  # numpy.fmin () in Python

NumPy | Python Methods and Functions

If one of the compared elements is NaN, then an element other than nan is returned. If both elements are NaN, then the first is returned.

Syntax: numpy.fmin (arr1, arr2, /, out = None, *, where = True, casting = `same_kind`, order = `K`, dtype = None, ufunc `fmin`)

Parameters:
arr1: [ array_like] The array holding the elements to be compared.
arr2: [array_like] The array holding the elements to be compared.
out: [ ndarray, optional] A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
** kwargs: Allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.
where: [array_like, optional] True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone.

Return: [ndarray or scalar] The minimum of arr1 and arr2, element-wise. Returns scalar if both arr1 and arr2 are scalars.

Code # 1: Work

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` # Python program explaining # fmin () function    import numpy as geek in_num1 = 10 in_num2 = 11   print ( "Input number1:" , in_num1) print ( "Input number2:"  , in_num2)    out_num = geek.fmin (in_num1, in_num2)  print ( "minimum of 10 and 11:" , out_num)  `

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Output:

` Input number1 : 10 Input number2: 11 minimum of 10 and 11:10 `

Code # 2:

 ` # Python program explaining ` ` # fmin () function `   ` import ` ` numpy as geek `   ` in_arr1 ` ` = ` ` [` ` 2 ` `, ` ` 8 ` `, ` ` 125 ` `, geek.nan] ` ` in_arr2 ` ` = ` ` [geek.nan, ` ` 3 ` `, ` ` 115 ` `, geek.nan] `   ` print ` ` (` ` "Input array1:" ` `, in_arr1) ` ` print ` ` (` ` "Input array2:" ` `, in_arr2) `   ` out_arr ` ` = ` ` geek.fmin (in_arr1, in_arr2) ` print ` (` ` "Output array:" ` ` , out_arr) `

Output:

` Input array1: [2, 8, 125, nan] Input array2: [nan, 3, 115, nan] Output array: [2. 3. 115. nan] `

Code # 3:

 ` # Python program explaining ` ` # fmin () function `   ` import ` ` numpy as geek `   ` in_arr1 ` ` = ` ` [` ` 2 ` `, ` ` 8 ` `, ` ` 1 25 ` `] ` ` in_arr2 ` ` = [ 3 , 3 , 115 ] ``     print ( "Input array1:" , in_arr1)  print ( "Input array2:" , in_arr2)   out_arr = geek.fmin (in_arr1, in_arr2)  print ( "Output array:"  , out_arr) `

Output:

``` Input array1: [2, 8, 125] Input array2: [3, 3, 115] Output array: [2 3 115]