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MNT output proper constant when some outputs only have intercepts #73

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Merged
merged 1 commit into from
Apr 10, 2025
Merged

MNT output proper constant when some outputs only have intercepts #73

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8 changes: 5 additions & 3 deletions fastcan/narx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -760,7 +760,8 @@ def fit(self, X, y, sample_weight=None, coef_init=None, **params):
warnings.warn(
f"output_ids got {self.output_ids_}, which does not "
f"contain all values from 0 to {self.n_outputs_ - 1}."
"The predicted outputs for the missing values will be 0.",
"The prediction for the missing outputs will be a constant"
"(i.e., intercept).",
UserWarning,
)

Expand All @@ -783,6 +784,7 @@ def fit(self, X, y, sample_weight=None, coef_init=None, **params):
for i in range(self.n_outputs_):
output_i_mask = self.output_ids_ == i
if np.sum(output_i_mask) == 0:
intercept[i] = np.mean(y_masked[:, i])
continue
osa_narx.fit(
poly_terms_masked[:, output_i_mask],
Expand Down Expand Up @@ -974,8 +976,8 @@ def _update_dydx(
dydx[k, y_ids, x_ids] = terms

# Update dynamic terms of Jacobian
cfd = np.zeros((n_y, n_y, max_delay), dtype=float)
if max_delay > 0:
if max_delay > 0 and grad_yyd_ids.size > 0:
cfd = np.zeros((n_y, n_y, max_delay), dtype=float)
_update_cfd(
X,
y_hat,
Expand Down
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