rmontanana/BayesNet
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Add header to grid output and report

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This commit is contained in:
Ricardo Montañana Gómez
2023-12-01 10:30:53 +01:00
parent c460ef46ed
commit 33cd32c639
3 changed files with 117 additions and 23 deletions
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92
src/Platform/GridSearch.cc
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@@ -63,7 +63,7 @@ namespace platform {
return Colors::RESET();
}
}
double GridSearch::processFile(std::string fileName, Datasets& datasets, HyperParameters& hyperparameters)
double GridSearch::processFileSingle(std::string fileName, Datasets& datasets, HyperParameters& hyperparameters)
{
// Get dataset
auto [X, y] = datasets.getTensors(fileName);
@@ -135,11 +135,8 @@ namespace platform {
}
return datasets_names;
}
void GridSearch::go()
json GridSearch::initializeResults()
{
auto datasets = Datasets(config.discretize, Paths::datasets());
auto datasets_names = processDatasets(datasets);
// Load previous results
json results;
if (config.continue_from != "No") {
@@ -149,6 +146,7 @@ namespace platform {
std::ifstream file(Paths::grid_output(config.model));
if (file.is_open()) {
results = json::parse(file);
results = results["results"];
}
}
catch (const std::exception& e) {
@@ -157,7 +155,15 @@ namespace platform {
results = json();
}
}
std::cout << "***************** Starting Gridsearch *****************" << std::endl;
return results;
}
void GridSearch::goSingle()
{
auto datasets = Datasets(config.discretize, Paths::datasets());
auto datasets_names = processDatasets(datasets);
json results = initializeResults();
std::cout << "***************** Starting Single Gridsearch *****************" << std::endl;
std::cout << "input file=" << Paths::grid_input(config.model) << std::endl;
auto grid = GridData(Paths::grid_input(config.model));
// Generate hyperparameters grid & run gridsearch
@@ -174,7 +180,7 @@ namespace platform {
if (!config.quiet)
showProgressComb(++num, totalComb, Colors::CYAN());
auto hyperparameters = platform::HyperParameters(datasets.getNames(), hyperparam_line);
double score = processFile(dataset, datasets, hyperparameters);
double score = processFileSingle(dataset, datasets, hyperparameters);
if (score > bestScore) {
bestScore = score;
bestHyperparameters = hyperparam_line;
@@ -184,20 +190,80 @@ namespace platform {
std::cout << "end." << " Score: " << setw(9) << setprecision(7) << fixed
<< bestScore << " [" << bestHyperparameters.dump() << "]" << std::endl;
}
results[dataset]["score"] = bestScore;
results[dataset]["hyperparameters"] = bestHyperparameters;
results[dataset]["date"] = get_date() + " " + get_time();
results[dataset]["grid"] = grid.getInputGrid(dataset);
json result = {
{ "score", bestScore },
{ "hyperparameters", bestHyperparameters },
{ "date", get_date() + " " + get_time() },
{ "grid", grid.getInputGrid(dataset) }
};
results[dataset] = result;
// Save partial results
save(results);
}
// Save final results
save(results);
std::cout << "***************** Ending Gridsearch *******************" << std::endl;
std::cout << "***************** Ending Single Gridsearch *******************" << std::endl;
}
void GridSearch::goNested()
{
auto datasets = Datasets(config.discretize, Paths::datasets());
auto datasets_names = processDatasets(datasets);
json results = initializeResults();
std::cout << "***************** Starting Nested Gridsearch *****************" << std::endl;
std::cout << "input file=" << Paths::grid_input(config.model) << std::endl;
auto grid = GridData(Paths::grid_input(config.model));
// Generate hyperparameters grid & run gridsearch
// Check each combination of hyperparameters for each dataset and each seed
for (const auto& dataset : datasets_names) {
auto totalComb = grid.getNumCombinations(dataset);
if (!config.quiet)
std::cout << "- " << setw(20) << left << dataset << " " << right << flush;
int num = 0;
double bestScore = 0.0;
json bestHyperparameters;
auto combinations = grid.getGrid(dataset);
for (const auto& hyperparam_line : combinations) {
if (!config.quiet)
showProgressComb(++num, totalComb, Colors::CYAN());
auto hyperparameters = platform::HyperParameters(datasets.getNames(), hyperparam_line);
double score = processFileSingle(dataset, datasets, hyperparameters);
if (score > bestScore) {
bestScore = score;
bestHyperparameters = hyperparam_line;
}
}
if (!config.quiet) {
std::cout << "end." << " Score: " << setw(9) << setprecision(7) << fixed
<< bestScore << " [" << bestHyperparameters.dump() << "]" << std::endl;
}
json result = {
{ "score", bestScore },
{ "hyperparameters", bestHyperparameters },
{ "date", get_date() + " " + get_time() },
{ "grid", grid.getInputGrid(dataset) }
};
results[dataset] = result;
// Save partial results
save(results);
}
// Save final results
save(results);
std::cout << "***************** Ending Nested Gridsearch *******************" << std::endl;
}
void GridSearch::save(json& results) const
{
std::ofstream file(Paths::grid_output(config.model));
file << results.dump(4);
json output = {
{ "model", config.model },
{ "score", config.score },
{ "discretize", config.discretize },
{ "stratified", config.stratified },
{ "n_folds", config.n_folds },
{ "seeds", config.seeds },
{ "date", get_date() + " " + get_time()},
{ "nested", config.nested},
{ "results", results }
};
file << output.dump(4);
}
} /* namespace platform */