How to Find the Closest Value in a NumPy Array?

Finding Nearest Value in a Numpy Array

In numpy, finding the nearest value to a given target value can be achieved through a straightforward process. Let's define a function to accommodate this requirement:

import numpy as np

def find_nearest(array, value):
    array = np.asarray(array)
    idx = (np.abs(array - value)).argmin()
    return array[idx]

This function accepts an array and a target value. It converts the array to a numpy array and calculates the absolute differences between each element of the array and the target value. The index of the element with the smallest absolute difference is determined using argmin(). Finally, the element at that index is returned.

Example Usage:

Let's illustrate the usage of the find_nearest() function with an example:

array = np.random.random(10)
print(array)

print(find_nearest(array, value=0.5))

In this example, a random array of 10 elements is created. The find_nearest() function is then used to find the element in the array that is closest to 0.5. The output will be the nearest value in the array to 0.5.

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