package de.unidue.ltl.escrito.examples.local.models;

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;

public class TrainConfig {

	/*
	 * each declared field must correspond exactly to one column in
	 * the CSV-file where the training configurations are specified otherwise
	 * reflection cannot be used as intended in TrainAndSaveModel.java 
	 */
	
	String datasetName;
	String prompt;
	int nGrams;
	int nReferences;
	String kernelClass;
	double C;
	double E;
	
	public TrainConfig(String datasetName, String prompt, int nGrams, int nReferences, 
			String kernelClass, double C, double E) {
		this.datasetName = datasetName;
		this.prompt = prompt;
		this.nGrams = nGrams;
		this.nReferences = nReferences;
		this.kernelClass = kernelClass;
		this.C = C;
		this.E = E;
	}

	public String toString() {
		return "[dataset: " + this.datasetName + "; prompt: " + this.prompt + "; nGrams: "
				+ this.nGrams + "; nReferences: " + this.nReferences + "; kernelClass: " 
				+ this.kernelClass + "; C: " + C + "; E: " + E +"]";
	}
	
	
	public static TrainConfig[] createTrainConfigsFromCSV(String pathToConfigCSVFile) {
		
		ArrayList<TrainConfig> trainConfigs = new ArrayList<>();
		
		try(BufferedReader br = new BufferedReader(new  FileReader(pathToConfigCSVFile))) {
				// read first line, which is the header
				String line = br.readLine();
				
				while ((line = br.readLine()) != null) {
					if (line.startsWith("#")) {
						continue; // ignore lines starting with #
					}
					String[] configParts = line.split(",");
					TrainConfig trainConfig = new TrainConfig(
							configParts[0], // datasetName
							configParts[1], // prompt
							Integer.parseInt(configParts[2]), // nGrams
							Integer.parseInt(configParts[3]), // nReferences
							configParts[4], // kernelClass
							Double.parseDouble(configParts[5]), // C
							Double.parseDouble(configParts[6]) // E
							);
					trainConfigs.add(trainConfig);
					}
				
			} catch (IOException e) {
				System.out.println("Error while reading " + pathToConfigCSVFile);
				e.printStackTrace();
		}
		// return array containing TrainConfig objects
		return trainConfigs.toArray(new TrainConfig[trainConfigs.size()]);
		
	}


}