if is_obj_array(field):
ls = field.shape
else:
ls = ()
else:
ls = log_shape(field)
if ls != ():
from pytools import indices_in_shape
result = np.zeros(ls, dtype=object)
for i in indices_in_shape(ls):
result[i] = f(field[i])
return result
else:
return f(field)
as_oarray_func = decorator(with_object_array_or_scalar)
def with_object_array_or_scalar_n_args(f, *args):
oarray_arg_indices = []
for i, arg in enumerate(args):
if is_obj_array(arg):
oarray_arg_indices.append(i)
if not oarray_arg_indices:
return f(*args)
leading_oa_index = oarray_arg_indices[0]
ls = log_shape(args[leading_oa_index])
if ls != ():
ls = field.shape
else:
ls = ()
else:
ls = log_shape(field)
if ls != ():
from pytools import indices_in_shape
result = np.zeros(ls, dtype=object)
for i in indices_in_shape(ls):
result[i] = f(field[i])
return result
else:
return f(field)
as_oarray_func = decorator(with_object_array_or_scalar)
def with_object_array_or_scalar_n_args(f, *args):
oarray_arg_indices = []
for i, arg in enumerate(args):
if is_obj_array(arg):
oarray_arg_indices.append(i)
if not oarray_arg_indices:
return f(*args)
leading_oa_index = oarray_arg_indices[0]
ls = log_shape(args[leading_oa_index])
if ls != ():
.. note ::
This function exists because :func:`numpy.vectorize` suffers from the same
issue described under :func:`make_obj_array`.
"""
if isinstance(ary, np.ndarray) and ary.dtype.char == "O":
result = np.empty_like(ary)
for i in np.ndindex(ary.shape):
result[i] = f(ary[i])
return result
else:
return f(ary)
obj_array_vectorized = decorator(obj_array_vectorize)
def rec_obj_array_vectorize(f, ary):
"""Apply the function *f* to all entries of the object array *ary*.
Return an object array of the same shape consisting of the return
values.
If the elements of *ary* are further object arrays, recurse
until non-object-arrays are found and then apply *f* to those
entries.
If *ary* is not an object array, return ``f(ary)``.
.. note ::
This function exists because :func:`numpy.vectorize` suffers from the same
issue described under :func:`make_obj_array`.