/// @ref gtx_pca #ifndef GLM_HAS_CXX11_STL #include #else #include #endif namespace glm { template GLM_FUNC_QUALIFIER mat computeCovarianceMatrix(vec const* v, size_t n) { return computeCovarianceMatrix const*>(v, v + n); } template GLM_FUNC_QUALIFIER mat computeCovarianceMatrix(vec const* v, size_t n, vec const& c) { return computeCovarianceMatrix const*>(v, v + n, c); } template GLM_FUNC_QUALIFIER mat computeCovarianceMatrix(I const& b, I const& e) { glm::mat m(0); size_t cnt = 0; for(I i = b; i != e; i++) { vec const& v = *i; for(length_t x = 0; x < D; ++x) for(length_t y = 0; y < D; ++y) m[x][y] += static_cast(v[x] * v[y]); cnt++; } if(cnt > 0) m /= static_cast(cnt); return m; } template GLM_FUNC_QUALIFIER mat computeCovarianceMatrix(I const& b, I const& e, vec const& c) { glm::mat m(0); glm::vec v; size_t cnt = 0; for(I i = b; i != e; i++) { v = *i - c; for(length_t x = 0; x < D; ++x) for(length_t y = 0; y < D; ++y) m[x][y] += static_cast(v[x] * v[y]); cnt++; } if(cnt > 0) m /= static_cast(cnt); return m; } namespace _internal_ { template GLM_FUNC_QUALIFIER static T transferSign(T const& v, T const& s) { return ((s) >= 0 ? glm::abs(v) : -glm::abs(v)); } template GLM_FUNC_QUALIFIER static T pythag(T const& a, T const& b) { static const T epsilon = static_cast(0.0000001); T absa = glm::abs(a); T absb = glm::abs(b); if(absa > absb) { absb /= absa; absb *= absb; return absa * glm::sqrt(static_cast(1) + absb); } if(glm::equal(absb, 0, epsilon)) return static_cast(0); absa /= absb; absa *= absa; return absb * glm::sqrt(static_cast(1) + absa); } } template GLM_FUNC_QUALIFIER unsigned int findEigenvaluesSymReal ( mat const& covarMat, vec& outEigenvalues, mat& outEigenvectors ) { using _internal_::transferSign; using _internal_::pythag; T a[D * D]; // matrix -- input and workspace for algorithm (will be changed inplace) T d[D]; // diagonal elements T e[D]; // off-diagonal elements for(length_t r = 0; r < D; r++) for(length_t c = 0; c < D; c++) a[(r) * D + (c)] = covarMat[c][r]; // 1. Householder reduction. length_t l, k, j, i; T scale, hh, h, g, f; static const T epsilon = static_cast(0.0000001); for(i = D; i >= 2; i--) { l = i - 1; h = scale = 0; if(l > 1) { for(k = 1; k <= l; k++) { scale += glm::abs(a[(i - 1) * D + (k - 1)]); } if(glm::equal(scale, 0, epsilon)) { e[i - 1] = a[(i - 1) * D + (l - 1)]; } else { for(k = 1; k <= l; k++) { a[(i - 1) * D + (k - 1)] /= scale; h += a[(i - 1) * D + (k - 1)] * a[(i - 1) * D + (k - 1)]; } f = a[(i - 1) * D + (l - 1)]; g = ((f >= 0) ? -glm::sqrt(h) : glm::sqrt(h)); e[i - 1] = scale * g; h -= f * g; a[(i - 1) * D + (l - 1)] = f - g; f = 0; for(j = 1; j <= l; j++) { a[(j - 1) * D + (i - 1)] = a[(i - 1) * D + (j - 1)] / h; g = 0; for(k = 1; k <= j; k++) { g += a[(j - 1) * D + (k - 1)] * a[(i - 1) * D + (k - 1)]; } for(k = j + 1; k <= l; k++) { g += a[(k - 1) * D + (j - 1)] * a[(i - 1) * D + (k - 1)]; } e[j - 1] = g / h; f += e[j - 1] * a[(i - 1) * D + (j - 1)]; } hh = f / (h + h); for(j = 1; j <= l; j++) { f = a[(i - 1) * D + (j - 1)]; e[j - 1] = g = e[j - 1] - hh * f; for(k = 1; k <= j; k++) { a[(j - 1) * D + (k - 1)] -= (f * e[k - 1] + g * a[(i - 1) * D + (k - 1)]); } } } } else { e[i - 1] = a[(i - 1) * D + (l - 1)]; } d[i - 1] = h; } d[0] = 0; e[0] = 0; for(i = 1; i <= D; i++) { l = i - 1; if(!glm::equal(d[i - 1], 0, epsilon)) { for(j = 1; j <= l; j++) { g = 0; for(k = 1; k <= l; k++) { g += a[(i - 1) * D + (k - 1)] * a[(k - 1) * D + (j - 1)]; } for(k = 1; k <= l; k++) { a[(k - 1) * D + (j - 1)] -= g * a[(k - 1) * D + (i - 1)]; } } } d[i - 1] = a[(i - 1) * D + (i - 1)]; a[(i - 1) * D + (i - 1)] = 1; for(j = 1; j <= l; j++) { a[(j - 1) * D + (i - 1)] = a[(i - 1) * D + (j - 1)] = 0; } } // 2. Calculation of eigenvalues and eigenvectors (QL algorithm) length_t m, iter; T s, r, p, dd, c, b; const length_t MAX_ITER = 30; for(i = 2; i <= D; i++) { e[i - 2] = e[i - 1]; } e[D - 1] = 0; for(l = 1; l <= D; l++) { iter = 0; do { for(m = l; m <= D - 1; m++) { dd = glm::abs(d[m - 1]) + glm::abs(d[m - 1 + 1]); if(glm::equal(glm::abs(e[m - 1]) + dd, dd, epsilon)) break; } if(m != l) { if(iter++ == MAX_ITER) { return 0; // Too many iterations in FindEigenvalues } g = (d[l - 1 + 1] - d[l - 1]) / (2 * e[l - 1]); r = pythag(g, 1); g = d[m - 1] - d[l - 1] + e[l - 1] / (g + transferSign(r, g)); s = c = 1; p = 0; for(i = m - 1; i >= l; i--) { f = s * e[i - 1]; b = c * e[i - 1]; e[i - 1 + 1] = r = pythag(f, g); if(glm::equal(r, 0, epsilon)) { d[i - 1 + 1] -= p; e[m - 1] = 0; break; } s = f / r; c = g / r; g = d[i - 1 + 1] - p; r = (d[i - 1] - g) * s + 2 * c * b; d[i - 1 + 1] = g + (p = s * r); g = c * r - b; for(k = 1; k <= D; k++) { f = a[(k - 1) * D + (i - 1 + 1)]; a[(k - 1) * D + (i - 1 + 1)] = s * a[(k - 1) * D + (i - 1)] + c * f; a[(k - 1) * D + (i - 1)] = c * a[(k - 1) * D + (i - 1)] - s * f; } } if(glm::equal(r, 0, epsilon) && (i >= l)) continue; d[l - 1] -= p; e[l - 1] = g; e[m - 1] = 0; } } while(m != l); } // 3. output for(i = 0; i < D; i++) outEigenvalues[i] = d[i]; for(i = 0; i < D; i++) for(j = 0; j < D; j++) outEigenvectors[i][j] = a[(j) * D + (i)]; return D; } template GLM_FUNC_QUALIFIER void sortEigenvalues(vec<2, T, Q>& eigenvalues, mat<2, 2, T, Q>& eigenvectors) { if (eigenvalues[0] < eigenvalues[1]) { std::swap(eigenvalues[0], eigenvalues[1]); std::swap(eigenvectors[0], eigenvectors[1]); } } template GLM_FUNC_QUALIFIER void sortEigenvalues(vec<3, T, Q>& eigenvalues, mat<3, 3, T, Q>& eigenvectors) { if (eigenvalues[0] < eigenvalues[1]) { std::swap(eigenvalues[0], eigenvalues[1]); std::swap(eigenvectors[0], eigenvectors[1]); } if (eigenvalues[0] < eigenvalues[2]) { std::swap(eigenvalues[0], eigenvalues[2]); std::swap(eigenvectors[0], eigenvectors[2]); } if (eigenvalues[1] < eigenvalues[2]) { std::swap(eigenvalues[1], eigenvalues[2]); std::swap(eigenvectors[1], eigenvectors[2]); } } template GLM_FUNC_QUALIFIER void sortEigenvalues(vec<4, T, Q>& eigenvalues, mat<4, 4, T, Q>& eigenvectors) { if (eigenvalues[0] < eigenvalues[2]) { std::swap(eigenvalues[0], eigenvalues[2]); std::swap(eigenvectors[0], eigenvectors[2]); } if (eigenvalues[1] < eigenvalues[3]) { std::swap(eigenvalues[1], eigenvalues[3]); std::swap(eigenvectors[1], eigenvectors[3]); } if (eigenvalues[0] < eigenvalues[1]) { std::swap(eigenvalues[0], eigenvalues[1]); std::swap(eigenvectors[0], eigenvectors[1]); } if (eigenvalues[2] < eigenvalues[3]) { std::swap(eigenvalues[2], eigenvalues[3]); std::swap(eigenvectors[2], eigenvectors[3]); } if (eigenvalues[1] < eigenvalues[2]) { std::swap(eigenvalues[1], eigenvalues[2]); std::swap(eigenvectors[1], eigenvectors[2]); } } }//namespace glm