Python numpy.sctypeDict() Examples

The following are 10 code examples of numpy.sctypeDict(). 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: linsolve.py    From lambda-packs with MIT License 6 votes vote down vote up 
def _get_umf_family(A):
    """Get umfpack family string given the sparse matrix dtype."""
    _families = {
        (np.float64, np.int32): 'di',
        (np.complex128, np.int32): 'zi',
        (np.float64, np.int64): 'dl',
        (np.complex128, np.int64): 'zl'
    }

    f_type = np.sctypeDict[A.dtype.name]
    i_type = np.sctypeDict[A.indices.dtype.name]

    try:
        family = _families[(f_type, i_type)]

    except KeyError:
        msg = 'only float64 or complex128 matrices with int32 or int64' \
            ' indices are supported! (got: matrix: %s, indices: %s)' \
            % (f_type, i_type)
        raise ValueError(msg)

    return family
Example #2
Source File: linsolve.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def _get_umf_family(A):
    """Get umfpack family string given the sparse matrix dtype."""
    _families = {
        (np.float64, np.int32): 'di',
        (np.complex128, np.int32): 'zi',
        (np.float64, np.int64): 'dl',
        (np.complex128, np.int64): 'zl'
    }

    f_type = np.sctypeDict[A.dtype.name]
    i_type = np.sctypeDict[A.indices.dtype.name]

    try:
        family = _families[(f_type, i_type)]

    except KeyError:
        msg = 'only float64 or complex128 matrices with int32 or int64' \
            ' indices are supported! (got: matrix: %s, indices: %s)' \
            % (f_type, i_type)
        raise ValueError(msg)

    return family
Example #3
Source File: test_numerictypes.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_longdouble(self):
        assert_(np.sctypeDict['f8'] is not np.longdouble)
        assert_(np.sctypeDict['c16'] is not np.clongdouble)
Example #4
Source File: data_maker.py    From BiblioPixel with MIT License 5 votes vote down vote up 
def __init__(self, floating=None, shared_memory=False, numpy_dtype=None):
        if numpy_dtype:
            log.debug('Using numpy')
            if numpy_dtype in NUMPY_DEFAULTS:
                numpy_dtype = 'float32'
            if numpy_dtype not in numpy.sctypeDict:
                raise ValueError(BAD_NUMPY_TYPE_ERROR % numpy_dtype)

        if shared_memory and numpy_dtype:
            log.error('Shared memory for numpy arrays is not yet supported.')
            numpy_dtype = None

        if floating is None:
            floating = not shared_memory

        c_type = c_float if floating else c_uint8

        if shared_memory:
            self.bytes = lambda size: RawArray(c_uint8, size)
            self.color_list = lambda size: RawArray(3 * c_type, size)
            # Note https://stackoverflow.com/questions/37705974/

        elif numpy_dtype:
            self.bytes = bytearray
            self.color_list = lambda size: numpy.zeros((size, 3), numpy_dtype)

        else:
            self.bytes = bytearray
            self.color_list = lambda size: [(0, 0, 0)] * size
Example #5
Source File: basic.py    From D-VAE with MIT License 5 votes vote down vote up 
def impl(self, x, y):
        x = numpy.asarray(x)
        y = numpy.asarray(y)
        if all(a.dtype in discrete_types for a in (x, y)):
            return numpy.sctypeDict[config.floatX](float(x) / y)
        else:
            return x / y
Example #6
Source File: test_numerictypes.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_longdouble(self):
        assert_(np.sctypeDict['f8'] is not np.longdouble)
        assert_(np.sctypeDict['c16'] is not np.clongdouble)
Example #7
Source File: basic.py    From attention-lvcsr with MIT License 5 votes vote down vote up 
def impl(self, x, y):
        x = numpy.asarray(x)
        y = numpy.asarray(y)
        if all(a.dtype in discrete_types for a in (x, y)):
            return numpy.sctypeDict[config.floatX](float(x) / y)
        else:
            return x / y
Example #8
Source File: test_numerictypes.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_longdouble(self):
        assert_(np.sctypeDict['f8'] is not np.longdouble)
        assert_(np.sctypeDict['c16'] is not np.clongdouble)
Example #9
Source File: interface.py    From scikit-umfpack with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def __init__(self, A):
        if not (isspmatrix_csc(A) or isspmatrix_csr(A)):
            A = csc_matrix(A)
            warn('spsolve requires A be CSC or CSR matrix format',
                    SparseEfficiencyWarning)

        A.sort_indices()
        A = A.asfptype()  # upcast to a floating point format

        M, N = A.shape
        if (M != N):
            raise ValueError("matrix must be square (has shape %s)" % ((M, N),))

        f_type = np.sctypeDict[A.dtype.name]
        i_type = np.sctypeDict[A.indices.dtype.name]
        try:
            family = _families[(f_type, i_type)]

        except KeyError:
            msg = 'only float64 or complex128 matrices with int32 or int64' \
                ' indices are supported! (got: matrix: %s, indices: %s)' \
                % (f_type, i_type)
            raise ValueError(msg)

        self.umf = UmfpackContext(family)
        self.umf.numeric(A)

        self._A = A
        self._L = None
        self._U = None
        self._P = None
        self._Q = None
        self._R = None
Example #10
Source File: test_numerictypes.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_longdouble(self):
        assert_(np.sctypeDict['f8'] is not np.longdouble)
        assert_(np.sctypeDict['c16'] is not np.clongdouble)