fix Prophet insufficient data error in detect_anomalies

[spolisar]

For #258
In some cases, detect_anomalies can pass a number of windows as an argument to cross_validation that results in a dataframe with a single row being passed to a model. Prophet requires at least 2 rows to function properly.

Decrementing the max possible windows for Prophet fixes that by guaranteeing that the minimum number of rows passed to the model is 2.

There is an implicit minimum of 3 rows in a dataframe used with Prophet for detect_anomalies to function properly. It may be good to make minimums like that explicit.

[AzulGarza]

thanks for the pr, Shane! it looks good so far and i agree about making the minimum explicit. would you mind adding a note on the docstrings about this behavior when using Prophet?

also, it'd be super helpful if you could add tests for this fix. something similar to

timecopilot/tests/models/utils/test_forecaster.py

Lines 324 to 334 in 9f83ec7

	def test_detect_anomalies_short_series_error():
	model = SeasonalNaive()
	df = pd.DataFrame(
	{
	"unique_id": ["A", "A"],
	"ds": pd.date_range("2023-01-01", periods=2, freq="D"),
	"y": [1.0, 2.0],
	}
	)
	with pytest.raises(ValueError, match="Cannot perform anomaly detection"):
	model.detect_anomalies(df, h=5, freq="D")

works.

[Copilot]

Pull request overview

This PR addresses issue #258 by fixing an error in detect_anomalies where Prophet models would fail when cross-validation resulted in single-row dataframes. The fix decrements the maximum number of windows for Prophet models to ensure at least 2 rows are passed to the model.

Key changes:

• Added Prophet-specific logic to reduce max_possible_windows by 1, ensuring minimum 2-row dataframes for cross-validation
• Updated error message to reflect different minimum series length requirements for Prophet vs other models
• Added test case to verify Prophet raises appropriate error for short series

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.

File	Description
timecopilot/models/utils/forecaster.py	Implements Prophet-specific logic to decrement max windows and updates error messaging for minimum series length requirements
tests/models/utils/test_forecaster.py	Adds test case verifying Prophet correctly raises ValueError for insufficient data

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[Copilot]

The comment "3 row minimum for a df with Prophet" is imprecise. The actual minimum depends on the forecast horizon h. For h=1, the minimum is 3 rows, but for h=2, it would be 5 rows (2h+1). Consider updating the comment to clarify this relationship, e.g., "Prophet requires min_series_length >= 2h + 1".

Suggested change

	# 3 row minimum for a df with Prophet
	# Prophet requires min_series_length >= 2h + 1, where h is the forecast horizon

[Copilot]

The documentation comment is unclear and potentially misleading. It states "Minimum series length is 1 higher for Prophet than other models" but doesn't specify what that minimum is. Consider being more explicit, e.g., "For Prophet models, the minimum series length is h + 2 instead of h + 1."

Suggested change

	Minimum series length is 1 higher for Prophet than other models.
	For Prophet models, the minimum series length is `h + 2`; for other models, it is `h + 1`.

[Copilot]

The comment states "min series length should be 1 higher for Prophet than other models" which is correct in concept, but the actual implementation in the next line has the conditional logic inverted (Prophet gets h + 1 when it should get h + 2).

Suggested change

	exp_min_series_length = h + 1 if isinstance(self, ProphetBase) else h + 2
	exp_min_series_length = h + 2 if isinstance(self, ProphetBase) else h + 1