Adapt to esodata changes

3 files changed, 57 insertions, 57 deletions

diff --git a/base/src/main/java/bjc/utils/gen/RandomGrammar.java b/base/src/main/java/bjc/utils/gen/RandomGrammar.java
index 050165b..620cc5b 100644
--- a/base/src/main/java/bjc/utils/gen/RandomGrammar.java
+++ b/base/src/main/java/bjc/utils/gen/RandomGrammar.java
@@ -1,7 +1,7 @@
 package bjc.utils.gen;
 
 import bjc.funcdata.FunctionalMap;
-import bjc.funcdata.IList;
+import bjc.funcdata.ListEx;
 
 /**
  * A weighted grammar where all the rules have a equal chance of occuring.
@@ -27,8 +27,8 @@ public class RandomGrammar<E> extends WeightedGrammar<E> {
 	 *              The cases to add for this rule.
 	 */
 	@SafeVarargs
-	public final void addCases(final E rule, final IList<E>... cases) {
-		for (final IList<E> currentCase : cases) {
+	public final void addCases(final E rule, final ListEx<E>... cases) {
+		for (final ListEx<E> currentCase : cases) {
 			super.addCase(rule, 1, currentCase);
 		}
 	}
@@ -43,10 +43,10 @@ public class RandomGrammar<E> extends WeightedGrammar<E> {
 	 *              The cases to add for this rule.
 	 */
 	@SafeVarargs
-	public final void makeRule(final E rule, final IList<E>... cases) {
+	public final void makeRule(final E rule, final ListEx<E>... cases) {
 		super.addRule(rule);
 
-		for (final IList<E> currentCase : cases) {
+		for (final ListEx<E> currentCase : cases) {
 			super.addCase(rule, 1, currentCase);
 		}
 	}
@@ -60,7 +60,7 @@ public class RandomGrammar<E> extends WeightedGrammar<E> {
 	 * @param cases
 	 *              The cases to add for this rule.
 	 */
-	public void makeRule(final E rule, final IList<IList<E>> cases) {
+	public void makeRule(final E rule, final ListEx<ListEx<E>> cases) {
 		if (cases == null)
 			throw new NullPointerException("Cases must not be null");
 
diff --git a/base/src/main/java/bjc/utils/gen/WeightedGrammar.java b/base/src/main/java/bjc/utils/gen/WeightedGrammar.java
index 540efbc..48cc658 100644
--- a/base/src/main/java/bjc/utils/gen/WeightedGrammar.java
+++ b/base/src/main/java/bjc/utils/gen/WeightedGrammar.java
@@ -6,12 +6,12 @@ import java.util.function.Function;
 import java.util.function.Predicate;
 import java.util.function.Supplier;
 
-import bjc.data.IPair;
 import bjc.data.Pair;
+import bjc.data.SimplePair;
 import bjc.funcdata.FunctionalList;
 import bjc.funcdata.FunctionalMap;
-import bjc.funcdata.IList;
-import bjc.funcdata.IMap;
+import bjc.funcdata.ListEx;
+import bjc.funcdata.MapEx;
 
 /**
  * A random grammar, where certain rules will come up more often than others.
@@ -26,22 +26,22 @@ public class WeightedGrammar<E> {
 	protected String initialRule;
 
 	/** The rules currently in this grammar */
-	protected IMap<E, WeightedRandom<IList<E>>> rules;
+	protected MapEx<E, WeightedRandom<ListEx<E>>> rules;
 
 	/** The random number generator used for random numbers */
 	private Random rng;
 
 	/** All of the subgrammars of this grammar */
-	protected IMap<E, WeightedGrammar<E>> subgrammars;
+	protected MapEx<E, WeightedGrammar<E>> subgrammars;
 
 	/** Rules that require special handling */
-	private IMap<E, Supplier<IList<E>>> specialRules;
+	private MapEx<E, Supplier<ListEx<E>>> specialRules;
 
 	/** Predicate for marking special tokens */
 	private Predicate<E> specialMarker;
 
 	/** Action for special tokens */
-	private BiFunction<E, WeightedGrammar<E>, IList<E>> specialAction;
+	private BiFunction<E, WeightedGrammar<E>, ListEx<E>> specialAction;
 
 	/** Create a new weighted grammar. */
 	public WeightedGrammar() {
@@ -75,7 +75,7 @@ public class WeightedGrammar<E> {
 	 *               The action to take on those tokens.
 	 */
 	public void configureSpecial(final Predicate<E> marker,
-			final BiFunction<E, WeightedGrammar<E>, IList<E>> action) {
+			final BiFunction<E, WeightedGrammar<E>, ListEx<E>> action) {
 		specialMarker = marker;
 		specialAction = action;
 	}
@@ -89,7 +89,7 @@ public class WeightedGrammar<E> {
 	 * @param cse
 	 *                 The case for the rule.
 	 */
-	public void addSpecialRule(final E ruleName, final Supplier<IList<E>> cse) {
+	public void addSpecialRule(final E ruleName, final Supplier<ListEx<E>> cse) {
 		if (ruleName == null) {
 			throw new NullPointerException("Rule name must not be null");
 		} else if (cse == null) {
@@ -111,7 +111,7 @@ public class WeightedGrammar<E> {
 	 * @param cse
 	 *                    The case being added.
 	 */
-	public void addCase(final E ruleName, final int probability, final IList<E> cse) {
+	public void addCase(final E ruleName, final int probability, final ListEx<E> cse) {
 		if (ruleName == null) {
 			throw new NullPointerException("Rule name must be not null");
 		} else if (cse == null) {
@@ -180,7 +180,7 @@ public class WeightedGrammar<E> {
 	 *
 	 * @return Whether or not the rule was succesfully added.
 	 */
-	public boolean addRule(final E name, final WeightedRandom<IList<E>> cases) {
+	public boolean addRule(final E name, final WeightedRandom<ListEx<E>> cases) {
 		if (name == null) {
 			throw new NullPointerException("Name must not be null");
 		} else if (cases == null) {
@@ -255,13 +255,13 @@ public class WeightedGrammar<E> {
 	 *
 	 * @return A set of sentences generated by the specified rule.
 	 */
-	public IList<IList<E>> generateDebugValues(final E ruleName) {
+	public ListEx<ListEx<E>> generateDebugValues(final E ruleName) {
 		if (ruleName == null)
 			throw new NullPointerException("Rule name must not be null");
 
-		final IList<IList<E>> returnedList = new FunctionalList<>();
+		final ListEx<ListEx<E>> returnedList = new FunctionalList<>();
 
-		final WeightedRandom<IList<E>> ruleGenerator = rules.get(ruleName).get();
+		final WeightedRandom<ListEx<E>> ruleGenerator = rules.get(ruleName).get();
 
 		for (int i = 0; i < 10; i++) {
 			returnedList.add(ruleGenerator.generateValue());
@@ -288,7 +288,7 @@ public class WeightedGrammar<E> {
 	 *
 	 * @return A randomly generated sentence from the specified initial rule.
 	 */
-	public <T> IList<T> generateGenericValues(final E initRules,
+	public <T> ListEx<T> generateGenericValues(final E initRules,
 			final Function<E, T> tokenTransformer, final T spacer) {
 		if (initRules == null) {
 			throw new NullPointerException("Initial rule must not be null");
@@ -298,9 +298,9 @@ public class WeightedGrammar<E> {
 			throw new NullPointerException("Spacer must not be null");
 		}
 
-		final IList<T> returnedList = new FunctionalList<>();
+		final ListEx<T> returnedList = new FunctionalList<>();
 
-		IList<E> genRules = new FunctionalList<>(initRules);
+		ListEx<E> genRules = new FunctionalList<>(initRules);
 
 		if (specialMarker != null) {
 			if (specialMarker.test(initRules)) {
@@ -371,8 +371,8 @@ public class WeightedGrammar<E> {
 	 *
 	 * @return A list of random grammar elements generated by the specified rule.
 	 */
-	public IList<E> generateListValues(final E initRule, final E spacer) {
-		final IList<E> retList
+	public ListEx<E> generateListValues(final E initRule, final E spacer) {
+		final ListEx<E> retList
 				= generateGenericValues(initRule, strang -> strang, spacer);
 
 		return retList;
@@ -401,8 +401,8 @@ public class WeightedGrammar<E> {
 	 *
 	 * @return The set of all rule names in this grammar.
 	 */
-	public IList<E> getRuleNames() {
-		final IList<E> ruleNames = new FunctionalList<>();
+	public ListEx<E> getRuleNames() {
+		final ListEx<E> ruleNames = new FunctionalList<>();
 
 		ruleNames.addAll(rules.keyList());
 		ruleNames.addAll(specialRules.keyList());
@@ -471,19 +471,19 @@ public class WeightedGrammar<E> {
 			throw new IllegalArgumentException(
 					"Number of times to prefix must be positive.");
 
-		final WeightedRandom<IList<E>> rule = rules.get(ruleName).get();
+		final WeightedRandom<ListEx<E>> rule = rules.get(ruleName).get();
 
-		final IList<IPair<Integer, IList<E>>> newResults = new FunctionalList<>();
+		final ListEx<Pair<Integer, ListEx<E>>> newResults = new FunctionalList<>();
 
 		/*
 		 * @NOTE Can this be simplified?
 		 */
 		rule.getValues().forEach(pair -> {
-			final IList<IList<E>> newRule = new FunctionalList<>();
+			final ListEx<ListEx<E>> newRule = new FunctionalList<>();
 
 			for (int i = 1; i <= numberOfTimes; i++) {
-				final IList<E> newCase = pair.merge((left, right) -> {
-					final IList<E> returnVal = new FunctionalList<>();
+				final ListEx<E> newCase = pair.merge((left, right) -> {
+					final ListEx<E> returnVal = new FunctionalList<>();
 
 					for (final E val : right.toIterable()) {
 						returnVal.add(val);
@@ -502,7 +502,7 @@ public class WeightedGrammar<E> {
 			newRule.forEach((list) -> {
 				final Integer currentProb = pair.merge((left, right) -> left);
 
-				newResults.add(new Pair<>(currentProb + additionalProbability, list));
+				newResults.add(new SimplePair<>(currentProb + additionalProbability, list));
 			});
 		});
 
@@ -534,13 +534,13 @@ public class WeightedGrammar<E> {
 			throw new NullPointerException("Prefix token must not be null");
 		}
 
-		final WeightedRandom<IList<E>> rule = rules.get(ruleName).get();
+		final WeightedRandom<ListEx<E>> rule = rules.get(ruleName).get();
 
-		final IList<IPair<Integer, IList<E>>> newResults = new FunctionalList<>();
+		final ListEx<Pair<Integer, ListEx<E>>> newResults = new FunctionalList<>();
 
 		rule.getValues().forEach(pair -> {
-			final IList<E> newCase = pair.merge((left, right) -> {
-				final IList<E> returnVal = new FunctionalList<>();
+			final ListEx<E> newCase = pair.merge((left, right) -> {
+				final ListEx<E> returnVal = new FunctionalList<>();
 
 				for (final E val : right.toIterable()) {
 					returnVal.add(val);
@@ -551,7 +551,7 @@ public class WeightedGrammar<E> {
 
 			newCase.prepend(prefixToken);
 
-			newResults.add(new Pair<>(
+			newResults.add(new SimplePair<>(
 					pair.merge((left, right) -> left) + additionalProbability, newCase));
 		});
 
@@ -589,13 +589,13 @@ public class WeightedGrammar<E> {
 			throw new NullPointerException("Prefix token must not be null");
 		}
 
-		final WeightedRandom<IList<E>> rule = rules.get(ruleName).get();
+		final WeightedRandom<ListEx<E>> rule = rules.get(ruleName).get();
 
-		final IList<IPair<Integer, IList<E>>> newResults = new FunctionalList<>();
+		final ListEx<Pair<Integer, ListEx<E>>> newResults = new FunctionalList<>();
 
 		rule.getValues().forEach(par -> {
-			final IList<E> newCase = par.merge((left, right) -> {
-				final IList<E> returnVal = new FunctionalList<>();
+			final ListEx<E> newCase = par.merge((left, right) -> {
+				final ListEx<E> returnVal = new FunctionalList<>();
 
 				for (final E val : right.toIterable()) {
 					returnVal.add(val);
@@ -606,7 +606,7 @@ public class WeightedGrammar<E> {
 
 			newCase.add(suffixToken);
 
-			newResults.add(new Pair<>(
+			newResults.add(new SimplePair<>(
 					par.merge((left, right) -> left) + additionalProbability, newCase));
 		});
 
diff --git a/base/src/main/java/bjc/utils/gen/WeightedRandom.java b/base/src/main/java/bjc/utils/gen/WeightedRandom.java
index 969020e..01a961f 100644
--- a/base/src/main/java/bjc/utils/gen/WeightedRandom.java
+++ b/base/src/main/java/bjc/utils/gen/WeightedRandom.java
@@ -2,10 +2,10 @@ package bjc.utils.gen;
 
 import java.util.Random;
 
-import bjc.data.IPair;
 import bjc.data.Pair;
+import bjc.data.SimplePair;
 import bjc.funcdata.FunctionalList;
-import bjc.funcdata.IList;
+import bjc.funcdata.ListEx;
 
 /**
  * Represents a random number generator where certain results are weighted more
@@ -17,7 +17,7 @@ import bjc.funcdata.IList;
  *            The type of values that are randomly selected.
  */
 public class WeightedRandom<E> {
-	private final IList<IPair<Integer, E>> values;
+	private final ListEx<Pair<Integer, E>> values;
 
 	/* The source for any needed random numbers */
 	private Random source;
@@ -50,7 +50,7 @@ public class WeightedRandom<E> {
 		this(BASE);
 	}
 
-	private WeightedRandom(Random src, IList<IPair<Integer, E>> vals, int chance) {
+	private WeightedRandom(Random src, ListEx<Pair<Integer, E>> vals, int chance) {
 		source = src;
 
 		values = vals;
@@ -68,7 +68,7 @@ public class WeightedRandom<E> {
 	 *               The result to get when the chance comes up.
 	 */
 	public void addProbability(final int chance, final E result) {
-		values.add(new Pair<>(chance, result));
+		values.add(new SimplePair<>(chance, result));
 
 		totalChance += chance;
 	}
@@ -91,7 +91,7 @@ public class WeightedRandom<E> {
 	 */
 	public E generateValue(Random rn) {
 		int target = rn.nextInt(totalChance);
-		for (IPair<Integer, E> val : values) {
+		for (Pair<Integer, E> val : values) {
 			int prob = val.getLeft();
 
 			if (target < prob) {
@@ -114,8 +114,8 @@ public class WeightedRandom<E> {
 	 *
 	 * @return A list of all the values that can be generated
 	 */
-	public IList<E> getResults() {
-		return values.map(IPair::getRight);
+	public ListEx<E> getResults() {
+		return values.map(Pair::getRight);
 	}
 
 	/**
@@ -124,7 +124,7 @@ public class WeightedRandom<E> {
 	 *
 	 * @return A list of pairs of values and value probabilities
 	 */
-	public IList<IPair<Integer, E>> getValues() {
+	public ListEx<Pair<Integer, E>> getValues() {
 		return values;
 	}
 
@@ -157,7 +157,7 @@ public class WeightedRandom<E> {
 	public E getDescent(int factor, Random rn) {
 		if (values.getSize() == 0) return null;
 
-		for (IPair<Integer, E> val : values) {
+		for (Pair<Integer, E> val : values) {
 			if (rn.nextInt(factor) == 0) continue;
 
 			if (exhaust) {
@@ -169,7 +169,7 @@ public class WeightedRandom<E> {
 			return val.getRight();
 		}
 
-		IPair<Integer, E> val = values.getByIndex(values.getSize() - 1);
+		Pair<Integer, E> val = values.getByIndex(values.getSize() - 1);
 		if (exhaust) values.removeMatching(val);
 
 		return val.getRight();
@@ -231,7 +231,7 @@ public class WeightedRandom<E> {
 
 		// System.err.printf("\tTRACE: got %d success for binomial trials (%d <= 1d%d,
 		// %d times)\n", numSuc, target, bound, trials);
-		IPair<Integer, E> val = values.getByIndex(Math.min(numSuc, values.getSize() - 1));
+		Pair<Integer, E> val = values.getByIndex(Math.min(numSuc, values.getSize() - 1));
 		if (exhaust) {
 			totalChance -= val.getLeft();
 
@@ -248,8 +248,8 @@ public class WeightedRandom<E> {
 	 * @return A new WeightedRandom that is exhaustible.
 	 */
 	public WeightedRandom<E> exhaustible() {
-		IList<IPair<Integer, E>> lst = new FunctionalList<>();
-		for (IPair<Integer, E> val : values) lst.add(val);
+		ListEx<Pair<Integer, E>> lst = new FunctionalList<>();
+		for (Pair<Integer, E> val : values) lst.add(val);
 
 		WeightedRandom<E> res = new WeightedRandom<>(source, lst, totalChance);