list/src/main/java/data/StatisticsNew.java

package data;

import static gui.ValidationUtil.*;

import java.io.UnsupportedEncodingException;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
import java.util.regex.Pattern;

import org.apache.commons.lang3.StringUtils;
import org.apache.commons.lang3.tuple.ImmutablePair;
import org.apache.commons.lang3.tuple.Pair;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;

import alg.inflectedJOS.WordFormation;
import data.Enums.WordLevelType;
import javafx.collections.ObservableList;
import util.Export;
import util.Util;
import util.db.RDB;

@SuppressWarnings("Duplicates")
public class StatisticsNew {
	public final static Logger logger = LogManager.getLogger(StatisticsNew.class);

	private Corpus corpus;
	private Filter filter;

	private String resultTitle;
	private Map<String, AtomicLong> result;
	private Map<String, Map<MultipleHMKeys, AtomicLong>> taxonomyResult;
	private Object[][] resultCustom; // for when calculating percentages that don't add up to 100%
	private Map<String, ConcurrentHashMap<MultipleHMKeys, AtomicLong>> resultNestedSuffix;
	private Map<String, ConcurrentHashMap<MultipleHMKeys, AtomicLong>> resultNestedPrefix;
	private boolean useDB;
	private RDB db;
	private boolean analysisProducedResults;
	private LocalDateTime time;

	public StatisticsNew(Corpus corpus, Filter filter, boolean useDB) {
		this.corpus = corpus;
		this.filter = filter;
		this.taxonomyResult = new ConcurrentHashMap<>();
		this.taxonomyResult.put("Total", new ConcurrentHashMap<>());

		// create table for counting word occurances per taxonomies

		if (this.filter.getTaxonomy().isEmpty()) {
			for (int i = 0; i < this.corpus.getTaxonomy().size(); i++) {
				this.taxonomyResult.put(this.corpus.getTaxonomy().get(i), new ConcurrentHashMap<>());
			}
		} else {
			for (int i = 0; i < this.filter.getTaxonomy().size(); i++) {
				Tax taxonomy = new Tax();
				this.taxonomyResult.put(taxonomy.getLongTaxonomyName(this.filter.getTaxonomy().get(i)), new ConcurrentHashMap<>());
			}
		}

		if (useDB) {
			this.useDB = true;
			db = new RDB();
		}

		if (filter.getAl() == AnalysisLevel.WORD_LEVEL) {
			resultNestedSuffix = new ConcurrentHashMap<>();
			resultNestedPrefix = new ConcurrentHashMap<>();
		} else {
			result = new ConcurrentHashMap<>();
		}

		resultTitle = generateResultTitle();

		logger.debug(toString());
	}

	/**
	 * Result's title consists of:
	 * <ul>
	 * <li>Corpus type</li>
	 * <li>Analysis level</li>
	 * <li>Calculate for</li>
	 * <li></li>
	 * <li></li>
	 * <li></li>
	 * <li></li>
	 * </ul>
	 *
	 * @return
	 */
	private String generateResultTitle() {
		String separator = "_";
		StringBuilder sb = new StringBuilder();

		if (filter.getAl() == AnalysisLevel.STRING_LEVEL) {
			Integer ngramLevel = filter.getNgramValue();
			if(ngramLevel == 0) {
				sb.append(corpus.getCorpusType().toString())
						.append(separator)
						.append("crke")
						.append(separator)
						.append(filter.getCalculateFor())
						.append(separator);
			} else if(ngramLevel == 1) {
				sb.append(corpus.getCorpusType().toString())
						.append(separator)
						.append("besede")
						.append(separator)
						.append(filter.getCalculateFor())
						.append(separator);
			}
			else {
				sb.append(filter.getAl().toString())
						.append(separator)
						.append(corpus.getCorpusType().toString())
						.append(separator);
				sb.append(filter.getCalculateFor().toString())
						.append(separator);
				// ngram value
				sb.append(filter.getNgramValue()).append("-gram")
						.append(separator);
				sb.append(filter.getSkipValue()).append("-preskok")
						.append(separator);
			}
			// TODO: assure skip is not null but zero

		} else {
			sb.append(filter.getAl().toString()) // analysis level
					.append(separator)
					.append(corpus.getCorpusType().toString())
					.append(separator);
		}
		// skip value
		// msd ?
		// if taxonomy -> taxonomy
		// if cvv -> cvv + dolžina

		this.time = this.time != null ? this.time : LocalDateTime.now();

		sb.append(time.format(DateTimeFormatter.ofPattern("dd.MM.yyyy_hh.mm.ss")));
		return sb.toString();

	}

	public boolean isAnalysisProducedResults() {
		return analysisProducedResults;
	}

	public void setAnalysisProducedResults(boolean analysisProducedResults) {
		this.analysisProducedResults = analysisProducedResults;
	}

	public String toString() {
		String newLine = "\n\t- ";
		StringBuilder sb = new StringBuilder();
		sb.append(newLine).append("Statistic properties:");
		sb.append(newLine).append(corpus.getCorpusType().toString()).append(String.format(" (%d files)", corpus.getDetectedCorpusFiles().size()));
		sb.append(newLine).append(useDB ? "use DB" : "run in memory");
		sb.append(newLine).append(filter.toString());

		return sb.toString();
	}

	public String getResultTitle() {
		return resultTitle;
	}

	// ****************************************
	// ***************** util *****************
	// ****************************************

	/**
	 * Stores results from this batch to a database and clears results map
	 */
	public void storeTmpResultsToDB() {
		try {
			db.writeBatch(result);
			result = new ConcurrentHashMap<>();
		} catch (UnsupportedEncodingException e) {
			logger.error("Store tmp results to DB", e);
			// e.printStackTrace();
		}
	}

	public Filter getFilter() {
		return filter;
	}

	public Corpus getCorpus() {
		return corpus;
	}

	public boolean saveResultToDisk(int... limit) throws UnsupportedEncodingException {
		Set<Pair<String, Map<MultipleHMKeys, Long>>> stats = new HashSet<>();

		if (useDB) {
			result = db.getDump();
			db.delete();
		}

		// if no results and nothing to save, return false
		if (!(taxonomyResult.get("Total").size() > 0)) {
			analysisProducedResults = false;
			return false;
		} else {
			analysisProducedResults = true;
		}

		stats.add(ImmutablePair.of(resultTitle, getSortedResult(taxonomyResult.get("Total"), Util.getValidInt(limit))));
		Export.SetToCSV(stats, corpus.getChosenResultsLocation(), headerInfoBlock(), taxonomyResult);
		return true;
	}

	public boolean saveResultNestedToDisk(int... limit) throws UnsupportedEncodingException {
		resultTitle = generateResultTitle();

		if (useDB) {
			result = db.getDump();
			db.delete();
		}
		Map<WordLevelType, Map<String, Map<String, Long>>> results = new HashMap<>();

		// UNCOMMENT!!!!!!
//		if (!isEmpty(resultNestedSuffix)) {
//			results.put(WordLevelType.SUFFIX, sortNestedMap(resultNestedSuffix, Util.getValidInt(limit)));
//		}
//
//		if (!isEmpty(resultNestedPrefix)) {
//			results.put(WordLevelType.PREFIX, sortNestedMap(resultNestedPrefix, Util.getValidInt(limit)));
//		}

		// if no results and nothing to save, return false
		if (!(results.size() > 0)) {
			analysisProducedResults = false;
			return false;
		} else {
			analysisProducedResults = true;
		}

		Export.nestedMapToCSV(resultTitle, results, corpus.getChosenResultsLocation(), headerInfoBlock());
		return true;
	}

	public boolean recalculateAndSaveResultToDisk() throws UnsupportedEncodingException {
		filter.setAl(AnalysisLevel.WORD_FORMATION);
		resultTitle = generateResultTitle();

		if (useDB) {
			result = db.getDump();
			db.delete();
		}

		// if no results and nothing to save, return false
		if (!(result.size() > 0)) {
			analysisProducedResults = false;
			return false;
		} else {
			analysisProducedResults = true;
		}

		WordFormation.calculateStatistics(this);

		Export.SetToCSV(resultTitle, resultCustom, corpus.getChosenResultsLocation(), headerInfoBlock());
		return true;
	}

	private Map<String, Map<MultipleHMKeys, Long>> sortNestedMap(Map<String, ConcurrentHashMap<MultipleHMKeys, AtomicLong>> nestedMap, int limit) {
		Map<String, Map<MultipleHMKeys, Long>> sorted = new HashMap<>();

		for (String s : nestedMap.keySet()) {
			sorted.put(s, getSortedResult(nestedMap.get(s), Util.getValidInt(limit)));
		}

		return sorted;
	}


	private Map<MultipleHMKeys, Long> getSortedResult(Map<MultipleHMKeys, AtomicLong> map, int limit) {
		return Util.sortByValue(Util.atomicInt2StringAndInt(map), limit);
	}

	public void updateTaxonomyResults(MultipleHMKeys o, List<String> taxonomy) {
		for (String key : taxonomyResult.keySet()) {
			// first word should have the same taxonomy as others
			if (taxonomy.contains(key) || key.equals("Total")) {
				// if taxonomy not in map and in this word
				AtomicLong r = taxonomyResult.get(key).putIfAbsent(o, new AtomicLong(1));

				if (r != null)
					taxonomyResult.get(key).get(o).incrementAndGet();
			} else {
				// if taxonomy not in map and not in this word
				AtomicLong r = taxonomyResult.get(key).putIfAbsent(o, new AtomicLong(0));
			}
		}

		// if not in map


		// else

	}

	public void updateResults(String o) {
		// if not in map
		AtomicLong r = result.putIfAbsent(o, new AtomicLong(1));

		// else
		if (r != null)
			result.get(o).incrementAndGet();
	}

	public Map<String, AtomicLong> getResult() {
		return result;
	}

	public Object[][] getResultCustom() {
		return resultCustom;
	}

	public void setResultCustom(Object[][] resultCustom) {
		this.resultCustom = resultCustom;
	}

	public void updateResultsNested(WordLevelType type, String key, String stringValue) {
		ConcurrentHashMap<String, ConcurrentHashMap<String, AtomicLong>> resultsMap;

		if (type == WordLevelType.SUFFIX) {
			updateResultsNestedSuffix(key, stringValue);
		} else if (type == WordLevelType.PREFIX) {
			updateResultsNestedPrefix(key, stringValue);
		}
	}

	public void updateResultsNestedSuffix(String key, String stringValue) {
		MultipleHMKeys mkStringValue = new MultipleHMKeys(stringValue);

		if (resultNestedSuffix.containsKey(key)) {
			// if not in map
			AtomicLong r = resultNestedSuffix.get(key).putIfAbsent(mkStringValue, new AtomicLong(1));

			// else
			if (r != null) {
				resultNestedSuffix.get(key).get(stringValue).incrementAndGet();
			}
		} else {
			resultNestedSuffix.putIfAbsent(key, new ConcurrentHashMap<>());
			AtomicLong r = resultNestedSuffix.get(key).putIfAbsent(mkStringValue, new AtomicLong(1));

			if (r != null) {
				resultNestedSuffix.get(key).get(stringValue).incrementAndGet();
			}
		}
	}

	public void updateResultsNestedPrefix(String key, String stringValue) {
		MultipleHMKeys mkStringValue = new MultipleHMKeys(stringValue);

		if (resultNestedPrefix.containsKey(key)) {
			// if not in map
			AtomicLong r = resultNestedPrefix.get(key).putIfAbsent(mkStringValue, new AtomicLong(1));

			// else
			if (r != null) {
				resultNestedPrefix.get(key).get(stringValue).incrementAndGet();
			}
		} else {
			resultNestedPrefix.putIfAbsent(key, new ConcurrentHashMap<>());
			AtomicLong r = resultNestedPrefix.get(key).putIfAbsent(mkStringValue, new AtomicLong(1));

			if (r != null) {
				resultNestedPrefix.get(key).get(stringValue).incrementAndGet();
			}
		}
	}

	private LinkedHashMap<String, String> headerInfoBlock() {
		LinkedHashMap<String, String> info = new LinkedHashMap<>();

		info.put("Korpus:", corpus.getCorpusType().toString());
		info.put("Datum:", time.format(DateTimeFormatter.ofPattern("dd.MM.yyyy hh:mm")));
		if (filter.getAl() == AnalysisLevel.STRING_LEVEL) {
			Integer ngramLevel = filter.getNgramValue();
			if (ngramLevel == 0)
				info.put("Analiza:", "Črke");
			else if (ngramLevel == 1)
				info.put("Analiza", "Besede");
			else
				info.put("Analiza:", filter.getAl().toString());
		} else {
			info.put("Analiza:", filter.getAl().toString());
		}

		if (filter.getAl() == AnalysisLevel.STRING_LEVEL) {
			Integer ngramLevel = filter.getNgramValue();

			// n.gram nivo
			if (ngramLevel > 1) {
				info.put("n-gram nivo:", String.valueOf(ngramLevel));
			}

//			else if (ngramLevel == 1){
//				info.put("n-gram nivo:", "nivo besed");
//			} else {
//				info.put("n-gram nivo:", "nivo črk");
//			}
			// skip
			if (ngramLevel > 1)
				info.put("Skip:", isNotEmpty(filter.getSkipValue()) ? filter.getSkipValue().toString() : "0");

			// izračunaj za
			info.put("Izračunaj za:", filter.getCalculateFor().toString());

			// msd
			if (!isEmpty(filter.getMsd())) {
				StringBuilder msdPattern = new StringBuilder();
				for (Pattern pattern : filter.getMsd()) {
					msdPattern.append(pattern.toString()).append(" ");
				}

				info.put("MSD:", msdPattern.toString());
			}

			// taksonomija
//			if (!isEmpty(filter.getTaxonomy())) {
//				info.put("Taksonomija:", StringUtils.join(filter.getTaxonomy(), ", "));
//			}


		}

		if (isNotEmpty(filter.getTaxonomy()) && Tax.getCorpusTypesWithTaxonomy().contains(corpus.getCorpusType())) {
			ArrayList<String> tax = Tax.getTaxonomyForInfo(corpus.getCorpusType(), filter.getTaxonomy());

			info.put("Taksonomija: ", "");
			String sep = "";
			for (String s : tax) {
				info.put(sep = sep + " ", s);
			}
		}

		if (corpus.getCorpusType() == CorpusType.SOLAR) {
			HashMap<String, ObservableList<String>> filters = corpus.getSolarFilters();

			if (!isEmpty(filters)) {
				info.put("Dodatni filtri: ", "");

				for (Map.Entry<String, ObservableList<String>> f : filters.entrySet()) {
					info.put(f.getKey(), StringUtils.join(f.getValue(), ", "));
				}
			}
		}

		return info;
	}
}