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What is the numpy.fmod() function in NumPy?

Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

Overview

The fmod() function in NumPy is used to return the remainder of the division of two input arrays (x1x2\frac{x1}{x2}), element-wise.

Syntax

numpy.fmod(x1, x2, /, out=None, *, where=True)
Syntax for the "fmod()" function

Parameter values

The fmod() function takes the following parameter values:

  • x1: This represents an input array of elements, which are the dividends. This is a required parameter value.
  • x2: This represents an array that contains the divisors. This is a required parameter value.
  • out: This represents the location where the result is stored. This is an optional parameter value. 
  • where: This is the condition over which the input is being broadcast. At a given location where this condition is True, the resulting array will be set to the ufunc result. Otherwise, the resulting array will retain its original value. This is an optional parameter value.
  • **kwargs: This represents the other keyword arguments. This is an optional parameter value.
  • Return value

    The fmod() function returns an array that contains the remainder of the division of the two given input arrays.

    Code example

    import numpy as np
    # creating input arrays
    x1 = np.array([1, 2, 3])
    x2 = np.array([1, 2, 2])
    # implementing the fmod() function
    myarray = np.fmod(x1, x2)
    print(x1)
    print(x2)
    print("The remainders values of the division are: ", myarray)
    Implementing the "fmod()" function in NumPy

    Code explanation

    • Line 1: We import the numpy module.
    • Line 4: We create the input arrays, x1 and x2, using the array() function.
    • Line 7: We implement the numpy.fmod() function on the input arrays. We assign the result to a variable called myarray.
    • Lines 9–10: We print the input arrays x1 and x2 to the console.
    • Line 11: We print the variable called myarray to the console.

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    Onyejiaku Theophilus Chidalu

    Grokking Modern System Design Interview for Engineers & Managers

    Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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