Vectorized Matrix Manhattan Distance in NumPy

numpy 924

When working with matrices in NumPy, it is often necessary to calculate the Manhattan distance between two matrices. The Manhattan distance, also known as the L1 distance or city block distance, measures the sum of the absolute differences between corresponding elements of the matrices. In this blog post, we will explore different approaches to compute …

Read more

Numpy Covariance Matrix: numpy.cov

numpy 3305

What is the Covariance Matrix? In statistics, the covariance matrix is a square matrix that summarizes the covariance between multiple variables. It provides valuable information about the relationships and dependencies between variables in a dataset. The diagonal elements of the covariance matrix represent the variances of individual variables, while the off-diagonal elements represent the covariances …

Read more

How to Use numpy.correlate for Autocorrelation

numpy 1851

Autocorrelation is a fundamental concept in signal processing and time series analysis. It measures the similarity between a signal and a time-shifted version of itself. One way to calculate autocorrelation is by using the numpy.correlate function in Python. What is numpy.correlate? The numpy.correlate function performs the convolution of two arrays. In the context of autocorrelation, …

Read more