Refactored results - moved to taxonomyResults

.gitignore

@@ -1,6 +1,7 @@
 # Created by .ignore support plugin (hsz.mobi)
 ### Maven template
 target/
+corpus_analyzer_jar/
 pom.xml.tag
 pom.xml.releaseBackup
 pom.xml.versionsBackup

src/main/java/alg/ngram/Ngrams.java

@@ -46,7 +46,7 @@ public class Ngrams {
 				}
 
 				// UPDATE TAXONOMY HERE!!!
-                stats.updateTaxonomyResults(wordToString(ngramCandidate, stats.getFilter().getCalculateFor()), ngramCandidate);
+                stats.updateTaxonomyResults(wordToString(ngramCandidate, stats.getFilter().getCalculateFor()), ngramCandidate.get(0).getTaxonomy());
 				stats.updateResults(wordToString(ngramCandidate, stats.getFilter().getCalculateFor()));
 			}
 		}
@@ -114,6 +114,7 @@ public class Ngrams {
 	private static void generateNgramLetterCandidates(List<Sentence> corpus, StatisticsNew stats) {
 		for (Sentence s : corpus) {
 			for (Word w : s.getWords()) {
+				List<String> taxonomy = w.getTaxonomy();
 				String word = w.getForCf(stats.getFilter().getCalculateFor(), stats.getFilter().isCvv());
 
 				// skip this iteration if:
@@ -128,6 +129,10 @@ public class Ngrams {
 
 				for (int i = 0; i < word.length() - stats.getFilter().getStringLength() + 1; i++) {
 					// TODO: locila?
+					stats.updateTaxonomyResults(word.substring(i, i + stats.getFilter().getStringLength()), taxonomy);
+//					stats.updateResults(wordToString(ngramCandidate, stats.getFilter().getCalculateFor()));
+
+
 					stats.updateResults(word.substring(i, i + stats.getFilter().getStringLength()));
 				}
 			}

src/main/java/data/MultipleHMKeys.java

@@ -0,0 +1,49 @@
+package data;
+/*
+Created for when words are sorted by multiple keys, i.e. not just lemmas but lemmas and msd simultaneously.
+*/
+final class MultipleHMKeys {
+    private final String key1, key2, key3;
+
+    public MultipleHMKeys(String key1) {
+        this.key1 = key1;
+        this.key2 = null;
+        this.key3 = null;
+    }
+
+    public MultipleHMKeys(String key1, String key2) {
+        this.key1 = key1;
+        this.key2 = key2;
+        this.key3 = null;
+    }
+
+    public MultipleHMKeys(String key1, String key2, String key3) {
+        this.key1 = key1;
+        this.key2 = key2;
+        this.key3 = key3;
+    }
+
+    public String getKey1() {
+        return key1;
+    }
+
+    public String getKey2() {
+        return key2;
+    }
+
+    public String getKey3() {
+        return key3;
+    }
+
+    @Override
+    public int hashCode() {
+        return key1.hashCode() ^ key2.hashCode() ^ key3.hashCode();
+    }
+
+    @Override
+    public boolean equals(Object obj) {
+        return (obj instanceof MultipleHMKeys) && ((MultipleHMKeys) obj).key1.equals(key1)
+                && ((MultipleHMKeys) obj).key2.equals(key2)
+                && ((MultipleHMKeys) obj).key3.equals(key3);
+    }
+}

src/main/java/data/StatisticsNew.java

@@ -45,6 +45,7 @@ public class StatisticsNew {
 		this.corpus = corpus;
 		this.filter = filter;
 		this.taxonomyResult = new ConcurrentHashMap<>();
+		this.taxonomyResult.put("Total", new ConcurrentHashMap<>());
 
 		// create table for counting word occurances per taxonomies
 
@@ -97,13 +98,18 @@ public class StatisticsNew {
 		if (filter.getAl() == AnalysisLevel.STRING_LEVEL) {
 			Integer ngramLevel = filter.getNgramValue();
 			if(ngramLevel == 0) {
-				sb.append("Crke").
-						append(separator)
-						.append(corpus.getCorpusType().toString())
+				sb.append(corpus.getCorpusType().toString())
+						.append(separator)
+						.append("crke")
+						.append(separator)
+						.append(filter.getCalculateFor())
 						.append(separator);
 			} else if(ngramLevel == 1) {
-				sb.append("Besede").append(separator)
-						.append(corpus.getCorpusType().toString())
+				sb.append(corpus.getCorpusType().toString())
+						.append(separator)
+						.append("besede")
+						.append(separator)
+						.append(filter.getCalculateFor())
 						.append(separator);
 			}
 			else {
@@ -196,14 +202,14 @@ public class StatisticsNew {
 		}
 
 		// if no results and nothing to save, return false
-		if (!(result.size() > 0)) {
+		if (!(taxonomyResult.get("Total").size() > 0)) {
 			analysisProducedResults = false;
 			return false;
 		} else {
 			analysisProducedResults = true;
 		}
 
-		stats.add(ImmutablePair.of(resultTitle, getSortedResult(result, Util.getValidInt(limit))));
+		stats.add(ImmutablePair.of(resultTitle, getSortedResult(taxonomyResult.get("Total"), Util.getValidInt(limit))));
 		Export.SetToCSV(stats, corpus.getChosenResultsLocation(), headerInfoBlock(), taxonomyResult);
 		return true;
 	}
@@ -275,10 +281,10 @@ public class StatisticsNew {
 		return Util.sortByValue(Util.atomicInt2StringAndInt(map), limit);
 	}
 
-	public void updateTaxonomyResults(String o, List<Word> ngramCandidate) {
+	public void updateTaxonomyResults(String o, List<String> taxonomy) {
 		for (String key : taxonomyResult.keySet()) {
 			// first word should have the same taxonomy as others
-			if (ngramCandidate.get(0).getTaxonomy().contains(key)) {
+			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));
 

src/main/java/data/Word.java

@@ -55,7 +55,8 @@ public class Word implements Serializable {
 	//private char besedna_vrsta;
 	public Word(String word, String lemma, String msd, List<String> taxonomy) {
 		this.lemma = lemma;
-		this.msd = normalizeMsd(msd);
+//		this.msd = normalizeMsd(msd);
+		this.msd = msd;
 		this.taxonomy = taxonomy;
 
 		// veliko zacetnico ohranimo samo za lastna imena

src/main/java/man/META-INF/MANIFEST.MF

@@ -1,3 +1,3 @@
-Manifest-Version: 1.0
-Main-Class: gui.GUIController
-
+Manifest-Version: 1.0
+Main-Class: gui.GUIController
+

src/main/java/manifest/META-INF/MANIFEST.MF

@@ -1,3 +0,0 @@
-Manifest-Version: 1.0
-Main-Class: gui.GUIController
-

src/main/java/util/Export.java

@@ -108,9 +108,11 @@ public class Export {
 			}
 			FILE_HEADER_AL.add("Skupna relativna pogostost");
 			for (String key : taxonomyResults.keySet()) {
-				FILE_HEADER_AL.add("Absolutna pogostost [" + key + "]");
-				FILE_HEADER_AL.add("Delež [" + key + "]");
-				FILE_HEADER_AL.add("Relativna pogostost [" + key + "]");
+				if(!key.equals("Total")) {
+					FILE_HEADER_AL.add("Absolutna pogostost [" + key + "]");
+					FILE_HEADER_AL.add("Delež [" + key + "]");
+					FILE_HEADER_AL.add("Relativna pogostost [" + key + "]");
+				}
 			}
 			FILE_HEADER = new String[ FILE_HEADER_AL.size() ];
 			FILE_HEADER_AL.toArray(FILE_HEADER);
@@ -160,11 +162,12 @@ public class Export {
 					dataEntry.add(formatNumberAsPercent((double) e.getValue() / num_frequencies));
 					dataEntry.add(String.format("%.2f", ((double) e.getValue() * 10000)/num_frequencies));
 					for (String key : taxonomyResults.keySet()){
-						AtomicLong frequency = taxonomyResults.get(key).get(e.getKey());
-						dataEntry.add(frequency.toString());
-						dataEntry.add(formatNumberAsPercent((double) frequency.get() / num_taxonomy_frequencies.get(key)));
-						dataEntry.add(String.format("%.2f", ((double) frequency.get() * 10000) / num_taxonomy_frequencies.get(key)));
-
+						if(!key.equals("Total")) {
+							AtomicLong frequency = taxonomyResults.get(key).get(e.getKey());
+							dataEntry.add(frequency.toString());
+							dataEntry.add(formatNumberAsPercent((double) frequency.get() / num_taxonomy_frequencies.get(key)));
+							dataEntry.add(String.format("%.2f", ((double) frequency.get() * 10000) / num_taxonomy_frequencies.get(key)));
+						}
 					}
 
 					csvFilePrinter.printRecord(dataEntry);