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test: ⚡
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@@ -1,117 +0,0 @@
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#include "ArffFiles.h"
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#include <fstream>
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#include <sstream>
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#include <map>
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#include <iostream>
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using namespace std;
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ArffFiles::ArffFiles()
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{
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}
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vector<string> ArffFiles::getLines()
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{
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return lines;
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}
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unsigned long int ArffFiles::getSize()
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{
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return lines.size();
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}
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vector<tuple<string, string>> ArffFiles::getAttributes()
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{
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return attributes;
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}
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string ArffFiles::getClassName()
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{
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return className;
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}
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string ArffFiles::getClassType()
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{
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return classType;
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}
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vector<vector<float>>& ArffFiles::getX()
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{
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return X;
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}
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vector<int>& ArffFiles::getY()
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{
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return y;
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}
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void ArffFiles::load(string fileName, bool classLast)
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{
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ifstream file(fileName);
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string keyword, attribute, type;
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if (file.is_open()) {
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string line;
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while (getline(file, line)) {
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if (line[0] == '%' || line.empty() || line == "\r" || line == " ") {
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continue;
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}
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if (line.find("@attribute") != string::npos || line.find("@ATTRIBUTE") != string::npos) {
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stringstream ss(line);
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ss >> keyword >> attribute >> type;
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attributes.push_back(make_tuple(attribute, type));
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continue;
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}
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if (line[0] == '@') {
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continue;
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}
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lines.push_back(line);
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}
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file.close();
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if (attributes.empty())
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throw invalid_argument("No attributes found");
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if (classLast) {
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className = get<0>(attributes.back());
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classType = get<1>(attributes.back());
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attributes.pop_back();
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} else {
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className = get<0>(attributes.front());
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classType = get<1>(attributes.front());
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attributes.erase(attributes.begin());
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}
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generateDataset(classLast);
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} else
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throw invalid_argument("Unable to open file");
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}
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void ArffFiles::generateDataset(bool classLast)
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{
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X = vector<vector<float>>(attributes.size(), vector<float>(lines.size()));
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vector<string> yy = vector<string>(lines.size(), "");
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int labelIndex = classLast ? attributes.size() : 0;
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for (int i = 0; i < lines.size(); i++) {
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stringstream ss(lines[i]);
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string value;
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int pos = 0, xIndex = 0;
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while (getline(ss, value, ',')) {
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if (pos++ == labelIndex) {
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yy[i] = value;
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} else {
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X[xIndex++][i] = stof(value);
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}
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}
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}
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y = factorize(yy);
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}
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string ArffFiles::trim(const string& source)
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{
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string s(source);
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s.erase(0, s.find_first_not_of(" \n\r\t"));
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s.erase(s.find_last_not_of(" \n\r\t") + 1);
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return s;
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}
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vector<int> ArffFiles::factorize(const vector<string>& labels_t)
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{
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vector<int> yy;
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yy.reserve(labels_t.size());
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map<string, int> labelMap;
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int i = 0;
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for (string label : labels_t) {
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if (labelMap.find(label) == labelMap.end()) {
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labelMap[label] = i++;
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}
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yy.push_back(labelMap[label]);
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}
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return yy;
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}
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@@ -1,28 +0,0 @@
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#ifndef ARFFFILES_H
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#define ARFFFILES_H
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#include <string>
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#include <vector>
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#include <tuple>
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using namespace std;
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class ArffFiles {
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private:
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vector<string> lines;
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vector<tuple<string, string>> attributes;
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string className, classType;
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vector<vector<float>> X;
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vector<int> y;
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void generateDataset(bool);
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public:
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ArffFiles();
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void load(string, bool = true);
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vector<string> getLines();
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unsigned long int getSize();
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string getClassName();
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string getClassType();
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string trim(const string&);
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vector<vector<float>>& getX();
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vector<int>& getY();
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vector<tuple<string, string>> getAttributes();
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vector<int> factorize(const vector<string>& labels_t);
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};
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#endif
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@@ -3,4 +3,4 @@ project(main)
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set(CMAKE_CXX_STANDARD 14)
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add_executable(sample sample.cpp ArffFiles.cpp ../src/cppmdlp/Metrics.cpp ../src/cppmdlp/CPPFImdlp.cpp)
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add_executable(sample sample.cpp ../src/cppmdlp/tests/ArffFiles.cpp ../src/cppmdlp/Metrics.cpp ../src/cppmdlp/CPPFImdlp.cpp)
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@@ -1,4 +1,4 @@
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#include "ArffFiles.h"
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#include "../src/cppmdlp/tests/ArffFiles.h"
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#include <iostream>
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#include <vector>
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#include <iomanip>
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@@ -14,10 +14,8 @@ datasets = {
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}
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ap = argparse.ArgumentParser()
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ap.add_argument("--proposal", action="store_const", const=1)
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ap.add_argument("--original", dest="proposal", action="store_const", const=0)
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ap.add_argument(
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"--alternative", dest="proposal", action="store_const", const=2
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"--alternative", dest="proposal", action="store_const", const=1
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)
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ap.add_argument("dataset", type=str, choices=datasets.keys())
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args = ap.parse_args()
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@@ -32,7 +30,7 @@ class_name = df.columns.to_list()[class_column]
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X = df.drop(class_name, axis=1)
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y, _ = pd.factorize(df[class_name])
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X = X.to_numpy()
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test = FImdlp(proposal=args.proposal)
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test = FImdlp(algorithm=args.proposal if args.proposal is not None else 0)
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now = time.time()
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test.fit(X, y)
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fit_time = time.time()
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