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author | Charles Harris <charlesr.harris@gmail.com> | 2018-05-15 11:13:46 -0600 |
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committer | GitHub <noreply@github.com> | 2018-05-15 11:13:46 -0600 |
commit | 79ec65de3064cbdc687820ab09f20b989028509d (patch) | |
tree | d1db3a47f86b4377738b433fc663a9ceef81597e /numpy/lib/tests/test_shape_base.py | |
parent | 9584c2f8ed78194ec18d20aea9616d4a89ee74fa (diff) | |
parent | 8e74c991d1336bd51e71dc492544223055c130f4 (diff) | |
download | numpy-79ec65de3064cbdc687820ab09f20b989028509d.tar.gz |
Merge pull request #11010 from mhvk/poly-matrix-tests-to-matrixlib
Move remaining Matrix tests to matrixlib
Diffstat (limited to 'numpy/lib/tests/test_shape_base.py')
-rw-r--r-- | numpy/lib/tests/test_shape_base.py | 22 |
1 files changed, 9 insertions, 13 deletions
diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index 0e86fbb19..a35d90b70 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -29,19 +29,21 @@ class TestApplyAlongAxis(object): [[27, 30, 33], [36, 39, 42], [45, 48, 51]]) def test_preserve_subclass(self): - # this test is particularly malicious because matrix - # refuses to become 1d def double(row): return row * 2 - m = np.matrix([[0, 1], [2, 3]]) - expected = np.matrix([[0, 2], [4, 6]]) + + class MyNDArray(np.ndarray): + pass + + m = np.array([[0, 1], [2, 3]]).view(MyNDArray) + expected = np.array([[0, 2], [4, 6]]).view(MyNDArray) result = apply_along_axis(double, 0, m) - assert_(isinstance(result, np.matrix)) + assert_(isinstance(result, MyNDArray)) assert_array_equal(result, expected) result = apply_along_axis(double, 1, m) - assert_(isinstance(result, np.matrix)) + assert_(isinstance(result, MyNDArray)) assert_array_equal(result, expected) def test_subclass(self): @@ -492,16 +494,10 @@ class TestSqueeze(object): class TestKron(object): def test_return_type(self): - a = np.ones([2, 2]) - m = np.asmatrix(a) - assert_equal(type(kron(a, a)), np.ndarray) - assert_equal(type(kron(m, m)), np.matrix) - assert_equal(type(kron(a, m)), np.matrix) - assert_equal(type(kron(m, a)), np.matrix) - class myarray(np.ndarray): __array_priority__ = 0.0 + a = np.ones([2, 2]) ma = myarray(a.shape, a.dtype, a.data) assert_equal(type(kron(a, a)), np.ndarray) assert_equal(type(kron(ma, ma)), myarray) |