def _divide_by_count(a, b, out=None):
"""
Compute a/b ignoring invalid results. If `a` is an array the division
is done in place. If `a` is a scalar, then its type is preserved in the
output. If out is None, then then a is used instead so that the
division is in place. Note that this is only called with `a` an inexact
type.
Parameters
----------
a : {ndarray, numpy scalar}
Numerator. Expected to be of inexact type but not checked.
b : {ndarray, numpy scalar}
Denominator.
out : ndarray, optional
Alternate output array in which to place the result. The default
is ``None``; if provided, it must have the same shape as the
expected output, but the type will be cast if necessary.
Returns
-------
ret : {ndarray, numpy scalar}
The return value is a/b. If `a` was an ndarray the division is done
in place. If `a` is a numpy scalar, the division preserves its type.
"""
with np.errstate(invalid='ignore'):
if isinstance(a, np.ndarray):
if out is None:
return np.divide(a, b, out=a, casting='unsafe')
else:
return np.divide(a, b, out=out, casting='unsafe')
else:
if out is None:
return a.dtype.type(a / b)
else:
# This is questionable, but currently a numpy scalar can
# be output to a zero dimensional array.
return np.divide(a, b, out=out, casting='unsafe')
评论列表
文章目录