Source code for energy_analysis_toolbox.tests.fake.timeseries
import numpy as np
import pandas as pd
DAY_DEFAULT = pd.Timestamp("2020-03-05")
np.random.seed(42)
[docs]
def example_volume_one_day(day_start=None, total_volume=1.0):
"""Return an example series of "volume" on a day.
"volume" means any quantity which follows a conservation law.
The total volume sums to 1(arbitrary unit) so that it can easily be scaled to
match a target daily volume. The time location of the consumption as well as
proportions is summarized in the following diagram::
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Consumption
|__|__|__|__|__|__|_3|__|._|__|__|__|__|_1.|__|__|__|__|__|__|_2|_3|__|__|
Parameters
----------
day_start : pd.Timestamp
Date for which the data are generated. The default is None in case
data are generated for 2020-03-05.
total_volume : float
Total volume consumed during the example day (used to scale the series
represented above). Default is 1 , meaning that the series returned by
the function sums up to 1.
Returns
-------
day_example : pd.Series
An example consumption of an equivalent volume with 30min timestep.
The series is sampled such that the value with label ``ti`` is the
volume associated to the interval ``[ti, ti=1[``.
"""
day_start = day_start or DAY_DEFAULT
begin = pd.Timestamp(day_start).floor("D")
index_day = pd.date_range(begin, periods=48, freq="30min")
day_example = pd.Series(np.zeros(index_day.size), index=index_day)
day_example.iloc[13] = 0.3 # 6h30 - 30%
day_example.iloc[16] = 0.05 # 8h - 5%
day_example.iloc[27] = 0.15 # 13h30 - 15%
day_example.iloc[41] = 0.2 # 20h30 - 20%
day_example.iloc[43] = 0.3 # 21h30 - 30%
return day_example * total_volume
