python类cdouble()的实例源码

def test_complex_type_print():
    """Check formatting when using print """
    for t in [np.complex64, np.cdouble, np.clongdouble]:
        yield check_complex_type_print, t

def test_export_record(self):
        dt = [('a', 'b'),
              ('b', 'h'),
              ('c', 'i'),
              ('d', 'l'),
              ('dx', 'q'),
              ('e', 'B'),
              ('f', 'H'),
              ('g', 'I'),
              ('h', 'L'),
              ('hx', 'Q'),
              ('i', np.single),
              ('j', np.double),
              ('k', np.longdouble),
              ('ix', np.csingle),
              ('jx', np.cdouble),
              ('kx', np.clongdouble),
              ('l', 'S4'),
              ('m', 'U4'),
              ('n', 'V3'),
              ('o', '?'),
              ('p', np.half),
              ]
        x = np.array(
                [(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
                    asbytes('aaaa'), 'bbbb', asbytes('   '), True, 1.0)],
                dtype=dt)
        y = memoryview(x)
        assert_equal(y.shape, (1,))
        assert_equal(y.ndim, 1)
        assert_equal(y.suboffsets, EMPTY)

        sz = sum([np.dtype(b).itemsize for a, b in dt])
        if np.dtype('l').itemsize == 4:
            assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
        else:
            assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
        # Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides
        if not (np.ones(1).strides[0] == np.iinfo(np.intp).max):
            assert_equal(y.strides, (sz,))
        assert_equal(y.itemsize, sz)

def test_array(self):
        a = np.array([], float)
        self.check_roundtrips(a)

        a = np.array([[1, 2], [3, 4]], float)
        self.check_roundtrips(a)

        a = np.array([[1, 2], [3, 4]], int)
        self.check_roundtrips(a)

        a = np.array([[1 + 5j, 2 + 6j], [3 + 7j, 4 + 8j]], dtype=np.csingle)
        self.check_roundtrips(a)

        a = np.array([[1 + 5j, 2 + 6j], [3 + 7j, 4 + 8j]], dtype=np.cdouble)
        self.check_roundtrips(a)

def test_basic(self):
        ai32 = np.array([[1, 2], [3, 4]], dtype=np.int32)
        af16 = np.array([[1, 2], [3, 4]], dtype=np.float16)
        af32 = np.array([[1, 2], [3, 4]], dtype=np.float32)
        af64 = np.array([[1, 2], [3, 4]], dtype=np.float64)
        acs = np.array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=np.csingle)
        acd = np.array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=np.cdouble)
        assert_(common_type(ai32) == np.float64)
        assert_(common_type(af16) == np.float16)
        assert_(common_type(af32) == np.float32)
        assert_(common_type(af64) == np.float64)
        assert_(common_type(acs) == np.csingle)
        assert_(common_type(acd) == np.cdouble)

def get_complex_dtype(dtype):
    return {single: csingle, double: cdouble,
            csingle: csingle, cdouble: cdouble}[dtype]

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.solve(x, x).dtype, dtype)
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.inv(x).dtype, dtype)
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, dtype)
            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            w, v = np.linalg.eig(x)
            assert_equal(w.dtype, dtype)
            assert_equal(v.dtype, dtype)

            x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
            w, v = np.linalg.eig(x)
            assert_equal(w.dtype, get_complex_dtype(dtype))
            assert_equal(v.dtype, get_complex_dtype(dtype))

        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_zero(self):
        assert_equal(linalg.det([[0.0]]), 0.0)
        assert_equal(type(linalg.det([[0.0]])), double)
        assert_equal(linalg.det([[0.0j]]), 0.0)
        assert_equal(type(linalg.det([[0.0j]])), cdouble)

        assert_equal(linalg.slogdet([[0.0]]), (0.0, -inf))
        assert_equal(type(linalg.slogdet([[0.0]])[0]), double)
        assert_equal(type(linalg.slogdet([[0.0]])[1]), double)
        assert_equal(linalg.slogdet([[0.0j]]), (0.0j, -inf))
        assert_equal(type(linalg.slogdet([[0.0j]])[0]), cdouble)
        assert_equal(type(linalg.slogdet([[0.0j]])[1]), double)

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            assert_equal(np.linalg.det(x).dtype, dtype)
            ph, s = np.linalg.slogdet(x)
            assert_equal(s.dtype, get_real_dtype(dtype))
            assert_equal(ph.dtype, dtype)
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            w = np.linalg.eigvalsh(x)
            assert_equal(w.dtype, get_real_dtype(dtype))
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def test_types(self):
        def check(dtype):
            x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
            w, v = np.linalg.eigh(x)
            assert_equal(w.dtype, get_real_dtype(dtype))
            assert_equal(v.dtype, dtype)
        for dtype in [single, double, csingle, cdouble]:
            yield check, dtype

def Sequence_Mask(\
    self,
    pipelineitem
    ):
    if self.pipeline_started == True:
        title = "Sequence " + pipelineitem.treeitem['name']
        self.ancestor.GetPage(0).queue_info.put("Preparing mask array...")
        filename_in = pipelineitem.input_filename.objectpath.GetValue()
        filename_out = pipelineitem.output_filename.objectpath.GetValue()
        frac_max =  float(pipelineitem.max.value.GetValue())
        frac_min =  float(pipelineitem.min.value.GetValue())
        try:
                array = LoadArray(self, filename_in)
        except:
            msg = "Could not load array."
            wx.CallAfter(self.UserMessage, title, msg)
            self.pipeline_started = False
            return
        else:
            mask = numpy.asarray(array, dtype=numpy.cdouble, order='C')
            from ..lib.prfftw import rangereplace
            rangereplace(mask, frac_min, frac_max, 0.0, 1.0)
            try:
                SaveArray(self, filename_out,mask)
            except:
                msg = "Could not save array."
                wx.CallAfter(self.UserMessage, title, msg)
                self.pipeline_started = False
                return

def WrapArray2(array):
    if array.shape[2] == 1:
        b1 = numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[0]
        b2 = numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[1]
        b3 = numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[0]
        b4 = numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[1]
        v1 = numpy.vstack((b4,b2))
        v2 = numpy.vstack((b3,b1))
        arrayfinal = numpy.array(numpy.hstack((v1,v2)), dtype=numpy.cdouble, copy=True, order='C')
        return arrayfinal
    else:
        b1 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[0], 2, axis=2 )[0]
        b2 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[0], 2, axis=2 )[1]
        b3 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[1], 2, axis=2 )[0]
        b4 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[0], 2, axis=1 )[1], 2, axis=2 )[1]
        b5 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[0], 2, axis=2 )[0]
        b6 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[0], 2, axis=2 )[1]
        b7 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[1], 2, axis=2 )[0]
        b8 = numpy.array_split( numpy.array_split( numpy.array_split( array, 2, axis=0 )[1], 2, axis=1 )[1], 2, axis=2 )[1]
        v1 = numpy.vstack((b8,b4))
        v2 = numpy.vstack((b7,b3))
        v3 = numpy.vstack((b6,b2))
        v4 = numpy.vstack((b5,b1))
        h1 = numpy.hstack((v1,v3))
        h2 = numpy.hstack((v2,v4))
        arrayfinal = numpy.array(numpy.dstack((h1,h2)), dtype=numpy.cdouble, copy=True, order='C')
        return arrayfinal

def NewArray(self,x,y,z):
    try:
        array = numpy.zeros((x,y,z), dtype=numpy.cdouble, order='C')
    except MemoryError:
        self.ancestor.GetPage(0).queue_info.put("Could not create array. Insufficient memory.")
        raise MemoryError
    else:
        return array

def test_complex_scalar_warning(self):
        for tp in [np.csingle, np.cdouble, np.clongdouble]:
            x = tp(1+2j)
            assert_warns(np.ComplexWarning, float, x)
            with warnings.catch_warnings():
                warnings.simplefilter('ignore')
                assert_equal(float(x), float(x.real))

def test_complex_scalar_complex_cast(self):
        for tp in [np.csingle, np.cdouble, np.clongdouble]:
            x = tp(1+2j)
            assert_equal(complex(x), 1+2j)

def test_complex_boolean_cast(self):
        # Ticket #2218
        for tp in [np.csingle, np.cdouble, np.clongdouble]:
            x = np.array([0, 0+0.5j, 0.5+0j], dtype=tp)
            assert_equal(x.astype(bool), np.array([0, 1, 1], dtype=bool))
            assert_(np.any(x))
            assert_(np.all(x[1:]))

def test_precisions_consistent(self):
        z = 1 + 1j
        for f in self.funcs:
            fcf = f(np.csingle(z))
            fcd = f(np.cdouble(z))
            fcl = f(np.clongdouble(z))
            assert_almost_equal(fcf, fcd, decimal=6, err_msg='fch-fcd %s' % f)
            assert_almost_equal(fcl, fcd, decimal=15, err_msg='fch-fcl %s' % f)