Add wrappers for R's "arima" and "ets" functions
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10 changed files with 441 additions and 88 deletions
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@ -5,157 +5,149 @@ import math
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import pandas as pd
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import pytest
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from tests import config as test_config
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from urban_meal_delivery import config
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from tests.forecasts.conftest import NS
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from tests.forecasts.conftest import VERTICAL_FREQUENCY
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from urban_meal_delivery.forecasts import decomposition
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# See remarks in `datetime_index` fixture.
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FREQUENCY = 7 * 12
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# The default `ns` suggested for the STL method.
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NS = 7
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@pytest.fixture
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def datetime_index():
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"""A `pd.Index` with `DateTime` values.
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The times resemble a vertical time series with a
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`frequency` of `7` times the number of daily time steps,
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which is `12` for `LONG_TIME_STEP` values.
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"""
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gen = (
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start_at
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for start_at in pd.date_range(
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test_config.START, test_config.END, freq=f'{test_config.LONG_TIME_STEP}T',
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)
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if config.SERVICE_START <= start_at.hour < config.SERVICE_END
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)
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index = pd.Index(gen)
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index.name = 'start_at'
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return index
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@pytest.fixture
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def no_demand(datetime_index):
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"""A time series of order totals when there was no demand."""
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return pd.Series(0, index=datetime_index, name='order_totals')
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class TestInvalidArguments:
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"""Test `stl()` with invalid arguments."""
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def test_no_nans_in_time_series(self, datetime_index):
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def test_no_nans_in_time_series(self, vertical_datetime_index):
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"""`stl()` requires a `time_series` without `NaN` values."""
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time_series = pd.Series(dtype=float, index=datetime_index)
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time_series = pd.Series(dtype=float, index=vertical_datetime_index)
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with pytest.raises(ValueError, match='`NaN` values'):
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decomposition.stl(time_series, frequency=FREQUENCY, ns=99)
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decomposition.stl(time_series, frequency=VERTICAL_FREQUENCY, ns=99)
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def test_ns_not_odd(self, no_demand):
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def test_ns_not_odd(self, vertical_no_demand):
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"""`ns` must be odd and `>= 7`."""
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with pytest.raises(ValueError, match='`ns`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=8)
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decomposition.stl(vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=8)
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@pytest.mark.parametrize('ns', [-99, -1, 1, 5])
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def test_ns_smaller_than_seven(self, no_demand, ns):
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def test_ns_smaller_than_seven(self, vertical_no_demand, ns):
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"""`ns` must be odd and `>= 7`."""
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with pytest.raises(ValueError, match='`ns`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=ns)
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decomposition.stl(vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=ns)
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def test_nt_not_odd(self, no_demand):
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def test_nt_not_odd(self, vertical_no_demand):
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"""`nt` must be odd and `>= default_nt`."""
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nt = 200
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default_nt = math.ceil((1.5 * FREQUENCY) / (1 - (1.5 / NS)))
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default_nt = math.ceil((1.5 * VERTICAL_FREQUENCY) / (1 - (1.5 / NS)))
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assert nt > default_nt # sanity check
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with pytest.raises(ValueError, match='`nt`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, nt=nt)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, nt=nt,
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)
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@pytest.mark.parametrize('nt', [-99, -1, 0, 1, 99, 159])
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def test_nt_not_at_least_the_default(self, no_demand, nt):
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def test_nt_not_at_least_the_default(self, vertical_no_demand, nt):
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"""`nt` must be odd and `>= default_nt`."""
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# `default_nt` becomes 161.
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default_nt = math.ceil((1.5 * FREQUENCY) / (1 - (1.5 / NS)))
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default_nt = math.ceil((1.5 * VERTICAL_FREQUENCY) / (1 - (1.5 / NS)))
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assert nt < default_nt # sanity check
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with pytest.raises(ValueError, match='`nt`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, nt=nt)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, nt=nt,
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)
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def test_nl_not_odd(self, no_demand):
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def test_nl_not_odd(self, vertical_no_demand):
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"""`nl` must be odd and `>= frequency`."""
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nl = 200
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assert nl > FREQUENCY # sanity check
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assert nl > VERTICAL_FREQUENCY # sanity check
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with pytest.raises(ValueError, match='`nl`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, nl=nl)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, nl=nl,
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)
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def test_nl_at_least_the_frequency(self, no_demand):
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def test_nl_at_least_the_frequency(self, vertical_no_demand):
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"""`nl` must be odd and `>= frequency`."""
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nl = 77
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assert nl < FREQUENCY # sanity check
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assert nl < VERTICAL_FREQUENCY # sanity check
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with pytest.raises(ValueError, match='`nl`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, nl=nl)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, nl=nl,
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)
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def test_ds_not_zero_or_one(self, no_demand):
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def test_ds_not_zero_or_one(self, vertical_no_demand):
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"""`ds` must be `0` or `1`."""
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with pytest.raises(ValueError, match='`ds`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, ds=2)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, ds=2,
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)
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def test_dt_not_zero_or_one(self, no_demand):
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def test_dt_not_zero_or_one(self, vertical_no_demand):
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"""`dt` must be `0` or `1`."""
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with pytest.raises(ValueError, match='`dt`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, dt=2)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, dt=2,
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)
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def test_dl_not_zero_or_one(self, no_demand):
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def test_dl_not_zero_or_one(self, vertical_no_demand):
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"""`dl` must be `0` or `1`."""
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with pytest.raises(ValueError, match='`dl`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, dl=2)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, dl=2,
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)
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@pytest.mark.parametrize('js', [-1, 0])
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def test_js_not_positive(self, no_demand, js):
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def test_js_not_positive(self, vertical_no_demand, js):
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"""`js` must be positive."""
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with pytest.raises(ValueError, match='`js`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, js=js)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, js=js,
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)
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@pytest.mark.parametrize('jt', [-1, 0])
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def test_jt_not_positive(self, no_demand, jt):
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def test_jt_not_positive(self, vertical_no_demand, jt):
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"""`jt` must be positive."""
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with pytest.raises(ValueError, match='`jt`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, jt=jt)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, jt=jt,
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)
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@pytest.mark.parametrize('jl', [-1, 0])
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def test_jl_not_positive(self, no_demand, jl):
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def test_jl_not_positive(self, vertical_no_demand, jl):
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"""`jl` must be positive."""
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with pytest.raises(ValueError, match='`jl`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, jl=jl)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, jl=jl,
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)
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@pytest.mark.parametrize('ni', [-1, 0])
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def test_ni_not_positive(self, no_demand, ni):
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def test_ni_not_positive(self, vertical_no_demand, ni):
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"""`ni` must be positive."""
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with pytest.raises(ValueError, match='`ni`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, ni=ni)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, ni=ni,
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)
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def test_no_not_non_negative(self, no_demand):
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def test_no_not_non_negative(self, vertical_no_demand):
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"""`no` must be non-negative."""
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with pytest.raises(ValueError, match='`no`'):
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decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS, no=-1)
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decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS, no=-1,
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)
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@pytest.mark.r
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class TestValidArguments:
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"""Test `stl()` with valid arguments."""
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def test_structure_of_returned_dataframe(self, no_demand):
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def test_structure_of_returned_dataframe(self, vertical_no_demand):
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"""`stl()` returns a `pd.DataFrame` with three columns."""
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result = decomposition.stl(no_demand, frequency=FREQUENCY, ns=NS)
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result = decomposition.stl(
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vertical_no_demand, frequency=VERTICAL_FREQUENCY, ns=NS,
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)
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assert isinstance(result, pd.DataFrame)
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assert list(result.columns) == ['seasonal', 'trend', 'residual']
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@ -173,15 +165,15 @@ class TestValidArguments:
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@pytest.mark.parametrize('ni', [2, 3])
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@pytest.mark.parametrize('no', [0, 1])
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def test_decompose_time_series_with_no_demand( # noqa:WPS211,WPS216
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self, no_demand, nt, nl, ds, dt, dl, js, jt, jl, ni, no, # noqa:WPS110
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self, vertical_no_demand, nt, nl, ds, dt, dl, js, jt, jl, ni, no, # noqa:WPS110
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):
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"""Decomposing a time series with no demand ...
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... returns a `pd.DataFrame` with three columns holding only `0.0` values.
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"""
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decomposed = decomposition.stl(
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no_demand,
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frequency=FREQUENCY,
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vertical_no_demand,
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frequency=VERTICAL_FREQUENCY,
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ns=NS,
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nt=nt,
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nl=nl,
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