Python make_hills Examples

Example #1

File: test_obsim_log.py Project: misken/hillmaker

scenario_name = 'log_unitocc_test_5'
in_fld_name = 'EnteredTS'
out_fld_name = 'ExitedTS'
cat_fld_name = 'Unit'
start_analysis = '12/12/2015 00:00'
end_analysis = '12/19/2021 00:00'
# Optional inputs

tot_fld_name = 'OBTot'
bin_size_mins = 5
excludecats = ['Obs']

df = pd.read_csv(file_stopdata)
basedate = Timestamp('20150215 00:00:00')
df['EnteredTS'] = df.apply(lambda row:
                           Timestamp(round((basedate + pd.DateOffset(hours=row['Entered'])).value, -9)), axis=1)

df['ExitedTS'] = df.apply(lambda row:
                           Timestamp(round((basedate + pd.DateOffset(hours=row['Exited'])).value,-9)), axis=1)

# Filter input data by included included categories

df = df[df[cat_fld_name].isin(excludecats) == False]

hillmaker.make_hills(scenario_name, df, in_fld_name, out_fld_name,
                     start_analysis, end_analysis, cat_fld_name,
                     total_str=tot_fld_name, bin_size_minutes=bin_size_mins,
                     nonstationary_stats=False,
                     export_path='.',
                     cat_to_exclude=excludecats, verbose=1)

Example #2

File: test_obsim_log.py Project: misken/hillmaker-examples

scenario_name = 'log_unitocc_test'
in_fld_name = 'EnteredTS'
out_fld_name = 'ExitedTS'
cat_fld_name = 'Unit'
start_analysis = '4/1/2015 00:00'
end_analysis = '11/1/2017 00:00'

# Optional inputs

tot_fld_name = 'OBTot'
bin_size_mins = 60
excludecats = ['Obs']

df = pd.read_csv(file_stopdata)
basedate = Timestamp('20150215 00:00:00')
df['EnteredTS'] = df.apply(lambda row:
                           Timestamp(round((basedate + pd.DateOffset(hours=row['Entered'])).value, -9)), axis=1)

df['ExitedTS'] = df.apply(lambda row:
                           Timestamp(round((basedate + pd.DateOffset(hours=row['Exited'])).value,-9)), axis=1)

# Filter input data by included included categories

df = df[df[cat_fld_name].isin(excludecats) == False]

hillmaker.make_hills(scenario_name, df, in_fld_name, out_fld_name,
                     start_analysis, end_analysis, cat_fld_name,
                     total_str=tot_fld_name, bin_size_minutes=bin_size_mins,
                     export_path='./testing/output',
                     cat_to_exclude=excludecats, verbose=1)

Example #3

import pandas as pd
import hillmaker as hm

file_stopdata = '../data/ShortStay.csv'

# Required inputs
scenario = 'sstest_60'
in_fld_name = 'InRoomTS'
out_fld_name = 'OutRoomTS'
cat_fld_name = 'PatType'
start = '1/1/1996'
end = '3/30/1996 23:45'

# Optional inputs
bin_mins = 120
output_path = './output'


df = pd.read_csv(file_stopdata, parse_dates=[in_fld_name, out_fld_name])

hm.make_hills(scenario, df, in_fld_name, out_fld_name,
                     start, end, cat_fld_name,
                     tot_fld_name, bin_mins,
                     export_path=output_path,
                     verbose=1)

Example #4

scenario = 'ShortStay2_PatTypeSeverity'
in_fld_name = 'InRoomTS'
out_fld_name = 'OutRoomTS'
cat_fld_name = ['PatType', 'Severity']
start = '1/1/1996'
end = '3/30/1996 23:45'

# Optional inputs
bin_mins = 60
totals = 2
verbose = 1

stops_df = pd.read_csv(file_stopdata, parse_dates=[in_fld_name, out_fld_name])

hills = hm.make_hills(scenario,
                      stops_df,
                      in_fld_name,
                      out_fld_name,
                      start,
                      end,
                      cat_fld_name,
                      bin_mins,
                      cat_to_exclude=None,
                      nonstationary_stats=nonstationary_stats,
                      stationary_stats=stationary_stats,
                      totals=totals,
                      export_bydatetime_csv=True,
                      export_summaries_csv=True,
                      export_path='./output',
                      verbose=1)

Example #5

end_analysis = '11/1/2017 00:00'

# Optional inputs

bin_size_mins = 60

df = pd.read_csv(file_stopdata)
basedate = Timestamp('20150215 00:00:00')
df['EnteredTS'] = df.apply(lambda row: Timestamp(
    round((basedate + pd.DateOffset(hours=row['Entered'])).value, -9)),
                           axis=1)

df['ExitedTS'] = df.apply(lambda row: Timestamp(
    round((basedate + pd.DateOffset(hours=row['Exited'])).value, -9)),
                          axis=1)

# Filter input data by included included categories

df = df[df[cat_fld_name].isin(excludecats) == False]

hillmaker.make_hills(scenario_name,
                     df,
                     in_fld_name,
                     out_fld_name,
                     start_analysis,
                     end_analysis,
                     cat_fld_name,
                     bin_size_minutes=bin_size_mins,
                     export_path='./output',
                     verbose=1)

Example #6

File: test_shortstay.py Project: misken/hillmaker-examples

import pandas as pd

import hillmaker as hm

file_stopdata = '../data/ShortStay.csv'

# Required inputs
scenario = 'sstest_60'
in_fld_name = 'InRoomTS'
out_fld_name = 'OutRoomTS'
cat_fld_name = 'PatType'
start = '1/1/1996'
end = '3/30/1996 23:45'

# Optional inputs
tot_fld_name = 'SSU'
bin_mins = 120
output_path = './output'


df = pd.read_csv(file_stopdata, parse_dates=[in_fld_name, out_fld_name])

hm.make_hills(scenario, df, in_fld_name, out_fld_name,
                     start, end, cat_fld_name,
                     tot_fld_name, bin_mins,
                     cat_to_exclude=None,
                     export_path=output_path,
                     verbose=1)