本文整理汇总了C++中dgMatrix::Transpose4X4方法的典型用法代码示例。如果您正苦于以下问题：C++ dgMatrix::Transpose4X4方法的具体用法？C++ dgMatrix::Transpose4X4怎么用？C++ dgMatrix::Transpose4X4使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类dgMatrix的用法示例。
在下文中一共展示了dgMatrix::Transpose4X4方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: EigenVectors
void dgMatrix::EigenVectors (dgVector &eigenValues, const dgMatrix& initialGuess)
{
hacd::HaF32 b[3];
hacd::HaF32 z[3];
hacd::HaF32 d[3];
dgMatrix& mat = *this;
dgMatrix eigenVectors (initialGuess.Transpose4X4());
mat = initialGuess * mat * eigenVectors;
b[0] = mat[0][0];
b[1] = mat[1][1];
b[2] = mat[2][2];
d[0] = mat[0][0];
d[1] = mat[1][1];
d[2] = mat[2][2];
z[0] = hacd::HaF32 (0.0f);
z[1] = hacd::HaF32 (0.0f);
z[2] = hacd::HaF32 (0.0f);
for (hacd::HaI32 i = 0; i < 50; i++) {
hacd::HaF32 sm = dgAbsf(mat[0][1]) + dgAbsf(mat[0][2]) + dgAbsf(mat[1][2]);
if (sm < hacd::HaF32 (1.0e-6f)) {
HACD_ASSERT (dgAbsf((eigenVectors.m_front % eigenVectors.m_front) - hacd::HaF32(1.0f)) < dgEPSILON);
HACD_ASSERT (dgAbsf((eigenVectors.m_up % eigenVectors.m_up) - hacd::HaF32(1.0f)) < dgEPSILON);
HACD_ASSERT (dgAbsf((eigenVectors.m_right % eigenVectors.m_right) - hacd::HaF32(1.0f)) < dgEPSILON);
// order the eigenvalue vectors
dgVector tmp (eigenVectors.m_front * eigenVectors.m_up);
if (tmp % eigenVectors.m_right < hacd::HaF32(0.0f)) {
eigenVectors.m_right = eigenVectors.m_right.Scale (-hacd::HaF32(1.0f));
}
eigenValues = dgVector (d[0], d[1], d[2], hacd::HaF32 (0.0f));
*this = eigenVectors.Inverse();
return;
}
hacd::HaF32 thresh = hacd::HaF32 (0.0f);
if (i < 3) {
thresh = (hacd::HaF32)(0.2f / 9.0f) * sm;
}
for (hacd::HaI32 ip = 0; ip < 2; ip ++) {
for (hacd::HaI32 iq = ip + 1; iq < 3; iq ++) {
hacd::HaF32 g = hacd::HaF32 (100.0f) * dgAbsf(mat[ip][iq]);
//if ((i > 3) && (dgAbsf(d[0]) + g == dgAbsf(d[ip])) && (dgAbsf(d[1]) + g == dgAbsf(d[1]))) {
if ((i > 3) && ((dgAbsf(d[ip]) + g) == dgAbsf(d[ip])) && ((dgAbsf(d[iq]) + g) == dgAbsf(d[iq]))) {
mat[ip][iq] = hacd::HaF32 (0.0f);
} else if (dgAbsf(mat[ip][iq]) > thresh) {
hacd::HaF32 t;
hacd::HaF32 h = d[iq] - d[ip];
if (dgAbsf(h) + g == dgAbsf(h)) {
t = mat[ip][iq] / h;
} else {
hacd::HaF32 theta = hacd::HaF32 (0.5f) * h / mat[ip][iq];
t = hacd::HaF32(1.0f) / (dgAbsf(theta) + dgSqrt(hacd::HaF32(1.0f) + theta * theta));
if (theta < hacd::HaF32 (0.0f)) {
t = -t;
}
}
hacd::HaF32 c = hacd::HaF32(1.0f) / dgSqrt (hacd::HaF32 (1.0f) + t * t);
hacd::HaF32 s = t * c;
hacd::HaF32 tau = s / (hacd::HaF32(1.0f) + c);
h = t * mat[ip][iq];
z[ip] -= h;
z[iq] += h;
d[ip] -= h;
d[iq] += h;
mat[ip][iq] = hacd::HaF32(0.0f);
for (hacd::HaI32 j = 0; j <= ip - 1; j ++) {
//ROT (mat, j, ip, j, iq, s, tau);
//ROT(dgMatrix &a, hacd::HaI32 i, hacd::HaI32 j, hacd::HaI32 k, hacd::HaI32 l, hacd::HaF32 s, hacd::HaF32 tau)
hacd::HaF32 g = mat[j][ip];
hacd::HaF32 h = mat[j][iq];
mat[j][ip] = g - s * (h + g * tau);
mat[j][iq] = h + s * (g - h * tau);
}
for (hacd::HaI32 j = ip + 1; j <= iq - 1; j ++) {
//ROT (mat, ip, j, j, iq, s, tau);
//ROT(dgMatrix &a, hacd::HaI32 i, hacd::HaI32 j, hacd::HaI32 k, hacd::HaI32 l, hacd::HaF32 s, hacd::HaF32 tau)
hacd::HaF32 g = mat[ip][j];
hacd::HaF32 h = mat[j][iq];
mat[ip][j] = g - s * (h + g * tau);
mat[j][iq] = h + s * (g - h * tau);
}
for (hacd::HaI32 j = iq + 1; j < 3; j ++) {
//ROT (mat, ip, j, iq, j, s, tau);
//ROT(dgMatrix &a, hacd::HaI32 i, hacd::HaI32 j, hacd::HaI32 k, hacd::HaI32 l, hacd::HaF32 s, hacd::HaF32 tau)
hacd::HaF32 g = mat[ip][j];
hacd::HaF32 h = mat[iq][j];
mat[ip][j] = g - s * (h + g * tau);
mat[iq][j] = h + s * (g - h * tau);
}
//.........这里部分代码省略.........