safe_min instead of min

TomDLT · TomDLT · commit 37a64919698d · 2016-10-07T16:15:22.000+02:00
diff --git a/sklearn/decomposition/nmf.py b/sklearn/decomposition/nmf.py
@@ -20,7 +20,7 @@
 from ..base import BaseEstimator, TransformerMixin
 from ..utils import check_random_state, check_array
 from ..utils.extmath import randomized_svd, safe_sparse_dot, squared_norm
-from ..utils.extmath import fast_dot
+from ..utils.extmath import fast_dot, safe_min
 from ..utils.validation import check_is_fitted, check_non_negative
 from ..exceptions import ConvergenceWarning
 from .cdnmf_fast import _update_cdnmf_fast
@@ -954,7 +954,7 @@ def non_negative_factorization(X, W=None, H=None, n_components=None,
     check_non_negative(X, "NMF (input X)")
     beta_loss = _check_string_param(solver, regularization, beta_loss, init)
 
-    if X.min() == 0 and beta_loss <= 0:
+    if safe_min(X) == 0 and beta_loss <= 0:
         raise ValueError("When beta_loss <= 0 and X contains zeros, "
                          "the solver may diverge. Please add small values to "
                          "X, or use a positive beta_loss.")
