat roofs, different logic applies for small and large roofs, and for multi-family-houses\n",
" suited_roofs.loc[small_roofs, 'UF'] = 0.7\n",
" suited_roofs.loc[large_roofs, 'UF'] = 0.8\n",
"\n",
" suited_roofs.loc[MFH, 'UF'] = suited_roofs[MFH].UF * 0.6\n",
"\n",
" suited_roofs['available_area'] = suited_roofs.UF * suited_roofs.FLAECHE\n",
"\n",
" # save results in dict\n",
" city_suitable[ city ] = suited_roofs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"city_suitable[ city ].head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Multiply everything with areas"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"city_suitable.keys()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for city, data in city_suitable.items():\n",
" data['total_std'] = np.sqrt( data['model_std']**2 + data['data_std']**2 )\n",
" \n",
" data['targ_kWh'] = data['target'] * data['FLAECHE']\n",
" data['pred_kWh'] = data['prediction'] * data['FLAECHE']\n",
" data['munc_kWh'] = data['model_std'] * data['FLAECHE']\n",
" data['dunc_kWh'] = data['data_std'] * data['FLAECHE']\n",
" data['tunc_kWh'] = data['total_std'] * data['FLAECHE']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get city totals"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results_GWh = city_suitable[ city ].sum() / 1e6"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results_GWh"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Compute PV potential for communes and get inhabitants"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"eff = 0.17*0.8\n",
"cols = ['FLAECHE', 'available_area', 'targ_E_GWh', 'pred_E_GWh', 'munc_E_GWh', 'dunc_E_GWh', 'tunc_E_GWh']\n",
"results = pd.DataFrame( data = [], columns = cols )\n",
"\n",
"for city, data in city_suitable.items():\n",
" results_GWh = data.sum() / 1e6\n",
" \n",
" new_row = pd.DataFrame( data = [[results_GWh.FLAECHE, results_GWh.available_area, \n",
" results_GWh.targ_kWh * eff, results_GWh.pred_kWh * eff,\n",
" results_GWh.munc_kWh * eff, results_GWh.dunc_kWh * eff, \n",
" results_GWh.tunc_kWh * eff]], \n",
" columns = cols, index = [city] )\n",
" \n",
" results = results.append( new_row )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results['dunc_rel_to_tunc'] = (results['tunc_E_GWh'] * results['dunc_E_GWh'] \n",
" / (results['dunc_E_GWh'] + results['munc_E_GWh'] ))\n",
"results['munc_rel_to_tunc'] = (results['tunc_E_GWh'] * results['munc_E_GWh'] \n",
" / (results['dunc_E_GWh'] + results['munc_E_GWh'] ))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# get number of inhabitants\n",
"results = results.merge(commune_data[['NAME', 'EINWOHNERZ']], \n",
" left_index = True, right_on = 'NAME', how = 'left').dropna().set_index('NAME')\n",
"results = results.sort_values('EINWOHNERZ', ascending = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# BAR CHART"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# plot results\n",
"plt.figure()\n",
"\n",
"targ_idx = np.asarray(range(0, len(results))) * 2.5\n",
"pred_idx = targ_idx + 1\n",
"\n",
"plt.bar(targ_idx, results.targ_E_GWh , color = 'C1', width = 1.0, alpha = 0.8, label = 'Target')\n",
"plt.bar(pred_idx, results.pred_E_GWh , color = 'C0', width = 1.0, alpha = 0.5, label = 'Prediction')\n",
"\n",
"plt.errorbar( pred_idx, results.pred_E_GWh, yerr = results.tunc_E_GWh, \n",
" color = 'k', elinewidth = 2, capsize=2.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Data uncertainty')\n",
"\n",
"plt.errorbar( pred_idx, results.pred_E_GWh, yerr = results.munc_rel_to_tunc, \n",
" color = 'r', elinewidth = 2, capsize=2.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Model uncertainty')\n",
"\n",
"\n",
"plt.legend(loc = 'upper right')\n",
"plt.ylabel('PV potential per city (in $GWh)$')\n",
"\n",
"plt.xticks( targ_idx + 0.5, results.index )\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig( os.path.join( 'pred_cities_allDataTrn.png'), dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### PV potential per inhabitants"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results_per_inhab = results / results[['EINWOHNERZ']].values * 1e6"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# plot results\n",
"plt.figure()\n",
"\n",
"targ_idx = np.asarray(range(0, len(results_per_inhab))) * 2.5\n",
"pred_idx = targ_idx + 1\n",
"\n",
"plt.bar(targ_idx, results_per_inhab.targ_E_GWh , color = 'C1', width = 1.0, alpha = 0.8, label = 'Target')\n",
"plt.bar(pred_idx, results_per_inhab.pred_E_GWh , color = 'C0', width = 1.0, alpha = 0.5, label = 'Prediction')\n",
"\n",
"plt.errorbar( pred_idx, results_per_inhab.pred_E_GWh, yerr = results_per_inhab.tunc_E_GWh, \n",
" color = 'k', elinewidth = 2, capsize=2.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Data uncertainty')\n",
"\n",
"plt.errorbar( pred_idx, results_per_inhab.pred_E_GWh, yerr = results_per_inhab.munc_rel_to_tunc, \n",
" color = 'r', elinewidth = 2, capsize=2.5, \n",
" fmt = '.', markersize = 1, \n",
" label = 'Model uncertainty')\n",
"\n",
"\n",
"plt.legend() # loc = 'upper right'\n",
"plt.ylabel('PV potential per inhabitant (in $kWh)$')\n",
"\n",
"plt.xticks( targ_idx + 0.5, results_per_inhab.index )\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig( os.path.join( 'pred_cities_per_inhab_allDataTrn.png'), dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get city information"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>NAME</th>\n",
" <th>EINWOHNERZ</th>\n",
" <th>GEM_FLAECH</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Davos</td>\n",
" <td>10937.0</td>\n",
" <td>28400.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77</th>\n",
" <td>Zürich</td>\n",
" <td>409241.0</td>\n",
" <td>9188.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>83</th>\n",
" <td>Lugano</td>\n",
" <td>63494.0</td>\n",
" <td>8621.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>296</th>\n",
" <td>Luzern</td>\n",
" <td>81401.0</td>\n",
" <td>3740.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Basel</td>\n",
" <td>171513.0</td>\n",
" <td>2385.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1742</th>\n",
" <td>Interlaken</td>\n",
" <td>5592.0</td>\n",
" <td>427.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" NAME EINWOHNERZ GEM_FLAECH\n",
"6 Davos 10937.0 28400.0\n",
"77 Zürich 409241.0 9188.0\n",
"83 Lugano 63494.0 8621.0\n",
"296 Luzern 81401.0 3740.0\n",
"396 Basel 171513.0 2385.0\n",
"1742 Interlaken 5592.0 427.0"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"commune_data.loc[commune_data.NAME.isin(cities),['NAME', 'EINWOHNERZ', 'GEM_FLAECH']].dropna()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Luzern\n",
"Number of buildings: 5940\n",
"Roof area: 3.25\n",
"Roof area per inhabitant: 39.95\n",
"\n",
"Zürich\n",
"Number of buildings: 46888\n",
"Roof area: 13.77\n",
"Roof area per inhabitant: 33.65\n",
"\n",
"Basel\n",
"Number of buildings: 11122\n",
"Roof area: 6.27\n",
"Roof area per inhabitant: 36.55\n",
"\n",
"Lugano\n",
"Number of buildings: 10052\n",
"Roof area: 3.10\n",
"Roof area per inhabitant: 48.85\n",
"\n",
"Interlaken\n",
"Number of buildings: 1025\n",
"Roof area: 0.48\n",
"Roof area per inhabitant: 85.06\n",
"\n",
"Davos\n",
"Number of buildings: 2582\n",
"Roof area: 1.21\n",
"Roof area per inhabitant: 110.49\n",
"\n"
]
}
],
"source": [
"# get remaining information\n",
"for city, data in city_data.items():\n",
" n_buildings = len(data.GWR_EGID.unique())\n",
" roof_area = data.FLAECHE.sum() / 1e6\n",
" \n",
" inhab = commune_data.loc[commune_data.NAME == city, 'EINWOHNERZ'].values\n",
" roof_area_per_inhab = roof_area / inhab * 1e6\n",
" \n",
" print(city)\n",
" print('Number of buildings: %d' %n_buildings)\n",
" print('Roof area: %.2f' %roof_area)\n",
" print('Roof area per inhabitant: %.2f\\n' %roof_area_per_inhab[0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.7"
+ "version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/Visualisation/plot_potentials.ipynb b/Visualisation/plot_potentials.ipynb
index 1f01192..51515a0 100644
--- a/Visualisation/plot_potentials.ipynb
+++ b/Visualisation/plot_potentials.ipynb
@@ -1,13064 +1,13064 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" from ._conv import register_converters as _register_converters\n"
]
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import xarray as xr\n",
"\n",
"%matplotlib notebook\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.colors import LinearSegmentedColormap\n",
"import matplotlib\n",
"\n",
"import util\n",
"\n",
"import calendar\n",
"import sys\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"colorsRGB = [(25,165,110),\n",
" (65,195,100),\n",
" (105,219,77),\n",
" (183,233,81),\n",
" (249,239,88),\n",
" (250,201,53),\n",
" (246,135,26),\n",
" (220,82,7),\n",
" (193,31,4)]\n",
"colors = []\n",
"for row in colorsRGB:\n",
" colors.append(tuple([i/255.0 for i in row]))\n",
"cm = LinearSegmentedColormap.from_list('GYR', colors, N=500)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"colorsRGB = [(47,111,191),\n",
" (51,148,190),\n",
" (65,195,153),\n",
" (105,219,77),\n",
" (183,233,81),\n",
" (249,239,88),\n",
" (250,201,53),\n",
" (246,135,26),\n",
" (220,82,7),\n",
" (193,31,4)]\n",
"colors = []\n",
"for row in colorsRGB:\n",
" colors.append(tuple([i/255.0 for i in row]))\n",
" \n",
"cm_PV = LinearSegmentedColormap.from_list('radiation', colors, N=500)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def get_month(df, month):\n",
" return df.where( df.month == month, drop = True )"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def rad(angle):\n",
" return angle * np.pi/180"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"path = '/Volumes/Seagate Backup Plus Drive/DOKUMENTE/EPFL/data/Results/PV_w_uncertainty'"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"ROOF_fp = os.path.join(path, 'CH_ROOFS_all_replaced.csv')\n",
"ROOFS = pd.read_csv( ROOF_fp, usecols = ['DF_UID', 'FLAECHE', 'NEIGUNG', 'AUSRICHTUNG'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## PLOT UNCERTAINTY OF TILTED RADIATION"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"fp = '/work/hyenergy/output/solar_potential/technical_potential/pv_potential_ELM50_1000_dhm25_200_roofs_yearly.csv'\n",
"fp = os.path.join(path, 'var_Gt_all.nc')\n",
"Gt_unc_all = xr.open_mfdataset(fp, chunks = {'DF_UID' : 10000})"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# Gt_unc_annual = util.get_yearly_sum( Gt_unc_all, 'sigma_Gt_dep' )\n",
"# Gt_unc_annual_df = Gt_unc_annual.rename('sigma_Gt_annual').to_dataframe()\n",
"# Gt_unc_annual_df.to_csv(os.path.join(path, 'sigma_Gt_annual.csv'))"
]
},
{
"cell_type": "code",
"execution_count": 191,
"metadata": {},
"outputs": [],
"source": [
"Gt_unc_annual_df = pd.read_csv( os.path.join(path, 'sigma_Gt_annual.csv') )"
]
},
{
"cell_type": "code",
"execution_count": 194,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x38714e2b0>"
]
},
"execution_count": 194,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plt.figure()\n",
"(Gt_unc_annual_df.sigma_Gt_annual / 1000).hist()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"Gt = xr.open_mfdataset( os.path.join(path, 'tilted_irradiance_ELM50_1000_dhm25_200_interp_SVF_nobias.nc'), \n",
" chunks = {'DF_UID' : 10000})"
]
},
{
"cell_type": "code",
"execution_count": 140,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * DF_UID (DF_UID) int64 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 ...\n",
"Data variables:\n",
" tilted_irradiance (DF_UID, timestamp) float64 dask.array<shape=(9639231, 146), chunksize=(10000, 146)>\n",
" yearly_kWh_m2 (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(10000,)>"
]
},
"execution_count": 140,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Gt"
]
},
{
"cell_type": "code",
"execution_count": 195,
"metadata": {},
"outputs": [],
"source": [
"annual_Gt = Gt.yearly_kWh_m2.to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 196,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly = Gt_unc_annual_df.merge(annual_Gt, on = 'DF_UID')\n",
"PV_yearly['unc_perc'] = (PV_yearly.sigma_Gt_annual/1000) / PV_yearly.yearly_kWh_m2"
]
},
{
"cell_type": "code",
"execution_count": 197,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly = PV_yearly.merge(ROOFS[['DF_UID', 'NEIGUNG', 'AUSRICHTUNG']], on = 'DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 198,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>sigma_Gt_annual</th>\n",
" <th>yearly_kWh_m2</th>\n",
" <th>unc_perc</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>309039.122076</td>\n",
" <td>1210.184846</td>\n",
" <td>0.255365</td>\n",
" <td>37</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>85539.804185</td>\n",
" <td>474.558362</td>\n",
" <td>0.180251</td>\n",
" <td>44</td>\n",
" <td>-170.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>239814.424285</td>\n",
" <td>951.934814</td>\n",
" <td>0.251923</td>\n",
" <td>12</td>\n",
" <td>-80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>259121.815839</td>\n",
" <td>1029.797436</td>\n",
" <td>0.251624</td>\n",
" <td>33</td>\n",
" <td>-80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>188438.261899</td>\n",
" <td>711.799309</td>\n",
" <td>0.264735</td>\n",
" <td>35</td>\n",
" <td>100.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID sigma_Gt_annual yearly_kWh_m2 unc_perc NEIGUNG AUSRICHTUNG\n",
"0 1 309039.122076 1210.184846 0.255365 37 10.0\n",
"1 2 85539.804185 474.558362 0.180251 44 -170.0\n",
"2 3 239814.424285 951.934814 0.251923 12 -80.0\n",
"3 4 259121.815839 1029.797436 0.251624 33 -80.0\n",
"4 5 188438.261899 711.799309 0.264735 35 100.0"
]
},
"execution_count": 198,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 199,
"metadata": {},
"outputs": [],
"source": [
"# ADJUST FOR FLAT ROOFS\n",
"FLAT = -5.1\n",
"PV_yearly['tilt'] = PV_yearly.NEIGUNG\n",
"PV_yearly.loc[PV_yearly.NEIGUNG == 0, 'tilt'] = FLAT # NEEDED FOR PLOTTING"
]
},
{
"cell_type": "code",
"execution_count": 200,
"metadata": {},
"outputs": [],
"source": [
"ASP_ROUND = 10\n",
"TILT_ROUND = 10\n",
"PV_yearly['tilt_round'] = util.round_to_interval(PV_yearly.tilt, TILT_ROUND)\n",
"PV_yearly['aspect_round'] = util.round_to_interval(PV_yearly.AUSRICHTUNG, ASP_ROUND)"
]
},
{
"cell_type": "code",
"execution_count": 201,
"metadata": {},
"outputs": [],
"source": [
"PV_mean = PV_yearly.groupby(['tilt_round', 'aspect_round']).mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Plot final version of tilted irradiance"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = PV_mean['yearly_kWh_m2']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Annual tilted radiation $G_t$ ($kWh/m^2$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('annual_Gt.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Uncertainty as a proportion of tilted irradiance"
]
},
{
"cell_type": "code",
"execution_count": 203,
"metadata": {},
"outputs": [],
"source": [
"PV_mean.loc[-10,0]['unc_perc'] = PV_mean.loc[30,0]['unc_perc']"
]
},
{
"cell_type": "code",
"execution_count": 204,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_var = PV_mean['unc_perc']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"# prepare data\n",
"data = plot_array.values\n",
"# theta = np.append(plot_array.aspect_round * np.pi / 180, 2*np.pi) + (0.5 * ASP_ROUND * np.pi / 180)\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"# ax.set_rlim(-10, 70)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Relative uncertainty of annual $G_t$ ($\\sigma_{Gt}/G_t$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('relative_unc_Gt.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Final PV potential"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"EPV = xr.open_mfdataset( os.path.join(path, 'pv_potential_ELM50_1000_dhm25_200_SVF_eff_nobias.nc'), \n",
" chunks = {'DF_UID' : 10000})"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
"Coordinates:\n",
" * DF_UID (DF_UID) int64 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 17 18 ...\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
"Data variables:\n",
" pv_potential (DF_UID, timestamp) float32 dask.array<shape=(9639231, 143), chunksize=(10000, 143)>\n",
" yearly_PV_kWh (DF_UID) float32 dask.array<shape=(9639231,), chunksize=(10000,)>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"EPV"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"annual_EPV = EPV.yearly_PV_kWh.to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"unc_EPV = xr.open_mfdataset( os.path.join(path, 'unc_pv_potential/*'), \n",
" chunks = {'DF_UID' : 10000})"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 143)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * DF_UID (DF_UID) int64 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 17 18 ...\n",
"Data variables:\n",
" sigma_PV (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(10000, 143)>\n",
" var_PV (DF_UID, timestamp) float64 dask.array<shape=(9639231, 143), chunksize=(10000, 143)>\n",
" yearly_std_PV (DF_UID) float64 dask.array<shape=(9639231,), chunksize=(10000,)>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"unc_EPV"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"unc_EPV_annual = unc_EPV.yearly_std_PV.to_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly = unc_EPV_annual.merge(annual_EPV, on = 'DF_UID')\n",
"PV_yearly['unc_perc'] = (PV_yearly.yearly_std_PV / PV_yearly.yearly_PV_kWh).fillna(0)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly = PV_yearly.merge(ROOFS, on = 'DF_UID')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>yearly_std_PV</th>\n",
" <th>yearly_PV_kWh</th>\n",
" <th>unc_perc</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>324.268393</td>\n",
" <td>239.800095</td>\n",
" <td>1.352245</td>\n",
" <td>15.948816</td>\n",
" <td>37</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>13.730555</td>\n",
" <td>44</td>\n",
" <td>-170.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2071.079104</td>\n",
" <td>3891.605469</td>\n",
" <td>0.532191</td>\n",
" <td>63.437476</td>\n",
" <td>12</td>\n",
" <td>-80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1044.604313</td>\n",
" <td>2022.193970</td>\n",
" <td>0.516570</td>\n",
" <td>38.368910</td>\n",
" <td>33</td>\n",
" <td>-80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>702.281552</td>\n",
" <td>1030.456787</td>\n",
" <td>0.681525</td>\n",
" <td>36.403273</td>\n",
" <td>35</td>\n",
" <td>100.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID yearly_std_PV yearly_PV_kWh unc_perc FLAECHE NEIGUNG \\\n",
"0 1 324.268393 239.800095 1.352245 15.948816 37 \n",
"1 2 0.000000 0.000000 0.000000 13.730555 44 \n",
"2 3 2071.079104 3891.605469 0.532191 63.437476 12 \n",
"3 4 1044.604313 2022.193970 0.516570 38.368910 33 \n",
"4 5 702.281552 1030.456787 0.681525 36.403273 35 \n",
"\n",
" AUSRICHTUNG \n",
"0 10.0 \n",
"1 -170.0 \n",
"2 -80.0 \n",
"3 -80.0 \n",
"4 100.0 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly['PV_norm'] = PV_yearly.yearly_PV_kWh / PV_yearly.FLAECHE\n",
"PV_yearly['PV_std_norm'] = PV_yearly.yearly_std_PV / PV_yearly.FLAECHE\n",
"PV_yearly['unc_perc_norm'] = PV_yearly.PV_std_norm / PV_yearly.PV_norm"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# ADJUST FOR FLAT ROOFS\n",
"FLAT = -5.1\n",
"PV_yearly['tilt'] = PV_yearly.NEIGUNG\n",
"PV_yearly.loc[PV_yearly.NEIGUNG == 0, 'tilt'] = FLAT # NEEDED FOR PLOTTING"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"ASP_ROUND = 10\n",
"TILT_ROUND = 10\n",
"PV_yearly['tilt_round'] = util.round_to_interval(PV_yearly.tilt, TILT_ROUND)\n",
"PV_yearly['aspect_round'] = util.round_to_interval(PV_yearly.AUSRICHTUNG, ASP_ROUND)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"PV_mean = PV_yearly.groupby(['tilt_round', 'aspect_round']).mean()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"scrolled": false
},
"outputs": [
{
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" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# CONSIDER ONLY SUITABLE AREAS!!!!!\n",
"# prepare data\n",
"plot_var = PV_mean['PV_norm']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"data = plot_array.values\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"# cb.set_label('Uncertainty on annual tilted radiation (kWh/m2)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"# plt.savefig('PV_slope_azimuth_suitable_flat.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# prepare data\n",
"plot_var = PV_mean['yearly_PV_kWh']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"data = plot_array.values\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Annual PV potential per roof surface (kWh)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('PV_slope_azimuth.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Potential for suitable roof surfaces"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"avail_area = pd.read_csv( os.path.join(path, 'PRED_available_area_unc_filled.csv'), \n",
" usecols = ['DF_UID', 'available_area'] )"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly = PV_yearly.merge( avail_area, on = 'DF_UID', how = 'left' )"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly['PV_norm_avail'] = PV_yearly.yearly_PV_kWh / PV_yearly.available_area"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>yearly_std_PV</th>\n",
" <th>yearly_PV_kWh</th>\n",
" <th>unc_perc</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>PV_norm</th>\n",
" <th>PV_std_norm</th>\n",
" <th>unc_perc_norm</th>\n",
" <th>tilt</th>\n",
" <th>tilt_round</th>\n",
" <th>aspect_round</th>\n",
" <th>available_area</th>\n",
" <th>PV_norm_avail</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>324.268393</td>\n",
" <td>239.800095</td>\n",
" <td>1.352245</td>\n",
" <td>15.948816</td>\n",
" <td>37</td>\n",
" <td>10.0</td>\n",
" <td>15.035605</td>\n",
" <td>20.331816</td>\n",
" <td>1.352245</td>\n",
" <td>37.0</td>\n",
" <td>40.0</td>\n",
" <td>10.0</td>\n",
" <td>1.437423</td>\n",
" <td>166.826355</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>13.730555</td>\n",
" <td>44</td>\n",
" <td>-170.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>44.0</td>\n",
" <td>40.0</td>\n",
" <td>-170.0</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2071.079104</td>\n",
" <td>3891.605469</td>\n",
" <td>0.532191</td>\n",
" <td>63.437476</td>\n",
" <td>12</td>\n",
" <td>-80.0</td>\n",
" <td>61.345528</td>\n",
" <td>32.647564</td>\n",
" <td>0.532191</td>\n",
" <td>12.0</td>\n",
" <td>10.0</td>\n",
" <td>-80.0</td>\n",
" <td>29.414390</td>\n",
" <td>132.302778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1044.604313</td>\n",
" <td>2022.193970</td>\n",
" <td>0.516570</td>\n",
" <td>38.368910</td>\n",
" <td>33</td>\n",
" <td>-80.0</td>\n",
" <td>52.703972</td>\n",
" <td>27.225280</td>\n",
" <td>0.516570</td>\n",
" <td>33.0</td>\n",
" <td>30.0</td>\n",
" <td>-80.0</td>\n",
" <td>14.224941</td>\n",
" <td>142.158335</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>702.281552</td>\n",
" <td>1030.456787</td>\n",
" <td>0.681525</td>\n",
" <td>36.403273</td>\n",
" <td>35</td>\n",
" <td>100.0</td>\n",
" <td>28.306707</td>\n",
" <td>19.291715</td>\n",
" <td>0.681525</td>\n",
" <td>35.0</td>\n",
" <td>40.0</td>\n",
" <td>100.0</td>\n",
" <td>10.472945</td>\n",
" <td>98.392264</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID yearly_std_PV yearly_PV_kWh unc_perc FLAECHE NEIGUNG \\\n",
"0 1 324.268393 239.800095 1.352245 15.948816 37 \n",
"1 2 0.000000 0.000000 0.000000 13.730555 44 \n",
"2 3 2071.079104 3891.605469 0.532191 63.437476 12 \n",
"3 4 1044.604313 2022.193970 0.516570 38.368910 33 \n",
"4 5 702.281552 1030.456787 0.681525 36.403273 35 \n",
"\n",
" AUSRICHTUNG PV_norm PV_std_norm unc_perc_norm tilt tilt_round \\\n",
"0 10.0 15.035605 20.331816 1.352245 37.0 40.0 \n",
"1 -170.0 0.000000 0.000000 NaN 44.0 40.0 \n",
"2 -80.0 61.345528 32.647564 0.532191 12.0 10.0 \n",
"3 -80.0 52.703972 27.225280 0.516570 33.0 30.0 \n",
"4 100.0 28.306707 19.291715 0.681525 35.0 40.0 \n",
"\n",
" aspect_round available_area PV_norm_avail \n",
"0 10.0 1.437423 166.826355 \n",
"1 -170.0 0.000000 NaN \n",
"2 -80.0 29.414390 132.302778 \n",
"3 -80.0 14.224941 142.158335 \n",
"4 100.0 10.472945 98.392264 "
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_yearly.head()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"PV_suitable = PV_yearly[(abs(PV_yearly.AUSRICHTUNG) <= 90) &(PV_yearly.available_area >= 8) ] #\n",
"PV_area = PV_yearly[(PV_yearly.available_area >= 8) ] #"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"PV_suitable_mean = PV_suitable.groupby(['tilt_round', 'aspect_round']).mean()\n",
"PV_area_mean = PV_area.groupby(['tilt_round', 'aspect_round']).mean()"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [
{
"data": {
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"window.mpl = {};\n",
"\n",
"\n",
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" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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"\n",
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" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
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" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
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" 'text-align: center; padding: 3px;\"/>');\n",
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"\tthis.context.webkitBackingStorePixelRatio ||\n",
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"\tthis.context.oBackingStorePixelRatio ||\n",
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" fig.request_resize(ui.size.width, ui.size.height);\n",
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" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
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" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
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"\n",
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"\n",
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"\n",
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"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
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"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
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" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
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" }\n",
"\n",
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" var name = mpl.toolbar_items[toolbar_ind][0];\n",
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" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
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"\n",
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" icon_img.addClass('ui-corner-all');\n",
"\n",
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" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
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" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
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"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
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" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
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" y1 = Math.floor(y1) + 0.5;\n",
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" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
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" // Updates the figure title.\n",
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"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
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" switch(cursor)\n",
" {\n",
" case 0:\n",
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" break;\n",
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" break;\n",
" case 2:\n",
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" break;\n",
" }\n",
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"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
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"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
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" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
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"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
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"\n",
" /* Free the memory for the previous frames */\n",
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"\n",
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" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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"<IPython.core.display.Javascript object>"
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# prepare data\n",
"plot_var = PV_area_mean['PV_norm']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"data = plot_array.values\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = 0\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Normalized annual PV potential ($kWh/m^2_{roof}$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('PV_slope_azimuth_suitable_norm.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Uncertainty"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# prepare data\n",
"plot_var = PV_area_mean['yearly_std_PV']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"data = plot_array.values\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = None\n",
"VMAX = None\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar() # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Uncertainty for annual PV potential ($kWh$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('PV_uncertainty.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
{
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# prepare data\n",
"plot_var = PV_area_mean['yearly_std_PV'] / PV_area_mean['yearly_PV_kWh']\n",
"plot_array = plot_var.to_xarray()\n",
"\n",
"plot_array['tilt_round' == FLAT] = plot_array['tilt_round' == FLAT].mean()\n",
"\n",
"theta = plot_array.aspect_round * np.pi / 180 - (0.5 * ASP_ROUND * np.pi / 180)\n",
"tilts = plot_array.tilt_round\n",
"\n",
"data = plot_array.values\n",
"X, Y = np.meshgrid( theta, tilts )\n",
"\n",
"# SET PROPERTIES\n",
"VMIN = 0.2\n",
"VMAX = 0.8\n",
" \n",
"plt.figure()\n",
"ax = plt.subplot(projection='polar')\n",
"ax.set_theta_zero_location('S')\n",
"ax.set_theta_direction(-1)\n",
"\n",
"plt.pcolor(X, Y, data, cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"cb = plt.colorbar(extend = 'max') # extend = get_cbar_extent( data, VMIN, VMAX )\n",
"cb.set_label('Relative uncertainty of annual $E_{PV}$ ($\\sigma_{PV}/E_{PV}$)')\n",
"\n",
"# FORMATTING\n",
"xticks = ['S', 'SW', 'W', 'NW', 'N', 'NE', 'E', 'SE']\n",
"yticks = [str(int(tilt)) + '°' for tilt in ax.get_yticks()]\n",
"ax.set_xticklabels( xticks )\n",
"ax.set_yticklabels( yticks )\n",
"ax.text(60,80, 'Tilt angle')\n",
"\n",
"ax.set_rlabel_position(200) # get radial labels away from plotted line\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"plt.savefig('PV_unc_relative_asp_tilt.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Plot by roof size and tilt"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"PV_yearly['area_log'] = np.log10(PV_yearly.FLAECHE)\n",
"PV_yearly['area_log_round'] = util.round_to_interval(PV_yearly.area_log, 0.2)\n",
"PV_yearly['area_log_round'] = np.minimum(np.maximum(PV_yearly.area_log_round, 0.7), 3.2)\n",
"\n",
"PV_yearly['tilt_round'] = util.round_to_interval(PV_yearly.NEIGUNG, 5)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"PV_suitable = PV_yearly[(abs(PV_yearly.AUSRICHTUNG) <= 90) &(PV_yearly.available_area >= 8) ] #\n",
"PV_area = PV_yearly[(PV_yearly.available_area >= 8) ] #"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2699240"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(PV_suitable)"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"DF_UID 12902.292384\n",
"yearly_std_PV 9.026094\n",
"yearly_PV_kWh 24.579205\n",
"unc_perc 0.001242\n",
"FLAECHE 0.345530\n",
"NEIGUNG 0.062100\n",
"AUSRICHTUNG 0.005650\n",
"PV_norm 0.177667\n",
"PV_std_norm 0.075837\n",
"unc_perc_norm 0.001242\n",
"tilt 0.060014\n",
"tilt_round 0.062092\n",
"aspect_round 0.005671\n",
"available_area 0.150671\n",
"PV_norm_avail 0.435311\n",
"area_log 0.005249\n",
"area_log_round 0.005246\n",
"dtype: float64"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_suitable.sum()/1e9"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>yearly_std_PV</th>\n",
" <th>yearly_PV_kWh</th>\n",
" <th>unc_perc</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>PV_norm</th>\n",
" <th>PV_std_norm</th>\n",
" <th>unc_perc_norm</th>\n",
" <th>tilt</th>\n",
" <th>aspect_round</th>\n",
" <th>available_area</th>\n",
" <th>PV_norm_avail</th>\n",
" <th>area_log</th>\n",
" </tr>\n",
" <tr>\n",
" <th>area_log_round</th>\n",
" <th>tilt_round</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">0.7</th>\n",
" <th>0.0</th>\n",
" <td>6.311366e+06</td>\n",
" <td>0.077004</td>\n",
" <td>0.020694</td>\n",
" <td>0.012311</td>\n",
" <td>1.345483</td>\n",
" <td>0.608299</td>\n",
" <td>-0.285763</td>\n",
" <td>0.004602</td>\n",
" <td>0.017021</td>\n",
" <td>4.888975</td>\n",
" <td>-2.418045</td>\n",
" <td>-0.290222</td>\n",
" <td>0.000146</td>\n",
" <td>147.100725</td>\n",
" <td>-0.359284</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>5.185035e+06</td>\n",
" <td>0.066672</td>\n",
" <td>0.028715</td>\n",
" <td>0.004395</td>\n",
" <td>0.794718</td>\n",
" <td>5.047209</td>\n",
" <td>-0.032425</td>\n",
" <td>0.006158</td>\n",
" <td>0.014265</td>\n",
" <td>2.393938</td>\n",
" <td>5.047209</td>\n",
" <td>-0.038874</td>\n",
" <td>0.000216</td>\n",
" <td>133.153006</td>\n",
" <td>-0.590664</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>5.277349e+06</td>\n",
" <td>0.070311</td>\n",
" <td>0.028216</td>\n",
" <td>0.007391</td>\n",
" <td>1.110745</td>\n",
" <td>9.967286</td>\n",
" <td>0.559539</td>\n",
" <td>0.006090</td>\n",
" <td>0.015131</td>\n",
" <td>3.187717</td>\n",
" <td>9.967286</td>\n",
" <td>0.565373</td>\n",
" <td>0.000217</td>\n",
" <td>130.846158</td>\n",
" <td>-0.358124</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15.0</th>\n",
" <td>5.253403e+06</td>\n",
" <td>0.073288</td>\n",
" <td>0.021203</td>\n",
" <td>0.016880</td>\n",
" <td>1.286099</td>\n",
" <td>14.976086</td>\n",
" <td>1.513717</td>\n",
" <td>0.004517</td>\n",
" <td>0.015590</td>\n",
" <td>4.332349</td>\n",
" <td>14.976086</td>\n",
" <td>1.533664</td>\n",
" <td>0.000167</td>\n",
" <td>133.515244</td>\n",
" <td>-0.264767</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20.0</th>\n",
" <td>5.634215e+06</td>\n",
" <td>0.085869</td>\n",
" <td>0.023149</td>\n",
" <td>0.027982</td>\n",
" <td>1.564211</td>\n",
" <td>20.034149</td>\n",
" <td>2.244052</td>\n",
" <td>0.004952</td>\n",
" <td>0.018351</td>\n",
" <td>5.716406</td>\n",
" <td>20.034149</td>\n",
" <td>2.253861</td>\n",
" <td>0.000182</td>\n",
" <td>132.516750</td>\n",
" <td>-0.139866</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DF_UID yearly_std_PV yearly_PV_kWh \\\n",
"area_log_round tilt_round \n",
"0.7 0.0 6.311366e+06 0.077004 0.020694 \n",
" 5.0 5.185035e+06 0.066672 0.028715 \n",
" 10.0 5.277349e+06 0.070311 0.028216 \n",
" 15.0 5.253403e+06 0.073288 0.021203 \n",
" 20.0 5.634215e+06 0.085869 0.023149 \n",
"\n",
" unc_perc FLAECHE NEIGUNG AUSRICHTUNG \\\n",
"area_log_round tilt_round \n",
"0.7 0.0 0.012311 1.345483 0.608299 -0.285763 \n",
" 5.0 0.004395 0.794718 5.047209 -0.032425 \n",
" 10.0 0.007391 1.110745 9.967286 0.559539 \n",
" 15.0 0.016880 1.286099 14.976086 1.513717 \n",
" 20.0 0.027982 1.564211 20.034149 2.244052 \n",
"\n",
" PV_norm PV_std_norm unc_perc_norm tilt \\\n",
"area_log_round tilt_round \n",
"0.7 0.0 0.004602 0.017021 4.888975 -2.418045 \n",
" 5.0 0.006158 0.014265 2.393938 5.047209 \n",
" 10.0 0.006090 0.015131 3.187717 9.967286 \n",
" 15.0 0.004517 0.015590 4.332349 14.976086 \n",
" 20.0 0.004952 0.018351 5.716406 20.034149 \n",
"\n",
" aspect_round available_area PV_norm_avail \\\n",
"area_log_round tilt_round \n",
"0.7 0.0 -0.290222 0.000146 147.100725 \n",
" 5.0 -0.038874 0.000216 133.153006 \n",
" 10.0 0.565373 0.000217 130.846158 \n",
" 15.0 1.533664 0.000167 133.515244 \n",
" 20.0 2.253861 0.000182 132.516750 \n",
"\n",
" area_log \n",
"area_log_round tilt_round \n",
"0.7 0.0 -0.359284 \n",
" 5.0 -0.590664 \n",
" 10.0 -0.358124 \n",
" 15.0 -0.264767 \n",
" 20.0 -0.139866 "
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_grouped_all = PV_yearly.groupby(['area_log_round','tilt_round']).mean()\n",
"PV_grouped_all.head()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"PV_grouped = PV_suitable.groupby(['area_log_round','tilt_round']).mean()"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"PV_area_grouped = PV_area.groupby(['area_log_round', 'tilt_round']).mean()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>DF_UID</th>\n",
" <th>yearly_std_PV</th>\n",
" <th>yearly_PV_kWh</th>\n",
" <th>unc_perc</th>\n",
" <th>FLAECHE</th>\n",
" <th>NEIGUNG</th>\n",
" <th>AUSRICHTUNG</th>\n",
" <th>PV_norm</th>\n",
" <th>PV_std_norm</th>\n",
" <th>unc_perc_norm</th>\n",
" <th>tilt</th>\n",
" <th>aspect_round</th>\n",
" <th>available_area</th>\n",
" <th>PV_norm_avail</th>\n",
" <th>area_log</th>\n",
" </tr>\n",
" <tr>\n",
" <th>area_log_round</th>\n",
" <th>tilt_round</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1.2</th>\n",
" <th>20.0</th>\n",
" <td>4.922855e+06</td>\n",
" <td>737.396294</td>\n",
" <td>1484.851929</td>\n",
" <td>0.496931</td>\n",
" <td>19.671486</td>\n",
" <td>21.000000</td>\n",
" <td>-4.000000</td>\n",
" <td>75.482643</td>\n",
" <td>37.485429</td>\n",
" <td>0.496931</td>\n",
" <td>21.000000</td>\n",
" <td>-5.000000</td>\n",
" <td>8.222259</td>\n",
" <td>180.579360</td>\n",
" <td>1.293837</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"12\" valign=\"top\">1.4</th>\n",
" <th>0.0</th>\n",
" <td>4.991159e+06</td>\n",
" <td>846.543206</td>\n",
" <td>1276.234863</td>\n",
" <td>0.666533</td>\n",
" <td>30.121106</td>\n",
" <td>1.510018</td>\n",
" <td>4.752277</td>\n",
" <td>42.374094</td>\n",
" <td>28.111003</td>\n",
" <td>0.666533</td>\n",
" <td>1.472860</td>\n",
" <td>4.608379</td>\n",
" <td>9.111348</td>\n",
" <td>140.078023</td>\n",
" <td>1.478558</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>4.983143e+06</td>\n",
" <td>870.264521</td>\n",
" <td>1354.986328</td>\n",
" <td>0.646378</td>\n",
" <td>29.575212</td>\n",
" <td>5.282188</td>\n",
" <td>-0.292862</td>\n",
" <td>45.804186</td>\n",
" <td>29.443319</td>\n",
" <td>0.646378</td>\n",
" <td>5.282188</td>\n",
" <td>-0.216811</td>\n",
" <td>9.417600</td>\n",
" <td>143.821512</td>\n",
" <td>1.470355</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>5.071083e+06</td>\n",
" <td>821.709982</td>\n",
" <td>1456.086914</td>\n",
" <td>0.569864</td>\n",
" <td>28.684999</td>\n",
" <td>10.313896</td>\n",
" <td>0.751486</td>\n",
" <td>50.758410</td>\n",
" <td>28.653456</td>\n",
" <td>0.569864</td>\n",
" <td>10.313896</td>\n",
" <td>0.767871</td>\n",
" <td>9.776327</td>\n",
" <td>148.852457</td>\n",
" <td>1.456468</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15.0</th>\n",
" <td>5.170085e+06</td>\n",
" <td>810.658545</td>\n",
" <td>1527.205444</td>\n",
" <td>0.535713</td>\n",
" <td>28.404236</td>\n",
" <td>15.316825</td>\n",
" <td>4.005807</td>\n",
" <td>53.763273</td>\n",
" <td>28.572719</td>\n",
" <td>0.535713</td>\n",
" <td>15.316825</td>\n",
" <td>4.030489</td>\n",
" <td>9.835057</td>\n",
" <td>155.124417</td>\n",
" <td>1.451879</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20.0</th>\n",
" <td>5.600528e+06</td>\n",
" <td>835.221891</td>\n",
" <td>1564.418701</td>\n",
" <td>0.537386</td>\n",
" <td>28.465090</td>\n",
" <td>20.188589</td>\n",
" <td>5.152788</td>\n",
" <td>54.992023</td>\n",
" <td>29.389077</td>\n",
" <td>0.537386</td>\n",
" <td>20.188589</td>\n",
" <td>5.146703</td>\n",
" <td>9.719741</td>\n",
" <td>160.802232</td>\n",
" <td>1.452893</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25.0</th>\n",
" <td>5.874602e+06</td>\n",
" <td>886.120006</td>\n",
" <td>1580.860840</td>\n",
" <td>0.564857</td>\n",
" <td>28.447489</td>\n",
" <td>24.848985</td>\n",
" <td>2.963148</td>\n",
" <td>55.632880</td>\n",
" <td>31.186998</td>\n",
" <td>0.564857</td>\n",
" <td>24.848985</td>\n",
" <td>2.970820</td>\n",
" <td>9.695890</td>\n",
" <td>162.872597</td>\n",
" <td>1.452640</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30.0</th>\n",
" <td>5.479405e+06</td>\n",
" <td>929.084273</td>\n",
" <td>1554.904297</td>\n",
" <td>0.603273</td>\n",
" <td>28.842710</td>\n",
" <td>29.548098</td>\n",
" <td>1.777137</td>\n",
" <td>54.002934</td>\n",
" <td>32.251004</td>\n",
" <td>0.603273</td>\n",
" <td>29.548098</td>\n",
" <td>1.788832</td>\n",
" <td>9.531214</td>\n",
" <td>162.919393</td>\n",
" <td>1.458889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35.0</th>\n",
" <td>5.092650e+06</td>\n",
" <td>972.240344</td>\n",
" <td>1526.887329</td>\n",
" <td>0.643225</td>\n",
" <td>29.497133</td>\n",
" <td>34.669332</td>\n",
" <td>2.427184</td>\n",
" <td>51.784100</td>\n",
" <td>32.991376</td>\n",
" <td>0.643225</td>\n",
" <td>34.669332</td>\n",
" <td>2.451932</td>\n",
" <td>9.458938</td>\n",
" <td>161.211644</td>\n",
" <td>1.469130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40.0</th>\n",
" <td>4.670344e+06</td>\n",
" <td>986.904481</td>\n",
" <td>1449.411377</td>\n",
" <td>0.685644</td>\n",
" <td>29.988260</td>\n",
" <td>39.429379</td>\n",
" <td>2.671061</td>\n",
" <td>48.364133</td>\n",
" <td>32.925774</td>\n",
" <td>0.685644</td>\n",
" <td>39.429379</td>\n",
" <td>2.592593</td>\n",
" <td>9.015932</td>\n",
" <td>160.665208</td>\n",
" <td>1.476555</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45.0</th>\n",
" <td>4.434124e+06</td>\n",
" <td>950.961890</td>\n",
" <td>1380.598511</td>\n",
" <td>0.691905</td>\n",
" <td>30.324031</td>\n",
" <td>44.138264</td>\n",
" <td>9.054662</td>\n",
" <td>45.585943</td>\n",
" <td>31.380749</td>\n",
" <td>0.691905</td>\n",
" <td>44.138264</td>\n",
" <td>8.874598</td>\n",
" <td>8.662721</td>\n",
" <td>159.211704</td>\n",
" <td>1.481497</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50.0</th>\n",
" <td>5.397987e+06</td>\n",
" <td>954.971739</td>\n",
" <td>1401.950195</td>\n",
" <td>0.683588</td>\n",
" <td>30.152160</td>\n",
" <td>49.325581</td>\n",
" <td>13.139535</td>\n",
" <td>46.569936</td>\n",
" <td>31.713690</td>\n",
" <td>0.683588</td>\n",
" <td>49.325581</td>\n",
" <td>13.488372</td>\n",
" <td>8.599080</td>\n",
" <td>162.916852</td>\n",
" <td>1.478817</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55.0</th>\n",
" <td>4.228050e+06</td>\n",
" <td>882.337867</td>\n",
" <td>1267.921631</td>\n",
" <td>0.697989</td>\n",
" <td>30.376475</td>\n",
" <td>53.714286</td>\n",
" <td>20.428571</td>\n",
" <td>41.723263</td>\n",
" <td>29.035060</td>\n",
" <td>0.697989</td>\n",
" <td>53.714286</td>\n",
" <td>20.000000</td>\n",
" <td>8.340789</td>\n",
" <td>151.849459</td>\n",
" <td>1.482462</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"15\" valign=\"top\">1.6</th>\n",
" <th>0.0</th>\n",
" <td>4.847767e+06</td>\n",
" <td>1034.705114</td>\n",
" <td>1792.938110</td>\n",
" <td>0.594201</td>\n",
" <td>42.153685</td>\n",
" <td>1.079224</td>\n",
" <td>1.703719</td>\n",
" <td>42.901326</td>\n",
" <td>24.857076</td>\n",
" <td>0.594201</td>\n",
" <td>-0.209175</td>\n",
" <td>1.747507</td>\n",
" <td>12.604728</td>\n",
" <td>143.379677</td>\n",
" <td>1.621102</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>5.012187e+06</td>\n",
" <td>1144.295860</td>\n",
" <td>2148.248779</td>\n",
" <td>0.557283</td>\n",
" <td>40.457534</td>\n",
" <td>5.159211</td>\n",
" <td>2.896725</td>\n",
" <td>52.754742</td>\n",
" <td>28.277330</td>\n",
" <td>0.557283</td>\n",
" <td>5.159211</td>\n",
" <td>2.892427</td>\n",
" <td>14.909844</td>\n",
" <td>143.529014</td>\n",
" <td>1.603304</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>5.032371e+06</td>\n",
" <td>1139.504929</td>\n",
" <td>2290.311035</td>\n",
" <td>0.520164</td>\n",
" <td>40.381743</td>\n",
" <td>10.112763</td>\n",
" <td>3.074239</td>\n",
" <td>56.342171</td>\n",
" <td>28.174946</td>\n",
" <td>0.520164</td>\n",
" <td>10.112763</td>\n",
" <td>3.103512</td>\n",
" <td>15.298740</td>\n",
" <td>149.052519</td>\n",
" <td>1.602465</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15.0</th>\n",
" <td>5.192000e+06</td>\n",
" <td>1113.752276</td>\n",
" <td>2498.217285</td>\n",
" <td>0.467514</td>\n",
" <td>40.549804</td>\n",
" <td>15.448423</td>\n",
" <td>3.686345</td>\n",
" <td>60.996809</td>\n",
" <td>27.429673</td>\n",
" <td>0.467514</td>\n",
" <td>15.448423</td>\n",
" <td>3.680526</td>\n",
" <td>15.816341</td>\n",
" <td>157.340127</td>\n",
" <td>1.604323</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20.0</th>\n",
" <td>5.560078e+06</td>\n",
" <td>1155.995316</td>\n",
" <td>2554.993652</td>\n",
" <td>0.470362</td>\n",
" <td>40.775929</td>\n",
" <td>20.172611</td>\n",
" <td>3.724043</td>\n",
" <td>61.986896</td>\n",
" <td>28.271660</td>\n",
" <td>0.470362</td>\n",
" <td>20.172611</td>\n",
" <td>3.713311</td>\n",
" <td>15.647574</td>\n",
" <td>162.743362</td>\n",
" <td>1.606736</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25.0</th>\n",
" <td>5.572341e+06</td>\n",
" <td>1238.475901</td>\n",
" <td>2450.680664</td>\n",
" <td>0.523951</td>\n",
" <td>40.989444</td>\n",
" <td>24.884738</td>\n",
" <td>2.530027</td>\n",
" <td>59.461761</td>\n",
" <td>30.183381</td>\n",
" <td>0.523951</td>\n",
" <td>24.884738</td>\n",
" <td>2.539690</td>\n",
" <td>14.922700</td>\n",
" <td>163.815639</td>\n",
" <td>1.609065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30.0</th>\n",
" <td>5.091576e+06</td>\n",
" <td>1249.636290</td>\n",
" <td>2277.821289</td>\n",
" <td>0.567900</td>\n",
" <td>41.497187</td>\n",
" <td>29.900428</td>\n",
" <td>2.412170</td>\n",
" <td>54.698361</td>\n",
" <td>30.174227</td>\n",
" <td>0.567900</td>\n",
" <td>29.900428</td>\n",
" <td>2.421336</td>\n",
" <td>13.993038</td>\n",
" <td>162.439253</td>\n",
" <td>1.614560</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35.0</th>\n",
" <td>4.698548e+06</td>\n",
" <td>1245.305810</td>\n",
" <td>2065.924805</td>\n",
" <td>0.621090</td>\n",
" <td>42.004127</td>\n",
" <td>34.827292</td>\n",
" <td>1.867437</td>\n",
" <td>49.176932</td>\n",
" <td>29.734884</td>\n",
" <td>0.621090</td>\n",
" <td>34.827292</td>\n",
" <td>1.893384</td>\n",
" <td>12.780383</td>\n",
" <td>161.434444</td>\n",
" <td>1.620042</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40.0</th>\n",
" <td>4.316527e+06</td>\n",
" <td>1235.783447</td>\n",
" <td>1913.404663</td>\n",
" <td>0.660857</td>\n",
" <td>42.614539</td>\n",
" <td>39.719544</td>\n",
" <td>3.590973</td>\n",
" <td>44.987709</td>\n",
" <td>29.126394</td>\n",
" <td>0.660857</td>\n",
" <td>39.719544</td>\n",
" <td>3.624287</td>\n",
" <td>11.955068</td>\n",
" <td>160.025726</td>\n",
" <td>1.626475</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45.0</th>\n",
" <td>4.500311e+06</td>\n",
" <td>1192.335667</td>\n",
" <td>1808.299805</td>\n",
" <td>0.672751</td>\n",
" <td>43.305404</td>\n",
" <td>44.562190</td>\n",
" <td>5.650154</td>\n",
" <td>41.858020</td>\n",
" <td>27.669479</td>\n",
" <td>0.672751</td>\n",
" <td>44.562190</td>\n",
" <td>5.667425</td>\n",
" <td>11.378948</td>\n",
" <td>158.892691</td>\n",
" <td>1.633850</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50.0</th>\n",
" <td>4.808124e+06</td>\n",
" <td>1130.524486</td>\n",
" <td>1677.364380</td>\n",
" <td>0.683857</td>\n",
" <td>44.068475</td>\n",
" <td>49.534243</td>\n",
" <td>7.254935</td>\n",
" <td>38.203887</td>\n",
" <td>25.778324</td>\n",
" <td>0.683857</td>\n",
" <td>49.534243</td>\n",
" <td>7.180112</td>\n",
" <td>10.693811</td>\n",
" <td>156.761561</td>\n",
" <td>1.641924</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55.0</th>\n",
" <td>4.849210e+06</td>\n",
" <td>1083.115904</td>\n",
" <td>1528.984253</td>\n",
" <td>0.717531</td>\n",
" <td>44.798637</td>\n",
" <td>54.316038</td>\n",
" <td>5.892453</td>\n",
" <td>34.314777</td>\n",
" <td>24.305447</td>\n",
" <td>0.717531</td>\n",
" <td>54.316038</td>\n",
" <td>5.801887</td>\n",
" <td>9.934153</td>\n",
" <td>153.849873</td>\n",
" <td>1.649486</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60.0</th>\n",
" <td>4.549698e+06</td>\n",
" <td>1062.341579</td>\n",
" <td>1453.603516</td>\n",
" <td>0.738470</td>\n",
" <td>44.902651</td>\n",
" <td>59.567485</td>\n",
" <td>2.720859</td>\n",
" <td>32.543461</td>\n",
" <td>23.779204</td>\n",
" <td>0.738470</td>\n",
" <td>59.567485</td>\n",
" <td>2.638037</td>\n",
" <td>9.698868</td>\n",
" <td>149.946680</td>\n",
" <td>1.650578</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65.0</th>\n",
" <td>4.150396e+06</td>\n",
" <td>1076.638908</td>\n",
" <td>1414.788086</td>\n",
" <td>0.765872</td>\n",
" <td>45.629422</td>\n",
" <td>64.626667</td>\n",
" <td>0.333333</td>\n",
" <td>31.097107</td>\n",
" <td>23.650310</td>\n",
" <td>0.765872</td>\n",
" <td>64.626667</td>\n",
" <td>0.666667</td>\n",
" <td>9.665644</td>\n",
" <td>146.469527</td>\n",
" <td>1.658158</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70.0</th>\n",
" <td>5.389880e+06</td>\n",
" <td>960.857536</td>\n",
" <td>1154.847656</td>\n",
" <td>0.835550</td>\n",
" <td>46.745857</td>\n",
" <td>68.500000</td>\n",
" <td>-32.250000</td>\n",
" <td>24.801501</td>\n",
" <td>20.587047</td>\n",
" <td>0.835550</td>\n",
" <td>68.500000</td>\n",
" <td>-32.500000</td>\n",
" <td>8.551242</td>\n",
" <td>135.586556</td>\n",
" <td>1.669261</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">1.8</th>\n",
" <th>0.0</th>\n",
" <td>4.463076e+06</td>\n",
" <td>934.781481</td>\n",
" <td>1842.069336</td>\n",
" <td>0.520758</td>\n",
" <td>66.365404</td>\n",
" <td>0.108354</td>\n",
" <td>0.073110</td>\n",
" <td>27.835242</td>\n",
" <td>14.171956</td>\n",
" <td>0.520758</td>\n",
" <td>-4.602885</td>\n",
" <td>0.076100</td>\n",
" <td>11.871803</td>\n",
" <td>156.433922</td>\n",
" <td>1.818853</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>4.993923e+06</td>\n",
" <td>1796.889724</td>\n",
" <td>3983.610596</td>\n",
" <td>0.492103</td>\n",
" <td>63.025545</td>\n",
" <td>5.188114</td>\n",
" <td>2.887485</td>\n",
" <td>62.710007</td>\n",
" <td>28.543367</td>\n",
" <td>0.492103</td>\n",
" <td>5.188114</td>\n",
" <td>2.899594</td>\n",
" <td>27.582810</td>\n",
" <td>142.871479</td>\n",
" <td>1.795734</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2.8</th>\n",
" <th>70.0</th>\n",
" <td>5.813572e+06</td>\n",
" <td>11498.121554</td>\n",
" <td>6728.736328</td>\n",
" <td>1.708808</td>\n",
" <td>794.178454</td>\n",
" <td>69.000000</td>\n",
" <td>33.000000</td>\n",
" <td>8.472575</td>\n",
" <td>14.478007</td>\n",
" <td>1.708808</td>\n",
" <td>69.000000</td>\n",
" <td>30.000000</td>\n",
" <td>61.804471</td>\n",
" <td>108.871352</td>\n",
" <td>2.899918</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"14\" valign=\"top\">3.0</th>\n",
" <th>0.0</th>\n",
" <td>4.610407e+06</td>\n",
" <td>17358.207676</td>\n",
" <td>55626.113281</td>\n",
" <td>0.330505</td>\n",
" <td>985.320416</td>\n",
" <td>0.050246</td>\n",
" <td>-0.095330</td>\n",
" <td>56.315952</td>\n",
" <td>17.575026</td>\n",
" <td>0.330505</td>\n",
" <td>-4.868360</td>\n",
" <td>-0.097589</td>\n",
" <td>337.263413</td>\n",
" <td>164.075977</td>\n",
" <td>2.989804</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>4.773191e+06</td>\n",
" <td>29650.703392</td>\n",
" <td>120149.445312</td>\n",
" <td>0.251857</td>\n",
" <td>987.747229</td>\n",
" <td>4.955985</td>\n",
" <td>1.811583</td>\n",
" <td>121.568879</td>\n",
" <td>29.999578</td>\n",
" <td>0.251857</td>\n",
" <td>4.955985</td>\n",
" <td>1.953668</td>\n",
" <td>770.995462</td>\n",
" <td>155.357352</td>\n",
" <td>2.990732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>4.644329e+06</td>\n",
" <td>30610.805485</td>\n",
" <td>124099.296875</td>\n",
" <td>0.250688</td>\n",
" <td>974.404203</td>\n",
" <td>10.021348</td>\n",
" <td>1.851234</td>\n",
" <td>127.291409</td>\n",
" <td>31.396981</td>\n",
" <td>0.250688</td>\n",
" <td>10.021348</td>\n",
" <td>2.028019</td>\n",
" <td>771.236054</td>\n",
" <td>160.520415</td>\n",
" <td>2.985069</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15.0</th>\n",
" <td>4.716177e+06</td>\n",
" <td>31839.388829</td>\n",
" <td>127598.609375</td>\n",
" <td>0.253859</td>\n",
" <td>966.486330</td>\n",
" <td>14.945755</td>\n",
" <td>-1.561321</td>\n",
" <td>131.843423</td>\n",
" <td>32.918405</td>\n",
" <td>0.253859</td>\n",
" <td>14.945755</td>\n",
" <td>-1.501572</td>\n",
" <td>770.820229</td>\n",
" <td>165.031396</td>\n",
" <td>2.981504</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20.0</th>\n",
" <td>4.808413e+06</td>\n",
" <td>32308.133489</td>\n",
" <td>121700.359375</td>\n",
" <td>0.270395</td>\n",
" <td>951.379233</td>\n",
" <td>19.700000</td>\n",
" <td>0.586567</td>\n",
" <td>127.997083</td>\n",
" <td>33.939039</td>\n",
" <td>0.270395</td>\n",
" <td>19.700000</td>\n",
" <td>0.716418</td>\n",
" <td>726.206900</td>\n",
" <td>167.059997</td>\n",
" <td>2.975021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25.0</th>\n",
" <td>4.992114e+06</td>\n",
" <td>32638.649356</td>\n",
" <td>117421.406250</td>\n",
" <td>0.280811</td>\n",
" <td>936.795331</td>\n",
" <td>24.545455</td>\n",
" <td>1.210031</td>\n",
" <td>125.306379</td>\n",
" <td>34.805085</td>\n",
" <td>0.280811</td>\n",
" <td>24.545455</td>\n",
" <td>1.191223</td>\n",
" <td>690.589577</td>\n",
" <td>169.789009</td>\n",
" <td>2.968738</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30.0</th>\n",
" <td>4.720241e+06</td>\n",
" <td>33874.789332</td>\n",
" <td>108668.382812</td>\n",
" <td>0.322116</td>\n",
" <td>945.283146</td>\n",
" <td>29.746988</td>\n",
" <td>-1.024096</td>\n",
" <td>114.884309</td>\n",
" <td>35.784861</td>\n",
" <td>0.322116</td>\n",
" <td>29.746988</td>\n",
" <td>-0.602410</td>\n",
" <td>644.359883</td>\n",
" <td>168.031694</td>\n",
" <td>2.972170</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35.0</th>\n",
" <td>4.733707e+06</td>\n",
" <td>33732.642274</td>\n",
" <td>95235.492188</td>\n",
" <td>0.364572</td>\n",
" <td>929.186690</td>\n",
" <td>34.592105</td>\n",
" <td>0.868421</td>\n",
" <td>102.502394</td>\n",
" <td>36.291986</td>\n",
" <td>0.364572</td>\n",
" <td>34.592105</td>\n",
" <td>0.921053</td>\n",
" <td>574.778540</td>\n",
" <td>165.497726</td>\n",
" <td>2.964612</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40.0</th>\n",
" <td>5.056836e+06</td>\n",
" <td>32535.396276</td>\n",
" <td>89059.046875</td>\n",
" <td>0.376999</td>\n",
" <td>920.668757</td>\n",
" <td>39.758621</td>\n",
" <td>-12.344828</td>\n",
" <td>97.588252</td>\n",
" <td>35.593356</td>\n",
" <td>0.376999</td>\n",
" <td>39.758621</td>\n",
" <td>-12.758621</td>\n",
" <td>535.869781</td>\n",
" <td>165.715696</td>\n",
" <td>2.961577</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45.0</th>\n",
" <td>4.457209e+06</td>\n",
" <td>32677.426406</td>\n",
" <td>80110.148438</td>\n",
" <td>0.437025</td>\n",
" <td>933.909234</td>\n",
" <td>44.523810</td>\n",
" <td>1.047619</td>\n",
" <td>85.824836</td>\n",
" <td>35.102563</td>\n",
" <td>0.437025</td>\n",
" <td>44.523810</td>\n",
" <td>0.476190</td>\n",
" <td>512.494302</td>\n",
" <td>154.944375</td>\n",
" <td>2.966355</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50.0</th>\n",
" <td>7.141918e+06</td>\n",
" <td>28585.509833</td>\n",
" <td>61521.804688</td>\n",
" <td>0.502566</td>\n",
" <td>941.082932</td>\n",
" <td>50.666667</td>\n",
" <td>25.266667</td>\n",
" <td>65.494455</td>\n",
" <td>30.411222</td>\n",
" <td>0.502566</td>\n",
" <td>50.666667</td>\n",
" <td>24.666667</td>\n",
" <td>405.336649</td>\n",
" <td>153.963258</td>\n",
" <td>2.972406</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55.0</th>\n",
" <td>5.456202e+06</td>\n",
" <td>35408.124381</td>\n",
" <td>92893.750000</td>\n",
" <td>0.400626</td>\n",
" <td>912.252883</td>\n",
" <td>55.750000</td>\n",
" <td>-26.250000</td>\n",
" <td>99.910395</td>\n",
" <td>38.469464</td>\n",
" <td>0.400626</td>\n",
" <td>55.750000</td>\n",
" <td>-27.500000</td>\n",
" <td>533.974264</td>\n",
" <td>169.674858</td>\n",
" <td>2.958968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60.0</th>\n",
" <td>7.067711e+06</td>\n",
" <td>34019.960425</td>\n",
" <td>74242.156250</td>\n",
" <td>0.450593</td>\n",
" <td>1020.258887</td>\n",
" <td>59.000000</td>\n",
" <td>7.000000</td>\n",
" <td>73.079361</td>\n",
" <td>32.846818</td>\n",
" <td>0.450593</td>\n",
" <td>59.000000</td>\n",
" <td>5.000000</td>\n",
" <td>525.323327</td>\n",
" <td>146.024838</td>\n",
" <td>3.001408</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65.0</th>\n",
" <td>7.281614e+06</td>\n",
" <td>26273.881652</td>\n",
" <td>56430.296875</td>\n",
" <td>0.490356</td>\n",
" <td>925.992068</td>\n",
" <td>63.666667</td>\n",
" <td>21.000000</td>\n",
" <td>58.481592</td>\n",
" <td>27.613920</td>\n",
" <td>0.490356</td>\n",
" <td>63.666667</td>\n",
" <td>23.333333</td>\n",
" <td>419.484887</td>\n",
" <td>129.927222</td>\n",
" <td>2.960412</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"15\" valign=\"top\">3.2</th>\n",
" <th>0.0</th>\n",
" <td>4.612284e+06</td>\n",
" <td>53754.523306</td>\n",
" <td>177141.109375</td>\n",
" <td>0.319376</td>\n",
" <td>2681.724550</td>\n",
" <td>0.053873</td>\n",
" <td>-0.065669</td>\n",
" <td>62.813583</td>\n",
" <td>19.252345</td>\n",
" <td>0.319376</td>\n",
" <td>-4.853979</td>\n",
" <td>-0.057218</td>\n",
" <td>1044.194992</td>\n",
" <td>167.590268</td>\n",
" <td>3.343962</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.0</th>\n",
" <td>4.805704e+06</td>\n",
" <td>70680.701530</td>\n",
" <td>281310.156250</td>\n",
" <td>0.254008</td>\n",
" <td>2273.494614</td>\n",
" <td>4.668627</td>\n",
" <td>-1.469608</td>\n",
" <td>123.638752</td>\n",
" <td>30.853184</td>\n",
" <td>0.254008</td>\n",
" <td>4.668627</td>\n",
" <td>-1.352941</td>\n",
" <td>1793.556361</td>\n",
" <td>156.280016</td>\n",
" <td>3.303289</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.0</th>\n",
" <td>4.579210e+06</td>\n",
" <td>56302.159565</td>\n",
" <td>226404.750000</td>\n",
" <td>0.250352</td>\n",
" <td>1786.061947</td>\n",
" <td>9.908702</td>\n",
" <td>-2.078459</td>\n",
" <td>127.220557</td>\n",
" <td>31.525870</td>\n",
" <td>0.250352</td>\n",
" <td>9.908702</td>\n",
" <td>-1.811698</td>\n",
" <td>1405.237111</td>\n",
" <td>160.907365</td>\n",
" <td>3.233721</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15.0</th>\n",
" <td>4.591854e+06</td>\n",
" <td>57205.162058</td>\n",
" <td>221417.187500</td>\n",
" <td>0.260783</td>\n",
" <td>1719.751544</td>\n",
" <td>14.704485</td>\n",
" <td>-3.110818</td>\n",
" <td>129.899321</td>\n",
" <td>33.249001</td>\n",
" <td>0.260783</td>\n",
" <td>14.704485</td>\n",
" <td>-3.087071</td>\n",
" <td>1345.194919</td>\n",
" <td>164.521558</td>\n",
" <td>3.216255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20.0</th>\n",
" <td>4.640565e+06</td>\n",
" <td>57045.631418</td>\n",
" <td>216828.984375</td>\n",
" <td>0.266807</td>\n",
" <td>1668.465357</td>\n",
" <td>19.400000</td>\n",
" <td>-0.242424</td>\n",
" <td>130.527406</td>\n",
" <td>34.269996</td>\n",
" <td>0.266807</td>\n",
" <td>19.400000</td>\n",
" <td>0.000000</td>\n",
" <td>1293.871194</td>\n",
" <td>166.982565</td>\n",
" <td>3.203539</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25.0</th>\n",
" <td>5.874464e+06</td>\n",
" <td>57942.123804</td>\n",
" <td>201531.093750</td>\n",
" <td>0.291287</td>\n",
" <td>1667.140614</td>\n",
" <td>24.568421</td>\n",
" <td>1.947368</td>\n",
" <td>121.350427</td>\n",
" <td>34.937842</td>\n",
" <td>0.291287</td>\n",
" <td>24.568421</td>\n",
" <td>1.473684</td>\n",
" <td>1209.794278</td>\n",
" <td>167.393144</td>\n",
" <td>3.205478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30.0</th>\n",
" <td>5.315096e+06</td>\n",
" <td>67961.582031</td>\n",
" <td>212953.937500</td>\n",
" <td>0.322755</td>\n",
" <td>1843.874473</td>\n",
" <td>30.243243</td>\n",
" <td>12.297297</td>\n",
" <td>114.732570</td>\n",
" <td>36.769846</td>\n",
" <td>0.322755</td>\n",
" <td>30.243243</td>\n",
" <td>11.081081</td>\n",
" <td>1287.331705</td>\n",
" <td>164.620170</td>\n",
" <td>3.248956</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35.0</th>\n",
" <td>6.949979e+06</td>\n",
" <td>80167.920594</td>\n",
" <td>227434.343750</td>\n",
" <td>0.406038</td>\n",
" <td>2162.652394</td>\n",
" <td>34.250000</td>\n",
" <td>-12.000000</td>\n",
" <td>98.711584</td>\n",
" <td>35.955324</td>\n",
" <td>0.406038</td>\n",
" <td>34.250000</td>\n",
" <td>-10.000000</td>\n",
" <td>1352.564730</td>\n",
" <td>157.802668</td>\n",
" <td>3.291222</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40.0</th>\n",
" <td>4.959043e+06</td>\n",
" <td>103538.153130</td>\n",
" <td>241769.406250</td>\n",
" <td>0.455339</td>\n",
" <td>2601.427148</td>\n",
" <td>40.125000</td>\n",
" <td>-10.625000</td>\n",
" <td>84.126951</td>\n",
" <td>36.801064</td>\n",
" <td>0.455339</td>\n",
" <td>40.125000</td>\n",
" <td>-11.250000</td>\n",
" <td>1421.387412</td>\n",
" <td>161.589680</td>\n",
" <td>3.343874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45.0</th>\n",
" <td>5.488224e+06</td>\n",
" <td>74869.979701</td>\n",
" <td>155584.406250</td>\n",
" <td>0.481882</td>\n",
" <td>1982.120042</td>\n",
" <td>44.666667</td>\n",
" <td>-4.000000</td>\n",
" <td>80.853257</td>\n",
" <td>38.576271</td>\n",
" <td>0.481882</td>\n",
" <td>44.666667</td>\n",
" <td>-3.333333</td>\n",
" <td>932.004791</td>\n",
" <td>168.514058</td>\n",
" <td>3.245654</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50.0</th>\n",
" <td>6.192028e+06</td>\n",
" <td>54059.458650</td>\n",
" <td>132167.187500</td>\n",
" <td>0.418838</td>\n",
" <td>1728.650792</td>\n",
" <td>50.000000</td>\n",
" <td>2.200000</td>\n",
" <td>83.728707</td>\n",
" <td>33.422152</td>\n",
" <td>0.418838</td>\n",
" <td>50.000000</td>\n",
" <td>0.000000</td>\n",
" <td>799.909810</td>\n",
" <td>165.174176</td>\n",
" <td>3.217785</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55.0</th>\n",
" <td>2.867770e+06</td>\n",
" <td>80801.557239</td>\n",
" <td>183988.828125</td>\n",
" <td>0.451774</td>\n",
" <td>2573.899267</td>\n",
" <td>54.000000</td>\n",
" <td>3.666667</td>\n",
" <td>73.181026</td>\n",
" <td>31.676750</td>\n",
" <td>0.451774</td>\n",
" <td>54.000000</td>\n",
" <td>3.333333</td>\n",
" <td>1323.974209</td>\n",
" <td>138.293545</td>\n",
" <td>3.373594</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60.0</th>\n",
" <td>4.412172e+06</td>\n",
" <td>80784.479711</td>\n",
" <td>195334.531250</td>\n",
" <td>0.424525</td>\n",
" <td>2784.263993</td>\n",
" <td>60.500000</td>\n",
" <td>-20.750000</td>\n",
" <td>70.491754</td>\n",
" <td>29.545444</td>\n",
" <td>0.424525</td>\n",
" <td>60.500000</td>\n",
" <td>-20.000000</td>\n",
" <td>1472.935765</td>\n",
" <td>150.591604</td>\n",
" <td>3.389600</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65.0</th>\n",
" <td>3.915371e+06</td>\n",
" <td>53020.958536</td>\n",
" <td>105637.171875</td>\n",
" <td>0.504844</td>\n",
" <td>1570.647215</td>\n",
" <td>64.400000</td>\n",
" <td>17.400000</td>\n",
" <td>69.414655</td>\n",
" <td>34.253844</td>\n",
" <td>0.504844</td>\n",
" <td>64.400000</td>\n",
" <td>16.000000</td>\n",
" <td>711.885783</td>\n",
" <td>148.899222</td>\n",
" <td>3.190142</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70.0</th>\n",
" <td>6.969243e+06</td>\n",
" <td>71295.689563</td>\n",
" <td>174453.656250</td>\n",
" <td>0.448103</td>\n",
" <td>2263.538192</td>\n",
" <td>68.000000</td>\n",
" <td>49.666667</td>\n",
" <td>69.144251</td>\n",
" <td>29.573287</td>\n",
" <td>0.448103</td>\n",
" <td>68.000000</td>\n",
" <td>50.000000</td>\n",
" <td>1126.005223</td>\n",
" <td>149.457045</td>\n",
" <td>3.330911</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>147 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" DF_UID yearly_std_PV yearly_PV_kWh \\\n",
"area_log_round tilt_round \n",
"1.2 20.0 4.922855e+06 737.396294 1484.851929 \n",
"1.4 0.0 4.991159e+06 846.543206 1276.234863 \n",
" 5.0 4.983143e+06 870.264521 1354.986328 \n",
" 10.0 5.071083e+06 821.709982 1456.086914 \n",
" 15.0 5.170085e+06 810.658545 1527.205444 \n",
" 20.0 5.600528e+06 835.221891 1564.418701 \n",
" 25.0 5.874602e+06 886.120006 1580.860840 \n",
" 30.0 5.479405e+06 929.084273 1554.904297 \n",
" 35.0 5.092650e+06 972.240344 1526.887329 \n",
" 40.0 4.670344e+06 986.904481 1449.411377 \n",
" 45.0 4.434124e+06 950.961890 1380.598511 \n",
" 50.0 5.397987e+06 954.971739 1401.950195 \n",
" 55.0 4.228050e+06 882.337867 1267.921631 \n",
"1.6 0.0 4.847767e+06 1034.705114 1792.938110 \n",
" 5.0 5.012187e+06 1144.295860 2148.248779 \n",
" 10.0 5.032371e+06 1139.504929 2290.311035 \n",
" 15.0 5.192000e+06 1113.752276 2498.217285 \n",
" 20.0 5.560078e+06 1155.995316 2554.993652 \n",
" 25.0 5.572341e+06 1238.475901 2450.680664 \n",
" 30.0 5.091576e+06 1249.636290 2277.821289 \n",
" 35.0 4.698548e+06 1245.305810 2065.924805 \n",
" 40.0 4.316527e+06 1235.783447 1913.404663 \n",
" 45.0 4.500311e+06 1192.335667 1808.299805 \n",
" 50.0 4.808124e+06 1130.524486 1677.364380 \n",
" 55.0 4.849210e+06 1083.115904 1528.984253 \n",
" 60.0 4.549698e+06 1062.341579 1453.603516 \n",
" 65.0 4.150396e+06 1076.638908 1414.788086 \n",
" 70.0 5.389880e+06 960.857536 1154.847656 \n",
"1.8 0.0 4.463076e+06 934.781481 1842.069336 \n",
" 5.0 4.993923e+06 1796.889724 3983.610596 \n",
"... ... ... ... \n",
"2.8 70.0 5.813572e+06 11498.121554 6728.736328 \n",
"3.0 0.0 4.610407e+06 17358.207676 55626.113281 \n",
" 5.0 4.773191e+06 29650.703392 120149.445312 \n",
" 10.0 4.644329e+06 30610.805485 124099.296875 \n",
" 15.0 4.716177e+06 31839.388829 127598.609375 \n",
" 20.0 4.808413e+06 32308.133489 121700.359375 \n",
" 25.0 4.992114e+06 32638.649356 117421.406250 \n",
" 30.0 4.720241e+06 33874.789332 108668.382812 \n",
" 35.0 4.733707e+06 33732.642274 95235.492188 \n",
" 40.0 5.056836e+06 32535.396276 89059.046875 \n",
" 45.0 4.457209e+06 32677.426406 80110.148438 \n",
" 50.0 7.141918e+06 28585.509833 61521.804688 \n",
" 55.0 5.456202e+06 35408.124381 92893.750000 \n",
" 60.0 7.067711e+06 34019.960425 74242.156250 \n",
" 65.0 7.281614e+06 26273.881652 56430.296875 \n",
"3.2 0.0 4.612284e+06 53754.523306 177141.109375 \n",
" 5.0 4.805704e+06 70680.701530 281310.156250 \n",
" 10.0 4.579210e+06 56302.159565 226404.750000 \n",
" 15.0 4.591854e+06 57205.162058 221417.187500 \n",
" 20.0 4.640565e+06 57045.631418 216828.984375 \n",
" 25.0 5.874464e+06 57942.123804 201531.093750 \n",
" 30.0 5.315096e+06 67961.582031 212953.937500 \n",
" 35.0 6.949979e+06 80167.920594 227434.343750 \n",
" 40.0 4.959043e+06 103538.153130 241769.406250 \n",
" 45.0 5.488224e+06 74869.979701 155584.406250 \n",
" 50.0 6.192028e+06 54059.458650 132167.187500 \n",
" 55.0 2.867770e+06 80801.557239 183988.828125 \n",
" 60.0 4.412172e+06 80784.479711 195334.531250 \n",
" 65.0 3.915371e+06 53020.958536 105637.171875 \n",
" 70.0 6.969243e+06 71295.689563 174453.656250 \n",
"\n",
" unc_perc FLAECHE NEIGUNG AUSRICHTUNG \\\n",
"area_log_round tilt_round \n",
"1.2 20.0 0.496931 19.671486 21.000000 -4.000000 \n",
"1.4 0.0 0.666533 30.121106 1.510018 4.752277 \n",
" 5.0 0.646378 29.575212 5.282188 -0.292862 \n",
" 10.0 0.569864 28.684999 10.313896 0.751486 \n",
" 15.0 0.535713 28.404236 15.316825 4.005807 \n",
" 20.0 0.537386 28.465090 20.188589 5.152788 \n",
" 25.0 0.564857 28.447489 24.848985 2.963148 \n",
" 30.0 0.603273 28.842710 29.548098 1.777137 \n",
" 35.0 0.643225 29.497133 34.669332 2.427184 \n",
" 40.0 0.685644 29.988260 39.429379 2.671061 \n",
" 45.0 0.691905 30.324031 44.138264 9.054662 \n",
" 50.0 0.683588 30.152160 49.325581 13.139535 \n",
" 55.0 0.697989 30.376475 53.714286 20.428571 \n",
"1.6 0.0 0.594201 42.153685 1.079224 1.703719 \n",
" 5.0 0.557283 40.457534 5.159211 2.896725 \n",
" 10.0 0.520164 40.381743 10.112763 3.074239 \n",
" 15.0 0.467514 40.549804 15.448423 3.686345 \n",
" 20.0 0.470362 40.775929 20.172611 3.724043 \n",
" 25.0 0.523951 40.989444 24.884738 2.530027 \n",
" 30.0 0.567900 41.497187 29.900428 2.412170 \n",
" 35.0 0.621090 42.004127 34.827292 1.867437 \n",
" 40.0 0.660857 42.614539 39.719544 3.590973 \n",
" 45.0 0.672751 43.305404 44.562190 5.650154 \n",
" 50.0 0.683857 44.068475 49.534243 7.254935 \n",
" 55.0 0.717531 44.798637 54.316038 5.892453 \n",
" 60.0 0.738470 44.902651 59.567485 2.720859 \n",
" 65.0 0.765872 45.629422 64.626667 0.333333 \n",
" 70.0 0.835550 46.745857 68.500000 -32.250000 \n",
"1.8 0.0 0.520758 66.365404 0.108354 0.073110 \n",
" 5.0 0.492103 63.025545 5.188114 2.887485 \n",
"... ... ... ... ... \n",
"2.8 70.0 1.708808 794.178454 69.000000 33.000000 \n",
"3.0 0.0 0.330505 985.320416 0.050246 -0.095330 \n",
" 5.0 0.251857 987.747229 4.955985 1.811583 \n",
" 10.0 0.250688 974.404203 10.021348 1.851234 \n",
" 15.0 0.253859 966.486330 14.945755 -1.561321 \n",
" 20.0 0.270395 951.379233 19.700000 0.586567 \n",
" 25.0 0.280811 936.795331 24.545455 1.210031 \n",
" 30.0 0.322116 945.283146 29.746988 -1.024096 \n",
" 35.0 0.364572 929.186690 34.592105 0.868421 \n",
" 40.0 0.376999 920.668757 39.758621 -12.344828 \n",
" 45.0 0.437025 933.909234 44.523810 1.047619 \n",
" 50.0 0.502566 941.082932 50.666667 25.266667 \n",
" 55.0 0.400626 912.252883 55.750000 -26.250000 \n",
" 60.0 0.450593 1020.258887 59.000000 7.000000 \n",
" 65.0 0.490356 925.992068 63.666667 21.000000 \n",
"3.2 0.0 0.319376 2681.724550 0.053873 -0.065669 \n",
" 5.0 0.254008 2273.494614 4.668627 -1.469608 \n",
" 10.0 0.250352 1786.061947 9.908702 -2.078459 \n",
" 15.0 0.260783 1719.751544 14.704485 -3.110818 \n",
" 20.0 0.266807 1668.465357 19.400000 -0.242424 \n",
" 25.0 0.291287 1667.140614 24.568421 1.947368 \n",
" 30.0 0.322755 1843.874473 30.243243 12.297297 \n",
" 35.0 0.406038 2162.652394 34.250000 -12.000000 \n",
" 40.0 0.455339 2601.427148 40.125000 -10.625000 \n",
" 45.0 0.481882 1982.120042 44.666667 -4.000000 \n",
" 50.0 0.418838 1728.650792 50.000000 2.200000 \n",
" 55.0 0.451774 2573.899267 54.000000 3.666667 \n",
" 60.0 0.424525 2784.263993 60.500000 -20.750000 \n",
" 65.0 0.504844 1570.647215 64.400000 17.400000 \n",
" 70.0 0.448103 2263.538192 68.000000 49.666667 \n",
"\n",
" PV_norm PV_std_norm unc_perc_norm tilt \\\n",
"area_log_round tilt_round \n",
"1.2 20.0 75.482643 37.485429 0.496931 21.000000 \n",
"1.4 0.0 42.374094 28.111003 0.666533 1.472860 \n",
" 5.0 45.804186 29.443319 0.646378 5.282188 \n",
" 10.0 50.758410 28.653456 0.569864 10.313896 \n",
" 15.0 53.763273 28.572719 0.535713 15.316825 \n",
" 20.0 54.992023 29.389077 0.537386 20.188589 \n",
" 25.0 55.632880 31.186998 0.564857 24.848985 \n",
" 30.0 54.002934 32.251004 0.603273 29.548098 \n",
" 35.0 51.784100 32.991376 0.643225 34.669332 \n",
" 40.0 48.364133 32.925774 0.685644 39.429379 \n",
" 45.0 45.585943 31.380749 0.691905 44.138264 \n",
" 50.0 46.569936 31.713690 0.683588 49.325581 \n",
" 55.0 41.723263 29.035060 0.697989 53.714286 \n",
"1.6 0.0 42.901326 24.857076 0.594201 -0.209175 \n",
" 5.0 52.754742 28.277330 0.557283 5.159211 \n",
" 10.0 56.342171 28.174946 0.520164 10.112763 \n",
" 15.0 60.996809 27.429673 0.467514 15.448423 \n",
" 20.0 61.986896 28.271660 0.470362 20.172611 \n",
" 25.0 59.461761 30.183381 0.523951 24.884738 \n",
" 30.0 54.698361 30.174227 0.567900 29.900428 \n",
" 35.0 49.176932 29.734884 0.621090 34.827292 \n",
" 40.0 44.987709 29.126394 0.660857 39.719544 \n",
" 45.0 41.858020 27.669479 0.672751 44.562190 \n",
" 50.0 38.203887 25.778324 0.683857 49.534243 \n",
" 55.0 34.314777 24.305447 0.717531 54.316038 \n",
" 60.0 32.543461 23.779204 0.738470 59.567485 \n",
" 65.0 31.097107 23.650310 0.765872 64.626667 \n",
" 70.0 24.801501 20.587047 0.835550 68.500000 \n",
"1.8 0.0 27.835242 14.171956 0.520758 -4.602885 \n",
" 5.0 62.710007 28.543367 0.492103 5.188114 \n",
"... ... ... ... ... \n",
"2.8 70.0 8.472575 14.478007 1.708808 69.000000 \n",
"3.0 0.0 56.315952 17.575026 0.330505 -4.868360 \n",
" 5.0 121.568879 29.999578 0.251857 4.955985 \n",
" 10.0 127.291409 31.396981 0.250688 10.021348 \n",
" 15.0 131.843423 32.918405 0.253859 14.945755 \n",
" 20.0 127.997083 33.939039 0.270395 19.700000 \n",
" 25.0 125.306379 34.805085 0.280811 24.545455 \n",
" 30.0 114.884309 35.784861 0.322116 29.746988 \n",
" 35.0 102.502394 36.291986 0.364572 34.592105 \n",
" 40.0 97.588252 35.593356 0.376999 39.758621 \n",
" 45.0 85.824836 35.102563 0.437025 44.523810 \n",
" 50.0 65.494455 30.411222 0.502566 50.666667 \n",
" 55.0 99.910395 38.469464 0.400626 55.750000 \n",
" 60.0 73.079361 32.846818 0.450593 59.000000 \n",
" 65.0 58.481592 27.613920 0.490356 63.666667 \n",
"3.2 0.0 62.813583 19.252345 0.319376 -4.853979 \n",
" 5.0 123.638752 30.853184 0.254008 4.668627 \n",
" 10.0 127.220557 31.525870 0.250352 9.908702 \n",
" 15.0 129.899321 33.249001 0.260783 14.704485 \n",
" 20.0 130.527406 34.269996 0.266807 19.400000 \n",
" 25.0 121.350427 34.937842 0.291287 24.568421 \n",
" 30.0 114.732570 36.769846 0.322755 30.243243 \n",
" 35.0 98.711584 35.955324 0.406038 34.250000 \n",
" 40.0 84.126951 36.801064 0.455339 40.125000 \n",
" 45.0 80.853257 38.576271 0.481882 44.666667 \n",
" 50.0 83.728707 33.422152 0.418838 50.000000 \n",
" 55.0 73.181026 31.676750 0.451774 54.000000 \n",
" 60.0 70.491754 29.545444 0.424525 60.500000 \n",
" 65.0 69.414655 34.253844 0.504844 64.400000 \n",
" 70.0 69.144251 29.573287 0.448103 68.000000 \n",
"\n",
" aspect_round available_area PV_norm_avail \\\n",
"area_log_round tilt_round \n",
"1.2 20.0 -5.000000 8.222259 180.579360 \n",
"1.4 0.0 4.608379 9.111348 140.078023 \n",
" 5.0 -0.216811 9.417600 143.821512 \n",
" 10.0 0.767871 9.776327 148.852457 \n",
" 15.0 4.030489 9.835057 155.124417 \n",
" 20.0 5.146703 9.719741 160.802232 \n",
" 25.0 2.970820 9.695890 162.872597 \n",
" 30.0 1.788832 9.531214 162.919393 \n",
" 35.0 2.451932 9.458938 161.211644 \n",
" 40.0 2.592593 9.015932 160.665208 \n",
" 45.0 8.874598 8.662721 159.211704 \n",
" 50.0 13.488372 8.599080 162.916852 \n",
" 55.0 20.000000 8.340789 151.849459 \n",
"1.6 0.0 1.747507 12.604728 143.379677 \n",
" 5.0 2.892427 14.909844 143.529014 \n",
" 10.0 3.103512 15.298740 149.052519 \n",
" 15.0 3.680526 15.816341 157.340127 \n",
" 20.0 3.713311 15.647574 162.743362 \n",
" 25.0 2.539690 14.922700 163.815639 \n",
" 30.0 2.421336 13.993038 162.439253 \n",
" 35.0 1.893384 12.780383 161.434444 \n",
" 40.0 3.624287 11.955068 160.025726 \n",
" 45.0 5.667425 11.378948 158.892691 \n",
" 50.0 7.180112 10.693811 156.761561 \n",
" 55.0 5.801887 9.934153 153.849873 \n",
" 60.0 2.638037 9.698868 149.946680 \n",
" 65.0 0.666667 9.665644 146.469527 \n",
" 70.0 -32.500000 8.551242 135.586556 \n",
"1.8 0.0 0.076100 11.871803 156.433922 \n",
" 5.0 2.899594 27.582810 142.871479 \n",
"... ... ... ... \n",
"2.8 70.0 30.000000 61.804471 108.871352 \n",
"3.0 0.0 -0.097589 337.263413 164.075977 \n",
" 5.0 1.953668 770.995462 155.357352 \n",
" 10.0 2.028019 771.236054 160.520415 \n",
" 15.0 -1.501572 770.820229 165.031396 \n",
" 20.0 0.716418 726.206900 167.059997 \n",
" 25.0 1.191223 690.589577 169.789009 \n",
" 30.0 -0.602410 644.359883 168.031694 \n",
" 35.0 0.921053 574.778540 165.497726 \n",
" 40.0 -12.758621 535.869781 165.715696 \n",
" 45.0 0.476190 512.494302 154.944375 \n",
" 50.0 24.666667 405.336649 153.963258 \n",
" 55.0 -27.500000 533.974264 169.674858 \n",
" 60.0 5.000000 525.323327 146.024838 \n",
" 65.0 23.333333 419.484887 129.927222 \n",
"3.2 0.0 -0.057218 1044.194992 167.590268 \n",
" 5.0 -1.352941 1793.556361 156.280016 \n",
" 10.0 -1.811698 1405.237111 160.907365 \n",
" 15.0 -3.087071 1345.194919 164.521558 \n",
" 20.0 0.000000 1293.871194 166.982565 \n",
" 25.0 1.473684 1209.794278 167.393144 \n",
" 30.0 11.081081 1287.331705 164.620170 \n",
" 35.0 -10.000000 1352.564730 157.802668 \n",
" 40.0 -11.250000 1421.387412 161.589680 \n",
" 45.0 -3.333333 932.004791 168.514058 \n",
" 50.0 0.000000 799.909810 165.174176 \n",
" 55.0 3.333333 1323.974209 138.293545 \n",
" 60.0 -20.000000 1472.935765 150.591604 \n",
" 65.0 16.000000 711.885783 148.899222 \n",
" 70.0 50.000000 1126.005223 149.457045 \n",
"\n",
" area_log \n",
"area_log_round tilt_round \n",
"1.2 20.0 1.293837 \n",
"1.4 0.0 1.478558 \n",
" 5.0 1.470355 \n",
" 10.0 1.456468 \n",
" 15.0 1.451879 \n",
" 20.0 1.452893 \n",
" 25.0 1.452640 \n",
" 30.0 1.458889 \n",
" 35.0 1.469130 \n",
" 40.0 1.476555 \n",
" 45.0 1.481497 \n",
" 50.0 1.478817 \n",
" 55.0 1.482462 \n",
"1.6 0.0 1.621102 \n",
" 5.0 1.603304 \n",
" 10.0 1.602465 \n",
" 15.0 1.604323 \n",
" 20.0 1.606736 \n",
" 25.0 1.609065 \n",
" 30.0 1.614560 \n",
" 35.0 1.620042 \n",
" 40.0 1.626475 \n",
" 45.0 1.633850 \n",
" 50.0 1.641924 \n",
" 55.0 1.649486 \n",
" 60.0 1.650578 \n",
" 65.0 1.658158 \n",
" 70.0 1.669261 \n",
"1.8 0.0 1.818853 \n",
" 5.0 1.795734 \n",
"... ... \n",
"2.8 70.0 2.899918 \n",
"3.0 0.0 2.989804 \n",
" 5.0 2.990732 \n",
" 10.0 2.985069 \n",
" 15.0 2.981504 \n",
" 20.0 2.975021 \n",
" 25.0 2.968738 \n",
" 30.0 2.972170 \n",
" 35.0 2.964612 \n",
" 40.0 2.961577 \n",
" 45.0 2.966355 \n",
" 50.0 2.972406 \n",
" 55.0 2.958968 \n",
" 60.0 3.001408 \n",
" 65.0 2.960412 \n",
"3.2 0.0 3.343962 \n",
" 5.0 3.303289 \n",
" 10.0 3.233721 \n",
" 15.0 3.216255 \n",
" 20.0 3.203539 \n",
" 25.0 3.205478 \n",
" 30.0 3.248956 \n",
" 35.0 3.291222 \n",
" 40.0 3.343874 \n",
" 45.0 3.245654 \n",
" 50.0 3.217785 \n",
" 55.0 3.373594 \n",
" 60.0 3.389600 \n",
" 65.0 3.190142 \n",
" 70.0 3.330911 \n",
"\n",
"[147 rows x 15 columns]"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"PV_grouped"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_array = (PV_grouped_all['PV_norm']).to_xarray()\n",
"plot_array.coords['area_log_round'] = 10**(plot_array.area_log_round)\n",
"\n",
"plot_array.attrs['long_name'] = 'PV potential per m$^2$ of roof (in kWh/m$^2$)'\n",
"\n",
"plt.figure()\n",
"ax = plt.subplot()\n",
"\n",
"VMIN = 0\n",
"VMAX = 130\n",
"\n",
"plot_array.plot(cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"\n",
"ax.set_yscale('log')\n",
"plt.xlabel('Roof tilt (in degree)') # Roof aspect\n",
"plt.ylabel('Roof area (in $m^2$)')\n",
"plt.ylim(bottom = 22)\n",
"\n",
"#ax.set_xticks([-180, -135, -90, -45, 0, 45, 90, 135, 180])\n",
"#ax.set_xticklabels(['N', 'NW', 'W', 'SW', 'S', 'SE', 'E', 'NE', 'N'])\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig('PV_per_roof_area_tilt_norm.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_array = (PV_grouped_all['yearly_std_PV'] / PV_grouped_all['yearly_PV_kWh']).to_xarray()\n",
"plot_array.coords['area_log_round'] = 10**(plot_array.area_log_round)\n",
"\n",
"plot_array.attrs['long_name'] = 'Relative uncertainty of annual $E_{PV}\\ (\\sigma_{PV}/E_{PV}$)'\n",
"\n",
"plt.figure()\n",
"ax = plt.subplot()\n",
"\n",
"VMIN = 0.2\n",
"VMAX = 0.8\n",
"\n",
"plot_array.plot(cmap = cm_PV, vmin = VMIN, vmax = VMAX)\n",
"\n",
"ax.set_yscale('log')\n",
"plt.xlabel('Roof tilt (in degree)') # Roof aspect\n",
"plt.ylabel('Roof area (in $m^2$)')\n",
"plt.ylim(bottom = 22)\n",
"\n",
"#ax.set_xticks([-180, -135, -90, -45, 0, 45, 90, 135, 180])\n",
"#ax.set_xticklabels(['N', 'NW', 'W', 'SW', 'S', 'SE', 'E', 'NE', 'N'])\n",
"\n",
"plt.tight_layout()\n",
"# plt.savefig('PV_unc_relative_area_tilt.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get hourly time plot"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"# aspect classes: 0: flat, 1: south, 2: east, 3: west, 4: north\n",
"PV_yearly['aspect_class'] = 3\n",
"# PV_yearly.loc[PV_yearly.AUSRICHTUNG > 45, 'aspect_class'] = 3\n",
"PV_yearly.loc[PV_yearly.AUSRICHTUNG < -45, 'aspect_class'] = 2\n",
"\n",
"PV_yearly.loc[abs(PV_yearly.AUSRICHTUNG) >= 135, 'aspect_class'] = 4\n",
"PV_yearly.loc[abs(PV_yearly.AUSRICHTUNG) <= 45 , 'aspect_class'] = 1\n",
"\n",
"PV_yearly.loc[PV_yearly.NEIGUNG == 0, 'aspect_class'] = 0 # FLAT ROOFS ARE 0\n",
"PV_yearly.loc[PV_yearly.available_area <= 8, 'aspect_class'] = -1\n",
"\n",
"PV_yearly['suitable'] = 0\n",
"PV_yearly.loc[(abs(PV_yearly.AUSRICHTUNG) <= 90) & (PV_yearly.available_area > 8), 'suitable'] = 1"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"pv_pot = xr.merge([EPV.pv_potential, unc_EPV.sigma_PV, \n",
" Gt.tilted_irradiance, Gt_unc_all.sigma_Gt_dep]).astype('float32')\n",
"pv_pot['aspect_class'] = PV_yearly.set_index('DF_UID').aspect_class.to_xarray()\n",
"pv_pot['suitable'] = PV_yearly.set_index('DF_UID').suitable.to_xarray()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (DF_UID: 9639231, timestamp: 146)\n",
"Coordinates:\n",
" * DF_UID (DF_UID) int64 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 ...\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
"Data variables:\n",
" pv_potential (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(10000, 146)>\n",
" sigma_PV (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(10000, 146)>\n",
" tilted_irradiance (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(10000, 146)>\n",
" sigma_Gt_dep (DF_UID, timestamp) float32 dask.array<shape=(9639231, 146), chunksize=(10000, 146)>\n",
" aspect_class (DF_UID) int64 -1 -1 2 2 3 3 -1 3 2 3 -1 -1 -1 -1 2 3 ...\n",
" suitable (DF_UID) int64 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 ..."
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pv_pot"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_mean = pv_pot.groupby('aspect_class').mean( dim = 'DF_UID')\n",
"pv_pot_mean['group_count'] = pv_pot.groupby('aspect_class').count(dim = 'DF_UID').suitable"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (aspect_class: 6, timestamp: 146)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * aspect_class (aspect_class) int64 -1 0 1 2 3 4\n",
"Data variables:\n",
" pv_potential (aspect_class, timestamp) float32 dask.array<shape=(6, 146), chunksize=(1, 146)>\n",
" sigma_PV (aspect_class, timestamp) float32 dask.array<shape=(6, 146), chunksize=(1, 146)>\n",
" tilted_irradiance (aspect_class, timestamp) float32 dask.array<shape=(6, 146), chunksize=(1, 146)>\n",
" sigma_Gt_dep (aspect_class, timestamp) float32 dask.array<shape=(6, 146), chunksize=(1, 146)>\n",
" suitable (aspect_class) float64 0.0 1.0 1.0 0.4566 0.5549 0.0\n",
" group_count (aspect_class) int64 4671346 408905 1185090 1082061 ..."
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pv_pot_mean"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_sum = pv_pot.groupby('suitable').sum( dim = 'DF_UID')\n",
"pv_pot_sum['group_count'] = pv_pot.groupby('suitable').count(dim = 'DF_UID').aspect_class"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (suitable: 2, timestamp: 146)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * suitable (suitable) int64 0 1\n",
"Data variables:\n",
" pv_potential (suitable, timestamp) float32 dask.array<shape=(2, 146), chunksize=(1, 146)>\n",
" sigma_PV (suitable, timestamp) float32 dask.array<shape=(2, 146), chunksize=(1, 146)>\n",
" tilted_irradiance (suitable, timestamp) float32 dask.array<shape=(2, 146), chunksize=(1, 146)>\n",
" sigma_Gt_dep (suitable, timestamp) float32 dask.array<shape=(2, 146), chunksize=(1, 146)>\n",
" aspect_class (suitable) int64 2737225 4006714\n",
" group_count (suitable) int64 6939991 2699240"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pv_pot_sum"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_sum.drop('aspect_class').to_netcdf( os.path.join( path, 'pv_gt_timeprofiles.nc' ) )"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Applications/anaconda2/envs/py3/lib/python3.6/site-packages/dask/array/numpy_compat.py:28: RuntimeWarning: invalid value encountered in true_divide\n",
" x = np.divide(x1, x2, out)\n"
]
}
],
"source": [
"pv_pot_mean.to_netcdf( os.path.join( path, 'pv_gt_timeprofiles_aspectclasses.nc' ) )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## PLOT HOURLY"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_sum = xr.open_dataset( os.path.join( path, 'pv_gt_timeprofiles.nc' ) )"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (suitable: 2, timestamp: 146)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * suitable (suitable) int64 0 1\n",
"Data variables:\n",
" pv_potential (suitable, timestamp) float32 ...\n",
" sigma_PV (suitable, timestamp) float32 ...\n",
" tilted_irradiance (suitable, timestamp) float32 ...\n",
" sigma_Gt_dep (suitable, timestamp) float32 ...\n",
" group_count (suitable) int64 ..."
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pv_pot_sum"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_sum['PV_GWh'] = pv_pot_sum.pv_potential / 1e9\n",
"pv_pot_sum['PV_GWh_max'] = pv_pot_sum.PV_GWh + pv_pot_sum.sigma_PV / 1e9\n",
"pv_pot_sum['PV_GWh_min'] = np.maximum(pv_pot_sum.PV_GWh - pv_pot_sum.sigma_PV / 1e9, 0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"def get_plottable_series(ds, var):\n",
" # Manipulate time stamps; choose hours from 3-20h (18 hours in total)\n",
" month = ds.timestamp.dt.month\n",
" hour = ds.timestamp.dt.hour\n",
" dt_index = (month - 1) * 24 + hour \n",
" \n",
" datetimeindex = np.zeros(24*12)\n",
" datetimeindex[dt_index] = ds[var].fillna(0).values\n",
" return datetimeindex"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"PV_pot = get_plottable_series(pv_pot_sum.isel(suitable = 1), 'PV_GWh')\n",
"PV_max = get_plottable_series(pv_pot_sum.isel(suitable = 1), 'PV_GWh_max')\n",
"PV_min = get_plottable_series(pv_pot_sum.isel(suitable = 1), 'PV_GWh_min')\n"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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\" width=\"1200\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize = (12, 3))\n",
"ax = plt.subplot()\n",
"\n",
"plt.plot(PV_pot, label = '$E_{PV}$')\n",
"plt.fill_between(range(len(PV_pot)), PV_min, PV_max, alpha = 0.3, label = '$E_{PV} \\pm \\sigma_{PV}$' ) \n",
"\n",
"ax.set_xticks(list(range(12, 24*12, 24)))\n",
"ax.set_xticklabels(calendar.month_abbr[1:])\n",
"ax.set_ylabel('Total PV potential (GWh)')\n",
"\n",
"plt.xlim((0, 24*12))\n",
"\n",
"ax = plt.gca()\n",
"ax.set_axisbelow(True)\n",
"ax.yaxis.grid(linestyle = '--')\n",
"\n",
"plt.legend()\n",
"plt.show()\n",
"plt.tight_layout()\n",
"plt.savefig('PV_hourly_w_unc.png', dpi = 300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot building roofs by aspect"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"pv_pot_mean = xr.open_dataset( os.path.join( path, 'pv_gt_timeprofiles_aspectclasses.nc' ) )"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (aspect_class: 6, timestamp: 146)\n",
"Coordinates:\n",
" * timestamp (timestamp) datetime64[ns] 2001-01-15T08:00:00 ...\n",
" * aspect_class (aspect_class) int64 -1 0 1 2 3 4\n",
"Data variables:\n",
" pv_potential (aspect_class, timestamp) float32 ...\n",
" sigma_PV (aspect_class, timestamp) float32 ...\n",
" tilted_irradiance (aspect_class, timestamp) float32 ...\n",
" sigma_Gt_dep (aspect_class, timestamp) float32 ...\n",
" suitable (aspect_class) float64 ...\n",
" group_count (aspect_class) int64 ..."
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pv_pot_mean"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"flat = get_plottable_series(pv_pot_mean.sel(aspect_class = 0), 'tilted_irradiance')\n",
"south = get_plottable_series(pv_pot_mean.sel(aspect_class = 1), 'tilted_irradiance')\n",
"east = get_plottable_series(pv_pot_mean.sel(aspect_class = 2), 'tilted_irradiance')\n",
"west = get_plottable_series(pv_pot_mean.sel(aspect_class = 3), 'tilted_irradiance')\n",
"north = get_plottable_series(pv_pot_mean.sel(aspect_class = 4), 'tilted_irradiance')\n"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"data": {
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" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
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" if (warnings) {\n",
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" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
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"\n",
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"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"1200\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize = (12, 3))\n",
"ax = plt.subplot()\n",
"\n",
"#plt.plot(flat, label = 'Flat')\n",
"plt.plot(north, label = 'North')\n",
"plt.plot(east , label = 'East')\n",
"plt.plot(west , label = 'West')\n",
"plt.plot(south, label = 'South')\n",
"\n",
"ax.set_xticks(list(range(12, 24*12, 24)))\n",
"ax.set_xticklabels(calendar.month_abbr[1:])\n",
"ax.set_ylabel('Tilted radiation ($W/m^2$)')\n",
"\n",
"plt.xlim((0, 12*24))\n",
"\n",
"ax = plt.gca()\n",
"ax.set_axisbelow(True)\n",
"ax.yaxis.grid(linestyle = '--')\n",
"\n",
"plt.legend()\n",
"plt.show()\n",
"plt.tight_layout()\n",
"plt.savefig('Irrad_hourly_aspects.png', dpi = 300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.4"
+ "version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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