mehr analyse, refactoringcram

Markov/src/directory/passive/markov/Builder.java

@@ -6,6 +6,7 @@ import java.util.LinkedList;
 import java.util.List;
 import java.util.Map;
 import java.util.concurrent.ThreadLocalRandom;
+import java.util.function.Function;
 
 public class Builder {
 
@@ -19,21 +20,37 @@ public class Builder {
 	}
 
 	public Collection<Map.Entry<Prefix, Token>> random() {
-		List<Map.Entry<Prefix, Token>> result = new LinkedList<>();
-		Token[] initToken = new Token[prefix_length];
-		for (int i = 0; i < prefix_length; i++) {
-			initToken[i] = Token.START;
+		return produce(p -> nextRandom(p));
 	}
-		Prefix p = new Prefix(initToken);
+
+	public Collection<Map.Entry<Prefix, Token>> average() {
+		return produce(p -> data.fetch(p).average());
+	}
+
+	private Collection<Map.Entry<Prefix, Token>> produce(
+			Function<Prefix, Token> producer) {
+		List<Map.Entry<Prefix, Token>> result = new LinkedList<>();
+		Prefix p = initPrefix();
 		Token t = Token.START;
-		while (t != Token.END) {
-			t = nextRandom(p);
+		for (int i = 0; i < 200; i++) {
+			if (t == Token.END)
+				break;
+			t = producer.apply(p);
 			result.add(new AbstractMap.SimpleEntry<Prefix, Token>(p, t));
 			p = p.slide(t);
 		}
 		return result;
 	}
 
+	private Prefix initPrefix() {
+		Token[] initToken = new Token[prefix_length];
+		for (int i = 0; i < prefix_length; i++) {
+			initToken[i] = Token.START;
+		}
+		Prefix p = new Prefix(initToken);
+		return p;
+	}
+
 	private Token nextRandom(Prefix prefix) {
 		return data.fetch(prefix).forRandom(nextRandomNumber());
 	}

Markov/src/directory/passive/markov/Data.java

 package directory.passive.markov;
 
+import java.util.Arrays;
 import java.util.HashMap;
 import java.util.Map;
 import java.util.stream.Collectors;
@@ -19,12 +20,20 @@ public class Data {
 		return data.get(p);
 	}
 
+	public Lookup info(Token... t) {
+		return data.get(new Prefix(t));
+	}
+
+	public Lookup info(String... s) {
+		return data.get(new Prefix(Arrays.stream(s).map(t -> new Token(t))
+				.collect(Collectors.toList())));
+	}
+
 	@Override
 	public String toString() {
 		return "Data [data=" + data + "]";
 	}
 
-	
 	public String dumpStats() {
 		return "Total hits: "
 				+ data.entrySet().stream()

Markov/src/directory/passive/markov/Lookup.java

@@ -2,6 +2,7 @@ package directory.passive.markov;
 
 import java.util.LinkedHashMap;
 import java.util.Map.Entry;
+import java.util.stream.Collectors;
 
 // FIXME rename
 public class Lookup {
@@ -25,15 +26,15 @@ public class Lookup {
 		return tokens.size();
 	}
 
+	int getAmount(Token t) {
+		return tokens.getOrDefault(t, 0);
+	}
+
 	public void add(Token t) {
 		Integer i = tokens.getOrDefault(t, 0);
 		tokens.put(t, i + 1);
 	}
 
-	public int getAmount(Token t) {
-		return tokens.getOrDefault(t, 0);
-	}
-
 	public Token forRandom(double random) {
 		int id = (int) Math.floor(random * getTotalCounts());
 		int i = 0;
@@ -49,9 +50,23 @@ public class Lookup {
 
 	}
 
+	public Token average() {
+		return tokens
+				.entrySet().stream().sorted((e1, e2) -> Integer
+						.compare(e2.getValue(), e1.getValue()))
+				.findFirst().get().getKey();
+	}
+
 	@Override
 	public String toString() {
-		return "Lookup [tokens=" + tokens + "]";
+		return "Lookup [tokens= "
+				+ tokens.entrySet().stream()
+						.sorted((e1, e2) -> Integer.compare(e2.getValue(),
+								e1.getValue()))
+						.map(e -> String.format("%d*%s", e.getValue(),
+								e.getKey()))
+						.collect(Collectors.joining(", "))
+				+ "]";
 	}
 
 }

Markov/src/directory/passive/markov/Main.java

@@ -3,14 +3,19 @@ package directory.passive.markov;
 public class Main {
 
 	public static void main(String[] args) {
-		int prefixLength = 1;
+		int prefixLength = 2;
 		Data data = new Parser(prefixLength).parse(input);
 		Builder b = new Builder(prefixLength, data);
-		Renderer r = new Renderer(data);
+		Renderer r = new Renderer(data, Renderer.Options.FULL);
 		for (int i = 0; i < 25; i++) {
 			System.out.println(r.render(b.random()));
 		}
-		System.out.println(data.dumpStats());
+		// Collection<Entry<Prefix, Token>> a = b.average();
+		// System.out.println("average: " + r.render(a));
+		// for (Entry<Prefix, Token> e : a) {
+		// System.out.println(e.getKey() + " -> " + data.fetch(e.getKey()));
+		// }
+		// System.out.println(data.dumpStats());
 	}
 
 	private static final String input = "Kai☺UWE empfiehlt \"langsam ist Präzise und Präzise ist schnell\" zu verinnerlichen.\n"

Markov/src/directory/passive/markov/Renderer.java

@@ -4,14 +4,38 @@ import java.util.Collection;
 import java.util.Map.Entry;
 
 public class Renderer {
+	public static class Options {
+		private final boolean propability;
+		private final boolean possibilities;
+
+		public Options(boolean propability, boolean possibilities) {
+			super();
+			this.propability = propability;
+			this.possibilities = possibilities;
+		}
+
+		public static final Options NONE = new Options(false, false);
+		public static final Options FULL = new Options(true, true);
+
+	}
+
 	private final Data data;
+	private final Options options;
 
 	public Renderer(Data data) {
 		super();
 		this.data = data;
+		this.options = Options.NONE;
+	}
+
+	public Renderer(Data data, Options options) {
+		super();
+		this.data = data;
+		this.options = options;
 	}
 
 	public String render(Collection<Entry<Prefix, Token>> collection) {
+
 		double p = 1;
 		StringBuilder sb = new StringBuilder();
 		sb.append("KAI-uwe empfiehlt");
@@ -20,6 +44,7 @@ public class Renderer {
 			int possibilities = lookup.getDistinctTokens();
 			p *= (double) lookup.getAmount(t.getValue())
 					/ (double) lookup.getTotalCounts();
+			if (options.possibilities) {
 
 				if (possibilities <= 1) {
 					sb.append("-");
@@ -42,9 +67,12 @@ public class Renderer {
 				} else {
 					sb.append(" ");
 				}
-			sb.append(t.getValue().render(""));
 			}
+			sb.append(t.getValue().render(" "));
+		}
+		if (options.propability) {
 			sb.append(" - " + p);
+		}
 		return sb.toString();
 	}