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AnalysisTool.cpp
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// qt
#include <QMessageBox>
#include <QThread>
// shapeworks
#include <Analysis/AnalysisTool.h>
#include <Data/Session.h>
#include <Data/ShapeWorksWorker.h>
#include <Interface/ShapeWorksStudioApp.h>
#include <Job/GroupPvalueJob.h>
#include <Job/NetworkAnalysisJob.h>
#include <Job/ParticleNormalEvaluationJob.h>
#include <Job/StatsGroupLDAJob.h>
#include <Logging.h>
#include <Python/PythonWorker.h>
#include <QMeshWarper.h>
#include <Shape.h>
#include <StudioMesh.h>
#include <Utils/AnalysisUtils.h>
#include <jkqtplotter/graphs/jkqtpscatter.h>
#include <jkqtplotter/jkqtplotter.h>
#include <ui_AnalysisTool.h>
#include <QClipboard>
#include <QMenu>
#include "ParticleAreaPanel.h"
#include "ShapeScalarPanel.h"
namespace shapeworks {
const std::string AnalysisTool::MODE_ALL_SAMPLES_C("all samples");
const std::string AnalysisTool::MODE_MEAN_C("mean");
const std::string AnalysisTool::MODE_PCA_C("pca");
const std::string AnalysisTool::MODE_SINGLE_SAMPLE_C("single sample");
const std::string AnalysisTool::MODE_REGRESSION_C("regression");
constexpr auto MESH_WARP_TEMPLATE_INDEX = "mesh_warp_template_index";
//---------------------------------------------------------------------------
//! Helper to extract x,y,z from x,y,z,scalar
static Eigen::VectorXd extract_shape_only(Eigen::VectorXd values) {
// need to drop every 4th value
Eigen::VectorXd particles(values.size() - values.size() / 4);
int j = 0;
for (int i = 0; i < values.size(); i++) {
if (i % 4 != 3) {
particles[j++] = values[i];
}
}
return particles;
}
//---------------------------------------------------------------------------
//! Helper to extract scalar from x,y,z,scalar
static Eigen::VectorXd extract_scalar_only(Eigen::VectorXd values) {
Eigen::VectorXd scalars(values.size() / 4);
int j = 0;
for (int i = 0; i < values.size(); i++) {
if (i % 4 == 3) {
scalars[j++] = values[i];
}
}
return scalars;
}
//---------------------------------------------------------------------------
AnalysisTool::AnalysisTool(Preferences& prefs) : preferences_(prefs) {
ui_ = new Ui_AnalysisTool;
ui_->setupUi(this);
particle_area_panel_ = new ParticleAreaPanel(this);
layout()->addWidget(particle_area_panel_);
shape_scalar_panel_ = new ShapeScalarPanel(this);
layout()->addWidget(shape_scalar_panel_);
auto spacer = new QSpacerItem(20, 40, QSizePolicy::Minimum, QSizePolicy::Expanding);
layout()->addItem(spacer);
#ifdef Q_OS_MACOS
ui_->tabWidget->tabBar()->setMinimumWidth(200);
ui_->tabWidget->setStyleSheet(
"QTabBar::tab:selected { border-radius: 4px; background-color: #3784f7; color: white; }");
ui_->tabWidget->tabBar()->setElideMode(Qt::TextElideMode::ElideNone);
#endif
connect(ui_->view_header, &QPushButton::clicked, ui_->view_open_button, &QPushButton::toggle);
connect(ui_->metrics_header, &QPushButton::clicked, ui_->metrics_open_button, &QPushButton::toggle);
connect(ui_->surface_header, &QPushButton::clicked, ui_->surface_open_button, &QPushButton::toggle);
connect(ui_->particles_header, &QPushButton::clicked, ui_->particles_open_button, &QPushButton::toggle);
connect(ui_->particles_open_button, &QPushButton::toggled, ui_->particles_content, &QWidget::setVisible);
ui_->view_label->setAttribute(Qt::WA_TransparentForMouseEvents);
ui_->surface_label->setAttribute(Qt::WA_TransparentForMouseEvents);
ui_->metrics_label->setAttribute(Qt::WA_TransparentForMouseEvents);
connect(ui_->allSamplesRadio, SIGNAL(clicked()), this, SLOT(handle_analysis_options()));
connect(ui_->singleSamplesRadio, SIGNAL(clicked()), this, SLOT(handle_analysis_options()));
connect(ui_->sampleSpinBox, SIGNAL(valueChanged(int)), this, SLOT(handle_analysis_options()));
connect(ui_->medianButton, SIGNAL(clicked()), this, SLOT(handle_median()));
connect(ui_->pcaAnimateCheckBox, SIGNAL(stateChanged(int)), this, SLOT(handle_pca_animate_state_changed()));
connect(&pca_animate_timer_, SIGNAL(timeout()), this, SLOT(handle_pca_timer()));
// multi-level PCA settings
connect(ui_->mcaLevelBetweenButton, &QPushButton::clicked, this, &AnalysisTool::pca_update);
connect(ui_->mcaLevelWithinButton, &QPushButton::clicked, this, &AnalysisTool::pca_update);
connect(ui_->vanillaPCAButton, &QPushButton::clicked, this, &AnalysisTool::pca_update);
// shape/scalar
connect(ui_->pca_scalar_only, &QCheckBox::clicked, this, &AnalysisTool::change_pca_analysis_type);
connect(ui_->pca_scalar_shape_only, &QCheckBox::clicked, this, &AnalysisTool::change_pca_analysis_type);
connect(ui_->pca_shape_and_scalar, &QCheckBox::clicked, this, &AnalysisTool::change_pca_analysis_type);
connect(ui_->pca_scalar_combo, qOverload<int>(&QComboBox::currentIndexChanged), this,
&AnalysisTool::change_pca_analysis_type);
connect(ui_->pca_predict_scalar, &QCheckBox::clicked, this, &AnalysisTool::change_pca_analysis_type);
connect(ui_->pca_predict_shape, &QCheckBox::clicked, this, &AnalysisTool::change_pca_analysis_type);
// group animation
connect(ui_->group_animate_checkbox, &QCheckBox::stateChanged, this,
&AnalysisTool::handle_group_animate_state_changed);
connect(&group_animate_timer_, &QTimer::timeout, this, &AnalysisTool::handle_group_timer);
connect(ui_->group_box, qOverload<int>(&QComboBox::currentIndexChanged), this, &AnalysisTool::update_group_values);
connect(ui_->group_left, qOverload<int>(&QComboBox::currentIndexChanged), this, &AnalysisTool::group_changed);
connect(ui_->group_right, qOverload<int>(&QComboBox::currentIndexChanged), this, &AnalysisTool::group_changed);
connect(ui_->group_p_values_checkbox, &QPushButton::clicked, this, &AnalysisTool::group_p_values_clicked);
// network analysis
connect(ui_->network_analysis_button, &QPushButton::clicked, this, &AnalysisTool::network_analysis_clicked);
connect(ui_->network_analysis_display, &QCheckBox::stateChanged, this, &AnalysisTool::update_view);
connect(ui_->network_analysis_option, &QRadioButton::clicked, this, &AnalysisTool::update_view);
connect(ui_->network_spm1d_option, &QRadioButton::clicked, this, &AnalysisTool::update_view);
connect(ui_->reference_domain, qOverload<int>(&QComboBox::currentIndexChanged), this,
&AnalysisTool::handle_alignment_changed);
ui_->surface_open_button->setChecked(false);
ui_->metrics_open_button->setChecked(false);
/// TODO nothing there yet (regression tab)
ui_->tabWidget->removeTab(3);
for (auto button : {ui_->distance_transform_radio_button, ui_->mesh_warping_radio_button, ui_->legacy_radio_button}) {
connect(button, &QRadioButton::clicked, this, &AnalysisTool::reconstruction_method_changed);
}
connect(ui_->run_good_bad, &QPushButton::clicked, this, &AnalysisTool::run_good_bad_particles);
ui_->reconstruction_options->hide();
ui_->mesh_warp_options->hide();
ui_->particles_open_button->toggle();
ui_->particles_progress->hide();
ui_->lda_graph->hide();
ui_->lda_hint_label->hide();
group_lda_job_ = QSharedPointer<StatsGroupLDAJob>::create();
connect(group_lda_job_.data(), &StatsGroupLDAJob::progress, this, &AnalysisTool::handle_lda_progress);
connect(group_lda_job_.data(), &StatsGroupLDAJob::finished, this, &AnalysisTool::handle_lda_complete);
connect(ui_->show_difference_to_mean, &QPushButton::clicked, this, &AnalysisTool::show_difference_to_mean_clicked);
connect(ui_->group_analysis_combo, qOverload<int>(&QComboBox::currentIndexChanged), this,
&AnalysisTool::group_analysis_combo_changed);
// when one is checked, turn the other off, connect these first
connect(ui_->show_difference_to_predicted_scalar, &QPushButton::clicked, this, [this]() {
bool checked = ui_->show_difference_to_predicted_scalar->isChecked();
if (checked) {
ui_->show_predicted_scalar->setChecked(false);
}
});
connect(ui_->show_predicted_scalar, &QPushButton::clicked, this, [this]() {
if (ui_->show_predicted_scalar->isChecked()) {
ui_->show_difference_to_predicted_scalar->setChecked(false);
}
});
connect(ui_->show_difference_to_predicted_scalar, &QPushButton::clicked, this,
&AnalysisTool::handle_samples_predicted_scalar_options);
connect(ui_->show_predicted_scalar, &QPushButton::clicked, this,
&AnalysisTool::handle_samples_predicted_scalar_options);
connect(ui_->show_absolute_difference, &QPushButton::clicked, this,
&AnalysisTool::handle_samples_predicted_scalar_options);
// add a right click menu to the samples table allowing the user to copy the table to the clipboard
ui_->samples_table->setContextMenuPolicy(Qt::CustomContextMenu);
connect(ui_->samples_table, &QTableWidget::customContextMenuRequested, this,
&AnalysisTool::samples_table_context_menu);
// disable editing of the table
ui_->samples_table->setEditTriggers(QAbstractItemView::NoEditTriggers);
// only connect one so that we only get one signal
connect(ui_->distance_method_particle, &QRadioButton::toggled, this, &AnalysisTool::handle_distance_method_changed);
// mesh warp options
connect(ui_->mesh_warp_median_button, &QPushButton::clicked, this, &AnalysisTool::mesh_warp_median_clicked);
connect(ui_->mesh_warp_sample_spinbox, qOverload<int>(&QSpinBox::valueChanged), this,
&AnalysisTool::mesh_warp_sample_changed);
connect(ui_->mesh_warp_run_button, &QPushButton::clicked, this, &AnalysisTool::mesh_warp_run_clicked);
}
//---------------------------------------------------------------------------
std::string AnalysisTool::get_analysis_mode() {
if (ui_->tabWidget->currentWidget() == ui_->samples_tab) {
if (ui_->allSamplesRadio->isChecked()) {
return AnalysisTool::MODE_ALL_SAMPLES_C;
}
if (ui_->singleSamplesRadio->isChecked()) {
return AnalysisTool::MODE_SINGLE_SAMPLE_C;
}
}
if (ui_->tabWidget->currentWidget() == ui_->mean_tab) {
return AnalysisTool::MODE_MEAN_C;
}
if (ui_->tabWidget->currentWidget() == ui_->pca_tab) {
return AnalysisTool::MODE_PCA_C;
}
if (ui_->tabWidget->currentWidget() == ui_->regression_tab) {
return AnalysisTool::MODE_REGRESSION_C;
}
return "";
}
//---------------------------------------------------------------------------
bool AnalysisTool::get_group_difference_mode() { return groups_active() && ui_->difference_button->isChecked(); }
//---------------------------------------------------------------------------
std::vector<Shape::Point> AnalysisTool::get_group_difference_vectors() {
std::vector<Shape::Point> vecs;
auto num_points = stats_.get_mean().size() / 3;
for (unsigned int i = 0; i < num_points; i++) {
Shape::Point tmp;
tmp.x = stats_.get_group2_mean()[i * 3] - stats_.get_group1_mean()[i * 3];
tmp.y = stats_.get_group2_mean()[i * 3 + 1] - stats_.get_group1_mean()[i * 3 + 1];
tmp.z = stats_.get_group2_mean()[i * 3 + 2] - stats_.get_group1_mean()[i * 3 + 2];
vecs.push_back(tmp);
}
return vecs;
}
//---------------------------------------------------------------------------
void AnalysisTool::handle_reconstruction_complete() {
session_->handle_clear_cache();
session_->calculate_reconstructed_samples();
Q_EMIT progress(100);
SW_LOG("Reconstruction Complete");
Q_EMIT reconstruction_complete();
/// TODO: Studio
/// ui_->run_optimize_button->setEnabled(true);
enable_actions();
}
//---------------------------------------------------------------------------
void AnalysisTool::on_reconstructionButton_clicked() {
store_settings();
SW_LOG("Please wait: running reconstruction step...");
Q_EMIT progress(5);
QThread* thread = new QThread;
ShapeworksWorker* worker =
new ShapeworksWorker(ShapeworksWorker::ReconstructType, nullptr, nullptr, nullptr, session_,
ui_->maxAngle->value(), ui_->meshDecimation->value(), ui_->numClusters->value());
worker->moveToThread(thread);
connect(thread, SIGNAL(started()), worker, SLOT(process()));
connect(worker, SIGNAL(result_ready()), this, SLOT(handle_reconstruction_complete()));
connect(worker, SIGNAL(finished()), worker, SLOT(deleteLater()));
thread->start();
Q_EMIT progress(15);
}
//---------------------------------------------------------------------------
int AnalysisTool::get_pca_mode() { return ui_->pcaModeSpinBox->value() - 1; }
//---------------------------------------------------------------------------
double AnalysisTool::get_group_ratio() {
double group_slider_value = ui_->group_slider->value();
double group_ratio = group_slider_value / static_cast<double>(ui_->group_slider->maximum());
return group_ratio;
}
//---------------------------------------------------------------------------
bool AnalysisTool::pca_animate() { return ui_->pcaAnimateCheckBox->isChecked(); }
//---------------------------------------------------------------------------
void AnalysisTool::set_labels(QString which, QString value) {
if (which == QString("pca")) {
ui_->pcaValueLabel->setText(value);
} else if (which == QString("eigen")) {
ui_->pcaEigenValueLabel->setText(value);
} else if (which == QString("lambda")) {
ui_->pcaLambdaLabel->setText(value);
}
}
//---------------------------------------------------------------------------
int AnalysisTool::get_sample_number() { return ui_->sampleSpinBox->value(); }
//---------------------------------------------------------------------------
AnalysisTool::~AnalysisTool() {}
//---------------------------------------------------------------------------
void AnalysisTool::set_session(QSharedPointer<Session> session) {
session_ = session;
particle_area_panel_->set_session(session);
shape_scalar_panel_->set_session(session);
// reset to original
ui_->mesh_warping_radio_button->setChecked(true);
ui_->difference_button->setChecked(false);
ui_->group_p_values_checkbox->setChecked(false);
ui_->group1_button->setChecked(false);
ui_->group2_button->setChecked(false);
update_difference_particles();
ui_->show_predicted_scalar->setChecked(false);
ui_->show_difference_to_predicted_scalar->setChecked(false);
handle_samples_predicted_scalar_options();
connect(ui_->show_good_bad, &QCheckBox::toggled, session_.data(), &Session::set_show_good_bad_particles);
}
//---------------------------------------------------------------------------
QSharedPointer<Session> AnalysisTool::get_session() { return session_; }
//---------------------------------------------------------------------------
void AnalysisTool::set_app(ShapeWorksStudioApp* app) { app_ = app; }
//---------------------------------------------------------------------------
void AnalysisTool::update_interface() {
ui_->show_good_bad->setEnabled(session_->get_good_bad_particles().size() == session_->get_num_particles());
ui_->show_good_bad->setChecked(ui_->show_good_bad->isEnabled() && session_->get_show_good_bad_particles());
}
//---------------------------------------------------------------------------
bool AnalysisTool::group_pvalues_valid() {
return group_pvalue_job_ && group_pvalue_job_->get_group_pvalues().rows() > 0;
}
//---------------------------------------------------------------------------
bool AnalysisTool::groups_on() { return ui_->group_box->currentText() != "-None-"; }
//---------------------------------------------------------------------------
void AnalysisTool::handle_analysis_options() {
if (ui_->tabWidget->currentWidget() == ui_->samples_tab) {
ui_->pcaAnimateCheckBox->setChecked(false);
ui_->pcaAnimateCheckBox->setEnabled(false);
ui_->pcaModeSpinBox->setEnabled(false);
pca_animate_timer_.stop();
ui_->pcaSlider->setEnabled(false);
if (ui_->singleSamplesRadio->isChecked()) {
// one sample mode
ui_->sampleSpinBox->setEnabled(true);
ui_->medianButton->setEnabled(true);
} else {
// all samples mode
ui_->sampleSpinBox->setEnabled(false);
ui_->medianButton->setEnabled(false);
}
} else if (ui_->tabWidget->currentWidget() == ui_->mean_tab) {
// mean mode
ui_->sampleSpinBox->setEnabled(false);
ui_->medianButton->setEnabled(false);
ui_->pcaSlider->setEnabled(false);
ui_->pcaAnimateCheckBox->setEnabled(false);
ui_->pcaModeSpinBox->setEnabled(false);
ui_->pcaAnimateCheckBox->setChecked(false);
pca_animate_timer_.stop();
} else if (ui_->tabWidget->currentWidget() == ui_->pca_tab) {
// pca mode
ui_->sampleSpinBox->setEnabled(false);
ui_->medianButton->setEnabled(false);
ui_->pcaSlider->setEnabled(true);
ui_->pcaAnimateCheckBox->setEnabled(true);
ui_->pcaModeSpinBox->setEnabled(true);
auto domain_names = session_->get_project()->get_domain_names();
bool multiple_domains = domain_names.size() > 1;
if (multiple_domains) {
ui_->vanillaPCAButton->setEnabled(true);
ui_->mcaLevelWithinButton->setEnabled(true);
ui_->mcaLevelBetweenButton->setEnabled(true);
ui_->vanillaPCAButton->setChecked(true);
}
} else {
// regression mode
ui_->sampleSpinBox->setEnabled(false);
ui_->medianButton->setEnabled(false);
ui_->pcaSlider->setEnabled(false);
ui_->pcaAnimateCheckBox->setEnabled(false);
ui_->pcaModeSpinBox->setEnabled(false);
pca_animate_timer_.stop();
}
update_difference_particles();
Q_EMIT analysis_mode_changed();
Q_EMIT update_view();
}
//---------------------------------------------------------------------------
void AnalysisTool::handle_median() {
if (!compute_stats()) {
return;
}
ui_->sampleSpinBox->setValue(stats_.compute_median_shape(-32)); //-32 = both groups
Q_EMIT update_view();
}
//-----------------------------------------------------------------------------
void AnalysisTool::on_mean_button_clicked() {
ui_->group1_button->setChecked(false);
ui_->group2_button->setChecked(false);
ui_->difference_button->setChecked(false);
ui_->group_animate_checkbox->setChecked(false);
ui_->mean_button->setChecked(true);
update_difference_particles();
Q_EMIT update_view();
}
//-----------------------------------------------------------------------------
void AnalysisTool::on_group1_button_clicked() {
ui_->group_slider->setValue(ui_->group_slider->minimum());
ui_->mean_button->setChecked(false);
ui_->group2_button->setChecked(false);
ui_->difference_button->setChecked(false);
ui_->group_animate_checkbox->setChecked(false);
ui_->group1_button->setChecked(true);
ui_->group_p_values_checkbox->setChecked(false);
update_difference_particles();
Q_EMIT update_view();
}
//-----------------------------------------------------------------------------
void AnalysisTool::on_group2_button_clicked() {
ui_->group_slider->setValue(ui_->group_slider->maximum());
ui_->mean_button->setChecked(false);
ui_->group1_button->setChecked(false);
ui_->difference_button->setChecked(false);
ui_->group_animate_checkbox->setChecked(false);
ui_->group2_button->setChecked(true);
ui_->group_p_values_checkbox->setChecked(false);
update_difference_particles();
Q_EMIT update_view();
}
//-----------------------------------------------------------------------------
void AnalysisTool::on_difference_button_clicked() {
ui_->group_slider->setValue(ui_->group_slider->minimum());
ui_->mean_button->setChecked(false);
ui_->group1_button->setChecked(false);
ui_->group2_button->setChecked(false);
ui_->group_p_values_checkbox->setChecked(false);
ui_->group_animate_checkbox->setChecked(false);
ui_->difference_button->setChecked(true);
update_difference_particles();
Q_EMIT update_view();
}
//---------------------------------------------------------------------------
void AnalysisTool::group_p_values_clicked() {
if (!ui_->group_p_values_checkbox->isChecked()) {
Q_EMIT update_view();
return;
}
ui_->group_slider->setValue(10);
ui_->mean_button->setChecked(false);
ui_->group1_button->setChecked(false);
ui_->group2_button->setChecked(false);
ui_->group_animate_checkbox->setChecked(false);
ui_->difference_button->setChecked(false);
update_difference_particles();
if (group_pvalues_valid()) {
handle_group_pvalues_complete();
} else {
if (group1_list_.size() < 3 || group2_list_.size() < 3) {
SW_ERROR("Unable to compute p-values with less than 3 shapes per group");
return;
}
group_pvalue_job_ = QSharedPointer<GroupPvalueJob>::create(stats_);
connect(group_pvalue_job_.data(), &GroupPvalueJob::progress, this, &AnalysisTool::progress);
connect(group_pvalue_job_.data(), &GroupPvalueJob::finished, this, &AnalysisTool::handle_group_pvalues_complete);
app_->get_py_worker()->run_job(group_pvalue_job_);
}
}
//---------------------------------------------------------------------------
void AnalysisTool::network_analysis_clicked() {
network_analysis_job_ =
QSharedPointer<NetworkAnalysisJob>::create(session_->get_project(), ui_->group_box->currentText().toStdString(),
ui_->network_feature->currentText().toStdString());
network_analysis_job_->set_pvalue_of_interest(ui_->network_pvalue_of_interest->text().toDouble());
network_analysis_job_->set_pvalue_threshold(ui_->network_pvalue_threshold->text().toDouble());
network_analysis_job_->set_num_iterations(ui_->network_iterations->text().toInt());
connect(network_analysis_job_.data(), &NetworkAnalysisJob::progress, this,
&AnalysisTool::handle_network_analysis_progress);
connect(network_analysis_job_.data(), &NetworkAnalysisJob::finished, this,
&AnalysisTool::handle_network_analysis_complete);
app_->get_py_worker()->run_job(network_analysis_job_);
}
//-----------------------------------------------------------------------------
bool AnalysisTool::compute_stats() {
if (stats_ready_) {
return true;
}
if (session_->get_non_excluded_shapes().size() == 0 || !session_->particles_present()) {
return false;
}
SW_DEBUG("Compute Stats!");
compute_reconstructed_domain_transforms();
ui_->pcaModeSpinBox->setMaximum(std::max<double>(1, session_->get_non_excluded_shapes().size() - 1));
std::vector<Eigen::VectorXd> points;
std::vector<int> group_ids;
std::string group_set = ui_->group_box->currentText().toStdString();
std::string left_group = ui_->group_left->currentText().toStdString();
std::string right_group = ui_->group_right->currentText().toStdString();
bool groups_enabled = groups_active();
group1_list_.clear();
group2_list_.clear();
auto domain_names = session_->get_project()->get_domain_names();
unsigned int domains_per_shape = domain_names.size();
number_of_particles_array_.resize(domains_per_shape);
for (auto& shape : session_->get_non_excluded_shapes()) {
Eigen::VectorXd particles;
stats_.set_num_values_per_particle(3);
if (pca_shape_only_mode()) {
particles = shape->get_global_correspondence_points();
} else if (pca_scalar_only_mode()) {
stats_.set_num_values_per_particle(1);
shape->get_reconstructed_meshes(true);
std::string target_feature = ui_->pca_scalar_combo->currentText().toStdString();
shape->load_feature(DisplayMode::Reconstructed, target_feature);
particles = shape->get_point_features(ui_->pca_scalar_combo->currentText().toStdString());
} else { // shape and scalar (x,y,z, and scalar)
stats_.set_num_values_per_particle(4);
std::string target_feature = ui_->pca_scalar_combo->currentText().toStdString();
auto positions = shape->get_global_correspondence_points();
shape->get_reconstructed_meshes(true);
shape->load_feature(DisplayMode::Reconstructed, target_feature);
auto scalars = particles = shape->get_point_features(target_feature);
// combine positions and scalars, interleave 3 positions for every scalar
particles.resize(positions.size() + scalars.size());
int num_particles = positions.size() / 3;
for (int i = 0; i < num_particles; i++) {
particles[i * 4] = positions[i * 3];
particles[i * 4 + 1] = positions[i * 3 + 1];
particles[i * 4 + 2] = positions[i * 3 + 2];
}
for (int i = 0; i < scalars.size(); i++) {
particles[i * 4 + 3] = scalars[i];
}
}
if (particles.size() == 0) {
continue; // skip any that don't have particles
}
if (groups_enabled) {
auto value = shape->get_subject()->get_group_value(group_set);
if (value == left_group) {
points.push_back(particles);
group_ids.push_back(1);
group1_list_.push_back(shape);
} else if (value == right_group) {
points.push_back(particles);
group_ids.push_back(2);
group2_list_.push_back(shape);
} else {
// we don't include it
}
} else {
points.push_back(particles);
group_ids.push_back(1);
}
auto local_particles = shape->get_particles().get_local_particles();
if (local_particles.size() != domains_per_shape) {
SW_ERROR("Inconsistency in number of particles size");
return false;
}
for (unsigned int i = 0; i < domains_per_shape; i++) {
number_of_particles_array_[i] = local_particles[i].size() / 3;
}
}
if (points.empty()) {
return false;
}
// consistency check
size_t point_size = points[0].size();
for (auto&& p : points) {
if (p.size() != point_size) {
SW_ERROR("Inconsistency in data, particle files must contain the same number of points");
return false;
}
}
stats_.import_points(points, group_ids);
// MCA needs to know number of particles per domain/object
stats_.set_num_particles_per_domain(number_of_particles_array_);
if (domains_per_shape > 1) {
stats_.compute_multi_level_analysis_statistics(points, domains_per_shape);
}
stats_.compute_modes();
if (domains_per_shape > 1) {
stats_.compute_relative_pose_modes_for_mca();
stats_.compute_shape_dev_modes_for_mca();
}
update_difference_particles();
if (ui_->metrics_open_button->isChecked()) {
compute_shape_evaluations();
}
stats_ready_ = true;
/// Set this to true to export long format sample data (e.g. for import into R)
const bool export_long_format = false;
if (export_long_format && groups_enabled) {
auto feature_names = session_->get_project()->get_feature_names();
std::ofstream file;
file.open("/tmp/stats.csv");
file << "subject,group,particle,x,y,z";
for (int i = 0; i < feature_names.size(); i++) {
file << "," << feature_names[i];
}
file << "\n";
int shape_id = 0;
Q_FOREACH (ShapeHandle shape, session_->get_non_excluded_shapes()) {
auto group = shape->get_subject()->get_group_value(group_set);
auto particles = shape->get_particles();
auto points = particles.get_world_points(0);
int point_id = 0;
for (int j = 0; j < points.size(); j++) {
auto point = points[j];
file << shape_id << "," << group << "," << point_id++ << "," << point[0] << "," << point[1] << "," << point[2];
for (int i = 0; i < feature_names.size(); i++) {
auto scalars = shape->get_point_features(feature_names[i]);
file << "," << scalars[j];
}
file << "\n";
}
shape_id++;
}
file.close();
}
return true;
}
//-----------------------------------------------------------------------------
Particles AnalysisTool::get_mean_shape_points() {
if (!compute_stats()) {
return Particles();
}
if (ui_->pca_scalar_only->isChecked()) {
return convert_from_combined(construct_mean_shape());
}
if (ui_->group1_button->isChecked() || ui_->difference_button->isChecked()) {
return convert_from_combined(stats_.get_group1_mean());
} else if (ui_->group2_button->isChecked()) {
return convert_from_combined(stats_.get_group2_mean());
} else if (ui_->mean_button->isChecked()) {
return convert_from_combined(stats_.get_mean());
}
if (groups_active()) {
auto group_ratio = get_group_ratio();
temp_shape_ = stats_.get_group1_mean() + (stats_.get_group_difference() * group_ratio);
return convert_from_combined(temp_shape_);
}
return convert_from_combined(stats_.get_mean());
}
//-----------------------------------------------------------------------------
Particles AnalysisTool::get_shape_points(int mode, double value) {
if (!compute_stats() || stats_.get_eigen_vectors().size() <= 1) {
return Particles();
}
if (mode + 2 > stats_.get_eigen_values().size()) {
mode = stats_.get_eigen_values().size() - 2;
}
unsigned int m = stats_.get_eigen_vectors().cols() - (mode + 1);
m = std::clamp<unsigned int>(m, 0, stats_.get_eigen_vectors().cols() - 1);
Eigen::VectorXd e = stats_.get_eigen_vectors().col(m);
double lambda = sqrt(stats_.get_eigen_values()[m]);
pca_labels_changed(QString::number(value, 'g', 2), QString::number(stats_.get_eigen_values()[m]),
QString::number(value * lambda));
std::vector<double> vals;
for (int i = stats_.get_eigen_values().size() - 1; i > 0; i--) {
vals.push_back(stats_.get_eigen_values()[i]);
}
double sum = std::accumulate(vals.begin(), vals.end(), 0.0);
double cumulation = 0;
for (size_t i = 0; i < mode + 1; ++i) {
cumulation += vals[i];
}
if (sum > 0) {
ui_->explained_variance->setText(QString::number(vals[mode] / sum * 100, 'f', 1) + "%");
ui_->cumulative_explained_variance->setText(QString::number(cumulation / sum * 100, 'f', 1) + "%");
} else {
ui_->explained_variance->setText("");
ui_->cumulative_explained_variance->setText("");
}
temp_shape_ = stats_.get_mean() + (e * (value * lambda));
auto positions = temp_shape_;
computed_scalars_ = Eigen::VectorXd();
if (pca_shape_plus_scalar_mode()) {
positions = extract_shape_only(temp_shape_);
computed_scalars_ = extract_scalar_only(temp_shape_);
} else if (pca_scalar_only_mode()) {
computed_scalars_ = temp_shape_;
if (ui_->pca_predict_shape->isChecked()) {
positions = ShapeScalarJob::predict_shape(session_, QString::fromStdString(feature_map_), computed_scalars_);
} else {
positions = construct_mean_shape();
}
}
return convert_from_combined(positions);
}
//---------------------------------------------------------------------------
Particles AnalysisTool::get_multi_level_shape_points(int mode, double value, McaMode level) {
// Get Shape Points for Multi-Level Analysis
Eigen::MatrixXd eigenvectors;
std::vector<double> eigenvalues;
if (level == McaMode::Within) {
eigenvectors = stats_.get_eigenvectors_shape_dev();
eigenvalues = stats_.get_eigenvalues_shape_dev();
} else if (level == McaMode::Between) {
eigenvectors = stats_.get_eigenvectors_rel_pos();
eigenvalues = stats_.get_eigenvalues_rel_pose();
}
if (!compute_stats() || eigenvectors.size() <= 1) {
return Particles();
}
if (mode + 2 > eigenvalues.size()) {
mode = eigenvalues.size() - 2;
}
unsigned int m = eigenvectors.cols() - (mode + 1);
Eigen::VectorXd e = eigenvectors.col(m);
double lambda = sqrt(eigenvalues[m]);
pca_labels_changed(QString::number(value, 'g', 2), QString::number(eigenvalues[m]), QString::number(value * lambda));
std::vector<double> vals;
for (int i = eigenvalues.size() - 1; i > 0; i--) {
vals.push_back(eigenvalues[i]);
}
double sum = std::accumulate(vals.begin(), vals.end(), 0.0);
double cumulation = 0;
for (size_t i = 0; i < mode + 1; ++i) {
cumulation += vals[i];
}
if (sum > 0) {
ui_->explained_variance->setText(QString::number(vals[mode] / sum * 100, 'f', 1) + "%");
ui_->cumulative_explained_variance->setText(QString::number(cumulation / sum * 100, 'f', 1) + "%");
} else {
ui_->explained_variance->setText("");
ui_->cumulative_explained_variance->setText("");
}
unsigned int D = stats_.get_domains_per_shape();
unsigned int sz = stats_.get_mean().size();
if (level == McaMode::Within) {
// Morphological Variations
temp_shape_mca = stats_.get_mean() + (e * (value * lambda));
} else if (level == McaMode::Between) {
// Relative Pose Variations
Eigen::VectorXd e_between;
e_between.resize(sz);
for (unsigned int i = 0; i < D; i++) {
int num_points = number_of_particles_array_[i];
int row = 0;
for (int idx = 0; idx < i; idx++) {
row += (3 * number_of_particles_array_[idx]);
}
for (unsigned int j = 0; j < num_points; j++) {
e_between(row + (j * 3)) = e(i * 3);
e_between(row + (j * 3) + 1) = e(i * 3 + 1);
e_between(row + (j * 3) + 2) = e(i * 3 + 2);
}
}
temp_shape_mca = stats_.get_mean() + (e_between * (value * lambda));
}
return convert_from_combined(temp_shape_mca);
}
//---------------------------------------------------------------------------
ShapeHandle AnalysisTool::get_mode_shape(int mode, double value) {
return create_shape_from_points(get_shape_points(mode, value));
}
//---------------------------------------------------------------------------
ShapeHandle AnalysisTool::get_mca_mode_shape(int mode, double value, McaMode level) {
return create_shape_from_points(get_multi_level_shape_points(mode, value, level));
}
//---------------------------------------------------------------------------
ShapeHandle AnalysisTool::get_current_shape() {
int pca_mode = get_pca_mode();
double pca_value = get_pca_value();
auto mca_level = get_mca_level();
if (mca_level == AnalysisTool::McaMode::Vanilla) {
return get_mode_shape(pca_mode, pca_value);
} else {
return get_mca_mode_shape(pca_mode, pca_value, mca_level);
}
}
//---------------------------------------------------------------------------
ParticleShapeStatistics AnalysisTool::get_stats() {
compute_stats();
return stats_;
}
//---------------------------------------------------------------------------
void AnalysisTool::load_settings() {
Parameters params = session_->get_project()->get_parameters(Parameters::ANALYSIS_PARAMS);
ui_->numClusters->setValue(params.get("reconstruction_clusters", 3));
ui_->meshDecimation->setValue(params.get("reconstruction_decimation", 0.30));
ui_->maxAngle->setValue(params.get("reconstruction_max_angle", 60));
ui_->network_iterations->setText(QString::number(static_cast<double>(params.get("network_iterations", 10000))));
double pvalue_of_interest = params.get("network_pvalue_of_interest", 0.05);
ui_->network_pvalue_of_interest->setText(QString::number(pvalue_of_interest));
ui_->network_pvalue_threshold->setText(
QString::number(static_cast<double>(params.get("network_pvalue_threshold", 0.05))));
ui_->mesh_warp_sample_spinbox->setValue(params.get(MESH_WARP_TEMPLATE_INDEX, -1));
update_group_boxes();
ui_->group_box->setCurrentText(QString::fromStdString(params.get("current_group", "-None-")));
}
//---------------------------------------------------------------------------
void AnalysisTool::store_settings() {
Parameters params = session_->get_project()->get_parameters(Parameters::ANALYSIS_PARAMS);
params.set("reconstruction_clusters", ui_->numClusters->value());
params.set("reconstruction_decimation", ui_->meshDecimation->value());
params.set("reconstruction_max_angle", ui_->maxAngle->value());
params.set("network_iterations", ui_->network_iterations->text().toStdString());
params.set("network_pvalue_of_interest", ui_->network_pvalue_of_interest->text().toStdString());
params.set("network_pvalue_threshold", ui_->network_pvalue_threshold->text().toStdString());
session_->get_project()->set_parameters(Parameters::ANALYSIS_PARAMS, params);
}
//---------------------------------------------------------------------------
void AnalysisTool::shutdown() {
pca_animate_timer_.stop();
for (const auto& worker : workers_) {
if (worker) {
worker->stop();
}
}
}
//---------------------------------------------------------------------------
void AnalysisTool::compute_shape_evaluations() {
if (evals_ready_) {
return;
}
// reset
eval_compactness_ = Eigen::VectorXd();
eval_specificity_ = Eigen::VectorXd();
eval_generalization_ = Eigen::VectorXd();
ui_->compactness_graph->setMinimumSize(QSize(250, 250));
ui_->generalization_graph->setMinimumSize(QSize(250, 250));
ui_->specificity_graph->setMinimumSize(QSize(250, 250));
ui_->compactness_progress_widget->show();
ui_->generalization_progress_widget->show();
ui_->specificity_progress_widget->show();
ui_->compactness_graph->hide();
ui_->generalization_graph->hide();
ui_->specificity_graph->hide();
ui_->compactness_progress->setValue(0);
ui_->generalization_progress->setValue(0);
ui_->specificity_progress->setValue(0);
if ((stats_.matrix().rows() > 10000 || stats_.matrix().cols() > 10000) && !large_particle_disclaimer_waived_) {
QMessageBox::StandardButton reply;
reply = QMessageBox::question(this, "Are you sure?",
"Shape evaluation on large numbers of particles or samples may exhaust "
"system memory and cause ShapeWorksStudio to become unresponsive, "
"are you sure you want to continue?",
QMessageBox::Yes | QMessageBox::No);
if (reply == QMessageBox::No) {
skip_evals_ = true;
}
large_particle_disclaimer_waived_ = true;
}
std::vector<ShapeEvaluationJob::JobType> job_types = {ShapeEvaluationJob::JobType::CompactnessType,
ShapeEvaluationJob::JobType::GeneralizationType,
ShapeEvaluationJob::JobType::SpecificityType};
if (skip_evals_) {
// compactness isn't ever a problem.
job_types = {ShapeEvaluationJob::JobType::CompactnessType};
}
stats_.set_particle_to_surface_mode(ui_->distance_method_surface->isChecked());
// stop any running jobs
for (const auto& worker : workers_) {
if (worker) {
worker->stop();
}
}
for (auto job_type : job_types) {
switch (job_type) {
case ShapeEvaluationJob::JobType::CompactnessType:
SW_DEBUG("job type: compactness");
break;
case ShapeEvaluationJob::JobType::GeneralizationType:
SW_DEBUG("job type: gen job");
break;
case ShapeEvaluationJob::JobType::SpecificityType:
SW_DEBUG("job type: spec job");
break;
default:
SW_DEBUG("job type: unknown");
}
QPointer<Worker> worker = Worker::create_worker();
workers_.push_back(worker);
auto job = QSharedPointer<ShapeEvaluationJob>::create(job_type, stats_, session_);
connect(job.data(), &ShapeEvaluationJob::result_ready, this, &AnalysisTool::handle_eval_thread_complete);
connect(job.data(), &ShapeEvaluationJob::report_progress, this, &AnalysisTool::handle_eval_thread_progress);
worker->run_job(job);
}
evals_ready_ = true;
}
//---------------------------------------------------------------------------
AnalysisTool::GroupAnalysisType AnalysisTool::get_group_analysis_type() {
if (!groups_on()) {
return GroupAnalysisType::None;
} else {
return static_cast<GroupAnalysisType>(ui_->group_analysis_combo->currentIndex());
}
}
//---------------------------------------------------------------------------
bool AnalysisTool::pca_scalar_only_mode() { return ui_->pca_scalar_only->isChecked(); }
//---------------------------------------------------------------------------
bool AnalysisTool::pca_shape_plus_scalar_mode() { return ui_->pca_shape_and_scalar->isChecked(); }
//---------------------------------------------------------------------------
bool AnalysisTool::pca_shape_only_mode() { return ui_->pca_scalar_shape_only->isChecked(); }
//---------------------------------------------------------------------------
void AnalysisTool::on_tabWidget_currentChanged() { handle_analysis_options(); }
//---------------------------------------------------------------------------
void AnalysisTool::on_pcaSlider_valueChanged() {
// this will make the slider handle redraw making the UI appear more responsive
QCoreApplication::processEvents();
Q_EMIT pca_update();
}
//---------------------------------------------------------------------------
void AnalysisTool::on_group_slider_valueChanged() {
// this will make the slider handle redraw making the UI appear more responsive