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## NumPy np.gcd()

We all remember GCD or Greatest Common Divisor in Elementary Mathematics. However, in this tutorial, we will learn how to simplify the manual GCD calculation using a simple function in NumPy.

Let us take back our time.

## Function Syntax

GCD or Greatest Common Divisor is the greatest positive value that can divide two or more numbers.

The gcd function in NumPy has a syntax as shown:

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

Despite the crazy-looking syntax, you only need to worry about two parameters, as shown:

1. x1 and x2 – refer to the input arrays.

## Example #1

The code below shows using the gcd() function with two scalar values.

# import numpy
import numpy as np
print(f"gcd: {np.gcd(130, 13)}")

The above code should return the GCD of 130 and 13 as shown:

gcd: 13

## Example #2

To get the GCD of two arrays, we can do:

arr_1 = np.array([11,12,13])
arr_2 = np.array([14,145,15])
print(f"gcd: {np.gcd(arr_1, arr_2)}")

The code above should return:

gcd: [1 1 1]

## Example #3

You can also determine the GCD of an element of arrays and a scalar value. For example:

arr = np.array([14,145,15])
print(f"GCD: {np.gcd(arr, 5)}")

The example code above should return the GCD of the array, and 5.

GCD: [1 5 5]

## Closing

This tutorial walks through how to calculate the GCD of array elements along a given axis.