numpy.all
-
numpy.all(a, axis=None, out=None, keepdims=<no value>)
[source] -
Test whether all array elements along a given axis evaluate to True.
Parameters: -
a : array_like
-
Input array or object that can be converted to an array.
-
axis : None or int or tuple of ints, optional
-
Axis or axes along which a logical AND reduction is performed. The default (
axis
=None
) is to perform a logical AND over all the dimensions of the input array.axis
may be negative, in which case it counts from the last to the first axis.New in version 1.7.0.
If this is a tuple of ints, a reduction is performed on multiple axes, instead of a single axis or all the axes as before.
-
out : ndarray, optional
-
Alternate output array in which to place the result. It must have the same shape as the expected output and its type is preserved (e.g., if
dtype(out)
is float, the result will consist of 0.0’s and 1.0’s). Seedoc.ufuncs
(Section “Output arguments”) for more details. -
keepdims : bool, optional
-
If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
If the default value is passed, then
keepdims
will not be passed through to theall
method of sub-classes ofndarray
, however any non-default value will be. If the sub-class’ method does not implementkeepdims
any exceptions will be raised.
Returns: -
all : ndarray, bool
-
A new boolean or array is returned unless
out
is specified, in which case a reference toout
is returned.
See also
-
ndarray.all
- equivalent method
-
any
- Test whether any element along a given axis evaluates to True.
Notes
Not a Number (NaN), positive infinity and negative infinity evaluate to
True
because these are not equal to zero.Examples
>>> np.all([[True,False],[True,True]]) False
>>> np.all([[True,False],[True,True]], axis=0) array([ True, False])
>>> np.all([-1, 4, 5]) True
>>> np.all([1.0, np.nan]) True
>>> o=np.array(False) >>> z=np.all([-1, 4, 5], out=o) >>> id(z), id(o), z (28293632, 28293632, array(True)) # may vary
-
© 2005–2019 NumPy Developers
Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.all.html