From 57b3e0965b08e6ac2290cac7ce3edec1b32435fa Mon Sep 17 00:00:00 2001
From: Sylvain Calinon <sylvain.calinon@idiap.ch>
Date: Fri, 7 Jul 2017 11:51:05 +0200
Subject: [PATCH] List of examples added
---
CMakeLists.txt | 18 +-
README.md | 167 +++++++++++++--
src/demo_proMP01.cpp | 468 -------------------------------------------
3 files changed, 147 insertions(+), 506 deletions(-)
delete mode 100644 src/demo_proMP01.cpp
diff --git a/CMakeLists.txt b/CMakeLists.txt
index f305553..b995ef4 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -172,22 +172,6 @@ target_link_libraries(demo_LQR_infHor
${PBD_LIB}
)
-add_executable(demo_proMP01
- ${PROJECT_SOURCE_DIR}/src/imgui_impl_glfw_gl3.cpp
- ${PROJECT_SOURCE_DIR}/src/gfx_ui.cpp
- ${PROJECT_SOURCE_DIR}/src/gfx3.cpp
- ${PROJECT_SOURCE_DIR}/src/imgui.cpp
- ${PROJECT_SOURCE_DIR}/src/imgui_draw.cpp
- ${PROJECT_SOURCE_DIR}/src/demo_proMP01.cpp
-)
-target_link_libraries(demo_proMP01
- ${OPENGL_LIBRARIES}
- ${GLEW_LIBRARIES}
- ${GLFW_LIB}
- ${ARMADILLO_LIBRARIES}
- ${PBD_LIB}
-)
-
add_executable(demo_Riemannian_cov_interp02
${PROJECT_SOURCE_DIR}/src/imgui.cpp
${PROJECT_SOURCE_DIR}/src/imgui_impl_glfw.cpp
@@ -342,4 +326,4 @@ target_link_libraries(demo_teleop
${ARMADILLO_LIBRARIES}
${GLFW_LIB}
${PBD_LIB}
-)
\ No newline at end of file
+)
diff --git a/README.md b/README.md
index 9af449a..e3c4ade 100644
--- a/README.md
+++ b/README.md
@@ -51,36 +51,161 @@ make
**Note:** The `-DBUILD_SHARED_LIBS` is necessary otherwise cmake will create a
static library.
-### Execution
-This project will build a number of executables, as listed below:
+### References
-- *demo_dptpgmm*: online tp-gmm learning and lqr-based trajectory generation.
+Did you find PbDLib useful for your research? Please acknowledge the authors in any academic publications that used parts of these codes.
+<br><br>
-- *demo_glsl*: Minimalist example with glsl display
+[1] Tutorial (GMM, TP-GMM, MFA, MPPCA, GMR, LWR, GPR, MPC, LQR, trajGMM):
+```
+@article{Calinon16JIST,
+ author="Calinon, S.",
+ title="A Tutorial on Task-Parameterized Movement Learning and Retrieval",
+ journal="Intelligent Service Robotics",
+ publisher="Springer Berlin Heidelberg",
+ year="2016",
+ volume="9",
+ number="1",
+ pages="1--29",
+ doi="10.1007/s11370-015-0187-9",
+}
+```
-- *demo_LQR_infHor*: Minimalist example of discrete infinite horizon linear
- quadratic regulation.
+[2] HMM, HSMM:
+```
+@article{Rozo16Frontiers,
+ author="Rozo, L. and Silv\'erio, J. and Calinon, S. and Caldwell, D. G.",
+ title="Learning Controllers for Reactive and Proactive Behaviors in Human-Robot Collaboration",
+ journal="Frontiers in Robotics and {AI}",
+ year="2016",
+ month="June",
+ volume="3",
+ number="30",
+ pages="1--11",
+ doi="10.3389/frobt.2016.00030"
+}
+```
-- *demo_online_gmm*: online gmm learning and lqr-based trajectory generation.
+[3] Riemannian manifolds (S2,S3):
+```
+@article{Zeestraten17RAL,
+ author="Zeestraten, M. J. A. and Havoutis, I. and Silv\'erio, J. and Calinon, S. and Caldwell, D. G.",
+ title="An Approach for Imitation Learning on {R}iemannian Manifolds",
+ journal="{IEEE} Robotics and Automation Letters ({RA-L})",
+ year="2017",
+ month="June",
+ volume="2",
+ number="3",
+ pages="1240--1247"
+ doi="10.1109/LRA.2017.2657001",
+}
+```
-- *demo_online_hsmm*: online hsmm learning and sampling with lqr-based trajectory
- generation.
+[4] Riemannian manifolds (S+):
+```
+@inproceedings{Jaquier17IROS,
+ author="Jaquier, N. and Calinon, S.",
+ title="Gaussian Mixture Regression on Symmetric Positive Definite Matrices Manifolds: Application to Wrist Motion Estimation with {sEMG}",
+ booktitle="Proc. {IEEE/RSJ} Intl Conf. on Intelligent Robots and Systems ({IROS})",
+ year="2017",
+ month="September",
+ address="Vancouver, Canada",
+ pages=""
+}
+```
-- *demo_proMP01*: Conditioning on trajectory distributions with ProMP
+[5] Semi-tied GMM:
+```
+@article{Tanwani16RAL,
+ author="Tanwani, A. K. and Calinon, S.",
+ title="Learning Robot Manipulation Tasks with Task-Parameterized Semi-Tied Hidden Semi-{M}arkov Model",
+ journal="{IEEE} Robotics and Automation Letters ({RA-L})",
+ year="2016",
+ month="January",
+ volume="1",
+ number="1",
+ pages="235--242",
+ doi="10.1109/LRA.2016.2517825"
+}
+```
-- *demo_Riemannian_cov_interp02*: Covariance interpolation on Riemannian manifold
- from a GMM with augmented covariances.
+[6] DP-means:
+```
+@article{Bruno17AURO,
+ author="Bruno, D. and Calinon, S. and Caldwell, D. G.",
+ title="Learning Autonomous Behaviours for the Body of a Flexible Surgical Robot",
+ journal="Autonomous Robots",
+ year="2017",
+ month="February",
+ volume="41",
+ number="2",
+ pages="333--347",
+ doi="10.1007/s10514-016-9544-6"
+}
+```
-- *demo_Riemannian_sphere_infHorLQR*: Linear quadratic regulation on a sphere by
- relying on Riemannian manifold and
- infinite-horizon LQR.
+[7] Shared control, adaptive teleoperation:
+```
+@inproceedings{Havoutis17ICRA,
+ author="Havoutis, I. and Calinon, S.",
+ title="Supervisory teleoperation with online learning and optimal control",
+ booktitle=ICRA,
+ year="2017",
+ month="May-June",
+ address="Singapore",
+ pages="1534--1540"
+}
+```
-- *demo_teleop*: Example of online learning of tp-hsmm model and teleoperator-like
- usage example.
+[8] Calligraphy, graffiti, handwriting movement generation:
+```
+@inproceedings{Berio17GI,
+ author="Berio, D. and Calinon, S. and Fol Leymarie, F.",
+ title="Generating Calligraphic Trajectories with Model Predictive Control",
+ booktitle="Proc. 43rd Conf. on Graphics Interface",
+ year="2017",
+ month="May",
+ address="Edmonton, AL, Canada",
+ pages=""
+}
+```
+
+[9] Adaptive assistance:
+```
+@article{Pignat17RAS,
+ author="Pignat, E. and Calinon, S.",
+ title="Learning adaptive dressing assistance from human demonstration",
+ journal="Robotics and Autonomous Systems",
+ year="2017",
+ month="July",
+ volume="93",
+ number="",
+ pages="61--75",
+ doi="10.1016/j.robot.2017.03.017",
+}
+```
-- *demo_tp_multiLqr*: online tp-hsmm and tp-gmm with lqr-based trajectory generation
- and multiframe-lqr trajectory generation.
+### List of examples
+
+This project will build a number of executables, as listed in the table below.
+
+| Filename | ref. | Description |
+|----------|------|-------------|
+| demo_dptpgmm | [9] | Online tp-gmm learning and lqr-based trajectory generation |
+| demo_glsl | [8] | Rendering example with glsl display |
+| demo_glsl_gfx | [8] | Rendering example with glsl display (using glfx) |
+| demo_LQR_infHor | [1] | Discrete infinite horizon linear quadratic regulation |
+| demo_MPC_batch_01 | [1,8] | Model predictive control (MPC) with batch linear quadratic tracking (LQT) formulation |
+| demo_MPC_iterative_01 | [1,8] | Model predictive control (MPC) with iterative linear quadratic tracking (LQT) formulation |
+| demo_MPC_semitied_01 | [5,8] | MPC with semi-tied covariances |
+| demo_MPC_velocity_01 | [1,8] | MPC with an objective including velocity tracking |
+| demo_online_gmm | [6] | Online GMM learning and LQR-based trajectory generation |
+| demo_online_hsmm | [2,7] | Online HSMM learning and sampling with LQR-based trajectory generation |
+| demo_Riemannian_cov_interp02 | [4] | Covariance interpolation on Riemannian manifold from a GMM with augmented covariances |
+| demo_Riemannian_quat_infHorLQR | [3] | Linear quadratic regulation on hypersphere (orientation as unit quaternions) by relying on Riemannian manifold and infinite-horizon LQR |
+| demo_Riemannian_sphere_infHorLQR | [3] | Linear quadratic regulation on a sphere by relying on Riemannian manifold and infinite-horizon LQR |
+| demo_teleop | [7] | Online learning of tp-hsmm model and teleoperator-like usage example |
+| demo_tp_multiLqr | [7] | Online tp-hsmm and tp-gmm with lqr-based trajectory generation and multiframe-lqr trajectory generation |
+| demo_tp_trajMpc | [7] | Online tp-hsmm learning and trajMPC-based trajectory generation when communication is cut |
-- *demo_tp_trajMpc*: online tp-hsmm learning and trajMPC-based trajectory generation
- when communication is cut.
diff --git a/src/demo_proMP01.cpp b/src/demo_proMP01.cpp
deleted file mode 100644
index 55c57a3..0000000
--- a/src/demo_proMP01.cpp
+++ /dev/null
@@ -1,468 +0,0 @@
-/*
- * demo_proMP01.cpp
- *
- * Conditioning on trajectory distributions with ProMP
- *
- * @incollection{Paraschos13,
- * title = {Probabilistic Movement Primitives},
- * author = {Paraschos, A. and Daniel, C. and Peters, J. and Neumann, G.},
- * booktitle = NIPS,
- * pages = {2616--2624},
- * year = {2013},
- * publisher = {Curran Associates, Inc.}
- * }
- * @inproceedings{Rueckert15,
- * author = "Rueckert, E. and Mundo, J. and Paraschos, A. and Peters, J. and Neumann, G.",
- * title = "Extracting Low-Dimensional Control Variables for Movement Primitives",
- * booktitle = ICRA,
- * year = "2015",
- * pages = "1511--1518",
- * address = "Seattle, WA, USA"
- * }
- *
- * Authors: Sylvain Calinon, Philip Abbet
- */
-
-
-#include <stdio.h>
-#include <armadillo>
-#include <pbdlib/demonstration.h>
-#include <pbdlib/mvn.h>
-
-#include <gfx3.h>
-#include <gfx_ui.h>
-#include <GLFW/glfw3.h>
-#include <imgui.h>
-#include <imgui_impl_glfw_gl3.h>
-
-
-using namespace pbdlib;
-
-
-/*********************************** TYPES ***********************************/
-
-struct parameters_t {
- int nb_states; // Number of components in the GMM
- int nb_var; // Dimension of position data (here: x1, x2)
- int nb_data; // Number of datapoints in a trajectory
- float dt; // Time step (without rescaling, large values such
- // as 1 has the advantage of creating clusers based
- // on position information)
-};
-
-
-/******************************** CONSTANTS **********************************/
-
-const arma::mat COLORS({
- { 0.00000, 0.00000, 1.00000},
- { 0.00000, 0.50000, 0.00000},
- { 1.00000, 0.00000, 0.00000},
- { 0.00000, 0.75000, 0.75000},
- { 0.75000, 0.00000, 0.75000},
- { 0.75000, 0.75000, 0.00000},
- { 0.25000, 0.25000, 0.25000},
- { 0.00000, 0.00000, 1.00000},
- { 0.00000, 0.50000, 0.00000},
- { 1.00000, 0.00000, 0.00000},
-});
-
-
-/****************************** HELPER FUNCTIONS *****************************/
-
-static void error_callback(int error, const char* description) {
- fprintf(stderr, "Error %d: %s\n", error, description);
-}
-
-//-----------------------------------------------
-
-// Create a demonstration (with a length of 'nb_samples') from a trajectory
-// (of any length)
-Demonstration sample_trajectory(const std::vector<arma::vec>& trajectory, int nb_samples) {
-
- // Resampling of the trajectory
- arma::vec x(trajectory.size());
- arma::vec y(trajectory.size());
- arma::vec x2(trajectory.size());
- arma::vec y2(trajectory.size());
-
- for (size_t i = 0; i < trajectory.size(); ++i) {
- x(i) = trajectory[i](0);
- y(i) = trajectory[i](1);
- }
-
- arma::vec from_indices = arma::linspace<arma::vec>(0, trajectory.size() - 1, trajectory.size());
- arma::vec to_indices = arma::linspace<arma::vec>(0, trajectory.size() - 1, nb_samples);
-
- interp1(from_indices, x, to_indices, x2, "*linear");
- interp1(from_indices, y, to_indices, y2, "*linear");
-
- // Create the demonstration
- Demonstration demo = Demonstration(2, nb_samples);
- mat& datapoints = demo.getDatapoints().getData();
- for (int i = 0; i < nb_samples; ++i) {
- datapoints(0, i) = x2[i];
- datapoints(1, i) = y2[i];
- }
-
- return demo;
-}
-
-
-/********************************* FUNCTIONS *********************************/
-
-// The actual computation
-//
-// Inputs: demos, parameters
-// Outputs: mu_mat, mu2_mat, H
-void process(std::vector<Demonstration>& demos, const parameters_t& parameters,
- arma::mat &mu_mat, arma::mat &mu2_mat, arma::mat &H) {
-
- // Create basis functions (GMM with components equally split in time)
- arma::vec timesteps = arma::linspace<arma::vec>(
- 0, parameters.nb_data - 1, parameters.nb_data
- ) * parameters.dt;
-
- arma::vec mu = arma::linspace<arma::vec>(
- timesteps(0), timesteps(timesteps.n_rows - 1), parameters.nb_states
- );
-
- arma::vec sigma = arma::ones<arma::vec>(parameters.nb_states) * 0.01;
-
- // Compute basis functions activation
- H = arma::mat(parameters.nb_states, parameters.nb_data);
-
- for (unsigned int i = 0; i < parameters.nb_states; ++i) {
- arma::colvec mu_({ mu(i) });
- arma::mat sigma_({ sigma(i) });
-
- GaussianDistribution gauss(mu_, sigma_);
-
- H.row(i) = gauss.getPDFValue(timesteps.t()).t();
- }
-
- H = H / repmat(sum(H, 0), parameters.nb_states, 1);
-
-
- //_____ ProMP __________
-
- arma::mat psi(parameters.nb_var * parameters.nb_data,
- parameters.nb_var * parameters.nb_states);
-
- for (unsigned int i = 0; i < parameters.nb_data; ++i) {
- psi.rows(i * parameters.nb_var, (i + 1) * parameters.nb_var - 1) =
- arma::kron(H.col(i).t(), arma::eye(parameters.nb_var, parameters.nb_var));
- }
-
- arma::mat w(parameters.nb_var * parameters.nb_states, demos.size());
- for (size_t i = 0; i < demos.size(); ++i) {
- w.col(i) = pinv(psi) * (arma::mat) arma::vectorise(demos[i].getDatapoints().getData());
- }
-
- // Distribution in parameter space
- arma::mat mu_w = arma::mean(w, 1);
-
- //-- First regularization term
- arma::mat sigma_w = arma::eye(parameters.nb_var * parameters.nb_states,
- parameters.nb_var * parameters.nb_states);
-
- if (w.n_cols == 1) {
- sigma_w += arma::rowvec(arma::cov(w.t()))[0];
- }
- else {
- sigma_w += arma::cov(w.t());
- }
-
- // Trajectory distribution
- mu = psi * mu_w;
-
- arma::mat sigma2 = psi * sigma_w * psi.t() + // Second regularization term
- 0.01 * arma::eye(parameters.nb_var * parameters.nb_data,
- parameters.nb_var * parameters.nb_data);
-
-
- //_____ Conditioning on trajectory distribution __________
- // (reconstruction from partial data)
-
- arma::uvec in_out = arma::linspace<arma::uvec>(
- 0, parameters.nb_data * parameters.nb_var - 1, parameters.nb_data * parameters.nb_var
- );
-
- arma::uvec in(2 * parameters.nb_var);
-
- in.head(parameters.nb_var) = in_out.head(parameters.nb_var);
- in.tail(parameters.nb_var) = in_out.tail(parameters.nb_var);
-
- arma::uvec out = in_out.subvec(parameters.nb_var, in_out.n_elem - parameters.nb_var - 1);
-
- // Input data
- arma::vec mu_in = arma::reshape(
- demos[0].getDatapoints().getData().cols(arma::uvec({0, (unsigned) parameters.nb_data - 1})) +
- arma::repmat((arma::randu(parameters.nb_var, 1) - 0.5) * 10.0, 1, 2),
- parameters.nb_var * 2, 1
- );
-
- // Gaussian conditioning with trajectory distribution
- arma::vec mu2(in_out.n_elem, fill::zeros);
-
- mu2.rows(in) = mu_in;
-
- arma::mat A = sigma_w * psi.rows(in).t(); // Used to simplify the
- arma::mat B = psi.rows(in) * sigma_w * psi.rows(in).t(); // following operation
-
- arma::mat mu_w_tmp = mu_w +
- (arma::inv(B.t()) * A.t()).t() * // == A / B (not
- (mu2.rows(in) - psi.rows(in) * mu_w); // supported by armadillo)
-
- mu2.rows(out) = psi.rows(out) * mu_w_tmp;
-
-
- //_____ Results __________
-
- mu_mat = arma::conv_to<arma::mat>::from(mu);
- mu_mat.reshape(parameters.nb_var, parameters.nb_data);
-
- mu2_mat = arma::conv_to<arma::mat>::from(mu2);
- mu2_mat.reshape(parameters.nb_var, parameters.nb_data);
-}
-
-//-----------------------------------------------
-
-int main(int argc, char **argv) {
- arma::arma_rng::set_seed_random();
-
- // Parameters
- parameters_t parameters;
- parameters.nb_states = 6;
- parameters.nb_var = 2;
- parameters.dt = 0.01;
- parameters.nb_data = 100;
-
-
- // Initialise GLFW
- glfwSetErrorCallback(error_callback);
-
- if (!glfwInit())
- return -1;
-
- glfwWindowHint(GLFW_SAMPLES, 4);
- glfwWindowHint(GLFW_CONTEXT_VERSION_MAJOR, 3);
- glfwWindowHint(GLFW_CONTEXT_VERSION_MINOR, 3);
- glfwWindowHint(GLFW_OPENGL_FORWARD_COMPAT, GL_TRUE);
- glfwWindowHint(GLFW_OPENGL_PROFILE, GLFW_OPENGL_CORE_PROFILE);
-
- // Open a window and create its OpenGL context
- GLFWwindow* window = glfwCreateWindow(
- 800, 800, "Demo Conditioning on trajectory distributions", NULL, NULL
- );
-
- glfwMakeContextCurrent(window);
-
- // Take 4k screens into account (framebuffer size != window size)
- int win_width = ImGui::GetIO().DisplaySize.x;
- int win_height = ImGui::GetIO().DisplaySize.y;
-
- int fb_width, fb_height;
- glfwGetFramebufferSize(window, &fb_width, &fb_height);
-
- // Setup GLSL
- gfx3::init();
- glEnable(GL_DEPTH_TEST);
- glEnable(GL_CULL_FACE);
- glEnable(GL_LINE_SMOOTH);
- glDepthFunc(GL_LESS);
-
- // Setup ImGui
- ImGui_ImplGlfwGL3_Init(window, true);
-
- // Creation of the Vertex Array Object (VAO)
- GLuint vertexArrayID;
- glGenVertexArrays(1, &vertexArrayID);
- glBindVertexArray(vertexArrayID);
-
-
- // Projection matrix
- arma::fmat projection = gfx3::orthographic(
- (float) fb_width, (float) fb_height, 0.1f, 10.0f);
-
- // Camera matrix
- arma::fmat view = gfx3::lookAt(
- arma::fvec({0, 0, 3}), // Position of the camera
- arma::fvec({0, 0, 0}), // Look at the origin
- arma::fvec({0, 1, 0}) // Head is up
- );
-
-
- // Loading of the shaders
- gfx3::shader_t colored_shader = gfx3::loadShader(gfx3::VERTEX_SHADER_COLORED,
- gfx3::FRAGMENT_SHADER_COLORED);
-
-
- // Main loop
- bool adding_line = false;
- std::vector<arma::vec> current_trajectory;
- std::vector< std::vector<arma::vec> > original_trajectories;
- std::vector<Demonstration> demos;
- arma::mat mu;
- arma::mat mu2;
- arma::mat H;
- int current_nb_data = parameters.nb_data;
- int current_nb_states = parameters.nb_states;
-
- while (!glfwWindowShouldClose(window)) {
- glfwPollEvents();
-
- // Detect when the window was resized
- if ((ImGui::GetIO().DisplaySize.x != win_width) ||
- (ImGui::GetIO().DisplaySize.y != win_height)) {
-
- win_width = ImGui::GetIO().DisplaySize.x;
- win_height = ImGui::GetIO().DisplaySize.y;
-
- glfwGetFramebufferSize(window, &fb_width, &fb_height);
-
- // Update the projection matrix
- projection = gfx3::orthographic(
- (float) fb_width, (float) fb_height, 0.1f, 10.0f);
- }
-
-
- // If the parameters changed, recompute
- if ((parameters.nb_data != current_nb_data) ||
- (parameters.nb_states != current_nb_states)) {
-
- demos.clear();
-
- for (size_t i = 0; i < original_trajectories.size(); ++i)
- demos.push_back(sample_trajectory(original_trajectories[i], parameters.nb_data));
-
- process(demos, parameters, mu, mu2, H);
-
- current_nb_data = parameters.nb_data;
- current_nb_states = parameters.nb_states;
- }
-
-
- // Start the rendering
- ImGui_ImplGlfwGL3_NewFrame();
- glViewport(0, 0, fb_width, fb_height);
- glClearColor(0.6f, 0.6f, 0.6f, 0.0f);
- glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
-
-
- // Draw the currently created demonstration (if any)
- if (current_trajectory.size() > 1) {
- gfx3::model_t line = gfx3::create_line(
- colored_shader, arma::fvec({0.33f, 0.97f, 0.33f}), current_trajectory);
-
- gfx3::draw(line, view, projection);
-
- gfx3::destroy(line);
- }
-
-
- // Draw the demonstrations (if any)
- for (auto iter = demos.begin(); iter != demos.end(); ++iter) {
- Datapoints& datapoints = iter->getDatapoints();
-
- for (uint i = 0; i < datapoints.getNumPOINTS(); ++i) {
- arma::fvec color = arma::conv_to<arma::fvec>::from(H.col(i).t() * COLORS.rows(0, parameters.nb_states - 1));
-
- gfx3::model_t point = gfx3::create_square(colored_shader, color, 10.0f);
-
- point.transforms.position = arma::conv_to<arma::fvec>::from(datapoints.getData(i));
- point.transforms.position.reshape(3, point.transforms.position.n_cols);
-
- gfx3::draw(point, view, projection);
-
- gfx3::destroy(point);
- }
- }
-
-
- // Draw the computed trajectories
- if (mu.n_elem > 0) {
- gfx3::model_t line = gfx3::create_line(
- colored_shader, arma::fvec({0.0f, 0.0f, 0.0f}), mu);
-
- gfx3::draw(line, view, projection);
-
- gfx3::destroy(line);
-
- line = gfx3::create_line(
- colored_shader, arma::fvec({0.8f, 0.0f, 0.0f}), mu2);
-
- gfx3::draw(line, view, projection);
-
- gfx3::destroy(line);
- }
-
-
- // Parameter window
- ImGui::SetNextWindowSize(ImVec2(400, 110));
- ImGui::Begin("Parameters", NULL,
- ImGuiWindowFlags_NoResize | ImGuiWindowFlags_NoSavedSettings |
- ImGuiWindowFlags_NoMove
- );
-
- ImGui::SliderInt("Nb states", ¶meters.nb_states, 2, 10);
- ImGui::SliderInt("Nb data", ¶meters.nb_data, 20, 300);
-
- if (ImGui::Button("Clear")){
- demos.clear();
- original_trajectories.clear();
- mu = arma::mat();
- mu2 = arma::mat();
- H = arma::mat();
- }
-
- ImGui::Text("Draw several similar trajectories");
- ImGui::End();
-
-
- // GUI rendering
- ImGui::Render();
-
- // Swap buffers
- glfwSwapBuffers(window);
-
- // Keyboard input
- if (ImGui::IsKeyPressed(GLFW_KEY_ESCAPE))
- break;
-
-
- // Left click: start a new demonstration
- if (!adding_line && ImGui::IsMouseClicked(GLFW_MOUSE_BUTTON_1)) {
- // Only if not on the UI
- if (!ImGui::GetIO().WantCaptureMouse)
- adding_line = true;
- }
-
- if (adding_line) {
- double mouse_x, mouse_y;
- glfwGetCursorPos(window, &mouse_x, &mouse_y);
-
- current_trajectory.push_back(gfx3::ui2fb({ mouse_x, mouse_y },
- win_width, win_height,
- fb_width, fb_height));
- }
-
- // Left mouse button release: end the demonstration creation
- if (adding_line && !ImGui::IsMouseDown(GLFW_MOUSE_BUTTON_1)) {
- adding_line = false;
-
- demos.push_back(sample_trajectory(current_trajectory, parameters.nb_data));
-
- original_trajectories.push_back(current_trajectory);
- current_trajectory.clear();
-
- process(demos, parameters, mu, mu2, H);
- }
- }
-
-
- // Cleanup
- ImGui_ImplGlfwGL3_Shutdown();
- glfwTerminate();
-
- return 0;
-}
--
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