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- numpy.logical_or
...NumPy reference Routines and objects by topic Logic functions numpy.logical_or...
- numpy.logical_or (Python data, in numpy.logical_or)
- NumPy 1.16.0 Release Notes
...tity which is used when .reduce is called on an empty axis. As of this release, the logical binary ufuncs, logical_and, logical_or, and logical_xor, now have identity s of type bool, where previously they were of type int. This restores the...
- NumPy 1.7.0 Release Notes
...lar axis chosen for concatenation. A bug was also fixed which silently allowed out of bounds axis arguments. The ufuncs logical_or, logical_and, and logical_not now follow Python’s behavior with object arrays, instead of trying to call meth...
- NumPy 1.8.0 Release Notes
...structions. Float32 and float64: base math (add, subtract, divide, multiply) sqrt minimum/maximum absolute Bool: logical_or logical_and logical_not This improves performance of these operations up to 4x/2x for float32/float64 an...
- NumPy 2.0.0 Release Notes
...a reduction which behaved like the Python or and and operators which evaluates to one of the arguments. You can use np.logical_or.reduce and np.logical_and.reduce to achieve the previous behavior. (gh-25712) np.can_cast cannot be called...
- NumPy for MATLAB users
...) L2 norm of vector v a & b logical_and(a,b) element-by-element AND operator (NumPy ufunc) See note LOGICOPS a | b np.logical_or(a,b) element-by-element OR operator (NumPy ufunc) See note LOGICOPS bitand(a,b) a & b bitwise AND operator (...
- numpy.any
...0: Before NumPy 2.0, any did not return booleans for object dtype input arrays. This behavior is still available via np.logical_or.reduce. Examples >>> import numpy as np >>> np.any([[True, False], [True, True]]) True >>> np.any([[True,...
- numpy.bitwise_or
...the ufunc docs. Returns: outndarray or scalarResult. This is a scalar if both x1 and x2 are scalars. See also logical_or bitwise_and bitwise_xor binary_reprReturn the binary representation of the input number as a string. Examp...
- numpy.logical_and
...s of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars. See also logical_or, logical_not, logical_xor bitwise_and Examples >>> import numpy as np >>> np.logical_and(True, False) False...
- numpy.logical_not
...e same shape as x of the NOT operation on elements of x. This is a scalar if x is a scalar. See also logical_and, logical_or, logical_xor Examples >>> import numpy as np >>> np.logical_not(3) False >>> np.logical_not([True, False, 0...
- numpy.logical_or
...NumPy reference Routines and objects by topic Logic functions numpy.logical_or...
- numpy.logical_xor
...2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars. See also logical_and, logical_or, logical_not, bitwise_xor Examples >>> import numpy as np >>> np.logical_xor(True, False) True >>> np.logic...
- numpy.ma.mask_or
...numpy.ma.mask_or ma.mask_or(m1, m2, copy=False, shrink=True)[source] Combine two masks with the logical_or operator. The result may be a view on m1 or m2 if the other is nomask (i.e. False). Parameters: m1, m2array...