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commit a5b1aa029457e69b98064413dd4e32ed3a68512a
Author: Gilles Sadowski <gillese...@gmail.com>
AuthorDate: Wed Jun 9 16:18:57 2021 +0200
Typo.
---
.../AbstractLeastSquaresOptimizerAbstractTest.java | 56 +++++++++++-----------
.../GaussNewtonOptimizerWithSVDTest.java | 7 ++-
2 files changed, 31 insertions(+), 32 deletions(-)
diff --git
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/AbstractLeastSquaresOptimizerAbstractTest.java
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/AbstractLeastSquaresOptimizerAbstractTest.java
index bd0aed4..d7f2768 100644
---
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/AbstractLeastSquaresOptimizerAbstractTest.java
+++
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/AbstractLeastSquaresOptimizerAbstractTest.java
@@ -55,7 +55,7 @@ import static org.hamcrest.CoreMatchers.sameInstance;
public abstract class AbstractLeastSquaresOptimizerAbstractTest {
/** default absolute tolerance of comparisons */
- public static final double TOl = 1e-10;
+ public static final double TOL = 1e-10;
public LeastSquaresBuilder base() {
return new LeastSquaresBuilder()
@@ -160,9 +160,9 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(ls);
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 1.5);
- Assert.assertEquals(0.0, optimum.getResiduals().getEntry(0), TOl);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 1.5);
+ Assert.assertEquals(0.0, optimum.getResiduals().getEntry(0), TOL);
}
@Test
@@ -173,9 +173,9 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 7, 3);
- assertEquals(TOl, optimum.getResiduals(), 0, 0, 0);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 7, 3);
+ assertEquals(TOL, optimum.getResiduals(), 0, 0, 0);
}
@Test
@@ -191,9 +191,9 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
for (int i = 0; i < problem.target.length; ++i) {
- Assert.assertEquals(0.55 * i, optimum.getPoint().getEntry(i), TOl);
+ Assert.assertEquals(0.55 * i, optimum.getPoint().getEntry(i), TOL);
}
}
@@ -207,8 +207,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 1, 2, 3);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 1, 2, 3);
}
@Test
@@ -225,8 +225,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 3, 4, -1, -2, 1 + epsilon, 1 -
epsilon);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 3, 4, -1, -2, 1 + epsilon, 1 -
epsilon);
}
@Test
@@ -259,8 +259,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer
.optimize(problem1.getBuilder().start(start).build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 1, 1, 1, 1);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 1, 1, 1, 1);
LinearProblem problem2 = new LinearProblem(new double[][]{
{10.00, 7.00, 8.10, 7.20},
@@ -271,7 +271,7 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
optimum =
optimizer.optimize(problem2.getBuilder().start(start).build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
assertEquals(1e-8, optimum.getPoint(), -81, 137, -34, 22);
}
@@ -286,7 +286,7 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer
.optimize(problem.getBuilder().start(new double[]{7, 6, 5,
4}).build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
}
@Test
@@ -302,13 +302,13 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(
problem.getBuilder().start(new double[]{2, 2, 2, 2, 2,
2}).build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
RealVector point = optimum.getPoint();
//the first two elements are under constrained
//check first two elements obey the constraint: sum to 3
- Assert.assertEquals(3, point.getEntry(0) + point.getEntry(1), TOl);
+ Assert.assertEquals(3, point.getEntry(0) + point.getEntry(1), TOL);
//#constrains = #states fro the last 4 elements
- assertEquals(TOl, point.getSubVector(2, 4), 3, 4, 5, 6);
+ assertEquals(TOL, point.getSubVector(2, 4), 3, 4, 5, 6);
}
@Test
@@ -322,8 +322,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer
.optimize(problem.getBuilder().start(new double[]{1,
1}).build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), 2, 1);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), 2, 1);
}
@Test
@@ -352,8 +352,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
//TODO why is this part here? hasn't it been tested already?
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), -1, 1);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), -1, 1);
//TODO move to builder test
optimizer.optimize(
@@ -374,8 +374,8 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
- Assert.assertEquals(0, optimum.getRMS(), TOl);
- assertEquals(TOl, optimum.getPoint(), -1, 1);
+ Assert.assertEquals(0, optimum.getRMS(), TOL);
+ assertEquals(TOL, optimum.getPoint(), -1, 1);
//TODO move to builder test
optimizer.optimize(
@@ -406,7 +406,7 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
Assert.assertTrue(optimum.getEvaluations() < 10);
double rms = optimum.getRMS();
- Assert.assertEquals(1.768262623567235,
AccurateMath.sqrt(circle.getN()) * rms, TOl);
+ Assert.assertEquals(1.768262623567235,
AccurateMath.sqrt(circle.getN()) * rms, TOL);
Vector2D center = Vector2D.of(optimum.getPoint().getEntry(0),
optimum.getPoint().getEntry(1));
Assert.assertEquals(69.96016176931406, circle.getRadius(center), 1e-6);
@@ -553,7 +553,7 @@ public abstract class
AbstractLeastSquaresOptimizerAbstractTest {
previous.getPoint(),
not(sameInstance(current.getPoint())));
Assert.assertArrayEquals(new double[3],
previous.getPoint().toArray(), 0);
- Assert.assertArrayEquals(new double[] {1, 2, 3},
current.getPoint().toArray(), TOl);
+ Assert.assertArrayEquals(new double[] {1, 2, 3},
current.getPoint().toArray(), TOL);
checked[0] = true;
return true;
}
diff --git
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/GaussNewtonOptimizerWithSVDTest.java
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/GaussNewtonOptimizerWithSVDTest.java
index 87d0ee7..2df8fb8 100644
---
a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/GaussNewtonOptimizerWithSVDTest.java
+++
b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/fitting/leastsquares/GaussNewtonOptimizerWithSVDTest.java
@@ -17,10 +17,10 @@
package org.apache.commons.math4.legacy.fitting.leastsquares;
+import org.apache.commons.numbers.core.Precision;
import org.apache.commons.geometry.euclidean.threed.Plane;
import org.apache.commons.geometry.euclidean.threed.Planes;
import org.apache.commons.geometry.euclidean.threed.Vector3D;
-import
org.apache.commons.geometry.core.precision.EpsilonDoublePrecisionContext;
import org.apache.commons.math4.legacy.exception.ConvergenceException;
import org.apache.commons.math4.legacy.exception.TooManyEvaluationsException;
import
org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition;
@@ -140,12 +140,11 @@ public class GaussNewtonOptimizerWithSVDTest
Optimum optimum = optimizer.optimize(problem.getBuilder().build());
Plane span = Planes.fromPoints(Vector3D.ZERO, Vector3D.of(1, 2, -3),
Vector3D.of(2, 1, 0),
- new EpsilonDoublePrecisionContext(TOl));
+
Precision.doubleEquivalenceOfEpsilon(TOL));
double expected = AccurateMath.abs(span.offset(Vector3D.of(1, 1, 1)));
double actual = optimum.getResiduals().getNorm();
//verify
- Assert.assertEquals(expected, actual, TOl);
+ Assert.assertEquals(expected, actual, TOL);
}
-
}
