What is numpy.minimum() in Python?
Python’s numpy.minimum() computes the element-wise minimum of an array. It compares two arrays and returns a new array containing the minimum values. The illustration below shows this functionality:
Syntax
numpy.minimum() is declared as follows:
numpy.minimum(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'minimum'>
In the syntax given 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
minimum()method is a universal function.
Parameters
The numpy.minimum() method takes the following compulsory parameters:
x1andx2[array-like] - arrays holding the values that need to be compared. If theshape the shape of an array is the number of elements in each dimension x1andx2is different, they must be broadcastable to a common shape for representing the output.
The numpy.minimum() 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. |
Return value
numpy.minimum() returns the minimum of x1 and x2 element-wise. The return type is ndarray or scalar depending on the input.
If one of the elements being compared is
NaN(Not a Number),NaNis returned.
If both elements being compared are
NaN(Not a Number), thenNANis returned.
Examples
The examples below show different ways in which numpy.minimum() is used in Python.
The following code example outputs the minimum of two numbers a and b:
import numpy as npa = 10b = 20print(np.minimum(a,b))
The example below outputs the result after comparing the arrays arr1 and arr2:
import numpy as nparr1 = np.array([1.5,3.5,4,np.nan])arr2 = np.array([np.nan,6.5,2,np.nan])print(np.minimum(arr1,arr2))
The example below shows the result of comparing the arrays arr3 and arr4:
import numpy as nparr3 = np.array([[1,2,3], [4,5,6]])arr4 = np.array([[3,0,1], [6,-5,4]])print(np.minimum(arr3,arr4))
