Return True if all entries of two arrays are equal in Numpy


To return True if all entries of two arrays are equal, use the ma.allequal() method in Python Numpy. Returns True if the two arrays are equal within the given tolerance, False otherwise. If either array contains NaN, then False is returned.

The fill_value sets whether masked values in a or b are considered equal (True) or not (False). A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.

Steps

At first, import the required library −

import numpy as np

Create an array, 3x3 array with int elements using the numpy.arange() method −

arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1) print("
Array type...
", arr1.dtype)

Create masked array1 −

arr1 = ma.array(arr1)

Mask Array1 −

arr1[0, 1] = ma.masked
arr1[1, 1] = ma.masked

Display Masked Array 1 −

print("
Masked Array1...
",arr1)

Creating another array, a 3x3 array with int elements using the numpy.arange() method −

arr2 = np.arange(9).reshape((3,3))
print("
Array2...
", arr2) print("
Array type...
", arr2.dtype)

Create another masked array2 −

arr2 = ma.array(arr2)

Mask Array2 −

arr2[2, 1] = ma.masked
arr2[2, 2] = ma.masked

Display Masked Array 2 −

print("
Masked Array2...
",arr2)

To return True if all entries of two arrays are equal, use the ma.allequal() method in Python Numpy −

print("
Result...
",ma.allequal(arr1, arr2))

Example

import numpy as np
import numpy.ma as ma

# Array 1
# Creating a 3x3 array with int elements using the numpy.arange() method
arr1 = np.arange(9).reshape((3,3))
print("Array1...
", arr1) print("
Array type...
", arr1.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr1.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr1.shape) # Get the number of elements of the Array print("
Elements in the Array...
",arr1.size) # Create a masked array arr1 = ma.array(arr1) # Mask Array1 arr1[0, 1] = ma.masked arr1[1, 1] = ma.masked # Display Masked Array 1 print("
Masked Array1...
",arr1) # Array 2 # Creating another 3x3 array with int elements using the numpy.arange() method arr2 = np.arange(9).reshape((3,3)) print("
Array2...
", arr2) print("
Array type...
", arr2.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr2.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr2.shape) # Get the number of elements of the Array print("
Elements in the Array...
",arr2.size) # Create a masked array arr2 = ma.array(arr2) # Mask Array2 arr2[2, 1] = ma.masked arr2[2, 2] = ma.masked # Display Masked Array 2 print("
Masked Array2...
",arr2) # To Return True if all entries of two arrays are equal, use the ma.allequal() method in Python Numpy print("
Result...
",ma.allequal(arr1, arr2))

Output

Array1...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array1...
[[0 -- 2]
[3 -- 5]
[6 7 8]]

Array2...
[[0 1 2]
[3 4 5]
[6 7 8]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 3)

Elements in the Array...
9

Masked Array2...
[[0 1 2]
[3 4 5]
[6 -- --]]

Result...
True

Updated on: 22-Feb-2022

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