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@ -1,5 +1,5 @@
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cmake_minimum_required(VERSION 3.25)
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cmake_minimum_required(VERSION 3.25)
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project(COSC-4P80-Assignment-3 VERSION 0.0.21)
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project(COSC-4P80-Assignment-3 VERSION 0.0.22)
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FIND_PACKAGE_ARGS)
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FetchContent_MakeAvailable(implot)
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FetchContent_MakeAvailable(implot)
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FetchContent_Declare(matplotplusplus
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GIT_REPOSITORY https://github.com/alandefreitas/matplotplusplus
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GIT_TAG v1.2.1
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FIND_PACKAGE_ARGS)
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FetchContent_MakeAvailable(matplotplusplus)
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@ -26,7 +32,7 @@ add_executable(COSC-4P80-Assignment-3 ${PROJECT_BUILD_FILES} ${IM_PLOT_FILES})
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target_compile_options(COSC-4P80-Assignment-3 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
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target_compile_options(COSC-4P80-Assignment-3 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
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target_link_options(COSC-4P80-Assignment-3 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
|
target_link_options(COSC-4P80-Assignment-3 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
|
||||||
|
|
||||||
target_link_libraries(COSC-4P80-Assignment-3 PRIVATE BLT_WITH_GRAPHICS)
|
target_link_libraries(COSC-4P80-Assignment-3 PRIVATE BLT_WITH_GRAPHICS matplot)
|
||||||
|
|
||||||
if (${ENABLE_ADDRSAN} MATCHES ON)
|
if (${ENABLE_ADDRSAN} MATCHES ON)
|
||||||
target_compile_options(COSC-4P80-Assignment-3 PRIVATE -fsanitize=address)
|
target_compile_options(COSC-4P80-Assignment-3 PRIVATE -fsanitize=address)
|
||||||
|
|
|
||||||
|
|
@ -21,6 +21,7 @@
|
||||||
|
|
||||||
#include <assign3/fwdecl.h>
|
#include <assign3/fwdecl.h>
|
||||||
#include <blt/std/ranges.h>
|
#include <blt/std/ranges.h>
|
||||||
|
#include <memory>
|
||||||
|
|
||||||
namespace assign3
|
namespace assign3
|
||||||
{
|
{
|
||||||
|
|
@ -58,6 +59,8 @@ namespace assign3
|
||||||
[[nodiscard]] virtual Scalar distance(blt::span<const Scalar> x, blt::span<const Scalar> y) const = 0;
|
[[nodiscard]] virtual Scalar distance(blt::span<const Scalar> x, blt::span<const Scalar> y) const = 0;
|
||||||
|
|
||||||
virtual ~distance_function_t() = default;
|
virtual ~distance_function_t() = default;
|
||||||
|
|
||||||
|
static std::unique_ptr<distance_function_t> from_shape(shape_t shape, blt::u32 som_width, blt::u32 som_height);
|
||||||
};
|
};
|
||||||
|
|
||||||
struct euclidean_distance_function_t : public distance_function_t
|
struct euclidean_distance_function_t : public distance_function_t
|
||||||
|
|
|
||||||
|
|
@ -90,21 +90,7 @@ namespace assign3
|
||||||
|
|
||||||
void regenerate_network()
|
void regenerate_network()
|
||||||
{
|
{
|
||||||
switch (static_cast<shape_t>(selected_som_mode))
|
distance_function = distance_function_t::from_shape(static_cast<shape_t>(selected_som_mode), som_width, som_height);
|
||||||
{
|
|
||||||
case shape_t::GRID:
|
|
||||||
distance_function = std::make_unique<euclidean_distance_function_t>();
|
|
||||||
break;
|
|
||||||
case shape_t::GRID_WRAP:
|
|
||||||
distance_function = std::make_unique<toroidal_euclidean_distance_function_t>(som_width, som_height);
|
|
||||||
break;
|
|
||||||
case shape_t::GRID_OFFSET:
|
|
||||||
distance_function = std::make_unique<axial_distance_function_t>();
|
|
||||||
break;
|
|
||||||
case shape_t::GRID_OFFSET_WRAP:
|
|
||||||
distance_function = std::make_unique<toroidal_axial_distance_function_t>(som_width, som_height);
|
|
||||||
break;
|
|
||||||
}
|
|
||||||
som = std::make_unique<som_t>(motor_data.files[currently_selected_network], som_width, som_height, max_epochs,
|
som = std::make_unique<som_t>(motor_data.files[currently_selected_network], som_width, som_height, max_epochs,
|
||||||
distance_function.get(), topology_function.get(), static_cast<shape_t>(selected_som_mode),
|
distance_function.get(), topology_function.get(), static_cast<shape_t>(selected_som_mode),
|
||||||
static_cast<init_t>(selected_init_type), normalize_init);
|
static_cast<init_t>(selected_init_type), normalize_init);
|
||||||
|
|
|
||||||
|
|
@ -42,12 +42,18 @@ namespace assign3
|
||||||
|
|
||||||
Scalar topological_error();
|
Scalar topological_error();
|
||||||
|
|
||||||
|
Scalar quantization_error();
|
||||||
|
|
||||||
void compute_neuron_activations(Scalar distance = 2, Scalar activation = 0.5);
|
void compute_neuron_activations(Scalar distance = 2, Scalar activation = 0.5);
|
||||||
|
|
||||||
void write_activations(std::ostream& out);
|
void write_activations(std::ostream& out);
|
||||||
|
|
||||||
void write_topology_errors(std::ostream& out);
|
void write_topology_errors(std::ostream& out);
|
||||||
|
|
||||||
|
void write_quantization_errors(std::ostream& out);
|
||||||
|
|
||||||
|
void write_all_errors(std::ostream& out);
|
||||||
|
|
||||||
[[nodiscard]] const array_t& get_array() const
|
[[nodiscard]] const array_t& get_array() const
|
||||||
{ return array; }
|
{ return array; }
|
||||||
|
|
||||||
|
|
@ -60,6 +66,9 @@ namespace assign3
|
||||||
[[nodiscard]] const std::vector<Scalar>& get_topological_errors() const
|
[[nodiscard]] const std::vector<Scalar>& get_topological_errors() const
|
||||||
{ return topological_errors; }
|
{ return topological_errors; }
|
||||||
|
|
||||||
|
[[nodiscard]] const std::vector<Scalar>& get_quantization_errors() const
|
||||||
|
{ return quantization_errors; }
|
||||||
|
|
||||||
private:
|
private:
|
||||||
array_t array;
|
array_t array;
|
||||||
data_file_t file;
|
data_file_t file;
|
||||||
|
|
@ -68,7 +77,11 @@ namespace assign3
|
||||||
distance_function_t* dist_func;
|
distance_function_t* dist_func;
|
||||||
topology_function_t* topology_function;
|
topology_function_t* topology_function;
|
||||||
|
|
||||||
|
// normalized value for which below this will be considered neural
|
||||||
|
float quantization_distance = 0.25;
|
||||||
|
|
||||||
std::vector<Scalar> topological_errors;
|
std::vector<Scalar> topological_errors;
|
||||||
|
std::vector<Scalar> quantization_errors;
|
||||||
};
|
};
|
||||||
|
|
||||||
}
|
}
|
||||||
|
|
|
||||||
|
|
@ -88,4 +88,20 @@ namespace assign3
|
||||||
Scalar total = x_min + y_min;
|
Scalar total = x_min + y_min;
|
||||||
return total - std::min(x_min, y_min);
|
return total - std::min(x_min, y_min);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
std::unique_ptr<distance_function_t> distance_function_t::from_shape(shape_t shape, blt::u32 som_width, blt::u32 som_height)
|
||||||
|
{
|
||||||
|
switch (shape)
|
||||||
|
{
|
||||||
|
case shape_t::GRID:
|
||||||
|
return std::make_unique<euclidean_distance_function_t>();
|
||||||
|
case shape_t::GRID_WRAP:
|
||||||
|
return std::make_unique<toroidal_euclidean_distance_function_t>(som_width, som_height);
|
||||||
|
case shape_t::GRID_OFFSET:
|
||||||
|
return std::make_unique<axial_distance_function_t>();
|
||||||
|
case shape_t::GRID_OFFSET_WRAP:
|
||||||
|
return std::make_unique<toroidal_axial_distance_function_t>(som_width, som_height);
|
||||||
|
}
|
||||||
|
return nullptr;
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
@ -1,125 +0,0 @@
|
||||||
#include <blt/std/logging.h>
|
|
||||||
#include <blt/parse/argparse.h>
|
|
||||||
#include <blt/gfx/window.h>
|
|
||||||
#include "blt/gfx/renderer/resource_manager.h"
|
|
||||||
#include "blt/gfx/renderer/camera.h"
|
|
||||||
#include "implot.h"
|
|
||||||
#include <assign3/file.h>
|
|
||||||
#include <assign3/manager.h>
|
|
||||||
|
|
||||||
using namespace assign3;
|
|
||||||
|
|
||||||
blt::gfx::matrix_state_manager global_matrices;
|
|
||||||
blt::gfx::resource_manager resources;
|
|
||||||
blt::gfx::first_person_camera_2d camera;
|
|
||||||
assign3::motor_data_t data{};
|
|
||||||
assign3::renderer_t renderer{data, resources, global_matrices};
|
|
||||||
|
|
||||||
void init(const blt::gfx::window_data&)
|
|
||||||
{
|
|
||||||
using namespace blt::gfx;
|
|
||||||
BLT_INFO("Hello World!");
|
|
||||||
|
|
||||||
global_matrices.create_internals();
|
|
||||||
resources.load_resources();
|
|
||||||
renderer.create();
|
|
||||||
|
|
||||||
ImPlot::CreateContext();
|
|
||||||
}
|
|
||||||
|
|
||||||
void update(const blt::gfx::window_data& window_data)
|
|
||||||
{
|
|
||||||
using namespace blt::gfx;
|
|
||||||
global_matrices.update_perspectives(window_data.width, window_data.height, 90, 0.1, 2000);
|
|
||||||
|
|
||||||
camera.update();
|
|
||||||
camera.update_view(global_matrices);
|
|
||||||
global_matrices.update();
|
|
||||||
|
|
||||||
renderer.render();
|
|
||||||
}
|
|
||||||
|
|
||||||
void destroy(const blt::gfx::window_data&)
|
|
||||||
{
|
|
||||||
global_matrices.cleanup();
|
|
||||||
resources.cleanup();
|
|
||||||
renderer.cleanup();
|
|
||||||
ImPlot::DestroyContext();
|
|
||||||
blt::gfx::cleanup();
|
|
||||||
BLT_INFO("Goodbye World!");
|
|
||||||
}
|
|
||||||
|
|
||||||
void load_data_files(const std::string& str)
|
|
||||||
{
|
|
||||||
data.files = assign3::data_file_t::load_data_files_from_path(str);
|
|
||||||
for (auto& v : data.files)
|
|
||||||
v = v.normalize();
|
|
||||||
data.update();
|
|
||||||
}
|
|
||||||
|
|
||||||
void action_start_graphics(const std::vector<std::string>& argv_vector)
|
|
||||||
{
|
|
||||||
blt::arg_parse parser{};
|
|
||||||
|
|
||||||
parser.addArgument(blt::arg_builder{"--file", "-f"}
|
|
||||||
.setDefault("../data")
|
|
||||||
.setHelp("Path to data files").build());
|
|
||||||
|
|
||||||
auto args = parser.parse_args(argv_vector);
|
|
||||||
|
|
||||||
load_data_files(args.get<std::string>("file"));
|
|
||||||
|
|
||||||
blt::gfx::init(blt::gfx::window_data{"My Sexy Window", init, update, destroy}.setSyncInterval(1).setMaximized(true));
|
|
||||||
}
|
|
||||||
|
|
||||||
void action_test(const std::vector<std::string>& argv_vector)
|
|
||||||
{
|
|
||||||
blt::arg_parse parser{};
|
|
||||||
|
|
||||||
parser.addArgument(blt::arg_builder{"--file", "-f"}
|
|
||||||
.setDefault("../data")
|
|
||||||
.setHelp("Path to data files").build());
|
|
||||||
|
|
||||||
auto args = parser.parse_args(argv_vector);
|
|
||||||
|
|
||||||
load_data_files(args.get<std::string>("file"));
|
|
||||||
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
void action_convert(const std::vector<std::string>& argv_vector)
|
|
||||||
{
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
int main(int argc, const char** argv)
|
|
||||||
{
|
|
||||||
std::vector<std::string> argv_vector;
|
|
||||||
for (int i = 0; i < argc; i++)
|
|
||||||
argv_vector.emplace_back(argv[i]);
|
|
||||||
|
|
||||||
blt::arg_parse parser{};
|
|
||||||
|
|
||||||
parser.addArgument(blt::arg_builder{"action"}
|
|
||||||
.setAction(blt::arg_action_t::SUBCOMMAND)
|
|
||||||
.setHelp("Action to run. Can be: [graphics, test, convert]").build());
|
|
||||||
|
|
||||||
auto args = parser.parse_args(argv_vector);
|
|
||||||
|
|
||||||
if (!args.contains("action"))
|
|
||||||
{
|
|
||||||
BLT_ERROR("Please provide an action");
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
argv_vector.erase(argv_vector.begin() + 1);
|
|
||||||
|
|
||||||
auto action = blt::string::toLowerCase(args.get<std::string>("action"));
|
|
||||||
if (action == "graphics")
|
|
||||||
action_start_graphics(argv_vector);
|
|
||||||
else if (action == "test")
|
|
||||||
action_test(argv_vector);
|
|
||||||
else if (action == "convert")
|
|
||||||
action_convert(argv_vector);
|
|
||||||
|
|
||||||
}
|
|
||||||
136
src/main.cpp
136
src/main.cpp
|
|
@ -6,6 +6,11 @@
|
||||||
#include "implot.h"
|
#include "implot.h"
|
||||||
#include <assign3/file.h>
|
#include <assign3/file.h>
|
||||||
#include <assign3/manager.h>
|
#include <assign3/manager.h>
|
||||||
|
#include <thread>
|
||||||
|
#include <mutex>
|
||||||
|
#include <fstream>
|
||||||
|
#include <filesystem>
|
||||||
|
#include <matplot/matplot.h>
|
||||||
|
|
||||||
using namespace assign3;
|
using namespace assign3;
|
||||||
|
|
||||||
|
|
@ -73,6 +78,32 @@ void action_start_graphics(const std::vector<std::string>& argv_vector)
|
||||||
blt::gfx::init(blt::gfx::window_data{"My Sexy Window", init, update, destroy}.setSyncInterval(1).setMaximized(true));
|
blt::gfx::init(blt::gfx::window_data{"My Sexy Window", init, update, destroy}.setSyncInterval(1).setMaximized(true));
|
||||||
}
|
}
|
||||||
|
|
||||||
|
struct activation
|
||||||
|
{
|
||||||
|
Scalar x, y, act;
|
||||||
|
};
|
||||||
|
|
||||||
|
struct task_t // NOLINT
|
||||||
|
{
|
||||||
|
data_file_t* file;
|
||||||
|
blt::u32 width, height;
|
||||||
|
blt::size_t max_epochs;
|
||||||
|
shape_t shape;
|
||||||
|
init_t init;
|
||||||
|
Scalar initial_learn_rate;
|
||||||
|
|
||||||
|
task_t() = default; // NOLINT
|
||||||
|
|
||||||
|
task_t(data_file_t* file, blt::u32 width, blt::u32 height, size_t maxEpochs, shape_t shape, init_t init, Scalar initial_learn_rate):
|
||||||
|
file(file), width(width), height(height), max_epochs(maxEpochs), shape(shape), init(init), initial_learn_rate(initial_learn_rate)
|
||||||
|
{}
|
||||||
|
|
||||||
|
gaussian_function_t topology_func{};
|
||||||
|
std::vector<std::vector<Scalar>> topological_errors{};
|
||||||
|
std::vector<std::vector<Scalar>> quantization_errors{};
|
||||||
|
std::vector<std::vector<activation>> activations{};
|
||||||
|
};
|
||||||
|
|
||||||
void action_test(const std::vector<std::string>& argv_vector)
|
void action_test(const std::vector<std::string>& argv_vector)
|
||||||
{
|
{
|
||||||
blt::arg_parse parser{};
|
blt::arg_parse parser{};
|
||||||
|
|
@ -86,7 +117,112 @@ void action_test(const std::vector<std::string>& argv_vector)
|
||||||
|
|
||||||
load_data_files(args.get<std::string>("file"));
|
load_data_files(args.get<std::string>("file"));
|
||||||
|
|
||||||
|
std::vector<task_t> tasks;
|
||||||
|
std::vector<std::thread> threads;
|
||||||
|
std::mutex task_mutex;
|
||||||
|
|
||||||
|
tasks.emplace_back(&data.files[1], 5, 5, 1000, shape_t::GRID, init_t::RANDOM_DATA, 0.1);
|
||||||
|
|
||||||
|
static blt::size_t runs = 30;
|
||||||
|
|
||||||
|
for (blt::size_t i = 0; i < std::thread::hardware_concurrency(); i++)
|
||||||
|
{
|
||||||
|
threads.emplace_back([&task_mutex, &tasks]() {
|
||||||
|
do
|
||||||
|
{
|
||||||
|
task_t task;
|
||||||
|
{
|
||||||
|
std::scoped_lock lock(task_mutex);
|
||||||
|
if (tasks.empty())
|
||||||
|
break;
|
||||||
|
task = std::move(tasks.back());
|
||||||
|
tasks.pop_back();
|
||||||
|
}
|
||||||
|
|
||||||
|
for (blt::size_t i = 0; i < runs; i++)
|
||||||
|
{
|
||||||
|
gaussian_function_t func{};
|
||||||
|
auto dist = distance_function_t::from_shape(task.shape, task.width, task.height);
|
||||||
|
std::unique_ptr<som_t> som = std::make_unique<som_t>(*task.file, task.width, task.height, task.max_epochs, dist.get(),
|
||||||
|
&task.topology_func, task.shape, task.init, false);
|
||||||
|
while (som->get_current_epoch() < som->get_max_epochs())
|
||||||
|
som->train_epoch(task.initial_learn_rate);
|
||||||
|
som->compute_neuron_activations();
|
||||||
|
|
||||||
|
task.topological_errors.push_back(som->get_topological_errors());
|
||||||
|
task.quantization_errors.push_back(som->get_quantization_errors());
|
||||||
|
std::vector<activation> acts;
|
||||||
|
for (const auto& neuron : som->get_array().get_map())
|
||||||
|
acts.push_back({neuron.get_x(), neuron.get_y(), neuron.get_activation()});
|
||||||
|
task.activations.emplace_back(std::move(acts));
|
||||||
|
}
|
||||||
|
std::stringstream paths;
|
||||||
|
paths << "./bins-" << task.file->data_points.begin()->bins.size() << "/";
|
||||||
|
paths << task.width << "x" << task.height << '-' << task.max_epochs << '/';
|
||||||
|
std::string shape_name = shape_names[static_cast<int>(task.shape)];
|
||||||
|
blt::string::replaceAll(shape_name, " ", "-");
|
||||||
|
paths << shape_name << '/';
|
||||||
|
std::string init_name = init_names[static_cast<int>(task.init)];
|
||||||
|
blt::string::replaceAll(init_name, " ", "-");
|
||||||
|
paths << init_name << '-' << task.initial_learn_rate << '/';
|
||||||
|
auto path = paths.str();
|
||||||
|
std::filesystem::create_directories(path);
|
||||||
|
|
||||||
|
std::vector<Scalar> average_topological_errors;
|
||||||
|
std::vector<Scalar> average_quantization_errors;
|
||||||
|
std::vector<activation> average_activations;
|
||||||
|
|
||||||
|
average_topological_errors.resize(task.topological_errors.begin()->size());
|
||||||
|
average_quantization_errors.resize(task.quantization_errors.begin()->size());
|
||||||
|
average_activations.resize(task.activations.begin()->size());
|
||||||
|
|
||||||
|
for (const auto& vec : task.topological_errors)
|
||||||
|
for (auto [index, v] : blt::enumerate(vec))
|
||||||
|
average_topological_errors[index] += v;
|
||||||
|
for (const auto& vec : task.quantization_errors)
|
||||||
|
for (auto [index, v] : blt::enumerate(vec))
|
||||||
|
average_quantization_errors[index] += v;
|
||||||
|
for (const auto& vec : task.activations)
|
||||||
|
for (auto [index, v] : blt::enumerate(vec))
|
||||||
|
average_activations[index].act += v.act;
|
||||||
|
|
||||||
|
for (auto& v : average_topological_errors)
|
||||||
|
v /= static_cast<Scalar>(runs);
|
||||||
|
for (auto& v : average_quantization_errors)
|
||||||
|
v /= static_cast<Scalar>(runs);
|
||||||
|
for (auto& v : average_activations)
|
||||||
|
v.act /= static_cast<Scalar>(runs);
|
||||||
|
|
||||||
|
auto f = matplot::figure();
|
||||||
|
f->tiledlayout(2, 1);
|
||||||
|
auto axis = f->add_axes();
|
||||||
|
axis->hold(true);
|
||||||
|
axis->plot(matplot::linspace(0, static_cast<double>(task.max_epochs)), average_topological_errors)->display_name("Topological Error");
|
||||||
|
axis->title("Error");
|
||||||
|
axis->xlabel("Epoch");
|
||||||
|
axis->ylabel("Error");
|
||||||
|
axis->grid(true);
|
||||||
|
axis->plot(matplot::linspace(0, static_cast<double>(task.max_epochs)), average_quantization_errors)->display_name("Quantization Error");
|
||||||
|
f->title("Topological and Quantization Errors, " + std::to_string(runs) + " Runs");
|
||||||
|
|
||||||
|
f->save((path + "errors_plot.eps"), "postscript");
|
||||||
|
f->save((path + "errors_plot.tex"), "epslatex");
|
||||||
|
f->save((path + "errors_plot.png"), "png");
|
||||||
|
|
||||||
|
BLT_INFO("Task '%s' Complete", path.c_str());
|
||||||
|
|
||||||
|
} while (true);
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
while (!threads.empty())
|
||||||
|
{
|
||||||
|
if (threads.back().joinable())
|
||||||
|
{
|
||||||
|
threads.back().join();
|
||||||
|
threads.pop_back();
|
||||||
|
}
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
void action_convert(const std::vector<std::string>& argv_vector)
|
void action_convert(const std::vector<std::string>& argv_vector)
|
||||||
|
|
|
||||||
|
|
@ -225,9 +225,15 @@ namespace assign3
|
||||||
ImPlot::EndPlot();
|
ImPlot::EndPlot();
|
||||||
}
|
}
|
||||||
ImPlot::SetNextAxesLimits(0, max_epochs, 0, 1, ImPlotCond_Once);
|
ImPlot::SetNextAxesLimits(0, max_epochs, 0, 1, ImPlotCond_Once);
|
||||||
if (ImPlot::BeginPlot("Error"))
|
if (ImPlot::BeginPlot("TError"))
|
||||||
{
|
{
|
||||||
ImPlot::PlotLine("##error", som->get_topological_errors().data(), static_cast<int>(som->get_topological_errors().size()));
|
ImPlot::PlotLine("##Terror", som->get_topological_errors().data(), static_cast<int>(som->get_topological_errors().size()));
|
||||||
|
ImPlot::EndPlot();
|
||||||
|
}
|
||||||
|
ImPlot::SetNextAxesLimits(0, max_epochs, 0, static_cast<int>(current_data_file.data_points.size()), ImPlotCond_Once);
|
||||||
|
if (ImPlot::BeginPlot("QError"))
|
||||||
|
{
|
||||||
|
ImPlot::PlotLine("##Qerror", som->get_quantization_errors().data(), static_cast<int>(som->get_quantization_errors().size()));
|
||||||
ImPlot::EndPlot();
|
ImPlot::EndPlot();
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
|
||||||
|
|
@ -34,7 +34,7 @@ namespace assign3
|
||||||
break;
|
break;
|
||||||
case init_t::RANDOM_DATA:
|
case init_t::RANDOM_DATA:
|
||||||
{
|
{
|
||||||
static std::vector<Scalar> min_values, max_values;
|
static thread_local std::vector<Scalar> min_values, max_values;
|
||||||
min_values.clear();
|
min_values.clear();
|
||||||
max_values.clear();
|
max_values.clear();
|
||||||
|
|
||||||
|
|
|
||||||
47
src/som.cpp
47
src/som.cpp
|
|
@ -22,6 +22,7 @@
|
||||||
#include <blt/iterator/enumerate.h>
|
#include <blt/iterator/enumerate.h>
|
||||||
#include <blt/std/logging.h>
|
#include <blt/std/logging.h>
|
||||||
#include <cstring>
|
#include <cstring>
|
||||||
|
#include "blt/iterator/zip.h"
|
||||||
|
|
||||||
namespace assign3
|
namespace assign3
|
||||||
{
|
{
|
||||||
|
|
@ -34,6 +35,7 @@ namespace assign3
|
||||||
for (auto& v : array.get_map())
|
for (auto& v : array.get_map())
|
||||||
v.randomize(std::random_device{}(), init, normalize, file);
|
v.randomize(std::random_device{}(), init, normalize, file);
|
||||||
topological_errors.push_back(topological_error());
|
topological_errors.push_back(topological_error());
|
||||||
|
quantization_errors.push_back(quantization_error());
|
||||||
}
|
}
|
||||||
|
|
||||||
void som_t::train_epoch(Scalar initial_learn_rate)
|
void som_t::train_epoch(Scalar initial_learn_rate)
|
||||||
|
|
@ -66,6 +68,7 @@ namespace assign3
|
||||||
}
|
}
|
||||||
current_epoch++;
|
current_epoch++;
|
||||||
topological_errors.push_back(topological_error());
|
topological_errors.push_back(topological_error());
|
||||||
|
quantization_errors.push_back(quantization_error());
|
||||||
}
|
}
|
||||||
|
|
||||||
blt::size_t som_t::get_closest_neuron(const std::vector<Scalar>& data)
|
blt::size_t som_t::get_closest_neuron(const std::vector<Scalar>& data)
|
||||||
|
|
@ -222,5 +225,49 @@ namespace assign3
|
||||||
out << i << ',' << v << '\n';
|
out << i << ',' << v << '\n';
|
||||||
}
|
}
|
||||||
|
|
||||||
|
void som_t::write_quantization_errors(std::ostream& out)
|
||||||
|
{
|
||||||
|
out << "epoch,error\n";
|
||||||
|
for (auto [i, v] : blt::enumerate(quantization_errors))
|
||||||
|
out << i << ',' << v << '\n';
|
||||||
|
}
|
||||||
|
|
||||||
|
void som_t::write_all_errors(std::ostream& out)
|
||||||
|
{
|
||||||
|
out << "epoch,topology error,quantization error\n";
|
||||||
|
for (auto [i, v] : blt::in_pairs(topological_errors, quantization_errors).enumerate())
|
||||||
|
{
|
||||||
|
auto [t, q] = v;
|
||||||
|
out << i << ',' << t << ',' << q << '\n';
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
Scalar som_t::quantization_error()
|
||||||
|
{
|
||||||
|
Scalar incorrect = 0;
|
||||||
|
|
||||||
|
for (const auto& point : file.data_points)
|
||||||
|
{
|
||||||
|
const auto& nearest = array.get_map()[get_closest_neuron(point.bins)];
|
||||||
|
|
||||||
|
bool is_neural = nearest.get_activation() > -quantization_distance && nearest.get_activation() < quantization_distance;
|
||||||
|
|
||||||
|
if (is_neural)
|
||||||
|
{
|
||||||
|
incorrect++;
|
||||||
|
continue;
|
||||||
|
}
|
||||||
|
|
||||||
|
bool is_bad = nearest.get_activation() <= -quantization_distance;
|
||||||
|
bool is_good = nearest.get_activation() >= quantization_distance;
|
||||||
|
|
||||||
|
if ((is_bad && point.is_bad) || (is_good && !point.is_bad))
|
||||||
|
continue;
|
||||||
|
incorrect++;
|
||||||
|
}
|
||||||
|
|
||||||
|
return incorrect;
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
}
|
}
|
||||||
Loading…
Reference in New Issue