numpy.ma.MaskedArray - python examples

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

50 Examples 7

3 View Complete Implementation : test_mrecords.py
Copyright MIT License
Author : abhisuri97
    def test_view_simple_dtype(self):
        (mrec, a, b, arr) = self.data
        ntype = (np.float, 2)
        test = mrec.view(ntype)
        self.astertTrue(isinstance(test, ma.MaskedArray))
        astert_equal(test, np.array(list(zip(a, b)), dtype=np.float))
        self.astertTrue(test[3, 1] is ma.masked)

3 View Complete Implementation : test_recfunctions.py
Copyright MIT License
Author : alvarob96
    def test_join_subdtype(self):
        # tests the bug in https://stackoverflow.com/q/44769632/102441
        from numpy.lib import recfunctions as rfn
        foo = np.array([(1,)],
                       dtype=[('key', int)])
        bar = np.array([(1, np.array([1,2,3]))],
                       dtype=[('key', int), ('value', 'uint16', 3)])
        res = join_by('key', foo, bar)
        astert_equal(res, bar.view(ma.MaskedArray))

3 View Complete Implementation : test_mrecords.py
Copyright MIT License
Author : alvarob96
    def test_view_simple_dtype(self):
        (mrec, a, b, arr) = self.data
        ntype = (float, 2)
        test = mrec.view(ntype)
        astert_(isinstance(test, ma.MaskedArray))
        astert_equal(test, np.array(list(zip(a, b)), dtype=float))
        astert_(test[3, 1] is ma.masked)

3 View Complete Implementation : test_regression.py
Copyright MIT License
Author : alvarob96
    def test_mask_not_backmangled(self):
        # See gh-10314.  Test case taken from gh-3140.
        a = np.ma.MaskedArray([1., 2.], mask=[False, False])
        astert_(a.mask.shape == (2,))
        b = np.tile(a, (2, 1))
        # Check that the above no longer changes a.shape to (1, 2)
        astert_(a.mask.shape == (2,))
        astert_(b.shape == (2, 2))
        astert_(b.mask.shape == (2, 2))

3 View Complete Implementation : test_utils.py
Copyright MIT License
Author : alvarob96
    def test_masked_nan_inf(self):
        # Regression test for gh-11121
        a = np.ma.MaskedArray([3., 4., 6.5], mask=[False, True, False])
        b = np.array([3., np.nan, 6.5])
        self._test_equal(a, b)
        self._test_equal(b, a)
        a = np.ma.MaskedArray([3., 4., 6.5], mask=[True, False, False])
        b = np.array([np.inf, 4., 6.5])
        self._test_equal(a, b)
        self._test_equal(b, a)

3 View Complete Implementation : test_pilutil.py
Copyright MIT License
Author : alvarob96
    def test_bytescale_mask(self):
        a = np.ma.MaskedArray(data=[1, 2, 3], mask=[False, False, True])
        with suppress_warnings() as sup:
            sup.filter(DeprecationWarning)
            actual = misc.bytescale(a)
        expected = [0, 255, 3]
        astert_equal(expected, actual)
        astert_mask_equal(a.mask, actual.mask)
        astert_(isinstance(actual, np.ma.MaskedArray))

3 View Complete Implementation : fixes.py
Copyright MIT License
Author : alvarob96
        def __getstate__(self):
            """Return the internal state of the masked array, for pickling
            purposes.

            """
            cf = 'CF'[self.flags.fnc]
            data_state = super(np.ma.MaskedArray, self).__reduce__()[2]
            return data_state + (np.ma.getmaskarray(self).tostring(cf),
                                 self._fill_value)

3 View Complete Implementation : stats.py
Copyright MIT License
Author : Ardavans
def cov(a):
    # return np.cov(a,rowvar=0,bias=1)
    mu = a.mean(0)
    if isinstance(a,np.ma.MaskedArray):
        return np.ma.dot(a.T,a)/a.count(0)[0] - np.ma.outer(mu,mu)
    else:
        return a.T.dot(a)/a.shape[0] - np.outer(mu,mu)

3 View Complete Implementation : vop.py
Copyright GNU General Public License v3.0
Author : asarnow
def normalize(vol, ref=None, return_stats=False):
    volm = vol.view(ma.MaskedArray)
    sz = volm.shape[0]
    rng = np.arange(-sz/2, sz)
    x, y, z = np.meshgrid(rng, rng, rng)
    r2 = x**2 + y**2 + z**2
    mask = r2 > sz**2
    volm.mask = mask
    if ref is not None:
        ref = ref.view(ma.MaskedArray)
        ref.mask = mask
        sigma = np.std(ref)
        mu = np.mean(ref)
    else:
        sigma = np.std(volm)
        mu = np.mean(volm)
    if return_stats:
        return (vol - mu) / sigma, mu, sigma
    return (vol - mu) / sigma

3 View Complete Implementation : resampling.py
Copyright MIT License
Author : CCI-Tools
def _get_mask(src):
    if isinstance(src, np.ma.MaskedArray):
        mask = np.ma.getmask(src)
        if mask is not np.ma.nomask:
            return mask, True
    return _NOMASK2D, False