FIX: lars_path -- assure that at least some features get added if necessary

yarikoptic · yarikoptic · commit 8eaf6983e4f9 · 2011-05-13T12:09:24.000-04:00
Otherwise can run into situation when max_features == n_active, so add_features
becomes == 0, thus no actual resize happens, and then next assignment to coefs
fails.
diff --git a/scikits/learn/linear_model/least_angle.py b/scikits/learn/linear_model/least_angle.py
@@ -222,7 +222,7 @@ def lars_path(X, y, Xy=None, Gram=None, max_features=None,
 
         if n_iter >= coefs.shape[0]:
             # resize the coefs and alphas array
-            add_features = 2 * (max_features - n_active)
+            add_features = 2 * max(1, (max_features - n_active))
             coefs.resize((n_iter + add_features, n_features))
             alphas.resize(n_iter + add_features)
 
