There are a number of applications that make use of circles, spheres, regular polygons and polyhedra. Most of them are in the area of computer graphics and most likely you are reading this because you'd like to know how are those objects generated in 3d modelling tools or perhaps in that awesome drawing library you are using.
Quick links to demos:
Overview:
Imagine an equilateral triangle. Do the same for a square. And again for a regular pentagon. Now imagine a regular hectogon (100sided polygon). Doesn't it look more like a circle? If you can't imagine it, worry not. Check out the polygons demo to see how it looks like. You just made an important observation – as n goes to infinity, nsided polygons converge into a circle. This basically means that we only need an algorithm to generate a regular polygon for every n, then use a large enough number of sides to simulate a circle. We can only simulate a circle since a circle is a continuous set of points thus it has infinitely many points and is not representable in a computer. The same rule applies to polyhedra and spheres (and as we'll see soon, applies to higher dimensions as well).
The 2d case
Firstly, we'll change our coordinate system. The Cartesian coordinate system you are accustomed to using is best used for describing lines and polygons (planes and polyhedra in 3d). For circles (spheres) a polar coordinate system is much better suited. If you have never used such a system check out this summary in Wikipedia. Every paragraph starting from the next will assume you know your polar system and how to convert between Cartesian and polar coordinates.
Moreover, we will only use radians. Take a look here if you need a reminder in degrees to radians conversion.
The 2d circle has the following equation in a polar system (actually that is true for any other number of dimensions as well):
where is the radius of circle.
Convert that to a Cartesian system and you get:
Now make a quick observation. The vertices on the circle all have the same radius (I don't say). To generate them we only need to change the angle ( ).
A second observation – a circle represents an angle with magnitude 2 * π radians. Therefore one can split it into n equal angles, each with magnitude . Generating those angles and the vertex coordinates in pseudocode goes like:
for (i = 0; i < n; i++) {
angle = i * 2 * Pi / n
nextVertex.X = radius * cos(angle)
nextVertex.Y = radius * sin(angle)
}
Aaand that it is. You now have an algorithm for generating a regular nsided polygon. Let n = 100 and you have yourself a circle.
Going 3d
In 3d the polar coordinate system becomes a spherical one. We now need 2 angles instead of one but everything else stays the same. The parametric equations of a sphere are:
Time for another observation. Take the ground (XZ) plane. Its intersection with the sphere will always be a circle (the intersection of any plane with a sphere is a circle). The points on that circle have their thus they are defined only by the radius of the sphere and just their first angle () .
Now take the YZ plane axis. Its intersection once again is a circle. Likewise, its points are defined by the sphere's radius and just their second angle ().
Therefore, to divide the sphere into equal volumes we need only split both circles into equal angles. But we already have an algorithm for doing that from the 2d case. It's easy to see that the code breaks down to this:
for (i = 0; i < n; i++) {
for (j = 0; j < n; j++) {
phi = i * 2 * Pi / n
theta = j * 2 * Pi / n
nextVertex.X = radius * cos(phi)
nextVertex.Y = radius * sin(phi) * cos(theta)
nextVertex.Z = radius * sin(phi) * sin(theta)
}
}
This way we generate an nsided polygon horizontally and vertically. Once again setting n to a big enough number causes the polyhedra to appear like a sphere.
What if you want vertical polygons to have different size that the horizontal polygons thus creating new polyhedra or increasing the sphere approximation in just one direction? Easy, just introduce an additional parameter m. Now generate an nsided polygon vertically and an msided one horizontally! Often n is called the number of width segments and m is known as the number of height segments. Finally, our polyhedra pseudo code looks like:
for (i = 0; i < widthSegments; i++) {
for (j = 0; j < heightSegments; j++) {
phi = i * 2 * Pi / widthSegments
theta = j * 2 * Pi / heightSegments
nextVertex.X = radius * cos(phi)
nextVertex.Y = radius * sin(phi) * cos(theta)
nextVertex.Z = radius * sin(phi) * sin(theta)
}
}
Set the number of width and height segments to a large number and enjoy the smoothie sphere.
The demo uses the awesome Three.js to visualize the above algorithm. The library is open – source and if you go check out the source code of its buildin sphere generator and strip out implementation details and the index buffer generation guess what's left:
for (y = 0; y <= heightSegments; y++) {
var verticesRow = [];
for (x = 0; x <= widthSegments; x++) {
var u = x / widthSegments;
var v = y / heightSegments;
var vertex = new THREE.Vector3();
vertex.x = radius * Math.cos(phiStart + u * phiLength) * Math.sin(thetaStart + v * thetaLength);
vertex.y = radius * Math.cos(thetaStart + v * thetaLength);
vertex.z = radius * Math.sin(phiStart + u * phiLength) * Math.sin(thetaStart + v * thetaLength);
this.vertices.push(vertex);
verticesRow.push(this.vertices.length  1);
}
vertices.push(verticesRow);
}
As you see, this is the same thing besides the fact that the coordinate system has been rotated 90 degrees around the z axis (the y and x axes have been swapped). This changes nothing since a sphere is a sphere however you rotate it.
Generalization to higher dimensions
We can go beyond our 3d vision and talk about 4d spheres. Moreover, we can talk about ndimensional spheres aka hyperspheres! Let's see how to generate those.
First off, some more observations.
 We already saw that an ndimensional polar system requires n – 1 angles and a radius.

Given what we know from the previous 2 algorithms (and of course given what Wikipedia says about hyperspheres) we can conclude that the parametric equations of an nsphere are:
(when reading the Wikipedia article, take note that an nsphere is defined as a ball in (n+1) dimensional space, while I define it as a ball in n dimensions to ease the reader)
The implementation is a bit trickier this time. We can't have a bunch of nested loops as we did in the previous cases since the number of loops varies depending on the dimensions. Instead, we'll generate all possible ndimensional tuples. In every tuple, the ith element will vary between 0 and the number of segments in that dimension. Given that we know the tuples, we can calculate the angles for each vertex as we did earlier – . Take a look at the tuple generation implementation in JS:
var segments = [5, 4];
var radius = 1;
// A generic function to copy the tuple
function copy(array) {
var newArray = [];
for (var i = 0; i < array.length; i++) {
newArray[i] = array[i];
}
return newArray;
}
// A function that computes the successor of a given tuple
function getNextTuple(lastGeneratedTuple) {
var newTuple = copy(lastGeneratedTuple)
for (i = segments.length  1; i >= 0; i) {
// Increment the last coordinate. If it overflows, continue incrementing the next coordinate, else we are done
newTuple[i]++;
if (newTuple[i] > segments[i]  1) {
newTuple[i] = 0;
}
else {
break;
}
}
return newTuple;
}
// A function that enumerates all possible tuples
function enumerateAllTuples() {
// The number of tuples is the product of all segments
var numberOfTuples = 1;
for (i = 0; i < segments.length; i++) {
numberOfTuples *= segments[i];
}
var allTuples = [],
zeroTuple = [];
for (var i = 0; i < segments.length; i++) {
zeroTuple[i] = 0;
}
allTuples[0] = zeroTuple;
for (i = 1; i < numberOfTuples; i++) {
allTuples[i] = getNextTuple(allTuples[i  1]);
}
return allTuples;
}
Moving on to the actual vertices. The algorithm to produce them is as follows:
 Generate all tuples whose ith coordinate is between 0 and segments[i].

For each tuple, build the vertex.
 Calculate the actual angles from the values in the tuple.

For each vertex coordinate:
 Set it to the radius.
 Multiply the coordinate by the sines of all angles with indices less than the index of the coordinate
 If it is that last coordinate, multiply it by sine of the last angle. Else, multiply it by the cosine of the angle with the same index as the coordinate.
 Some tuples produce the same vertex (for instance (0, 0, 1) and (0, 0, 2), use the formulae above to proof it). Check if the vertex has been generated and add it to the list only in case it isn't already there
The code awaits you below. You can test it here. The number of dimensions is limited to 12 since I didn't come up with a way to visualize more than that.
var epsilon = 0.000001;
// Function to test if the same vertex has already been produced
function isVertexGenerated(vertices, vertex) {
var found = false;
for (var i = 0; i < vertices.length; i++) {
var current = vertices[i];
for (var j = 0; j < vertex.length; j++) {
if (Math.abs(current[j]  vertex[j]) > epsilon) {
break;
}
}
if (j == vertex.length) {
found = true;
break;
}
}
return found;
}
function generatePoints() {
var allTuples = enumerateAllTuples();
var vertices = [];
for (var k = 0; k < allTuples.length; k++) {
var tuple = allTuples[k];
// Compute the angles using the known formula
var angles = [];
for (j = 0; j < segments.length; j++) {
angles[j] = tuple[j] * 2 * Math.PI / segments[j].value;
}
var nextVertex = [];
var dimensions = segments.length + 1; // The total number of dimensions is the number of angles + 1
// Go trough all coordinates of the vertex,
// starting from one instead of 0 to be consistent with the math equations
for (var i = 1; i < dimensions + 1; i++) {
nextVertex[i] = radius;
// Multiply by all sines with indices less than the index of the component
for (var j = 1; j < i; j++) {
nextVertex[i] *= Math.sin(angles[j  1]);
}
// If it is not the last component,
// multiply by the cosine of the angle with the same index
if (i != dimensions) {
nextVertex[i] *= Math.cos(angles[i  1]);
}
}
// Shift the array so we start from 0 instead of 1
nextVertex.shift();
// Check if already haven't generated the same vertex
var found = isVertexGenerated(nextVertex);
if (!found) {
vertices.push(nextVertex);
}
}
}
Summary
The last algorithm is the most general and produces the same values as the 2d and 3d cases but obviously is much slower. Currently, hyperspheres and polytopes have limited application outside modern physics (most notable example is string theory), but they certainly are an interesting topic. If you'd like to learn more about them Wikipedia has a good set of articles.
Hope you've enjoyed the reading, don't hesitate to ask questions and make suggestions for improvements.