'date', 'precipitation', 'temperature', 'evapotranspiration', 'flow',
'flow_mm'
]
df.index = df['date']
# One month aggregation using period as index :
precipitation = df['precipitation'].resample('M', kind='period').sum()
temperature = df['temperature'].resample('M', kind='period').mean()
evapotranspiration = df['evapotranspiration'].resample(
'm', kind='period').sum()
flow_mm = df['flow_mm'].resample('M', kind='period').sum()
df = pd.concat([precipitation, temperature, evapotranspiration, flow_mm],
axis=1)
df['date'] = df.index
input_handler = InputDataHandler(ModelGr2m, df)
warm_up_start_date = datetime.datetime(1989, 1, 1, 0, 0)
start_date = datetime.datetime(1990, 1, 1, 0, 0)
end_date = datetime.datetime(1999, 1, 1, 0, 0)
sub_input = input_handler.get_sub_period(warm_up_start_date, end_date)
air_gr_parameters = [265.072, 1.040]
model = ModelGr2m(sub_input, air_gr_parameters)
outputs = model.run()
filtered_input = model.input_data[model.input_data.index >= start_date]
filtered_output = outputs[outputs.index >= start_date]
plot_hydrograph(filtered_output, sub_input.data['flow_mm'])
from pathlib import Path
import pandas as pd
import datetime
from hydrogr import InputDataHandler, ModelGr6j
from hydrogr.plot_tools import plot_hydrograph
if __name__ == '__main__':
data_path = Path.cwd().parent / 'data'
df = pd.read_pickle(data_path / 'L0123001.pkl')
df.columns = [
'date', 'precipitation', 'temperature', 'evapotranspiration', 'flow',
'flow_mm'
]
df.index = df['date']
air_gr_parameters = [242.257, 0.637, 53.517, 2.218, 0.424, 4.759]
input_handler = InputDataHandler(ModelGr6j, df)
start_date = datetime.datetime(1989, 1, 1, 0, 0)
end_date = datetime.datetime(1999, 12, 31, 0, 0)
sub_input = input_handler.get_sub_period(start_date, end_date)
model = ModelGr6j(sub_input, air_gr_parameters)
model.set_initial_conditions(production_store_filling=0.3,
routing_store_filling=0.5)
outputs = model.run()
plot_hydrograph(outputs, sub_input.data['flow_mm'])
import pandas as pd
import datetime
from hydrogr import InputDataHandler, ModelGr4h
from hydrogr.plot_tools import plot_hydrograph
if __name__ == '__main__':
data_path = Path.cwd().parent / 'data'
# df = pd.read_csv(data_path / 'L0123003.csv')
# df['date'] = pd.to_datetime(df['date'], format='%d/%m/%Y %H:%M')
# df.to_pickle(data_path / 'L0123003.pkl')
df = pd.read_pickle(data_path / 'L0123003.pkl')
df.columns = [
'date', 'precipitation', 'temperature', 'evapotranspiration', 'flow',
'flow_mm'
]
df.index = df['date']
my_inputs_handler = InputDataHandler(ModelGr4h, df)
filtered_input = my_inputs_handler.get_sub_period(
datetime.datetime(2004, 1, 1, 0, 0),
datetime.datetime(2008, 1, 1, 0, 0))
model = ModelGr4h(filtered_input, [521.113, -2.918, 218.009, 4.124])
model.set_initial_conditions(production_store_filling=0.9,
routing_store_filling=0.9)
outputs = model.run()
print(outputs.head())
plot_hydrograph(outputs, my_inputs_handler.data['flow_mm'])