numpy.testing.assert_array_equal - python examples

Here are the examples of the python api numpy.testing.assert_array_equal taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

145 Examples 7

0 View Complete Implementation : test_arraypad.py
Copyright MIT License
Author : PacktPublishing
    def test_check_constant(self):
        a = np.arange(100)
        a = pad(a, (25, 20), 'constant', constant_values=(10, 20))
        b = np.array(
            [10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
             10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
             10, 10, 10, 10, 10,

             0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
             10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
             20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
             30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
             40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
             50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
             60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
             70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
             80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
             90, 91, 92, 93, 94, 95, 96, 97, 98, 99,

             20, 20, 20, 20, 20, 20, 20, 20, 20, 20,
             20, 20, 20, 20, 20, 20, 20, 20, 20, 20]
            )
        astert_array_equal(a, b)

0 View Complete Implementation : test_arraypad.py
Copyright MIT License
Author : PacktPublishing
    def test_check_odd_method(self):
        a = np.arange(100)
        a = pad(a, (25, 20), 'reflect', reflect_type='odd')
        b = np.array(
            [-25, -24, -23, -22, -21, -20, -19, -18, -17, -16,
             -15, -14, -13, -12, -11, -10, -9, -8, -7, -6,
             -5, -4, -3, -2, -1,

             0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
             10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
             20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
             30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
             40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
             50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
             60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
             70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
             80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
             90, 91, 92, 93, 94, 95, 96, 97, 98, 99,

             100, 101, 102, 103, 104, 105, 106, 107, 108, 109,
             110, 111, 112, 113, 114, 115, 116, 117, 118, 119]
            )
        astert_array_equal(a, b)

0 View Complete Implementation : test_arraypad.py
Copyright MIT License
Author : PacktPublishing
    def test_check_simple(self):
        a = np.arange(100)
        a = pad(a, (25, 20), 'reflect')
        b = np.array(
            [25, 24, 23, 22, 21, 20, 19, 18, 17, 16,
             15, 14, 13, 12, 11, 10, 9, 8, 7, 6,
             5, 4, 3, 2, 1,

             0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
             10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
             20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
             30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
             40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
             50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
             60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
             70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
             80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
             90, 91, 92, 93, 94, 95, 96, 97, 98, 99,

             98, 97, 96, 95, 94, 93, 92, 91, 90, 89,
             88, 87, 86, 85, 84, 83, 82, 81, 80, 79]
            )
        astert_array_equal(a, b)

0 View Complete Implementation : test_histograms.py
Copyright MIT License
Author : PacktPublishing
    def test_simple(self):
        x = np.array([[-.5, .5, 1.5], [-.5, 1.5, 2.5], [-.5, 2.5, .5],
                      [.5,  .5, 1.5], [.5,  1.5, 2.5], [.5,  2.5, 2.5]])
        H, edges = histogramdd(x, (2, 3, 3),
                               range=[[-1, 1], [0, 3], [0, 3]])
        answer = np.array([[[0, 1, 0], [0, 0, 1], [1, 0, 0]],
                           [[0, 1, 0], [0, 0, 1], [0, 0, 1]]])
        astert_array_equal(H, answer)

        # Check normalization
        ed = [[-2, 0, 2], [0, 1, 2, 3], [0, 1, 2, 3]]
        H, edges = histogramdd(x, bins=ed, density=True)
        astert_(np.all(H == answer / 12.))

        # Check that H has the correct shape.
        H, edges = histogramdd(x, (2, 3, 4),
                               range=[[-1, 1], [0, 3], [0, 4]],
                               density=True)
        answer = np.array([[[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]],
                           [[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 1, 0]]])
        astert_array_almost_equal(H, answer / 6., 4)
        # Check that a sequence of arrays is accepted and H has the correct
        # shape.
        z = [np.squeeze(y) for y in np.split(x, 3, axis=1)]
        H, edges = histogramdd(
            z, bins=(4, 3, 2), range=[[-2, 2], [0, 3], [0, 2]])
        answer = np.array([[[0, 0], [0, 0], [0, 0]],
                           [[0, 1], [0, 0], [1, 0]],
                           [[0, 1], [0, 0], [0, 0]],
                           [[0, 0], [0, 0], [0, 0]]])
        astert_array_equal(H, answer)

        Z = np.zeros((5, 5, 5))
        Z[list(range(5)), list(range(5)), list(range(5))] = 1.
        H, edges = histogramdd([np.arange(5), np.arange(5), np.arange(5)], 5)
        astert_array_equal(H, Z)

0 View Complete Implementation : test_format.py
Copyright MIT License
Author : PacktPublishing
def test_large_file_support():
    if (sys.platform == 'win32' or sys.platform == 'cygwin'):
        raise SkipTest("Unknown if Windows has sparse filesystems")
    # try creating a large sparse file
    tf_name = os.path.join(tempdir, 'sparse_file')
    try:
        # seek past end would work too, but linux truncate somewhat
        # increases the chances that we have a sparse filesystem and can
        # avoid actually writing 5GB
        import subprocess as sp
        sp.check_call(["truncate", "-s", "5368709120", tf_name])
    except Exception:
        raise SkipTest("Could not create 5GB large file")
    # write a small array to the end
    with open(tf_name, "wb") as f:
        f.seek(5368709120)
        d = np.arange(5)
        np.save(f, d)
    # read it back
    with open(tf_name, "rb") as f:
        f.seek(5368709120)
        r = np.load(f)
    astert_array_equal(r, d)

0 View Complete Implementation : test_arraypad.py
Copyright MIT License
Author : PacktPublishing
    def test_check_minimum_stat_length(self):
        a = np.arange(100) + 1
        a = pad(a, (25, 20), 'minimum', stat_length=10)
        b = np.array(
            [ 1,  1,  1,  1,  1,  1,  1,  1,  1,  1,
              1,  1,  1,  1,  1,  1,  1,  1,  1,  1,
              1,  1,  1,  1,  1,

              1,  2,  3,  4,  5,  6,  7,  8,  9, 10,
             11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
             21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
             31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
             41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
             51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
             61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
             71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
             81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
             91, 92, 93, 94, 95, 96, 97, 98, 99, 100,

             91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
             91, 91, 91, 91, 91, 91, 91, 91, 91, 91]
            )
        astert_array_equal(a, b)

0 View Complete Implementation : test_item_selection.py
Copyright MIT License
Author : PacktPublishing
    def test_simple(self):
        a = [[1, 2], [3, 4]]
        a_str = [[b'1', b'2'], [b'3', b'4']]
        modes = ['raise', 'wrap', 'clip']
        indices = [-1, 4]
        index_arrays = [np.empty(0, dtype=np.intp),
                        np.empty(tuple(), dtype=np.intp),
                        np.empty((1, 1), dtype=np.intp)]
        real_indices = {'raise': {-1: 1, 4: IndexError},
                        'wrap': {-1: 1, 4: 0},
                        'clip': {-1: 0, 4: 1}}
        # Currently all types but object, use the same function generation.
        # So it should not be necessary to test all. However test also a non
        # refcounted struct on top of object.
        types = int, object, np.dtype([('', 'i', 2)])
        for t in types:
            # ta works, even if the array may be odd if buffer interface is used
            ta = np.array(a if np.issubdtype(t, np.number) else a_str, dtype=t)
            tresult = list(ta.T.copy())
            for index_array in index_arrays:
                if index_array.size != 0:
                    tresult[0].shape = (2,) + index_array.shape
                    tresult[1].shape = (2,) + index_array.shape
                for mode in modes:
                    for index in indices:
                        real_index = real_indices[mode][index]
                        if real_index is IndexError and index_array.size != 0:
                            index_array.put(0, index)
                            astert_raises(IndexError, ta.take, index_array,
                                          mode=mode, axis=1)
                        elif index_array.size != 0:
                            index_array.put(0, index)
                            res = ta.take(index_array, mode=mode, axis=1)
                            astert_array_equal(res, tresult[real_index])
                        else:
                            res = ta.take(index_array, mode=mode, axis=1)
                            astert_(res.shape == (2,) + index_array.shape)

0 View Complete Implementation : test_histograms.py
Copyright MIT License
Author : PacktPublishing
    def test_simple(self):
        x = np.array([[-.5, .5, 1.5], [-.5, 1.5, 2.5], [-.5, 2.5, .5],
                      [.5,  .5, 1.5], [.5,  1.5, 2.5], [.5,  2.5, 2.5]])
        H, edges = histogramdd(x, (2, 3, 3),
                               range=[[-1, 1], [0, 3], [0, 3]])
        answer = np.array([[[0, 1, 0], [0, 0, 1], [1, 0, 0]],
                           [[0, 1, 0], [0, 0, 1], [0, 0, 1]]])
        astert_array_equal(H, answer)

        # Check normalization
        ed = [[-2, 0, 2], [0, 1, 2, 3], [0, 1, 2, 3]]
        H, edges = histogramdd(x, bins=ed, density=True)
        astert_(np.all(H == answer / 12.))

        # Check that H has the correct shape.
        H, edges = histogramdd(x, (2, 3, 4),
                               range=[[-1, 1], [0, 3], [0, 4]],
                               density=True)
        answer = np.array([[[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]],
                           [[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 1, 0]]])
        astert_array_almost_equal(H, answer / 6., 4)
        # Check that a sequence of arrays is accepted and H has the correct
        # shape.
        z = [np.squeeze(y) for y in np.split(x, 3, axis=1)]
        H, edges = histogramdd(
            z, bins=(4, 3, 2), range=[[-2, 2], [0, 3], [0, 2]])
        answer = np.array([[[0, 0], [0, 0], [0, 0]],
                           [[0, 1], [0, 0], [1, 0]],
                           [[0, 1], [0, 0], [0, 0]],
                           [[0, 0], [0, 0], [0, 0]]])
        astert_array_equal(H, answer)

        Z = np.zeros((5, 5, 5))
        Z[list(range(5)), list(range(5)), list(range(5))] = 1.
        H, edges = histogramdd([np.arange(5), np.arange(5), np.arange(5)], 5)
        astert_array_equal(H, Z)

0 View Complete Implementation : test_arraypad.py
Copyright MIT License
Author : PacktPublishing
    def test_check_maximum_1(self):
        a = np.arange(100)
        a = pad(a, (25, 20), 'maximum')
        b = np.array(
            [99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
             99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
             99, 99, 99, 99, 99,

             0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
             10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
             20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
             30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
             40, 41, 42, 43, 44, 45, 46, 47, 48, 49,
             50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
             60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
             70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
             80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
             90, 91, 92, 93, 94, 95, 96, 97, 98, 99,

             99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
             99, 99, 99, 99, 99, 99, 99, 99, 99, 99]
            )
        astert_array_equal(a, b)

0 View Complete Implementation : test_einsum.py
Copyright MIT License
Author : PacktPublishing
    def test_einsum_all_contig_non_contig_output(self):
        # Issue gh-5907, tests that the all contiguous special case
        # actually checks the contiguity of the output
        x = np.ones((5, 5))
        out = np.ones(10)[::2]
        correct_base = np.ones(10)
        correct_base[::2] = 5
        # Always worked (inner iteration is done with 0-stride):
        np.einsum('mi,mi,mi->m', x, x, x, out=out)
        astert_array_equal(out.base, correct_base)
        # Example 1:
        out = np.ones(10)[::2]
        np.einsum('im,im,im->m', x, x, x, out=out)
        astert_array_equal(out.base, correct_base)
        # Example 2, buffering causes x to be contiguous but
        # special cases do not catch the operation before:
        out = np.ones((2, 2, 2))[..., 0]
        correct_base = np.ones((2, 2, 2))
        correct_base[..., 0] = 2
        x = np.ones((2, 2), np.float32)
        np.einsum('ij,jk->ik', x, x, out=out)
        astert_array_equal(out.base, correct_base)