How to Use the Numpy maximum() Function in Python

09/28/2021

Contents

In this article, you will learn how to use the Numpy maximum() function in Python.

Numpy maximum() Function

The NumPy maximum() function is used to compute the element-wise maximum of two arrays. The function returns a new array that contains the maximum value from each pair of corresponding elements in the input arrays.

Syntax

Here’s the syntax for the NumPy maximum() function:

numpy.maximum(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Parameters

  • x1and x2: The input arrays to be compared.
  • out: An optional output array in which to place the results. If not specified, a new array is created.
  • where: An optional Boolean array that specifies which elements to include in the computation.
  • casting: An optional string that specifies the typecasting rules to use when computing the result.
  • order: An optional string that specifies the memory layout of the output array.
  • dtype: An optional data type for the output array.
  • subok: An optional Boolean flag that specifies whether to return a subclass of the input arrays if possible.

Example

Here’s an example of how to use the NumPy maximum() function to compute the element-wise maximum of two arrays:

import numpy as np

x1 = np.array([1, 2, 3, 4])
x2 = np.array([3, 1, 4, 2])

result = np.maximum(x1, x2)

print(result)

Output:

[3 2 4 4]

In this example, the maximum value from each pair of corresponding elements in the input arrays x1 and x2 is computed and stored in the result array.

#Python