numpy.all

numpy.all(a, axis=None, out=None)

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 : int, optional

Axis along which a logical AND is performed. The default (axis = None) is to perform a logical AND over a flattened input array. axis may be negative, in which case it counts from the last to the first axis.

out : ndarray, optional

Alternative output array in which to place the result. It must have the same shape as the expected output and the type is preserved. See doc.ufuncs (Section “Output arguments”) for more details.

Returns:

all : ndarray, bool

A new boolean or array is returned unless out is specified, in which case a reference to out is returned.

See also

ndarray.all

equivalent method

any

Test whether any array 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], dtype=bool)

>>> 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], dtype=bool))