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Posted to commits@commons.apache.org by er...@apache.org on 2021/05/31 13:05:44 UTC

[commons-math] 02/02: Unused classes (in "src/test").

This is an automated email from the ASF dual-hosted git repository.

erans pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-math.git

commit 53cb2cce5f7bbcc2301ee131b26abf9354fd6302
Author: Gilles Sadowski <gi...@gmail.com>
AuthorDate: Mon May 31 15:00:32 2021 +0200

    Unused classes (in "src/test").
---
 .../stat/descriptive/ListUnivariateImpl.java       | 159 --------------------
 .../stat/descriptive/ListUnivariateImplTest.java   | 157 -------------------
 .../descriptive/MixedListUnivariateImplTest.java   | 167 ---------------------
 3 files changed, 483 deletions(-)

diff --git a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImpl.java b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImpl.java
deleted file mode 100644
index 3ada560..0000000
--- a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImpl.java
+++ /dev/null
@@ -1,159 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You 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 org.apache.commons.math4.legacy.stat.descriptive;
-
-import java.io.Serializable;
-import java.util.ArrayList;
-import java.util.List;
-
-import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
-import org.apache.commons.math4.legacy.util.FastMath;
-
-/**
- */
-public class ListUnivariateImpl extends DescriptiveStatistics implements Serializable {
-    /** Serializable version identifier */
-    private static final long serialVersionUID = -8837442489133392138L;
-    /**
-     * Holds a reference to a list - GENERICs are going to make
-     * our lives easier here as we could only accept List<Number>
-     */
-    protected List<Double> list = new ArrayList<>();
-
-    /**
-     * Construct a ListUnivariate with a specific List.
-     * @param list The list that will back this DescriptiveStatistics
-     */
-    public ListUnivariateImpl(List<Double> list) {
-        this.list = list;
-    }
-
-
-    /**
-     * Default constructor
-     */
-    public ListUnivariateImpl() {
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public double[] getValues() {
-        int length = list.size();
-
-        // If the window size is not INFINITE_WINDOW AND
-        // the current list is larger that the window size, we need to
-        // take into account only the last n elements of the list
-        // as defined by windowSize
-
-        final int wSize = getWindowSize();
-        if (wSize != DescriptiveStatistics.INFINITE_WINDOW && wSize < list.size()) {
-            length = list.size() - FastMath.max(0, list.size() - wSize);
-        }
-
-        // Create an array to hold all values
-        double[] copiedArray = new double[length];
-
-        for (int i = 0; i < copiedArray.length; i++) {
-            copiedArray[i] = getElement(i);
-        }
-        return copiedArray;
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public double getElement(int index) {
-        double value = Double.NaN;
-        int calcIndex = index;
-
-        final int wSize = getWindowSize();
-        if (wSize != DescriptiveStatistics.INFINITE_WINDOW && wSize < list.size()) {
-            calcIndex = (list.size() - wSize) + index;
-        }
-
-
-        try {
-            value = list.get(calcIndex);
-        } catch (MathIllegalArgumentException e) {
-            e.printStackTrace();
-        }
-
-        return value;
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public long getN() {
-        int n = 0;
-
-        final int wSize = getWindowSize();
-        if (wSize != DescriptiveStatistics.INFINITE_WINDOW) {
-            if (list.size() > wSize) {
-                n = wSize;
-            } else {
-                n = list.size();
-            }
-        } else {
-            n = list.size();
-        }
-
-        return n;
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public void addValue(double v) {
-        list.add(v);
-    }
-
-    /**
-     * Clears all statistics.
-     * <p>
-     * <strong>N.B.: </strong> This method has the side effect of clearing the underlying list.
-     */
-    @Override
-    public void clear() {
-        list.clear();
-    }
-
-    /**
-     * Apply the given statistic to this univariate collection.
-     * @param stat the statistic to apply
-     * @return the computed value of the statistic.
-     */
-    @Override
-    public double apply(UnivariateStatistic stat) {
-        final double[] v = this.getValues();
-
-        if (v != null) {
-            return stat.evaluate(v, 0, v.length);
-        }
-
-        return Double.NaN;
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public void setWindowSize(int windowSize) {
-        super.setWindowSize(windowSize);
-        // Discard elements from the front of the list if "windowSize"
-        // is less than the size of the list.
-        final int extra = list.size() - windowSize;
-        if (extra > 0) {
-            list.subList(0, extra).clear();
-        }
-    }
-}
diff --git a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImplTest.java b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImplTest.java
deleted file mode 100644
index c225285..0000000
--- a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/ListUnivariateImplTest.java
+++ /dev/null
@@ -1,157 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You 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 org.apache.commons.math4.legacy.stat.descriptive;
-
-import java.util.ArrayList;
-import java.util.List;
-
-import org.apache.commons.math4.legacy.TestUtils;
-import org.apache.commons.math4.legacy.util.FastMath;
-import org.junit.Assert;
-import org.junit.Test;
-
-/**
- * Test cases for the {@link ListUnivariateImpl} class.
- *
- */
-
-public final class ListUnivariateImplTest {
-
-    private double one = 1;
-    private float two = 2;
-    private int three = 3;
-
-    private double mean = 2;
-    private double sumSq = 18;
-    private double sum = 8;
-    private double var = 0.666666666666666666667;
-    private double std = FastMath.sqrt(var);
-    private double n = 4;
-    private double min = 1;
-    private double max = 3;
-    private double tolerance = 10E-15;
-
-    /** test stats */
-    @Test
-    public void testStats() {
-        List<Double> externalList = new ArrayList<>();
-
-        DescriptiveStatistics u = new ListUnivariateImpl( externalList );
-
-        Assert.assertEquals("total count",0,u.getN(),tolerance);
-        u.addValue(one);
-        u.addValue(two);
-        u.addValue(two);
-        u.addValue(three);
-        Assert.assertEquals("N",n,u.getN(),tolerance);
-        Assert.assertEquals("sum",sum,u.getSum(),tolerance);
-        Assert.assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
-        Assert.assertEquals("var",var,u.getVariance(),tolerance);
-        Assert.assertEquals("std",std,u.getStandardDeviation(),tolerance);
-        Assert.assertEquals("mean",mean,u.getMean(),tolerance);
-        Assert.assertEquals("min",min,u.getMin(),tolerance);
-        Assert.assertEquals("max",max,u.getMax(),tolerance);
-        u.clear();
-        Assert.assertEquals("total count",0,u.getN(),tolerance);
-    }
-
-    @Test
-    public void testN0andN1Conditions() {
-        List<Double> list = new ArrayList<>();
-
-        DescriptiveStatistics u = new ListUnivariateImpl(list);
-
-        Assert.assertTrue("Mean of n = 0 set should be NaN", Double.isNaN( u.getMean() ) );
-        Assert.assertTrue("Standard Deviation of n = 0 set should be NaN", Double.isNaN( u.getStandardDeviation() ) );
-        Assert.assertTrue("Variance of n = 0 set should be NaN", Double.isNaN(u.getVariance() ) );
-
-        list.add( Double.valueOf(one));
-
-        Assert.assertTrue( "Mean of n = 1 set should be value of single item n1", u.getMean() == one);
-        Assert.assertTrue( "StdDev of n = 1 set should be zero, instead it is: " + u.getStandardDeviation(), u.getStandardDeviation() == 0);
-        Assert.assertTrue( "Variance of n = 1 set should be zero", u.getVariance() == 0);
-    }
-
-    @Test
-    public void testSkewAndKurtosis() {
-        DescriptiveStatistics u = new DescriptiveStatistics();
-
-        double[] testArray = { 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
-                                             9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
-        for( int i = 0; i < testArray.length; i++) {
-            u.addValue( testArray[i]);
-        }
-
-        Assert.assertEquals("mean", 12.40455, u.getMean(), 0.0001);
-        Assert.assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
-        Assert.assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
-        Assert.assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
-    }
-
-    @Test
-    public void testProductAndGeometricMean() {
-        ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<>());
-        u.setWindowSize(10);
-
-        u.addValue( 1.0 );
-        u.addValue( 2.0 );
-        u.addValue( 3.0 );
-        u.addValue( 4.0 );
-
-        Assert.assertEquals( "Geometric mean not expected", 2.213364, u.getGeometricMean(), 0.00001 );
-
-        // Now test rolling - StorelessDescriptiveStatistics should discount the contribution
-        // of a discarded element
-        for( int i = 0; i < 10; i++ ) {
-            u.addValue( i + 2 );
-        }
-        // Values should be (2,3,4,5,6,7,8,9,10,11)
-
-        Assert.assertEquals( "Geometric mean not expected", 5.755931, u.getGeometricMean(), 0.00001 );
-
-
-    }
-
-    /** test stats */
-    @Test
-    public void testSerialization() {
-
-        DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>());
-
-        Assert.assertEquals("total count",0,u.getN(),tolerance);
-        u.addValue(one);
-        u.addValue(two);
-
-        DescriptiveStatistics u2 = (DescriptiveStatistics)TestUtils.serializeAndRecover(u);
-
-        u2.addValue(two);
-        u2.addValue(three);
-
-        Assert.assertEquals("N",n,u2.getN(),tolerance);
-        Assert.assertEquals("sum",sum,u2.getSum(),tolerance);
-        Assert.assertEquals("sumsq",sumSq,u2.getSumsq(),tolerance);
-        Assert.assertEquals("var",var,u2.getVariance(),tolerance);
-        Assert.assertEquals("std",std,u2.getStandardDeviation(),tolerance);
-        Assert.assertEquals("mean",mean,u2.getMean(),tolerance);
-        Assert.assertEquals("min",min,u2.getMin(),tolerance);
-        Assert.assertEquals("max",max,u2.getMax(),tolerance);
-
-        u2.clear();
-        Assert.assertEquals("total count",0,u2.getN(),tolerance);
-    }
-}
-
diff --git a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/MixedListUnivariateImplTest.java b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/MixedListUnivariateImplTest.java
deleted file mode 100644
index ae41153..0000000
--- a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/MixedListUnivariateImplTest.java
+++ /dev/null
@@ -1,167 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You 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 org.apache.commons.math4.legacy.stat.descriptive;
-
-import org.apache.commons.math4.legacy.util.FastMath;
-import org.junit.Assert;
-import org.junit.Test;
-
-import java.util.ArrayList;
-import java.util.List;
-
-/**
- * Test cases for the {@link ListUnivariateImpl} class.
- */
-public final class MixedListUnivariateImplTest {
-    private final double one = 1;
-    private final float two = 2;
-    private final int three = 3;
-
-    private final double mean = 2;
-    private final double sumSq = 18;
-    private final double sum = 8;
-    private final double var = 0.666666666666666666667;
-    private final double std = FastMath.sqrt(var);
-    private final double n = 4;
-    private final double min = 1;
-    private final double max = 3;
-    private final double tolerance = 10E-15;
-
-
-    public MixedListUnivariateImplTest() {
-
-
-    }
-
-    /** test stats */
-    @Test
-    public void testStats() {
-        List<Double> externalList = new ArrayList<>();
-
-        DescriptiveStatistics u = new ListUnivariateImpl(externalList);
-
-        Assert.assertEquals("total count", 0, u.getN(), tolerance);
-        u.addValue(one);
-        u.addValue(two);
-        u.addValue(two);
-        u.addValue(three);
-        Assert.assertEquals("N", n, u.getN(), tolerance);
-        Assert.assertEquals("sum", sum, u.getSum(), tolerance);
-        Assert.assertEquals("sumsq", sumSq, u.getSumsq(), tolerance);
-        Assert.assertEquals("var", var, u.getVariance(), tolerance);
-        Assert.assertEquals("std", std, u.getStandardDeviation(), tolerance);
-        Assert.assertEquals("mean", mean, u.getMean(), tolerance);
-        Assert.assertEquals("min", min, u.getMin(), tolerance);
-        Assert.assertEquals("max", max, u.getMax(), tolerance);
-        u.clear();
-        Assert.assertEquals("total count", 0, u.getN(), tolerance);
-    }
-
-    @Test
-    public void testN0andN1Conditions() {
-        DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>());
-
-        Assert.assertTrue(
-            "Mean of n = 0 set should be NaN",
-            Double.isNaN(u.getMean()));
-        Assert.assertTrue(
-            "Standard Deviation of n = 0 set should be NaN",
-            Double.isNaN(u.getStandardDeviation()));
-        Assert.assertTrue(
-            "Variance of n = 0 set should be NaN",
-            Double.isNaN(u.getVariance()));
-
-        u.addValue(one);
-
-        Assert.assertTrue(
-            "Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean() ,
-            u.getMean() == one);
-
-        Assert.assertTrue(
-            "StdDev of n = 1 set should be zero, instead it is: "
-                + u.getStandardDeviation(),
-            u.getStandardDeviation() == 0);
-        Assert.assertTrue(
-            "Variance of n = 1 set should be zero",
-            u.getVariance() == 0);
-    }
-
-    @Test
-    public void testSkewAndKurtosis() {
-        ListUnivariateImpl u =
-            new ListUnivariateImpl(new ArrayList<>());
-
-        u.addValue(12.5);
-        u.addValue(12);
-        u.addValue(11.8);
-        u.addValue(14.2);
-        u.addValue(14.5);
-        u.addValue(14.9);
-        u.addValue(12.0);
-        u.addValue(21);
-        u.addValue(8.2);
-        u.addValue(10.3);
-        u.addValue(11.3);
-        u.addValue(14.1f);
-        u.addValue(9.9);
-        u.addValue(12.2);
-        u.addValue(12.1);
-        u.addValue(11);
-        u.addValue(19.8);
-        u.addValue(11);
-        u.addValue(10);
-        u.addValue(8.8);
-        u.addValue(9);
-        u.addValue(12.3);
-
-
-        Assert.assertEquals("mean", 12.40455, u.getMean(), 0.0001);
-        Assert.assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
-        Assert.assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
-        Assert.assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
-    }
-
-    @Test
-    public void testProductAndGeometricMean() {
-        ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<>());
-        u.setWindowSize(10);
-
-        u.addValue(1.0);
-        u.addValue(2.0);
-        u.addValue(3.0);
-        u.addValue(4.0);
-
-        Assert.assertEquals(
-            "Geometric mean not expected",
-            2.213364,
-            u.getGeometricMean(),
-            0.00001);
-
-        // Now test rolling - StorelessDescriptiveStatistics should discount the contribution
-        // of a discarded element
-        for (int i = 0; i < 10; i++) {
-            u.addValue(i + 2);
-        }
-        // Values should be (2,3,4,5,6,7,8,9,10,11)
-        Assert.assertEquals(
-            "Geometric mean not expected",
-            5.755931,
-            u.getGeometricMean(),
-            0.00001);
-
-    }
-}