1 files changed, 0 insertions, 51 deletions
diff --git a/dev-python/patsy/files/patsy-0.5.6-np2.patch b/dev-python/patsy/files/patsy-0.5.6-np2.patch
deleted file mode 100644
index 169eadb851fe..000000000000
--- a/dev-python/patsy/files/patsy-0.5.6-np2.patch
+++ /dev/null
@@ -1,51 +0,0 @@
-diff --git a/patsy/highlevel.py b/patsy/highlevel.py
-index 78d2942..298739d 100644
---- a/patsy/highlevel.py
-+++ b/patsy/highlevel.py
-@@ -178,7 +178,7 @@ def _do_highlevel_design(formula_like, data, eval_env,
-         else:
-             # subok=True is necessary here to allow DesignMatrixes to pass
-             # through
--            (lhs, rhs) = (None, asarray_or_pandas(formula_like, subok=True))
-+            (lhs, rhs) = (None, asarray_or_pandas(formula_like, subok=True, copy=None))
-         # some sort of explicit matrix or matrices were given. Currently we
-         # have them in one of these forms:
-         #   -- an ndarray or subclass
-diff --git a/patsy/state.py b/patsy/state.py
-index 933c588..c489a4b 100644
---- a/patsy/state.py
-+++ b/patsy/state.py
-@@ -103,7 +103,7 @@ class Center(object):
-         pass
- 
-     def transform(self, x):
--        x = asarray_or_pandas(x)
-+        x = asarray_or_pandas(x, copy=None)
-         # This doesn't copy data unless our input is a DataFrame that has
-         # heterogeneous types. And in that case we're going to be munging the
-         # types anyway, so copying isn't a big deal.
-diff --git a/patsy/util.py b/patsy/util.py
-index 3116e11..7ac6f79 100644
---- a/patsy/util.py
-+++ b/patsy/util.py
-@@ -69,7 +69,7 @@ def asarray_or_pandas(a, copy=False, dtype=None, subok=False):
- 
- def test_asarray_or_pandas():
-     import warnings
--    assert type(asarray_or_pandas([1, 2, 3])) is np.ndarray
-+    assert type(asarray_or_pandas([1, 2, 3], copy=True)) is np.ndarray
-     with warnings.catch_warnings() as w:
-         warnings.filterwarnings('ignore', 'the matrix subclass',
-                                 PendingDeprecationWarning)
-@@ -83,9 +83,9 @@ def test_asarray_or_pandas():
-     assert np.array_equal(a, a_copy)
-     a_copy[0] = 100
-     assert not np.array_equal(a, a_copy)
--    assert np.allclose(asarray_or_pandas([1, 2, 3], dtype=float),
-+    assert np.allclose(asarray_or_pandas([1, 2, 3], dtype=float, copy=None),
-                        [1.0, 2.0, 3.0])
--    assert asarray_or_pandas([1, 2, 3], dtype=float).dtype == np.dtype(float)
-+    assert asarray_or_pandas([1, 2, 3], dtype=float, copy=None).dtype == np.dtype(float)
-     a_view = asarray_or_pandas(a, dtype=a.dtype)
-     a_view[0] = 99
-     assert a[0] == 99