FIX: always raise ValueError on deficient input in BaseLibSVM.

Author: Fabian Pedregosa

scikits/learn/svm/base.py

@@ -38,14 +38,13 @@ class BaseLibSVM(BaseEstimator):
     def __init__(self, impl, kernel, degree, gamma, coef0, cache_size,
                  eps, C, nu, p, shrinking, probability):
 
-        assert impl in self._svm_types, \
-            "impl should be one of %s, %s was given" % (
-                self._svm_types, impl)
-
-        assert kernel in self._kernel_types or \
-               hasattr(kernel, '__call__'), \
-               "kernel should be one of %s or a callable, " \
-               "%s was given." % ( self._kernel_types, kernel)
+        if not impl in self._svm_types:
+            raise ValueError("impl should be one of %s, %s was given" % (
+                self._svm_types, impl))
+
+        if not kernel in self._kernel_types or hasattr(kernel, '__call__'):
+            raise ValueError("kernel should be one of %s or a callable, " \
+                             "%s was given." % ( self._kernel_types, kernel))
 
         self.kernel = kernel
         self.impl = impl

scikits/learn/svm/tests/test_svm.py

@@ -328,7 +328,7 @@ def test_error():
 
     Y2 = Y[:-1]  # wrong dimensions for labels
     assert_raises(ValueError, clf.fit, X, Y2)
-    assert_raises(AssertionError, svm.SVC, X, Y2)
+    assert_raises(ValueError, svm.SVC, X, Y2)
 
     # Test with arrays that are non-contiguous.
     Xf = np.asfortranarray(X)
@@ -361,6 +361,7 @@ def test_LinearSVC():
     clf = svm.LinearSVC(penalty='l2', loss='l1', dual=True).fit(X, Y)
     assert_array_equal(clf.predict(T), true_result)
 
+    # test also decision function
     dec = clf.decision_function(X)
     assert_array_equal(np.argmax(dec, 1), true_result)