Switch to GT XSTR

2 files changed, 1 insertions, 236 deletions

diff --git a/src/main/java/com/github/technus/tectech/TecTech.java b/src/main/java/com/github/technus/tectech/TecTech.java
index b3adb46c2c..292ebeb7e3 100644
--- a/src/main/java/com/github/technus/tectech/TecTech.java
+++ b/src/main/java/com/github/technus/tectech/TecTech.java
@@ -12,7 +12,6 @@ import com.github.technus.tectech.mechanics.enderStorage.EnderWorldSavedData;
 import com.github.technus.tectech.nei.IMCForNEI;
 import com.github.technus.tectech.proxy.CommonProxy;
 import com.github.technus.tectech.recipe.EyeOfHarmonyRecipeStorage;
-import com.github.technus.tectech.util.XSTR;
 
 import cpw.mods.fml.common.FMLCommonHandler;
 import cpw.mods.fml.common.Mod;
@@ -23,6 +22,7 @@ import cpw.mods.fml.common.event.FMLPostInitializationEvent;
 import cpw.mods.fml.common.event.FMLPreInitializationEvent;
 import eu.usrv.yamcore.auxiliary.IngameErrorLog;
 import eu.usrv.yamcore.auxiliary.LogHelper;
+import gregtech.api.objects.XSTR;
 
 @Mod(
         modid = Reference.MODID,
diff --git a/src/main/java/com/github/technus/tectech/util/XSTR.java b/src/main/java/com/github/technus/tectech/util/XSTR.java
deleted file mode 100644
index c739eb2e3e..0000000000
--- a/src/main/java/com/github/technus/tectech/util/XSTR.java
+++ /dev/null
@@ -1,235 +0,0 @@
-package com.github.technus.tectech.util;
-/*
- * A subclass of java.util.random that implements the Xorshift random number generator <p> - it is 30% faster than the
- * generator from Java's library - it produces random sequences of higher quality than java.util.Random - this class
- * also provides a clone() function <p> Usage: XSRandom rand = new XSRandom(); //Instantiation x = rand.nextInt();
- * //pull a random number <p> To use the class in legacy code, you may also instantiate an XSRandom object and assign it
- * to a java.util.Random object: java.util.Random rand = new XSRandom(); <p> for an explanation of the algorithm, see
- * http://demesos.blogspot.com/2011/09/pseudo-random-number-generators.html
- * @author Wilfried Elmenreich University of Klagenfurt/Lakeside Labs http://www.elmenreich.tk <p> This code is released
- * under the GNU Lesser General Public License Version 3 http://www.gnu.org/licenses/lgpl-3.0.txt
- */
-
-import java.util.Random;
-import java.util.concurrent.atomic.AtomicLong;
-
-/**
- * XSTR - Xorshift ThermiteRandom Modified by Bogdan-G 03.06.2016 version 0.0.4
- */
-public class XSTR extends Random {
-
-    private static final long serialVersionUID = 6208727693524452904L;
-    private long seed;
-    private static final double DOUBLE_UNIT = 0x1.0p-53; // 1.0 / (1L << 53)
-    private static final float FLOAT_UNIT = 0x1.0p-24f; // 1.0f / (1 << 24)
-    private static final AtomicLong seedUniquifier = new AtomicLong(8682522807148012L);
-    public static final XSTR XSTR_INSTANCE = new XSTR() {
-
-        private static final long serialVersionUID = 8778284761958251721L;
-
-        @Override
-        public synchronized void setSeed(long seed) {
-            if (!Thread.currentThread().getStackTrace()[2].getClassName().equals(Random.class.getName())) {
-                throw new NoSuchMethodError("This is meant to be shared!, leave seed state alone!");
-            }
-        }
-    };
-
-    /*
-     * MODIFIED BY: Robotia Modification: Implemented Random class seed generator
-     */
-
-    /**
-     * Creates a new pseudo random number generator. The seed is initialized to the current time, as if by
-     * <code>setSeed(System.currentTimeMillis());</code>.
-     */
-    public XSTR() {
-        this(seedUniquifier() ^ System.nanoTime());
-    }
-
-    private static long seedUniquifier() {
-        // L'Ecuyer, "Tables of Linear Congruential Generators of
-        // Different Sizes and Good Lattice Structure", 1999
-        while (true) {
-            long current = seedUniquifier.get();
-            long next = current * 181783497276652981L;
-            if (seedUniquifier.compareAndSet(current, next)) {
-                return next;
-            }
-        }
-    }
-
-    /**
-     * Creates a new pseudo random number generator, starting with the specified seed, using
-     * <code>setSeed(seed);</code>.
-     *
-     * @param seed the initial seed
-     */
-    public XSTR(long seed) {
-        this.seed = seed;
-    }
-
-    @Override
-    public boolean nextBoolean() {
-        return next(1) != 0;
-    }
-
-    @Override
-    public double nextDouble() {
-        return (((long) next(26) << 27) + next(27)) * DOUBLE_UNIT;
-    }
-
-    /**
-     * Returns the current state of the seed, can be used to clone the object
-     *
-     * @return the current seed
-     */
-    public synchronized long getSeed() {
-        return seed;
-    }
-
-    /**
-     * Sets the seed for this pseudo random number generator. As described above, two instances of the same random
-     * class, starting with the same seed, produce the same results, if the same methods are called.
-     *
-     * @param seed the new seed
-     */
-    @Override
-    public synchronized void setSeed(long seed) {
-        this.seed = seed;
-    }
-
-    /**
-     * @return Returns an XSRandom object with the same state as the original
-     */
-    @Override
-    public XSTR clone() {
-        return new XSTR(getSeed());
-    }
-
-    /**
-     * Implementation of George Marsaglia's elegant Xorshift random generator 30% faster and better quality than the
-     * built-in java.util.random see also see http://www.javamex.com/tutorials/random_numbers/xorshift.shtml
-     *
-     * @param nbits will shift nbits bits
-     * @return next seed
-     */
-    @Override
-    public int next(int nbits) {
-        long x = seed;
-        x ^= x << 21;
-        x ^= x >>> 35;
-        x ^= x << 4;
-        seed = x;
-        x &= (1L << nbits) - 1;
-        return (int) x;
-    }
-
-    private boolean haveNextNextGaussian = false;
-    private double nextNextGaussian = 0;
-
-    @Override
-    public synchronized double nextGaussian() {
-        // See Knuth, ACP, Section 3.4.1 Algorithm C.
-        if (haveNextNextGaussian) {
-            haveNextNextGaussian = false;
-            return nextNextGaussian;
-        } else {
-            double v1, v2, vs;
-            do {
-                v1 = 2 * nextDouble() - 1; // between -1 and 1
-                v2 = 2 * nextDouble() - 1; // between -1 and 1
-                vs = v1 * v1 + v2 * v2;
-            } while (vs >= 1 || vs == 0);
-            double multiplier = StrictMath.sqrt(-2 * StrictMath.log(vs) / vs);
-            nextNextGaussian = v2 * multiplier;
-            haveNextNextGaussian = true;
-            return v1 * multiplier;
-        }
-    }
-
-    /**
-     * Returns a pseudorandom, uniformly distributed {@code int} value between 0 (inclusive) and the specified value
-     * (exclusive), drawn from this random number generator's sequence. The general contract of {@code nextInt} is that
-     * one {@code int} value in the specified range is pseudorandomly generated and returned. All {@code bound} possible
-     * {@code int} values are produced with (approximately) equal probability. The method {@code nextInt(int bound)} is
-     * implemented by class {@code Random} as if by:
-     * 
-     * <pre>
-     *  {@code
-     * public int nextInt(int bound) {
-     *   if (bound <= 0)
-     *     throw new IllegalArgumentException("bound must be positive");
-     *
-     *   if ((bound & -bound) == bound)  // i.e., bound is a power of 2
-     *     return (int)((bound * (long)next(31)) >> 31);
-     *
-     *   int bits, val;
-     *   do {
-     *       bits = next(31);
-     *       val = bits % bound;
-     *   } while (bits - val + (bound-1) < 0);
-     *   return val;
-     * }}
-     * </pre>
-     *
-     * <p>
-     * The hedge "approx imately" is used in the foregoing description only because the next method is only
-     * approximately an unbiased source of independently chosen bits. If it were a perfect source of randomly chosen
-     * bits, then the algorithm shown would choose {@code int} values from the stated range with perfect uniformity.
-     * <p>
-     * The algorithm is slightly tricky. It rejects values that would result in an uneven distribution (due to the fact
-     * that 2^31 is not divisible by n). The probability of a value being rejected depends on n. The worst case is
-     * n=2^30+1, for which the probability of a reject is 1/2, and the expected number of iterations before the loop
-     * terminates is 2.
-     * <p>
-     * The algorithm treats the case where n is a power of two specially: it returns the correct number of high-order
-     * bits from the underlying pseudo-random number generator. In the absence of special treatment, the correct number
-     * of <i>low-order</i> bits would be returned. Linear congruential pseudo-random number generators such as the one
-     * implemented by this class are known to have short periods in the sequence of values of their low-order bits.
-     * Thus, this special case greatly increases the length of the sequence of values returned by successive calls to
-     * this method if n is a small power of two.
-     *
-     * @param bound the upper bound (exclusive). Must be positive.
-     * @return the next pseudorandom, uniformly distributed {@code int} value between zero (inclusive) and {@code bound}
-     *         (exclusive) from this random number generator's sequence
-     * @throws IllegalArgumentException if bound is not positive
-     * @since 1.2
-     */
-    @Override
-    public int nextInt(int bound) {
-        // speedup, new nextInt ~+40%
-        long last = seed ^ seed << 21;
-        last ^= last >>> 35;
-        last ^= last << 4;
-        seed = last;
-        int out = (int) last % bound;
-        return out < 0 ? -out : out;
-    }
-
-    @Override
-    public int nextInt() {
-        return next(32);
-    }
-
-    @Override
-    public float nextFloat() {
-        return next(24) * FLOAT_UNIT;
-    }
-
-    @Override
-    public long nextLong() {
-        // it's okay that the bottom word remains signed.
-        return ((long) next(32) << 32) + next(32);
-    }
-
-    @Override
-    public void nextBytes(byte[] bytes_arr) {
-        for (int iba = 0, lenba = bytes_arr.length; iba < lenba;) {
-            for (int rndba = nextInt(), nba = Math.min(lenba - iba, Integer.SIZE / Byte.SIZE); nba--
-                    > 0; rndba >>= Byte.SIZE) {
-                bytes_arr[iba++] = (byte) rndba;
-            }
-        }
-    }
-}