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solarPOT/Shading/fill_shading_CH_v2.py
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fill_shading_CH_v2.py
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import pandas as pd
import numpy as np
import xarray as xr
from rooftop_handling import get_tilt_category, get_orientation_category
import os
import time
## == PATH DEFINITIONS == ##
path = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/shading_stats'
data = 'CH_LV03/CH_shading_all.csv'
cats = 'CH_shading_categories.csv'
roofs = '/work/hyenergy/output/solar_potential/geographic_potential/available_area/ROOFS_CH_replaced.csv'
## == LOAD DATA == ##
tt = time.time()
print('\nReading data ...')
shading_cats = pd.read_csv( os.path.join( path, cats ))
roof_cols = pd.read_csv( roofs, usecols = ['DF_UID', 'NEIGUNG', 'AUSRICHTUNG'] )
shading = pd.read_csv( os.path.join( path, data ))
print('Finished in %.3f seconds\n' %(time.time()-tt))
## == GET ALL ROOF UIDs == ##
tt = time.time()
print('Merging roofs and shading...')
all_roofs = roof_cols.merge( shading, on = 'DF_UID', how = 'left' )
all_roofs.drop_duplicates(inplace = True)
print('Finished in %.3f seconds\n' %(time.time()-tt))
## == GET MISSING ROOF ID'S & CORRESPONDING DATA == ##
tt = time.time()
print('Getting replacement values...')
shade_null_idx = all_roofs[ 'fully_shaded_ratio' ].isnull()
replacemnt_shade = all_roofs.loc[shade_null_idx, ['DF_UID', 'NEIGUNG', 'AUSRICHTUNG']]
replacemnt_shade['tilt_cat'] = replacemnt_shade.apply(get_tilt_category, axis = 1)
replacemnt_shade['orientation_cat'] = replacemnt_shade.apply(get_orientation_category, axis = 1)
REPLACEMENT = replacemnt_shade.merge(shading_cats, how = 'left', on = ['orientation_cat', 'tilt_cat'])
print('Finished in %.3f seconds\n' %(time.time()-tt))
## == REPLACE MISSING DATA == ##
tt = time.time()
print('Replacing missing data...')
replace = REPLACEMENT[ all_roofs.columns ]
all_roofs.loc[shade_null_idx] = replace.values
print('Finished in %.3f seconds\n' %(time.time()-tt))
## == SELECT RELEVANT COLUMNS == ##
tt = time.time()
print('Saving fully shaded data to file...')
data = all_roofs[ shading.columns ]
fully_shaded = data[['DF_UID', 'non_null_cells', 'n_cells', 'fully_shaded_ratio']].set_index('DF_UID')
partly_shaded = data.drop( columns = ['non_null_cells', 'n_cells', 'fully_shaded_ratio'] ).set_index('DF_UID')
print(fully_shaded.head())
print(fully_shaded.columns)
# fully_shaded.to_csv("/work/hyenergy/output/solar_potential/geographic_potential/available_area/CH_fully_shaded_replaced.csv")
print('Finished in %.3f seconds\n' %(time.time()-tt))
## == RENAME COLUMNS OF PARTLY SHADING == ##
tt = time.time()
print('Renaming partly shaded rows to timestamps...')
col_dict = {}
for col_name in partly_shaded.columns:
tmp = col_name.split('_')
if tmp[0] == 'mean':
month = tmp[1]
hour = tmp[2]
else: continue
col_dict[ col_name ] = pd.to_datetime('2001-%s-15 %s' %(month, hour))
# partly_shaded.rename( { col_name : pd.to_datetime('2001-%s-15 %s' %(month, hour))}, axis = 1, inplace = True )
print(col_dict)
partly_shaded.rename( col_dict, axis = 1, inplace = True )
print(partly_shaded.head())
print(partly_shaded.columns)
print('Finished in %.3f seconds\n' %(time.time()-tt))
tt = time.time()
print('Saving replaced partly shading stats to file...')
partly_shaded.to_csv("/scratch/walch/scratch/CH_partly_shaded_replaced.csv")
print('Finished in %.3f seconds\n' %(time.time()-tt))
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