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Author SHA1 Message Date
Brett 7b2bd7679a parker is a little bitch :3 
i love him so much
 2024-11-06 01:33:28 -05:00
Brett 062956f7d5 silly 2024-11-06 01:22:52 -05:00
12 changed files with 334 additions and 178 deletions
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164
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2
CMakeLists.txt
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@ -1,5 +1,5 @@
cmake_minimum_required(VERSION 3.25) cmake_minimum_required(VERSION 3.25)
project(COSC-4P80-Assignment-3 VERSION 0.0.5) project(COSC-4P80-Assignment-3 VERSION 0.0.7)
option(ENABLE_ADDRSAN "Enable the address sanitizer" OFF) option(ENABLE_ADDRSAN "Enable the address sanitizer" OFF)
option(ENABLE_UBSAN "Enable the ub sanitizer" OFF) option(ENABLE_UBSAN "Enable the ub sanitizer" OFF)

0
commit.py Normal file → Executable file
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70
include/assign3/array.h Normal file
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@ -0,0 +1,70 @@
#pragma once
/*
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#ifndef COSC_4P80_ASSIGNMENT_3_ARRAY_H
#define COSC_4P80_ASSIGNMENT_3_ARRAY_H
#include <assign3/fwdecl.h>
#include <assign3/neuron.h>
namespace assign3
{
class array_t
{
public:
explicit array_t(blt::size_t dimensions, blt::size_t width, blt::size_t height):
width(static_cast<blt::i64>(width)), height(static_cast<blt::i64>(height))
{
for (blt::size_t i = 0; i < width; i++)
for (blt::size_t j = 0; j < height; j++)
map.emplace_back(dimensions, i, j);
}
inline neuron_t& get(blt::size_t x, blt::size_t y)
{ return map[y * width + x]; }
[[nodiscard]] inline const neuron_t& get(blt::size_t x, blt::size_t y) const
{ return map[y * width + x]; }
[[nodiscard]] inline blt::size_t get_width() const
{ return width; }
[[nodiscard]] inline blt::size_t get_height() const
{ return height; }
[[nodiscard]] inline std::vector<neuron_t>& get_map()
{ return map; }
[[nodiscard]] inline const std::vector<neuron_t>& get_map() const
{ return map; }
private:
[[nodiscard]] inline blt::i64 wrap_width(blt::i64 x) const;
[[nodiscard]] inline blt::i64 wrap_height(blt::i64 y) const;
private:
blt::i64 width, height;
std::vector<neuron_t> map;
};
}
#endif //COSC_4P80_ASSIGNMENT_3_ARRAY_H

5
include/assign3/functions.h
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@ -26,6 +26,11 @@ namespace assign3
struct topology_function_t struct topology_function_t
{ {
/**
* @param dist input - usually the distance
* @param r time ratio - t / max_t
* @return basis results
*/
[[nodiscard]] virtual Scalar call(Scalar dist, Scalar r) const = 0; [[nodiscard]] virtual Scalar call(Scalar dist, Scalar r) const = 0;
}; };

5
include/assign3/fwdecl.h
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@ -22,6 +22,11 @@
namespace assign3 namespace assign3
{ {
using Scalar = float; using Scalar = float;
enum class shape
{
GRID, HONEYCOMB
};
} }
#endif //COSC_4P80_ASSIGNMENT_3_FWDECL_H #endif //COSC_4P80_ASSIGNMENT_3_FWDECL_H

9
include/assign3/neuron.h
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@ -36,9 +36,11 @@ namespace assign3
neuron_t& randomize(blt::size_t seed); neuron_t& randomize(blt::size_t seed);
neuron_t& update(const std::vector<Scalar>& new_data, const topology_function_t* basis_func, Scalar eta, Scalar r); neuron_t& update(const std::vector<Scalar>& new_data, Scalar dist, Scalar eta);
static Scalar distance(const neuron_t& n1, const neuron_t& n2, Scalar time_ratio); static Scalar distance(const neuron_t& n1, const neuron_t& n2);
[[nodiscard]] Scalar dist(const std::vector<Scalar>& X) const;
[[nodiscard]] inline const std::vector<Scalar>& get_data() const [[nodiscard]] inline const std::vector<Scalar>& get_data() const
{ return data; } { return data; }
@ -48,9 +50,8 @@ namespace assign3
[[nodiscard]] inline Scalar get_y() const [[nodiscard]] inline Scalar get_y() const
{ return y_pos; } { return y_pos; }
private:
[[nodiscard]] Scalar dist(const std::vector<Scalar>& X) const;
private:
Scalar x_pos, y_pos; Scalar x_pos, y_pos;
std::vector<Scalar> data; std::vector<Scalar> data;
}; };

56
include/assign3/som.h Normal file
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@ -0,0 +1,56 @@
#pragma once
/*
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#ifndef COSC_4P80_ASSIGNMENT_3_SOM_H
#define COSC_4P80_ASSIGNMENT_3_SOM_H
#include <assign3/array.h>
#include <assign3/file.h>
#include <assign3/functions.h>
namespace assign3
{
class som_t
{
public:
som_t(const data_file_t& file, blt::size_t width, blt::size_t height, blt::size_t max_epochs);
blt::size_t get_closest_neuron(const std::vector<Scalar>& data);
void train_epoch(Scalar initial_learn_rate, topology_function_t* basis_func);
[[nodiscard]] const array_t& get_array() const
{ return array; }
[[nodiscard]] blt::size_t get_current_epoch() const
{ return current_epoch; }
[[nodiscard]] blt::size_t get_max_epochs() const
{ return max_epochs; }
private:
array_t array;
data_file_t file;
blt::size_t current_epoch = 0;
blt::size_t max_epochs;
};
}
#endif //COSC_4P80_ASSIGNMENT_3_SOM_H

43
src/array.cpp Normal file
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@ -0,0 +1,43 @@
/*
* <Short Description>
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <assign3/array.h>
#include <cmath>
namespace assign3
{
blt::i64 array_t::wrap_height(blt::i64 y) const
{
if (y >= height)
return y - height;
else if (y < 0)
return height + y;
else
return y;
}
blt::i64 array_t::wrap_width(blt::i64 x) const
{
if (x >= width)
return x - width;
else if (x < 0)
return width + x;
else
return x;
}
}

57
src/main.cpp
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@ -6,9 +6,13 @@
#include "blt/gfx/renderer/batch_2d_renderer.h" #include "blt/gfx/renderer/batch_2d_renderer.h"
#include "blt/gfx/renderer/camera.h" #include "blt/gfx/renderer/camera.h"
#include <assign3/file.h> #include <assign3/file.h>
#include <assign3/som.h>
#include <imgui.h> #include <imgui.h>
std::vector<assign3::data_file_t> files; using namespace assign3;
std::vector<data_file_t> files;
std::unique_ptr<som_t> som;
blt::gfx::matrix_state_manager global_matrices; blt::gfx::matrix_state_manager global_matrices;
blt::gfx::resource_manager resources; blt::gfx::resource_manager resources;
@ -23,16 +27,67 @@ void init(const blt::gfx::window_data&)
global_matrices.create_internals(); global_matrices.create_internals();
resources.load_resources(); resources.load_resources();
renderer_2d.create(); renderer_2d.create();
blt::size_t size = 5;
som = std::make_unique<som_t>(
*std::find_if(files.begin(), files.end(), [](const data_file_t& v) { return v.data_points.begin()->bins.size() == 32; }),
size, size, 100);
} }
void update(const blt::gfx::window_data& data) void update(const blt::gfx::window_data& data)
{ {
using namespace blt::gfx;
global_matrices.update_perspectives(data.width, data.height, 90, 0.1, 2000); global_matrices.update_perspectives(data.width, data.height, 90, 0.1, 2000);
camera.update(); camera.update();
camera.update_view(global_matrices); camera.update_view(global_matrices);
global_matrices.update(); global_matrices.update();
if (ImGui::Begin("Controls"))
{
ImGui::Button("Run Epoch");
if (ImGui::IsItemClicked())
{
static gaussian_function_t func;
som->train_epoch(0.1, &func);
}
}
ImGui::End();
auto& meow = *std::find_if(files.begin(), files.end(), [](const data_file_t& v) { return v.data_points.begin()->bins.size() == 32; });
for (auto& v : som->get_array().get_map())
{
float scale = 35;
float total_good_distance = 0;
float total_bad_distance = 0;
float total_goods = 0;
float total_bads = 0;
for (auto& point : meow.data_points)
{
auto dist = v.dist(point.bins);
if (point.is_bad)
{
total_bads++;
total_bad_distance += dist;
} else
{
total_goods++;
total_good_distance += dist;
}
}
float good_ratio = total_goods > 0 ? total_good_distance / total_goods : 0;
float bad_ratio = total_bads > 0 ? total_bad_distance / total_bads : 0;
float good_to_bad = total_good_distance / total_bad_distance;
BLT_TRACE("%f %f %f", good_ratio, bad_ratio, good_to_bad);
renderer_2d.drawPointInternal(blt::make_color(good_ratio, bad_ratio, good_to_bad),
point2d_t{v.get_x() * scale + scale, v.get_y() * scale + scale, scale});
}
renderer_2d.render(data.width, data.height); renderer_2d.render(data.width, data.height);
} }

22
src/neuron.cpp
View File

@ -32,11 +32,17 @@ namespace assign3
return *this; return *this;
} }
neuron_t& neuron_t::update(const std::vector<Scalar>& new_data, const topology_function_t* basis_func, Scalar eta, Scalar r) neuron_t& neuron_t::update(const std::vector<Scalar>& new_data, Scalar dist, Scalar eta)
{ {
auto d = dist(new_data); static thread_local std::vector<Scalar> diff;
for (auto& v : data) diff.clear();
v = eta * basis_func->call(d, r);
for (auto [x, v] : blt::in_pairs(new_data, data))
diff.push_back(v - x);
for (auto [v, d] : blt::in_pairs(data, diff))
v += eta * dist * d;
return *this; return *this;
} }
@ -51,10 +57,10 @@ namespace assign3
return std::sqrt(dist); return std::sqrt(dist);
} }
Scalar neuron_t::distance(const neuron_t& n1, const neuron_t& n2, Scalar time_ratio) Scalar neuron_t::distance(const neuron_t& n1, const neuron_t& n2)
{ {
auto dist = n1.dist(n2.data); auto dx = n1.get_x() - n2.get_x();
auto dist_sq = dist * dist; auto dy = n1.get_y() - n2.get_y();
return std::exp(-time_ratio * dist_sq); return std::sqrt(dx * dx + dy * dy);
} }
} }

79
src/som.cpp Normal file
View File

@ -0,0 +1,79 @@
/*
* <Short Description>
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
#include <assign3/som.h>
#include <random>
#include <algorithm>
#include <blt/std/random.h>
#include <blt/iterator/enumerate.h>
namespace assign3
{
som_t::som_t(const data_file_t& file, blt::size_t width, blt::size_t height, blt::size_t max_epochs):
array(file.data_points.begin()->bins.size(), width, height), file(file), max_epochs(max_epochs)
{
for (auto& v : array.get_map())
v.randomize(std::random_device{}());
}
void som_t::train_epoch(Scalar initial_learn_rate, topology_function_t* basis_func)
{
blt::random::random_t rand{std::random_device{}()};
std::shuffle(file.data_points.begin(), file.data_points.end(), rand);
auto time_ratio = static_cast<Scalar>(current_epoch) / static_cast<Scalar>(max_epochs);
auto eta = initial_learn_rate * std::exp(-2 * time_ratio);
for (auto& current_data : file.data_points)
{
auto v0_idx = get_closest_neuron(current_data.bins);
auto v0 = array.get_map()[v0_idx];
v0.update(current_data.bins, 1, eta);
for (auto [i, n] : blt::enumerate(array.get_map()))
{
if (i == v0_idx)
continue;
auto dist = basis_func->call(neuron_t::distance(v0, n), time_ratio);
n.update(current_data.bins, dist, eta);
}
}
current_epoch++;
}
blt::size_t som_t::get_closest_neuron(const std::vector<Scalar>& data)
{
blt::size_t index = 0;
Scalar distance = std::numeric_limits<Scalar>::max();
for (auto [i, d] : blt::enumerate(array.get_map()))
{
auto dist = d.dist(data);
if (dist < distance)
{
index = i;
distance = dist;
}
}
return index;
}
}