nlcpy.all

nlcpy.all(a, axis=None, out=None, keepdims=<no value>)[source]

Tests whether all array elements along a given axis evaluate to True.

Parameters
aarray_like

Input array or object that can be converted to an array.

axisNone 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. If this is a tuple of ints, a reduction is performed on multiple axes.

outndarray, 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).

keepdimsbool, 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.

Returns
allndarray

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

See also

any

Tests whether any array element along a given axis evaluates to True.

Note

Not a Number (NaN), positive infinity and negative infinity evaluate to True because these are not equal to zero.

>>> import nlcpy as vp
>>> vp.all([[True, False], [True, True]])
array(False)
>>> vp.all([[True,False],[True,True]], axis=0)
array([ True, False])
>>> vp.all([-1, 4, 5])
array(True)
>>> vp.all([1.0, vp.nan])
array(True)
>>> o=vp.array(False)
>>> z=vp.all([-1, 4, 5], out=o)
>>> id(z), id(o), z   
(140052379774144, 140052379774144, array(True)) # may vary