Source code for prody.utilities.checkers

"""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