numpy.equal() in Python
numpy.equal(arr1, arr2, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None, ufunc ‘not_equal’) : This logical function checks for arr1 == arr2 element-wise. Parameters :
arr1 : [array_like]Input array arr2 : [array_like]Input array out : [ndarray, optional]Output array with same dimensions as Input array, placed with result. **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 :
Returns arr1 == arr2 element-wise
Code 1 :
Python3
# Python Program illustrating # numpy.equal() method import numpy as geek a = geek.equal([ 1. , 2. ], [ 1. , 3. ]) print ("Check to be Equal : \n", a, "\n") b = geek.equal([ 1 , 2 ], [[ 1 , 3 ],[ 1 , 4 ]]) print ("Check to be Equal : \n", b, "\n") |
Output :
Check to be Equal : [ True False] Check to be Equal : [[ True False] [ True False]]
Code 2 : Comparing data-type using .equal() function
Python3
# Python Program illustrating # numpy.equal() method import numpy as geek # Here we will compare Complex values with int a = geek.array([ 0 + 1j , 2 ]) b = geek.array([ 1 , 2 ]) d = geek.equal(a, b) print ("Comparing complex with int using .equal() : ", d) |
Output :
Comparing complex with int using .equal() : [False True]
Code 3 :
Python3
# Python Program illustrating # numpy.not_equal() method import numpy as geek # Here we will compare Float with int values a = geek.array([ 1.1 , 1 ]) b = geek.array([ 1 , 2 ]) d = geek.not_equal(a, b) print ("\nComparing float with int using .not_equal() : ", d) |
Output :
Comparing float with int using .not_equal() : [ True True]
Time complexity :
equal has time complexity of O(N). Where k is the length of list which need to be added.
References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.equal.html .