rmontanana/BayesNet
rmontanana/BayesNet
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boostAode #5

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rmontanana merged 21 commits from boostAode into main 2023-08-20 09:02:08 +00:00
Conversation 0 Commits 21 Files Changed 49 +190 -46
9 changed files with 190 additions and 46 deletions
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Showing only changes of commit 9972738deb - Show all commits

8
.vscode/launch.json vendored
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@ -46,6 +46,14 @@
],
"cwd": "/Users/rmontanana/Code/discretizbench",
},
{
"type": "lldb",
"request": "launch",
"name": "list",
"program": "${workspaceFolder}/build/src/Platform/list",
"args": [],
"cwd": "/Users/rmontanana/Code/discretizbench",
},
{
"name": "Build & debug active file",
"type": "cppdbg",

23
.vscode/tasks.json vendored
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@ -32,6 +32,29 @@
],
"group": "build",
"detail": "Task generated by Debugger."
},
{
"type": "cppbuild",
"label": "C/C++: g++ build active file",
"command": "/usr/bin/g++",
"args": [
"-fdiagnostics-color=always",
"-g",
"${file}",
"-o",
"${fileDirname}/${fileBasenameNoExtension}"
],
"options": {
"cwd": "${fileDirname}"
},
"problemMatcher": [
"$gcc"
],
"group": {
"kind": "build",
"isDefault": true
},
"detail": "Task generated by Debugger."
}
]
}

4
Makefile
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@ -15,7 +15,7 @@ dependency: ## Create a dependency graph diagram of the project (build/dependenc
cd build && cmake .. --graphviz=dependency.dot && dot -Tpng dependency.dot -o dependency.png
build: ## Build the main and BayesNetSample
cmake --build build -t main -t BayesNetSample -t manage -j 32
cmake --build build -t main -t BayesNetSample -t manage -t list -j 32
clean: ## Clean the debug info
@echo ">>> Cleaning Debug BayesNet ...";
@ -35,7 +35,7 @@ release: ## Build a Release version of the project
@if [ -d ./build ]; then rm -rf ./build; fi
@mkdir build;
cmake -S . -B build -D CMAKE_BUILD_TYPE=Release; \
cmake --build build -t main -t BayesNetSample -t manage -j 32;
cmake --build build -t main -t BayesNetSample -t manage -t list -j 32;
@echo ">>> Done";
test: ## Run tests

4
src/Platform/CMakeLists.txt
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@ -6,5 +6,7 @@ include_directories(${BayesNet_SOURCE_DIR}/lib/argparse/include)
include_directories(${BayesNet_SOURCE_DIR}/lib/json/include)
add_executable(main main.cc Folding.cc platformUtils.cc Experiment.cc Datasets.cc Models.cc Report.cc)
add_executable(manage manage.cc Results.cc Report.cc)
add_executable(list list.cc platformUtils Datasets.cc)
target_link_libraries(main BayesNet ArffFiles mdlp "${TORCH_LIBRARIES}")
target_link_libraries(manage "${TORCH_LIBRARIES}")
target_link_libraries(manage "${TORCH_LIBRARIES}")
target_link_libraries(list ArffFiles mdlp "${TORCH_LIBRARIES}")

79
src/Platform/Datasets.cc
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@ -24,75 +24,110 @@ namespace platform {
transform(datasets.begin(), datasets.end(), back_inserter(result), [](const auto& d) { return d.first; });
return result;
}
vector<string> Datasets::getFeatures(string name)
vector<string> Datasets::getFeatures(const string& name) const
{
if (datasets[name]->isLoaded()) {
return datasets[name]->getFeatures();
if (datasets.at(name)->isLoaded()) {
return datasets.at(name)->getFeatures();
} else {
throw invalid_argument("Dataset not loaded.");
}
}
map<string, vector<int>> Datasets::getStates(string name)
map<string, vector<int>> Datasets::getStates(const string& name) const
{
if (datasets[name]->isLoaded()) {
return datasets[name]->getStates();
if (datasets.at(name)->isLoaded()) {
return datasets.at(name)->getStates();
} else {
throw invalid_argument("Dataset not loaded.");
}
}
string Datasets::getClassName(string name)
void Datasets::loadDataset(const string& name) const
{
if (datasets[name]->isLoaded()) {
return datasets[name]->getClassName();
if (datasets.at(name)->isLoaded()) {
return;
} else {
datasets.at(name)->load();
}
}
string Datasets::getClassName(const string& name) const
{
if (datasets.at(name)->isLoaded()) {
return datasets.at(name)->getClassName();
} else {
throw invalid_argument("Dataset not loaded.");
}
}
int Datasets::getNSamples(string name)
int Datasets::getNSamples(const string& name) const
{
if (datasets[name]->isLoaded()) {
return datasets[name]->getNSamples();
if (datasets.at(name)->isLoaded()) {
return datasets.at(name)->getNSamples();
} else {
throw invalid_argument("Dataset not loaded.");
}
}
pair<vector<vector<float>>&, vector<int>&> Datasets::getVectors(string name)
int Datasets::getNClasses(const string& name)
{
if (datasets.at(name)->isLoaded()) {
auto className = datasets.at(name)->getClassName();
if (discretize) {
auto states = getStates(name);
return states.at(className).size();
}
auto [Xv, yv] = getVectors(name);
return *max_element(yv.begin(), yv.end()) + 1;
} else {
throw invalid_argument("Dataset not loaded.");
}
}
vector<int> Datasets::getClassesCounts(const string& name) const
{
if (datasets.at(name)->isLoaded()) {
auto [Xv, yv] = datasets.at(name)->getVectors();
vector<int> counts(*max_element(yv.begin(), yv.end()) + 1);
for (auto y : yv) {
counts[y]++;
}
return counts;
} else {
throw invalid_argument("Dataset not loaded.");
}
}
pair<vector<vector<float>>&, vector<int>&> Datasets::getVectors(const string& name)
{
if (!datasets[name]->isLoaded()) {
datasets[name]->load();
}
return datasets[name]->getVectors();
}
pair<vector<vector<int>>&, vector<int>&> Datasets::getVectorsDiscretized(string name)
pair<vector<vector<int>>&, vector<int>&> Datasets::getVectorsDiscretized(const string& name)
{
if (!datasets[name]->isLoaded()) {
datasets[name]->load();
}
return datasets[name]->getVectorsDiscretized();
}
pair<torch::Tensor&, torch::Tensor&> Datasets::getTensors(string name)
pair<torch::Tensor&, torch::Tensor&> Datasets::getTensors(const string& name)
{
if (!datasets[name]->isLoaded()) {
datasets[name]->load();
}
return datasets[name]->getTensors();
}
bool Datasets::isDataset(const string& name)
bool Datasets::isDataset(const string& name) const
{
return datasets.find(name) != datasets.end();
}
Dataset::Dataset(const Dataset& dataset) : path(dataset.path), name(dataset.name), className(dataset.className), n_samples(dataset.n_samples), n_features(dataset.n_features), features(dataset.features), states(dataset.states), loaded(dataset.loaded), discretize(dataset.discretize), X(dataset.X), y(dataset.y), Xv(dataset.Xv), Xd(dataset.Xd), yv(dataset.yv), fileType(dataset.fileType)
{
}
string Dataset::getName()
string Dataset::getName() const
{
return name;
}
string Dataset::getClassName()
string Dataset::getClassName() const
{
return className;
}
vector<string> Dataset::getFeatures()
vector<string> Dataset::getFeatures() const
{
if (loaded) {
return features;
@ -100,7 +135,7 @@ namespace platform {
throw invalid_argument("Dataset not loaded.");
}
}
int Dataset::getNFeatures()
int Dataset::getNFeatures() const
{
if (loaded) {
return n_features;
@ -108,7 +143,7 @@ namespace platform {
throw invalid_argument("Dataset not loaded.");
}
}
int Dataset::getNSamples()
int Dataset::getNSamples() const
{
if (loaded) {
return n_samples;
@ -116,7 +151,7 @@ namespace platform {
throw invalid_argument("Dataset not loaded.");
}
}
map<string, vector<int>> Dataset::getStates()
map<string, vector<int>> Dataset::getStates() const
{
if (loaded) {
return states;

31
src/Platform/Datasets.h
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@ -29,15 +29,15 @@ namespace platform {
public:
Dataset(const string& path, const string& name, const string& className, bool discretize, fileType_t fileType) : path(path), name(name), className(className), discretize(discretize), loaded(false), fileType(fileType) {};
explicit Dataset(const Dataset&);
string getName();
string getClassName();
vector<string> getFeatures();
map<string, vector<int>> getStates();
string getName() const;
string getClassName() const;
vector<string> getFeatures() const;
map<string, vector<int>> getStates() const;
pair<vector<vector<float>>&, vector<int>&> getVectors();
pair<vector<vector<int>>&, vector<int>&> getVectorsDiscretized();
pair<torch::Tensor&, torch::Tensor&> getTensors();
int getNFeatures();
int getNSamples();
int getNFeatures() const;
int getNSamples() const;
void load();
const bool inline isLoaded() const { return loaded; };
};
@ -51,14 +51,17 @@ namespace platform {
public:
explicit Datasets(const string& path, bool discretize = false, fileType_t fileType = ARFF) : path(path), discretize(discretize), fileType(fileType) { load(); };
vector<string> getNames();
vector<string> getFeatures(string name);
int getNSamples(string name);
string getClassName(string name);
map<string, vector<int>> getStates(string name);
pair<vector<vector<float>>&, vector<int>&> getVectors(string name);
pair<vector<vector<int>>&, vector<int>&> getVectorsDiscretized(string name);
pair<torch::Tensor&, torch::Tensor&> getTensors(string name);
bool isDataset(const string& name);
vector<string> getFeatures(const string& name) const;
int getNSamples(const string& name) const;
string getClassName(const string& name) const;
int getNClasses(const string& name);
vector<int> getClassesCounts(const string& name) const;
map<string, vector<int>> getStates(const string& name) const;
pair<vector<vector<float>>&, vector<int>&> getVectors(const string& name);
pair<vector<vector<int>>&, vector<int>&> getVectorsDiscretized(const string& name);
pair<torch::Tensor&, torch::Tensor&> getTensors(const string& name);
bool isDataset(const string& name) const;
void loadDataset(const string& name) const;
};
};

1
src/Platform/Paths.h
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@ -1,5 +1,6 @@
#ifndef PATHS_H
#define PATHS_H
#include <string>
namespace platform {
class Paths {
public:

29
src/Platform/Report.cc
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@ -1,6 +1,9 @@
#include <sstream>
#include <locale>
#include "Report.h"
#include "BestResult.h"
namespace platform {
string headerLine(const string& text)
{
@ -31,21 +34,31 @@ namespace platform {
body();
footer();
}
struct separated : numpunct<char> {
char do_decimal_point() const { return ','; }
char do_thousands_sep() const { return '.'; }
string do_grouping() const { return "\03"; }
};
void Report::header()
{
locale mylocale(cout.getloc(), new separated);
locale::global(mylocale);
cout.imbue(mylocale);
stringstream oss;
cout << Colors::MAGENTA() << string(MAXL, '*') << endl;
cout << headerLine("Report " + data["model"].get<string>() + " ver. " + data["version"].get<string>() + " with " + to_string(data["folds"].get<int>()) + " Folds cross validation and " + to_string(data["seeds"].size()) + " random seeds. " + data["date"].get<string>() + " " + data["time"].get<string>());
cout << headerLine(data["title"].get<string>());
cout << headerLine("Random seeds: " + fromVector("seeds") + " Stratified: " + (data["stratified"].get<bool>() ? "True" : "False"));
cout << headerLine("Execution took " + to_string(data["duration"].get<float>()) + " seconds, " + to_string(data["duration"].get<float>() / 3600) + " hours, on " + data["platform"].get<string>());
oss << "Execution took " << setprecision(2) << fixed << data["duration"].get<float>() << " seconds, " << data["duration"].get<float>() / 3600 << " hours, on " << data["platform"].get<string>();
cout << headerLine(oss.str());
cout << headerLine("Score is " + data["score_name"].get<string>());
cout << string(MAXL, '*') << endl;
cout << endl;
}
void Report::body()
{
cout << Colors::GREEN() << "Dataset Sampl. Feat. Cls Nodes Edges States Score Time Hyperparameters" << endl;
cout << "============================== ====== ===== === ======= ======= ======= =============== ================== ===============" << endl;
cout << Colors::GREEN() << "Dataset Sampl. Feat. Cls Nodes Edges States Score Time Hyperparameters" << endl;
cout << "============================== ====== ===== === ========= ========= ========= =============== ================== ===============" << endl;
json lastResult;
totalScore = 0;
bool odd = true;
@ -55,9 +68,9 @@ namespace platform {
cout << setw(6) << right << r["samples"].get<int>() << " ";
cout << setw(5) << right << r["features"].get<int>() << " ";
cout << setw(3) << right << r["classes"].get<int>() << " ";
cout << setw(7) << setprecision(2) << fixed << r["nodes"].get<float>() << " ";
cout << setw(7) << setprecision(2) << fixed << r["leaves"].get<float>() << " ";
cout << setw(7) << setprecision(2) << fixed << r["depth"].get<float>() << " ";
cout << setw(9) << setprecision(2) << fixed << r["nodes"].get<float>() << " ";
cout << setw(9) << setprecision(2) << fixed << r["leaves"].get<float>() << " ";
cout << setw(9) << setprecision(2) << fixed << r["depth"].get<float>() << " ";
cout << setw(8) << right << setprecision(6) << fixed << r["score"].get<double>() << "±" << setw(6) << setprecision(4) << fixed << r["score_std"].get<double>() << " ";
cout << setw(11) << right << setprecision(6) << fixed << r["time"].get<double>() << "±" << setw(6) << setprecision(4) << fixed << r["time_std"].get<double>() << " ";
try {
@ -85,7 +98,9 @@ namespace platform {
cout << Colors::MAGENTA() << string(MAXL, '*') << endl;
auto score = data["score_name"].get<string>();
if (score == BestResult::scoreName()) {
cout << headerLine(score + " compared to " + BestResult::title() + " .: " + to_string(totalScore / BestResult::score()));
stringstream oss;
oss << score << " compared to " << BestResult::title() << " .: " << totalScore / BestResult::score();
cout << headerLine(oss.str());
}
cout << string(MAXL, '*') << endl << Colors::RESET();

57
src/Platform/list.cc Normal file
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@ -0,0 +1,57 @@
#include <iostream>
#include <locale>
#include "Paths.h"
#include "Colors.h"
#include "Datasets.h"
using namespace std;
const int BALANCE_LENGTH = 75;
struct separated : numpunct<char> {
char do_decimal_point() const { return ','; }
char do_thousands_sep() const { return '.'; }
string do_grouping() const { return "\03"; }
};
void outputBalance(const string& balance)
{
auto temp = string(balance);
while (temp.size() > BALANCE_LENGTH - 1) {
auto part = temp.substr(0, BALANCE_LENGTH);
cout << part << endl;
cout << setw(48) << " ";
temp = temp.substr(BALANCE_LENGTH);
}
cout << temp << endl;
}
int main(int argc, char** argv)
{
auto data = platform::Datasets(platform::Paths().datasets(), false);
locale mylocale(cout.getloc(), new separated);
locale::global(mylocale);
cout.imbue(mylocale);
cout << Colors::GREEN() << "Dataset Sampl. Feat. Cls. Balance" << endl;
string balanceBars = string(BALANCE_LENGTH, '=');
cout << "============================== ====== ===== === " << balanceBars << endl;
bool odd = true;
for (const auto& dataset : data.getNames()) {
auto color = odd ? Colors::CYAN() : Colors::BLUE();
cout << color << setw(30) << left << dataset << " ";
data.loadDataset(dataset);
auto nSamples = data.getNSamples(dataset);
cout << setw(6) << right << nSamples << " ";
cout << setw(5) << right << data.getFeatures(dataset).size() << " ";
cout << setw(3) << right << data.getNClasses(dataset) << " ";
stringstream oss;
string sep = "";
for (auto number : data.getClassesCounts(dataset)) {
oss << sep << setprecision(2) << fixed << (float)number / nSamples * 100.0 << "% (" << number << ")";
sep = " / ";
}
outputBalance(oss.str());
odd = !odd;
}
cout << Colors::RESET() << endl;
return 0;
}