This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-statistics.git
commit bf13f6969a26efe61d7fb2d5d7ea82a551d2d101
Author: aherbert <aherb...@apache.org>
AuthorDate: Fri Nov 25 18:51:50 2022 +0000
Support per-test properties (tolerance, disable)
Use an enum to define the standard test names. This is the key in the
test resource file used to look-up the test tolerance and disable flag.
---
.../BaseContinuousDistributionTest.java | 146 ++++-----
.../distribution/BaseDiscreteDistributionTest.java | 171 ++++++-----
.../distribution/BaseDistributionTest.java | 327 +++------------------
.../distribution/DistributionTestData.java | 277 +++++++----------
.../HypergeometricDistributionTest.java | 4 +-
.../distribution/NormalDistributionTest.java | 10 -
.../distribution/ParetoDistributionTest.java | 4 +-
.../distribution/PoissonDistributionTest.java | 2 +-
.../commons/statistics/distribution/TestName.java | 82 ++++++
.../distribution/test.binomial.2.properties | 1 +
.../distribution/test.binomial.3.properties | 1 +
.../statistics/distribution/test.levy.1.properties | 1 +
.../distribution/test.normal.1.properties | 2 +
.../distribution/test.pareto.10.properties | 2 +-
.../distribution/test.pareto.11.properties | 2 +-
.../distribution/test.pareto.5.properties | 2 +-
.../distribution/test.pareto.6.properties | 2 +-
.../distribution/test.pareto.7.properties | 2 +-
.../distribution/test.pareto.9.properties | 2 +-
19 files changed, 399 insertions(+), 641 deletions(-)
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.java
index 2510156..a9831d4 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.java
@@ -89,13 +89,11 @@ import org.junit.jupiter.params.provider.MethodSource;
* <li>Points for the PDF (and log PDF) can be specified. The default will use
the CDF points.
* Note: It is not expected that evaluation of the PDF will require different
points to the CDF.
* <li>Points and expected values for the inverse CDF can be specified. These
are used in
- * addition to test the inverse mapping of the CDF values to the CDF test
points. The
- * inverse mapping test can be disabled.
+ * addition to test the inverse mapping of the CDF values to the CDF test
points.
* <li>Expected values for the log PDF can be specified. The default will use
* {@link Math#log(double)} on the PDF values.
* <li>Points and expected values for the survival function can be specified.
These are used in
- * addition to test the inverse mapping of the SF values to the SF test
points. The
- * inverse mapping test can be disabled.
+ * addition to test the inverse mapping of the SF values to the SF test points.
* The default will use the expected CDF values (SF = 1 - CDF).
* <li>A tolerance for equality assertions. The default is set by {@link
#getAbsoluteTolerance()}
* and {@link #getRelativeTolerance()}.
@@ -103,9 +101,19 @@ import org.junit.jupiter.params.provider.MethodSource;
*
* <p>If the distribution provides higher precision implementations of
* cumulative probability and/or survival probability as the values approach
zero, then test
- * points and expected values can be provided with a tolerance for equality
assertions of
- * high-precision computations. The default is set by {@link
#getHighPrecisionAbsoluteTolerance()}
- * and {@link #getHighPrecisionRelativeTolerance()}.
+ * points and expected values can be provided for high-precision computations.
If the default
+ * absolute tolerance has been set to non-zero, then very small p-values will
require the
+ * high-precision absolute tolerance is configured for the test to a suitable
magnitude (see below).
+ *
+ * <p>Per-test configuration
+ *
+ * <p>Each test is identified with a {@link TestName} key in the properties
file. This key
+ * can be used to set a per-test tolerance, or disable the test:
+ * <pre>
+ * cdf.hp.relative = 1e-14
+ * cdf.hp.absolute = 1e-50
+ * sampling.disable
+ * </pre>
*
* <p>Note: All properties files are read during test initialization. Any
errors in a single
* property file will throw an exception, invalidating the initialization and
no tests
@@ -138,7 +146,7 @@ import org.junit.jupiter.params.provider.MethodSource;
*
* <p>The properties file uses {@code key=value} pairs loaded using a
* {@link java.util.Properties} object. Values will be read as String and then
parsed to
- * numeric data, and data arrays. Multi-line values can use a {@code \}
character.
+ * numeric data, and data arrays. Multi-line values can use a {@code \}
character to join lines.
* Data in the properties file will be converted to numbers using standard
parsing
* functions appropriate to the primitive type, e.g. {@link
Double#parseDouble(String)}.
* Special double values should use NaN, Infinity and -Infinity. As a
convenience
@@ -159,10 +167,6 @@ import org.junit.jupiter.params.provider.MethodSource;
* tolerance.relative = 1e-9
* # optional (default 0.0 or over-ridden in getAbsoluteTolerance())
* tolerance.absolute = 0.0
- * # optional (default 1e-12 or over-ridden in
getHighPrecisionRelativeTolerance())
- * tolerance.relative.hp = 1e-10
- * # optional (default 0.0 or over-ridden in
getHighPrecisionAbsoluteTolerance())
- * tolerance.absolute.hp = 1e-30
* cdf.points = 0, 0.2
* cdf.values = 0.0, 0.5
* # optional (default uses cdf.points)
@@ -186,20 +190,10 @@ import org.junit.jupiter.params.provider.MethodSource;
* # optional inverse CDF test (defaults to ignore)
* isf.points = 1.0, 0.5
* isf.values = 0.0, 0.2
- * # CDF inverse mapping test (default false)
- * disable.cdf.inverse = false
- * # SF inverse mapping test (default false)
- * disable.sf.inverse = false
- * # Sampling test (default false)
- * disable.sample = false
- * # PDF values test (default false)
- * disable.pdf = false
- * # Log PDF values test (default false)
- * disable.logpdf = false
- * # CDF values test (default false)
- * disable.cdf = false
- * # Survival function values test (default false)
- * disable.sf = false
+ * # Optional per-test tolerance and disable
+ * cdf.hp.relative = 1e-14
+ * cdf.hp.absolute = 1e-50
+ * sampling.disable = true
* </pre>
*
* <p>See {@link NakagamiDistributionTest} for an example and the resource
file {@code test.nakagami.1.properties}.
@@ -224,17 +218,6 @@ abstract class BaseContinuousDistributionTest
// as the @ParameterizedTest method. These can be overridden by child
classes to
// stream different arguments to the test case.
- /**
- * Create a stream of arguments containing the distribution to test, the
CDF
- * test points and the test tolerance.
- *
- * @return the stream
- */
- Stream<Arguments> streamCdfTestPoints() {
- return streamPoints(ContinuousDistributionTestData::getCdfPoints,
- this::createTestTolerance, "cdf test points");
- }
-
/**
* Create a stream of arguments containing the distribution to test, the
PDF test points
* and values, and the test tolerance.
@@ -242,10 +225,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testDensity() {
- return stream(ContinuousDistributionTestData::isDisablePdf,
+ return stream(TestName.PDF,
ContinuousDistributionTestData::getPdfPoints,
- ContinuousDistributionTestData::getPdfValues,
- this::createTestTolerance, "pdf");
+ ContinuousDistributionTestData::getPdfValues);
}
/**
@@ -255,10 +237,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testLogDensity() {
- return stream(ContinuousDistributionTestData::isDisableLogPdf,
+ return stream(TestName.LOGPDF,
ContinuousDistributionTestData::getPdfPoints,
- ContinuousDistributionTestData::getLogPdfValues,
- this::createTestTolerance, "logpdf");
+ ContinuousDistributionTestData::getLogPdfValues);
}
/**
@@ -268,10 +249,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbability() {
- return stream(ContinuousDistributionTestData::isDisableCdf,
+ return stream(TestName.CDF,
ContinuousDistributionTestData::getCdfPoints,
- ContinuousDistributionTestData::getCdfValues,
- this::createTestTolerance, "cdf");
+ ContinuousDistributionTestData::getCdfValues);
}
/**
@@ -283,10 +263,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbability() {
- return stream(ContinuousDistributionTestData::isDisableSf,
+ return stream(TestName.SF,
ContinuousDistributionTestData::getSfPoints,
- ContinuousDistributionTestData::getSfValues,
- this::createTestTolerance, "sf");
+ ContinuousDistributionTestData::getSfValues);
}
/**
@@ -296,9 +275,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbabilityHighPrecision() {
- return stream(ContinuousDistributionTestData::getCdfHpPoints,
- ContinuousDistributionTestData::getCdfHpValues,
- this::createTestHighPrecisionTolerance, "cdf.hp");
+ return stream(TestName.CDF_HP,
+ ContinuousDistributionTestData::getCdfHpPoints,
+ ContinuousDistributionTestData::getCdfHpValues);
}
/**
@@ -308,9 +287,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbabilityHighPrecision() {
- return stream(ContinuousDistributionTestData::getSfHpPoints,
- ContinuousDistributionTestData::getSfHpValues,
- this::createTestHighPrecisionTolerance, "sf.hp");
+ return stream(TestName.SF_HP,
+ ContinuousDistributionTestData::getSfHpPoints,
+ ContinuousDistributionTestData::getSfHpValues);
}
/**
@@ -320,9 +299,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testInverseCumulativeProbability() {
- return stream(ContinuousDistributionTestData::getIcdfPoints,
- ContinuousDistributionTestData::getIcdfValues,
- this::createTestTolerance, "icdf");
+ return stream(TestName.ICDF,
+ ContinuousDistributionTestData::getIcdfPoints,
+ ContinuousDistributionTestData::getIcdfValues);
}
/**
@@ -332,9 +311,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testInverseSurvivalProbability() {
- return stream(ContinuousDistributionTestData::getIsfPoints,
- ContinuousDistributionTestData::getIsfValues,
- this::createTestTolerance, "isf");
+ return stream(TestName.ISF,
+ ContinuousDistributionTestData::getIsfPoints,
+ ContinuousDistributionTestData::getIsfValues);
}
/**
@@ -345,9 +324,8 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbabilityInverseMapping() {
- return
streamPoints(ContinuousDistributionTestData::isDisableCdfInverse,
- ContinuousDistributionTestData::getCdfPoints,
- this::createTestTolerance, "cdf test points");
+ return stream(TestName.CDF_MAPPING,
+ ContinuousDistributionTestData::getCdfPoints);
}
/**
@@ -358,9 +336,8 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbabilityInverseMapping() {
- return streamPoints(ContinuousDistributionTestData::isDisableSfInverse,
- ContinuousDistributionTestData::getSfPoints,
- this::createTestTolerance, "sf test points");
+ return stream(TestName.SF_MAPPING,
+ ContinuousDistributionTestData::getSfPoints);
}
/**
@@ -370,9 +347,10 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalAndCumulativeProbabilityComplement() {
- // This is not disabled based on isDisableCdf && isDisableSf.
+ // This is not disabled based on cdf.disable && sf.disable.
// Those flags are intended to ignore tests against reference values.
- return streamCdfTestPoints();
+ return stream(TestName.COMPLEMENT,
+ ContinuousDistributionTestData::getCdfPoints);
}
/**
@@ -383,9 +361,10 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testConsistency() {
- // This is not disabled based on isDisableCdf.
- // That flags is intended to ignore tests against reference values.
- return streamCdfTestPoints();
+ // This is not disabled based on cdf.disable.
+ // That flag is intended to ignore tests against reference values.
+ return stream(TestName.CONSISTENCY,
+ ContinuousDistributionTestData::getCdfPoints);
}
/**
@@ -394,7 +373,7 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSampling() {
- return
streamDistributionWithFilter(ContinuousDistributionTestData::isDisableSample,
"sampling");
+ return stream(TestName.SAMPLING);
}
/**
@@ -404,20 +383,17 @@ abstract class BaseContinuousDistributionTest
* the underlying integrator (abs=1e-10, rel=1e-12).
* Override this method to change the tolerance.
*
- * <p>This is disabled by {@link
ContinuousDistributionTestData#isDisablePdf()}. If
- * the distribution cannot compute the density to match reference values
then it
- * is assumed an integral of the PDF will fail to match reference CDF
values.
- *
* @return the stream
*/
Stream<Arguments> testDensityIntegrals() {
// Create a tolerance suitable for the same thresholds used by the
integrator.
final Function<ContinuousDistributionTestData, DoubleTolerance>
tolerance =
d -> createAbsOrRelTolerance(INTEGRATOR_ABS_ACCURACY * 10,
INTEGRATOR_REL_ACCURACY * 10);
- return stream(ContinuousDistributionTestData::isDisablePdf,
+ final TestName name = TestName.INTEGRALS;
+ return stream(d -> d.isDisabled(name),
ContinuousDistributionTestData::getCdfPoints,
ContinuousDistributionTestData::getCdfValues,
- tolerance, "pdf integrals");
+ tolerance, name.toString());
}
/**
@@ -427,7 +403,8 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testSupport() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), d.getLower(), d.getUpper()));
+ return streamArguments(TestName.SUPPORT,
+ d -> Arguments.of(namedDistribution(d.getParameters()),
d.getLower(), d.getUpper()));
}
/**
@@ -437,7 +414,10 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testMoments() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), d.getMean(),
d.getVariance(), createTestTolerance(d)));
+ final TestName name = TestName.MOMENTS;
+ return streamArguments(name,
+ d -> Arguments.of(namedDistribution(d.getParameters()),
d.getMean(), d.getVariance(),
+ createTestTolerance(d, name)));
}
/**
@@ -446,7 +426,9 @@ abstract class BaseContinuousDistributionTest
* @return the stream
*/
Stream<Arguments> testMedian() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), createTestTolerance(d)));
+ final TestName name = TestName.MEDIAN;
+ return streamArguments(name,
+ d -> Arguments.of(namedDistribution(d.getParameters()),
createTestTolerance(d, name)));
}
//------------------------ Tests -----------------------------
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDiscreteDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDiscreteDistributionTest.java
index 6253e56..c38483a 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDiscreteDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDiscreteDistributionTest.java
@@ -65,7 +65,7 @@ import org.junit.jupiter.params.provider.MethodSource;
* The parameters are parsed from String values to the appropriate parameter
object. Currently
* this supports Double and Integer; numbers can be unboxed and used to create
the distribution.
*
- * <p>Illegal arguments for the distribution are tested from
parametersprovided by
+ * <p>Illegal arguments for the distribution are tested from parameters
provided by
* {@link #makeInvalidParameters()}. If there are no illegal arguments this
method may return
* null to skip the test. Primitive parameters are boxed to objects so ensure
the canonical form
* is used, e.g. {@code 1.0} not {@code 1} for a {@code double} argument.
@@ -87,13 +87,11 @@ import org.junit.jupiter.params.provider.MethodSource;
* <li>Points for the PMF (and log PMF) can be specified. The default will use
the CDF points.
* Note: It is not expected that evaluation of the PMF will require different
points to the CDF.
* <li>Points and expected values for the inverse CDF can be specified. These
are used in
- * addition to test the inverse mapping of the CDF values to the CDF test
points. The
- * inverse mapping test can be disabled.
+ * addition to test the inverse mapping of the CDF values to the CDF test
points.
* <li>Expected values for the log PMF can be specified. The default will use
* {@link Math#log(double)} on the PMF values.
* <li>Points and expected values for the survival function can be specified.
These are used in
- * addition to test the inverse mapping of the SF values to the SF test
points. The
- * inverse mapping test can be disabled.
+ * addition to test the inverse mapping of the SF values to the SF test points.
* The default will use the expected CDF values (SF = 1 - CDF).
* <li>A tolerance for equality assertions. The default is set by {@link
#getAbsoluteTolerance()}
* and {@link #getRelativeTolerance()}.
@@ -101,9 +99,19 @@ import org.junit.jupiter.params.provider.MethodSource;
*
* <p>If the distribution provides higher precision implementations of
* cumulative probability and/or survival probability as the values approach
zero, then test
- * points and expected values can be provided with a tolerance for equality
assertions of
- * high-precision computations. The default is set by {@link
#getHighPrecisionAbsoluteTolerance()}
- * and {@link #getHighPrecisionRelativeTolerance()}.
+ * points and expected values can be provided for high-precision computations.
If the default
+ * absolute tolerance has been set to non-zero, then very small p-values will
require the
+ * high-precision absolute tolerance is configured for the test to a suitable
magnitude (see below).
+ *
+ * <p>Per-test configuration
+ *
+ * <p>Each test is identified with a {@link TestName} key in the properties
file. This key
+ * can be used to set a per-test tolerance, or disable the test:
+ * <pre>
+ * cdf.hp.relative = 1e-14
+ * cdf.hp.absolute = 1e-50
+ * sampling.disable
+ * </pre>
*
* <p>Note: All properties files are read during test initialization. Any
errors in a single
* property file will throw an exception, invalidating the initialization and
no tests
@@ -136,7 +144,7 @@ import org.junit.jupiter.params.provider.MethodSource;
*
* <p>The properties file uses {@code key=value} pairs loaded using a
* {@link java.util.Properties} object. Values will be read as String and then
parsed to
- * numeric data, and data arrays. Multi-line values can use a {@code \}
character.
+ * numeric data, and data arrays. Multi-line values can use a {@code \}
character to join lines.
* Data in the properties file will be converted to numbers using standard
parsing
* functions appropriate to the primitive type, e.g. {@link
Double#parseDouble(String)}.
* Special double values should use NaN, Infinity and -Infinity. As a
convenience
@@ -158,10 +166,6 @@ import org.junit.jupiter.params.provider.MethodSource;
* tolerance.relative = 1e-9
* # optional (default 0.0 or over-ridden in getAbsoluteTolerance())
* tolerance.absolute = 0.0
- * # optional (default 1e-12 or over-ridden in
getHighPrecisionRelativeTolerance())
- * tolerance.relative.hp = 1e-10
- * # optional (default 0.0 or over-ridden in
getHighPrecisionAbsoluteTolerance())
- * tolerance.absolute.hp = 1e-30
* cdf.points = 0, 2
* cdf.values = 0.0, 0.5
* # optional (default uses cdf.points)
@@ -185,22 +189,10 @@ import org.junit.jupiter.params.provider.MethodSource;
* # optional inverse CDF test (defaults to ignore)
* isf.points = 1.0, 0.5
* isf.values = 3, 4
- * # CDF inverse mapping test (default false)
- * disable.cdf.inverse = false
- * # SF inverse mapping test (default false)
- * disable.sf.inverse = false
- * # Sampling test (default false)
- * disable.sample = false
- * # PMF values test (default false)
- * disable.pmf = false
- * # Log PMF values test (default false)
- * disable.logpmf = false
- * # CDF values test (default false)
- * disable.cdf = false
- * # Survival function values test (default false)
- * disable.sf = false
- * # Sampling PMF summation verses CDF test (default false)
- * disable.pmf.sum = false
+ * # Optional per-test tolerance and disable
+ * cdf.hp.relative = 1e-14
+ * cdf.hp.absolute = 1e-50
+ * sampling.disable = true
* </pre>
*
* <p>See {@link BinomialDistributionTest} for an example and the resource
file {@code test.binomial.1.properties}.
@@ -224,14 +216,15 @@ abstract class BaseDiscreteDistributionTest
// stream different arguments to the test case.
/**
- * Create a stream of arguments containing the distribution to test, the
CDF test points and
- * the test tolerance.
+ * Create a stream of arguments containing the distribution to test, the
CDF test
+ * points and the test tolerance.
*
+ * @param name Name of the function under test
* @return the stream
*/
- Stream<Arguments> streamCdfTestPoints() {
- return streamPoints(DiscreteDistributionTestData::getCdfPoints,
- this::createTestTolerance, "cdf test points");
+ Stream<Arguments> streamCdfTestPoints(TestName name) {
+ return stream(name,
+ DiscreteDistributionTestData::getCdfPoints);
}
/**
@@ -241,10 +234,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testProbability() {
- return stream(DiscreteDistributionTestData::isDisablePmf,
+ return stream(TestName.PMF,
DiscreteDistributionTestData::getPmfPoints,
- DiscreteDistributionTestData::getPmfValues,
- this::createTestTolerance, "pmf");
+ DiscreteDistributionTestData::getPmfValues);
}
/**
@@ -254,10 +246,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testLogProbability() {
- return stream(DiscreteDistributionTestData::isDisableLogPmf,
+ return stream(TestName.LOGPMF,
DiscreteDistributionTestData::getPmfPoints,
- DiscreteDistributionTestData::getLogPmfValues,
- this::createTestTolerance, "logpmf");
+ DiscreteDistributionTestData::getLogPmfValues);
}
/**
@@ -267,10 +258,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbability() {
- return stream(DiscreteDistributionTestData::isDisableCdf,
+ return stream(TestName.CDF,
DiscreteDistributionTestData::getCdfPoints,
- DiscreteDistributionTestData::getCdfValues,
- this::createTestTolerance, "cdf");
+ DiscreteDistributionTestData::getCdfValues);
}
/**
@@ -282,10 +272,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbability() {
- return stream(DiscreteDistributionTestData::isDisableSf,
+ return stream(TestName.SF,
DiscreteDistributionTestData::getSfPoints,
- DiscreteDistributionTestData::getSfValues,
- this::createTestTolerance, "sf");
+ DiscreteDistributionTestData::getSfValues);
}
/**
@@ -295,9 +284,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbabilityHighPrecision() {
- return stream(DiscreteDistributionTestData::getCdfHpPoints,
- DiscreteDistributionTestData::getCdfHpValues,
- this::createTestHighPrecisionTolerance, "cdf.hp");
+ return stream(TestName.CDF_HP,
+ DiscreteDistributionTestData::getCdfHpPoints,
+ DiscreteDistributionTestData::getCdfHpValues);
}
/**
@@ -307,9 +296,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbabilityHighPrecision() {
- return stream(DiscreteDistributionTestData::getSfHpPoints,
- DiscreteDistributionTestData::getSfHpValues,
- this::createTestHighPrecisionTolerance, "sf.hp");
+ return stream(TestName.SF_HP,
+ DiscreteDistributionTestData::getSfHpPoints,
+ DiscreteDistributionTestData::getSfHpValues);
}
/**
@@ -319,8 +308,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testInverseCumulativeProbability() {
- return stream(DiscreteDistributionTestData::getIcdfPoints,
- DiscreteDistributionTestData::getIcdfValues, "icdf");
+ return stream(TestName.ICDF,
+ DiscreteDistributionTestData::getIcdfPoints,
+ DiscreteDistributionTestData::getIcdfValues);
}
/**
@@ -330,8 +320,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testInverseSurvivalProbability() {
- return stream(DiscreteDistributionTestData::getIsfPoints,
- DiscreteDistributionTestData::getIsfValues, "isf");
+ return stream(TestName.ISF,
+ DiscreteDistributionTestData::getIsfPoints,
+ DiscreteDistributionTestData::getIsfValues);
}
/**
@@ -340,9 +331,8 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testCumulativeProbabilityInverseMapping() {
- return stream(DiscreteDistributionTestData::isDisableCdfInverse,
- DiscreteDistributionTestData::getCdfPoints,
- "cdf test points");
+ return stream(TestName.CDF_MAPPING,
+ DiscreteDistributionTestData::getCdfPoints);
}
/**
@@ -351,9 +341,8 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalProbabilityInverseMapping() {
- return stream(DiscreteDistributionTestData::isDisableSfInverse,
- DiscreteDistributionTestData::getSfPoints,
- "sf test points");
+ return stream(TestName.SF_MAPPING,
+ DiscreteDistributionTestData::getSfPoints);
}
/**
@@ -363,9 +352,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testSurvivalAndCumulativeProbabilityComplement() {
- // This is not disabled based on isDisableCdf && isDisableSf.
+ // This is not disabled based on cdf.disable && sf.disable.
// Those flags are intended to ignore tests against reference values.
- return streamCdfTestPoints();
+ return streamCdfTestPoints(TestName.COMPLEMENT);
}
/**
@@ -376,9 +365,9 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testConsistency() {
- // This is not disabled based on isDisableCdf.
- // That flags is intended to ignore tests against reference values.
- return streamCdfTestPoints();
+ // This is not disabled based on cdf.disable.
+ // That flag is intended to ignore tests against reference values.
+ return streamCdfTestPoints(TestName.CONSISTENCY);
}
/**
@@ -387,7 +376,7 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testOutsideSupport() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), createTestTolerance(d)));
+ return stream(TestName.OUTSIDE_SUPPORT);
}
/**
@@ -396,10 +385,10 @@ abstract class BaseDiscreteDistributionTest
*
* @return the stream
*/
- Stream<Arguments> testSampling() {
- return stream(DiscreteDistributionTestData::isDisableSample,
+ Stream<Arguments> testSamplingPMF() {
+ return stream(TestName.SAMPLING_PMF,
DiscreteDistributionTestData::getPmfPoints,
- DiscreteDistributionTestData::getPmfValues, "pmf
sampling");
+ DiscreteDistributionTestData::getPmfValues);
}
/**
@@ -410,8 +399,8 @@ abstract class BaseDiscreteDistributionTest
*
* @return the stream
*/
- Stream<Arguments> testSamplingQuartiles() {
- return
streamDistributionWithFilter(DiscreteDistributionTestData::isDisableSample,
"sampling quartiles");
+ Stream<Arguments> testSampling() {
+ return stream(TestName.SAMPLING);
}
/**
@@ -421,22 +410,21 @@ abstract class BaseDiscreteDistributionTest
* of single points of the CDF.
* Override this method to change the tolerance.
*
- * <p>This is disabled by {@link
DiscreteDistributionTestData#isDisablePmf()}. If
- * the distribution cannot compute the PMF to match reference values then
it
- * is assumed a sum of the PMF will fail to match reference CDF values.
- *
* @return the stream
*/
Stream<Arguments> testProbabilitySums() {
// Assume the the test tolerance for single CDF values can be relaxed
slightly
// when summing values.
final double scale = 10;
+ final TestName cdf = TestName.CDF;
final Function<DiscreteDistributionTestData, DoubleTolerance>
tolerance =
- d -> createAbsOrRelTolerance(d.getAbsoluteTolerance() * scale,
d.getRelativeTolerance() * scale);
- return stream(d -> d.isDisablePmf() || d.isDisablePmfSum(),
+ d -> createAbsOrRelTolerance(d.getAbsoluteTolerance(cdf) * scale,
+ d.getRelativeTolerance(cdf) * scale);
+ final TestName name = TestName.PMF_SUM;
+ return stream(d -> d.isDisabled(name),
DiscreteDistributionTestData::getCdfPoints,
DiscreteDistributionTestData::getCdfValues,
- tolerance, "pmf sums");
+ tolerance, name.toString());
}
/**
@@ -446,7 +434,8 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testSupport() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), d.getLower(), d.getUpper()));
+ return streamArguments(TestName.SUPPORT,
+ d -> Arguments.of(namedDistribution(d.getParameters()),
d.getLower(), d.getUpper()));
}
/**
@@ -456,7 +445,10 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testMoments() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters()), d.getMean(),
d.getVariance(), createTestTolerance(d)));
+ final TestName name = TestName.MOMENTS;
+ return streamArguments(name,
+ d -> Arguments.of(namedDistribution(d.getParameters()),
d.getMean(), d.getVariance(),
+ createTestTolerance(d, name)));
}
/**
@@ -465,7 +457,8 @@ abstract class BaseDiscreteDistributionTest
* @return the stream
*/
Stream<Arguments> testMedian() {
- return data.stream().map(d ->
Arguments.of(namedDistribution(d.getParameters())));
+ return streamArguments(TestName.MEDIAN,
+ d -> Arguments.of(namedDistribution(d.getParameters())));
}
//------------------------ Tests -----------------------------
@@ -942,12 +935,14 @@ abstract class BaseDiscreteDistributionTest
/**
* Test sampling from the distribution.
+ * This test uses the points that are used to test the distribution PMF.
+ * The test is skipped if the sum of the PMF values is less than 0.5.
*/
@ParameterizedTest
@MethodSource
- final void testSampling(DiscreteDistribution dist,
- int[] points,
- double[] values) {
+ final void testSamplingPMF(DiscreteDistribution dist,
+ int[] points,
+ double[] values) {
// This test uses the points that are used to test the distribution
PMF.
// The sum of the probability values does not have to be 1 (or very
close to 1).
// Any value generated by the sampler that is not an expected point
will
@@ -1002,12 +997,12 @@ abstract class BaseDiscreteDistributionTest
* Test sampling from the distribution using quartiles.
* This test is ignored if the range for the distribution PMF is small
* and the quartiles do not map to approximately 0.25. When the range of
- * the distribution is small then the {@link
#testSampling(DiscreteDistribution, int[], double[])}
+ * the distribution is small then the {@link
#testSamplingPMF(DiscreteDistribution, int[], double[])}
* method should be used with points that covers at least 50% of the PMF.
*/
@ParameterizedTest
@MethodSource
- final void testSamplingQuartiles(DiscreteDistribution dist) {
+ final void testSampling(DiscreteDistribution dist) {
final int[] quartiles = TestUtils.getDistributionQuartiles(dist);
// The distribution quartiles are created using the inverse CDF.
// This may not be accurate for extreme parameterizations of the
distribution.
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDistributionTest.java
index aa7da83..e669a3a 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BaseDistributionTest.java
@@ -27,7 +27,6 @@ import java.util.Locale;
import java.util.Properties;
import java.util.function.Function;
import java.util.function.Predicate;
-import java.util.function.ToDoubleFunction;
import java.util.stream.Stream;
import java.util.stream.Stream.Builder;
import org.junit.jupiter.api.Assertions;
@@ -55,7 +54,7 @@ import org.junit.jupiter.params.provider.MethodSource;
* <p>The class has two specializations for testing {@link
ContinuousDistribution} and
* {@link DiscreteDistribution}. It is not intended to extend this class when
creating
* a test for a new distribution. This class exists for the sole purpose of
containing
- * commons functionality to search for and load properties files containing
the distribution
+ * common functionality to search for and load properties files containing the
distribution
* data.
*
* <p>To test a new distribution extend the specialized classes:
@@ -105,8 +104,6 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
final Properties defaults = new Properties();
defaults.setProperty(DistributionTestData.KEY_TOLERANCE_ABSOLUTE,
String.valueOf(getAbsoluteTolerance()));
defaults.setProperty(DistributionTestData.KEY_TOLERANCE_RELATIVE,
String.valueOf(getRelativeTolerance()));
- defaults.setProperty(DistributionTestData.KEY_TOLERANCE_ABSOLUTE_HP,
String.valueOf(getHighPrecisionAbsoluteTolerance()));
- defaults.setProperty(DistributionTestData.KEY_TOLERANCE_RELATIVE_HP,
String.valueOf(getHighPrecisionRelativeTolerance()));
for (int i = 1; ; i++) {
final String filename = String.format("test.%s.%d.properties",
key, i);
try (InputStream resource = this.getClass().getResourceAsStream(
@@ -161,42 +158,6 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
return 1e-12;
}
- /**
- * Gets the default absolute tolerance used in comparing expected and
returned values in high precision tests.
- *
- * <p>The initial value is 0.0 (disabled).
- *
- * <p>Override this method to set the <strong>default</strong>
high-precision absolute tolerance for all test
- * cases defined by a properties file. Any properties file with a
high-precision absolute tolerance entry
- * ignores this value.
- *
- * <p>Notes: Floating-point values are considered equal using the absolute
or the relative tolerance.
- * See {@link #createHighPrecisionTolerance()}.
- *
- * @return the high precision absolute tolerance
- */
- protected double getHighPrecisionAbsoluteTolerance() {
- return 0.0;
- }
-
- /**
- * Gets the default relative tolerance used in comparing expected and
returned values in high precision tests.
- *
- * <p>The initial value is 1e-12.
- *
- * <p>Override this method to set the <strong>default</strong>
high-precision relative tolerance for all test
- * cases defined by a properties file. Any properties file with a
high-precision relative tolerance entry
- * ignores this value.
- *
- * <p>Notes: Floating-point values are considered equal using the absolute
or the relative tolerance.
- * See {@link #createHighPrecisionTolerance()}.
- *
- * @return the high precision relative tolerance
- */
- protected double getHighPrecisionRelativeTolerance() {
- return 1e-12;
- }
-
/**
* Gets the distribution name. This is used to search for test case
resource files.
*
@@ -296,27 +257,8 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
}
/**
- * Creates the tolerance using an {@code Or} combination of absolute and
relative error.
- *
- * <p>If the absolute tolerance is zero it is ignored and a tolerance of
numerical equality
- * is used.
- *
- * <p>If the relative tolerance is zero it is ignored.
- *
- * @param testData Test data
- * @param absTolerance Function to create the absolute tolerance
- * @param relTolerance Function to create the relative tolerance
- * @return the tolerance
- */
- DoubleTolerance createTestAbsOrRelTolerance(
- D testData, ToDoubleFunction<D> absTolerance, ToDoubleFunction<D>
relTolerance) {
- final double abs = absTolerance == null ? 0 :
absTolerance.applyAsDouble(testData);
- final double rel = relTolerance == null ? 0 :
relTolerance.applyAsDouble(testData);
- return createAbsOrRelTolerance(abs, rel);
- }
-
- /**
- * Creates the default tolerance for the test data.
+ * Creates the tolerance using an {@code Or} combination of absolute and
relative error
+ * defined in the test data.
*
* <p>If the absolute tolerance is zero it is ignored and a tolerance of
numerical equality
* is used.
@@ -327,13 +269,15 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
* @return the tolerance
*/
DoubleTolerance createTestTolerance(D testData) {
- return createTestAbsOrRelTolerance(testData,
-
DistributionTestData::getAbsoluteTolerance,
-
DistributionTestData::getRelativeTolerance);
+ final double abs = testData.getAbsoluteTolerance();
+ final double rel = testData.getRelativeTolerance();
+ return createAbsOrRelTolerance(abs, rel);
}
/**
- * Creates the default high-precision tolerance for the test data.
+ * Creates the tolerance for the named test using an {@code Or}
combination of absolute
+ * and relative error defined in the test data. If the named test
tolerance is not defined
+ * then this uses the default tolerance.
*
* <p>If the absolute tolerance is zero it is ignored and a tolerance of
numerical equality
* is used.
@@ -341,12 +285,13 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
* <p>If the relative tolerance is zero it is ignored.
*
* @param testData Test data
+ * @param name Name of the function under test
* @return the tolerance
*/
- DoubleTolerance createTestHighPrecisionTolerance(D testData) {
- return createTestAbsOrRelTolerance(testData,
-
DistributionTestData::getHighPrecisionAbsoluteTolerance,
-
DistributionTestData::getHighPrecisionRelativeTolerance);
+ DoubleTolerance createTestTolerance(D testData, TestName name) {
+ final double abs = testData.getAbsoluteTolerance(name);
+ final double rel = testData.getRelativeTolerance(name);
+ return createAbsOrRelTolerance(abs, rel);
}
/**
@@ -364,21 +309,6 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
getRelativeTolerance());
}
- /**
- * Creates the default high-precision tolerance.
- *
- * <p>If the absolute tolerance is zero it is ignored and a tolerance of
numerical equality
- * is used.
- *
- * <p>If the relative tolerance is zero it is ignored.
- *
- * @return the tolerance
- */
- DoubleTolerance createHighPrecisionTolerance() {
- return createAbsOrRelTolerance(getHighPrecisionAbsoluteTolerance(),
- getHighPrecisionRelativeTolerance());
- }
-
//------------------------ Methods to stream the test data
-----------------------------
// The @MethodSource annotation will default to a no arguments method of
the same name
@@ -475,17 +405,6 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
return Named.of(sb.toString(), array);
}
- /**
- * Create a predicate that returns false. This can be used to signal do
not ignore
- * for test data.
- *
- * @param <D> Type of object
- * @return the predicate
- */
- private static <D> Predicate<D> doNotIgnore() {
- return d -> false;
- }
-
/**
* Create a stream of arguments containing the distribution to test.
*
@@ -496,81 +415,23 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
}
/**
- * Create a stream of arguments containing the distribution to test.
+ * Create a stream of arguments containing the distribution to test and
the test tolerance.
+ * The tolerance is identified using functions on the test instance data.
+ * The test data will be skipped if disabled.
*
- * @param filter Filter applied on the test data. If true the data is
ignored.
- * @param name Name of the function under test
- * @return the stream
- */
- Stream<Arguments> streamDistributionWithFilter(Predicate<D> filter,
- String name) {
- final Builder<Arguments> b = Stream.builder();
- final int[] size = {0};
- data.forEach(d -> {
- if (filter.test(d)) {
- return;
- }
- size[0]++;
- b.accept(Arguments.of(namedDistribution(d.getParameters())));
- });
- Assumptions.assumeTrue(size[0] != 0, () -> "Distribution has no data
for " + name);
- return b.build();
- }
-
- /**
- * Create a stream of arguments containing the distribution to test, the
test
- * points, test values and the test tolerance. The points, values and
tolerance
- * are identified using functions on the test instance data.
- *
- * <p>If the length of the points or values is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param points Function to create the points
- * @param values Function to create the values
- * @param tolerance Function to create the tolerance
- * @param name Name of the function under test
- * @return the stream
- */
- <P, V> Stream<Arguments> stream(Function<D, P> points,
- Function<D, V> values,
- ToDoubleFunction<D> tolerance,
- String name) {
- return stream(doNotIgnore(), points, values, tolerance, name);
- }
-
- /**
- * Create a stream of arguments containing the distribution to test, the
test
- * points, test values and the test tolerance. The points, values and
tolerance
- * are identified using functions on the test instance data.
- *
- * <p>If the length of the points or values is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param filter Filter applied on the test data. If true the data is
ignored.
- * @param points Function to create the points
- * @param values Function to create the values
- * @param tolerance Function to create the tolerance
* @param name Name of the function under test
* @return the stream
*/
- <P, V> Stream<Arguments> stream(Predicate<D> filter,
- Function<D, P> points,
- Function<D, V> values,
- ToDoubleFunction<D> tolerance,
- String name) {
+ Stream<Arguments> stream(TestName name) {
final Builder<Arguments> b = Stream.builder();
final int[] size = {0};
data.forEach(d -> {
- final P p = points.apply(d);
- final V v = values.apply(d);
- if (filter.test(d) || TestUtils.getLength(p) == 0 ||
TestUtils.getLength(v) == 0) {
+ if (d.isDisabled(name)) {
return;
}
size[0]++;
b.accept(Arguments.of(namedDistribution(d.getParameters()),
- namedArray("points", p),
- namedArray("values", v),
- tolerance.applyAsDouble(d)));
+ createTestTolerance(d, name)));
});
Assumptions.assumeTrue(size[0] != 0, () -> "Distribution has no data
for " + name);
return b.build();
@@ -580,50 +441,28 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
* Create a stream of arguments containing the distribution to test, the
test
* points, and the test tolerance. The points and tolerance
* are identified using functions on the test instance data.
+ * The test data will be skipped if disabled or the length of the points
is zero.
*
- * <p>If the length of the points is zero then a
+ * <p>If all test data is skipped then a
* {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
*
- * @param points Function to create the points
- * @param tolerance Function to create the tolerance
* @param name Name of the function under test
- * @return the stream
- */
- <P, V> Stream<Arguments> streamPoints(Function<D, P> points,
- Function<D, DoubleTolerance>
tolerance,
- String name) {
- return streamPoints(doNotIgnore(), points, tolerance, name);
- }
-
- /**
- * Create a stream of arguments containing the distribution to test, the
test
- * points, and the test tolerance. The points and tolerance
- * are identified using functions on the test instance data.
- *
- * <p>If the length of the points is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param filter Filter applied on the test data. If true the data is
ignored.
* @param points Function to create the points
- * @param tolerance Function to create the tolerance
- * @param name Name of the function under test
* @return the stream
*/
- <P, V> Stream<Arguments> streamPoints(Predicate<D> filter,
- Function<D, P> points,
- Function<D, DoubleTolerance>
tolerance,
- String name) {
+ <P> Stream<Arguments> stream(TestName name,
+ Function<D, P> points) {
final Builder<Arguments> b = Stream.builder();
final int[] size = {0};
data.forEach(d -> {
final P p = points.apply(d);
- if (filter.test(d) || TestUtils.getLength(p) == 0) {
+ if (d.isDisabled(name) || TestUtils.getLength(p) == 0) {
return;
}
size[0]++;
b.accept(Arguments.of(namedDistribution(d.getParameters()),
namedArray("points", p),
- tolerance.apply(d)));
+ createTestTolerance(d, name)));
});
Assumptions.assumeTrue(size[0] != 0, () -> "Distribution has no data
for " + name);
return b.build();
@@ -633,29 +472,34 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
* Create a stream of arguments containing the distribution to test, the
test
* points, test values and the test tolerance. The points, values and
tolerance
* are identified using functions on the test instance data.
+ * The test data will be skipped if disabled or the length of the points
or values is zero.
*
- * <p>If the length of the points or values is zero then a
+ * <p>If all test data is skipped then a
* {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
*
+ * @param name Name of the function under test
* @param points Function to create the points
* @param values Function to create the values
- * @param tolerance Function to create the tolerance
- * @param name Name of the function under test
* @return the stream
*/
- <P, V> Stream<Arguments> stream(Function<D, P> points,
- Function<D, V> values,
- Function<D, DoubleTolerance> tolerance,
- String name) {
- return stream(doNotIgnore(), points, values, tolerance, name);
+ <P, V> Stream<Arguments> stream(TestName name,
+ Function<D, P> points,
+ Function<D, V> values) {
+ // Delegate
+ return stream(d -> d.isDisabled(name),
+ points,
+ values,
+ d -> createTestTolerance(d, name),
+ name.toString());
}
/**
* Create a stream of arguments containing the distribution to test, the
test
* points, test values and the test tolerance. The points, values and
tolerance
* are identified using functions on the test instance data.
+ * The test data will be skipped if disabled or the length of the points
or values is zero.
*
- * <p>If the length of the points or values is zero then a
+ * <p>If all test data is skipped then a
* {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
*
* @param filter Filter applied on the test data. If true the data is
ignored.
@@ -689,101 +533,26 @@ abstract class BaseDistributionTest<T, D extends
DistributionTestData> {
}
/**
- * Create a stream of arguments containing the distribution to test, the
test
- * points, and test values. The points and values
- * are identified using functions on the test instance data.
- *
- * <p>If the length of the points or values is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param points Function to create the points
- * @param values Function to create the values
- * @param name Name of the function under test
- * @return the stream
- */
- <P, V> Stream<Arguments> stream(Function<D, P> points,
- Function<D, V> values,
- String name) {
- return stream(doNotIgnore(), points, values, name);
- }
-
- /**
- * Create a stream of arguments containing the distribution to test, the
test
- * points, and test values. The points and values
- * are identified using functions on the test instance data.
- *
- * <p>If the length of the points or values is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param filter Filter applied on the test data. If true the data is
ignored.
- * @param points Function to create the points
- * @param values Function to create the values
- * @param name Name of the function under test
- * @return the stream
- */
- <P, V> Stream<Arguments> stream(Predicate<D> filter,
- Function<D, P> points,
- Function<D, V> values,
- String name) {
- final Builder<Arguments> b = Stream.builder();
- final int[] size = {0};
- data.forEach(d -> {
- final P p = points.apply(d);
- final V v = values.apply(d);
- if (filter.test(d) || TestUtils.getLength(p) == 0 ||
TestUtils.getLength(v) == 0) {
- return;
- }
- size[0]++;
- b.accept(Arguments.of(namedDistribution(d.getParameters()),
- namedArray("points", p),
- namedArray("values", v)));
- });
- Assumptions.assumeTrue(size[0] != 0, () -> "Distribution has no data
for " + name);
- return b.build();
- }
-
-
- /**
- * Create a stream of arguments containing the distribution to test and
the test
- * points. The points are identified using functions on the test instance
data.
- *
- * <p>If the length of the points or values is zero then a
- * {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
- *
- * @param points Function to create the points
- * @param name Name of the function under test
- * @return the stream
- */
- <P> Stream<Arguments> stream(Function<D, P> points,
- String name) {
- return stream(doNotIgnore(), points, name);
- }
-
- /**
- * Create a stream of arguments containing the distribution to test and
the test
- * points. The points are identified using functions on the test instance
data.
+ * Create a stream of arguments built using the provided mapping function.
+ * The test data will be skipped if disabled.
*
- * <p>If the length of the points or values is zero then a
+ * <p>If all test data is skipped then a
* {@link org.opentest4j.TestAbortedException TestAbortedException} is
raised.
*
- * @param filter Filter applied on the test data. If true the data is
ignored.
- * @param points Function to create the points
* @param name Name of the function under test
+ * @param mappingFunction Function to create the arguments for the test
data
* @return the stream
*/
- <P> Stream<Arguments> stream(Predicate<D> filter,
- Function<D, P> points,
- String name) {
+ Stream<Arguments> streamArguments(TestName name,
+ Function<D, Arguments> mappingFunction) {
final Builder<Arguments> b = Stream.builder();
final int[] size = {0};
data.forEach(d -> {
- final P p = points.apply(d);
- if (filter.test(d) || TestUtils.getLength(p) == 0) {
+ if (d.isDisabled(name)) {
return;
}
size[0]++;
- b.accept(Arguments.of(namedDistribution(d.getParameters()),
- namedArray("points", p)));
+ b.accept(mappingFunction.apply(d));
});
Assumptions.assumeTrue(size[0] != 0, () -> "Distribution has no data
for " + name);
return b.build();
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/DistributionTestData.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/DistributionTestData.java
index 747192b..c05ae93 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/DistributionTestData.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/DistributionTestData.java
@@ -17,8 +17,13 @@
package org.apache.commons.statistics.distribution;
import java.util.Arrays;
+import java.util.Collections;
+import java.util.EnumMap;
+import java.util.EnumSet;
+import java.util.Map;
import java.util.Objects;
import java.util.Properties;
+import java.util.Set;
import java.util.regex.Pattern;
/**
@@ -35,10 +40,21 @@ abstract class DistributionTestData {
static final String KEY_TOLERANCE_ABSOLUTE = "tolerance.absolute";
/** The key for the relative tolerance value. */
static final String KEY_TOLERANCE_RELATIVE = "tolerance.relative";
- /** The key for the high-precision absolute tolerance value. */
- static final String KEY_TOLERANCE_ABSOLUTE_HP = "tolerance.absolute.hp";
- /** The key for the high-precision relative tolerance value. */
- static final String KEY_TOLERANCE_RELATIVE_HP = "tolerance.relative.hp";
+
+ /** The key suffix to disable a test. */
+ private static final String SUFFIX_DISABLE = ".disable";
+ /** The key suffix for the absolute tolerance value. */
+ private static final String SUFFIX_TOLERANCE_ABSOLUTE = ".absolute";
+ /** The key suffix for the relative tolerance value. */
+ private static final String SUFFIX_TOLERANCE_RELATIVE = ".relative";
+ /** The index for the absolute tolerance value in the array of tolerances.
*/
+ private static final int INDEX_ABSOLUTE = 0;
+ /** The index for the relative tolerance value in the array of tolerances.
*/
+ private static final int INDEX_RELATIVE = 1;
+ /** The unset (default) value for the tolerance. */
+ private static final double UNSET_TOLERANCE = -1;
+ /** The unset (default) values for the array of tolerances. */
+ private static final double[] UNSET_TOLERANCES = {UNSET_TOLERANCE,
UNSET_TOLERANCE};
/** Regex to split delimited text data (e.g. arrays of numbers). */
private static final Pattern PATTERN = Pattern.compile("[ ,]+");
@@ -47,10 +63,6 @@ abstract class DistributionTestData {
protected final double[] pfValues;
/** Expected log probability function values. */
protected final double[] logPfValues;
- /** Disable tests of the probability function method. */
- protected final boolean disablePf;
- /** Disable tests of the log probability function method. */
- protected final boolean disableLogPf;
/** Distribution parameters. */
private final Object[] parameters;
@@ -58,14 +70,15 @@ abstract class DistributionTestData {
private final double mean;
/** Variance. */
private final double variance;
+ /** Test tolerances. */
+ private final Map<TestName, double[]> tolerance;
+ /** Disabled tests. */
+ private final Set<TestName> disabled;
+
/** Test absolute tolerance for calculations. */
private final double absoluteTolerance;
/** Test relative tolerance for calculations. */
private final double relativeTolerance;
- /** Test absolute tolerance for high-precision calculations.. */
- private final double absoluteToleranceHp;
- /** Test relative tolerance for high-precision calculations.. */
- private final double relativeToleranceHp;
/** Expected CDF values. */
private final double[] cdfValues;
/** Expected SF values for the survival function test points. */
@@ -75,19 +88,6 @@ abstract class DistributionTestData {
/** Expected CDF values for the high-precision survival function test
points. */
private final double[] sfHpValues;
- // Flags to ignore required tests
-
- /** Disable a {@code x = icdf(cdf(x))} mapping test. */
- private final boolean disableCdfInverse;
- /** Disable a {@code x = isf(sf(x))} mapping test. */
- private final boolean disableSfInverse;
- /** Disable tests of the sample method. */
- private final boolean disableSample;
- /** Disable tests of the cumulative probability function method. */
- private final boolean disableCdf;
- /** Disable tests of the survival probability function method. */
- private final boolean disableSf;
-
/**
* Contains the data for the continuous distribution parameters, the
expected properties
* of the distribution (moments and support bounds) and test points to
evaluate
@@ -264,26 +264,6 @@ abstract class DistributionTestData {
double[] getIsfValues() {
return isfValues;
}
-
- /**
- * Checks if a test of the PDF method is disabled.
- *
- * @return true if a PDF test is disabled.
- * @see #getPdfValues()
- */
- boolean isDisablePdf() {
- return disablePf;
- }
-
- /**
- * Checks if a test of the log PDF method is disabled.
- *
- * @return true if a log PDF test is disabled.
- * @see #getLogPdfValues()
- */
- boolean isDisableLogPdf() {
- return disableLogPf;
- }
}
/**
@@ -314,8 +294,6 @@ abstract class DistributionTestData {
private final double[] isfPoints;
/** Expected inverse SF values. */
private final int[] isfValues;
- /** Disable tests of the summation of the PMF verses the CDF. */
- private final boolean disablePmfSum;
/**
* @param props Properties containing the test data
@@ -338,7 +316,6 @@ abstract class DistributionTestData {
icdfValues = getAsIntArray(props, "icdf.values", null);
isfPoints = getAsDoubleArray(props, "isf.points", null);
isfValues = getAsIntArray(props, "isf.values", null);
- disablePmfSum = getAsBoolean(props, "disable.pmf.sum", false);
// Validation
validatePair(cdfPoints, getCdfValues(), "cdf");
validatePair(pmfPoints, getPmfValues(), "pmf");
@@ -465,36 +442,6 @@ abstract class DistributionTestData {
int[] getIsfValues() {
return isfValues;
}
-
- /**
- * Checks if a test of the PMF method is disabled.
- *
- * @return true if a PMF test is disabled.
- * @see #getPmfValues()
- */
- boolean isDisablePmf() {
- return disablePf;
- }
-
- /**
- * Checks if a test of the log PMF method is disabled.
- *
- * @return true if a log PMF test is disabled.
- * @see #getLogPmfValues()
- */
- boolean isDisableLogPmf() {
- return disableLogPf;
- }
-
- /**
- * Checks if a test of the sum of the PMF verses the PDF is disabled.
- *
- * @return true the PMF sum test is disabled.
- * @see #getSfValues()
- */
- boolean isDisablePmfSum() {
- return disablePmfSum;
- }
}
/**
@@ -507,9 +454,7 @@ abstract class DistributionTestData {
mean = getAsDouble(props, "mean");
variance = getAsDouble(props, "variance");
absoluteTolerance = getAsDouble(props, KEY_TOLERANCE_ABSOLUTE);
- absoluteToleranceHp = getAsDouble(props, KEY_TOLERANCE_ABSOLUTE_HP);
relativeTolerance = getAsDouble(props, KEY_TOLERANCE_RELATIVE);
- relativeToleranceHp = getAsDouble(props, KEY_TOLERANCE_RELATIVE_HP);
// Required
cdfValues = getAsDoubleArray(props, "cdf.values");
final String pf = getProbabilityFunctionName();
@@ -527,13 +472,37 @@ abstract class DistributionTestData {
sfValues = tmp;
cdfHpValues = getAsDoubleArray(props, "cdf.hp.values", null);
sfHpValues = getAsDoubleArray(props, "sf.hp.values", null);
- disableCdfInverse = getAsBoolean(props, "disable.cdf.inverse", false);
- disableSfInverse = getAsBoolean(props, "disable.sf.inverse", false);
- disableSample = getAsBoolean(props, "disable.sample", false);
- disablePf = getAsBoolean(props, "disable." + pf, false);
- disableLogPf = getAsBoolean(props, "disable." + pf, false);
- disableCdf = getAsBoolean(props, "disable.cdf", false);
- disableSf = getAsBoolean(props, "disable.sf", false);
+
+ // Remove keys to prevent detection in when searching for test
tolerances
+ props.remove(KEY_TOLERANCE_ABSOLUTE);
+ props.remove(KEY_TOLERANCE_RELATIVE);
+
+ // Store custom tolerances and disabled tests
+ EnumMap<TestName, double[]> map = new EnumMap<>(TestName.class);
+ EnumSet<TestName> set = EnumSet.noneOf(TestName.class);
+ props.stringPropertyNames().forEach(key -> {
+ if (key.endsWith(SUFFIX_DISABLE) && getAsBoolean(props, key,
false)) {
+ final TestName name = TestName.fromString(key.substring(0,
key.length() - SUFFIX_DISABLE.length()));
+ if (name != null) {
+ set.add(name);
+ }
+ } else if (key.endsWith(SUFFIX_TOLERANCE_ABSOLUTE)) {
+ final TestName name = TestName.fromString(key.substring(0,
key.length() - SUFFIX_TOLERANCE_ABSOLUTE.length()));
+ if (name != null) {
+ final double[] tolerances = map.computeIfAbsent(name, k ->
UNSET_TOLERANCES.clone());
+ tolerances[INDEX_ABSOLUTE] = getAsDouble(props, key);
+ }
+ } else if (key.endsWith(SUFFIX_TOLERANCE_RELATIVE)) {
+ final TestName name = TestName.fromString(key.substring(0,
key.length() - SUFFIX_TOLERANCE_RELATIVE.length()));
+ if (name != null) {
+ final double[] tolerances = map.computeIfAbsent(name, k ->
UNSET_TOLERANCES.clone());
+ tolerances[INDEX_RELATIVE] = getAsDouble(props, key);
+ }
+ }
+ });
+
+ this.tolerance = map.isEmpty() ? Collections.emptyMap() : map;
+ this.disabled = set.isEmpty() ? Collections.emptySet() : set;
}
/**
@@ -681,22 +650,6 @@ abstract class DistributionTestData {
}
}
- /**
- * Gets the property as a boolean, or a default value if the property is
missing.
- *
- * @param props Properties
- * @param key Key
- * @return the value
- * @throws IllegalArgumentException if the parameter is not a boolean.
- */
- private static boolean getAsBoolean(Properties props, String key) {
- try {
- return Boolean.parseBoolean(props.getProperty(key));
- } catch (NumberFormatException ex) {
- throw new IllegalArgumentException("Invalid boolean: " + key, ex);
- }
- }
-
/**
* Gets the property as a boolean, or a default value if the property is
missing.
*
@@ -863,6 +816,45 @@ abstract class DistributionTestData {
/**
* Gets the absolute tolerance used when comparing expected and actual
results.
+ * If no tolerance exists for the named test then the default is returned.
+ *
+ * @param name Name of the test.
+ * @return the absolute tolerance
+ */
+ double getAbsoluteTolerance(TestName name) {
+ return getTolerance(name, INDEX_ABSOLUTE, absoluteTolerance);
+ }
+
+ /**
+ * Gets the relative tolerance used when comparing expected and actual
results.
+ * If no tolerance exists for the named test then the default is returned.
+ *
+ * @param name Name of the test.
+ * @return the relative tolerance
+ */
+ double getRelativeTolerance(TestName name) {
+ return getTolerance(name, INDEX_RELATIVE, relativeTolerance);
+ }
+
+ /**
+ * Gets the specified tolerance for the named test.
+ * If no tolerance exists for the named test then the default is returned.
+ *
+ * @param name Name of the test.
+ * @param index Index of the tolerance.
+ * @param defaultValue Default value is the tolerance is unset.
+ * @return the relative tolerance
+ */
+ private double getTolerance(TestName name, int index, double defaultValue)
{
+ final double[] tol = tolerance.get(name);
+ if (tol != null && tol[index] != UNSET_TOLERANCE) {
+ return tol[index];
+ }
+ return defaultValue;
+ }
+
+ /**
+ * Gets the default absolute tolerance used when comparing expected and
actual results.
*
* @return the absolute tolerance
*/
@@ -871,7 +863,7 @@ abstract class DistributionTestData {
}
/**
- * Gets the relative tolerance used when comparing expected and actual
results.
+ * Gets the default relative tolerance used when comparing expected and
actual results.
*
* @return the relative tolerance
*/
@@ -880,23 +872,23 @@ abstract class DistributionTestData {
}
/**
- * Gets the absolute tolerance used when comparing expected and actual
results
- * of high-precision computations.
+ * Checks if the named test is disabled.
*
- * @return the high-precision absolute tolerance
+ * @param name Name of the test.
+ * @return true if test is disabled.
*/
- double getHighPrecisionAbsoluteTolerance() {
- return absoluteToleranceHp;
+ boolean isDisabled(TestName name) {
+ return disabled.contains(name);
}
/**
- * Gets the relative tolerance used when comparing expected and actual
results
- * of high-precision computations.
+ * Checks if the named test is enabled.
*
- * @return the high-precision relative tolerance
+ * @param name Name of the test.
+ * @return true if test is enabled.
*/
- double getHighPrecisionRelativeTolerance() {
- return relativeToleranceHp;
+ boolean isEnabled(TestName name) {
+ return !isDisabled(name);
}
/**
@@ -948,62 +940,5 @@ abstract class DistributionTestData {
* @return the inverse SF points
*/
abstract double[] getIsfPoints();
-
- /**
- * Checks if a {@code x = icdf(cdf(x))} mapping test is disabled.
- *
- * <p>Note that this property disables a round-trip test of the points
used to test
- * the cumulative probability. The inverse cumulative probability can also
be tested
- * separately using the {@link #getIcdfPoints()} allowing the forward and
reverse
- * functions to target different data.
- *
- * @return true if a CDF inverse mapping test is disabled.
- */
- boolean isDisableCdfInverse() {
- return disableCdfInverse;
- }
-
- /**
- * Checks if a {@code x = isf(sf(x))} mapping test is disabled.
- *
- * <p>Note that this property disables a round-trip test of the points
used to test
- * the survival probability. The inverse survival probability can also be
tested
- * separately using the {@link #getIsfPoints()} allowing the forward and
reverse
- * functions to target different data.
- *
- * @return true if a SF inverse mapping test is disabled.
- */
- boolean isDisableSfInverse() {
- return disableSfInverse;
- }
-
- /**
- * Checks if a test of the sample method is disabled.
- *
- * @return true if a sample test is disabled.
- */
- boolean isDisableSample() {
- return disableSample;
- }
-
- /**
- * Checks if a test of the CDF method is disabled.
- *
- * @return true if a CDF test is disabled.
- * @see #getCdfValues()
- */
- boolean isDisableCdf() {
- return disableCdf;
- }
-
- /**
- * Checks if a test of the survival function method is disabled.
- *
- * @return true if a survival function test is disabled.
- * @see #getSfValues()
- */
- boolean isDisableSf() {
- return disableSf;
- }
}
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
index b5c72c7..64c4ea8 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
@@ -227,7 +227,7 @@ class HypergeometricDistributionTest extends
BaseDiscreteDistributionTest {
HypergeometricDistribution.of(500, 70, 300),
new int[] {10, 8},
new double[] {2.4055720603264525e-17, 1.2848174992266236e-19},
- createHighPrecisionTolerance());
+ DoubleTolerances.relative(5e-14));
}
@Test
@@ -237,6 +237,6 @@ class HypergeometricDistributionTest extends
BaseDiscreteDistributionTest {
HypergeometricDistribution.of(500, 70, 300),
new int[] {68, 69},
new double[] {4.570379934029859e-16, 7.4187180434325268e-18},
- createHighPrecisionTolerance());
+ DoubleTolerances.relative(5e-14));
}
}
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NormalDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NormalDistributionTest.java
index bbfba7f..da769f4 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NormalDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/NormalDistributionTest.java
@@ -59,16 +59,6 @@ class NormalDistributionTest extends
BaseContinuousDistributionTest {
return 20 * RELATIVE_EPS;
}
- @Override
- protected double getHighPrecisionRelativeTolerance() {
- // Tests are limited by the survival probability.
- // Tolerance is 1.6653345369377348E-14.
- // This is the lowest achieved with various implementations of the
- // survival function against high precision reference data.
- // It requires computing the factor sqrt(2 * sd * sd) exactly.
- return 75 * RELATIVE_EPS;
- }
-
//-------------------- Additional test cases
-------------------------------
@Test
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
index f719f40..0988410 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
@@ -84,7 +84,7 @@ class ParetoDistributionTest extends
BaseContinuousDistributionTest {
dist,
new double[] {2.100000000000001, 2.100000000000005},
new double[] {6.217248937900875e-16, 3.2640556923979585e-15},
- createHighPrecisionTolerance());
+ DoubleTolerances.relative(5e-14));
}
@Test
@@ -94,7 +94,7 @@ class ParetoDistributionTest extends
BaseContinuousDistributionTest {
dist,
new double[] {42e11, 64e11},
new double[] {6.005622169907148e-18, 3.330082930386111e-18},
- createHighPrecisionTolerance());
+ DoubleTolerances.relative(5e-14));
}
@Test
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
index 095de50..ed548b0 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
@@ -130,7 +130,7 @@ class PoissonDistributionTest extends
BaseDiscreteDistributionTest {
PoissonDistribution.of(100),
new int[] {28, 25},
new double[] {1.6858675763053070496e-17,
3.184075559619425735e-19},
- createHighPrecisionTolerance());
+ DoubleTolerances.relative(5e-14));
}
/**
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TestName.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TestName.java
new file mode 100644
index 0000000..7d71a8f
--- /dev/null
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TestName.java
@@ -0,0 +1,82 @@
+/*
+ * 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.statistics.distribution;
+
+import java.util.Locale;
+
+/**
+ * Contains the names for the standard tests.
+ * These names are used as keys in the test resource properties files.
+ */
+enum TestName {
+ PDF,
+ LOGPDF,
+ PMF,
+ LOGPMF,
+ CDF,
+ SF,
+ CDF_HP,
+ SF_HP,
+ ICDF,
+ ISF,
+ CDF_MAPPING,
+ SF_MAPPING,
+ COMPLEMENT,
+ CONSISTENCY,
+ OUTSIDE_SUPPORT,
+ SAMPLING,
+ SAMPLING_PMF,
+ INTEGRALS,
+ SUPPORT,
+ MOMENTS,
+ MEDIAN,
+ PMF_SUM;
+
+ /** Cache the values for use in string conversion. */
+ private static final TestName[] VALUES = values();
+
+ /** The test name as a String. */
+ private final String name;
+
+ /**
+ * Create an instance.
+ */
+ TestName() {
+ name = this.name().toLowerCase(Locale.ROOT).replace('_', '.');
+ }
+
+ @Override
+ public String toString() {
+ return name;
+ }
+
+ /**
+ * Get the instance from the the String representation.
+ *
+ * @param key String representation.
+ * @return the instance (or null)
+ */
+ static TestName fromString(String key) {
+ for (final TestName v : VALUES) {
+ if (v.name.equals(key)) {
+ return v;
+ }
+ }
+ return null;
+ }
+}
+
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.2.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.2.properties
index 92bac80..af855fb 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.2.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.2.properties
@@ -30,3 +30,4 @@ pmf.values = 1.000000000000088817841970016428095E-200
# computed using R version 3.4.4
cdf.hp.points = 82, 81
cdf.hp.values = 1.4061271955993513664e-17, 6.1128083336354843707e-19
+cdf.hp.relative = 1e-14
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.3.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.3.properties
index 09cb32c..663d065 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.3.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.binomial.3.properties
@@ -28,3 +28,4 @@ pmf.values = 1.000000000000002081668171172170658E-200
# computed using R version 3.4.4
sf.hp.points = 18, 19
sf.hp.values = 6.1128083336353977038e-19, 2.4944165604029235392e-20
+sf.hp.relative = 1e-14
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.levy.1.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.levy.1.properties
index 0410f7e..2f7d37c 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.levy.1.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.levy.1.properties
@@ -47,6 +47,7 @@ logpdf.values = \
# Computed using WolframAlpha
cdf.hp.points = 1.205, 1.2049
cdf.hp.values = 3.7440973842063723e-19, 1.6388396909072308e-19
+cdf.hp.relative = 5e-14
sf.hp.points = 1e39, 42e37
sf.hp.values = 1.5957691216057308e-20, 2.4623252122982907e-20
# As cdf.values above but with the redundant 0 removed
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.normal.1.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.normal.1.properties
index 39424da..a16a2c9 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.normal.1.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.normal.1.properties
@@ -64,6 +64,7 @@ sf.values = \
# scipy: 2.7412226346110703e-18 4.1045652533918685e-19
cdf.hp.points = -10, -10.3
cdf.hp.values = 2.74122263461107252124815886312e-18,
4.10456525339188007632261800065e-19
+cdf.hp.relative = 1e-14
# E.g.
# x = sym(14.5)
@@ -76,3 +77,4 @@ cdf.hp.values = 2.74122263461107252124815886312e-18,
4.1045652533918800763226180
# scipy: 4.1045652533918685e-19 1.7495528006975224e-17
sf.hp.points = 14.5, 13.9
sf.hp.values = 4.10456525339190342717686865166e-19,
1.74955280069751640746342569694e-17
+sf.hp.relative = 1e-14
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.10.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.10.properties
index 7882d53..333c239 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.10.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.10.properties
@@ -27,4 +27,4 @@ logpdf.values = -744.4400719213812 -744.5353821011855
-744.6223934781751 -Inf
# The sampling test is not applicable as there are no quartiles.
# As shape -> infinity then sampling will return the scale parameter.
-disable.sample = true
+sampling.disable = true
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.11.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.11.properties
index f22b078..c1b51e0 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.11.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.11.properties
@@ -27,4 +27,4 @@ logpdf.values = -742.1374868283872 -742.8306340089471
-743.2360991170552 -Inf
# The sampling test is not applicable as there are no quartiles.
# As shape -> infinity then sampling will return the scale parameter.
-disable.sample = true
+sampling.disable = true
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.5.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.5.properties
index f23e9b1..39fa152 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.5.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.5.properties
@@ -24,4 +24,4 @@ pdf.values = Inf 0 0
# The sampling test is not applicable as there are no quartiles.
# As shape -> infinity then sampling will return the scale parameter.
-disable.sample = true
+sampling.disable = true
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.6.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.6.properties
index 9f89f68..241e2ae 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.6.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.6.properties
@@ -24,4 +24,4 @@ pdf.values = Inf 0 0 0
# The sampling test is not applicable as there are no quartiles.
# As shape -> infinity then sampling will return the scale parameter.
-disable.sample = true
+sampling.disable = true
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.7.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.7.properties
index 24871e6..a0f0d7a 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.7.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.7.properties
@@ -24,4 +24,4 @@ pdf.values = Inf 0 0
# The sampling test is not applicable as there are no quartiles.
# As shape -> infinity then sampling will return the scale parameter.
-disable.sample = true
+sampling.disable = true
diff --git
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.9.properties
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.9.properties
index eb18228..d7bc7ca 100644
---
a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.9.properties
+++
b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.pareto.9.properties
@@ -27,4 +27,4 @@ logpdf.values = -746.7426570143753 -746.7526073452284
-746.7624596416714 -Inf
# The sampling test is not applicable as there are no quartiles.
# As 1 / shape -> infinity then sampling will return infinity.
-disable.sample = true
+sampling.disable = true
