Book Image

C++20 STL Cookbook

By : Bill Weinman
Book Image

C++20 STL Cookbook

By: Bill Weinman

Overview of this book

Fast, efficient, and flexible, the C++ programming language has come a long way and is used in every area of the industry to solve many problems. The latest version C++20 will see programmers change the way they code as it brings a whole array of features enabling the quick deployment of applications. This book will get you up and running with using the STL in the best way possible. Beginning with new language features in C++20, this book will help you understand the language's mechanics and library features and offer insights into how they work. Unlike other books, the C++20 STL Cookbook takes an implementation-specific, problem-solution approach that will help you overcome hurdles quickly. You'll learn core STL concepts, such as containers, algorithms, utility classes, lambda expressions, iterators, and more, while working on real-world recipes. This book is a reference guide for using the C++ STL with its latest capabilities and exploring the cutting-edge features in functional programming and lambda expressions. By the end of the book C++20 book, you'll be able to leverage the latest C++ features and save time and effort while solving tasks elegantly using the STL.
Table of Contents (13 chapters)

Calculate the error sum of two vectors

Given two similar vectors that differ only by quantization or resolution, we can use the inner_product() algorithm to calculate an error sum, defined as:

Figure 11.2 – Error sum definition

Where e is the error sum, the sum of the square of the difference between a series of points in two vectors.

We can use the inner_product() algorithm, from the <numeric> header, to calculate the error sum between two vectors.

How to do it…

In this recipe we define two vectors, each with a sine wave. One vector has values of type double and the other has type int. This gives us vectors that differ in quantization, because the int type cannot represent fractional values. We then use inner_product() to calculate the error sum between the two vectors:

  • In our main() function we define our vectors and a handy index variable:
    int main() {
        constexpr size_t vlen{ 100 };