# -*- coding: utf-8 -*- """ Created on Sun Feb 6 19:11:00 2022 @author: chris """ from main import attribut2dataframe demand_hist_path = 'C:/Users/chris/Documents/LVM_geoprocessing/Nachfrage_aus_Visum/cm_LVM2015_OD_totalDEMANDforHISTOGRAM.att' demand_hist_df = attribut2dataframe(demand_hist_path, False) print(demand_hist_df.min()) demand_hist_df2 = demand_hist_df[ demand_hist_df['$ODPAIR:MATVALUE(10000)'] > 1.0] #demand_hist_df2 = demand_hist_df2[demand_hist_df2['$ODPAIR:MATVALUE(10000)'] < 5.0] print(demand_hist_df2.min()) demand_hist_df2['$ODPAIR:MATVALUE(10000)'].hist(bins=100)
@author: chris """ import matplotlib.pyplot as plt from main import attribut2dataframe, att_path, pdf_path, svg_path import numpy as np act_ver = 'v5p1' att_file = att_path('C:/Users/chris/proj-lvm_files/Strecken_UAM_', act_ver) UAMcap4 = 4 * 24 * 4 UAMcap7 = 4 * 24 * 7 df = attribut2dataframe(att_file, False)#[0, 1, 2]) df = df[df['TSYSSET']=='UAM200'] rename_dict = {'BELPERS-OEV_AP__CM11M000_' + act_ver.upper(): '0', 'BELPERS-OEV_AP__CM11M050_' + act_ver.upper(): '50', 'BELPERS-OEV_AP__CM11M100_' + act_ver.upper(): '100', 'BELPERS-OEV_AP__CM11M150_' + act_ver.upper(): '150', 'BELPERS-OEV_AP__CM11M250_' + act_ver.upper(): '250', 'BELPERS-OEV_AP__CM11M500_' + act_ver.upper(): '500', 'LENGTH': 'LENGTH_km'} df.rename(columns = rename_dict, inplace=True) # if unit is also exported from Visum...: if False: df['LENGTH_km'] = df['LENGTH_km'].str[:-2].astype(np.double)
import matplotlib.pyplot as plt from main import attribut2dataframe, idx_aliases, cmap1, att_path, pdf_path, svg_path import pandas as pd pd.options.mode.chained_assignment = None # run version of Visum act_ver = 'v5p1' # specify input file vsys_file = att_path('C:/Users/chris/proj-lvm_files/VSYS_UAM_KM_H_C_', act_ver) # read VSYS attribute table df2 = attribut2dataframe(vsys_file, [0]) # rename index for legend in plot df2.rename(index=idx_aliases, inplace=True) # prepare filters # pers_km = ['PERSKM_AP__CM0', 'PERSKM_AP__CM50', 'PERSKM_AP__CM100', 'PERSKM_AP__CM250', 'PERSKM_AP__CM500', 'PERSKM_AP__CM10000'] # pers_h = ['PERSSTD_AP__CM0', 'PERSSTD_AP__CM50', 'PERSSTD_AP__CM100', 'PERSSTD_AP__CM250', 'PERSSTD_AP__CM500', 'PERSSTD_AP__CM10000'] # V4: #pers_km = ['PERSKM_AP__CM0_V4', 'PERSKM_AP__CM50_V4', 'PERSKM_AP__CM100_V4', 'PERSKM_AP__CM250_V4', 'PERSKM_AP__CM500_V4', 'PERSKM_AP__CM1000_V4'] #pers_h = ['PERSSTD_AP__CM0_V4', 'PERSSTD_AP__CM50_V4', 'PERSSTD_AP__CM100_V4', 'PERSSTD_AP__CM250_V4', 'PERSSTD_AP__CM500_V4', 'PERSSTD_AP__CM1000_V4'] #pers_cases = ['LINBEF_AP__CM0_V4', 'LINBEF_AP__CM50_V4', 'LINBEF_AP__CM100_V4', 'LINBEF_AP__CM250_V4', 'LINBEF_AP__CM500_V4', 'LINBEF_AP__CM1000_V4'] pers_cases = [ 'LINBEF_AP__CM11M000_' + act_ver.upper(), 'LINBEF_AP__CM11M050_' + act_ver.upper(),
df_2write['TOZONE\YCOORD'].astype(str) + \ ')' # print(df_2write.head()) df_2write.to_csv(path + 'test4.csv', sep ='\t', index=False, quoting=csv.QUOTE_NONE) return None def create_qgisEXP(df_in, path): df_2write = df_in df_2write.to_csv(path + 'test4.csv', sep ='\t', index=False, quoting=csv.QUOTE_NONE) return None cmPLOT = False in_path = 'C:/Users/chris/Documents/LVM_geoprocessing/Nachfrage_aus_Visum/cm_LVM_OD_time_demand_filtered_geq1.att' out_path = 'C:/Users/chris/Documents/LVM_geoprocessing/Nachfrage_aus_Visum/' df = attribut2dataframe(in_path, False).rename(columns={'$ODPAIR:FROMZONENO': 'FROMZONENO'}) # add cloumn for beeline speed df['beeline_speed_PuT'] = ( 60 * df['DIRECTDIST'] / df['MATVALUE(309)']) # add cloumn for ratio PrT-speed and PuT-speed df['speed_ratio'] = ( df['MATVALUE(309)'] / df['MATVALUE(116)'] ) # filter df #df = df[ (df['MATVALUE(10000)'] >= 1) ] #df = df[ (df['speed_ratio'] >= 1.5) ] #df = df[ (df['DIRECTDIST'] >= 250) ]
# -*- coding: utf-8 -*- """ Created on Fri Apr 2 17:11:07 2021 @author: chris """ from main import attribut2dataframe, GEH, roundup # , cmap1 import numpy as np import matplotlib.pyplot as plt # import pandas as pd path = 'C:/Users/chris/proj-lvm_files/EinsteigerVSySDiff2.att' df = attribut2dataframe(path, False) # [0, 1, 2]) df_temp_count = df[['NAME', 'NEU_EINST_N14']] df = df[df['B_BAYERN'] == 1] print(len(df_temp_count)) print(df_temp_count['NEU_EINST_N14'].isna().sum()) print('================') # print(df_temp_count) # print(np.where(pd.isnull(df))) # todo:, Evtl. Filtern auf Zählwert > ''
""" Created on Wed May 26 09:56:25 2021 @author: chris """ import matplotlib.pyplot as plt from main import attribut2dataframe, att_path, pdf_path, svg_path, cmap1 # import numpy as np act_ver = 'v5p1' att_file = att_path('C:/Users/chris/proj-lvm_files/STOPS_UAM_', act_ver) # read STOPS. ACHTUNG!!! Auf Index-Column aufpassen, insb. auch beim Export df3 = attribut2dataframe(att_file, [2]) df3 = df3[df3['CM_UAM'] == 1] # remove some dirt... hbf_aliases = {'Ingolstadt Hbf.': 'Ingolstadt Hbf', 'Augsburg, Hauptbahnhof': 'Augsburg Hbf'} df3.rename(index=hbf_aliases, inplace=True) plot_lang = 'eng' # 'deu' if plot_lang == 'eng': hbf_aliases = {'München Hbf': 'Munich Central', 'München-Moosach': 'Munich Moosach', 'München, Studentenstadt': 'Munich StuSta', 'Würzburg Hauptbahnhof': 'Würzburg Central', 'Nürnberg Hbf': 'Nuremberg Central', 'Augsburg Hbf': 'Augsburg Central', 'Ulm Hbf': 'Ulm Central', 'München Flughafen': 'Munich Airport'} df3.rename(index=hbf_aliases, inplace=True)