def sample_weighted(self, series):
series0 = series
freq = self.settings["freq"]
series = series.resample(freq).mean()
series = timestep_weighted_resample(series0, series.index)
logger.info("Time Series %s were sampled down to freq %s with method "
"%s" % (self.name, freq, 'timestep_weighted_resample'))
return series
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from pastas.utils import timestep_weighted_resample, timestep_weighted_resample_fast
# make a daily series from monthly (mostly) values, without specifying the
# frequency of the original series
#series0 = pd.read_csv("data/tswr1.csv", index_col=0, parse_dates=True,
# squeeze=True)
index = pd.date_range('2000-1-1', '2001-1-1', freq='MS')
series0 = pd.Series(np.random.rand(len(index)), index)
series = series0.resample('d').mean()
series = timestep_weighted_resample(series0, series.index)
series2 = timestep_weighted_resample_fast(series0, 'd')
plt.figure()
series0.plot(label='Monthly (mostly)')
series.plot(label='Daily')
series2.plot(label='Daily (fast)', linestyle='--')
plt.legend()
# make a precipitation-series at 0:00 from values at 9:00
#series0 = pd.read_csv("data/tswr2.csv", index_col=0, parse_dates=True,
# squeeze=True)
index = pd.date_range('2000-1-1 9:00', '2000-1-10 9:00')
series0 = pd.Series(np.random.rand(len(index)), index)
series = timestep_weighted_resample(series0, series0.index.normalize())
series2 = timestep_weighted_resample_fast(series0, 'd')
plt.figure()
series0.plot(label='Original (9:00)')
import os
import pastas as ps
import matplotlib.pyplot as plt
from pastas.utils import timestep_weighted_resample
if not os.getcwd().endswith('examples'):
os.chdir('examples')
fname = 'data/MenyanthesTest.men'
meny = ps.read.MenyData(fname)
# make a daily series from monthly (mostly) values, without specifying the frequency of the original series
series0 = meny.IN['Extraction 1']['values']
series = series0.resample('d').mean()
series = timestep_weighted_resample(series0, series.index)
plt.figure()
series0.plot(label='Monthly (mostly)')
series.plot(label='Daily')
plt.legend()
# make a precipitation-series at 0:00 from values at 9:00
series0 = meny.IN['Precipitation']['values']
series = timestep_weighted_resample(series0, series0.index.normalize())
plt.figure()
series0.plot(label='Original (9:00)')
series.plot(label='Resampled (0:00)')
plt.legend()