# Processing Test 3 - Fourier Transformation Demo

## What is this?

This is a test page for checking out p5.js animation. This is the 5th javascript export version of processing programming language. Here, the fourier transformation of the boundary points of the eight note is taken and using the discrete fourier transformation of the $$x$$ and $$y$$ coordinates, a set of epicycles is used to recreate the figure.

## How is this done?

This is the image ### Step 1 : Extract the points using Python OpenCV

import cv2
import numpy as np

# make it grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Find Canny edges
edged = cv2.Canny(gray, 30, 200)

# Finding Contours
contours, hierarchy = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

# Remove extra array axes
new_contours = np.squeeze(contours)

# Extract the points
points = []
for point in new_contours:
temp = {'x': point, 'y': point}
points.append(temp)

# Print them for viewing
# print(points)

# Write the points as a javascript file.
file_path = "logo.js" ## your path variable
with open(file_path, 'w') as f:
f.write("%s\n" % 'let drawing = [')
for item in points:
f.write("%s,\n" % item)
f.write("%s\n" % '];')


The logo.js file will look like this:

let drawing = [
{'x': 197, 'y': 21},
{'x': 196, 'y': 22},
{'x': 195, 'y': 22},
{'x': 195, 'y': 23},
{'x': 195, 'y': 24},
{'x': 195, 'y': 25},
.....
{'x': 200, 'y': 21},
{'x': 199, 'y': 21},
{'x': 198, 'y': 21},
];


### Step 2 - Write the DFT function using p5.js

The Discrete Fourier Transform (DFT) of $$N$$ complex numbers $$\{x_n\} := x_0, x_1, \dots, x_{n-1}$$ is another sequence of $$N$$ complex numbers $$\{X_n\} := X_0, X_1, \dots, X_{n-1}$$ given by

\begin{align*} X_k &= \sum_{n=0}^{N-1}x_n.e^{-\frac{i2\pi}{N}kn}\\ &= \sum_{n=0}^{N-1}x_n.[cos(2\pi kn/N) - i.sin(2\pi kn/N)] \end{align*}

The equivalent source code is written in the file fourier.js.

function dft(x)
{

let X = [];
const N = x.length;

for (let k = 0; k < N; k++)
{
let re = 0;
let im = 0;
for (let n = 0; n < N; n++)
{
const phi = (TWO_PI * k * n) / N;
re += x[n] * cos(phi);
im -= x[n] * sin(phi);
}

re = re / N;
im = im / N;

let freq = k;
let amp = sqrt(re * re + im * im);
let phase = atan2(im, re);

X[k] = {re, im, freq, amp, phase};
}
return X;
}


### Step 3 - Write the main code

let x = [];
let y = [];
let fourierX = [];
let fourierY = [];
let time = 0;
let path = [];

function setup() {
createCanvas(800, 800);
const skip = 1;
for(let i = 0; i < drawing.length; i+= skip){
x[i] = drawing[i].x;
y[i] = drawing[i].y;
}

// for(let i = 0; i < 100; i+= skip){
//   x[i] = i;
//   y[i] = i;
// }

fourierX = dft(x);
fourierY = dft(y);

fourierX.sort((a, b) => b.amp - a.amp);
fourierY.sort((a, b) => b.amp - a.amp);
}

function epiCycle(x, y, rotation, fourier)
{
for (let i = 0; i < fourierY.length; i++)
{
let prev_x = x;
let prev_y = y;

let freq = fourier[i].freq;
let angle = rotation + freq * time + fourier[i].phase;

stroke(255, 100);
noFill();
stroke(255);
line(prev_x, prev_y, x, y);
}
return createVector(x, y);
}

function draw() {
background(0);

let vx = epiCycle(300, 50, 0, fourierX);
let vy = epiCycle(50, 200, HALF_PI, fourierY);
let v = createVector(vx.x, vy.y);

path.unshift(v);

// translate(200, 0);
line(vx.x, vx.y, v.x, v.y);
line(vy.x, vy.y, v.x, v.y);
beginShape();
noFill();
for (let i = 0; i < path.length; i++) {
vertex(path[i].x, path[i].y);
}
endShape();

const dt = TWO_PI / fourierY.length;
time += dt;

if (time > TWO_PI)
{
time = 0;
path.pop();
}
}


## Status

It works pretty slowly! The code is quite slow as it calculates more than 1700 components for $$x$$ coordinates and another 1700+ components for $$y$$ coordinates respectively.

## Acknowledgement

Special thanks to Daniel Shiffman for his phenomenal enthusiasm in getting me interested in p5.js. This code is a slightly tweaked version of the same code Daniel used to teach the tutorial in his YouTube Channel - The Coding Train and in his website - The Coding Train