Python

In Python, the concept of Einstein summation helps us simplify the calculations of arrays. It provides a great help in solving matrices, particularly calculating their cross-product, dot product, sum of diagonals, etc. In this article, let us explore this concept and understand the numpy.einsum() function. Understanding Einstein Summation Einstein summation is something that helps us […]

Have you ever needed to find the distance between two points in space? In this guide, we will solve this problem using the NumPy hypot() function. By using hypot, we can accurately measure the straight-line distance between two points in space, typically known as the hypotenuse. Let us look at this function in detail. What

The gcd function in NumPy is used to calculate the greatest common divisor of numbers in arrays (GCD). It is used to facilitate fractions and solve many mathematical problems. Without this function, discovering the GCD would take longer and be more error-prone, particularly when dealing with large datasets. After reading this article, you will know

Phase wraparound is the instantaneous transition in phase values. This is as a result of converting the phase to fit within -π and π. In this case, when it passes above or below these limits, the phase wraps around to remain within them. To restore precision in signal processing, these jumps must be resolved. One

Hello Geeks! Welcome to another guide where we will explore an interesting mathematical concept: the logarithm of the sum of exponentials. Sounds new, right? You will be surprised to know that a separate function is dedicated to calculating it in NumPy, which is called logaddexp(). In this article, we will discuss everything from the basic

The numpy.gradient() function is a powerful tool for calculating the gradient of array inputs. The concept of the gradient is essential in fields like data analysis and scientific research, where it is used to create graphical representations of changes in large datasets. Let’s understand this concept before diving deep into the numpy.gradient function. Understanding the

Welcome back, readers! In our series on Python arithmetic operations, we bring you a new topic of remainder. The Numpy library provides us with a dedicated function to find the remainder in Python. We need to know this because the remainder helps us in tasks like checking divisibility, writing algorithms, distributing work equally among processors,

Welcome to the next chapter of our NumPy logarithmic series. I hope you’ve gone through the first one, i.e., Log10. Here we will discuss another important log function, which is log2. It helps us to calculate the logarithm base 2 of the input. We will delve into its concept, syntax, parameters, and real-life use cases,

Hello Coders! We are all aware of the power of the NumPy library. It is great for our mathematical calculations. One such mathematical calculation includes logarithmic computation, and yes, NumPy has a logarithm function that helps us perform such complex calculations. In this article, let’s learn about the log10 function, its format, parameters, and example

And we are back again with a new function to add to our logarithmic series. This time we will explore the log1p() function, which will return the natural log of the given value. We will see what the natural log is, why it is important to calculate, and how we can calculate it, every answer