Mapping A Sphere To A Cube - math

There is a special way of mapping a cube to a sphere described here:
http://mathproofs.blogspot.com/2005/07/mapping-cube-to-sphere.html
It is not your basic "normalize the point and you're done" approach and gives a much more evenly spaced mapping.
I've tried to do the inverse of the mapping going from sphere coords to cube coords and have been unable to come up the working equations. It's a rather complex system of equations with lots of square roots.
Any math geniuses want to take a crack at it?
Here's the equations in c++ code:
sx = x * sqrtf(1.0f - y * y * 0.5f - z * z * 0.5f + y * y * z * z / 3.0f);
sy = y * sqrtf(1.0f - z * z * 0.5f - x * x * 0.5f + z * z * x * x / 3.0f);
sz = z * sqrtf(1.0f - x * x * 0.5f - y * y * 0.5f + x * x * y * y / 3.0f);
sx,sy,sz are the sphere coords and x,y,z are the cube coords.

I want to give gmatt credit for this because he's done a lot of the work. The only difference in our answers is the equation for x.
To do the inverse mapping from sphere to cube first determine the cube face the sphere point projects to. This step is simple - just find the component of the sphere vector with the greatest length like so:
// map the given unit sphere position to a unit cube position
void cubizePoint(Vector3& position) {
double x,y,z;
x = position.x;
y = position.y;
z = position.z;
double fx, fy, fz;
fx = fabsf(x);
fy = fabsf(y);
fz = fabsf(z);
if (fy >= fx && fy >= fz) {
if (y > 0) {
// top face
position.y = 1.0;
}
else {
// bottom face
position.y = -1.0;
}
}
else if (fx >= fy && fx >= fz) {
if (x > 0) {
// right face
position.x = 1.0;
}
else {
// left face
position.x = -1.0;
}
}
else {
if (z > 0) {
// front face
position.z = 1.0;
}
else {
// back face
position.z = -1.0;
}
}
}
For each face - take the remaining cube vector components denoted as s and t and solve for them using these equations, which are based on the remaining sphere vector components denoted as a and b:
s = sqrt(-sqrt((2 a^2-2 b^2-3)^2-24 a^2)+2 a^2-2 b^2+3)/sqrt(2)
t = sqrt(-sqrt((2 a^2-2 b^2-3)^2-24 a^2)-2 a^2+2 b^2+3)/sqrt(2)
You should see that the inner square root is used in both equations so only do that part once.
Here's the final function with the equations thrown in and checks for 0.0 and -0.0 and the code to properly set the sign of the cube component - it should be equal to the sign of the sphere component.
void cubizePoint2(Vector3& position)
{
double x,y,z;
x = position.x;
y = position.y;
z = position.z;
double fx, fy, fz;
fx = fabsf(x);
fy = fabsf(y);
fz = fabsf(z);
const double inverseSqrt2 = 0.70710676908493042;
if (fy >= fx && fy >= fz) {
double a2 = x * x * 2.0;
double b2 = z * z * 2.0;
double inner = -a2 + b2 -3;
double innersqrt = -sqrtf((inner * inner) - 12.0 * a2);
if(x == 0.0 || x == -0.0) {
position.x = 0.0;
}
else {
position.x = sqrtf(innersqrt + a2 - b2 + 3.0) * inverseSqrt2;
}
if(z == 0.0 || z == -0.0) {
position.z = 0.0;
}
else {
position.z = sqrtf(innersqrt - a2 + b2 + 3.0) * inverseSqrt2;
}
if(position.x > 1.0) position.x = 1.0;
if(position.z > 1.0) position.z = 1.0;
if(x < 0) position.x = -position.x;
if(z < 0) position.z = -position.z;
if (y > 0) {
// top face
position.y = 1.0;
}
else {
// bottom face
position.y = -1.0;
}
}
else if (fx >= fy && fx >= fz) {
double a2 = y * y * 2.0;
double b2 = z * z * 2.0;
double inner = -a2 + b2 -3;
double innersqrt = -sqrtf((inner * inner) - 12.0 * a2);
if(y == 0.0 || y == -0.0) {
position.y = 0.0;
}
else {
position.y = sqrtf(innersqrt + a2 - b2 + 3.0) * inverseSqrt2;
}
if(z == 0.0 || z == -0.0) {
position.z = 0.0;
}
else {
position.z = sqrtf(innersqrt - a2 + b2 + 3.0) * inverseSqrt2;
}
if(position.y > 1.0) position.y = 1.0;
if(position.z > 1.0) position.z = 1.0;
if(y < 0) position.y = -position.y;
if(z < 0) position.z = -position.z;
if (x > 0) {
// right face
position.x = 1.0;
}
else {
// left face
position.x = -1.0;
}
}
else {
double a2 = x * x * 2.0;
double b2 = y * y * 2.0;
double inner = -a2 + b2 -3;
double innersqrt = -sqrtf((inner * inner) - 12.0 * a2);
if(x == 0.0 || x == -0.0) {
position.x = 0.0;
}
else {
position.x = sqrtf(innersqrt + a2 - b2 + 3.0) * inverseSqrt2;
}
if(y == 0.0 || y == -0.0) {
position.y = 0.0;
}
else {
position.y = sqrtf(innersqrt - a2 + b2 + 3.0) * inverseSqrt2;
}
if(position.x > 1.0) position.x = 1.0;
if(position.y > 1.0) position.y = 1.0;
if(x < 0) position.x = -position.x;
if(y < 0) position.y = -position.y;
if (z > 0) {
// front face
position.z = 1.0;
}
else {
// back face
position.z = -1.0;
}
}
So, this solution isn't nearly as pretty as the cube to sphere mapping, but it gets the job done!
Any suggestions to improve the efficiency or read ability of the code above are appreciated!
--- edit ---
I should mention that I have tested this and so far in my tests the code appears correct with the results being accurate to at least the 7th decimal place. And that was from when I was using floats, it's probably more accurate now with doubles.
--- edit ---
Here's an optimized glsl fragment shader version by Daniel to show that it doesn't have to be such a big scary function. Daniel uses this to filter sampling on cube maps! Great idea!
const float isqrt2 = 0.70710676908493042;
vec3 cubify(const in vec3 s)
{
float xx2 = s.x * s.x * 2.0;
float yy2 = s.y * s.y * 2.0;
vec2 v = vec2(xx2 – yy2, yy2 – xx2);
float ii = v.y – 3.0;
ii *= ii;
float isqrt = -sqrt(ii – 12.0 * xx2) + 3.0;
v = sqrt(v + isqrt);
v *= isqrt2;
return sign(s) * vec3(v, 1.0);
}
vec3 sphere2cube(const in vec3 sphere)
{
vec3 f = abs(sphere);
bool a = f.y >= f.x && f.y >= f.z;
bool b = f.x >= f.z;
return a ? cubify(sphere.xzy).xzy : b ? cubify(sphere.yzx).zxy : cubify(sphere);
}

After some rearranging you can get the "nice" forms
(1) 1/2 z^2 = (alpha) / ( y^2 - x^2) + 1
(2) 1/2 y^2 = (beta) / ( z^2 - x^2) + 1
(3) 1/2 x^2 = (gamma) / ( y^2 - z^2) + 1
where alpha = sx^2-sy^2 , beta = sx^2 - sz^2 and gamma = sz^2 - sy^2. Verify this yourself.
Now I neither have the motivation nor the time but from this point on its pretty straightforward to solve:
Substitute (1) into (2). Rearrange (2) until you get a polynomial (root) equation of the form
(4) a(x) * y^4 + b(x) * y^2 + c(x) = 0
this can be solved using the quadratic formula for y^2. Note that a(x),b(x),c(x) are some functions of x. The quadratic formula yields 2 roots for (4) which you will have to keep in mind.
Using (1),(2),(4) figure out an expression for z^2 in terms of only x^2.
Using (3) write out a polynomial root equation of the form:
(5) a * x^4 + b * x^2 + c = 0
where a,b,c are not functions but constants. Solve this using the quadratic formula. In total you will have 2*2=4 possible solutions for x^2,y^2,z^2 pair meaning you will
have 4*2=8 total solutions for possible x,y,z pairs satisfying these equations. Check conditions on each x,y,z pair and (hopefully) eliminate all but one (otherwise an inverse mapping does not exist.)
Good luck.
PS. It very well may be that the inverse mapping does not exist, think about the geometry: the sphere has surface area 4*pi*r^2 while the cube has surface area 6*d^2=6*(2r)^2=24r^2 so intuitively you have many more points on the cube that get mapped to the sphere. This means a many to one mapping, and any such mapping is not injective and hence is not bijective (i.e. the mapping has no inverse.) Sorry but I think you are out of luck.
----- edit --------------
if you follow the advice from MO, setting z=1 means you are looking at the solid square in the plane z=1.
Use your first two equations to solve for x,y, wolfram alpha gives the result:
x = (sqrt(6) s^2 sqrt(1/2 (sqrt((2 s^2-2 t^2-3)^2-24 t^2)+2 s^2-2 t^2-3)+3)-sqrt(6) t^2 sqrt(1/2 (sqrt((2 s^2-2 t^2-3)^2-24 t^2)+2 s^2-2 t^2-3)+3)-sqrt(3/2) sqrt((2 s^2-2 t^2-3)^2-24 t^2) sqrt(1/2 (sqrt((2 s^2-2 t^2-3)^2-24 t^2)+2 s^2-2 t^2-3)+3)+3 sqrt(3/2) sqrt(1/2 (sqrt((2 s^2-2 t^2-3)^2-24 t^2)+2 s^2-2 t^2-3)+3))/(6 s)
and
y = sqrt(-sqrt((2 s^2-2 t^2-3)^2-24 t^2)-2 s^2+2 t^2+3)/sqrt(2)
where above I use s=sx and t=sy, and I will use u=sz. Then you can use the third equation you have for u=sz. That is lets say that you want to map the top part of the sphere to the cube. Then for any 0 <= s,t <= 1 (where s,t are in the sphere's coordinate frame ) then the tuple (s,t,u) maps to (x,y,1) (here x,y are in the cubes coordinate frame.) The only thing left is for you to figure out what u is. You can figure this out by using s,t to solve for x,y then using x,y to solve for u.
Note that this will only map the top part of the cube to only the top plane of the cube z=1. You will have to do this for all 6 sides (x=1, y=1, z=0 ... etc ). I suggest using wolfram alpha to solve the resulting equations you get for each sub-case, because they will be as ugly or uglier as those above.

This answer contains the cube2sphere and sphere2cube without the restriction of a = 1. So the cube has side 2a from -a to a and the radius of the sphere is a.
I know it's been 10 years since this question was asked. Nevertheless, I am giving the answer in case someone needs it. The implementation is in Python,
I am using (x, y, z) for the cube coordinates, (p, q, r) for the sphere coordinates and the relevant underscore variables (x_, y_, z_) meaning they have been produced by using the inverse function.
import math
from random import randint # for testing
def sign_aux(x):
return lambda y: math.copysign(x, y)
sign = sign_aux(1) # no built-in sign function in python, I know...
def cube2sphere(x, y, z):
if (all([x == 0, y == 0, z == 0])):
return 0, 0, 0
def aux(x, y_2, z_2, a, a_2):
return x * math.sqrt(a_2 - y_2/2 - z_2/2 + y_2*z_2/(3*a_2))/a
x_2 = x*x
y_2 = y*y
z_2 = z*z
a = max(abs(x), abs(y), abs(z))
a_2 = a*a
return aux(x, y_2, z_2, a, a_2), aux(y, x_2, z_2, a, a_2), aux(z, x_2, y_2, a, a_2)
def sphere2cube(p, q, r):
if (all([p == 0, q == 0, r == 0])):
return 0, 0, 0
def aux(s, t, radius):
A = 3*radius*radius
R = 2*(s*s - t*t)
S = math.sqrt( max(0, (A+R)*(A+R) - 8*A*s*s) ) # use max 0 for accuraccy error
iot = math.sqrt(2)/2
s_ = sign(s) * iot * math.sqrt(max(0, A + R - S)) # use max 0 for accuraccy error
t_ = sign(t) * iot * math.sqrt(max(0, A - R - S)) # use max 0 for accuraccy error
return s_, t_
norm_p, norm_q, norm_r = abs(p), abs(q), abs(r)
norm_max = max(norm_p, norm_q, norm_r)
radius = math.sqrt(p*p + q*q + r*r)
if (norm_max == norm_p):
y, z = aux(q, r, radius)
x = sign(p) * radius
return x, y, z
if (norm_max == norm_q):
z, x = aux(r, p, radius)
y = sign(q) * radius
return x, y, z
x, y = aux(p, q, radius)
z = sign(r) * radius
return x, y, z
# measuring accuracy
max_mse = 0
for i in range(100000):
x = randint(-20, 20)
y = randint(-20, 20)
z = randint(-20, 20)
p, q, r = cube2sphere(x, y, z)
x_, y_, z_ = sphere2cube(p, q, r)
max_mse = max(max_mse, math.sqrt(((x-x_)**2 + (y-y_)**2 + (z-z_)**2))/3)
print(max_mse)
# 1.1239159602905078e-07
max_mse = 0
for i in range(100000):
p = randint(-20, 20)
q = randint(-20, 20)
r = randint(-20, 20)
x, y, z = sphere2cube(p, q, r)
p_, q_, r_ = cube2sphere(x, y, z)
max_mse = max(max_mse, math.sqrt(((p-p_)**2 + (q-q_)**2 + (r-r_)**2))/3)
print(max_mse)
# 9.832883321715792e-08
Also, I mapped some points to check the function visually and these are the results.

Here's one way you can think about it: for a given point P in the sphere, take the segment that starts at the origin, passes through P, and ends at the surface of the cube. Let L be the length of this segment. Now all you need to do is multiply P by L; this is equivalent to mapping ||P|| from the interval [0, 1] to the interval [0, L]. This mapping should be one-to-one - every point in the sphere goes to a unique point in the cube (and points on the surface stay on the surface). Note that this is assuming a unit sphere and cube; the idea should hold elsewhere, you'll just have a few scale factors involved.
I've glossed over the hard part (finding the segment), but this is a standard raycasting problem. There are some links here that explain how to compute this for an arbitrary ray versus axis-aligned bounding box; you can probably simplify things since your ray starts at the origin and goes to the unit cube. If you need help simplify the equations, let me know and I'll take a stab at it.

It looks like there is a much cleaner solution if you're not afraid of trig and pi, not sure if it's faster/comparable though.
Just take the remaining components after determining the face and do:
u = asin ( x ) / half_pi
v = asin ( y ) / half_pi
This is an intuitive leap, but this seems to back it up ( though not exactly the same topic ), so please correct me if I'm wrong.
I'm too lazy to post an illustration that explains why. :D

Related

Why we use CORDIC gain?

I'm studying the cordic. And I found the cordic gain. K=0.607XXX.
From CORDIC, K_i = cos(tan^-1(2^i)).
As I know the K is approched 0.607xxx.when I is going to infinity
this value come up with from all K multiplying.
I understand the reason of exist each k. But I am curioused Where does it used ? Why we use that value K=0.607xx?
The scale factor for the rotation mode of the circular variant of CORDIC can easily be established from first principles. The idea behind CORDIC is to take a point on the unit circle and rotate it, in steps, through the angle u whose sine and cosine we want to determine.
To that end we define a set of incremental angles a0, ..., an-1, such that ak = atan(0.5k). We sum these incremental angles appropriately into a partial sum of angles sk, such than sn ~= u. Let yk = cos(sk) and xk = sin(sk). If in a given step k we rotate by ak, we have
yk+1 = cos (sk+1) = cos (sk + ak)
xk+1 = sin (sk+1) = sin (sk + ak)
we can compute xk+1 and yk+1 from xk and yk as follows:
yk+1 = yk * cos (ak) - xk * sin (ak)
xk+1 = xk * cos (ak) + yk * sin (ak)
Considering that we may both add and subtract ak, and that tan(ak) = sin(ak)/cos(ak), we get:
yk+1 = cos (ak) * (yk ∓ xk * tan(ak)) = cos (sk+1)
xk+1 = cos (ak) * (xk ± yk * tan(ak)) = sin (sk+1)
To simplify this computation, we can leave out the multiplication with cos(ak) in every step, which gives us our CORDIC iteration scheme:
yk+1 = y ∓ xk * tan(ak)
xk+1 = x ± yk * tan(ak)
Because of our choice of ak, the multiplications with tan(ak) turn into simple right shifts if we compute in fixed-point arithmetic. Because we left off the factors cos(ak), we wind up with
yn ~= cos(u) * (1 / (cos (a0) * cos (a1) * ... * cos (an))
xn ~= sin(u) * (1 / (cos (a0) * cos (a1) * ... * cos (an))
The factor f = cos (a0) * cos (a1) * ... * cos (an) is 0.607..., as already noted. We incorporate it into the computation by setting the starting values
y0 = f * cos(0) = f
x0 = f * sin(0) = 0
Here is C code that shows the entire computation in action, using 16-bit fixed-point arithmetic. Input angles are scaled such that 360 degrees correspond to 216, while sine and cosine outputs are scaled such that 1 corresponds to 215.
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
/* round (atand (0.5**i) * 65536/360) */
static const short a[15] =
{
0x2000, 0x12e4, 0x09fb, 0x0511,
0x028b, 0x0146, 0x00a3, 0x0051,
0x0029, 0x0014, 0x000a, 0x0005,
0x0003, 0x0001, 0x0001
};
#define swap(a,b){a=a^b; b=b^a; a=a^b;}
void cordic (unsigned short u, short *s, short *c)
{
short x, y, oldx, oldy, q;
int i;
x = 0;
y = 0x4dba; /* 0.60725 */
oldx = x;
oldy = y;
q = u >> 14; /* quadrant */
u = u & 0x3fff; /* reduced angle */
u = -(short)u;
i = 0;
do {
if ((short)u < 0) {
x = x + oldy;
y = y - oldx;
u = u + a[i];
} else {
x = x - oldy;
y = y + oldx;
u = u - a[i];
}
oldx = x;
oldy = y;
i++;
/* right shift of signed negative number implementation defined in C */
oldx = (oldx < 0) ? (-((-oldx) >> i)) : (oldx >> i);
oldy = (oldy < 0) ? (-((-oldy) >> i)) : (oldy >> i);
} while (i < 15);
for (i = 0; i < q; i++) {
swap (x, y);
y = -y;
}
*s = x;
*c = y;
}
int main (void)
{
float angle;
unsigned short u;
short s, c;
printf ("angle in degrees [0,360): ");
scanf ("%f", &angle);
u = (unsigned short)(angle * 65536.0f / 360.0f + 0.5f);
cordic (u, &s, &c);
printf ("sin = % f (ref: % f) cos = % f (ref: % f)\n",
s/32768.0f, sinf(angle/360*2*3.14159265f),
c/32768.0f, cosf(angle/360*2*3.14159265f));
return EXIT_SUCCESS;
}

how to detect point on/around a line (with some offset)

Drawn a line from a point A to point B. Let d be offset. Let C be point to be tested.
I am going to do a kind of hit testing around the line with offset.
How can i do the hit testing around the line with the given offset.
Ex: A = (10,10), B (30,30), offset = 2. choose C as any point. Please Refer the image in the link please.
http://s10.postimg.org/6by2dzvax/reference.png
Please help me.
Thanks in advance.
Find offset for C.
e.g. dx1 and dy1. If dy1/dx1=dy/dx then your C hits the line.
For segment you should also check if whether dx1 < dx or dy1 < dy.
In other words, you want to check if that point C is inside a certain rectangle, with dimensions 2*d and |A-B|+2*d. You need to represent the line as u*x+v*y+w=0, this can be accomplished by
u = A.y-B.y
v = B.x-A.x
w = A.x*B.y - A.y * B.x
Then the (signed) distance of C from that line would be
d = (u*C.x + v*C.y +w) / sqrt( u*u+v*v)
You compare abs(d) to your offset.
The next step would be to check the position of C in the direction of the line. To that end you consider the orthogonal line u2*x+v2*y+w2=0 with
u2 = v
v2 = -u
w2 = -u2*(A.x+B.x)/2 - v2*(A.y+B.y)/2
and the distance
d2 = (u2 * C.x + v2 * C.y + w2 ) / sqrt( u2*u2+v2*v2 )
This distance must be compared to something like the length of the line+offset:
abs(d2) < |A-B| / 2 + offset
A convenient trick is to rotate and translate the plane in such a way that the segment AB maps to the segment (0, 0)-(0, L) (just like on the image), L being the segment length.
If you apply the same transform to C, then it a very simple matter to test inclusion in the rectangle.
That useful transform is given by:
x = ((X - XA).(XB - XA) + (Y - YA).(YB - YA)) / L
y = ((X - XA).(YB - YA) - (Y - YA).(XB - XA)) / L
maybe you can use this function to count the shortest distance of the point to the line. If the distance is <= offset, then that point is hitting the line.
private double pointDistanceToLine(PointF line1, PointF line2, PointF pt)
{
var isValid = false;
PointF r = new PointF();
if (line1.Y == line2.Y && line1.X == line2.X)
line1.Y -= 0.00001f;
double U = ((pt.Y - line1.Y ) * (line2.Y - line1.Y )) + ((pt.X - line1.X) * (line2.X - line1.X));
double Udenom = Math.Pow(line2.Y - line1.Y , 2) + Math.Pow(line2.X - line1.X, 2);
U /= Udenom;
r.Y = (float)(line1.Y + (U * (line2.Y - line1.Y ))); r.X = (float)(line1.X + (U * (line2.X - line1.X)));
double minX, maxX, minY , maxY ;
minX = Math.Min(line1.Y , line2.Y );
maxX = Math.Max(line1.Y , line2.Y );
minY = Math.Min(line1.X, line2.X);
maxY = Math.Max(line1.X, line2.X);
isValid = (r.Y >= minX && r.Y <= maxX) && (r.X >= minY && r.X <= maxY );
//return isValid ? r : null;
if (isValid)
{
double result = Math.Pow((pt.X - r.X), 2) + Math.Pow((pt.Y - r.Y), 2);
result = Math.Sqrt(result);
return result;
}
else {
double result1 = Math.Pow((pt.X - line1.X), 2) + Math.Pow((pt.Y - line1.Y), 2);
result1 = Math.Sqrt(result1);
double result2 = Math.Pow((pt.X - line2.X), 2) + Math.Pow((pt.Y - line2.Y), 2);
result2 = Math.Sqrt(result2);
return Math.Min(result1, result2);
}
}

How can I generate a set of points evenly distributed along the perimeter of an ellipse?

If I want to generate a bunch of points distributed uniformly around a circle, I can do this (python):
r = 5 #radius
n = 20 #points to generate
circlePoints = [
(r * math.cos(theta), r * math.sin(theta))
for theta in (math.pi*2 * i/n for i in range(n))
]
However, the same logic doesn't generate uniform points on an ellipse: points on the "ends" are more closely spaced than points on the "sides".
r1 = 5
r2 = 10
n = 20 #points to generate
ellipsePoints = [
(r1 * math.cos(theta), r2 * math.sin(theta))
for theta in (math.pi*2 * i/n for i in range(n))
]
Is there an easy way to generate equally spaced points around an ellipse?
This is an old thread, but since I am seeking the same task of creating evenly spaced points along and ellipse and was not able to find an implementation, I offer this Java code that implements the pseudo code of Howard:
package com.math;
public class CalculatePoints {
public static void main(String[] args) {
// TODO Auto-generated method stub
/*
*
dp(t) = sqrt( (r1*sin(t))^2 + (r2*cos(t))^2)
circ = sum(dp(t), t=0..2*Pi step 0.0001)
n = 20
nextPoint = 0
run = 0.0
for t=0..2*Pi step 0.0001
if n*run/circ >= nextPoint then
set point (r1*cos(t), r2*sin(t))
nextPoint = nextPoint + 1
next
run = run + dp(t)
next
*/
double r1 = 20.0;
double r2 = 10.0;
double theta = 0.0;
double twoPi = Math.PI*2.0;
double deltaTheta = 0.0001;
double numIntegrals = Math.round(twoPi/deltaTheta);
double circ=0.0;
double dpt=0.0;
/* integrate over the elipse to get the circumference */
for( int i=0; i < numIntegrals; i++ ) {
theta += i*deltaTheta;
dpt = computeDpt( r1, r2, theta);
circ += dpt;
}
System.out.println( "circumference = " + circ );
int n=20;
int nextPoint = 0;
double run = 0.0;
theta = 0.0;
for( int i=0; i < numIntegrals; i++ ) {
theta += deltaTheta;
double subIntegral = n*run/circ;
if( (int) subIntegral >= nextPoint ) {
double x = r1 * Math.cos(theta);
double y = r2 * Math.sin(theta);
System.out.println( "x=" + Math.round(x) + ", y=" + Math.round(y));
nextPoint++;
}
run += computeDpt(r1, r2, theta);
}
}
static double computeDpt( double r1, double r2, double theta ) {
double dp=0.0;
double dpt_sin = Math.pow(r1*Math.sin(theta), 2.0);
double dpt_cos = Math.pow( r2*Math.cos(theta), 2.0);
dp = Math.sqrt(dpt_sin + dpt_cos);
return dp;
}
}
(UPDATED: to reflect new packaging).
An efficient solution of this problem for Python can be found in the numeric branch FlyingCircus-Numeric, derivated from the FlyingCircus Python package.
Disclaimer: I am the main author of them.
Briefly, the (simplified) code looks (where a is the minor axis, and b is the major axis):
import numpy as np
import scipy as sp
import scipy.optimize
def angles_in_ellipse(
num,
a,
b):
assert(num > 0)
assert(a < b)
angles = 2 * np.pi * np.arange(num) / num
if a != b:
e2 = (1.0 - a ** 2.0 / b ** 2.0)
tot_size = sp.special.ellipeinc(2.0 * np.pi, e2)
arc_size = tot_size / num
arcs = np.arange(num) * arc_size
res = sp.optimize.root(
lambda x: (sp.special.ellipeinc(x, e2) - arcs), angles)
angles = res.x
return angles
It makes use of scipy.special.ellipeinc() which provides the numerical integral along the perimeter of the ellipse, and scipy.optimize.root()
for solving the equal-arcs length equation for the angles.
To test that it is actually working:
a = 10
b = 20
n = 16
phi = angles_in_ellipse(n, a, b)
print(np.round(np.rad2deg(phi), 2))
# [ 0. 17.55 36.47 59.13 90. 120.87 143.53 162.45 180. 197.55
# 216.47 239.13 270. 300.87 323.53 342.45]
e = (1.0 - a ** 2.0 / b ** 2.0) ** 0.5
arcs = sp.special.ellipeinc(phi, e)
print(np.round(np.diff(arcs), 4))
# [0.3022 0.2982 0.2855 0.2455 0.2455 0.2855 0.2982 0.3022 0.3022 0.2982
# 0.2855 0.2455 0.2455 0.2855 0.2982]
# plotting
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca()
ax.axes.set_aspect('equal')
ax.scatter(b * np.sin(phi), a * np.cos(phi))
plt.show()
You have to calculate the perimeter, then divide it into equal length arcs. The length of an arc of an ellipse is an elliptic integral and cannot be written in closed form so you need numerical computation.
The article on ellipses on wolfram gives you the formula needed to do this, but this is going to be ugly.
A possible (numerical) calculation can look as follows:
dp(t) = sqrt( (r1*sin(t))^2 + (r2*cos(t))^2)
circ = sum(dp(t), t=0..2*Pi step 0.0001)
n = 20
nextPoint = 0
run = 0.0
for t=0..2*Pi step 0.0001
if n*run/circ >= nextPoint then
set point (r1*cos(t), r2*sin(t))
nextPoint = nextPoint + 1
next
run = run + dp(t)
next
This is a simple numerical integration scheme. If you need better accuracy you might also use any other integration method.
I'm sure this thread is long dead by now, but I just came across this issue and this was the closest that came to a solution.
I started with Dave's answer here, but I noticed that it wasn't really answering the poster's question. It wasn't dividing the ellipse equally by arc lengths, but by angle.
Anyway, I made some adjustments to his (awesome) work to get the ellipse to divide equally by arc length instead (written in C# this time). If you look at the code, you'll see some of the same stuff -
void main()
{
List<Point> pointsInEllipse = new List<Point>();
// Distance in radians between angles measured on the ellipse
double deltaAngle = 0.001;
double circumference = GetLengthOfEllipse(deltaAngle);
double arcLength = 0.1;
double angle = 0;
// Loop until we get all the points out of the ellipse
for (int numPoints = 0; numPoints < circumference / arcLength; numPoints++)
{
angle = GetAngleForArcLengthRecursively(0, arcLength, angle, deltaAngle);
double x = r1 * Math.Cos(angle);
double y = r2 * Math.Sin(angle);
pointsInEllipse.Add(new Point(x, y));
}
}
private double GetLengthOfEllipse()
{
// Distance in radians between angles
double deltaAngle = 0.001;
double numIntegrals = Math.Round(Math.PI * 2.0 / deltaAngle);
double radiusX = (rectangleRight - rectangleLeft) / 2;
double radiusY = (rectangleBottom - rectangleTop) / 2;
// integrate over the elipse to get the circumference
for (int i = 0; i < numIntegrals; i++)
{
length += ComputeArcOverAngle(radiusX, radiusY, i * deltaAngle, deltaAngle);
}
return length;
}
private double GetAngleForArcLengthRecursively(double currentArcPos, double goalArcPos, double angle, double angleSeg)
{
// Calculate arc length at new angle
double nextSegLength = ComputeArcOverAngle(majorRadius, minorRadius, angle + angleSeg, angleSeg);
// If we've overshot, reduce the delta angle and try again
if (currentArcPos + nextSegLength > goalArcPos) {
return GetAngleForArcLengthRecursively(currentArcPos, goalArcPos, angle, angleSeg / 2);
// We're below the our goal value but not in range (
} else if (currentArcPos + nextSegLength < goalArcPos - ((goalArcPos - currentArcPos) * ARC_ACCURACY)) {
return GetAngleForArcLengthRecursively(currentArcPos + nextSegLength, goalArcPos, angle + angleSeg, angleSeg);
// current arc length is in range (within error), so return the angle
} else
return angle;
}
private double ComputeArcOverAngle(double r1, double r2, double angle, double angleSeg)
{
double distance = 0.0;
double dpt_sin = Math.Pow(r1 * Math.Sin(angle), 2.0);
double dpt_cos = Math.Pow(r2 * Math.Cos(angle), 2.0);
distance = Math.Sqrt(dpt_sin + dpt_cos);
// Scale the value of distance
return distance * angleSeg;
}
From my answer in BSE here .
I add it in stackoverflow as it is a different approach which does not rely on a fixed iteration steps but rely on a convergence of the distances between the points, to the mean distance.
So the calculation is shorter as it depends only on the wanted vertices amount and on the precision to reach (about 6 iterations for less than 0.01%).
The principle is :
0/ First step : calculate the points normally using a * cos(t) and b * sin(t)
1/ Calculate the lengths between vertices
2/ Adjust the angles variations depending on the gap between each distance to the mean distance
3/ Reposition the points
4/ Exit when the wanted precision is reached or return to 1/
import bpy, bmesh
from math import radians, sqrt, cos, sin
rad90 = radians( 90.0 )
rad180 = radians( 180.0 )
def createVertex( bm, x, y ): #uses bmesh to create a vertex
return bm.verts.new( [x, y, 0] )
def listSum( list, index ): #helper to sum on a list
sum = 0
for i in list:
sum = sum + i[index]
return sum
def calcLength( points ): #calculate the lenghts for consecutives points
prevPoint = points[0]
for point in points :
dx = point[0] - prevPoint[0]
dy = point[1] - prevPoint[1]
dist = sqrt( dx * dx + dy *dy )
point[3] = dist
prevPoint = point
def calcPos( points, a, b ): #calculate the positions following the angles
angle = 0
for i in range( 1, len(points) - 1 ):
point = points[i]
angle += point[2]
point[0] = a * cos( angle )
point[1] = b * sin( angle )
def adjust( points ): #adjust the angle by comparing each length to the mean length
totalLength = listSum( points, 3 )
averageLength = totalLength / (len(points) - 1)
maxRatio = 0
for i in range( 1, len(points) ):
point = points[i]
ratio = (averageLength - point[3]) / averageLength
point[2] = (1.0 + ratio) * point[2]
absRatio = abs( ratio )
if absRatio > maxRatio:
maxRatio = absRatio
return maxRatio
def ellipse( bm, a, b, steps, limit ):
delta = rad90 / steps
angle = 0.0
points = [] #will be a list of [ [x, y, angle, length], ...]
for step in range( steps + 1 ) :
x = a * cos( angle )
y = b * sin( angle )
points.append( [x, y, delta, 0.0] )
angle += delta
print( 'start' )
doContinue = True
while doContinue:
calcLength( points )
maxRatio = adjust( points )
calcPos( points, a, b )
doContinue = maxRatio > limit
print( maxRatio )
verts = []
for point in points:
verts.append( createVertex( bm, point[0], point[1] ) )
for i in range( 1, len(verts) ):
bm.edges.new( [verts[i - 1], verts[i]] )
A = 4
B = 6
bm = bmesh.new()
ellipse( bm, A, B, 32, 0.00001 )
mesh = bpy.context.object.data
bm.to_mesh(mesh)
mesh.update()
Do take into consideration the formula for ellipse perimeter as under if the ellipse is squashed. (If the minor axis is three times as small as the major axis)
tot_size = np.pi*(3*(a+b) -np.sqrt((3*a+b)*a+3*b))
Ellipse Perimeter
There is working MATLAB code available here. I replicate that below in case that link ever goes dead. Credits are due to the original author.
This code assumes that the major axis is a line segment from (x1, y1) to (x2, y2) and e is the eccentricity of the ellipse.
a = 1/2*sqrt((x2-x1)^2+(y2-y1)^2);
b = a*sqrt(1-e^2);
t = linspace(0,2*pi, 20);
X = a*cos(t);
Y = b*sin(t);
w = atan2(y2-y1,x2-x1);
x = (x1+x2)/2 + X*cos(w) - Y*sin(w);
y = (y1+y2)/2 + X*sin(w) + Y*cos(w);
plot(x,y,'o')
axis equal

Intersection between a line and a sphere

I'm trying to find the point of intersection between a sphere and a line but honestly, I don't have any idea of how to do so.
Could anyone help me on this one ?
Express the line as an function of t:
{ x(t) = x0*(1-t) + t*x1
{ y(t) = y0*(1-t) + t*y1
{ z(t) = z0*(1-t) + t*z1
When t = 0, it will be at one end-point (x0,y0,z0). When t = 1, it will be at the other end-point (x1,y1,z1).
Write a formula for the distance to the center of the sphere (squared) in t (where (xc,yc,zc) is the center of the sphere):
f(t) = (x(t) - xc)^2 + (y(t) - yc)^2 + (z(t) - zc)^2
Solve for t when f(t) equals R^2 (R being the radius of the sphere):
(x(t) - xc)^2 + (y(t) - yc)^2 + (z(t) - zc)^2 = R^2
A = (x0-xc)^2 + (y0-yc)^2 + (z0-zc)^2 - R^2
B = (x1-xc)^2 + (y1-yc)^2 + (z1-zc)^2 - A - C - R^2
C = (x0-x1)^2 + (y0-y1)^2 + (z0-z1)^2
Solve A + B*t + C*t^2 = 0 for t. This is a normal quadratic equation.
You can get up to two solutions. Any solution where t lies between 0 and 1 are valid.
If you got a valid solution for t, plug it in the first equations to get the point of intersection.
I assumed you meant a line segment (two end-points). If you instead want a full line (infinite length), then you could pick two points along the line (not too close), and use them. Also let t be any real value, not just between 0 and 1.
Edit: I fixed the formula for B. I was mixing up the signs. Thanks M Katz, for mentioning that it didn't work.
I believe there is an inaccuracy in the solution by Markus Jarderot. Not sure what the problem is, but I'm pretty sure I translated it faithfully to code, and when I tried to find the intersection of a line segment known to cross into a sphere, I got a negative discriminant (no solutions).
I found this: http://www.codeproject.com/Articles/19799/Simple-Ray-Tracing-in-C-Part-II-Triangles-Intersec, which gives a similar but slightly different derivation.
I turned that into the following C# code and it works for me:
public static Point3D[] FindLineSphereIntersections( Point3D linePoint0, Point3D linePoint1, Point3D circleCenter, double circleRadius )
{
// http://www.codeproject.com/Articles/19799/Simple-Ray-Tracing-in-C-Part-II-Triangles-Intersec
double cx = circleCenter.X;
double cy = circleCenter.Y;
double cz = circleCenter.Z;
double px = linePoint0.X;
double py = linePoint0.Y;
double pz = linePoint0.Z;
double vx = linePoint1.X - px;
double vy = linePoint1.Y - py;
double vz = linePoint1.Z - pz;
double A = vx * vx + vy * vy + vz * vz;
double B = 2.0 * (px * vx + py * vy + pz * vz - vx * cx - vy * cy - vz * cz);
double C = px * px - 2 * px * cx + cx * cx + py * py - 2 * py * cy + cy * cy +
pz * pz - 2 * pz * cz + cz * cz - circleRadius * circleRadius;
// discriminant
double D = B * B - 4 * A * C;
if ( D < 0 )
{
return new Point3D[ 0 ];
}
double t1 = ( -B - Math.Sqrt ( D ) ) / ( 2.0 * A );
Point3D solution1 = new Point3D( linePoint0.X * ( 1 - t1 ) + t1 * linePoint1.X,
linePoint0.Y * ( 1 - t1 ) + t1 * linePoint1.Y,
linePoint0.Z * ( 1 - t1 ) + t1 * linePoint1.Z );
if ( D == 0 )
{
return new Point3D[] { solution1 };
}
double t2 = ( -B + Math.Sqrt( D ) ) / ( 2.0 * A );
Point3D solution2 = new Point3D( linePoint0.X * ( 1 - t2 ) + t2 * linePoint1.X,
linePoint0.Y * ( 1 - t2 ) + t2 * linePoint1.Y,
linePoint0.Z * ( 1 - t2 ) + t2 * linePoint1.Z );
// prefer a solution that's on the line segment itself
if ( Math.Abs( t1 - 0.5 ) < Math.Abs( t2 - 0.5 ) )
{
return new Point3D[] { solution1, solution2 };
}
return new Point3D[] { solution2, solution1 };
}
Don't have enough reputation to comment on M Katz answer, but his answer assumes that the line can go on infinitely in each direction. If you need only the line SEGMENT's intersection points, you need t1 and t2 to be less than one (based on the definition of a parameterized equation). Please see my answer in C# below:
public static Point3D[] FindLineSphereIntersections(Point3D linePoint0, Point3D linePoint1, Point3D circleCenter, double circleRadius)
{
double cx = circleCenter.X;
double cy = circleCenter.Y;
double cz = circleCenter.Z;
double px = linePoint0.X;
double py = linePoint0.Y;
double pz = linePoint0.Z;
double vx = linePoint1.X - px;
double vy = linePoint1.Y - py;
double vz = linePoint1.Z - pz;
double A = vx * vx + vy * vy + vz * vz;
double B = 2.0 * (px * vx + py * vy + pz * vz - vx * cx - vy * cy - vz * cz);
double C = px * px - 2 * px * cx + cx * cx + py * py - 2 * py * cy + cy * cy +
pz * pz - 2 * pz * cz + cz * cz - circleRadius * circleRadius;
// discriminant
double D = B * B - 4 * A * C;
double t1 = (-B - Math.Sqrt(D)) / (2.0 * A);
Point3D solution1 = new Point3D(linePoint0.X * (1 - t1) + t1 * linePoint1.X,
linePoint0.Y * (1 - t1) + t1 * linePoint1.Y,
linePoint0.Z * (1 - t1) + t1 * linePoint1.Z);
double t2 = (-B + Math.Sqrt(D)) / (2.0 * A);
Point3D solution2 = new Point3D(linePoint0.X * (1 - t2) + t2 * linePoint1.X,
linePoint0.Y * (1 - t2) + t2 * linePoint1.Y,
linePoint0.Z * (1 - t2) + t2 * linePoint1.Z);
if (D < 0 || t1 > 1 || t2 >1)
{
return new Point3D[0];
}
else if (D == 0)
{
return new [] { solution1 };
}
else
{
return new [] { solution1, solution2 };
}
}
You may use Wolfram Alpha to solve it in the coordinate system where the sphere is centered.
In this system, the equations are:
Sphere:
x^2 + y^2 + z^2 = r^2
Straight line:
x = x0 + Cos[x1] t
y = y0 + Cos[y1] t
z = z0 + Cos[z1] t
Then we ask Wolfram Alpha to solve for t: (Try it!)
and after that you may change again to your original coordinate system (a simple translation)
Find the solution of the two equations in (x,y,z) describing the line and the sphere.
There may be 0, 1 or 2 solutions.
0 implies they don't intersect
1 implies the line is a tangent to the sphere
2 implies the line passes through the sphere.
Here's a more concise formulation using inner products, less than 100 LOCs, and no external links. Also, the question was asked for a line, not a line segment.
Assume that the sphere is centered at C with radius r. The line is described by P+l*D where D*D=1. P and C are points, D is a vector, l is a number.
We set PC = P-C, pd = PC*D and s = pd*pd - PC*PC + r*r. If s < 0 there are no solutions, if s == 0 there is just one, otherwise there are two. For the solutions we set l = -pd +- sqrt(s), then plug into P+l*D.
Or you can just find the formula of both:
line: (x-x0)/a=(y-y0)/b=(z-z0)/c, which are symmetric equations of the line segment between the points you can find.
sphere: (x-xc)^2+(y-yc)^2+(z-zc)^2 = R^2.
Use the symmetric equation to find relationship between x and y, and x and z.
Then plug in y and z in terms of x into the equation of the sphere.
Then find x, and then you can find y and z.
If x gives you an imaginary result, that means the line and the sphere doesn't intersect.
I don't have the reputation to comment on Ashavsky's solution, but the check at the end needed a bit more tweaking.
if (D < 0)
return new Point3D[0];
else if ((t1 > 1 || t1 < 0) && (t2 > 1 || t2 < 0))
return new Point3D[0];
else if (!(t1 > 1 || t1 < 0) && (t2 > 1 || t2 < 0))
return new [] { solution1 };
else if ((t1 > 1 || t1 < 0) && !(t2 > 1 || t2 < 0))
return new [] { solution2 };
else if (D == 0)
return new [] { solution1 };
else
return new [] { solution1, solution2 };

extract rotation, scale values from 2d transformation matrix

how can i extract rotation, scale and translation values from 2d transformation matrix? i mean a have a 2d transformation
matrix = [1, 0, 0, 1, 0, 0]
matrix.rotate(45 / 180 * PI)
matrix.scale(3, 4)
matrix.translate(50, 100)
matrix.rotate(30 / 180 * PI)
matrix.scale(-2, 4)
now my matrix have values [a, b, c, d, tx, ty]
lets forget about the processes above and imagine that we have only the values a, b, c, d, tx, ty
how can i find total rotation and scale values via a, b, c, d, tx, ty
sorry for my english
Thanks your advance
EDIT
I think it should be an answer somewhere...
i just tried in Flash Builder (AS3) like this
var m:Matrix = new Matrix;
m.rotate(.25 * Math.PI);
m.scale(4, 5);
m.translate(100, 50);
m.rotate(.33 * Math.PI);
m.scale(-3, 2.5);
var shape:Shape = new Shape;
shape.transform.matrix = m;
trace(shape.x, shape.y, shape.scaleX, shape.scaleY, shape.rotation);
and the output is:
x = -23.6
y = 278.8
scaleX = 11.627334873920528
scaleY = -13.54222263865791
rotation = 65.56274134518259 (in degrees)
Not all values of a,b,c,d,tx,ty will yield a valid rotation sequence. I assume the above values are part of a 3x3 homogeneous rotation matrix in 2D
| a b tx |
A = | c d ty |
| 0 0 1 |
which transforms the coordinates [x, y, 1] into:
[x', y', 1] = A * |x|
|y|
|z|
Thus set the traslation into [dx, dy]=[tx, ty]
The scale is sx = sqrt(a² + c²) and sy = sqrt(b² + d²)
The rotation angle is t = atan(c/d) or t = atan(-b/a) as also they should be the same.
Otherwise you don't have a valid rotation matrix.
The above transformation is expanded to:
x' = tx + sx (x Cos θ - y Sin θ)
y' = ty + sy (x Sin θ + y Cos θ)
when the order is rotation, followed by scale and then translation.
I ran into this problem today and found the easiest solution to transform a point using the matrix. This way, you can extract the translation first, then rotation and scaling.
This only works if x and y are always scaled the same (uniform scaling).
Given your matrix m which has undergone a series of transforms,
var translate:Point;
var rotate:Number;
var scale:Number;
// extract translation
var p:Point = new Point();
translate = m.transformPoint(p);
m.translate( -translate.x, -translate.y);
// extract (uniform) scale
p.x = 1.0;
p.y = 0.0;
p = m.transformPoint(p);
scale = p.length;
// and rotation
rotate = Math.atan2(p.y, p.x);
There you go!
The term for this is matrix decomposition. Here is a solution that includes skew as described by Frédéric Wang.
function decompose_2d_matrix(mat) {
var a = mat[0];
var b = mat[1];
var c = mat[2];
var d = mat[3];
var e = mat[4];
var f = mat[5];
var delta = a * d - b * c;
let result = {
translation: [e, f],
rotation: 0,
scale: [0, 0],
skew: [0, 0],
};
// Apply the QR-like decomposition.
if (a != 0 || b != 0) {
var r = Math.sqrt(a * a + b * b);
result.rotation = b > 0 ? Math.acos(a / r) : -Math.acos(a / r);
result.scale = [r, delta / r];
result.skew = [Math.atan((a * c + b * d) / (r * r)), 0];
} else if (c != 0 || d != 0) {
var s = Math.sqrt(c * c + d * d);
result.rotation =
Math.PI / 2 - (d > 0 ? Math.acos(-c / s) : -Math.acos(c / s));
result.scale = [delta / s, s];
result.skew = [0, Math.atan((a * c + b * d) / (s * s))];
} else {
// a = b = c = d = 0
}
return result;
}
If in scaling you'd scaled by the same amount in x and in y, then the determinant of the matrix, i.e. ad-bc, which tells you the area multiplier would tell you the linear change of scale too - it would be the square root of the determinant. atan( b/a ) or better atan2( b,a ) would tell you the total angle you have rotated through.
However, as your scaling isn't uniform, there is usually not going to be a way to condense your series of rotations and scaling to a single rotation followed by a single non-uniform scaling in x and y.

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