Python numpy.issubsctype() Examples
The following are 12
code examples of numpy.issubsctype().
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: ray_transform_slow_test.py From odl with Mozilla Public License 2.0 | 6 votes |
def test_reconstruction(projector): """Test RayTransform for reconstruction.""" if ( isinstance(projector.geometry, odl.tomo.ConeBeamGeometry) and projector.geometry.pitch != 0 ): pytest.skip('reconstruction with CG is hopeless with so few angles') # Create Shepp-Logan phantom vol = odl.phantom.shepp_logan(projector.domain, modified=True) # Project data projections = projector(vol) # Reconstruct using ODL recon = projector.domain.zero() odl.solvers.conjugate_gradient_normal(projector, recon, projections, niter=20) # Make sure the result is somewhat close to the actual result maxerr = vol.norm() * 0.5 if np.issubsctype(projector.domain.dtype, np.complexfloating): # Error has double the amount of components practically maxerr *= np.sqrt(2) assert recon.dist(vol) < maxerr
Example #2
Source File: hierarchy.py From lambda-packs with MIT License | 5 votes |
def _copy_array_if_base_present(a): """ Copy the array if its base points to a parent array. """ if a.base is not None: return a.copy() elif np.issubsctype(a, np.float32): return np.array(a, dtype=np.double) else: return a
Example #3
Source File: distance.py From Computable with MIT License | 5 votes |
def _copy_array_if_base_present(a): """ Copies the array if its base points to a parent array. """ if a.base is not None: return a.copy() elif np.issubsctype(a, np.float32): return np.array(a, dtype=np.double) else: return a
Example #4
Source File: hierarchy.py From Computable with MIT License | 5 votes |
def _copy_array_if_base_present(a): """ Copies the array if its base points to a parent array. """ if a.base is not None: return a.copy() elif np.issubsctype(a, np.float32): return np.array(a, dtype=np.double) else: return a
Example #5
Source File: hierarchy.py From GraphicDesignPatternByPython with MIT License | 5 votes |
def _copy_array_if_base_present(a): """ Copy the array if its base points to a parent array. """ if a.base is not None: return a.copy() elif np.issubsctype(a, np.float32): return np.array(a, dtype=np.double) else: return a
Example #6
Source File: hierarchy.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
def _copy_array_if_base_present(a): """ Copies the array if its base points to a parent array. """ if a.base is not None: return a.copy() elif np.issubsctype(a, np.float32): return np.array(a, dtype=np.double) else: return a
Example #7
Source File: utility.py From odl with Mozilla Public License 2.0 | 5 votes |
def is_numeric_dtype(dtype): """Return ``True`` if ``dtype`` is a numeric type.""" dtype = np.dtype(dtype) return np.issubsctype(getattr(dtype, 'base', None), np.number)
Example #8
Source File: utility.py From odl with Mozilla Public License 2.0 | 5 votes |
def is_int_dtype(dtype): """Return ``True`` if ``dtype`` is an integer type.""" dtype = np.dtype(dtype) return np.issubsctype(getattr(dtype, 'base', None), np.integer)
Example #9
Source File: utility.py From odl with Mozilla Public License 2.0 | 5 votes |
def is_real_floating_dtype(dtype): """Return ``True`` if ``dtype`` is a real floating point type.""" dtype = np.dtype(dtype) return np.issubsctype(getattr(dtype, 'base', None), np.floating)
Example #10
Source File: utility.py From odl with Mozilla Public License 2.0 | 5 votes |
def is_complex_floating_dtype(dtype): """Return ``True`` if ``dtype`` is a complex floating point type.""" dtype = np.dtype(dtype) return np.issubsctype(getattr(dtype, 'base', None), np.complexfloating)
Example #11
Source File: design_info.py From vnpy_crypto with MIT License | 4 votes |
def slice(self, columns_specifier): """Locate a subset of design matrix columns, specified symbolically. A patsy design matrix has two levels of structure: the individual columns (which are named), and the :ref:`terms <formulas>` in the formula that generated those columns. This is a one-to-many relationship: a single term may span several columns. This method provides a user-friendly API for locating those columns. (While we talk about columns here, this is probably most useful for indexing into other arrays that are derived from the design matrix, such as regression coefficients or covariance matrices.) The `columns_specifier` argument can take a number of forms: * A term name * A column name * A :class:`Term` object * An integer giving a raw index * A raw slice object In all cases, a Python :func:`slice` object is returned, which can be used directly for indexing. Example:: y, X = dmatrices("y ~ a", demo_data("y", "a", nlevels=3)) betas = np.linalg.lstsq(X, y)[0] a_betas = betas[X.design_info.slice("a")] (If you want to look up a single individual column by name, use ``design_info.column_name_indexes[name]``.) """ if isinstance(columns_specifier, slice): return columns_specifier if np.issubsctype(type(columns_specifier), np.integer): return slice(columns_specifier, columns_specifier + 1) if (self.term_slices is not None and columns_specifier in self.term_slices): return self.term_slices[columns_specifier] if columns_specifier in self.term_name_slices: return self.term_name_slices[columns_specifier] if columns_specifier in self.column_name_indexes: idx = self.column_name_indexes[columns_specifier] return slice(idx, idx + 1) raise PatsyError("unknown column specified '%s'" % (columns_specifier,))
Example #12
Source File: design_info.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
def slice(self, columns_specifier): """Locate a subset of design matrix columns, specified symbolically. A patsy design matrix has two levels of structure: the individual columns (which are named), and the :ref:`terms <formulas>` in the formula that generated those columns. This is a one-to-many relationship: a single term may span several columns. This method provides a user-friendly API for locating those columns. (While we talk about columns here, this is probably most useful for indexing into other arrays that are derived from the design matrix, such as regression coefficients or covariance matrices.) The `columns_specifier` argument can take a number of forms: * A term name * A column name * A :class:`Term` object * An integer giving a raw index * A raw slice object In all cases, a Python :func:`slice` object is returned, which can be used directly for indexing. Example:: y, X = dmatrices("y ~ a", demo_data("y", "a", nlevels=3)) betas = np.linalg.lstsq(X, y)[0] a_betas = betas[X.design_info.slice("a")] (If you want to look up a single individual column by name, use ``design_info.column_name_indexes[name]``.) """ if isinstance(columns_specifier, slice): return columns_specifier if np.issubsctype(type(columns_specifier), np.integer): return slice(columns_specifier, columns_specifier + 1) if (self.term_slices is not None and columns_specifier in self.term_slices): return self.term_slices[columns_specifier] if columns_specifier in self.term_name_slices: return self.term_name_slices[columns_specifier] if columns_specifier in self.column_name_indexes: idx = self.column_name_indexes[columns_specifier] return slice(idx, idx + 1) raise PatsyError("unknown column specified '%s'" % (columns_specifier,))