281 lines
8.1 KiB
Java
281 lines
8.1 KiB
Java
/*
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* Pixel Dungeon
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* Copyright (C) 2012-2015 Oleg Dolya
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*
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* Shattered Pixel Dungeon
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* Copyright (C) 2014-2024 Evan Debenham
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>
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*/
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package com.watabou.utils;
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import com.watabou.noosa.Game;
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import java.util.ArrayDeque;
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import java.util.Collection;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.List;
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public class Random {
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//we store a stack of random number generators, which may be seeded deliberately or randomly.
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//top of the stack is what is currently being used to generate new numbers.
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//the base generator is always created with no seed, and cannot be popped.
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private static ArrayDeque<java.util.Random> generators;
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static {
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resetGenerators();
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}
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public static synchronized void resetGenerators(){
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generators = new ArrayDeque<>();
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generators.push(new java.util.Random());
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}
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public static synchronized void pushGenerator(){
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generators.push( new java.util.Random() );
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}
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public static synchronized void pushGenerator( long seed ){
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generators.push( new java.util.Random( scrambleSeed(seed) ) );
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}
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//scrambles a given seed, this helps eliminate patterns between the outputs of similar seeds
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//Algorithm used is MX3 by Jon Maiga (jonkagstrom.com), CC0 license.
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private static synchronized long scrambleSeed( long seed ){
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seed ^= seed >>> 32;
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seed *= 0xbea225f9eb34556dL;
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seed ^= seed >>> 29;
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seed *= 0xbea225f9eb34556dL;
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seed ^= seed >>> 32;
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seed *= 0xbea225f9eb34556dL;
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seed ^= seed >>> 29;
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return seed;
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}
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public static synchronized void popGenerator(){
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if (generators.size() == 1){
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Game.reportException( new RuntimeException("tried to pop the last random number generator!"));
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} else {
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generators.pop();
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}
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}
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//returns a uniformly distributed float in the range [0, 1)
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public static synchronized float Float() {
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return Float(true);
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}
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public static synchronized float Float( boolean useGeneratorStack ) {
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if (useGeneratorStack) return generators.peekFirst().nextFloat();
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else return generators.peekLast().nextFloat();
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}
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//returns a uniformly distributed float in the range [0, max)
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public static float Float( float max ) {
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return Float() * max;
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}
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//returns a uniformly distributed float in the range [min, max)
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public static float Float( float min, float max ) {
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return min + Float(max - min);
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}
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//returns a triangularly distributed float in the range [min, max)
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public static float NormalFloat( float min, float max ) {
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return min + ((Float(max - min) + Float(max - min))/2f);
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}
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//returns a uniformly distributed int in the range [-2^31, 2^31)
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public static synchronized int Int() {
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return Int(true);
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}
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//returns a uniformly distributed int in the range [-2^31, 2^31)
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//can either use the current generator in the stack, or force the first generator (pure random)
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public static synchronized int Int( boolean useGeneratorStack ) {
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if (useGeneratorStack) return generators.peekFirst().nextInt();
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else return generators.peekLast().nextInt();
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}
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//returns a uniformly distributed int in the range [0, max)
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public static synchronized int Int( int max ) {
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return Int(max, true);
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}
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//returns a uniformly distributed int in the range [0, max)
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//can either use the current generator in the stack, or force the first generator (pure random)
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public static synchronized int Int( int max, boolean useGeneratorStack ) {
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if (max <= 0) return 0;
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else if (useGeneratorStack) return generators.peekFirst().nextInt(max);
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else return generators.peekLast().nextInt(max);
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}
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//returns a uniformly distributed int in the range [min, max)
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public static int Int( int min, int max ) {
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return min + Int(max - min);
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}
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//returns a uniformly distributed int in the range [min, max]
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public static int IntRange( int min, int max ) {
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return min + Int(max - min + 1);
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}
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//returns a triangularly distributed int in the range [min, max]
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//this makes results more likely as they get closer to the middle of the range
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public static int NormalIntRange( int min, int max ) {
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return min + (int)((Float() + Float()) * (max - min + 1) / 2f);
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}
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//returns an inverse triangularly distributed int in the range [min, max]
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//this makes results more likely as they get further from the middle of the range
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public static int InvNormalIntRange( int min, int max ){
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float roll1 = Float(), roll2 = Float();
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if (Math.abs(roll1-0.5f) >= Math.abs(roll2-0.5f)){
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return min + (int)(roll1*(max - min + 1));
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} else {
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return min + (int)(roll2*(max - min + 1));
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}
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}
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//returns a uniformly distributed long in the range [-2^63, 2^63)
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public static synchronized long Long() {
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return Long(true);
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}
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//returns a uniformly distributed long in the range [-2^63, 2^63)
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//can either use the current generator in the stack, or force the first generator (pure random)
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public static synchronized long Long( boolean useGeneratorStack ) {
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if (useGeneratorStack) return generators.peekFirst().nextLong();
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else return generators.peekLast().nextLong();
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}
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//returns a mostly uniformly distributed long in the range [0, max)
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public static long Long( long max ) {
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long result = Long();
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if (result < 0) result += Long.MAX_VALUE;
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//modulo isn't perfect, but as long as max is reasonably below 2^63 it's close enough
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return result % max;
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}
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//returns an index from chances, the probability of each index is the weight values in changes
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public static int chances( float[] chances ) {
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int length = chances.length;
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float sum = 0;
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for (int i=0; i < length; i++) {
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sum += chances[i];
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}
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float value = Float( sum );
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sum = 0;
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for (int i=0; i < length; i++) {
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sum += chances[i];
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if (value < sum) {
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return i;
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}
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}
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return -1;
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}
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@SuppressWarnings("unchecked")
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//returns a key element from chances, the probability of each key is the weight value it maps to
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public static <K> K chances( HashMap<K,Float> chances ) {
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int size = chances.size();
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Object[] values = chances.keySet().toArray();
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float[] probs = new float[size];
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float sum = 0;
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for (int i=0; i < size; i++) {
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probs[i] = chances.get( values[i] );
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sum += probs[i];
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}
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if (sum <= 0) {
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return null;
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}
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float value = Float( sum );
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sum = probs[0];
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for (int i=0; i < size; i++) {
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if (value < sum) {
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return (K)values[i];
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}
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sum += probs[i + 1];
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}
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return null;
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}
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public static int index( Collection<?> collection ) {
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return Int(collection.size());
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}
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@SafeVarargs
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public static<T> T oneOf(T... array ) {
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return array[Int(array.length)];
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}
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public static<T> T element( T[] array ) {
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return element( array, array.length );
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}
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public static<T> T element( T[] array, int max ) {
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return array[Int(max)];
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}
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@SuppressWarnings("unchecked")
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public static<T> T element( Collection<? extends T> collection ) {
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int size = collection.size();
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return size > 0 ?
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(T)collection.toArray()[Int( size )] :
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null;
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}
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public synchronized static<T> void shuffle( List<?extends T> list){
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Collections.shuffle(list, generators.peek());
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}
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public static<T> void shuffle( T[] array ) {
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for (int i=0; i < array.length - 1; i++) {
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int j = Int( i, array.length );
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if (j != i) {
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T t = array[i];
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array[i] = array[j];
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array[j] = t;
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}
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}
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}
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public static<U,V> void shuffle( U[] u, V[]v ) {
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for (int i=0; i < u.length - 1; i++) {
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int j = Int( i, u.length );
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if (j != i) {
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U ut = u[i];
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u[i] = u[j];
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u[j] = ut;
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V vt = v[i];
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v[i] = v[j];
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v[j] = vt;
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}
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}
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}
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}
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