Fix some lint warnings
This commit is contained in:
parent
9a0449c12d
commit
5efa3beaee
@ -20,7 +20,7 @@ namespace bayesnet {
|
||||
{
|
||||
return samples;
|
||||
}
|
||||
void Network::addNode(string name, int numStates)
|
||||
void Network::addNode(const string& name, int numStates)
|
||||
{
|
||||
if (find(features.begin(), features.end(), name) == features.end()) {
|
||||
features.push_back(name);
|
||||
@ -69,7 +69,7 @@ namespace bayesnet {
|
||||
recStack.erase(nodeId); // remove node from recursion stack before function ends
|
||||
return false;
|
||||
}
|
||||
void Network::addEdge(const string parent, const string child)
|
||||
void Network::addEdge(const string& parent, const string& child)
|
||||
{
|
||||
if (nodes.find(parent) == nodes.end()) {
|
||||
throw invalid_argument("Parent node " + parent + " does not exist");
|
||||
@ -105,8 +105,8 @@ namespace bayesnet {
|
||||
for (int i = 0; i < featureNames.size(); ++i) {
|
||||
auto column = torch::flatten(X.index({ "...", i }));
|
||||
auto k = vector<int>();
|
||||
for (auto i = 0; i < X.size(0); ++i) {
|
||||
k.push_back(column[i].item<int>());
|
||||
for (auto z = 0; z < X.size(0); ++z) {
|
||||
k.push_back(column[z].item<int>());
|
||||
}
|
||||
dataset[featureNames[i]] = k;
|
||||
}
|
||||
@ -280,7 +280,7 @@ namespace bayesnet {
|
||||
}
|
||||
return result;
|
||||
}
|
||||
vector<string> Network::graph(string title)
|
||||
vector<string> Network::graph(const string& title)
|
||||
{
|
||||
auto output = vector<string>();
|
||||
auto prefix = "digraph BayesNet {\nlabel=<BayesNet ";
|
||||
|
@ -32,8 +32,8 @@ namespace bayesnet {
|
||||
explicit Network(Network&);
|
||||
torch::Tensor& getSamples();
|
||||
float getmaxThreads();
|
||||
void addNode(string, int);
|
||||
void addEdge(const string, const string);
|
||||
void addNode(const string&, int);
|
||||
void addEdge(const string&, const string&);
|
||||
map<string, std::unique_ptr<Node>>& getNodes();
|
||||
vector<string> getFeatures();
|
||||
int getStates();
|
||||
@ -48,7 +48,7 @@ namespace bayesnet {
|
||||
vector<vector<double>> predict_proba(const vector<vector<int>>&);
|
||||
double score(const vector<vector<int>>&, const vector<int>&);
|
||||
vector<string> show();
|
||||
vector<string> graph(string title); // Returns a vector of strings representing the graph in graphviz format
|
||||
vector<string> graph(const string& title); // Returns a vector of strings representing the graph in graphviz format
|
||||
inline string version() { return "0.1.0"; }
|
||||
};
|
||||
}
|
||||
|
@ -52,9 +52,9 @@ namespace platform {
|
||||
seeds_str = trim(seeds_str);
|
||||
seeds_str = seeds_str.substr(1, seeds_str.size() - 2);
|
||||
auto seeds_str_split = split(seeds_str, ',');
|
||||
for (auto seed_str : seeds_str_split) {
|
||||
seeds.push_back(stoi(seed_str));
|
||||
}
|
||||
transform(seeds_str_split.begin(), seeds_str_split.end(), back_inserter(seeds), [](const std::string& str) {
|
||||
return stoi(str);
|
||||
});
|
||||
return seeds;
|
||||
}
|
||||
};
|
||||
|
@ -40,7 +40,7 @@ namespace platform {
|
||||
string Models::toString()
|
||||
{
|
||||
string result = "";
|
||||
for (auto& pair : functionRegistry) {
|
||||
for (const auto& pair : functionRegistry) {
|
||||
result += pair.first + ", ";
|
||||
}
|
||||
return "{" + result.substr(0, result.size() - 2) + "}";
|
||||
|
@ -49,22 +49,17 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
|
||||
}});
|
||||
auto seed_values = env.getSeeds();
|
||||
program.add_argument("-s", "--seeds").nargs(1, 10).help("Random seeds. Set to -1 to have pseudo random").scan<'i', int>().default_value(seed_values);
|
||||
bool class_last, discretize_dataset, stratified;
|
||||
int n_folds;
|
||||
vector<int> seeds;
|
||||
string model_name, file_name, path, complete_file_name, title;
|
||||
try {
|
||||
program.parse_args(argc, argv);
|
||||
file_name = program.get<string>("dataset");
|
||||
path = program.get<string>("path");
|
||||
model_name = program.get<string>("model");
|
||||
discretize_dataset = program.get<bool>("discretize");
|
||||
stratified = program.get<bool>("stratified");
|
||||
n_folds = program.get<int>("folds");
|
||||
seeds = program.get<vector<int>>("seeds");
|
||||
complete_file_name = path + file_name + ".arff";
|
||||
class_last = false;//datasets[file_name];
|
||||
title = program.get<string>("title");
|
||||
auto file_name = program.get<string>("dataset");
|
||||
auto path = program.get<string>("path");
|
||||
auto model_name = program.get<string>("model");
|
||||
auto discretize_dataset = program.get<bool>("discretize");
|
||||
auto stratified = program.get<bool>("stratified");
|
||||
auto n_folds = program.get<int>("folds");
|
||||
auto seeds = program.get<vector<int>>("seeds");
|
||||
auto complete_file_name = path + file_name + ".arff";
|
||||
auto title = program.get<string>("title");
|
||||
if (title == "" && file_name == "") {
|
||||
throw runtime_error("title is mandatory if dataset is not provided");
|
||||
}
|
||||
|
@ -2,7 +2,7 @@
|
||||
|
||||
using namespace torch;
|
||||
|
||||
vector<string> split(string text, char delimiter)
|
||||
vector<string> split(const string& text, char delimiter)
|
||||
{
|
||||
vector<string> result;
|
||||
stringstream ss(text);
|
||||
@ -39,7 +39,7 @@ vector<mdlp::labels_t> discretizeDataset(vector<mdlp::samples_t>& X, mdlp::label
|
||||
return Xd;
|
||||
}
|
||||
|
||||
bool file_exists(const std::string& name)
|
||||
bool file_exists(const string& name)
|
||||
{
|
||||
if (FILE* file = fopen(name.c_str(), "r")) {
|
||||
fclose(file);
|
||||
@ -49,7 +49,7 @@ bool file_exists(const std::string& name)
|
||||
}
|
||||
}
|
||||
|
||||
tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(string path, string name, bool class_last, bool discretize_dataset)
|
||||
tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(const string& path, const string& name, bool class_last, bool discretize_dataset)
|
||||
{
|
||||
auto handler = ArffFiles();
|
||||
handler.load(path + static_cast<string>(name) + ".arff", class_last);
|
||||
@ -59,9 +59,8 @@ tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadData
|
||||
// Get className & Features
|
||||
auto className = handler.getClassName();
|
||||
vector<string> features;
|
||||
for (auto feature : handler.getAttributes()) {
|
||||
features.push_back(feature.first);
|
||||
}
|
||||
auto attributes = handler.getAttributes();
|
||||
transform(attributes.begin(), attributes.end(), back_inserter(features), [](const auto& pair) { return pair.first; });
|
||||
Tensor Xd;
|
||||
auto states = map<string, vector<int>>();
|
||||
if (discretize_dataset) {
|
||||
@ -83,7 +82,7 @@ tuple<Tensor, Tensor, vector<string>, string, map<string, vector<int>>> loadData
|
||||
return { Xd, torch::tensor(y, torch::kInt32), features, className, states };
|
||||
}
|
||||
|
||||
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>> loadFile(string name)
|
||||
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>> loadFile(const string& name)
|
||||
{
|
||||
auto handler = ArffFiles();
|
||||
handler.load(PATH + static_cast<string>(name) + ".arff");
|
||||
@ -93,9 +92,8 @@ tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vect
|
||||
// Get className & Features
|
||||
auto className = handler.getClassName();
|
||||
vector<string> features;
|
||||
for (auto feature : handler.getAttributes()) {
|
||||
features.push_back(feature.first);
|
||||
}
|
||||
auto attributes = handler.getAttributes();
|
||||
transform(attributes.begin(), attributes.end(), back_inserter(features), [](const auto& pair) { return pair.first; });
|
||||
// Discretize Dataset
|
||||
vector<mdlp::labels_t> Xd;
|
||||
map<string, int> maxes;
|
||||
|
@ -11,11 +11,11 @@ using namespace std;
|
||||
const string PATH = "../../data/";
|
||||
|
||||
bool file_exists(const std::string& name);
|
||||
vector<string> split(string text, char delimiter);
|
||||
vector<string> split(const string& text, char delimiter);
|
||||
pair<vector<mdlp::labels_t>, map<string, int>> discretize(vector<mdlp::samples_t>& X, mdlp::labels_t& y, vector<string> features);
|
||||
vector<mdlp::labels_t> discretizeDataset(vector<mdlp::samples_t>& X, mdlp::labels_t& y);
|
||||
pair<torch::Tensor, map<string, vector<int>>> discretizeTorch(torch::Tensor& X, torch::Tensor& y, vector<string>& features, string className);
|
||||
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>> loadFile(string name);
|
||||
tuple<torch::Tensor, torch::Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(string path, string name, bool class_last, bool discretize_dataset);
|
||||
pair<torch::Tensor, map<string, vector<int>>> discretizeTorch(torch::Tensor& X, torch::Tensor& y, vector<string>& features, const string& className);
|
||||
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>> loadFile(const string& name);
|
||||
tuple<torch::Tensor, torch::Tensor, vector<string>, string, map<string, vector<int>>> loadDataset(const string& path, const string& name, bool class_last, bool discretize_dataset);
|
||||
map<string, vector<int>> get_states(vector<string>& features, string className, map<string, int>& maxes);
|
||||
#endif //PLATFORM_UTILS_H
|
||||
|
Loading…
Reference in New Issue
Block a user