1 files changed, 100 insertions, 0 deletions
diff --git a/dev-python/astroscrappy/files/astroscrappy-1.0.3-endian-fix-tests.patch b/dev-python/astroscrappy/files/astroscrappy-1.0.3-endian-fix-tests.patch
new file mode 100644
index 000000000000..7a2bbb6299c6
--- /dev/null
+++ b/dev-python/astroscrappy/files/astroscrappy-1.0.3-endian-fix-tests.patch
@@ -0,0 +1,100 @@
+From 5b5ce99c63d03e60b6027f09f72231db11a87bf2 Mon Sep 17 00:00:00 2001
+From: Curtis McCully <cmccully@lcogt.net>
+Date: Thu, 3 Dec 2015 12:02:38 -0800
+Subject: [PATCH] Made tests not endian specific.
+--- a/astroscrappy/tests/test_utils.py
++++ b/astroscrappy/tests/test_utils.py
+@@ -56,7 +56,7 @@
+ 
+ 
+ def test_medfilt5():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed5 = ndimage.filters.median_filter(a, size=(5, 5), mode='nearest')
+     npmed5[:2, :] = a[:2, :]
+     npmed5[-2:, :] = a[-2:, :]
+@@ -68,7 +68,7 @@
+ 
+ 
+ def test_medfilt7():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed7 = ndimage.filters.median_filter(a, size=(7, 7), mode='nearest')
+     npmed7[:3, :] = a[:3, :]
+     npmed7[-3:, :] = a[-3:, :]
+@@ -80,7 +80,7 @@
+ 
+ 
+ def test_sepmedfilt3():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed3 = ndimage.filters.median_filter(a, size=(1, 3), mode='nearest')
+     npmed3[:, :1] = a[:, :1]
+     npmed3[:, -1:] = a[:, -1:]
+@@ -95,7 +95,7 @@
+ 
+ 
+ def test_sepmedfilt5():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed5 = ndimage.filters.median_filter(a, size=(1, 5), mode='nearest')
+     npmed5[:, :2] = a[:, :2]
+     npmed5[:, -2:] = a[:, -2:]
+@@ -110,7 +110,7 @@
+ 
+ 
+ def test_sepmedfilt7():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed7 = ndimage.filters.median_filter(a, size=(1, 7), mode='nearest')
+     npmed7[:, :3] = a[:, :3]
+     npmed7[:, -3:] = a[:, -3:]
+@@ -125,7 +125,7 @@
+ 
+ 
+ def test_sepmedfilt9():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npmed9 = ndimage.filters.median_filter(a, size=(1, 9), mode='nearest')
+     npmed9[:, :4] = a[:, :4]
+     npmed9[:, -4:] = a[:, -4:]
+@@ -174,7 +174,7 @@
+ 
+ 
+ def test_subsample():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     npsubsamp = np.zeros((a.shape[0] * 2, a.shape[1] * 2), dtype=np.float32)
+     for i in range(a.shape[0]):
+         for j in range(a.shape[1]):
+@@ -189,8 +189,8 @@
+ 
+ def test_rebin():
+     a = np.ascontiguousarray(np.random.random((2002, 2002)), dtype=np.float32)
+-    a = a.astype('<f4')
+-    nprebin = np.zeros((1001, 1001), dtype=np.float32).astype('<f4')
++    a = a.astype('f4')
++    nprebin = np.zeros((1001, 1001), dtype=np.float32).astype('f4')
+     for i in range(1001):
+         for j in range(1001):
+             nprebin[i, j] = (a[2 * i, 2 * j] + a[2 * i + 1, 2 * j] +
+@@ -202,7 +202,7 @@
+ 
+ 
+ def test_laplaceconvolve():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
+     k = np.array([[0.0, -1.0, 0.0], [-1.0, 4.0, -1.0], [0.0, -1.0, 0.0]])
+     k = k.astype('<f4')
+     npconv = ndimage.filters.convolve(a, k, mode='constant', cval=0.0)
+@@ -211,8 +211,8 @@
+ 
+ 
+ def test_convolve():
+-    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('<f4')
+-    k = np.ascontiguousarray(np.random.random((5, 5))).astype('<f4')
++    a = np.ascontiguousarray(np.random.random((1001, 1001))).astype('f4')
++    k = np.ascontiguousarray(np.random.random((5, 5))).astype('f4')
+     npconv = ndimage.filters.convolve(a, k, mode='constant', cval=0.0)
+     cconv = convolve(a, k)
+     assert_allclose(cconv, npconv, rtol=0, atol=1e-5)