Apache
/
commons-math
mirror of https://github.com/apache/commons-math.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Remove deprecated contructors in UniformRealDistribution.

This commit is contained in:
Thomas Neidhart 2015-02-24 23:38:51 +01:00
parent 0d3545e5f6
commit 96ba5ec216
8 changed files with 7 additions and 58 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

42
src/main/java/org/apache/commons/math4/distribution/UniformRealDistribution.java
View File

@ -32,11 +32,6 @@ import org.apache.commons.math4.random.Well19937c;
* @since 3.0
*/
public class UniformRealDistribution extends AbstractRealDistribution {
/** Default inverse cumulative probability accuracy.
* @deprecated as of 3.2 not used anymore, will be removed in 4.0
*/
@Deprecated
public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY = 1e-9;
/** Serializable version identifier. */
private static final long serialVersionUID = 20120109L;
/** Lower bound of this distribution (inclusive). */
@ -79,43 +74,6 @@ public class UniformRealDistribution extends AbstractRealDistribution {
this(new Well19937c(), lower, upper);
}
/**
* Create a uniform distribution.
*
* @param lower Lower bound of this distribution (inclusive).
* @param upper Upper bound of this distribution (exclusive).
* @param inverseCumAccuracy Inverse cumulative probability accuracy.
* @throws NumberIsTooLargeException if {@code lower >= upper}.
* @deprecated as of 3.2, inverse CDF is now calculated analytically, use
* {@link #UniformRealDistribution(double, double)} instead.
*/
@Deprecated
public UniformRealDistribution(double lower, double upper, double inverseCumAccuracy)
throws NumberIsTooLargeException {
this(new Well19937c(), lower, upper);
}
/**
* Creates a uniform distribution.
*
* @param rng Random number generator.
* @param lower Lower bound of this distribution (inclusive).
* @param upper Upper bound of this distribution (exclusive).
* @param inverseCumAccuracy Inverse cumulative probability accuracy.
* @throws NumberIsTooLargeException if {@code lower >= upper}.
* @since 3.1
* @deprecated as of 3.2, inverse CDF is now calculated analytically, use
* {@link #UniformRealDistribution(RandomGenerator, double, double)}
* instead.
*/
@Deprecated
public UniformRealDistribution(RandomGenerator rng,
double lower,
double upper,
double inverseCumAccuracy){
this(rng, lower, upper);
}
/**
* Creates a uniform distribution.
*

3
src/test/java/org/apache/commons/math4/fitting/leastsquares/RandomCirclePointGenerator.java
View File

@ -58,8 +58,7 @@ public class RandomCirclePointGenerator {
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
cY = new NormalDistribution(rng, y, ySigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI);
}
/**

3
src/test/java/org/apache/commons/math4/fitting/leastsquares/RandomStraightLinePointGenerator.java
View File

@ -66,8 +66,7 @@ public class RandomStraightLinePointGenerator {
intercept = b;
error = new NormalDistribution(rng, 0, sigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi);
}
/**

3
src/test/java/org/apache/commons/math4/optim/nonlinear/vector/jacobian/RandomCirclePointGenerator.java
View File

@ -59,8 +59,7 @@ public class RandomCirclePointGenerator {
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
cY = new NormalDistribution(rng, y, ySigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI);
}
/**

3
src/test/java/org/apache/commons/math4/optim/nonlinear/vector/jacobian/RandomStraightLinePointGenerator.java
View File

@ -67,8 +67,7 @@ public class RandomStraightLinePointGenerator {
intercept = b;
error = new NormalDistribution(rng, 0, sigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi);
}
/**

3
src/test/java/org/apache/commons/math4/optimization/general/RandomCirclePointGenerator.java
View File

@ -60,8 +60,7 @@ public class RandomCirclePointGenerator {
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
cY = new NormalDistribution(rng, y, ySigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI);
}
/**

3
src/test/java/org/apache/commons/math4/optimization/general/RandomStraightLinePointGenerator.java
View File

@ -67,8 +67,7 @@ public class RandomStraightLinePointGenerator {
intercept = b;
error = new NormalDistribution(rng, 0, sigma,
NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi,
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
x = new UniformRealDistribution(rng, lo, hi);
}
/**

5
src/test/java/org/apache/commons/math4/random/EmpiricalDistributionTest.java
View File

@ -44,9 +44,7 @@ import org.junit.Test;
/**
* Test cases for the EmpiricalDistribution class
*
*/
public final class EmpiricalDistributionTest extends RealDistributionAbstractTest {
protected EmpiricalDistribution empiricalDistribution = null;
@ -542,8 +540,7 @@ public final class EmpiricalDistributionTest extends RealDistributionAbstractTes
}
@Override
protected RealDistribution getKernel(SummaryStatistics bStats) {
return new UniformRealDistribution(randomData.getRandomGenerator(), bStats.getMin(), bStats.getMax(),
UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
return new UniformRealDistribution(randomData.getRandomGenerator(), bStats.getMin(), bStats.getMax());
}
}
}