예제 #1
0
    out_number = out_integer + decimal_part
    return out_number


def add_percent_sign(input):
    output = str(input) + " %"
    return output


# datafile = 'D:/soundcat/soundcat/outputs/daysim_outputs.h5'
# datafile = 'R:/JOE/summarize/daysim_outputs.h5'
datafile = "Q:/soundcast/outputs/daysim_outputs.h5"
guidefile = "Q:/soundcast/scripts/summarize/inputs/CatVarDict.xlsx"
districtfile = "Q:/soundcast/scripts/summarize/inputs/TAZ_TAD_County.csv"
urbcen = "Q:/soundcast/scripts/summarize/inputs/parcels_in_urbcens.csv"
data = h5toDF.convert(datafile, guidefile, "Results")
zone_district = get_districts(districtfile)
parcels_regional_centers = pd.DataFrame.from_csv(urbcen)
HHPer = pd.merge(
    data["Household"][["hhno", "hhparcel"]], data["Person"][["pwpcl", "hhno", "psexpfac", "pno"]], on="hhno"
)
hh_center = pd.merge(
    HHPer[["hhno", "pno", "hhparcel", "psexpfac"]],
    parcels_regional_centers,
    "outer",
    left_on="hhparcel",
    right_index=True,
)
hh_center = hh_center.dropna(subset=["NAME"])

center_populations = hh_center[["NAME", "psexpfac"]].groupby("NAME").sum()["psexpfac"]
예제 #2
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    return merge_trip_hh


# Get the data
SURVEY_DAYS = 2

zone_district = pd.DataFrame.from_csv(model_dir + districtfile, index_col=None)

#Model Outputs
trip_variables = [
    'otaz', 'dtaz', 'travtime', 'travcost', 'travdist', 'pno', 'mode',
    'tour_id', 'opcl', 'dpcl', 'dorp', 'dpurp'
]
hh_variables = ['hhno', 'hhincome', 'hhvehs', 'hhtaz']
person_variables = ['hhno', 'pno', 'pagey', 'pgend', 'id']
outputs = h5toDF.convert(model_dir + h5_results_file, model_dir + guidefile,
                         'outputs')
trips_output = get_variables_trips(outputs, trip_variables, hh_variables,
                                   person_variables)
trips_output = pd.merge(trips_output,
                        zone_district,
                        left_on='dtaz',
                        right_on='TAZ')
bikes_output = trips_output.loc[(trips_output['mode'] == 'Bike')]

#Household Survey
trip_variables_survey = [
    'otaz', 'dtaz', 'travtime', 'travcost', 'travdist', 'pno', 'mode', 'opcl',
    'dpcl', 'dorp', 'dpurp', 'hhno', 'trexpfac'
]
person_variables_survey = ['hhno', 'pno', 'pagey', 'pgend']
survey = h5toDF.convert(model_dir + h5_comparison_file, model_dir + guidefile,
예제 #3
0
    out_integer = ','.join(integer_list)
    out_number = out_integer + decimal_part
    return out_number

def add_percent_sign(input):
    output = str(input) + ' %'
    return output


#datafile = 'D:/soundcat/soundcat/outputs/daysim_outputs.h5'
#datafile = 'R:/JOE/summarize/daysim_outputs.h5'
datafile = 'Q:/soundcast/outputs/daysim_outputs.h5'
guidefile = 'Q:/soundcast/scripts/summarize/inputs/CatVarDict.xlsx'
districtfile = 'Q:/soundcast/scripts/summarize/inputs/TAZ_TAD_County.csv'
urbcen = 'Q:/soundcast/scripts/summarize/inputs/parcels_in_urbcens.csv'
data = h5toDF.convert(datafile, guidefile, 'Results')
zone_district = get_districts(districtfile)
parcels_regional_centers = pd.DataFrame.from_csv(urbcen)
HHPer = pd.merge(data['Household'][['hhno', 'hhparcel']], data['Person'][['pwpcl', 'hhno', 'psexpfac', 'pno']], on = 'hhno')
hh_center = pd.merge(HHPer[['hhno', 'pno', 'hhparcel', 'psexpfac']], parcels_regional_centers,
                     'outer', left_on = 'hhparcel', right_index = True)
hh_center = hh_center.dropna(subset = ['NAME'])

center_populations = hh_center[['NAME', 'psexpfac']].groupby('NAME').sum()['psexpfac']
total_population = pd.Series(data = hh_center['psexpfac'].sum(), index = ['Total'])
center_populations = center_populations.append(total_population)

work_center = pd.merge(HHPer[['hhno', 'pwpcl']], parcels_regional_centers,
                       'outer', left_on = 'pwpcl', right_index = True)
work_center = work_center.dropna(subset = ['NAME'])
예제 #4
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    out_number = out_integer + decimal_part
    return out_number


def add_percent_sign(input):
    output = str(input) + ' %'
    return output


#datafile = 'D:/soundcat/soundcat/outputs/daysim_outputs.h5'
#datafile = 'R:/JOE/summarize/daysim_outputs.h5'
datafile = 'Q:/soundcast/outputs/daysim_outputs.h5'
guidefile = 'Q:/soundcast/scripts/summarize/inputs/CatVarDict.xlsx'
districtfile = 'Q:/soundcast/scripts/summarize/inputs/TAZ_TAD_County.csv'
urbcen = 'Q:/soundcast/scripts/summarize/inputs/parcels_in_urbcens.csv'
data = h5toDF.convert(datafile, guidefile, 'Results')
zone_district = get_districts(districtfile)
parcels_regional_centers = pd.DataFrame.from_csv(urbcen)
HHPer = pd.merge(data['Household'][['hhno', 'hhparcel']],
                 data['Person'][['pwpcl', 'hhno', 'psexpfac', 'pno']],
                 on='hhno')
hh_center = pd.merge(HHPer[['hhno', 'pno', 'hhparcel', 'psexpfac']],
                     parcels_regional_centers,
                     'outer',
                     left_on='hhparcel',
                     right_index=True)
hh_center = hh_center.dropna(subset=['NAME'])

center_populations = hh_center[['NAME',
                                'psexpfac']].groupby('NAME').sum()['psexpfac']
total_population = pd.Series(data=hh_center['psexpfac'].sum(), index=['Total'])
예제 #5
0
    merge_hh_person.reset_index()
    merge_trip_hh = pd.merge(trip_data, merge_hh_person, 'inner',  on =('hhno', 'pno'))
    return merge_trip_hh


# Get the data
SURVEY_DAYS =2


zone_district = pd.DataFrame.from_csv(model_dir+districtfile, index_col = None)

#Model Outputs
trip_variables = ['otaz', 'dtaz', 'travtime', 'travcost',  'travdist', 'pno', 'mode', 'tour_id', 'opcl', 'dpcl', 'dorp', 'dpurp']
hh_variables = ['hhno', 'hhincome', 'hhvehs', 'hhtaz']
person_variables = ['hhno', 'pno', 'pagey', 'pgend', 'id']
outputs = h5toDF.convert(model_dir + h5_results_file,model_dir+guidefile, 'outputs')
trips_output = get_variables_trips(outputs, trip_variables, hh_variables, person_variables)
trips_output =  pd.merge(trips_output, zone_district, left_on = 'dtaz', right_on = 'TAZ')
bikes_output = trips_output.loc[(trips_output['mode']=='Bike')]


#Household Survey
trip_variables_survey = ['otaz', 'dtaz', 'travtime', 'travcost',  'travdist', 'pno', 'mode', 'opcl', 'dpcl', 'dorp', 'dpurp', 'hhno', 'trexpfac']
person_variables_survey = ['hhno', 'pno', 'pagey', 'pgend']
survey = h5toDF.convert(model_dir +h5_comparison_file, model_dir+guidefile, 'survey')
trips_survey = get_variables_trips_survey(survey, trip_variables_survey , person_variables_survey, hh_variables)
trips_survey =  pd.merge(trips_survey, zone_district, left_on = 'dtaz', right_on = 'TAZ')
bikes_survey = trips_survey.loc[(trips_survey['mode']=='Bike')]
bike_survey_geo = pd.merge(bikes_output, zone_district, left_on = 'dtaz', right_on = 'TAZ')

#Do some summaries###########