Python numpy.sctypeDict() Examples
The following are 10
code examples of numpy.sctypeDict().
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Example #1
Source File: linsolve.py From lambda-packs with MIT License | 6 votes |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
def test_longdouble(self): assert_(np.sctypeDict['f8'] is not np.longdouble) assert_(np.sctypeDict['c16'] is not np.clongdouble)