"""This module defines functions for type, value, and/or attribute checking."""
from numpy import any, float32, tile
__all__ = ['checkCoords', 'checkWeights', 'checkTypes']
COORDS_NDIM = set([2])
CSETS_NDIMS = set([2, 3])
[docs]def checkCoords(coords, csets=False, natoms=None, dtype=(float, float32),
name='coords'):
"""Returns **True** if shape, dimensionality, and data type of *coords*
array are as expected.
:arg coords: coordinate array
:arg csets: whether multiple coordinate sets (i.e. ``.ndim in (2, 3)``) are
allowed, default is **False**
:arg natoms: number of atoms, if **None** number of atoms is not checked
:arg dtype: allowed data type(s), default is ``(float, numpy.float32)``,
if **None** data type is not checked
:arg name: name of the coordinate argument
:raises: :exc:`TypeError` when *coords* is not an instance of
:class:`numpy.ndarray`
:raises: :exc:`ValueError` when wrong shape, dimensionality, or data type
is encountered"""
try:
ndim, shape = coords.ndim, coords.shape
except AttributeError:
raise TypeError('coords must be a numpy.ndarray instance')
ndims = CSETS_NDIMS if csets else COORDS_NDIM
if ndim not in ndims:
raise ValueError(str(name) + '.ndim must be ' +
' or '.join([str(d) for d in ndims]))
elif shape[-1] != 3:
raise ValueError(str(name) + '.shape[-1] must be 3')
elif natoms and shape[-2] != natoms:
raise ValueError(str(name) + '.shape[-2] must match number of atoms')
elif dtype:
if isinstance(dtype, type) and coords.dtype != dtype:
raise ValueError(str(name) + '.dtype must be ' + dtype.__name__)
elif coords.dtype not in dtype:
if len(dtype) > 1:
msg = ', '.join([repr(dt.__name__) for dt in dtype[:-1]]
) + ', or ' + repr(dtype[-1].__name__)
else:
msg = dtype[0].__name__
raise ValueError(str(name) + '.dtype must be ' + msg)
return True
NDIM12 = set([1, 2])
NDIM123 = set([1, 2, 3])
[docs]def checkWeights(weights, natoms, ncsets=None, dtype=float):
"""Returns *weights* if it has correct shape ([ncsets, ]natoms, 1).
after its shape and data type is corrected. otherwise raise an exception.
All items of *weights* must be greater than zero."""
try:
ndim, shape, wtype = weights.ndim, weights.shape, weights.dtype
except AttributeError:
raise TypeError('weights must be a numpy.ndarray instance')
if ncsets:
if ndim not in NDIM123:
raise ValueError('weights.dim must be 1, 2, or 3')
if ndim == 3:
if shape[0] != ncsets:
raise ValueError('weights.shape must be '
'(ncsets, natoms[, 1])')
if ndim < 3:
weights = tile(weights.reshape((1, natoms, 1)), (ncsets, 1, 1))
else:
if ndim not in NDIM12:
raise ValueError('weights.dim must be 1 or 2')
if shape[0] != natoms:
raise ValueError('weights.shape must be (natoms[, 1])')
if ndim == 1:
weights = weights.reshape((natoms, 1))
if dtype:
if wtype != dtype:
try:
weights = weights.astype(dtype)
except ValueError:
raise ValueError('weights.astype({0}) failed, {0} type '
'could not be assigned'.format(str(dtype)))
if any(weights < 0):
raise ValueError('all weights must be greater or equal to 0')
return weights
[docs]def checkTypes(args, **types):
"""Returns **True** if types of all *args* match those given in *types*.
:raises: :exc:`TypeError` when type of an argument is not one of allowed
types
::
def incr(n, i):
'''Return sum of *n* and *i*.'''
checkTypes(locals(), n=(float, int), i=(float, int))
return n + i"""
for arg, allowed in types.items():
if arg in args and not isinstance(args[arg], types[arg]):
val = args[arg]
if isinstance(allowed, (list, tuple)):
if len(allowed) > 1:
tstr = ', '.join([repr(tp.__name__) for tp in allowed[:-1]]
) + ', or ' + repr(allowed[-1].__name__)
else:
tstr = repr(allowed[0].__name__)
else:
tstr = repr(allowed.__name__)
raise TypeError('{0} must be an instance of {1}, not {2}'
.format(repr(arg), tstr, repr(type(val).__name__)))
return True
