org.joml.QuaterniondInterpolator Maven / Gradle / Ivy
/*
* The MIT License
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* Copyright (c) 2016-2019 JOML
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package org.joml;
/**
* Computes the weighted average of multiple rotations represented as {@link Quaterniond} instances.
*
* Instances of this class are not thread-safe.
*
* @author Kai Burjack
*/
public class QuaterniondInterpolator {
/**
* Performs singular value decomposition on {@link Matrix3d}.
*
* This code was adapted from http://www.public.iastate.edu/.
*
* @author Kai Burjack
*/
private static class SvdDecomposition3d {
private final double rv1[];
private final double w[];
private final double v[];
SvdDecomposition3d() {
this.rv1 = new double[3];
this.w = new double[3];
this.v = new double[9];
}
private double SIGN(double a, double b) {
return (b) >= 0.0 ? Math.abs(a) : -Math.abs(a);
}
void svd(double[] a, int maxIterations, Matrix3d destU, Matrix3d destV) {
int flag, i, its, j, jj, k, l = 0, nm = 0;
double c, f, h, s, x, y, z;
double anorm = 0.0, g = 0.0, scale = 0.0;
/* Householder reduction to bidiagonal form */
for (i = 0; i < 3; i++) {
/* left-hand reduction */
l = i + 1;
rv1[i] = scale * g;
g = s = scale = 0.0;
for (k = i; k < 3; k++)
scale += Math.abs(a[k + 3 * i]);
if (scale != 0.0) {
for (k = i; k < 3; k++) {
a[k + 3 * i] = (a[k + 3 * i] / scale);
s += (a[k + 3 * i] * a[k + 3 * i]);
}
f = a[i + 3 * i];
g = -SIGN(Math.sqrt(s), f);
h = f * g - s;
a[i + 3 * i] = f - g;
if (i != 3 - 1) {
for (j = l; j < 3; j++) {
for (s = 0.0, k = i; k < 3; k++)
s += a[k + 3 * i] * a[k + 3 * j];
f = s / h;
for (k = i; k < 3; k++)
a[k + 3 * j] += f * a[k + 3 * i];
}
}
for (k = i; k < 3; k++)
a[k + 3 * i] = a[k + 3 * i] * scale;
}
w[i] = (scale * g);
/* right-hand reduction */
g = s = scale = 0.0;
if (i < 3 && i != 3 - 1) {
for (k = l; k < 3; k++)
scale += Math.abs(a[i + 3 * k]);
if (scale != 0.0) {
for (k = l; k < 3; k++) {
a[i + 3 * k] = a[i + 3 * k] / scale;
s += a[i + 3 * k] * a[i + 3 * k];
}
f = a[i + 3 * l];
g = -SIGN(Math.sqrt(s), f);
h = f * g - s;
a[i + 3 * l] = f - g;
for (k = l; k < 3; k++)
rv1[k] = a[i + 3 * k] / h;
if (i != 3 - 1) {
for (j = l; j < 3; j++) {
for (s = 0.0, k = l; k < 3; k++)
s += a[j + 3 * k] * a[i + 3 * k];
for (k = l; k < 3; k++)
a[j + 3 * k] += s * rv1[k];
}
}
for (k = l; k < 3; k++)
a[i + 3 * k] = a[i + 3 * k] * scale;
}
}
anorm = Math.max(anorm, (Math.abs(w[i]) + Math.abs(rv1[i])));
}
/* accumulate the right-hand transformation */
for (i = 3 - 1; i >= 0; i--) {
if (i < 3 - 1) {
if (g != 0.0) {
for (j = l; j < 3; j++)
v[j + 3 * i] = (a[i + 3 * j] / a[i + 3 * l]) / g;
/* double division to avoid underflow */
for (j = l; j < 3; j++) {
for (s = 0.0, k = l; k < 3; k++)
s += a[i + 3 * k] * v[k + 3 * j];
for (k = l; k < 3; k++)
v[k + 3 * j] += s * v[k + 3 * i];
}
}
for (j = l; j < 3; j++)
v[i + 3 * j] = v[j + 3 * i] = 0.0;
}
v[i + 3 * i] = 1.0;
g = rv1[i];
l = i;
}
/* accumulate the left-hand transformation */
for (i = 3 - 1; i >= 0; i--) {
l = i + 1;
g = w[i];
if (i < 3 - 1)
for (j = l; j < 3; j++)
a[i + 3 * j] = 0.0;
if (g != 0.0) {
g = 1.0 / g;
if (i != 3 - 1) {
for (j = l; j < 3; j++) {
for (s = 0.0, k = l; k < 3; k++)
s += a[k + 3 * i] * a[k + 3 * j];
f = s / a[i + 3 * i] * g;
for (k = i; k < 3; k++)
a[k + 3 * j] += f * a[k + 3 * i];
}
}
for (j = i; j < 3; j++)
a[j + 3 * i] = a[j + 3 * i] * g;
} else {
for (j = i; j < 3; j++)
a[j + 3 * i] = 0.0;
}
++a[i + 3 * i];
}
/* diagonalize the bidiagonal form */
for (k = 3 - 1; k >= 0; k--) { /* loop over singular values */
for (its = 0; its < maxIterations; its++) { /* loop over allowed iterations */
flag = 1;
for (l = k; l >= 0; l--) { /* test for splitting */
nm = l - 1;
if (Math.abs(rv1[l]) + anorm == anorm) {
flag = 0;
break;
}
if (Math.abs(w[nm]) + anorm == anorm)
break;
}
if (flag != 0) {
c = 0.0;
s = 1.0;
for (i = l; i <= k; i++) {
f = s * rv1[i];
if (Math.abs(f) + anorm != anorm) {
g = w[i];
h = PYTHAG(f, g);
w[i] = h;
h = 1.0 / h;
c = g * h;
s = (-f * h);
for (j = 0; j < 3; j++) {
y = a[j + 3 * nm];
z = a[j + 3 * i];
a[j + 3 * nm] = y * c + z * s;
a[j + 3 * i] = z * c - y * s;
}
}
}
}
z = w[k];
if (l == k) { /* convergence */
if (z < 0.0) { /* make singular value nonnegative */
w[k] = -z;
for (j = 0; j < 3; j++)
v[j + 3 * k] = (-v[j + 3 * k]);
}
break;
}
if (its == maxIterations - 1) {
throw new RuntimeException("No convergence after " + maxIterations + " iterations");
}
/* shift from bottom 2 x 2 minor */
x = w[l];
nm = k - 1;
y = w[nm];
g = rv1[nm];
h = rv1[k];
f = ((y - z) * (y + z) + (g - h) * (g + h)) / (2.0 * h * y);
g = PYTHAG(f, 1.0);
f = ((x - z) * (x + z) + h * ((y / (f + SIGN(g, f))) - h)) / x;
/* next QR transformation */
c = s = 1.0;
for (j = l; j <= nm; j++) {
i = j + 1;
g = rv1[i];
y = w[i];
h = s * g;
g = c * g;
z = PYTHAG(f, h);
rv1[j] = z;
c = f / z;
s = h / z;
f = x * c + g * s;
g = g * c - x * s;
h = y * s;
y = y * c;
for (jj = 0; jj < 3; jj++) {
x = v[jj + 3 * j];
z = v[jj + 3 * i];
v[jj + 3 * j] = x * c + z * s;
v[jj + 3 * i] = z * c - x * s;
}
z = PYTHAG(f, h);
w[j] = z;
if (z != 0.0) {
z = 1.0 / z;
c = f * z;
s = h * z;
}
f = (c * g) + (s * y);
x = (c * y) - (s * g);
for (jj = 0; jj < 3; jj++) {
y = a[jj + 3 * j];
z = a[jj + 3 * i];
a[jj + 3 * j] = y * c + z * s;
a[jj + 3 * i] = z * c - y * s;
}
}
rv1[l] = 0.0;
rv1[k] = f;
w[k] = x;
}
}
destU.set(a);
destV.set(v);
}
private static double PYTHAG(double a, double b) {
double at = Math.abs(a), bt = Math.abs(b), ct, result;
if (at > bt) {
ct = bt / at;
result = at * Math.sqrt(1.0 + ct * ct);
} else if (bt > 0.0) {
ct = at / bt;
result = bt * Math.sqrt(1.0 + ct * ct);
} else
result = 0.0;
return (result);
}
}
private final SvdDecomposition3d svdDecomposition3d = new SvdDecomposition3d();
private final double[] m = new double[9];
private final Matrix3d u = new Matrix3d();
private final Matrix3d v = new Matrix3d();
/**
* Compute the weighted average of all of the quaternions given in qs using the specified interpolation factors weights, and store the result in dest.
*
* @param qs
* the quaternions to interpolate over
* @param weights
* the weights of each individual quaternion in qs
* @param maxSvdIterations
* the maximum number of iterations in the Singular Value Decomposition step used by this method
* @param dest
* will hold the result
* @return dest
*/
public Quaterniond computeWeightedAverage(Quaterniond[] qs, double[] weights, int maxSvdIterations, Quaterniond dest) {
double m00 = 0.0, m01 = 0.0, m02 = 0.0;
double m10 = 0.0, m11 = 0.0, m12 = 0.0;
double m20 = 0.0, m21 = 0.0, m22 = 0.0;
// Sum the rotation matrices of qs
for (int i = 0; i < qs.length; i++) {
Quaterniond q = qs[i];
double dx = q.x + q.x;
double dy = q.y + q.y;
double dz = q.z + q.z;
double q00 = dx * q.x;
double q11 = dy * q.y;
double q22 = dz * q.z;
double q01 = dx * q.y;
double q02 = dx * q.z;
double q03 = dx * q.w;
double q12 = dy * q.z;
double q13 = dy * q.w;
double q23 = dz * q.w;
m00 += weights[i] * (1.0 - q11 - q22);
m01 += weights[i] * (q01 + q23);
m02 += weights[i] * (q02 - q13);
m10 += weights[i] * (q01 - q23);
m11 += weights[i] * (1.0 - q22 - q00);
m12 += weights[i] * (q12 + q03);
m20 += weights[i] * (q02 + q13);
m21 += weights[i] * (q12 - q03);
m22 += weights[i] * (1.0 - q11 - q00);
}
m[0] = m00;
m[1] = m01;
m[2] = m02;
m[3] = m10;
m[4] = m11;
m[5] = m12;
m[6] = m20;
m[7] = m21;
m[8] = m22;
// Compute the Singular Value Decomposition of 'm'
svdDecomposition3d.svd(m, maxSvdIterations, u, v);
// Compute rotation matrix
u.mul(v.transpose());
// Build quaternion from it
return dest.setFromNormalized(u).normalize();
}
}