Python numpy.nancumprod() Examples

The following are 30 code examples of numpy.nancumprod(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function .
Example #1
Source File: test_reduction_execute.py    From mars with Apache License 2.0 6 votes vote down vote up 
def testNanCumReduction(self):
        raw = np.random.randint(5, size=(8, 8, 8))
        raw[:2, 2:4, 4:6] = np.nan

        arr = tensor(raw, chunk_size=3)

        res1 = self.executor.execute_tensor(nancumsum(arr, axis=1), concat=True)
        res2 = self.executor.execute_tensor(nancumprod(arr, axis=1), concat=True)
        expected1 = np.nancumsum(raw, axis=1)
        expected2 = np.nancumprod(raw, axis=1)
        np.testing.assert_array_equal(res1[0], expected1)
        np.testing.assert_array_equal(res2[0], expected2)

        raw = sps.random(8, 8, density=.1, format='lil')
        raw[:2, 2:4] = np.nan

        arr = tensor(raw, chunk_size=3)

        res1 = self.executor.execute_tensor(nancumsum(arr, axis=1), concat=True)[0]
        res2 = self.executor.execute_tensor(nancumprod(arr, axis=1), concat=True)[0]
        expected1 = np.nancumsum(raw.A, axis=1)
        expected2 = np.nancumprod(raw.A, axis=1)
        self.assertTrue(np.allclose(res1, expected1))
        self.assertTrue(np.allclose(res2, expected2))
Example #2
Source File: test_nanfunctions.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #3
Source File: test_nanfunctions.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #4
Source File: test_nanfunctions.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #5
Source File: test_interaction.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #6
Source File: test_nanfunctions.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #7
Source File: test_nanfunctions.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #8
Source File: test_nanfunctions.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #9
Source File: test_nanfunctions.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #10
Source File: test_nanfunctions.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #11
Source File: test_nanfunctions.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #12
Source File: test_interaction.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #13
Source File: test_interaction.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #14
Source File: test_nanfunctions.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #15
Source File: test_quantity_non_ufuncs.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def test_nancumprod(self):
        with pytest.raises(u.UnitsError):
            np.nancumprod(self.q)
Example #16
Source File: test_interaction.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #17
Source File: test_nanfunctions.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #18
Source File: test_nanfunctions.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #19
Source File: test_interaction.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #20
Source File: test_nanfunctions.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #21
Source File: test_nanfunctions.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #22
Source File: test_nanfunctions.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #23
Source File: test_nanfunctions.py    From lambda-packs with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #24
Source File: test_nanfunctions.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #25
Source File: test_nanfunctions.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #26
Source File: test_interaction.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))
Example #27
Source File: test_nanfunctions.py    From lambda-packs with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #28
Source File: test_nanfunctions.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_nancumprod(self):
        tgt = np.cumprod(self.mat)
        for mat in self.integer_arrays():
            assert_equal(np.nancumprod(mat), tgt)
Example #29
Source File: test_nanfunctions.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_result_values(self):
        for axis in (-2, -1, 0, 1, None):
            tgt = np.cumprod(_ndat_ones, axis=axis)
            res = np.nancumprod(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
            tgt = np.cumsum(_ndat_zeros,axis=axis)
            res = np.nancumsum(_ndat, axis=axis)
            assert_almost_equal(res, tgt)
Example #30
Source File: test_interaction.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def test_nanfunctions_matrices_general():
    # Check that it works and that type and
    # shape are preserved
    # 2018-04-29: moved here from core.tests.test_nanfunctions
    mat = np.matrix(np.eye(3))
    for f in (np.nanargmin, np.nanargmax, np.nansum, np.nanprod,
              np.nanmean, np.nanvar, np.nanstd):
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 1))
        res = f(mat)
        assert_(np.isscalar(res))

    for f in np.nancumsum, np.nancumprod:
        res = f(mat, axis=0)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat, axis=1)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (3, 3))
        res = f(mat)
        assert_(isinstance(res, np.matrix))
        assert_(res.shape == (1, 3*3))