1 | # -*- coding: utf-8 -*- |
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2 | |||
3 | import pandas as pd |
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4 | |||
5 | from oemof.solph import processing |
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6 | |||
7 | |||
8 | def test_disaggregate_timeindex(): |
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9 | ti_1 = pd.date_range("2020-01-01", periods=10, freq="h") |
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10 | ti_2 = pd.date_range("2030-01-01", periods=20, freq="h") |
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11 | ti_3 = pd.date_range("2040-01-01", periods=40, freq="h") |
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12 | ti = ti_1.union(ti_2).union(ti_3) |
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13 | |||
14 | periods = [ti_1, ti_2, ti_3] |
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15 | tsa_parameters = [ |
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16 | {"timesteps_per_period": 5, "order": [1, 0]}, |
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17 | {"timesteps_per_period": 5, "order": [1, 0, 0, 1]}, |
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18 | {"timesteps_per_period": 10, "order": [1, 0, 0, 1]}, |
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19 | ] |
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20 | |||
21 | for p, period_data in enumerate(tsa_parameters): |
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22 | if p == 0: |
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23 | result_index = processing._disaggregate_tsa_timeindex( |
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24 | periods[p], period_data |
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25 | ) |
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26 | else: |
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27 | result_index = result_index.union( |
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0 ignored issues
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28 | processing._disaggregate_tsa_timeindex(periods[p], period_data) |
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29 | ) |
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30 | |||
31 | assert all(result_index == ti) |
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32 |