Python program to check if two arrays are equal

There are several techniques that helps us to check whether the given arrays are equal or not. The comparison of an array will not depend on the indices of the elements, it will only compare whether that particular element in one array is present in the other array or not. Let us discuss few techniques that compares two arrays and checks whether they are equal or not.

There are several techniques that helps us to check whether the given arrays are equal or not. The comparison of an array will not depend on the indices of the elements, it will only compare whether that particular element in one array is present in the other array or not. Let us discuss few techniques that compares two arrays and checks whether they are equal or not.

Input Output Scenarios

考虑下面给出的两个数组 -

arr1 = [1, 3, 5, 7, 9, 2, 4, 6, 8, 10]
arr2 = [3, 5, 4, 7, 1, 2, 6, 9, 8, 10]

现在，让我们检查和验证arr1的每个元素是否都存在于arr2中。

• arr1的第一个元素是1（检查1是否存在于arr2中）。

• The element 1 is present in arr2 also. So, move to the next element in arr1.

• 第二个元素是3。该元素也存在于第二个数组中。

• 所以，移动到下一个元素 5。元素 5 也存在于 arr2 中。移动到 arr1 中的下一个元素，即 7。

• 7也出现在arr2的第4个位置。继续下一个元素9。元素9也出现在arr2中。

同样地，检查arr1中的所有元素是否存在于arr2中。如果第一个数组中的元素存在于第二个数组中，并且arr2中没有其他元素存在，则我们可以得出结论，给定的两个数组是相等的。

注意 - 数组的相等性不是根据数组特定索引处存在的元素，而是元素的存在是强制性的。

Using Numpy Module

The all() method belongs to Numpy module. This method helps to check and verify whether the given arrays are equal or not. An operator that is used to check their equality is ==.

The all() method takes a single argument, which is the array to evaluate. If any element of the array evaluates as false, then the overall result will be false; otherwise, it will return true. We can use this with the operator "==" to compare two arrays and judge whether they are equal or not.

Example

的中文翻译为：

示例

In the following example, we are going to compare the given arrays and check their equality with the help of all() method and == operator. The steps described below must be followed in order to construct the desired program.

• Import the numpy module to access its methods and attributes.

• Declare two arrays to compare and check their equality.

• Convert those arrays into numpy arrays to perform numpy operations.

• Use equality operator, i.e., == along with the method all() in order to compare the arrays clearly.

import numpy as n
arr1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
arr2 = [11, 12, 13, 14, 15, 16, 17, 18, 19, 20]

narr1 = n.array([arr1])
narr2 = n.array([arr2])

result_variable = (narr1 == narr2).all()

if(result_variable == True):
   print(" Yes!! The given arrays are equal. ")

else:
   print(" The given arrays are not equal. ")

Output

The output of the above program is as follows −

The given arrays are not equal.

使用排序技术

Sorting Technique is used for checking whether the arrays are equal or not also. Initially, the given arrays can be sorted using a sorting technique. Afterwards, the elements in one array can be compared to those in the other by considering their respective indices since they are already in sorted order.

If the element at the first index in the first array is also at the first index in the second array, the element at the second index is taken. This process continues until the last index is reached.

Example

的中文翻译为：

示例

在下面的示例中，我们将通过对数组进行排序来比较给定的数组并检查它们的相等性。

def equality_check(arr1, arr2, size1, size2):
   if (size1 != size2):
      return False
   arr1.sort()
   arr2.sort()
   for i in range(0, size2):
      if (arr1[i] != arr2[i]):
         return False
   return True

if __name__ == "__main__":
   arr1 = [1, 2, 4, 5, 3]
   arr2 = [6, 9, 7, 10, 8] 
   n = len(arr1)
   m = len(arr2)
   if (equality_check(arr1, arr2, n, m)):
      print(" Yes!! The given arrays are equal. ")
   else:
      print(" The given arrays are not equal. ")

Output

The output of the above program is as follows −

The given arrays are not equal.

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