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hrzn/river_flow_generate_data.py

Last active January 27, 2023 15:35
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river_flow_generate_data.py
# First, some imports:
import numpy as np
from darts.utils import timeseries_generation as tg
np.random.seed(42)
LENGTH = 3 * 365 # 3 years of daily data
# Melting: a sine with yearly periodicity and additive white noise
melting = (tg.sine_timeseries(length=LENGTH,
value_frequency=(1/365),
freq='D',
column_name='melting')
+ 0.15 * tg.gaussian_timeseries(length=LENGTH, freq='D'))
# Rainfalls: a sine with bi-weekly periodicity and additive white noise
rainfalls = (tg.sine_timeseries(length=LENGTH,
value_frequency=(1/14),
freq='D',
column_name='rainfall')
+ 0.3 * tg.gaussian_timeseries(length=LENGTH, freq='D'))
# We scale and shift the melting by 5 days; giving us the melting contribution
melting_contribution = 0.5 * melting.shift(5)
# We compute similar contribution from the rainfalls
all_contributions = [melting_contribution] + [0.1 * rainfalls.shift(lag) for lag in range(5)]
# We compute the final flow as the sum of everything,
# trimming series so they all have the same start time
flow = sum([series[melting_contribution.start_time():][:melting.end_time()]
for series in all_contributions]).with_columns_renamed('melting', 'flow')
# add some white noise
flow += 0.1 * tg.gaussian_timeseries(length=len(flow))
melting.plot()
rainfalls.plot()
flow.plot(lw=4)
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