# Return the outer product of two masked arrays with different shapes in Numpy

To return the outer product of two masked arrays with different shapes, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.

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 &mius;

import numpy as np

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

arr1 = np.arange(4).reshape((1, 2, 2))
print("Array1...", arr1)
print("Array type...", arr1.dtype)

arr1 = ma.array(arr1)

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

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


Create Array 2, a 2D array with int elements using the numpy.arange() method −

arr2 = np.arange(6).reshape((3,2))
print("Array2...", arr2)
print("Array type...", arr2.dtype)

arr2 = ma.array(arr2)

arr2[0, 1] = ma.masked

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


To return the outer product of two masked arrays with different shapes, use the ma.outer() method −

print("Result of outer product...",np.ma.outer(arr1, arr2))

## Example

import numpy as np
import numpy.ma as ma

# Array 1
# Creating a 3D array with int elements using the numpy.arange() method
arr1 = np.arange(4).reshape((1, 2, 2))
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)

arr1 = ma.array(arr1)

# Array 2
# Creating a 2D array with int elements using the numpy.arange() method
arr2 = np.arange(6).reshape((3,2))
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)

arr2 = ma.array(arr2)

# To return the outer product of two masked arrays with different shapes, use the ma.outer() method in Python Numpy
print("Result of outer product...",np.ma.outer(arr1, arr2))

## Output

Array1...
[[[0 1]
[2 3]]]

Array type...
int64

Array Dimensions...
3

Our Array Shape...
(1, 2, 2)

Elements in the Array...
4

[[[0 --]
[2 3]]]

Array2...
[[0 1]
[2 3]
[4 5]]

Array type...
int64

Array Dimensions...
2

Our Array Shape...
(3, 2)

Elements in the Array...
6

[0 -- 6 9 12 15]]