Find Maximum Value in NumPy Array along an Axis

NumPy - Maximum value in array along an axis

You can find the maximum or largest value of a Numpy array, not only in the whole numpy array, but also along a specific axis or set of axes.

To get the maximum value of a NumPy Array along an axis, use numpy.amax() function.

Syntax

The syntax of numpy.amax() function is as follows:

max_value = numpy.amax(arr, axis)

If you do not provide any axis, the maximum of the entire array is returned. You can also specify an axis or axes along which to operate. If the axis is a tuple of integers representing the axes, then the maximum is selected over these specified multiple axes.

Examples

1. Maximum value along an axis

In this example, we will take a numpy array with random integers and then find the maximum of the array along an axis using numpy.amax() function. We shall find the maximum value along axis=0 and axis=1 separately.

Python Program

import numpy as np

# 2D array => 2 axes
arr = np.random.randint(10, size=(4,5))
print('array\n', arr)

#find maximum value along axis=0
amax_value = np.amax(arr, axis=0)
print('Maximum value of the array along axis=0')
print(amax_value)

#find maximum value along axis=1
amax_value = np.amax(arr, axis=1)
print('Maximum value of the array along axis=1')
print(amax_value)

Explanation:

  1. The np.random.randint() function generates a 4x5 matrix with random integers between 0 and 9.
  2. Using np.amax(arr, axis=0), the function finds the maximum value for each column (along the vertical axis).
  3. Using np.amax(arr, axis=1), the function finds the maximum value for each row (along the horizontal axis).
  4. The results are printed for both axis 0 and axis 1.

Output

array
 [[4 3 0 0 9]
 [7 5 7 0 5]
 [2 8 1 8 7]
 [3 8 5 0 2]]
Maximum value of the array along axis=0
[7 8 7 8 9]
Maximum value of the array along axis=1
[9 7 8 8]

2. Maximum value along multiple axes

As mentioned earlier, we can calculate the maximum value along multiple axes by providing a tuple of axes. In the example below, we will find the maximum value along both axis 0 and axis 2.

Python Program

import numpy as np

# 3D array => 3 axes
arr = np.random.randint(9, size=(2,2,4))
print(arr)

# find maximum value along axis=0,2
amax_value = np.amax(arr, axis=(0, 2))
print('Maximum value of the array along axis=(0,2)')
print(amax_value)

Explanation:

  1. The array is created using np.random.randint() to generate random integers between 0 and 8 in a 2x2x4 matrix.
  2. np.amax(arr, axis=(0, 2)) calculates the maximum values along both axis 0 (depth) and axis 2 (columns).
  3. The result is a 1D array showing the maximum value for each slice along the specified axes.

Output

array
 [[[4 3 6 5]
  [4 8 8 3]]

 [[5 3 1 2]
  [8 0 2 5]]]
Maximum value of the array along axis=(0,2)
[6 8]

3. Maximum Value in a 1D Array

We can also find the maximum value in a 1D array, where only the array itself is considered, and the concept of axis doesn't apply.

Python Program

import numpy as np

# 1D array
arr = np.random.randint(20, size=5)
print('array\n', arr)

# find maximum value in the 1D array
amax_value = np.amax(arr)
print('Maximum value of the array')
print(amax_value)

Explanation:

  1. The array is created using np.random.randint() to generate random integers between 0 and 19 in a 1D array.
  2. np.amax(arr) is used to find the maximum value in the entire array as no axis is provided.
  3. The result shows the maximum value present in the array.

Output

array
 [11  2  8 13  6]
Maximum value of the array
 13

Summary

In this Numpy Tutorial, we explored how to find the maximum value in a Numpy array along an axis or multiple axes using the numpy.amax() function. We covered several use cases with detailed explanations and examples, including working with 1D, 2D, and 3D arrays.

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