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prepare_area_query.py
b2056863329baw_solar

prepare_area_query.py
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			import pandas as pd
			import numpy as np
			from rooftop_handling import get_tilt_category, get_orientation_category

			import os
			import sys
			import time

			###### GET DATA #########

			ROOFS_info = sys.argv[1]
			ROOFS_corners = sys.argv[2]

			PANELS_ftr = sys.argv[3]
			SHADE_ftr = sys.argv[4]
			SHADE_cats = sys.argv[5]

			OUTFILE = sys.argv[6]

			############################

			TILT_FIELD = 'NEIGUNG'
			ORIENTATION_FIELD = 'AUSRICHTUN'

			## == FUNCTION DEFINITIONS ==

			def print_input():
			print("")
			print('Rooftop info file: %s' %ROOFS_info)
			print('Roof corner file: %s' %ROOFS_corners)

			print('Panelling feature file: %s' %PANELS_ftr)
			print('Shading feature file: %s' %SHADE_ftr)
			print('Shading categories file: %s' %SHADE_cats)

			print('Output file: %s' %OUTFILE)
			print("")

			def replace_shade_NaNs(roofs, shade_cats):
			# finds all rows in "roofs" with column "shaded_area_ratio_ftr" == NaN, and replaces these with the mean values
			# in "shade_cats" based on the categorizations of "tilt_cat" and "orientation_cat" (specified in rooftop_handling.py)

			# get columns with shaded area NaN and calculate tilt and orientation categories for these
			shade_null_idx = roofs.shaded_area_ratio_ftr.isnull()
			replacemnt_shade = roofs.loc[shade_null_idx, ['DF_UID', TILT_FIELD, ORIENTATION_FIELD]]
			replacemnt_shade.rename( { TILT_FIELD : 'NEIGUNG', ORIENTATION_FIELD : 'AUSRICHTUNG' }, axis = 1, inplace = True)

			replacemnt_shade['tilt_cat'] = replacemnt_shade.apply(get_tilt_category, axis = 1)
			replacemnt_shade['orientation_cat'] = replacemnt_shade.apply(get_orientation_category, axis = 1)

			# find mean values for all rows with shaded area ratio NaN and replace
			replaced_shade = replacemnt_shade.merge(shade_cats.loc[:,['orientation_cat', 'tilt_cat', 'fully_shaded_ratio']], how = 'left', on = ['orientation_cat', 'tilt_cat'])
			roofs.loc[shade_null_idx, 'shaded_area_ratio_ftr'] = replaced_shade.fully_shaded_ratio.values

			return roofs

			## == Load data ==

			print_input()

			timer = time.time()

			roofs_info = pd.read_csv(ROOFS_info)
			roofs_corners = pd.read_csv(ROOFS_corners)

			panels_ftr = pd.read_csv(PANELS_ftr)
			shade_ftr = pd.read_csv(SHADE_ftr, usecols = ['DF_UID', 'fully_shaded_ratio'])
			shade_cats = pd.read_csv(SHADE_cats)

			print('Read all data in %.3f seconds' %(time.time() - timer))
			timer = time.time()

			## == Merge roofs with shading info and roofs with panelled area info

			## Step 1: merge information of number of vertices (roofs_corners) to rooftop information
			roofs = roofs_info.merge(roofs_corners, on = 'DF_UID')

			print('Merged rooftop information in %.3f seconds' %(time.time() - timer))
			timer = time.time()

			## Step 2: add panel information (available for all rooftops, based on Sonnendach roof polygons)
			## NOTE: all roofs with panelled area == 0 can be excluded from analysis - they are unsuitable for PV installation
			roofs_with_available_area = panels_ftr[panels_ftr.panel_count > 0]
			set_panels_ftr = roofs_with_available_area.loc[:,['DF_UID', 'panel_tilt', 'best_align', 'panelled_area_ratio']]

			# merge panelled area ratio for features
			roofs_w_panels = roofs.merge(set_panels_ftr, how = 'inner', on = 'DF_UID')
			roofs_w_panels.rename( {'panelled_area_ratio' : 'panelled_area_ratio_ftr'}, axis = 1, inplace = True)

			print('Added panel fitting information in %.3f seconds' %(time.time() - timer))
			timer = time.time()

			## Step 3: add shading information (shaded area only)
			## Not available for all roofs (missing approx. 20%) - unavailable data is filled using shade_cats
			roofs_w_shade = roofs_w_panels.merge(shade_ftr, how = 'left', on = 'DF_UID')
			roofs_w_shade.rename({ 'fully_shaded_ratio' : 'shaded_area_ratio_ftr' }, axis = 1, inplace = True)

			print('Added shading information in %.3f seconds' %(time.time() - timer))
			timer = time.time()

			roofs_final = replace_shade_NaNs( roofs_w_shade, shade_cats )

			print('Replaced NaNs of shading in %.3f seconds' %(time.time() - timer))
			timer = time.time()

			## == Save results as csv
			roofs_final.to_csv(OUTFILE, index = False)

			print('DONE - saved output to %s' %OUTFILE)

solarPOT/Available_area/prepare_area_query.pyb2056863329baw_solar

prepare_area_query.pyView Options

solarPOT/Available_area/prepare_area_query.py
b2056863329baw_solar

prepare_area_query.py
View Options