testing/py-numpy: remove unused patches

2 files changed, 0 insertions, 200 deletions

diff --git a/testing/py-numpy/numpy-1.10.1-backport-1.patch b/testing/py-numpy/numpy-1.10.1-backport-1.patch
deleted file mode 100644
index 77a3c01037..0000000000
--- a/testing/py-numpy/numpy-1.10.1-backport-1.patch
+++ /dev/null
@@ -1,127 +0,0 @@
-From 3a816a4db9b498eb64eb837fdcca0fa8ddbe063e Mon Sep 17 00:00:00 2001
-From: Allan Haldane <allan.haldane@gmail.com>
-Date: Sat, 17 Oct 2015 14:00:36 -0400
-Subject: [PATCH] BUG: recarrays viewed as subarrays don't convert to np.record
- type
-
-Record array views were updated in #5943 to return np.record dtype
-where possible, but forgot about the case of sub-arrays.
-
-That's fixed here, so accessing subarray fields by attribute or index
-works sensibly, as well as viewing a record array as a subarray dtype,
-and printing subarrays.
-
-This also happens to fix #6459, since it affects the same lines.
-
-Fixes #6497 #6459
----
- numpy/core/records.py            | 30 +++++++++++++++++++-----------
- numpy/core/tests/test_records.py | 23 +++++++++++++++++++++++
- 2 files changed, 42 insertions(+), 11 deletions(-)
-
-diff --git a/numpy/core/records.py b/numpy/core/records.py
-index 4a99553..4ce3fe9 100644
---- a/numpy/core/records.py
-+++ b/numpy/core/records.py
-@@ -448,12 +448,14 @@ def __getattribute__(self, attr):
- 
-         # At this point obj will always be a recarray, since (see
-         # PyArray_GetField) the type of obj is inherited. Next, if obj.dtype is
--        # non-structured, convert it to an ndarray. If obj is structured leave
--        # it as a recarray, but make sure to convert to the same dtype.type (eg
--        # to preserve numpy.record type if present), since nested structured
--        # fields do not inherit type.
-+        # non-structured, convert it to an ndarray. Then if obj is structured
-+        # with void type convert it to the same dtype.type (eg to preserve
-+        # numpy.record type if present), since nested structured fields do not
-+        # inherit type. Don't do this for non-void structures though.
-         if obj.dtype.fields:
--            return obj.view(dtype=(self.dtype.type, obj.dtype.fields))
-+            if issubclass(obj.dtype.type, nt.void):
-+                return obj.view(dtype=(self.dtype.type, obj.dtype))
-+            return obj
-         else:
-             return obj.view(ndarray)
- 
-@@ -463,8 +465,9 @@ def __getattribute__(self, attr):
-     # Thus, you can't create attributes on-the-fly that are field names.
-     def __setattr__(self, attr, val):
- 
--        # Automatically convert (void) dtypes to records.
--        if attr == 'dtype' and issubclass(val.type, nt.void):
-+        # Automatically convert (void) structured types to records
-+        # (but not non-void structures, subarrays, or non-structured voids)
-+        if attr == 'dtype' and issubclass(val.type, nt.void) and val.fields:
-             val = sb.dtype((record, val))
- 
-         newattr = attr not in self.__dict__
-@@ -499,7 +502,9 @@ def __getitem__(self, indx):
-         # we might also be returning a single element
-         if isinstance(obj, ndarray):
-             if obj.dtype.fields:
--                return obj.view(dtype=(self.dtype.type, obj.dtype.fields))
-+                if issubclass(obj.dtype.type, nt.void):
-+                    return obj.view(dtype=(self.dtype.type, obj.dtype))
-+                return obj
-             else:
-                 return obj.view(type=ndarray)
-         else:
-@@ -519,11 +524,14 @@ def __repr__(self):
-             # If this is a full record array (has numpy.record dtype),
-             # or if it has a scalar (non-void) dtype with no records,
-             # represent it using the rec.array function. Since rec.array
--            # converts dtype to a numpy.record for us, use only dtype.descr,
--            # not repr(dtype).
-+            # converts dtype to a numpy.record for us, convert back
-+            # to non-record before printing
-+            plain_dtype = self.dtype
-+            if plain_dtype.type is record:
-+                plain_dtype = sb.dtype((nt.void, plain_dtype))
-             lf = '\n'+' '*len("rec.array(")
-             return ('rec.array(%s, %sdtype=%s)' %
--                          (lst, lf, repr(self.dtype.descr)))
-+                          (lst, lf, plain_dtype))
-         else:
-             # otherwise represent it using np.array plus a view
-             # This should only happen if the user is playing
-diff --git a/numpy/core/tests/test_records.py b/numpy/core/tests/test_records.py
-index 7a18f29..290bc4f 100644
---- a/numpy/core/tests/test_records.py
-+++ b/numpy/core/tests/test_records.py
-@@ -121,6 +121,23 @@ def test_recarray_views(self):
-         assert_equal(type(rv), np.recarray)
-         assert_equal(rv.dtype.type, np.record)
- 
-+        # check that accessing nested structures keep record type, but
-+        # not for subarrays, non-void structures, non-structured voids
-+        test_dtype = [('a', 'f4,f4'), ('b', 'V8'), ('c', ('f4',2)),
-+                      ('d', ('i8', 'i4,i4'))]
-+        r = np.rec.array([((1,1), b'11111111', [1,1], 1),
-+                          ((1,1), b'11111111', [1,1], 1)], dtype=test_dtype)
-+        assert_equal(r.a.dtype.type, np.record)
-+        assert_equal(r.b.dtype.type, np.void)
-+        assert_equal(r.c.dtype.type, np.float32)
-+        assert_equal(r.d.dtype.type, np.int64)
-+        # check the same, but for views
-+        r = np.rec.array(np.ones(4, dtype='i4,i4'))
-+        assert_equal(r.view('f4,f4').dtype.type, np.record)
-+        assert_equal(r.view(('i4',2)).dtype.type, np.int32)
-+        assert_equal(r.view('V8').dtype.type, np.void)
-+        assert_equal(r.view(('i8', 'i4,i4')).dtype.type, np.int64)
-+
-         #check that we can undo the view
-         arrs = [np.ones(4, dtype='f4,i4'), np.ones(4, dtype='f8')]
-         for arr in arrs:
-@@ -135,6 +152,12 @@ def test_recarray_repr(self):
-         a = np.array(np.ones(4, dtype='f8'))
-         assert_(repr(np.rec.array(a)).startswith('rec.array'))
- 
-+        # check that the 'np.record' part of the dtype isn't shown
-+        a = np.rec.array(np.ones(3, dtype='i4,i4'))
-+        assert_equal(repr(a).find('numpy.record'), -1)
-+        a = np.rec.array(np.ones(3, dtype='i4'))
-+        assert_(repr(a).find('dtype=int32') != -1)
-+
-     def test_recarray_from_names(self):
-         ra = np.rec.array([
-             (1, 'abc', 3.7000002861022949, 0),
diff --git a/testing/py-numpy/numpy-1.10.1-backport-2.patch b/testing/py-numpy/numpy-1.10.1-backport-2.patch
deleted file mode 100644
index 9c33704f8e..0000000000
--- a/testing/py-numpy/numpy-1.10.1-backport-2.patch
+++ /dev/null
@@ -1,73 +0,0 @@
-From 0d25dc4175e00cdaf9545e8b1b1a5b879cf67248 Mon Sep 17 00:00:00 2001
-From: Ethan Kruse <eakruse@uw.edu>
-Date: Mon, 19 Oct 2015 13:29:01 -0700
-Subject: [PATCH 1/2] Potential fix for #6462
-
----
- numpy/lib/function_base.py | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
-index 555d083..fef69df 100644
---- a/numpy/lib/function_base.py
-+++ b/numpy/lib/function_base.py
-@@ -3339,7 +3339,7 @@ def _median(a, axis=None, out=None, overwrite_input=False):
-         indexer[axis] = slice(index-1, index+1)
- 
-     # Check if the array contains any nan's
--    if np.issubdtype(a.dtype, np.inexact):
-+    if np.issubdtype(a.dtype, np.inexact) and sz > 0:
-         # warn and return nans like mean would
-         rout = mean(part[indexer], axis=axis, out=out)
-         part = np.rollaxis(part, axis, part.ndim)
-
-From 59d859fb2160950ac93267d7461ad952145c8724 Mon Sep 17 00:00:00 2001
-From: Ethan Kruse <eakruse@uw.edu>
-Date: Tue, 20 Oct 2015 11:40:49 -0700
-Subject: [PATCH 2/2] Added tests for median of empty arrays
-
----
- numpy/lib/tests/test_function_base.py | 30 ++++++++++++++++++++++++++++++
- 1 file changed, 30 insertions(+)
-
-diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
-index 4516c92..aa41c1f 100644
---- a/numpy/lib/tests/test_function_base.py
-+++ b/numpy/lib/tests/test_function_base.py
-@@ -2597,6 +2597,36 @@ def test_nan_behavior(self):
-             assert_equal(np.median(a, (0, 2)), b)
-             assert_equal(len(w), 1)
- 
-+    def test_empty(self):
-+        # empty arrays
-+        a = np.array([], dtype=float)
-+        with warnings.catch_warnings(record=True) as w:
-+            warnings.filterwarnings('always', '', RuntimeWarning)
-+            assert_equal(np.median(a), np.nan)
-+            assert_(w[0].category is RuntimeWarning)
-+
-+        # multiple dimensions
-+        a = np.array([], dtype=float, ndmin=3)
-+        # no axis
-+        with warnings.catch_warnings(record=True) as w:
-+            warnings.filterwarnings('always', '', RuntimeWarning)
-+            assert_equal(np.median(a), np.nan)
-+            assert_(w[0].category is RuntimeWarning)
-+
-+        # axis 0 and 1
-+        b = np.array([], dtype=float, ndmin=2)
-+        with warnings.catch_warnings(record=True) as w:
-+            warnings.filterwarnings('always', '', RuntimeWarning)
-+            assert_equal(np.median(a, axis=0), b)
-+            assert_equal(np.median(a, axis=1), b)
-+
-+        # axis 2
-+        b = np.array(np.nan, dtype=float, ndmin=2)
-+        with warnings.catch_warnings(record=True) as w:
-+            warnings.filterwarnings('always', '', RuntimeWarning)
-+            assert_equal(np.median(a, axis=2), b)
-+            assert_(w[0].category is RuntimeWarning)
-+
-     def test_object(self):
-         o = np.arange(7.)
-         assert_(type(np.median(o.astype(object))), float)