- nlcpy.any(a, axis=None, out=None, keepdims=<no value>)
Tests whether any array elements along a given axis evaluate to True.
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 OR reduction is performed. The default (axis = None) is to perform a logical OR 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.
A new array is returned unless out is specified, in which case a reference to out is returned.
Tests whether all array element along a given axis evaluates to True.
Not a Number (NaN), positive infinity and negative infinity evaluate to True because these are not equal to zero.
>>> import nlcpy as vp >>> vp.any([[True, False], [True, True]]) array(True) >>> vp.any([[True,False],[False,False]], axis=0) array([ True, False]) >>> vp.any([-1, 0, 5]) array(True) >>> vp.any(vp.nan) array(True) >>> o=vp.array(False) >>> z=vp.any([-1, 4, 5], out=o) >>> z, o (array(True), array(True)) >>> z is o True >>> id(z), id(o) (140196865556152, 140196865556152) # may vary