std::vector<double> MultivariateFNormalSufficient::get_norms() const
{
if (!flag_norms_)
{
//Eigen::LLT<MatrixXd, Eigen::Upper> ldlt(get_ldlt());
Eigen::LDLT<MatrixXd, Eigen::Upper> ldlt(get_ldlt());
// determinant and derived constants
//MatrixXd L(ldlt.matrixU());
//std::cout << "L: " << L << std::endl << std::endl;
//std::cout << "D: " << ldlt.vectorD() << std::endl << std::endl;
//double logDetSigma=2*L.diagonal().array().log().sum() ;
double logDetSigma = ldlt.vectorD().array().abs().log().sum();
IMP_LOG_TERSE( "MVN: det(Sigma) = " <<exp(logDetSigma) << std::endl);
double norm=pow(2*IMP::PI*IMP::square(factor_), -double(N_*M_)/2.0)
* exp(-double(N_)/2.0*logDetSigma);
double lnorm=double(N_*M_)/2 * log(2*IMP::PI*IMP::square(factor_))
+ double(N_)/2 * logDetSigma;
IMP_LOG_TERSE( "MVN: norm = " << norm << " lnorm = "
<< lnorm << std::endl);
const_cast<MultivariateFNormalSufficient *>(this)
->set_norms(norm,lnorm);
}
std::vector<double> norms;
norms.push_back(norm_);
norms.push_back(lnorm_);
return norms;
}
IMPEM_BEGIN_NAMESPACE
EnvelopePenetrationRestraint::EnvelopePenetrationRestraint(
Particles ps,
DensityMap *em_map,Float threshold
): Restraint("Envelope penetration restraint")
{
IMP_LOG_TERSE("Load envelope penetration with the following input:"<<
"number of particles:"<<ps.size()<<
"\n");
threshold_=threshold;
target_dens_map_ = em_map;
IMP_IF_CHECK(USAGE) {
for (unsigned int i=0; i< ps.size(); ++i) {
IMP_USAGE_CHECK(core::XYZR::particle_is_instance(ps[i]),
"Particle " << ps[i]->get_name()
<< " is not XYZR"
<< std::endl);
}
}
add_particles(ps);
ps_=ps;
IMP_LOG_TERSE("after adding particles"<<std::endl);
IMP_LOG_TERSE( "Finish initialization" << std::endl);
}
ComplementarityRestraint::GridObject *ComplementarityRestraint::get_grid_object(
core::RigidBody rb, const kernel::ParticlesTemp &a, ObjectKey ok,
double thickness, double value, double interior_thickness,
double voxel) const {
IMP_USAGE_CHECK(!a.empty(), "No particles passed for excluded volume");
for (unsigned int i = 1; i < a.size(); ++i) {
IMP_USAGE_CHECK(core::RigidMember(a[0]).get_rigid_body() ==
core::RigidMember(a[i]).get_rigid_body(),
"Not all particles are from the same rigid body.");
}
if (!rb->has_attribute(ok)) {
IMP_LOG_TERSE("Creating grid for rigid body " << rb->get_name()
<< std::endl);
IMP::algebra::DenseGrid3D<float> grid =
get_grid(a, thickness, value, interior_thickness, voxel);
IMP_LOG_TERSE("Grid has size " << grid.get_number_of_voxels(0) << ", "
<< grid.get_number_of_voxels(1) << ", "
<< grid.get_number_of_voxels(2)
<< std::endl);
base::Pointer<GridObject> n(new GridObject(
GridPair(rb.get_reference_frame().get_transformation_to(), grid)));
rb->add_cache_attribute(ok, n);
}
IMP_CHECK_OBJECT(rb->get_value(ok));
IMP_INTERNAL_CHECK(dynamic_cast<GridObject *>(rb->get_value(ok)),
"The saved grid is not a grid.");
return dynamic_cast<GridObject *>(rb->get_value(ok));
}
void ProteomicsEMAlignmentAtomic::load_atomic_molecules(){
IMP_LOG_TERSE("load atomic molecules \n");
IMP_NEW(atom::ATOMPDBSelector,sel,());
// IMP_NEW(atom::CAlphaPDBSelector,sel,());
for(int i=0;i<prot_data_->get_number_of_proteins();i++) {
IMP_LOG_TERSE("going to load molecule "<<
asmb_data_->get_component_header(i)->get_filename()<<"\n");
// prot_data_.get_protein_filename(i)<<"|\n";
atom::Hierarchy mh =
atom::read_pdb(asmb_data_->get_component_header(i)->get_filename(),
mdl_,sel);
mh->set_name(asmb_data_->get_component_header(i)->get_name());
mh->set_was_used(true);
mhs_.push_back(mh);
std::cout<<"create pdb"<<std::endl;
std::cout<<"are subunits rigid?"
<<params_.get_fragments_params().subunit_rigid_<<std::endl;
if (params_.get_fragments_params().subunit_rigid_) {
std::cout<<"create rigid body"<<std::endl;
rbs_.push_back(atom::create_rigid_body(mh));
rbs_[rbs_.size()-1]->set_name(mh->get_name());
rbs_[rbs_.size()-1]->add_attribute(fit_state_key_,-1);
rbs_[rbs_.size()-1]->add_attribute(order_key_,i);
}
}
}
void IncrementalScoringFunction::create_scoring_functions() {
IMP_OBJECT_LOG;
IMP_LOG_TERSE("Creating scoring functions" << std::endl);
if (flattened_restraints_.empty()) return;
boost::unordered_map<Restraint *, int> mp;
IMP_LOG_TERSE("All restraints are " << flattened_restraints_ << std::endl);
for (unsigned int i = 0; i < flattened_restraints_.size(); ++i) {
mp[flattened_restraints_[i]] = i;
}
Restraints drs;
for (unsigned int i = 0; i < nbl_.size(); ++i) {
// This ensures that the score states needed for the non-bonded terms
drs.push_back(nbl_[i]->get_dummy_restraint());
}
Vector<RestraintsTemp> crs;
IMP_FOREACH(ParticleIndex pi, all_) {
RestraintsTemp cr = get_dependent_restraints(get_model(), pi);
/* Remove any duplicates in cr (could happen with rigid bodies) */
std::sort(cr.begin(), cr.end());
cr.erase(std::unique(cr.begin(), cr.end()), cr.end());
crs.push_back(cr);
}
void ProjectionFinder::set_projections(const em2d::Images &projections) {
IMP_LOG_TERSE("ProjectionFinder: Setting projections" << std::endl);
if(projections.size()==0) {
IMP_THROW("Passing empty set of projections",ValueException);
}
if(polar_params_.get_is_setup() == false) {
polar_params_.setup(projections[0]->get_data().rows,
projections[0]->get_data().cols);
polar_params_.set_estimated_number_of_angles(
projections[0]->get_header().get_number_of_columns());
polar_params_.create_maps_for_resampling();
}
projections_.resize(projections.size());
unsigned int n_projections = projections_.size();
PROJECTIONS_POLAR_AUTOC_.clear();
PROJECTIONS_POLAR_AUTOC_.resize(n_projections);
projections_cog_.resize(n_projections);
boost::timer preprocessing_timer;
for (unsigned int i = 0; i < n_projections; ++i) {
projections_[i] = projections[i]; // does not copy
std::ostringstream oss;
oss << "Projection" << i;
projections_[i]->set_name(oss.str());
do_preprocess_projection(i);
}
preprocessing_time_ = preprocessing_timer.elapsed();
IMP_LOG_TERSE("ProjectionFinder: Projections set: "
<< projections_.size() << std::endl);
}
double Em2DRestraint::unprotected_evaluate(DerivativeAccumulator *accum) const {
IMP_UNUSED(accum);
IMP_USAGE_CHECK(!accum, "No derivatives provided");
IMP_NEW(Model, model, ());
model = get_model();
// Project the model
RegistrationResults regs =
get_evenly_distributed_registration_results(params_.n_projections);
unsigned int rows = em_images_[0]->get_header().get_number_of_rows();
unsigned int cols = em_images_[0]->get_header().get_number_of_columns();
ProjectingOptions options(params_.pixel_size, params_.resolution);
Images projections = get_projections(particles_container_->get_particles(),
regs, rows, cols, options);
finder_->set_projections(projections);
if (only_coarse_registration_) {
IMP_LOG_TERSE("Em2DRestraint::unprotected::evaluate: Coarse registration"
<< std::endl);
finder_->get_coarse_registration();
} else {
if (fast_optimization_mode_) {
IMP_LOG_TERSE("Em2DRestraint::unprotected::evaluate: Fast Mode "
<< number_of_optimized_projections_
<< " projections optimized" << std::endl);
finder_->set_fast_mode(number_of_optimized_projections_);
}
IMP_LOG_TERSE("Em2DRestraint::unprotected::evaluate: Complete registration"
<< std::endl);
finder_->get_complete_registration();
}
return finder_->get_global_score();
}
void ProjectionFinder::set_subjects(const em2d::Images &subjects) {
IMP_LOG_TERSE("ProjectionFinder: Setting subject images" << std::endl);
if (subjects.size() == 0) {
IMP_THROW("Passing empty set of subjects", ValueException);
}
if (polar_params_.get_is_setup() == false) {
polar_params_.setup(subjects[0]->get_data().rows,
subjects[0]->get_data().cols);
polar_params_.set_estimated_number_of_angles(
subjects[0]->get_header().get_number_of_columns());
polar_params_.create_maps_for_resampling();
}
boost::timer preprocessing_timer;
subjects_.resize(subjects.size());
unsigned int n_subjects = subjects_.size();
registration_results_.clear();
registration_results_.resize(n_subjects);
SUBJECTS_.clear();
SUBJECTS_.resize(n_subjects);
SUBJECTS_POLAR_AUTOC_.clear();
SUBJECTS_POLAR_AUTOC_.resize(n_subjects);
subjects_cog_.resize(n_subjects);
for (unsigned int i = 0; i < n_subjects; ++i) {
subjects_[i] = subjects[i]; // doesn't not deep copy
std::ostringstream oss;
oss << "Image subject " << i;
subjects_[i]->set_name(oss.str());
subjects_[i]->set_was_used(true);
do_preprocess_subject(i);
}
preprocessing_time_ = preprocessing_timer.elapsed();
IMP_LOG_TERSE("ProjectionFinder: Subject images set" << std::endl);
}
void RestraintCache::add_restraint_internal(
kernel::Restraint *r, unsigned int index, kernel::RestraintSet *parent,
double parent_max, Subset parent_subset, const DepMap &dependencies) {
IMP_OBJECT_LOG;
IMP_LOG_TERSE("Processing " << Showable(r) << " with " << parent_max
<< std::endl);
r->set_was_used(true);
// fix using PST
Subset cur_subset = get_subset(r, dependencies);
double cur_max = r->get_maximum_score();
if (parent) {
cur_max = std::min(parent_max / r->get_weight(), cur_max);
}
if (cur_max < std::numeric_limits<double>::max()) {
IMP_LOG_TERSE("Adding restraint " << Showable(r) << " with max " << cur_max
<< " and subset " << cur_subset
<< std::endl);
known_restraints_[r] = cur_subset;
restraint_index_[r] = index;
}
add_restraint_set_child_internal(r, cur_subset, parent, parent_max,
parent_subset);
kernel::RestraintSet *rs = dynamic_cast<kernel::RestraintSet *>(r);
if (rs) {
add_restraint_set_internal(rs, index, cur_subset, cur_max, dependencies);
} else {
if (cur_max < std::numeric_limits<double>::max()) {
cache_.access_generator().add_restraint(r, cur_subset, cur_max);
}
}
}
void GaussianProcessInterpolationScoreState::do_before_evaluate() {
IMP_LOG_TERSE("GPISS: do_before_evaluate()" << std::endl);
GaussianProcessInterpolation *gpi_;
gpi_ = gpir_->gpi_;
MultivariateFNormalSufficient *mvn_;
mvn_ = gpir_->mvn_;
//
gpi_->update_flags_covariance(); // O(1)
gpi_->update_flags_mean(); // O(1)
if (!(gpi_->flag_m_gpir_)) // gpi says that our m is not up to date
{
mvn_->set_FM(gpi_->get_m()); // O(M_)
gpi_->flag_m_gpir_ = true;
IMP_LOG_TERSE(" updated mean");
}
if (!(gpi_->flag_Omega_gpir_)) {
mvn_->set_Sigma(gpi_->get_Omega()); // O(M^2)
gpi_->flag_Omega_gpir_ = true;
IMP_LOG_TERSE(" updated covariance");
}
IMP_LOG_TERSE(std::endl);
/*ParticlesTemp tmp(gpir_->get_input_particles());
std::cout << "values: ";
for (unsigned i=0; i<tmp.size(); i++)
{
std::cout << i << " = " << Scale(tmp[i]).get_nuisance() << " ";
}
std::cout <<std::endl;*/
}
double
get_diffusion_coefficient(const algebra::Vector3Ds &displacements,
double dt) {
algebra::Vector3D Ds;
for (unsigned int i=0; i< 3; ++i) {
Ds[i]= get_diffusion_coefficient(displacements.begin(),
displacements.end(), i, dt);
}
IMP_LOG_TERSE( "Diffusion coefficients are " << Ds << std::endl);
int len=displacements.size()/2;
algebra::Vector3D Ds0;
for (unsigned int i=0; i< 3; ++i) {
Ds0[i]= get_diffusion_coefficient(displacements.begin(),
displacements.begin()+len, i, dt);
}
algebra::Vector3D Ds1;
for (unsigned int i=0; i< 3; ++i) {
Ds1[i]= get_diffusion_coefficient(displacements.begin()+len,
displacements.end(), i, dt);
}
IMP_LOG_TERSE( "Partial coefficients are " << Ds0 << " and "
<< Ds1 << std::endl);
return std::accumulate(Ds1.coordinates_begin(),
Ds1.coordinates_end(), 0.0)/3.0;
}
/** \param[in] acc If true (not nullptr), partial first derivatives should be
calculated.
\return score associated with this restraint for the given state of
the model.
*/
double Restraint::unprotected_evaluate(DerivativeAccumulator* acc) const {
IMP_LOG_TERSE("SAXS Restraint::evaluate score\n");
IMP_NEW(Profile, model_profile, ());
handler_->compute_profile(model_profile);
double score = profile_fitter_->compute_score(model_profile);
bool calc_deriv = acc ? true : false;
if (!calc_deriv) return score;
IMP_LOG_TERSE("SAXS Restraint::compute derivatives\n");
// do we need to resample the curve since it's just been created??
// yes, since it does not correspond to the experimental one
IMP_NEW(Profile, resampled_profile, ());
profile_fitter_->resample(model_profile, resampled_profile);
Vector<double> effect_size; // Gaussian model-specific derivative weights
double offset = 0.0;
double c = profile_fitter_->compute_scale_factor(model_profile);
derivative_calculator_->compute_gaussian_effect_size(model_profile, c, offset,
effect_size);
handler_->compute_derivatives(derivative_calculator_, model_profile,
effect_size, acc);
IMP_LOG_TERSE("SAXS Restraint::done derivatives, score " << score
<< "\n");
return score;
}
MatrixXd MultivariateFNormalSufficient::get_PW() const
{
if (!flag_PW_)
{
////PW
timer_.start(SOLVE);
MatrixXd PW(M_,M_);
if (N_==1)
{
IMP_LOG_TERSE( "MVN: W=0 => PW=0" << std::endl);
PW.setZero();
} else {
IMP_LOG_TERSE( "MVN: solving for PW" << std::endl);
if (use_cg_)
{
if (first_PW_)
{
PW = compute_PW_direct();
(*const_cast<bool *>(&first_PW_))=false;
} else {
PW = compute_PW_cg();
}
} else {
PW = compute_PW_direct();
}
}
const_cast<MultivariateFNormalSufficient *>(this)->set_PW(PW);
timer_.stop(SOLVE);
}
return PW_;
}
IMPISD_BEGIN_NAMESPACE
GaussianProcessInterpolationRestraintSparse::
GaussianProcessInterpolationRestraintSparse(
GaussianProcessInterpolationSparse *gpi) : gpi_(gpi)
{
//number of observation points
IMP_LOG_TERSE( "GPIR: init" << std::endl);
M_ = gpi_->n_obs_.size();
//number of repetitions
int N=gpi_->n_obs_[0];
//check if the number of repetitions is the same for every point
IMP_IF_CHECK(USAGE) {
for (unsigned i=1; i<M_; i++)
IMP_USAGE_CHECK(N == gpi_->n_obs_[i],
"must have the same number of repetitions for each point!");
}
// build multivariate normal with
// mean : prior mean
// covariance : prior covariance
// observed at : the original observations
IMP_LOG_TERSE( "GPIR: multivariate normal()" << std::endl);
//args are: sample mean, jacobian, true mean,
// nobs, sample variance, true variance
c_ = gpi_->get_cholmod_common();
mvn_ = new MultivariateFNormalSufficientSparse(gpi_->get_I(), 1.0,
gpi_->get_m(), N, gpi_->get_S(), gpi_->get_W(), c_);
IMP_LOG_TERSE( "GPIR: done init" << std::endl);
}
void GaussianProcessInterpolation::compute_OmiIm() {
IMP_Eigen::VectorXd I(get_I());
IMP_Eigen::VectorXd m(get_m());
IMP_Eigen::MatrixXd Omi(get_Omi());
IMP_LOG_TERSE("OmiIm ");
OmiIm_ = ldlt_.solve(I - m);
IMP_LOG_TERSE(std::endl);
}
void GaussianProcessInterpolation::compute_I(Floats mean) {
I_ = IMP_Eigen::VectorXd(M_);
IMP_LOG_TERSE("I: ");
for (unsigned i = 0; i < M_; i++) {
I_(i) = mean[i];
IMP_LOG_TERSE(I_(i) << " ");
}
IMP_LOG_TERSE(std::endl);
}
void read_pdb(Model *model, const std::string file,
std::vector<std::string>& pdb_file_names,
std::vector<IMP::Particles>& particles_vec,
bool residue_level, bool heavy_atoms_only, int multi_model_pdb,
bool explicit_water) {
IMP::atom::Hierarchies mhds;
IMP::atom::PDBSelector* selector;
if (residue_level) // read CA only
selector = new IMP::atom::CAlphaPDBSelector();
else if (heavy_atoms_only) { // read without hydrogens
if (explicit_water)
selector = new IMP::atom::NonHydrogenPDBSelector();
else
selector = new IMP::atom::NonWaterNonHydrogenPDBSelector();
} else { // read with hydrogens
if (explicit_water)
selector = new IMP::atom::NonAlternativePDBSelector();
else
selector = new IMP::atom::NonWaterPDBSelector();
}
if (multi_model_pdb == 2) {
mhds = read_multimodel_pdb(file, model, selector, true);
} else {
if (multi_model_pdb == 3) {
IMP::atom::Hierarchy mhd =
IMP::atom::read_pdb(file, model, selector, false, true);
mhds.push_back(mhd);
} else {
IMP::atom::Hierarchy mhd =
IMP::atom::read_pdb(file, model, selector, true, true);
mhds.push_back(mhd);
}
}
for (unsigned int h_index = 0; h_index < mhds.size(); h_index++) {
IMP::ParticlesTemp ps =
get_by_type(mhds[h_index], IMP::atom::ATOM_TYPE);
if (ps.size() > 0) { // pdb file
std::string pdb_id = file;
if (mhds.size() > 1) {
pdb_id = trim_extension(file) + "_m" +
std::string(boost::lexical_cast<std::string>(h_index + 1)) +
".pdb";
}
pdb_file_names.push_back(pdb_id);
particles_vec.push_back(IMP::get_as<IMP::Particles>(ps));
if (mhds.size() > 1) {
IMP_LOG_TERSE(ps.size() << " atoms were read from PDB file " << file
<< " MODEL " << h_index + 1 << std::endl);
} else {
IMP_LOG_TERSE(ps.size() << " atoms were read from PDB file " << file
<< std::endl);
}
}
}
}
IMP_Eigen::MatrixXd GaussianProcessInterpolation::get_W() const {
IMP_LOG_TERSE("get_W()" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->update_flags_covariance();
if (!flag_W_) {
IMP_LOG_TERSE("need to update W" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->compute_W();
const_cast<GaussianProcessInterpolation *>(this)->flag_W_ = true;
IMP_LOG_TERSE("done updating W" << std::endl);
}
return W_;
}
IMP_Eigen::VectorXd GaussianProcessInterpolation::get_wx_vector(Floats xval)
const {
const_cast<GaussianProcessInterpolation *>(this)->update_flags_covariance();
IMP_LOG_TERSE(" get_wx_vector at q= " << xval[0] << " : ");
IMP_Eigen::VectorXd wx(M_);
for (unsigned i = 0; i < M_; i++) {
wx(i) = (*covariance_function_)(x_[i], xval)[0];
IMP_LOG_TERSE(wx(i) << " ");
}
IMP_LOG_TERSE(std::endl);
return wx;
}
IMP_Eigen::VectorXd GaussianProcessInterpolation::get_m() const {
IMP_LOG_TERSE("get_m()" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->update_flags_mean();
if (!flag_m_) {
IMP_LOG_TERSE("need to update m" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->compute_m();
const_cast<GaussianProcessInterpolation *>(this)->flag_m_ = true;
IMP_LOG_VERBOSE(m_);
IMP_LOG_TERSE("done updating m" << std::endl);
}
return m_;
}
IMP_Eigen::VectorXd GaussianProcessInterpolation::get_OmiIm() const {
IMP_LOG_TERSE("get_OmiIm()" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->update_flags_mean();
const_cast<GaussianProcessInterpolation *>(this)->update_flags_covariance();
if (!flag_OmiIm_) {
IMP_LOG_TERSE("need to update OmiIm_" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->compute_OmiIm();
const_cast<GaussianProcessInterpolation *>(this)->flag_OmiIm_ = true;
IMP_LOG_TERSE("done updating OmiIm_" << std::endl);
}
return OmiIm_;
}
IMP_Eigen::LDLT<IMP_Eigen::MatrixXd, IMP_Eigen::Upper>
GaussianProcessInterpolation::get_ldlt() const {
IMP_LOG_TERSE("get_ldlt()" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->update_flags_covariance();
if (!flag_ldlt_) {
IMP_LOG_TERSE("need to update ldlt" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->compute_ldlt();
const_cast<GaussianProcessInterpolation *>(this)->flag_ldlt_ = true;
IMP_LOG_TERSE("done updating ldlt" << std::endl);
}
return ldlt_;
}
double ComplementarityRestraint::unprotected_evaluate_if_good(
DerivativeAccumulator *accum, double max) const {
IMP_OBJECT_LOG;
IMP_USAGE_CHECK_VARIABLE(accum);
IMP_USAGE_CHECK(!accum,
"ComplementarityRestraint does not support derivatives.");
double vol = cube(voxel_size_);
internal::ComplementarityParameters params;
params.maximum_separation = maximum_separation_;
params.maximum_penetration_score =
std::min(maximum_penetration_score_ / vol, max);
// std::cout<<"max penet score:"<<params.maximum_penetration_score<<"(" <<
// maximum_penetration_score_<<","<<vol<<","<<max<<")"<<std::endl;
base::Pointer<GridObject> ga =
get_grid_object(rba_, a_, ok_, complementarity_thickness_,
complementarity_value_, interior_thickness_, voxel_size_);
base::Pointer<GridObject> gb =
get_grid_object(rbb_, b_, ok_, complementarity_thickness_,
complementarity_value_, interior_thickness_, voxel_size_);
algebra::Transformation3D tra =
ga->get_data().first *
rba_.get_reference_frame().get_transformation_from();
algebra::Transformation3D trb =
rbb_.get_reference_frame().get_transformation_to() / gb->get_data().first;
// transform a by tra and b by trb
// same as transforming b by na/oa Ma= oa/ nai nb/ob p
algebra::Transformation3D tr = tra * trb;
IMP_LOG_TERSE("Transformation is " << tr << " between "
<< rba_.get_reference_frame() << " and "
<< rbb_.get_reference_frame()
<< std::endl);
IMP::multifit::internal::FitScore ps =
IMP::multifit::internal::get_fit_scores(
ga->get_data().second, gb->get_data().second, tr, params);
IMP_LOG_TERSE("Scores are " << ps.penetration_score << ", "
<< ps.complementarity_score << " and "
<< ps.boundary_score << std::endl);
/* std::cout<<"Scores are " << ps.penetration_score << ", "
<< ps.complementarity_score << " and "
<< ps.boundary_score
<< std::endl;*/
if (!score_acceptable(ps)) {
// std::cout<<"scores are not acceptable"<<std::endl;
return std::numeric_limits<double>::max();
}
double score = penetration_coef_ * ps.penetration_score +
complementarity_coef_ * ps.complementarity_score +
boundary_coef_ * ps.boundary_score;
return score * vol;
}
void GaussianProcessInterpolation::compute_S(Floats std) {
// if you modify this routine so that
// S is not diagonal check the GPIR to make sure it still needs
// to call set_W_nonzero of MVN.
IMP_Eigen::VectorXd v(M_);
IMP_LOG_TERSE("S: ");
for (unsigned i = 0; i < M_; i++) {
v(i) = IMP::square(std[i]);
IMP_LOG_TERSE(v(i) << " ");
}
S_ = v.asDiagonal();
IMP_LOG_TERSE(std::endl);
}
double MonteCarlo::do_optimize(unsigned int max_steps) {
IMP_OBJECT_LOG;
IMP_CHECK_OBJECT(this);
if (get_number_of_movers() == 0) {
IMP_THROW("Running MonteCarlo without providing any"
<< " movers isn't very useful.",
ValueException);
}
ParticleIndexes movable = get_movable_particles();
// provide a way of feeding in this value
last_energy_ = do_evaluate(movable);
if (return_best_) {
best_ = new Configuration(get_model());
best_energy_ = last_energy_;
}
reset_statistics();
update_states();
IMP_LOG_TERSE("MC Initial energy is " << last_energy_ << std::endl);
for (unsigned int i = 0; i < max_steps; ++i) {
if (get_stop_on_good_score() &&
get_scoring_function()->get_had_good_score()) {
break;
}
do_step();
if (best_energy_ < get_score_threshold()) break;
}
IMP_LOG_TERSE("MC Final energy is " << last_energy_ << std::endl);
if (return_best_) {
// std::cout << "Final score is " << get_model()->evaluate(false)
//<< std::endl;
best_->swap_configuration();
IMP_LOG_TERSE("MC Returning energy " << best_energy_ << std::endl);
IMP_IF_CHECK(USAGE) {
IMP_LOG_TERSE("MC Got " << do_evaluate(get_movable_particles())
<< std::endl);
/*IMP_INTERNAL_CHECK((e >= std::numeric_limits<double>::max()
&& best_energy_ >= std::numeric_limits<double>::max())
|| std::abs(best_energy_ - e)
< .01+.1* std::abs(best_energy_ +e),
"Energies do not match "
<< best_energy_ << " vs " << e << std::endl);*/
}
return do_evaluate(movable);
} else {
return last_energy_;
IMP_Eigen::MatrixXd GaussianProcessInterpolation::get_Omega() const {
IMP_LOG_TERSE("get_Omega()" << std::endl);
// updates sigma as well
const_cast<GaussianProcessInterpolation *>(this)->update_flags_covariance();
if (!flag_Omega_) {
IMP_LOG_TERSE("need to update Omega" << std::endl);
const_cast<GaussianProcessInterpolation *>(this)->compute_Omega();
const_cast<GaussianProcessInterpolation *>(this)->flag_Omega_ = true;
// leave flag_Omega_gpir_ to false so that the gpir is notified
// if it wants to update some stuff on its own.
IMP_LOG_TERSE("done updating Omega" << std::endl);
}
return Omega_;
}
void MovedSingletonContainer::do_score_state_before_evaluate() {
IMP_OBJECT_LOG;
IMP_CHECK_OBJECT(this);
IMP_CHECK_OBJECT(pc_);
if (pc_version_ != pc_->get_contents_hash()) {
pc_version_ = pc_->get_contents_hash();
IMP_LOG_TERSE("First call" << std::endl);
initialize();
} else {
ParticleIndexes mved = do_get_moved();
IMP_LOG_TERSE("Setting moved list: " << Showable(mved) << std::endl);
swap(mved);
}
IMP_IF_CHECK(USAGE_AND_INTERNAL) { validate(); }
}
display::Geometries get_rigid_body_derivative_geometries(
Model *m, ParticleIndex pi) {
RigidBody d(m, pi);
display::Geometries ret;
Particles ms = get_as<Particles>(d.get_rigid_members());
algebra::Transformation3D otr =
d.get_reference_frame().get_transformation_to();
algebra::VectorD<4> rderiv = d.get_rotational_derivatives();
algebra::Vector3D tderiv = d.get_derivatives();
algebra::VectorD<4> rot = otr.get_rotation().get_quaternion();
IMP_LOG_TERSE("Old rotation was " << rot << std::endl);
Float scale = .1;
algebra::VectorD<4> dv = rderiv;
if (dv.get_squared_magnitude() > 0.00001) {
dv = scale * dv.get_unit_vector();
}
rot += dv;
rot = rot.get_unit_vector();
algebra::Rotation3D r(rot[0], rot[1], rot[2], rot[3]);
IMP_LOG_TERSE("Derivative was " << tderiv << std::endl);
IMP_LOG_TERSE("New rotation is " << rot << std::endl);
FloatRange xr =
d.get_particle()->get_model()->get_range(core::XYZ::get_xyz_keys()[0]);
Float wid = xr.second - xr.first;
algebra::Vector3D stderiv = scale * tderiv * wid;
algebra::Transformation3D ntr(
algebra::Rotation3D(rot[0], rot[1], rot[2], rot[3]),
stderiv + otr.get_translation());
for (unsigned int i = 0; i < ms.size(); ++i) {
core::RigidMember dm(ms[i]);
display::SegmentGeometry *tr = new display::SegmentGeometry(
algebra::Segment3D(dm.get_coordinates(), dm.get_coordinates() + tderiv),
/*xyzcolor_*/
display::Color(1, 0, 0));
ret.push_back(tr);
algebra::Vector3D ic =
r.get_rotated(dm.get_internal_coordinates()) + d.get_coordinates();
display::SegmentGeometry *rtr = new display::SegmentGeometry(
algebra::Segment3D(dm.get_coordinates(), ic), display::Color(0, 1, 0));
ret.push_back(rtr);
display::SegmentGeometry *nrtr = new display::SegmentGeometry(
algebra::Segment3D(dm.get_coordinates(),
ntr.get_transformed(dm.get_internal_coordinates())),
display::Color(0, 0, 1));
ret.push_back(nrtr);
}
return ret;
}
void Fine2DRegistrationRestraint::setup(
ParticlesTemp &ps, const ProjectingParameters ¶ms,
Model *scoring_model,
// ScoreFunctionPtr score_function,
ScoreFunction *score_function, MasksManagerPtr masks) {
IMP_LOG_TERSE("Initializing Fine2DRegistrationRestraint" << std::endl);
ps_ = ps;
params_ = params;
// Generate all the projection masks for the structure
if (masks == MasksManagerPtr()) {
// Create the masks
masks_ =
MasksManagerPtr(new MasksManager(params.resolution, params.pixel_size));
masks_->create_masks(ps);
IMP_LOG_VERBOSE("Created " << masks_->get_number_of_masks()
<< " masks withing Fine2DRegistrationRestraint "
<< std::endl);
} else {
masks_ = masks;
IMP_LOG_VERBOSE("masks given to Fine2DRegistrationRestraint " << std::endl);
}
// Create a particle for the projection parameters to be optimized
subj_params_particle_ = new Particle(scoring_model);
PP_ = ProjectionParameters::setup_particle(subj_params_particle_);
PP_.set_parameters_optimized(true);
// Add an score state to the model
IMP_NEW(ProjectionParametersScoreState, pp_score_state,
(subj_params_particle_));
scoring_model->add_score_state(pp_score_state);
score_function_ = score_function;
}
ResultAlign2D get_rotational_alignment(const cv::Mat &input,
cv::Mat &m_to_align,bool apply) {
IMP_LOG_TERSE(
"starting 2D rotational alignment" << std::endl);
IMP_USAGE_CHECK((input.rows==m_to_align.rows) &&
(input.cols==m_to_align.cols),
"em2d::align_rotational: Matrices have different size.");
cv::Mat polar1,polar2,corr;
// Build maps for resampling
PolarResamplingParameters polar_params(input.rows,input.cols);
polar_params.set_estimated_number_of_angles(std::min(input.rows,input.cols));
polar_params.create_maps_for_resampling();
do_resample_polar(input,polar1,polar_params); // subject image
do_resample_polar(m_to_align,polar2,polar_params); // projection image
ResultAlign2D RA= get_translational_alignment(polar1,polar2);
algebra::Vector2D shift=RA.first.get_translation();
// column shift[0] is the optimal angle to bring m_to_align to input
double angle =shift[0]*polar_params.get_angle_step();
RA.first.set_rotation(angle);
RA.first.set_translation(algebra::Vector2D(0.0,0.0));
// Apply the rotation if requested
if(apply) {
cv::Mat result;
get_transformed(m_to_align,result,RA.first);
result.copyTo(m_to_align);
}
IMP_LOG_VERBOSE("Rotational alingment: Transformation= "
<< RA.first << " cross_correlation = " << RA.second << std::endl);
return RA;
}
