Gadgetron::NFFT_internal::NFFT_Matrix<REAL>
Gadgetron::NFFT_internal::transpose(const Gadgetron::NFFT_internal::NFFT_Matrix<REAL> &matrix) {
GadgetronTimer timer("Transpose");
auto work_index = boost::irange(size_t(0),matrix.n_cols);
NFFT_Matrix<REAL> transposed(matrix.n_rows, matrix.n_cols);
std::vector<int> counts(matrix.n_rows, 0);
for (size_t i : work_index) {
auto &rows = matrix.indices[i];
for (auto &row : rows) {
counts[row]++;
}
}
for (size_t i = 0; i < counts.size(); i++) {
transposed.indices[i].reserve(counts[i]);
transposed.weights[i].reserve(counts[i]);
}
for (size_t i : work_index ) {
auto &rows = matrix.indices[i];
auto &weights = matrix.weights[i];
for (size_t n = 0; n < rows.size(); n++) {
transposed.indices[rows[n]].push_back(i);
transposed.weights[rows[n]].push_back(weights[n]);
}
}
return transposed;
}
/**
* @brief This function transposes a matrix represented by a 2-D array
* @param args[0] The input matrix
* return The transposed matrix
**/
AnyType lda_transpose::run(AnyType & args)
{
ArrayHandle<int64_t> matrix = args[0].getAs<ArrayHandle<int64_t> >();
if(matrix.dims() != 2)
throw std::domain_error("invalid dimension");
int32_t row_num = static_cast<int32_t>(matrix.sizeOfDim(0));
int32_t col_num = static_cast<int32_t>(matrix.sizeOfDim(1));
int dims[2] = {col_num, row_num};
int lbs[2] = {1, 1};
MutableArrayHandle<int64_t> transposed(
madlib_construct_md_array(
NULL, NULL, 2, dims, lbs, INT8TI.oid, INT8TI.len, INT8TI.byval,
INT8TI.align));
for(int32_t i = 0; i < row_num; i++){
int32_t index = i * col_num;
for(int32_t j = 0; j < col_num; j++){
transposed[j * row_num + i] = matrix[index];
index++;
}
}
return transposed;
}
Matrix<double> Matrix<double>::Multiply(const Matrix<double>& m) const
{
if ( GetColumnLength() != m.GetRowLength() )
{
Matrix<double> null;
return null;
}
Matrix<double> multiplied(GetRowLength(), m.GetColumnLength());
#if 0
for (size_t row = 0; row < multiplied.GetRowLength(); ++row)
{
for (size_t col = 0; col < multiplied.GetColumnLength(); ++col)
{
double v = 0;
for (size_t k = 0; k < GetColumnLength(); ++k)
{
v += (*this)[row][k] * m[k][col];
}
multiplied[row][col] = v;
}
}
#else
Matrix<double> transposed(m.T());
for (size_t row = 0; row < multiplied.GetRowLength(); ++row)
{
for (size_t col = 0; col < multiplied.GetColumnLength(); ++col)
{
multiplied[row][col] = (*this)[row].Dot(transposed[col]);
}
}
#endif
return multiplied;
}
Matrix<T> Matrix<T>::transpose() const
{
Matrix<T> transposed(size());
for (unsigned int i = 0; i<size(); i++)
for (unsigned int j = 0; j<size(); j++)
transposed[j][i] = m_matrix[i][j];
return transposed;
}
Matrix Matrix::getTransposed() const {
Matrix transposed(m_size);
for (size_t row = 0; row < m_size; ++row) {
for (size_t col = 0; col < m_size; ++col) {
transposed[row][col] = m_data[col][row];
}
}
return transposed;
}
Matrix Matrix::transpose() const
{
Matrix transposed(this->nCols(), this->nRows());
for (unsigned int i = 0; i < this->nRows(); i++) {
for (unsigned int j = 0; j < this->nCols(); j++) {
transposed[j][i] = (*(this))[i][j];
}
}
return transposed;
}
Matrix<double> Matrix<double>::Transpose(void) const
{
Matrix<double> transposed(GetColumnLength(), GetRowLength());
for (size_t i = 0; i < GetRowLength(); ++i)
{
for (size_t j = 0; j < GetColumnLength(); ++j)
{
transposed[j][i] = (*this)[i][j];
}
}
return transposed;
}
void RectangularMatrixTest::transposed() {
Matrix4x3 original(Vector3( 0.0f, 1.0f, 3.0f),
Vector3( 4.0f, 5.0f, 7.0f),
Vector3( 8.0f, 9.0f, 11.0f),
Vector3(12.0f, 13.0f, 15.0f));
Matrix3x4 transposed(Vector4(0.0f, 4.0f, 8.0f, 12.0f),
Vector4(1.0f, 5.0f, 9.0f, 13.0f),
Vector4(3.0f, 7.0f, 11.0f, 15.0f));
CORRADE_COMPARE(original.transposed(), transposed);
}
Matrix transpose(const Matrix& A){
assert(A.size() >= 1);
assert(A[0].size() >= 1);
int rows = A.size();
int cols = A[0].size();
Matrix transposed(cols, std::vector<double>(rows));
for(int row = 0; row < rows; row++){
for(int col = 0; col < cols; col++){
transposed[col][row] = A[row][col];
}
}
return transposed;
}
void Basis::get_rotation_axis_angle_local(Vector3 &p_axis, real_t &p_angle) const {
// Assumes that the matrix can be decomposed into a proper rotation and scaling matrix as M = R.S,
// and returns the Euler angles corresponding to the rotation part, complementing get_scale().
// See the comment in get_scale() for further information.
Basis m = transposed();
m.orthonormalize();
real_t det = m.determinant();
if (det < 0) {
// Ensure that the determinant is 1, such that result is a proper rotation matrix which can be represented by Euler angles.
m.scale(Vector3(-1, -1, -1));
}
m.get_axis_angle(p_axis, p_angle);
p_angle = -p_angle;
}
// Decomposes a Basis into a rotation-reflection matrix (an element of the group O(3)) and a positive scaling matrix as B = O.S.
// Returns the rotation-reflection matrix via reference argument, and scaling information is returned as a Vector3.
// This (internal) function is too specific and named too ugly to expose to users, and probably there's no need to do so.
Vector3 Basis::rotref_posscale_decomposition(Basis &rotref) const {
#ifdef MATH_CHECKS
ERR_FAIL_COND_V(determinant() == 0, Vector3());
Basis m = transposed() * (*this);
ERR_FAIL_COND_V(!m.is_diagonal(), Vector3());
#endif
Vector3 scale = get_scale();
Basis inv_scale = Basis().scaled(scale.inverse()); // this will also absorb the sign of scale
rotref = (*this) * inv_scale;
#ifdef MATH_CHECKS
ERR_FAIL_COND_V(!rotref.is_orthogonal(), Vector3());
#endif
return scale.abs();
}
/* called by the C++ code to render */
extern "C" void device_render (int* pixels,
const unsigned int width,
const unsigned int height,
const float time,
const ISPCCamera& camera)
{
float t0 = 0.7f*time;
float t1 = 1.5f*time;
/* rotate instances around themselves */
LinearSpace3fa xfm;
xfm.vx = Vec3fa(cos(t1),0,sin(t1));
xfm.vy = Vec3fa(0,1,0);
xfm.vz = Vec3fa(-sin(t1),0,cos(t1));
/* calculate transformations to move instances in cirle */
for (int i=0; i<4; i++) {
float t = t0+i*2.0f*float(pi)/4.0f;
instance_xfm[i] = AffineSpace3fa(xfm,2.2f*Vec3fa(+cos(t),0.0f,+sin(t)));
}
/* calculate transformations to properly transform normals */
for (int i=0; i<4; i++)
normal_xfm[i] = transposed(rcp(instance_xfm[i].l));
/* set instance transformations */
rtcSetTransform2(g_scene,g_instance0,RTC_MATRIX_COLUMN_MAJOR_ALIGNED16,(float*)&instance_xfm[0],0);
rtcSetTransform2(g_scene,g_instance1,RTC_MATRIX_COLUMN_MAJOR_ALIGNED16,(float*)&instance_xfm[1],0);
rtcSetTransform2(g_scene,g_instance2,RTC_MATRIX_COLUMN_MAJOR_ALIGNED16,(float*)&instance_xfm[2],0);
rtcSetTransform2(g_scene,g_instance3,RTC_MATRIX_COLUMN_MAJOR_ALIGNED16,(float*)&instance_xfm[3],0);
/* update scene */
rtcUpdate(g_scene,g_instance0);
rtcUpdate(g_scene,g_instance1);
rtcUpdate(g_scene,g_instance2);
rtcUpdate(g_scene,g_instance3);
rtcCommit (g_scene);
/* render all pixels */
const int numTilesX = (width +TILE_SIZE_X-1)/TILE_SIZE_X;
const int numTilesY = (height+TILE_SIZE_Y-1)/TILE_SIZE_Y;
parallel_for(size_t(0),size_t(numTilesX*numTilesY),[&](const range<size_t>& range) {
const int threadIndex = (int)TaskScheduler::threadIndex();
for (size_t i=range.begin(); i<range.end(); i++)
renderTileTask((int)i,threadIndex,pixels,width,height,time,camera,numTilesX,numTilesY);
});
}
Matrix<T> Matrix<T>::xxT() const
{
Q_ASSERT(constData() && size());
int stride1(bytesPerLine());
int stride2(bytesPerElement());
if (type() == CV_64F)
{
Matrix<T> mulRes(rows(), rows());
int dstStride1(mulRes.bytesPerLine());
int dstStride2(mulRes.bytesPerElement());
const Ipp64f* dataPtr(reinterpret_cast<const Ipp64f*>(constData()));
Ipp64f* mulResPtr(reinterpret_cast<Ipp64f*>(mulRes.data()));
IppStatus status(ippmMul_mt_64f(dataPtr, stride1, stride2, cols(), rows(),
dataPtr, stride1, stride2, cols(), rows(),
mulResPtr, dstStride1, dstStride2));
Q_ASSERT(status == ippStsNoErr);
return mulRes;
}
Q_ASSERT(!"CHECK");
return *this * transposed();
}
void MatrixTest:: testTransposedMatrix ()
{
Matrix<3,2,int> matrix;
assignList(matrix) = 1, 2,
3, 4,
5, 6;
typedef Matrix<3,2,int> Matrix;
TransposedMatrix<Matrix>& transposed = transpose(matrix);
validateEquals (transposed(0,0), 1);
validateEquals (transposed(0,1), 3);
validateEquals (transposed(0,2), 5);
validateEquals (transposed(1,0), 2);
validateEquals (transposed(1,1), 4);
validateEquals (transposed(1,2), 6);
validate (transpose(transposed) == matrix);
}
void check_geometry(Geometry1 const& geometry1,
Geometry2 const& geometry2,
std::string const& wkt1,
std::string const& wkt2,
std::string const& expected)
{
{
std::string res_str = bgdr::relate<bgdr::matrix9>(geometry1, geometry2);
bool ok = boost::equal(res_str, expected);
BOOST_CHECK_MESSAGE(ok,
"relate: " << wkt1
<< " and " << wkt2
<< " -> Expected: " << expected
<< " detected: " << res_str);
}
// changed sequence of geometries - transposed result
{
std::string res_str = bgdr::relate(geometry2, geometry1, bgdr::matrix9());
std::string expected_tr = transposed(expected);
bool ok = boost::equal(res_str, expected_tr);
BOOST_CHECK_MESSAGE(ok,
"relate: " << wkt2
<< " and " << wkt1
<< " -> Expected: " << expected_tr
<< " detected: " << res_str);
}
{
bool result = bgdr::relate(geometry1, geometry2, bgdr::mask9(expected));
// TODO: SHOULD BE !interrupted - CHECK THIS!
BOOST_CHECK_MESSAGE(result,
"relate: " << wkt1
<< " and " << wkt2
<< " -> Expected: " << expected);
}
if ( bg::detail::relate::interruption_enabled<Geometry1, Geometry2>::value )
{
// brake the expected output
std::string expected_interrupt = expected;
bool changed = false;
BOOST_FOREACH(char & c, expected_interrupt)
{
if ( c >= '0' && c <= '9' )
{
if ( c == '0' )
c = 'F';
else
--c;
changed = true;
}
}
if ( changed )
{
bool result = bgdr::relate(geometry1, geometry2, bgdr::mask9(expected_interrupt));
// TODO: SHOULD BE interrupted - CHECK THIS!
BOOST_CHECK_MESSAGE(!result,
"relate: " << wkt1
<< " and " << wkt2
<< " -> Expected interrupt for:" << expected_interrupt);
}
}
}
inline void matrix_reorder_columns(MatrixType& matrix, size_t row_first, size_t row_beyond, size_t column_first, size_t column_beyond,
ElementLess element_less)
{
matrix_transposed <MatrixType> transposed(matrix);
matrix_reorder_rows(matrix, column_first, column_beyond, row_first, row_beyond, element_less);
}
inline void matrix_apply_column_permutation(MatrixType& matrix, const permutation& perm)
{
matroid_transposed <MatrixType> transposed(matrix);
matrix_apply_row_permutation(transposed, perm);
}
bool Basis::is_orthogonal() const {
Basis id;
Basis m = (*this)*transposed();
return isequal_approx(id,m);
}
/**
* Set command
*/
void command_set(const char* line) {
char cmd[MAX_BUFFER];
char key[MAX_BUFFER];
char func[MAX_BUFFER];
char arg1[MAX_BUFFER];
char arg2[MAX_BUFFER];
int argc = sscanf(line, "%s %s = %s %s %s", cmd, key, func, arg1, arg2);
if (argc < 3) {
puts("invalid arguments");
return;
}
uint32_t* matrix = NULL;
switch (argc) {
case 3:
if (strcasecmp(func, "identity") == 0) {
matrix = identity_matrix();
} else {
goto invalid;
}
break;
case 4:
if (strcasecmp(func, "random") == 0) {
uint32_t seed = atoll(arg1);
matrix = random_matrix(seed);
} else if (strcasecmp(func, "uniform") == 0) {
uint32_t value = atoll(arg1);
matrix = uniform_matrix(value);
} else if (strcasecmp(func, "cloned") == 0) {
MATRIX_GUARD(arg1);
matrix = cloned(m);
} else if (strcasecmp(func, "reversed") == 0) {
MATRIX_GUARD(arg1);
matrix = reversed(m);
} else if (strcasecmp(func, "transposed") == 0) {
MATRIX_GUARD(arg1);
matrix = transposed(m);
} else {
goto invalid;
}
break;
case 5:
if (strcasecmp(func, "sequence") == 0) {
uint32_t start = atoll(arg1);
uint32_t step = atoll(arg2);
matrix = sequence_matrix(start, step);
} else if (strcasecmp(func, "scalar#add") == 0) {
MATRIX_GUARD(arg1);
uint32_t value = atoll(arg2);
matrix = scalar_add(m, value);
} else if (strcasecmp(func, "scalar#mul") == 0) {
MATRIX_GUARD(arg1);
uint32_t value = atoll(arg2);
matrix = scalar_mul(m, value);
} else if (strcasecmp(func, "matrix#add") == 0) {
MATRIX_GUARD_PAIR(arg1, arg2);
matrix = matrix_add(m1, m2);
} else if (strcasecmp(func, "matrix#mul") == 0) {
MATRIX_GUARD_PAIR(arg1, arg2);
matrix = matrix_mul(m1, m2);
} else if (strcasecmp(func, "matrix#pow") == 0) {
MATRIX_GUARD(arg1);
uint32_t exponent = atoll(arg2);
matrix = matrix_pow(m, exponent);
} else {
goto invalid;
}
break;
}
entry* e = find_entry(key);
if (e == NULL) {
e = add_entry(key);
} else {
free(e->matrix);
}
e->matrix = matrix;
puts("ok");
return;
invalid:
puts("invalid arguments");
}
std::vector<double> TimeSmoother::FitModel(int parameterIndex,
const std::vector<double>& dataPoints,
const std::vector<int>& framesWithDataPoints) const {
// 1. Project data points (from each frame) to model to get corresponding xi
// Here the data points are the nodal parameters at each frame and linearly map to xi
// 2. Construct P
FourierBasis basis;
int numRows = dataPoints.size();
gmm::dense_matrix<double> P(numRows, NUMBER_OF_PARAMETERS);
// std::cout << "\n\n\nnumRows = " << numRows << '\n';
for (int i = 0; i < numRows; i++) {
double xiDouble[1];
xiDouble[0] = MapToXi(static_cast<double>(i) / numRows); //REVISE design
// std::cout << "dataPoint(" << i << ") = " << dataPoints[i] << ", xi = "<< xiDouble[0] <<'\n';
double psi[NUMBER_OF_PARAMETERS];
basis.Evaluate(psi, xiDouble);
for (int columnIndex = 0; columnIndex < NUMBER_OF_PARAMETERS;
columnIndex++) {
P(i, columnIndex) = psi[columnIndex];
if (framesWithDataPoints[i]) {
P(i, columnIndex) *= CAP_WEIGHT_GP; //TEST
}
}
}
// std::cout << "P = " << P << std::endl;
// 3. Construct A
// Note that G is the identity matrix. StS is read in from file.
gmm::dense_matrix<double> A(NUMBER_OF_PARAMETERS, NUMBER_OF_PARAMETERS),
temp(NUMBER_OF_PARAMETERS, NUMBER_OF_PARAMETERS);
gmm::mult(gmm::transposed(P), P, temp);
gmm::add(pImpl->S, temp, A);
// std::cout << "A = " << A << std::endl;
// 4. Construct rhs
std::vector<double> prior(11), p(numRows), rhs(11);
for (int i = 0; i < 11; i++) {
prior[i] = pImpl->Priors(i, parameterIndex);
}
// std::cout << "prior: " << prior << std::endl;
gmm::mult(P, prior, p);
// std::transform(dataPoints.begin(), dataPoints.end(), p.begin(), p.begin(), std::minus<double>());
//TEST
// p[0] *= 10; //more weight for frame 0
std::vector<double> dataLambda = dataPoints;
for (unsigned int i = 0; i < dataLambda.size(); i++) {
if (framesWithDataPoints[i]) {
dataLambda[i] *= CAP_WEIGHT_GP;
}
}
std::transform(dataLambda.begin(), dataLambda.end(), p.begin(), p.begin(),
std::minus<double>());
gmm::mult(transposed(P), p, rhs);
// std::cout << "rhs: " << rhs << std::endl;
// 5. Solve normal equation (direct solver)
std::vector<double> x(gmm::mat_nrows(A));
gmm::lu_solve(A, x, rhs);
#ifndef NDEBUG
// std::cout << "delta x (" << parameterIndex << ") " << x << std::endl;
#endif
std::transform(x.begin(), x.end(), prior.begin(), x.begin(),
std::plus<double>());
return x;
}
