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How Can I Perform Logical OR/AND Operations on Multiple NumPy Arrays?

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Release: 2024-11-27 17:52:11
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How Can I Perform Logical OR/AND Operations on Multiple NumPy Arrays?

Applying Numpy's Logical Operations to Multiple Arrays

In Numpy, logical_or can only compare two arrays. This begs the question: how to find the union of more than two arrays? The same question applies to logical_and and obtaining the intersection of multiple arrays.

Limitations of Numpy's Logical Functions

Numpy explicitly limits logical_or to two arguments: x1 and x2.

Chaining Logical Operations

Multiple calls to logical_or can be chained:

result: [ True, True, True, False]

Generalizing Chaining Using Numpy's Reduce

To generalize this chaining, NumPy provides the reduce function:

result: [ True, True, True, False]

This approach also works with multi-dimensional arrays:

result: [ True, True, True, False]

Python's Reduce

Python's functools.reduce can also be used:

result: [ True, True, True, False]

Numpy's Any Function

Numpy's any function can also be used, but requires an explicit axis argument:

result: [ True, True, True, False]

Logical AND (logical_and) and Other Operations

Similar methods apply to other logical operations, including logical_and. For instance, logical_xor does not have an equivalent to all or any.

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