/* * The MIT License * * Copyright (c) 2016-2021 JOML * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ package com.jozufozu.flywheel.repack.joml; /** * Computes the weighted average of multiple rotations represented as {@link Quaternionf} instances. *

* Instances of this class are not thread-safe. * * @author Kai Burjack */ public class QuaternionfInterpolator { /** * Performs singular value decomposition on {@link Matrix3f}. *

* This code was adapted from http://www.public.iastate.edu/. * * @author Kai Burjack */ private static class SvdDecomposition3f { private final float rv1[]; private final float w[]; private final float v[]; SvdDecomposition3f() { this.rv1 = new float[3]; this.w = new float[3]; this.v = new float[9]; } private float SIGN(float a, float b) { return ((b) >= 0.0 ? Math.abs(a) : -Math.abs(a)); } void svd(float[] a, int maxIterations, Matrix3f destU, Matrix3f destV) { int flag, i, its, j, jj, k, l = 0, nm = 0; float c, f, h, s, x, y, z; float anorm = 0.0f, g = 0.0f, scale = 0.0f; /* Householder reduction to bidiagonal form */ for (i = 0; i < 3; i++) { /* left-hand reduction */ l = i + 1; rv1[i] = scale * g; g = s = scale = 0.0f; for (k = i; k < 3; k++) scale += Math.abs(a[k + 3 * i]); if (scale != 0.0f) { 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((float) 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 = 0.0f, 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 = 0.0f; if (i < 3 && i != 3 - 1) { for (k = l; k < 3; k++) scale += Math.abs(a[i + 3 * k]); if (scale != 0.0f) { 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((float) 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 = 0.0f, 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 != 0.0f) { 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 = 0.0f, 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] = 0.0f; } v[i + 3 * i] = 1.0f; 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] = 0.0f; if (g != 0.0f) { g = 1.0f / g; if (i != 3 - 1) { for (j = l; j < 3; j++) { for (s = 0.0f, 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] = 0.0f; } ++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 = 0.0f; s = 1.0f; 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 = 1.0f / 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 < 0.0f) { /* 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)) / (2.0f * h * y); g = PYTHAG(f, 1.0f); f = ((x - z) * (x + z) + h * ((y / (f + SIGN(g, f))) - h)) / x; /* next QR transformation */ c = s = 1.0f; 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 != 0.0f) { z = 1.0f / 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] = 0.0f; rv1[k] = f; w[k] = x; } } destU.set(a); destV.set(v); } private static float PYTHAG(float a, float b) { float at = Math.abs(a), bt = Math.abs(b), ct, result; if (at > bt) { ct = bt / at; result = at * (float) Math.sqrt(1.0 + ct * ct); } else if (bt > 0.0f) { ct = at / bt; result = bt * (float) Math.sqrt(1.0 + ct * ct); } else result = 0.0f; return (result); } } private final SvdDecomposition3f svdDecomposition3f = new SvdDecomposition3f(); private final float[] m = new float[9]; private final Matrix3f u = new Matrix3f(); private final Matrix3f v = new Matrix3f(); /** * 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 Quaternionf computeWeightedAverage(Quaternionfc[] qs, float[] weights, int maxSvdIterations, Quaternionf dest) { float m00 = 0.0f, m01 = 0.0f, m02 = 0.0f; float m10 = 0.0f, m11 = 0.0f, m12 = 0.0f; float m20 = 0.0f, m21 = 0.0f, m22 = 0.0f; // Sum the rotation matrices of qs for (int i = 0; i < qs.length; i++) { Quaternionfc q = qs[i]; float dx = q.x() + q.x(); float dy = q.y() + q.y(); float dz = q.z() + q.z(); float q00 = dx * q.x(); float q11 = dy * q.y(); float q22 = dz * q.z(); float q01 = dx * q.y(); float q02 = dx * q.z(); float q03 = dx * q.w(); float q12 = dy * q.z(); float q13 = dy * q.w(); float q23 = dz * q.w(); m00 += weights[i] * (1.0f - q11 - q22); m01 += weights[i] * (q01 + q23); m02 += weights[i] * (q02 - q13); m10 += weights[i] * (q01 - q23); m11 += weights[i] * (1.0f - q22 - q00); m12 += weights[i] * (q12 + q03); m20 += weights[i] * (q02 + q13); m21 += weights[i] * (q12 - q03); m22 += weights[i] * (1.0f - 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' svdDecomposition3f.svd(m, maxSvdIterations, u, v); // Compute rotation matrix u.mul(v.transpose()); // Build quaternion from it return dest.setFromNormalized(u).normalize(); } }