Unravel the mysteries of nature while learning to code with JavaScript.

A revised JavaScript edition of 『Nature of Code』, which has inspired countless readers for over a decade.
Written by Daniel Shiffman of the "Coding Train" channel, this groundbreaking guide introduces both beginners and experienced programmers to the world where code meets playful creativity.
It gently unravels the mysteries of nature, such as vectors, Newton's laws of motion, and vibration, and even explores complex topics like evolution, genetic algorithms, neural networks, and machine learning.
You can experience the amazing pleasure of implementing your own physics engine and turning code into art.

It's Saturday morning.
After a refreshing jog, a delicious bowl of cereal, and a quiet moment at the computer with a cup of warm chamomile tea, I went for a walk.
Looking at the calendar, I saw that it was soon to be an old friend's birthday, so I decided to make a congratulatory card with p5.js.
How about a greeting card with flying confetti? I decided to create a greeting card where confetti of various shapes and movements explodes on the screen at once: purple, pink, star-shaped, square, fast-flying, slow-falling.
/ This is a particle system.
This is a particle system that handles particles called confetti.
We can redesign the Particle class to include variables that store color, shape, movement, etc.

--- p.185

All Flappy Bird games made so far have been controlled by clicking the mouse.
Now, let's make computers play games themselves and teach them how to do so through neuroevolution.
ml5.js has built-in neural evolution functionality, making it relatively easy to implement.
The first step is to implant a 'brain' in the bird so that it can decide for itself whether to flap its wings or not.

--- p.557

A good random number generator produces numbers that are unrelated and show no apparent pattern.
However, when programming natural, lifelike movements, a little randomness is enough.
Rather, completely uniform randomness can be unnatural.
The Perlin noise algorithm, created by Ken Perlin, was created with these aspects in mind.
This algorithm ensures that consecutive numbers have similar values.
This smooths out the transitions between numbers, giving them a more natural feel than if they were completely random.
That's why Perlin noise is often used to create natural patterns such as clouds, landscapes, and marble patterns.

--- p.21

The following diagram provides ideas that may be helpful when creating an ecosystem based on the contents of this book.
Watch how this picture evolves as you learn new concepts and techniques.
/ Since the main purpose of this book is to demonstrate algorithms and behavioral principles, most of the examples consist of simple shapes such as circles.
But you may have more creative ideas than this.
So, challenge yourself to design with the elements you draw.
If you're new to translating your designs into code, check out this guide by Jana Marsh, the book's illustrator.
This guide in the appendix teaches you how to draw with code.

--- p.32

Let's take another look at the code for the attract() method.
Do you see the division sign? Every time you perform a division operation, you should ask yourself, "What happens if the distance is very small, or (even worse!) zero?"
Dividing by zero is impossible, and dividing by a very small number like 0.0001 is essentially the same as multiplying by 10,000! This might not be a problem in the real-world gravity formula, but p5.js isn't the real world.
In p5.js, the mover can get too close to the attractor, and the force can become so strong that the mover flies off the screen.
/ Conversely, let's assume the mover is 500 pixels away from the attractor.
Since we square the distance, this is equivalent to dividing the force by 250,000.
Then the force may be so weak that it may seem almost ineffective.

--- p.106

Not as interesting as the Sierpinski triangle.
As mentioned earlier, most of the 256 basic rule sets don't produce very nice patterns.
But it's truly fascinating that even simple cells with just two states can create the amazing patterns we see in nature.
For example, the snail shell in Figure 7.18 has a shape similar to the pattern created by Wolfram's Rule 30.
This shows how useful cellular automata are for mimicking natural patterns and creating new ones.
/ So before we dive into the details of what different sets of rules produce, let's learn how to create and display a basic Wolfram cellular automata using p5.js.

--- p.369