Apply the ufunc outer() function to all pairs of a One-Dimensional Arrays in Numpy

NumpyServer Side ProgrammingProgramming

We will apply the ufunc outer() function to all pairs of One-Dimensional arrays. 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-byelement 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

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 −

Create two 1D 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...\n", arr1)
print("\nArray 2...\n", arr2)

Get the type of the arrays −

print("\nOur Array 1 type...\n", arr1.dtype)
print("\nOur Array 2 type...\n", arr2.dtype)

Get the dimensions of the Arrays −

print("\nOur Array 1 Dimensions...\n",arr1.ndim)
print("\nOur Array 2 Dimensions...\n",arr2.ndim)

Get the shape of the Arrays −

print("\nOur Array 1 Shape...\n",arr1.shape)
print("\nOur Array 2 Shape...\n",arr2.shape)

Apply the ufunc outer() function to all pairs of 1D arrays −

res = np.multiply.outer(arr1, arr2)
print("\nResult...\n",res)
print("\nShape...\n",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 1D 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...\n", arr1)
print("\nArray 2...\n", arr2)

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

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

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

# Apply the ufunc outer() function to all pairs of 1D arrays
res = np.multiply.outer(arr1, arr2)
print("\nResult...\n",res)
print("\nShape...\n",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...
1

Our Array 2 Dimensions...
1

Our Array 1 Shape...
(8,)

Our Array 2 Shape...
(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...
(8, 5)
raja
Updated on 07-Feb-2022 09:53:04

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