def array_convert_function(sshape_one, sshape_two, variables):
""" Return a function defining the conversion process between two NumPy
arrays of different shapes """
if not isinstance(sshape_one, tuple): sshape_one = (sshape_one,)
if not isinstance(sshape_two, tuple): sshape_two = (sshape_two,)
s_one = flatten([eval_expr_names_and_nrs(d) if isinstance(d,str) else d
for d in sshape_one])
s_two = flatten([eval_expr_names_and_nrs(d) if isinstance(d,str) else d
for d in sshape_two])
if len(s_one) != len(s_two):
raise ValueError, ('Flattened shapes %s and %s '\
'do not have the same length. '
'Original shapes were %s and %s') % \
(s_one, s_two, sshape_one, sshape_two)
# Reason about the transpose
t_idx = tuple([s_one.index(v) for v in s_two])
# Figure out the actual numeric shape values to use
n_one = shape_from_str_tuple(s_one, variables)
n_two = [eval_expr(d,variables)
if isinstance(d,str) else d for d in sshape_two]
def f(ary): return np.reshape(ary, n_one).transpose(t_idx).reshape(n_two)
return f
def array_convert_function(sshape_one, sshape_two, variables):
""" Return a function defining the conversion process between two NumPy
arrays of different shapes """
if not isinstance(sshape_one, tuple): sshape_one = (sshape_one, )
if not isinstance(sshape_two, tuple): sshape_two = (sshape_two, )
s_one = flatten([
eval_expr_names_and_nrs(d) if isinstance(d, str) else d
for d in sshape_one
])
s_two = flatten([
eval_expr_names_and_nrs(d) if isinstance(d, str) else d
for d in sshape_two
])
if len(s_one) != len(s_two):
raise ValueError, ('Flattened shapes %s and %s '\
'do not have the same length. '
'Original shapes were %s and %s') % \
(s_one, s_two, sshape_one, sshape_two)
# Reason about the transpose
t_idx = tuple([s_one.index(v) for v in s_two])
# Figure out the actual numeric shape values to use
n_one = shape_from_str_tuple(s_one, variables)
n_two = [
eval_expr(d, variables) if isinstance(d, str) else d
for d in sshape_two
]
def f(ary):
return np.reshape(ary, n_one).transpose(t_idx).reshape(n_two)
return f
def shape_from_str_tuple(sshape, variables, ignore=None):
"""
Substitutes string values in the supplied shape parameter
with integer variables stored in a dictionary
Parameters
----------
sshape : tuple/string composed of integers and strings.
The strings should related to integral properties
registered with this Solver object
variables : dictionary
Keys with associated integer values. Used to replace
string values within the tuple
ignore : list
A list of tuple strings to ignore
>>> print self.shape_from_str_tuple((4,'na','ntime'),ignore=['ntime'])
(4, 3)
"""
if ignore is None: ignore = []
if not isinstance(sshape, tuple) and not isinstance(sshape, list):
raise TypeError, 'sshape argument must be a tuple or list'
if not isinstance(ignore, list):
raise TypeError, 'ignore argument must be a list'
return tuple([int(eval_expr(v,variables)) if isinstance(v,str) else int(v)
for v in sshape if v not in ignore])
def shape_from_str_tuple(sshape, variables, ignore=None):
"""
Substitutes string values in the supplied shape parameter
with integer variables stored in a dictionary
Parameters
----------
sshape : tuple/string composed of integers and strings.
The strings should related to integral properties
registered with this Solver object
variables : dictionary
Keys with associated integer values. Used to replace
string values within the tuple
ignore : list
A list of tuple strings to ignore
>>> print self.shape_from_str_tuple((4,'na','ntime'),ignore=['ntime'])
(4, 3)
"""
if ignore is None: ignore = []
if not isinstance(sshape, tuple) and not isinstance(sshape, list):
raise TypeError, 'sshape argument must be a tuple or list'
if not isinstance(ignore, list):
raise TypeError, 'ignore argument must be a list'
return tuple([
int(eval_expr(v, variables)) if isinstance(v, str) else int(v)
for v in sshape if v not in ignore
])
