mirror of
https://github.com/Akkudoktor-EOS/EOS.git
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Bobby NoelteandGitHub
e8dcfecf73
Add a configurable filename linter to enforce naming conventions and an AGENTS.md to guide AI coding agents in following project conventions. The guidelines steer code generation; the linter independently verifies filename compliance. Together, they improve consistency and reduce unnecessary files and review effort. Conflicting file names were renamed. Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
"""Raw forecast coverage must survive resampling without inventing valid intervals."""
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from unittest.mock import AsyncMock, Mock
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import numpy as np
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import pandas as pd
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import pytest
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from akkudoktoreos.optimization.genetic.forecast import bounded_forecast_array
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from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
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@pytest.mark.asyncio
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@pytest.mark.parametrize("drop,missing", [(1, 4), (2, 8)])
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async def test_hourly_gaps_and_unavailable_tail_are_not_forward_filled(drop, missing):
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index = pd.date_range("2026-09-16T00:00:00Z", periods=4, freq="h").delete(drop)
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prediction = Mock(key_to_raw_series=AsyncMock(return_value=pd.Series([100.0] * 3, index=index)))
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start = to_datetime("2026-09-16T00:00:00Z", in_timezone="UTC")
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values = await bounded_forecast_array(
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prediction,
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key="pv",
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start_datetime=start,
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end_datetime=start.add(hours=5),
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interval=to_duration(900),
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)
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assert np.isnan(values[missing : missing + 4]).all()
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assert np.isnan(values[16:]).all()
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assert np.isfinite(values[:4]).all()
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@pytest.mark.asyncio
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async def test_downsampling_requires_complete_coverage_and_uses_interval_average():
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index = pd.date_range("2026-09-16T00:00:00Z", periods=8, freq="15min")
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series = pd.Series([100.0, 200.0, 300.0, 400.0, 100.0, np.nan, 100.0, 100.0], index=index)
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prediction = Mock(key_to_raw_series=AsyncMock(return_value=series))
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start = to_datetime("2026-09-16T00:00:00Z", in_timezone="UTC")
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values = await bounded_forecast_array(
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prediction,
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key="pv",
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start_datetime=start,
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end_datetime=start.add(hours=2),
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interval=to_duration(3600),
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)
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assert values[0] == 250.0
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assert np.isnan(values[1])
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@pytest.mark.asyncio
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async def test_non_aligned_source_intervals_are_weighted_by_actual_overlap():
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index = pd.date_range("2026-09-16T00:05:00Z", periods=4, freq="15min")
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prediction = Mock(
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key_to_raw_series=AsyncMock(
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return_value=pd.Series([100.0, 400.0, 700.0, 1000.0], index=index)
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)
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)
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start = to_datetime("2026-09-16T00:00:00Z", in_timezone="UTC")
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values = await bounded_forecast_array(
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prediction,
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key="pv",
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start_datetime=start,
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end_datetime=start.add(hours=1),
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interval=to_duration(900),
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)
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assert np.isnan(values[0])
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assert values[1] == pytest.approx(300.0)
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assert values[2] == pytest.approx(600.0)
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