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(-)science/py-scikit-sparse/Makefile (+1 lines)
Lines 3-8 Link Here
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PORTNAME=	scikit-sparse
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PORTNAME=	scikit-sparse
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PORTVERSION=	0.2
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PORTVERSION=	0.2
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PORTREVISION=	1
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CATEGORIES=	science python
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CATEGORIES=	science python
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MASTER_SITES=	CHEESESHOP
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MASTER_SITES=	CHEESESHOP
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PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
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PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
(-)science/py-scikit-sparse/files/patch-scikits_sparse_test__cholmod.py (+33 lines)
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--- scikits/sparse/test_cholmod.py.orig	2015-06-24 10:39:06 UTC
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+++ scikits/sparse/test_cholmod.py
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@@ -53,17 +53,17 @@ def test_integer_size():
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 def test_cholesky_smoke_test():
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     f = cholesky(sparse.eye(10, 10) * 1.)
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     d = np.arange(20).reshape(10, 2)
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-    print "dense"
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+    print("dense")
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     assert np.allclose(f(d), d)
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-    print "sparse"
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+    print("sparse")
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     s_csc = sparse.csc_matrix(np.eye(10)[:, :2] * 1.)
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     assert sparse.issparse(f(s_csc))
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     assert np.allclose(f(s_csc).todense(), s_csc.todense())
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-    print "csr"
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+    print("csr")
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     s_csr = s_csc.tocsr()
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     assert sparse.issparse(f(s_csr))
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     assert np.allclose(f(s_csr).todense(), s_csr.todense())
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-    print "extract"
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+    print("extract")
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     assert np.all(f.P() == np.arange(10))
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 def real_matrix():
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@@ -193,7 +193,7 @@ def test_cholesky_matrix_market():
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             f3.cholesky_AAt_inplace(X.T)
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             assert np.allclose(f3(Xty), answer)
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-            print problem, mode
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+            print(problem, mode)
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             for f in (f1, f2, f3, f4):
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                 pXtX = XtX.todense()[f.P()[:, np.newaxis],
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                                      f.P()[np.newaxis, :]]
(-)science/py-scikit-sparse/pkg-descr (-1 / +1 lines)
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scikits-sparse is a Python module for sparse matrix calculations.
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scikits-sparse is a Python module for sparse matrix calculations.
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WWW: https://scikits.appspot.com/sparse/
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WWW: https://github.com/njsmith/scikits-sparse

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