numpy.ma.shape - python examples

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

7 Examples 7

3 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : abhisuri97
    def test_testBasic1d(self):
        # Test of basic array creation and properties in 1 dimension.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
        self.astertFalse(isMaskedArray(x))
        self.astertTrue(isMaskedArray(xm))
        self.astertEqual(shape(xm), s)
        self.astertEqual(xm.shape, s)
        self.astertEqual(xm.dtype, x.dtype)
        self.astertEqual(xm.size, reduce(lambda x, y:x * y, s))
        self.astertEqual(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
        self.astertTrue(eq(xm, xf))
        self.astertTrue(eq(filled(xm, 1.e20), xf))
        self.astertTrue(eq(x, xm))

3 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : alvarob96
    def test_testBasic1d(self):
        # Test of basic array creation and properties in 1 dimension.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
        astert_(not isMaskedArray(x))
        astert_(isMaskedArray(xm))
        astert_equal(shape(xm), s)
        astert_equal(xm.shape, s)
        astert_equal(xm.dtype, x.dtype)
        astert_equal(xm.size, reduce(lambda x, y:x * y, s))
        astert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
        astert_(eq(xm, xf))
        astert_(eq(filled(xm, 1.e20), xf))
        astert_(eq(x, xm))

0 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : abhisuri97
    def test_testBasic2d(self):
        # Test of basic array creation and properties in 2 dimensions.
        for s in [(4, 3), (6, 2)]:
            (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
            x.shape = s
            y.shape = s
            xm.shape = s
            ym.shape = s
            xf.shape = s

            self.astertFalse(isMaskedArray(x))
            self.astertTrue(isMaskedArray(xm))
            self.astertEqual(shape(xm), s)
            self.astertEqual(xm.shape, s)
            self.astertEqual(xm.size, reduce(lambda x, y:x * y, s))
            self.astertEqual(count(xm),
                             len(m1) - reduce(lambda x, y:x + y, m1))
            self.astertTrue(eq(xm, xf))
            self.astertTrue(eq(filled(xm, 1.e20), xf))
            self.astertTrue(eq(x, xm))
            self.setUp()

0 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : abhisuri97
    def test_testOddFeatures(self):
        # Test of other odd features
        x = arange(20)
        x = x.reshape(4, 5)
        x.flat[5] = 12
        astert_(x[1, 0] == 12)
        z = x + 10j * x
        astert_(eq(z.real, x))
        astert_(eq(z.imag, 10 * x))
        astert_(eq((z * conjugate(z)).real, 101 * x * x))
        z.imag[...] = 0.0

        x = arange(10)
        x[3] = masked
        astert_(str(x[3]) == str(masked))
        c = x >= 8
        astert_(count(where(c, masked, masked)) == 0)
        astert_(shape(where(c, masked, masked)) == c.shape)
        z = where(c, x, masked)
        astert_(z.dtype is x.dtype)
        astert_(z[3] is masked)
        astert_(z[4] is masked)
        astert_(z[7] is masked)
        astert_(z[8] is not masked)
        astert_(z[9] is not masked)
        astert_(eq(x, z))
        z = where(c, masked, x)
        astert_(z.dtype is x.dtype)
        astert_(z[3] is masked)
        astert_(z[4] is not masked)
        astert_(z[7] is not masked)
        astert_(z[8] is masked)
        astert_(z[9] is masked)
        z = masked_where(c, x)
        astert_(z.dtype is x.dtype)
        astert_(z[3] is masked)
        astert_(z[4] is not masked)
        astert_(z[7] is not masked)
        astert_(z[8] is masked)
        astert_(z[9] is masked)
        astert_(eq(x, z))
        x = array([1., 2., 3., 4., 5.])
        c = array([1, 1, 1, 0, 0])
        x[2] = masked
        z = where(c, x, -x)
        astert_(eq(z, [1., 2., 0., -4., -5]))
        c[0] = masked
        z = where(c, x, -x)
        astert_(eq(z, [1., 2., 0., -4., -5]))
        astert_(z[0] is masked)
        astert_(z[1] is not masked)
        astert_(z[2] is masked)
        astert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))
        astert_(eq(masked_where(greater_equal(x, 2), x),
                   masked_greater_equal(x, 2)))
        astert_(eq(masked_where(less(x, 2), x), masked_less(x, 2)))
        astert_(eq(masked_where(less_equal(x, 2), x), masked_less_equal(x, 2)))
        astert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
        astert_(eq(masked_where(equal(x, 2), x), masked_equal(x, 2)))
        astert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
        astert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
        astert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
        astert_(eq(masked_inside(array(list(range(5)),
                                       mask=[1, 0, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 1, 1, 0]))
        astert_(eq(masked_outside(array(list(range(5)),
                                        mask=[0, 1, 0, 0, 0]), 1, 3).mask,
                   [1, 1, 0, 0, 1]))
        astert_(eq(masked_equal(array(list(range(5)),
                                      mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 0]))
        astert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
                                          mask=[1, 0, 0, 0, 0]), 2).mask,
                   [1, 0, 1, 0, 1]))
        astert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
                   [99, 99, 3, 4, 5]))
        atest = ones((10, 10, 10), dtype=np.float32)
        btest = zeros(atest.shape, MaskType)
        ctest = masked_where(btest, atest)
        astert_(eq(atest, ctest))
        z = choose(c, (-x, x))
        astert_(eq(z, [1., 2., 0., -4., -5]))
        astert_(z[0] is masked)
        astert_(z[1] is not masked)
        astert_(z[2] is masked)
        x = arange(6)
        x[5] = masked
        y = arange(6) * 10
        y[2] = masked
        c = array([1, 1, 1, 0, 0, 0], mask=[1, 0, 0, 0, 0, 0])
        cm = c.filled(1)
        z = where(c, x, y)
        zm = where(cm, x, y)
        astert_(eq(z, zm))
        astert_(getmask(zm) is nomask)
        astert_(eq(zm, [0, 1, 2, 30, 40, 50]))
        z = where(c, masked, 1)
        astert_(eq(z, [99, 99, 99, 1, 1, 1]))
        z = where(c, 1, masked)
        astert_(eq(z, [99, 1, 1, 99, 99, 99]))

0 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : abhisuri97
    def test_testAverage2(self):
        # More tests of average.
        w1 = [0, 1, 1, 1, 1, 0]
        w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
        x = arange(6)
        self.astertTrue(allclose(average(x, axis=0), 2.5))
        self.astertTrue(allclose(average(x, axis=0, weights=w1), 2.5))
        y = array([arange(6), 2.0 * arange(6)])
        self.astertTrue(allclose(average(y, None),
                                 np.add.reduce(np.arange(6)) * 3. / 12.))
        self.astertTrue(allclose(average(y, axis=0), np.arange(6) * 3. / 2.))
        self.astertTrue(allclose(average(y, axis=1),
                                 [average(x, axis=0), average(x, axis=0)*2.0]))
        self.astertTrue(allclose(average(y, None, weights=w2), 20. / 6.))
        self.astertTrue(allclose(average(y, axis=0, weights=w2),
                                 [0., 1., 2., 3., 4., 10.]))
        self.astertTrue(allclose(average(y, axis=1),
                                 [average(x, axis=0), average(x, axis=0)*2.0]))
        m1 = zeros(6)
        m2 = [0, 0, 1, 1, 0, 0]
        m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
        m4 = ones(6)
        m5 = [0, 1, 1, 1, 1, 1]
        self.astertTrue(allclose(average(masked_array(x, m1), axis=0), 2.5))
        self.astertTrue(allclose(average(masked_array(x, m2), axis=0), 2.5))
        self.astertTrue(average(masked_array(x, m4), axis=0) is masked)
        self.astertEqual(average(masked_array(x, m5), axis=0), 0.0)
        self.astertEqual(count(average(masked_array(x, m4), axis=0)), 0)
        z = masked_array(y, m3)
        self.astertTrue(allclose(average(z, None), 20. / 6.))
        self.astertTrue(allclose(average(z, axis=0),
                                 [0., 1., 99., 99., 4.0, 7.5]))
        self.astertTrue(allclose(average(z, axis=1), [2.5, 5.0]))
        self.astertTrue(allclose(average(z, axis=0, weights=w2),
                                 [0., 1., 99., 99., 4.0, 10.0]))

        a = arange(6)
        b = arange(6) * 3
        r1, w1 = average([[a, b], [b, a]], axis=1, returned=1)
        self.astertEqual(shape(r1), shape(w1))
        self.astertEqual(r1.shape, w1.shape)
        r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=1)
        self.astertEqual(shape(w2), shape(r2))
        r2, w2 = average(ones((2, 2, 3)), returned=1)
        self.astertEqual(shape(w2), shape(r2))
        r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=1)
        self.astertTrue(shape(w2) == shape(r2))
        a2d = array([[1, 2], [0, 4]], float)
        a2dm = masked_array(a2d, [[0, 0], [1, 0]])
        a2da = average(a2d, axis=0)
        self.astertTrue(eq(a2da, [0.5, 3.0]))
        a2dma = average(a2dm, axis=0)
        self.astertTrue(eq(a2dma, [1.0, 3.0]))
        a2dma = average(a2dm, axis=None)
        self.astertTrue(eq(a2dma, 7. / 3.))
        a2dma = average(a2dm, axis=1)
        self.astertTrue(eq(a2dma, [1.5, 4.0]))

0 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : alvarob96
    def test_testBasic2d(self):
        # Test of basic array creation and properties in 2 dimensions.
        for s in [(4, 3), (6, 2)]:
            (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
            x.shape = s
            y.shape = s
            xm.shape = s
            ym.shape = s
            xf.shape = s

            astert_(not isMaskedArray(x))
            astert_(isMaskedArray(xm))
            astert_equal(shape(xm), s)
            astert_equal(xm.shape, s)
            astert_equal(xm.size, reduce(lambda x, y:x * y, s))
            astert_equal(count(xm),
                             len(m1) - reduce(lambda x, y:x + y, m1))
            astert_(eq(xm, xf))
            astert_(eq(filled(xm, 1.e20), xf))
            astert_(eq(x, xm))
            self.setup()

0 View Complete Implementation : test_old_ma.py
Copyright MIT License
Author : alvarob96
    def test_testAverage2(self):
        # More tests of average.
        w1 = [0, 1, 1, 1, 1, 0]
        w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
        x = arange(6)
        astert_(allclose(average(x, axis=0), 2.5))
        astert_(allclose(average(x, axis=0, weights=w1), 2.5))
        y = array([arange(6), 2.0 * arange(6)])
        astert_(allclose(average(y, None),
                                 np.add.reduce(np.arange(6)) * 3. / 12.))
        astert_(allclose(average(y, axis=0), np.arange(6) * 3. / 2.))
        astert_(allclose(average(y, axis=1),
                                 [average(x, axis=0), average(x, axis=0)*2.0]))
        astert_(allclose(average(y, None, weights=w2), 20. / 6.))
        astert_(allclose(average(y, axis=0, weights=w2),
                                 [0., 1., 2., 3., 4., 10.]))
        astert_(allclose(average(y, axis=1),
                                 [average(x, axis=0), average(x, axis=0)*2.0]))
        m1 = zeros(6)
        m2 = [0, 0, 1, 1, 0, 0]
        m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
        m4 = ones(6)
        m5 = [0, 1, 1, 1, 1, 1]
        astert_(allclose(average(masked_array(x, m1), axis=0), 2.5))
        astert_(allclose(average(masked_array(x, m2), axis=0), 2.5))
        astert_(average(masked_array(x, m4), axis=0) is masked)
        astert_equal(average(masked_array(x, m5), axis=0), 0.0)
        astert_equal(count(average(masked_array(x, m4), axis=0)), 0)
        z = masked_array(y, m3)
        astert_(allclose(average(z, None), 20. / 6.))
        astert_(allclose(average(z, axis=0),
                                 [0., 1., 99., 99., 4.0, 7.5]))
        astert_(allclose(average(z, axis=1), [2.5, 5.0]))
        astert_(allclose(average(z, axis=0, weights=w2),
                                 [0., 1., 99., 99., 4.0, 10.0]))

        a = arange(6)
        b = arange(6) * 3
        r1, w1 = average([[a, b], [b, a]], axis=1, returned=1)
        astert_equal(shape(r1), shape(w1))
        astert_equal(r1.shape, w1.shape)
        r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=1)
        astert_equal(shape(w2), shape(r2))
        r2, w2 = average(ones((2, 2, 3)), returned=1)
        astert_equal(shape(w2), shape(r2))
        r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=1)
        astert_(shape(w2) == shape(r2))
        a2d = array([[1, 2], [0, 4]], float)
        a2dm = masked_array(a2d, [[0, 0], [1, 0]])
        a2da = average(a2d, axis=0)
        astert_(eq(a2da, [0.5, 3.0]))
        a2dma = average(a2dm, axis=0)
        astert_(eq(a2dma, [1.0, 3.0]))
        a2dma = average(a2dm, axis=None)
        astert_(eq(a2dma, 7. / 3.))
        a2dma = average(a2dm, axis=1)
        astert_(eq(a2dma, [1.5, 4.0]))