Only select lags within FE window dictated by FH and gap#3773
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| def _find_significant_lags(y, conf_level, max_delay): | ||
| all_lags = np.arange(max_delay + 1) | ||
| def _find_significant_lags(y, conf_level, start_delay, max_delay): | ||
| all_lags = np.arange(start_delay, start_delay + max_delay + 1) |
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only filter by lags that start in the feature engineering window.
| # If no lags are significant get the first lag | ||
| significant_lags = sorted(significant_lags.intersection(all_lags)) or [1] | ||
| significant_lags = sorted(significant_lags.intersection(all_lags)) or [ | ||
| start_delay, |
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default to using the start of the feature engineering window.
| lagged_features[ | ||
| f"{col_name}_delay_{self.start_delay + t}" | ||
| ] = col.shift(self.start_delay + t) | ||
| ] = col.shift(t) |
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lags already have the start delay baked in since we're only selecting lags that start from the feature engineering window.
| lagged_features[ | ||
| self.target_colname_prefix.format(t + self.start_delay) | ||
| ] = y.shift(self.start_delay + t) | ||
| ] = y.shift(t) |
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same here.
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If the start_delay is 11 and the significant lag is 11, then this comes out to a format of 21 (because 11 + 11 - 1). So we'd be shifting by 11 and the feature would be called target_delay_21? Shouldn't the shift and the column name suffix come out to the same number?
Codecov Report
@@ Coverage Diff @@
## main #3773 +/- ##
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Coverage 99.7% 99.7%
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Files 344 344
Lines 36123 36123
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Hits 35986 35986
Misses 137 137
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| lagged_features[ | ||
| f"{col_name}_delay_{self.start_delay + t}" | ||
| ] = col.shift(self.start_delay + t) | ||
| f"{col_name}_delay_{self.start_delay + t - 1}" |
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-1 since the lag is inclusive of the start delay.
| # Check that the computed features to be explained aren't NaN. | ||
| for exp_idx in range(len(exp["explanations"])): | ||
| assert not np.isnan( | ||
| assert not pd.isnull( |
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@ParthivNaresh do you know why we need to do this conversion?
jeremyliweishih
requested review from
ParthivNaresh,
christopherbunn and
eccabay
| return_value=pd.DataFrame(), | ||
| ) | ||
| def test_delayed_feature_extractor_maxdelay3_forecasthorizon7_gap1( | ||
| def test_delayed_feature_extractor_maxdelay2_forecasthorizon7_gap1( |
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What was the reasoning behind changing this test?
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IIRC just to match the lags on the dataset
4 participants
Fixes #3770