Python core.dtype方法代码示例

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_basic1d(self):
        # Test of basic array creation and properties in 1 dimension.
        (x, y, a10, m1, m2, xm, ym, z, zm, xf) = self.d
        assert_(not isMaskedArray(x))
        assert_(isMaskedArray(xm))
        assert_((xm - ym).filled(0).any())
        fail_if_equal(xm.mask.astype(int), ym.mask.astype(int))
        s = x.shape
        assert_equal(np.shape(xm), s)
        assert_equal(xm.shape, s)
        assert_equal(xm.dtype, x.dtype)
        assert_equal(zm.dtype, z.dtype)
        assert_equal(xm.size, reduce(lambda x, y:x * y, s))
        assert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
        assert_array_equal(xm, xf)
        assert_array_equal(filled(xm, 1.e20), xf)
        assert_array_equal(x, xm) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_creation_maskcreation(self):
        # Tests how masks are initialized at the creation of Maskedarrays.
        data = arange(24, dtype=float)
        data[[3, 6, 15]] = masked
        dma_1 = MaskedArray(data)
        assert_equal(dma_1.mask, data.mask)
        dma_2 = MaskedArray(dma_1)
        assert_equal(dma_2.mask, dma_1.mask)
        dma_3 = MaskedArray(dma_1, mask=[1, 0, 0, 0] * 6)
        fail_if_equal(dma_3.mask, dma_1.mask)

        x = array([1, 2, 3], mask=True)
        assert_equal(x._mask, [True, True, True])
        x = array([1, 2, 3], mask=False)
        assert_equal(x._mask, [False, False, False])
        y = array([1, 2, 3], mask=x._mask, copy=False)
        assert_(np.may_share_memory(x.mask, y.mask))
        y = array([1, 2, 3], mask=x._mask, copy=True)
        assert_(not np.may_share_memory(x.mask, y.mask)) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_pickling(self):
        # Tests pickling
        for dtype in (int, float, str, object):
            a = arange(10).astype(dtype)
            a.fill_value = 999

            masks = ([0, 0, 0, 1, 0, 1, 0, 1, 0, 1],  # partially masked
                     True,                            # Fully masked
                     False)                           # Fully unmasked

            for proto in range(2, pickle.HIGHEST_PROTOCOL + 1):
                for mask in masks:
                    a.mask = mask
                    a_pickled = pickle.loads(pickle.dumps(a, protocol=proto))
                    assert_equal(a_pickled._mask, a._mask)
                    assert_equal(a_pickled._data, a._data)
                    if dtype in (object, int):
                        assert_equal(a_pickled.fill_value, 999)
                    else:
                        assert_equal(a_pickled.fill_value, dtype(999))
                    assert_array_equal(a_pickled.mask, mask) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_filled_with_nested_dtype(self):
        # Test filled w/ nested dtype
        ndtype = [('A', int), ('B', [('BA', int), ('BB', int)])]
        a = array([(1, (1, 1)), (2, (2, 2))],
                  mask=[(0, (1, 0)), (0, (0, 1))], dtype=ndtype)
        test = a.filled(0)
        control = np.array([(1, (0, 1)), (2, (2, 0))], dtype=ndtype)
        assert_equal(test, control)

        test = a['B'].filled(0)
        control = np.array([(0, 1), (2, 0)], dtype=a['B'].dtype)
        assert_equal(test, control)

        # test if mask gets set correctly (see #6760)
        Z = numpy.ma.zeros(2, numpy.dtype([("A", "(2,2)i1,(2,2)i1", (2,2))]))
        assert_equal(Z.data.dtype, numpy.dtype([('A', [('f0', 'i1', (2, 2)),
                                          ('f1', 'i1', (2, 2))], (2, 2))]))
        assert_equal(Z.mask.dtype, numpy.dtype([('A', [('f0', '?', (2, 2)),
                                          ('f1', '?', (2, 2))], (2, 2))])) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_fancy_printoptions(self):
        # Test printing a masked array w/ fancy dtype.
        fancydtype = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
        test = array([(1, (2, 3.0)), (4, (5, 6.0))],
                     mask=[(1, (0, 1)), (0, (1, 0))],
                     dtype=fancydtype)
        control = "[(--, (2, --)) (4, (--, 6.0))]"
        assert_equal(str(test), control)

        # Test 0-d array with multi-dimensional dtype
        t_2d0 = masked_array(data = (0, [[0.0, 0.0, 0.0],
                                        [0.0, 0.0, 0.0]],
                                    0.0),
                             mask = (False, [[True, False, True],
                                             [False, False, True]],
                                     False),
                             dtype = "int, (2,3)float, float")
        control = "(0, [[--, 0.0, --], [0.0, 0.0, --]], 0.0)"
        assert_equal(str(t_2d0), control) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_mvoid_getitem(self):
        # Test mvoid.__getitem__
        ndtype = [('a', int), ('b', int)]
        a = masked_array([(1, 2,), (3, 4)], mask=[(0, 0), (1, 0)],
                         dtype=ndtype)
        # w/o mask
        f = a[0]
        assert_(isinstance(f, mvoid))
        assert_equal((f[0], f['a']), (1, 1))
        assert_equal(f['b'], 2)
        # w/ mask
        f = a[1]
        assert_(isinstance(f, mvoid))
        assert_(f[0] is masked)
        assert_(f['a'] is masked)
        assert_equal(f[1], 4)

        # exotic dtype
        A = masked_array(data=[([0,1],)],
                         mask=[([True, False],)],
                         dtype=[("A", ">i2", (2,))])
        assert_equal(A[0]["A"], A["A"][0])
        assert_equal(A[0]["A"], masked_array(data=[0, 1],
                         mask=[True, False], dtype=">i2")) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_mvoid_print(self):
        # Test printing a mvoid
        mx = array([(1, 1), (2, 2)], dtype=[('a', int), ('b', int)])
        assert_equal(str(mx[0]), "(1, 1)")
        mx['b'][0] = masked
        ini_display = masked_print_option._display
        masked_print_option.set_display("-X-")
        try:
            assert_equal(str(mx[0]), "(1, -X-)")
            assert_equal(repr(mx[0]), "(1, -X-)")
        finally:
            masked_print_option.set_display(ini_display)

        # also check if there are object datatypes (see gh-7493)
        mx = array([(1,), (2,)], dtype=[('a', 'O')])
        assert_equal(str(mx[0]), "(1,)") 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_count_func(self):
        # Tests count
        assert_equal(1, count(1))
        assert_equal(0, array(1, mask=[1]))

        ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
        res = count(ott)
        assert_(res.dtype.type is np.intp)
        assert_equal(3, res)

        ott = ott.reshape((2, 2))
        res = count(ott)
        assert_(res.dtype.type is np.intp)
        assert_equal(3, res)
        res = count(ott, 0)
        assert_(isinstance(res, ndarray))
        assert_equal([1, 2], res)
        assert_(getmask(res) is nomask)

        ott = array([0., 1., 2., 3.])
        res = count(ott, 0)
        assert_(isinstance(res, ndarray))
        assert_(res.dtype.type is np.intp)
        assert_raises(np.AxisError, ott.count, axis=1) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_minmax_funcs_with_output(self):
        # Tests the min/max functions with explicit outputs
        mask = np.random.rand(12).round()
        xm = array(np.random.uniform(0, 10, 12), mask=mask)
        xm.shape = (3, 4)
        for funcname in ('min', 'max'):
            # Initialize
            npfunc = getattr(np, funcname)
            mafunc = getattr(numpy.ma.core, funcname)
            # Use the np version
            nout = np.empty((4,), dtype=int)
            try:
                result = npfunc(xm, axis=0, out=nout)
            except MaskError:
                pass
            nout = np.empty((4,), dtype=float)
            result = npfunc(xm, axis=0, out=nout)
            assert_(result is nout)
            # Use the ma version
            nout.fill(-999)
            result = mafunc(xm, axis=0, out=nout)
            assert_(result is nout) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_methods_with_output(self):
        xm = array(np.random.uniform(0, 10, 12)).reshape(3, 4)
        xm[:, 0] = xm[0] = xm[-1, -1] = masked

        funclist = ('sum', 'prod', 'var', 'std', 'max', 'min', 'ptp', 'mean',)

        for funcname in funclist:
            npfunc = getattr(np, funcname)
            xmmeth = getattr(xm, funcname)
            # A ndarray as explicit input
            output = np.empty(4, dtype=float)
            output.fill(-9999)
            result = npfunc(xm, axis=0, out=output)
            # ... the result should be the given output
            assert_(result is output)
            assert_equal(result, xmmeth(axis=0, out=output))

            output = empty(4, dtype=int)
            result = xmmeth(axis=0, out=output)
            assert_(result is output)
            assert_(output[0] is masked) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_eq_for_strings(self, dt, fill):
        # Test the equality of structured arrays
        a = array(['a', 'b'], dtype=dt, mask=[0, 1], fill_value=fill)

        test = (a == a)
        assert_equal(test.data, [True, True])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        test = (a == a[0])
        assert_equal(test.data, [True, False])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        b = array(['a', 'b'], dtype=dt, mask=[1, 0], fill_value=fill)
        test = (a == b)
        assert_equal(test.data, [False, False])
        assert_equal(test.mask, [True, True])
        assert_(test.fill_value == True)

        # test = (a[0] == b)  # doesn't work in Python2
        test = (b == a[0])
        assert_equal(test.data, [False, False])
        assert_equal(test.mask, [True, False])
        assert_(test.fill_value == True) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_ne_for_strings(self, dt, fill):
        # Test the equality of structured arrays
        a = array(['a', 'b'], dtype=dt, mask=[0, 1], fill_value=fill)

        test = (a != a)
        assert_equal(test.data, [False, False])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        test = (a != a[0])
        assert_equal(test.data, [False, True])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        b = array(['a', 'b'], dtype=dt, mask=[1, 0], fill_value=fill)
        test = (a != b)
        assert_equal(test.data, [True, True])
        assert_equal(test.mask, [True, True])
        assert_(test.fill_value == True)

        # test = (a[0] != b)  # doesn't work in Python2
        test = (b != a[0])
        assert_equal(test.data, [True, True])
        assert_equal(test.mask, [True, False])
        assert_(test.fill_value == True) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_eq_for_numeric(self, dt1, dt2, fill):
        # Test the equality of structured arrays
        a = array([0, 1], dtype=dt1, mask=[0, 1], fill_value=fill)

        test = (a == a)
        assert_equal(test.data, [True, True])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        test = (a == a[0])
        assert_equal(test.data, [True, False])
        assert_equal(test.mask, [False, True])
        assert_(test.fill_value == True)

        b = array([0, 1], dtype=dt2, mask=[1, 0], fill_value=fill)
        test = (a == b)
        assert_equal(test.data, [False, False])
        assert_equal(test.mask, [True, True])
        assert_(test.fill_value == True)

        # test = (a[0] == b)  # doesn't work in Python2
        test = (b == a[0])
        assert_equal(test.data, [False, False])
        assert_equal(test.mask, [True, False])
        assert_(test.fill_value == True) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_assign_dtype(self):
        # check that the mask's dtype is updated when dtype is changed
        a = np.zeros(4, dtype='f4,i4')

        m = np.ma.array(a)
        m.dtype = np.dtype('f4')
        repr(m)  # raises?
        assert_equal(m.dtype, np.dtype('f4'))

        # check that dtype changes that change shape of mask too much
        # are not allowed
        def assign():
            m = np.ma.array(a)
            m.dtype = np.dtype('f8')
        assert_raises(ValueError, assign)

        b = a.view(dtype='f4', type=np.ma.MaskedArray)  # raises?
        assert_equal(b.dtype, np.dtype('f4'))

        # check that nomask is preserved
        a = np.zeros(4, dtype='f4')
        m = np.ma.array(a)
        m.dtype = np.dtype('f4,i4')
        assert_equal(m.dtype, np.dtype('f4,i4'))
        assert_equal(m._mask, np.ma.nomask) 

# 需要导入模块: from numpy.ma import core [as 别名]
# 或者: from numpy.ma.core import dtype [as 别名]
def test_fillvalue_conversion(self):
        # Tests the behavior of fill_value during conversion
        # We had a tailored comment to make sure special attributes are
        # properly dealt with
        a = array([b'3', b'4', b'5'])
        a._optinfo.update({'comment':"updated!"})

        b = array(a, dtype=int)
        assert_equal(b._data, [3, 4, 5])
        assert_equal(b.fill_value, default_fill_value(0))

        b = array(a, dtype=float)
        assert_equal(b._data, [3, 4, 5])
        assert_equal(b.fill_value, default_fill_value(0.))

        b = a.astype(int)
        assert_equal(b._data, [3, 4, 5])
        assert_equal(b.fill_value, default_fill_value(0))
        assert_equal(b._optinfo['comment'], "updated!")

        b = a.astype([('a', '|S3')])
        assert_equal(b['a']._data, a._data)
        assert_equal(b['a'].fill_value, a.fill_value)