The Least Common Multiple (LCM) is the smallest number that is the multiple of all the numbers in question. Python’s numpy.lcm() method allows us to calculate the LCM of numbers and arrays.
numpy.lcm() is declared as follows:
numpy.lcm(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'lcm'>
In the syntax above, x1 and x2 are non-optional parameters, and the rest are optional parameters.
A universal function (ufunc) is a function that operates on ndarrays in an element-by-element fashion.
The numpy.lcm() method takes the following compulsory parameters:
x1 and x2 [array-like, int] - array of integer values. If the x1 and x2 is different, they must be broadcastable to a common shape for representing the output.The numpy.lcm() method takes the following optional parameters:
Parameter | Description |
out | represents the location into which the output of the method is stored. |
where | True value indicates that a universal function should be calculated at this position. |
casting | controls the type of datacasting that should occur. The same_kind option indicates that safe casting or casting within the same kind should take place. |
order | controls the memory layout order of the output function. The option K means reading the elements in the order they occur in memory. |
dtype | represents the desired data type of the array. |
subok | decides if subclasses should be made or not. If True, subclasses will be passed through. |
numpy.lcm() returns the lowest common multiple of the absolute values of the input. The return type is either ndarray or scalar, depending on the input type.
The examples below show the different ways numpy.lcm() is used in Python.
The code below outputs the least common multiple of two numbers, 12 and 42. The result is shown below:
import numpy as npa = 12b = 42result = np.lcm(a,b)print(result)
To find the LCM of all values in a given array, the reduce() method is used. In the code below, the reduce method utilizes the lcm method on each array element and reduces the array by one dimension. The result is shown in the code snippet below:
import numpy as nparr = np.array([3,12,15])result = np.lcm.reduce(arr)print(result)
numpy.lcm() calculates the least common multiple of the elements in the same location of the two arrays and returns an array.
In the example below, the first element of arr1 is 12, and the first element of arr2 is 20. The LCM of 12 and 20 is 60. Hence, the result array has 60 as its first element. This is shown in the example here:
import numpy as nparr1 = np.array([12,8,4])arr2 = np.array([20,16,2])result = np.lcm(arr1,arr2)print(result)
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