NumPy lcm() – LCM of Two Arrays Element-wise

NumPy lcm()

The numpy.lcm() function computes the lowest common multiple (LCM) of two input numbers or arrays element-wise. The function operates on the absolute values of the inputs.

Syntax

numpy.lcm(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True)

Parameters

Parameter	Type	Description
x1, x2	array_like, int	Input values or arrays. If x1.shape != x2.shape, they must be broadcastable to a common shape.
out	ndarray, None, or tuple of ndarray and None, optional	Optional output array to store the result. If None, a new array is created.
where	array_like, optional	Condition mask for selecting elements to compute. Elements where where=False retain their original value.
casting	str, optional	Defines the casting behavior when computing LCM.
order	str, optional	Memory layout order of the output array.
dtype	data-type, optional	Defines the data type of the output array.
subok	bool, optional	Determines if subclasses of ndarray are preserved in the output.

Return Value

Returns an array containing the LCM of the absolute values of the inputs. If both inputs are scalars, a scalar is returned.

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Examples

1. Finding LCM of Two Numbers

Computing the lowest common multiple of two integer values.

import numpy as np

# Define two numbers
num1 = 12
num2 = 18

# Compute LCM
result = np.lcm(num1, num2)

# Print the result
print("LCM of", num1, "and", num2, ":", result)

Output:

LCM of 12 and 18 : 36

2. Finding LCM for Arrays of Numbers

Computing LCM for element-wise pairs in two arrays.

import numpy as np

# Define two arrays
arr1 = np.array([4, 7, 12])
arr2 = np.array([5, 14, 18])

# Compute element-wise LCM
lcm_array = np.lcm(arr1, arr2)

# Print the results
print("Array 1:", arr1)
print("Array 2:", arr2)
print("LCM values:", lcm_array)

Output:

Array 1: [ 4  7 12]
Array 2: [ 5 14 18]
LCM values: [20 14 36]

3. Using the out Parameter

Using an output array to store the LCM results instead of creating a new array.

import numpy as np

# Define two arrays
arr1 = np.array([8, 15, 21])
arr2 = np.array([12, 20, 35])

# Create an output array
output_array = np.empty_like(arr1)

# Compute LCM and store result in output_array
np.lcm(arr1, arr2, out=output_array)

# Print the results
print("LCM stored in output array:", output_array)

Output:

LCM stored in output array: [24 60 105]

4. Using the where Parameter

Computing LCM only for selected elements using a condition.

import numpy as np

# Define two arrays
arr1 = np.array([6, 8, 10, 15])
arr2 = np.array([9, 12, 20, 25])

# Define a mask (compute LCM only where mask is True)
mask = np.array([True, False, True, False])

# Compute LCM where mask is True
result = np.lcm(arr1, arr2, where=mask)

# Print the results
print("LCM values with mask:", result)

Output:

LCM values with mask: [18  8 20 15]

The LCM is computed only for elements where mask=True. Other values remain unchanged.