def __array_wrap__(self, obj, context=None):
"""
Special hook for ufuncs.
Wraps the numpy array and sets the mask according to context.
"""
result = obj.view(type(self))
result._update_from(self)
if context is not None:
result._mask = result._mask.copy()
(func, args, _) = context
m = reduce(mask_or, [getmaskarray(arg) for arg in args])
# Get the domain mask
domain = ufunc_domain.get(func, None)
if domain is not None:
# Take the domain, and make sure it's a ndarray
if len(args) > 2:
with np.errstate(divide='ignore', invalid='ignore'):
d = filled(reduce(domain, args), True)
else:
with np.errstate(divide='ignore', invalid='ignore'):
d = filled(domain(*args), True)
if d.any():
# Fill the result where the domain is wrong
try:
# Binary domain: take the last value
fill_value = ufunc_fills[func][-1]
except TypeError:
# Unary domain: just use this one
fill_value = ufunc_fills[func]
except KeyError:
# Domain not recognized, use fill_value instead
fill_value = self.fill_value
result = result.copy()
np.copyto(result, fill_value, where=d)
# Update the mask
if m is nomask:
m = d
else:
# Don't modify inplace, we risk back-propagation
m = (m | d)
# Make sure the mask has the proper size
if result.shape == () and m:
return masked
else:
result._mask = m
result._sharedmask = False
return result
评论列表
文章目录
