from idf_analysis import IntensityDurationFrequencyAnalyse
from idf_analysis.definitions import *
import pandas as pd
from os import path
import matplotlib.pyplot as plt
# sub-folder for the results
output_directory = path.join('ehyd_112086_idf_data')
# initialize of the analysis class
idf = IntensityDurationFrequencyAnalyse(series_kind=SERIES.PARTIAL, worksheet=METHOD.KOSTRA, extended_durations=True)
# reading the pandas series of the precipitation (data from ehyd.gv.at - ID=112086)
series = pd.read_parquet('ehyd_112086.parquet')['precipitation']
# setting the series for the analysis
idf.set_series(series)
# idf.write_parameters(path.join(output_directory, 'idf_parameters.yaml'))
# exit()
# auto-save the calculated parameter so save time for a later use
idf.auto_save_parameters(path.join(output_directory, 'idf_parameters.yaml'))
idf.result_figure(color=False)
# --------
# plotting the IDF curves
fig, ax = idf.result_figure(color=True)
fig.set_size_inches(12, 8)
fig.tight_layout()
fig.savefig(path.join(output_directory, 'idf_curves_plot_color.png'), dpi=200)
plt.close(fig)
if path.isfile(fn):
df = pd.read_csv(fn, index_col=[0, 1])
df.columns = df.columns.astype(int)
else:
df = ehyd_design_rainfall_ascii_reader(
get_ehyd_file(grid_point_number=grid_point_number))
df.to_csv(fn)
idf_table = get_max_calculation_method(df)
idf_table = df.xs('ÖKOSTRA',
axis=0,
level=INDICES.CALCULATION_METHOD,
drop_level=True).copy()
idf_reverse = IntensityDurationFrequencyAnalyse(series_kind=SERIES.PARTIAL,
worksheet=METHOD.KOSTRA,
extended_durations=True)
idf_reverse._parameter.reverse_engineering(idf_table)
output_directory = path.join(f'design_rain_ehyd_{grid_point_number}')
idf_reverse.auto_save_parameters(
path.join(output_directory, 'idf_parameters.yaml'))
# exit()
# ----------------------------------
max_duration = 2880
fig, ax = idf_reverse.result_figure(color=True,
logx=True,
max_duration=max_duration)
fig.set_size_inches(12, 8)
ax = idf_table.loc[:max_duration, [1, 2, 5, 10, 50, 100]].plot(ax=ax,
from idf_analysis import IntensityDurationFrequencyAnalyse
from idf_analysis.definitions import *
import pandas as pd
from os import path
# sub-folder for the results
output_directory = path.join('ehyd_112086_idf_data')
# initialize of the analysis class
idf = IntensityDurationFrequencyAnalyse(series_kind=SERIES.PARTIAL, worksheet=METHOD.KOSTRA, extended_durations=True)
# reading the pandas series of the precipitation (data from ehyd.gv.at - ID=112086)
series = pd.read_parquet('ehyd_112086.parquet')['precipitation']
# setting the series for the analysis
idf.set_series(series)
# auto-save the calculated parameter so save time for a later use
idf.auto_save_parameters(path.join(output_directory, 'idf_parameters.yaml'))
# --------
# idf.write_return_periods_frame(path.join(output_directory, 'idf_return_periods_frame.parq'))
# exit()
# idf.auto_save_return_periods_frame(path.join(output_directory, 'idf_return_periods_frame.parq'))
# --------
# events = idf.rain_events
# idf.add_max_return_periods_to_events(events)
# idf.write_rain_events(path.join(output_directory, 'events.csv'), sep=',', decimal='.')
# exit()
# idf.auto_save_rain_events(path.join(output_directory, 'events.csv'), sep=',', decimal='.')
from idf_analysis import IntensityDurationFrequencyAnalyse
from idf_analysis.definitions import *
import pandas as pd
from os import path
# sub-folder for the results
output_directory = path.join('ehyd_112086_idf_data')
# initialize of the analysis class
idf = IntensityDurationFrequencyAnalyse(series_kind=PARTIAL, worksheet=DWA, extended_durations=True)
# reading the pandas series of the precipitation (data from ehyd.gv.at - ID=112086)
series = pd.read_parquet('ehyd_112086.parquet')['precipitation']
# setting the series for the analysis
idf.set_series(series)
# auto-save the calculated parameter so save time for a later use
idf.auto_save_parameters(path.join(output_directory, 'idf_parameters.yaml'))
# --------
# idf.write_return_periods_frame(path.join(output_directory, 'idf_return_periods_frame.parq'))
# exit()
idf.auto_save_return_periods_frame(path.join(output_directory, 'idf_return_periods_frame.parq'))
# --------
# events = idf.rain_events
# idf.add_max_return_periods_to_events(events)
# idf.write_rain_events(path.join(output_directory, 'events.csv'), sep=',', decimal='.')
# exit()
idf.auto_save_rain_events(path.join(output_directory, 'events.csv'), sep=',', decimal='.')
def set_series(self, series):
IntensityDurationFrequencyAnalyse.set_series(self, series)
self._sri_frame = None
def __init__(self, *args, method=METHODS.SCHMITT, **kwargs):
IntensityDurationFrequencyAnalyse.__init__(self, *args, **kwargs)
self.method = method
self._sri_frame = None
from idf_analysis import IntensityDurationFrequencyAnalyse
from idf_analysis.definitions import *
import pandas as pd
from os import path
# sub-folder for the results
output_directory = path.join('ehyd_112086_idf_data')
# initialize of the analysis class
idf = IntensityDurationFrequencyAnalyse(series_kind=SERIES.PARTIAL,
worksheet=METHOD.KOSTRA,
extended_durations=True)
# reading the pandas series of the precipitation (data from ehyd.gv.at - ID=112086)
# series = pd.read_parquet('ehyd_112086.parquet')['precipitation']
# setting the series for the analysis
# idf.set_series(series)
# idf.write_parameters(path.join(output_directory, 'idf_parameters.yaml'))
# exit()
# auto-save the calculated parameter so save time for a later use
idf.auto_save_parameters(
path.join(output_directory, 'idf_parameters_OLD_test.yaml'))