# -*- 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)