# numpy.array_equiv () in Python

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Consistent form means that either they have the same form, or one input array can be passed to create the same form as another.

Parameters:

`  arr1:  [array_like] Input array, we need to test.  arr2:  [array_like] Input array, we need to test. `

Return:

` True, if both arrays are equivalent; otherwise False `

Code: Explaining Operation

 ` # Python program explaining ` ` # array_equiv () function ` ` import ` ` numpy as np `   ` #input ` ` arr1 ` ` = ` ` np.arange (` ` 4 ` `) ` ` arr2 ` ` = ` ` [` ` 7 ` `, ` ` 4 ` `, ` ` 6 ` `, ` ` 7 ` `] ` ` print ` ` (` ` "arr1:" ` `, arr1) ` ` print ` ` (` ` "arr2:" ` `, arr2) `   ` print ` ` (` ` "Result:" ` `, np.array_equiv (arr1, arr2)) `   ` arr1 ` ` = ` ` np.arange (` ` 4 ` `) ` ` arr2 ` ` = ` ` np.arange (` ` 4 ` `) ` ` print ` ` (` ` "arr1:" ` `, arr1) ` ` print ` ` (` `" arr2: "` `, arr2) `   ` print ` ` (` ` "Result:" ` `, np.array_equiv (arr1, arr2)) `   ` arr1 ` ` = ` ` np.arange (` ` 4 ` `) ` ` arr2 ` ` = ` ` np.arange (` ` 5 ` `) ` ` print ` ` (` ` "arr1:" ` `, arr1) ` ` print ` ` (` ` "arr2:" ` `, arr2) ` < code class = "undefined spaces">   ` print ` ` (` `" Result: "` `, np.array_equiv (arr1, arr2)) ` ` `    ` a ` ` = ` ` np.array_equiv ([` ` 1 ` `, ` ` 2 ` `], [[` ` 1 ` `, ` ` 2 ` `, ` ` 1 ` `, ` ` 2 ` `], [` ` 1 ` `, ` ` 2 ` `, ` ` 1 ` `, ` ` 2 ` `]]) `    ` b ` ` = ` ` np.array_equiv ([` ` 1 ` `, ` ` 2 ` `], [[` ` 1 ` `, ` ` 2 ` `], [` ` 1 ` `, ` ` 2 ` `]]) `   ` print ` ` (` ` "a:" ` `, a) ` ` print ` ` (` ` "b:" ` `, b) `

Output:

` arr1: [0 1 2 3] arr2: [7, 4, 6, 7] Result: False arr1: [0 1 2 3] arr2: [0 1 2 3] Result: Tru e arr1: [0 1 2 3] arr2: [0 1 2 3 4] Result: False a: False b: True `

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