remove order checks for sparse matrices

Immanuel Bayer · Immanuel Bayer · commit 0949a2e35331 · 2015-04-16T14:13:26.000+02:00
diff --git a/sklearn/utils/tests/test_validation.py b/sklearn/utils/tests/test_validation.py
@@ -106,10 +106,6 @@ def test_ordering():
     X.data = X.data[::-1]
     assert_false(X.data.flags['C_CONTIGUOUS'])
 
-    for copy in (True, False):
-        Y = check_array(X, accept_sparse='csr', copy=copy, order='C')
-        assert_true(Y.data.flags['C_CONTIGUOUS'])
-
 
 def test_check_array():
     # accept_sparse == None
diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
@@ -200,7 +200,7 @@ def indexable(*iterables):
     return result
 
 
-def _ensure_sparse_format(spmatrix, accept_sparse, dtype, order, copy,
+def _ensure_sparse_format(spmatrix, accept_sparse, dtype, copy,
                           force_all_finite):
     """Convert a sparse matrix to a given format.
 
@@ -220,9 +220,6 @@ def _ensure_sparse_format(spmatrix, accept_sparse, dtype, order, copy,
     dtype : string, type or None (default=none)
         Data type of result. If None, the dtype of the input is preserved.
 
-    order : 'F', 'C' or None (default=None)
-        Whether an array will be forced to be fortran or c-style.
-
     copy : boolean (default=False)
         Whether a forced copy will be triggered. If copy=False, a copy might
         be triggered by a conversion.
@@ -260,8 +257,6 @@ def _ensure_sparse_format(spmatrix, accept_sparse, dtype, order, copy,
                           % spmatrix.format)
         else:
             _assert_all_finite(spmatrix.data)
-    if hasattr(spmatrix, "data"):
-        spmatrix.data = np.array(spmatrix.data, copy=False, order=order)
     return spmatrix
 
 
@@ -330,8 +325,8 @@ def check_array(array, accept_sparse=None, dtype="numeric", order=None,
     if sp.issparse(array):
         if dtype_numeric:
             dtype = None
-        array = _ensure_sparse_format(array, accept_sparse, dtype, order,
-                                      copy, force_all_finite)
+        array = _ensure_sparse_format(array, accept_sparse, dtype, copy,
+                                      force_all_finite)
     else:
         if ensure_2d:
             array = np.atleast_2d(array)
