Alexander Hess
b8952213d8
- the function implements a forecasting "method" similar to the
seasonal naive method
=> instead of simply taking the last observation given a seasonal lag,
it linearly extrapolates all observations of the same seasonal lag
from the past into the future; conceptually, it is like the
seasonal naive method with built-in smoothing
- the function is tested just like the `arima.predict()` and
`ets.predict()` functions
+ rename the `tests.forecasts.methods.test_ts_methods` module
into `tests.forecasts.methods.test_predictions`
- re-organize some constants in the `tests` package
- streamline some docstrings
69 lines
1.8 KiB
Python
69 lines
1.8 KiB
Python
"""Fixtures and globals for testing `urban_meal_delivery.forecasts`."""
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import datetime as dt
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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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@pytest.fixture
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def horizontal_datetime_index():
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"""A `pd.Index` with `DateTime` values.
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The times resemble a horizontal time series with a `frequency` of `7`.
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All observations take place at `NOON`.
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"""
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first_start_at = dt.datetime(
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test_config.YEAR, test_config.MONTH, test_config.DAY, test_config.NOON, 0,
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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(first_start_at, test_config.END, freq='D')
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)
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index = pd.Index(gen)
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index.name = 'start_at'
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assert len(index) == 15 # sanity check
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return index
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@pytest.fixture
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def horizontal_no_demand(horizontal_datetime_index):
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"""A horizontal time series with order totals: no demand."""
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return pd.Series(0, index=horizontal_datetime_index, name='n_orders')
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@pytest.fixture
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def vertical_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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assert len(index) == 15 * 12 # sanity check
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return index
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@pytest.fixture
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def vertical_no_demand(vertical_datetime_index):
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"""A vertical time series with order totals: no demand."""
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return pd.Series(0, index=vertical_datetime_index, name='n_orders')
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