# Apply the ufunc outer() function to all pairs in Numpy

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Apply the ufunc outer() function to all pairs. The numpy.ufunc has functions that operate element by element on whole arrays. The ufuncs are written in C (for speed) and linked into Python with NumPy's ufunc facility. A universal function (or ufunc for short) is a function that operates on ndarrays in an element-by-element fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a "vectorized" wrapper for a function that takes a fixed number of specific inputs and produces a fixed number of specific outputs.

## Steps

At first, import the required library −

import numpy as np

Create two arrays −

arr1 = np.array([[5, 10, 15, 20], [25, 30, 35, 40]])
arr2 = np.array([[7, 14, 21, 28, 35]])

Display the arrays −

print("Array 1...", arr1)
print("Array 2...", arr2)

Get the type of the arrays −

print("Our Array 1 type...", arr1.dtype)
print("Our Array 2 type...", arr2.dtype)

Get the dimensions of the Arrays −

print("Our Array 1 Dimensions...",arr1.ndim)
print("Our Array 2 Dimensions...",arr2.ndim)

Get the shape of the Arrays −

print("Our Array 1 Shape...",arr1.shape)
print("Our Array 2 Shape...",arr2.shape)

Apply the ufunc outer() function to all pairs −

res = np.multiply.outer(arr1, arr2)
print("Result...",res)
print("Shape...",res.shape)

## Example

import numpy as np

# The numpy.ufunc has functions that operate element by element on whole arrays.
# ufuncs are written in C (for speed) and linked into Python with NumPy's ufunc facility

# Create two arrays
arr1 = np.array([[5, 10, 15, 20], [25, 30, 35, 40]])
arr2 = np.array([[7, 14, 21, 28, 35]])

# Display the arrays
print("Array 1...", arr1)
print("Array 2...", arr2)

# Get the type of the arrays
print("Our Array 1 type...", arr1.dtype)
print("Our Array 2 type...", arr2.dtype)

# Get the dimensions of the Arrays
print("Our Array 1 Dimensions...",arr1.ndim)
print("Our Array 2 Dimensions...",arr2.ndim)

# Get the shape of the Arrays
print("Our Array 1 Shape...",arr1.shape)
print("Our Array 2 Shape...",arr2.shape)

# Apply the ufunc outer() function to all pairs
res = np.multiply.outer(arr1, arr2)
print("Result...",res)
print("Shape...",res.shape)

## Output

Array 1...
[[ 5 10 15 20]
[25 30 35 40]]

Array 2...
[[ 7 14 21 28 35]]

Our Array 1 type...
int64

Our Array 2 type...
int64

Our Array 1 Dimensions...
2

Our Array 2 Dimensions...
2

Our Array 1 Shape...
(2, 4)

Our Array 2 Shape...
(1, 5)

Result...
[[[[ 35 70 105 140 175]]

[[ 70 140 210 280 350]]

[[ 105 210 315 420 525]]

[[ 140 280 420 560 700]]]

[[[ 175 350 525 700 875]]

[[ 210 420 630 840 1050]]

[[ 245 490 735 980 1225]]

[[ 280 560 840 1120 1400]]]]

Shape...
(2, 4, 1, 5)
Updated on 07-Feb-2022 09:50:07