Public
Edited
May 14, 2024
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1 star
boole = {
let integral = 0;
const polys = [];
for (let i=0; i<curve.length-4*fineness-1; i+=4*fineness) {
integral += 2*fineness/45*(7*curve[i][1]+32*curve[i+fineness][1]+12*curve[i+2*fineness][1]+32*curve[i+3*fineness][1]+7*curve[i+4*fineness][1])/dpsPerUnit;
for (let j=curve[i][0]; j<curve[i+4*fineness][0]; j+=(curve[i+4*fineness][0]-curve[i][0])/300) {
polys.push({
x: j,
y: polynomial([curve[i], curve[i+fineness], curve[i+2*fineness], curve[i+3*fineness], curve[i+4*fineness]], j),
z: i
})
}
}
return [integral, polys]
}
simpson = {
let integral = 0;
const polys = [];
for(let i=0; i<curve.length-2*fineness-1; i+=2*fineness) {
integral += fineness/3*(curve[i][1]+4*curve[i+fineness][1]+curve[i+2*fineness][1])/dpsPerUnit;
for (let j=curve[i][0]; j<curve[i+2*fineness][0]; j+=(curve[i+2*fineness][0]-curve[i][0])/300) {
polys.push({
x: j,
y: polynomial([curve[i], curve[i+fineness], curve[i+2*fineness]], j),
z: i
})
}
}
return [integral, polys]
}
trapez = {
// calculate area of trapeze for the interval of h
let integral = 0;
const visualization = [];
let lastIndex = 0;
for (let i=0; i<curve.length-fineness-1; i+=fineness) {
lastIndex = i;
integral += 1/2*(curve[i][1]+curve[i+fineness][1])*fineness/dpsPerUnit
visualization.push({
x: curve[i][0],
y: curve[i][1],
z: 1
})
visualization.push({
x: curve[i+fineness][0],
y: curve[i+fineness][1],
z: 1
})
visualization.push({
x: curve[i][0],
y: 0,
z: i
})
visualization.push({
x: curve[i][0],
y: curve[i][1],
z: i
})
}
visualization.push({
x: curve[lastIndex+fineness][0],
y: 0,
z: lastIndex+fineness
})
visualization.push({
x: curve[lastIndex+fineness][0],
y: curve[lastIndex+fineness][1],
z: lastIndex+fineness
})
return [integral, visualization]
}
function computeValue(expression, x) {
let expr = expression.replace(/x/g, x.toString());
console.log(eval(expr))
// Evaluate the expression
let result = eval(expr);
return result;
}
import {polynomial} from "@maimp/lagrange-interpolation"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
