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/*
* Copyright (C) 2011 The Guava Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.google.common.math;
import java.math.BigInteger;
import java.util.Random;
/**
* Utilities for benchmarks.
*
* <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
* the input itself, so most methods which generate values use an exponential distribution varying
* the order of magnitude of the generated values uniformly at random.
*
* @author Louis Wasserman
*/
final class MathBenchmarking {
static final int ARRAY_SIZE = 0x10000;
static final int ARRAY_MASK = 0x0ffff;
static final Random RANDOM_SOURCE = new Random(314159265358979L);
static final int MAX_EXPONENT = 100;
/*
* Duplicated from LongMath.
* binomial(biggestBinomials[k], k) fits in a long, but not
* binomial(biggestBinomials[k] + 1, k).
*/
static final int[] biggestBinomials = {
Integer.MAX_VALUE,
Integer.MAX_VALUE,
Integer.MAX_VALUE,
3810779,
121977,
16175,
4337,
1733,
887,
534,
361,
265,
206,
169,
143,
125,
111,
101,
94,
88,
83,
79,
76,
74,
72,
70,
69,
68,
67,
67,
66,
66,
66,
66
};
/**
* Generates values in a distribution equivalent to randomNonNegativeBigInteger but omitting zero.
*/
static BigInteger randomPositiveBigInteger(int numBits) {
BigInteger result;
do {
result = randomNonNegativeBigInteger(numBits);
} while (result.signum() == 0);
return result;
}
/**
* Generates a number in [0, 2^numBits) with an exponential distribution. The floor of the log2 of
* the result is chosen uniformly at random in [0, numBits), and then the result is chosen in that
* range uniformly at random. Zero is treated as having log2 == 0.
*/
static BigInteger randomNonNegativeBigInteger(int numBits) {
int digits = RANDOM_SOURCE.nextInt(numBits);
if (digits == 0) {
return new BigInteger(1, RANDOM_SOURCE);
} else {
return new BigInteger(digits, RANDOM_SOURCE).setBit(digits);
}
}
/**
* Equivalent to calling randomPositiveBigInteger(numBits) and then flipping the sign with 50%
* probability.
*/
static BigInteger randomNonZeroBigInteger(int numBits) {
BigInteger result = randomPositiveBigInteger(numBits);
return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
}
/**
* Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
* lower magnitude.
*/
static BigInteger randomBigInteger(int numBits) {
while (true) {
if (RANDOM_SOURCE.nextBoolean()) {
return randomNonNegativeBigInteger(numBits);
}
BigInteger neg = randomNonNegativeBigInteger(numBits).negate();
if (neg.signum() != 0) {
return neg;
}
}
}
/**
* Generates a number in [0, 2^numBits) with an exponential distribution. The floor of the log2 of
* the absolute value of the result is chosen uniformly at random in [0, numBits), and then the
* result is chosen from those possibilities uniformly at random.
*
* <p>Zero is treated as having log2 == 0.
*/
static double randomDouble(int maxExponent) {
double result = RANDOM_SOURCE.nextDouble();
result = Math.scalb(result, RANDOM_SOURCE.nextInt(maxExponent + 1));
return RANDOM_SOURCE.nextBoolean() ? result : -result;
}
/** Returns a random integer between zero and {@code MAX_EXPONENT}. */
static int randomExponent() {
return RANDOM_SOURCE.nextInt(MAX_EXPONENT + 1);
}
static double randomPositiveDouble() {
return Math.exp(randomDouble(6));
}
}
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