Given 2 arrays create a Cauchy matrix from it using numpy

This recipe helps you create a Cauchy matrix from the given 2 arrays using numpy

Recipe Objective

A Cauchy matrix is a matrix determined by two vectors. Given two vectors x and y, the Cauchy matrix C generated by them is defined as: C[i][j] := 1/(x[i] - y[j]). Now, we can use for loop to create it but let's look at an efficient way.

So this recipe is a short example on how to create a Cauchy matrix from two arrays. Let's get started.

Step 1 - Import the library

import numpy as np

Let's pause and look at these imports. Numpy is generally helpful in data manipulation while working with arrays. It also helps in performing mathematical operation.

Step 2 - Generating two arrays

x = np.array([1,2,3,4]) y = np.array([5,6,7])

Here, we have created two simple arrays.

Step 3 - Generating Cauchy matrix

c= 1.0 / (x.reshape((-1,1)) - y)

Now, using the formula, we have created a simple cauchy matrix.

Step 4 - Printing the nearest value

print(c)

Now, simply using print function, we have print our matrix.

Step 5 - Let's look at our dataset now

Once we run the above code snippet, we will see:

Scroll down the ipython file to visualize the output.

What Users are saying..

profile image

Savvy Sahai

Data Science Intern, Capgemini
linkedin profile url

As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of... Read More

Relevant Projects

Recommender System Machine Learning Project for Beginners-3
Content Based Recommender System Project - Building a Content-Based Product Recommender App with Streamlit

Build a Multi ClassText Classification Model using Naive Bayes
Implement the Naive Bayes Algorithm to build a multi class text classification model in Python.

Deep Learning Project for Beginners with Source Code Part 1
Learn to implement deep neural networks in Python .

Classification Projects on Machine Learning for Beginners - 1
Classification ML Project for Beginners - A Hands-On Approach to Implementing Different Types of Classification Algorithms in Machine Learning for Predictive Modelling

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.

NLP Project on LDA Topic Modelling Python using RACE Dataset
Use the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python.

Build Classification Algorithms for Digital Transformation[Banking]
Implement a machine learning approach using various classification techniques in Python to examine the digitalisation process of bank customers.

Learn How to Build a Linear Regression Model in PyTorch
In this Machine Learning Project, you will learn how to build a simple linear regression model in PyTorch to predict the number of days subscribed.

Deep Learning Project- Real-Time Fruit Detection using YOLOv4
In this deep learning project, you will learn to build an accurate, fast, and reliable real-time fruit detection system using the YOLOv4 object detection model for robotic harvesting platforms.

Build a Text Generator Model using Amazon SageMaker
In this Deep Learning Project, you will train a Text Generator Model on Amazon Reviews Dataset using LSTM Algorithm in PyTorch and deploy it on Amazon SageMaker.