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authorDinh Danh Le <dinh.danh.le@ericsson.com>2018-08-29 17:21:52 +0100
committerDinh Danh Le <dinh.danh.le@ericsson.com>2018-09-05 12:48:49 +0100
commit825ae627d4378c5cc7ab4b7d5f4b4ffefcb7977e (patch)
treead4ca360252379ed8e07bc5c599cd4aa6e240199 /examples/examples-adaptive/src
parentf7689b84472ab4698d9d96f1de08402208d99ca8 (diff)
Fix checkstyle warnings in examples
Change-Id: Iad533f3987792d8713426234f3277c1ef6b72284 Issue-ID: POLICY-1034 Signed-off-by: Dinh Danh Le <dinh.danh.le@ericsson.com>
Diffstat (limited to 'examples/examples-adaptive/src')
-rw-r--r--examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java164
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDbWrite.java (renamed from examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java)9
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java10
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java1
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTslUseCase.java (renamed from examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java)12
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDbWrite.java (renamed from examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java)8
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java10
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java1
-rw-r--r--examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTslUseCase.java (renamed from examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java)24
9 files changed, 124 insertions, 115 deletions
diff --git a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java
index a044ad14b..2a654c38e 100644
--- a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java
+++ b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicy_Decide_TaskSelectionLogic.java
@@ -47,15 +47,18 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
/**
* A map to hold the Anomaly degree/levels/probabilities required for each task.<br>
- * If there is no task defined for a calculated anomaly-degree, then the default task is used.<br>
- * The map use (LinkedHashMap) is an insertion-ordered map, so the first interval matching a query is used.
+ * If there is no task defined for a calculated anomaly-degree, then the default task is
+ * used.<br>
+ * The map use (LinkedHashMap) is an insertion-ordered map, so the first interval matching a
+ * query is used.
*/
// CHECKSTYLE:OFF: checkstyle:magicNumber
private static final Map<double[], String> TASK_INTERVALS = new LinkedHashMap<>();
+
static {
- TASK_INTERVALS.put(new double[] { 0.0, 0.1 }, null); // null will mean default task
- TASK_INTERVALS.put(new double[] { 0.25, 0.5 }, "AnomalyDetectionDecideTask1");
- TASK_INTERVALS.put(new double[] { 0.5, 1.01 }, "AnomalyDetectionDecideTask2");
+ TASK_INTERVALS.put(new double[] {0.0, 0.1}, null); // null will mean default task
+ TASK_INTERVALS.put(new double[] {0.25, 0.5}, "AnomalyDetectionDecideTask1");
+ TASK_INTERVALS.put(new double[] {0.5, 1.01}, "AnomalyDetectionDecideTask2");
}
// CHECKSTYLE:ON: checkstyle:magicNumber
@@ -74,8 +77,8 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
logger.debug(executor.inFields.toString());
final double now = (Double) (executor.inFields.get("MonitoredValue"));
final Integer iteration = (Integer) (executor.inFields.get("Iteration"));
- final double[] vals = this.forecastingAndAnomaly(now); // double[forecastedValue, AnomalyScore,
- // AnomalyProbability]
+ // get the double[forecastedValue, AnomalyScore, AnomalyProbability]
+ final double[] vals = this.forecastingAndAnomaly(now);
final double anomalyness = vals[2];
String task = null;
for (final Map.Entry<double[], String> i : TASK_INTERVALS.entrySet()) {
@@ -103,8 +106,8 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
* Anomaly detection and forecast.
*
* @param value The current value
- * @return Null if the function can not be executed correctly, otherwise double[forecastedValue, AnomalyScore,
- * AnomalyProbability]
+ * @return Null if the function can not be executed correctly, otherwise double[forecastedValue,
+ * AnomalyScore, AnomalyProbability]
*/
public double[] forecastingAndAnomaly(final double value) {
try {
@@ -167,7 +170,7 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
double anomalyProbability = 0.0;
if (anomalyDetection.getAnomalyScores().size() > 30) {
// 0.5
- anomalyProbability = gStatsTest(anomalyDetection.getAnomalyScores(), ANOMALY_SENSITIVITY);
+ anomalyProbability = getStatsTest(anomalyDetection.getAnomalyScores(), ANOMALY_SENSITIVITY);
}
// CHECKSTYLE:ON: checkstyle:magicNumber
@@ -178,16 +181,16 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
return null;
}
- return new double[] { forecastedValue, anomalyScore, anomalyProbability };
+ return new double[] {forecastedValue, anomalyScore, anomalyProbability};
}
/**
- * Is the passed value inside the interval, i.e. (value<interval[1] && value>=interval[0])
+ * Is the passed value inside the interval, i.e. (value < interval[1] && value>=interval[0]).
*
* @param value The value to check
* @param interval A 2 element double array describing an interval
- * @return true if the value is between interval[0] (inclusive) and interval[1] (exclusive), i.e. (value<interval[1]
- * && value>=interval[0]). Otherwise false;
+ * @return true if the value is between interval[0] (inclusive) and interval[1] (exclusive),
+ * i.e. (value < interval[1] && value>=interval[0]). Otherwise false;
*/
private static boolean checkInterval(final double value, final double[] interval) {
if (interval == null || interval.length != 2) {
@@ -203,100 +206,89 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
*
* @param values the values
* @param significanceLevel the significance level
- * @return the double
+ * @return the anomaly probability
*/
- private static double gStatsTest(final List<Double> values, final double significanceLevel) {
+ private static double getStatsTest(final List<Double> values, final double significanceLevel) {
if (isAllEqual(values)) {
return 0.0;
}
// the targeted value or the last value
final double currentV = values.get(values.size() - 1);
- Double[] lValuesCopy = values.toArray(new Double[values.size()]);
- Arrays.sort(lValuesCopy); // takes ~40% of method time
- // if(logger.isDebugEnabled()){
- // logger.debug("values:" + Arrays.toString(lValuesCopy));
- // }
+ Double[] lvaluesCopy = values.toArray(new Double[values.size()]);
+ Arrays.sort(lvaluesCopy); // takes ~40% of method time
// get mean
- double mean = getMean(lValuesCopy);
- // get the test value: v
- double v = getV(lValuesCopy, mean, true);
+ double mean = getMean(lvaluesCopy);
+ // get the test value: val
+ double val = getV(lvaluesCopy, mean, true);
// get the p value for the test value
- double pValue = getPValue(lValuesCopy, v, mean); // takes approx 25% of method time
- // if(logger.isDebugEnabled()){
- // logger.debug("pValue:" + pValue);
- // }
+ double pvalue = getPValue(lvaluesCopy, val, mean); // takes approx 25% of method time
// check the critical level
- while (pValue < significanceLevel) { // takes approx 20% of method time
+ while (pvalue < significanceLevel) { // takes approx 20% of method time
// the score value as the anomaly probability
- final double score = (significanceLevel - pValue) / significanceLevel;
- if (Double.compare(v, currentV) == 0) {
+ final double score = (significanceLevel - pvalue) / significanceLevel;
+ if (Double.compare(val, currentV) == 0) {
return score;
}
// do the critical check again for the left values
- lValuesCopy = removevalue(lValuesCopy, v);
- if (isAllEqual(lValuesCopy)) {
+ lvaluesCopy = removevalue(lvaluesCopy, val);
+ if (isAllEqual(lvaluesCopy)) {
return 0.0;
}
- // if(logger.isDebugEnabled()){
- // logger.debug("left values:" + Arrays.toString(lValuesCopy));
- // }
- mean = getMean(lValuesCopy);
- v = getV(lValuesCopy, mean, true);
- pValue = getPValue(lValuesCopy, v, mean);
+
+ mean = getMean(lvaluesCopy);
+ val = getV(lvaluesCopy, mean, true);
+ pvalue = getPValue(lvaluesCopy, val, mean);
}
return 0.0;
}
/**
- * get the test value based on mean from sorted values.
+ * Get the test value based on mean from sorted values.
*
- * @param lValues the l values
+ * @param lvalues the l values
* @param mean the mean
* @param maxValueOnly : only the max extreme value will be tested
* @return the value to be tested
*/
- private static double getV(final Double[] lValues, final double mean, final boolean maxValueOnly) {
- double v = lValues[lValues.length - 1];
+ private static double getV(final Double[] lvalues, final double mean, final boolean maxValueOnly) {
+ double val = lvalues[lvalues.length - 1];
// max value as the extreme value
if (maxValueOnly) {
- return v;
+ return val;
}
// check the extreme side
- if ((v - mean) < (mean - lValues[0])) {
- v = lValues[0];
+ if ((val - mean) < (mean - lvalues[0])) {
+ val = lvalues[0];
}
- return v;
+ return val;
}
/**
* calculate the P value for the t distribution.
*
- * @param lValues the l values
- * @param v the v
+ * @param lvalues the l values
+ * @param val the value
* @param mean the mean
* @return the p value
*/
- private static double getPValue(final Double[] lValues, final double v, final double mean) {
+ private static double getPValue(final Double[] lvalues, final double val, final double mean) {
// calculate z value
- final double z = FastMath.abs(v - mean) / getStdDev(lValues, mean);
- // logger.debug("z: " + z);
+ final double z = FastMath.abs(val - mean) / getStdDev(lvalues, mean);
// calculate T
- final double n = lValues.length;
+ final double n = lvalues.length;
final double s = (z * z * n * (2.0 - n)) / (z * z * n - (n - 1.0) * (n - 1.0));
final double t = FastMath.sqrt(s);
- // logger.debug("t:" + t);
// default p value = 0
- double pValue = 0.0;
+ double pvalue = 0.0;
if (!Double.isNaN(t)) {
// t distribution with n-2 degrees of freedom
final TDistribution tDist = new TDistribution(n - 2);
- pValue = n * (1.0 - tDist.cumulativeProbability(t));
- // set max pValue = 1
- pValue = pValue > 1.0 ? 1.0 : pValue;
+ pvalue = n * (1.0 - tDist.cumulativeProbability(t));
+ // set max pvalue = 1
+ pvalue = pvalue > 1.0 ? 1.0 : pvalue;
}
- // logger.debug("value: "+ v + " , pValue: " + pValue);
- return pValue;
+ return pvalue;
}
/*
@@ -318,52 +310,52 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
}
/**
- * Remove the first occurence of the value v from the array.
+ * Remove the first occurrence of the value val from the array.
*
- * @param lValues the l values
- * @param v the v
+ * @param lvalues the l values
+ * @param val the value
* @return the double[]
*/
- private static Double[] removevalue(final Double[] lValues, final double v) {
- for (int i = 0; i < lValues.length; i++) {
- if (Double.compare(lValues[i], v) == 0) {
- final Double[] ret = new Double[lValues.length - 1];
- System.arraycopy(lValues, 0, ret, 0, i);
- System.arraycopy(lValues, i + 1, ret, i, lValues.length - i - 1);
+ private static Double[] removevalue(final Double[] lvalues, final double val) {
+ for (int i = 0; i < lvalues.length; i++) {
+ if (Double.compare(lvalues[i], val) == 0) {
+ final Double[] ret = new Double[lvalues.length - 1];
+ System.arraycopy(lvalues, 0, ret, 0, i);
+ System.arraycopy(lvalues, i + 1, ret, i, lvalues.length - i - 1);
return ret;
}
}
- return lValues;
+ return lvalues;
}
/**
* get mean value of double list.
*
- * @param lValues the l values
+ * @param lvalues the l values
* @return the mean
*/
- private static double getMean(final Double[] lValues) {
+ private static double getMean(final Double[] lvalues) {
double sum = 0.0;
- for (final double d : lValues) {
+ for (final double d : lvalues) {
sum += d;
}
- return sum / lValues.length;
+ return sum / lvalues.length;
}
/**
* get standard deviation of double list.
*
- * @param lValues the l values
+ * @param lvalues the l values
* @param mean the mean
* @return stddev
*/
- private static double getStdDev(final Double[] lValues, final double mean) {
+ private static double getStdDev(final Double[] lvalues, final double mean) {
double temp = 0.0;
- for (final double d : lValues) {
+ for (final double d : lvalues) {
temp += (mean - d) * (mean - d);
}
- return FastMath.sqrt(temp / lValues.length);
+ return FastMath.sqrt(temp / lvalues.length);
}
/**
@@ -383,12 +375,12 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
/**
* return true if all values are equal.
*
- * @param lValues the l values
+ * @param lvalues the l values
* @return true, if checks if is all equal
*/
- private static boolean isAllEqual(final List<Double> lValues) {
- final double first = lValues.get(0);
- for (final Double d : lValues) {
+ private static boolean isAllEqual(final List<Double> lvalues) {
+ final double first = lvalues.get(0);
+ for (final Double d : lvalues) {
if (Double.compare(d, first) != 0) {
return false;
}
@@ -399,12 +391,12 @@ public class AnomalyDetectionPolicy_Decide_TaskSelectionLogic {
/**
* return true if all values are equal.
*
- * @param lValues the l values
+ * @param lvalues the l values
* @return true, if checks if is all equal
*/
- private static boolean isAllEqual(final Double[] lValues) {
- final double first = lValues[0];
- for (final Double d : lValues) {
+ private static boolean isAllEqual(final Double[] lvalues) {
+ final double first = lvalues[0];
+ for (final Double d : lvalues) {
if (Double.compare(d, first) != 0) {
return false;
}
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDbWrite.java
index 9affa7876..8f54bf12f 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDBWrite.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionDbWrite.java
@@ -31,10 +31,14 @@ import org.onap.policy.apex.model.basicmodel.dao.DaoParameters;
import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-public class TestAnomalyDetectionDBWrite {
+public class TestAnomalyDetectionDbWrite {
private Connection connection;
TestApexModel<AxPolicyModel> testApexModel;
+ /**
+ * Sets up embedded Derby database and the Apex anomaly detection model for the tests.
+ * @throws Exception exception to be thrown while setting up the database connection
+ */
@Before
public void setup() throws Exception {
Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
@@ -50,11 +54,10 @@ public class TestAnomalyDetectionDBWrite {
}
@Test
- public void testModelWriteReadJPA() throws Exception {
+ public void testModelWriteReadJpa() throws Exception {
final DaoParameters DaoParameters = new DaoParameters();
DaoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
DaoParameters.setPersistenceUnit("AdaptiveModelsTest");
-
testApexModel.testApexModelWriteReadJpa(DaoParameters);
}
}
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java
index 3782f2d88..9e631ef2e 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModel.java
@@ -38,6 +38,10 @@ public class TestAnomalyDetectionModel {
private Connection connection;
TestApexModel<AxPolicyModel> testApexModel;
+ /**
+ * Sets up embedded Derby database and the Apex anomaly detection model for the tests.
+ * @throws Exception exception to be thrown while setting up the database connection
+ */
@Before
public void setup() throws Exception {
Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
@@ -59,17 +63,17 @@ public class TestAnomalyDetectionModel {
}
@Test
- public void testModelWriteReadXML() throws Exception {
+ public void testModelWriteReadXml() throws Exception {
testApexModel.testApexModelWriteReadXml();
}
@Test
- public void testModelWriteReadJSON() throws Exception {
+ public void testModelWriteReadJson() throws Exception {
testApexModel.testApexModelWriteReadJson();
}
@Test
- public void testModelWriteReadJPA() throws Exception {
+ public void testModelWriteReadJpa() throws Exception {
final DaoParameters DaoParameters = new DaoParameters();
DaoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
DaoParameters.setPersistenceUnit("AdaptiveModelsTest");
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java
index 2b50d69ab..439452cec 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionModelCreator.java
@@ -25,6 +25,7 @@ import org.onap.policy.apex.model.basicmodel.test.TestApexModelCreator;
import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
/**
+ * The class TestAnomalyDetectionModelCreator.
* @author Liam Fallon (liam.fallon@ericsson.com)
*/
public class TestAnomalyDetectionModelCreator implements TestApexModelCreator<AxPolicyModel> {
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTslUseCase.java
index 3d3fad973..1925a53f5 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTSLUseCase.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAnomalyDetectionTslUseCase.java
@@ -56,8 +56,8 @@ import org.slf4j.ext.XLoggerFactory;
*
* @author John Keeney (John.Keeney@ericsson.com)
*/
-public class TestAnomalyDetectionTSLUseCase {
- private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAnomalyDetectionTSLUseCase.class);
+public class TestAnomalyDetectionTslUseCase {
+ private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAnomalyDetectionTslUseCase.class);
private static final int MAXITERATIONS = 3660;
private static final Random RAND = new Random(System.currentTimeMillis());
@@ -107,7 +107,7 @@ public class TestAnomalyDetectionTSLUseCase {
@Test
// once through the long running test below
- public void TestAnomalyDetectionTSL() throws ApexException, InterruptedException, IOException {
+ public void testAnomalyDetectionTsl() throws ApexException, InterruptedException, IOException {
final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
assertNotNull(apexPolicyModel);
@@ -156,10 +156,10 @@ public class TestAnomalyDetectionTSLUseCase {
// Test is disabled by default. uncomment below, or execute using the main() method
// @Test
// EG Dos command: apex-core.engine> mvn
- // -Dtest=org.onap.policy.apex.core.engine.ml.TestAnomalyDetectionTSLUseCase test | findstr /L /C:"Apex [main] DEBUG
+ // -Dtest=org.onap.policy.apex.core.engine.ml.TestAnomalyDetectionTslUseCase test | findstr /L /C:"Apex [main] DEBUG
// c.e.a.e.TaskSelectionExecutionLogging -
// TestAnomalyDetectionTSL_Policy0000DecideStateTaskSelectionLogic.getTask():"
- public void TestAnomalyDetectionTSL_main() throws ApexException, InterruptedException, IOException {
+ public void testAnomalyDetectionTslmain() throws ApexException, InterruptedException, IOException {
final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAnomalyDetectionPolicyModel();
assertNotNull(apexPolicyModel);
@@ -206,6 +206,6 @@ public class TestAnomalyDetectionTSLUseCase {
}
public static void main(final String[] args) throws ApexException, InterruptedException, IOException {
- new TestAnomalyDetectionTSLUseCase().TestAnomalyDetectionTSL_main();
+ new TestAnomalyDetectionTslUseCase().testAnomalyDetectionTslmain();
}
}
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDbWrite.java
index e096105d9..d4c1ab193 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDBWrite.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnDbWrite.java
@@ -31,10 +31,14 @@ import org.onap.policy.apex.model.basicmodel.dao.DaoParameters;
import org.onap.policy.apex.model.basicmodel.test.TestApexModel;
import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
-public class TestAutoLearnDBWrite {
+public class TestAutoLearnDbWrite {
private Connection connection;
TestApexModel<AxPolicyModel> testApexModel;
+ /**
+ * Sets up embedded Derby database and the Apex AutoLearn model for the tests.
+ * @throws Exception exception to be thrown while setting up the database connection
+ */
@Before
public void setup() throws Exception {
Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
@@ -50,7 +54,7 @@ public class TestAutoLearnDBWrite {
}
@Test
- public void testModelWriteReadJPA() throws Exception {
+ public void testModelWriteReadJpa() throws Exception {
final DaoParameters DaoParameters = new DaoParameters();
DaoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
DaoParameters.setPersistenceUnit("AdaptiveModelsTest");
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java
index beb7a9c80..9bf7ce57a 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModel.java
@@ -38,6 +38,10 @@ public class TestAutoLearnModel {
private Connection connection;
TestApexModel<AxPolicyModel> testApexModel;
+ /**
+ * Sets up embedded Derby database and the Apex AutoLearn model for the tests.
+ * @throws Exception exception to be thrown while setting up the database connection
+ */
@Before
public void setup() throws Exception {
Class.forName("org.apache.derby.jdbc.EmbeddedDriver").newInstance();
@@ -59,17 +63,17 @@ public class TestAutoLearnModel {
}
@Test
- public void testModelWriteReadXML() throws Exception {
+ public void testModelWriteReadXml() throws Exception {
testApexModel.testApexModelWriteReadXml();
}
@Test
- public void testModelWriteReadJSON() throws Exception {
+ public void testModelWriteReadJson() throws Exception {
testApexModel.testApexModelWriteReadJson();
}
@Test
- public void testModelWriteReadJPA() throws Exception {
+ public void testModelWriteReadJpa() throws Exception {
final DaoParameters DaoParameters = new DaoParameters();
DaoParameters.setPluginClass("org.onap.policy.apex.model.basicmodel.dao.impl.DefaultApexDao");
DaoParameters.setPersistenceUnit("AdaptiveModelsTest");
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java
index 11f1991bf..35d049dc7 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnModelCreator.java
@@ -25,6 +25,7 @@ import org.onap.policy.apex.model.basicmodel.test.TestApexModelCreator;
import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel;
/**
+ * The class TestAutoLearnModelCreator.
* @author Liam Fallon (liam.fallon@ericsson.com)
*/
public class TestAutoLearnModelCreator implements TestApexModelCreator<AxPolicyModel> {
diff --git a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTslUseCase.java
index 723b56653..ce9a07e16 100644
--- a/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTSLUseCase.java
+++ b/examples/examples-adaptive/src/test/java/org/onap/policy/apex/examples/adaptive/TestAutoLearnTslUseCase.java
@@ -54,8 +54,8 @@ import org.slf4j.ext.XLoggerFactory;
*
* @author John Keeney (John.Keeney@ericsson.com)
*/
-public class TestAutoLearnTSLUseCase {
- private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAutoLearnTSLUseCase.class);
+public class TestAutoLearnTslUseCase {
+ private static final XLogger LOGGER = XLoggerFactory.getXLogger(TestAutoLearnTslUseCase.class);
private static final int MAXITERATIONS = 1000;
private static final Random rand = new Random(System.currentTimeMillis());
@@ -105,7 +105,7 @@ public class TestAutoLearnTSLUseCase {
@Test
// once through the long running test below
- public void TestAutoLearnTSL() throws ApexException, InterruptedException, IOException {
+ public void testAutoLearnTsl() throws ApexException, InterruptedException, IOException {
final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
assertNotNull(apexPolicyModel);
@@ -153,9 +153,9 @@ public class TestAutoLearnTSLUseCase {
* @throws IOException Signals that an I/O exception has occurred.
*/
// @Test
- public void TestAutoLearnTSL_main() throws ApexException, InterruptedException, IOException {
+ public void testAutoLearnTslMain() throws ApexException, InterruptedException, IOException {
- final double WANT = 50.0;
+ final double dwant = 50.0;
final double toleranceTileJump = 3.0;
final AxPolicyModel apexPolicyModel = new AdaptiveDomainModelFactory().getAutoLearnPolicyModel();
@@ -179,10 +179,10 @@ public class TestAutoLearnTSLUseCase {
final EnEvent triggerEvent = apexEngine1.createEvent(new AxArtifactKey("AutoLearnTriggerEvent", "0.0.1"));
assertNotNull(triggerEvent);
- final double MIN = -100;
- final double MAX = 100;
+ final double dmin = -100;
+ final double dmax = 100;
- double rval = (((rand.nextGaussian() + 1) / 2) * (MAX - MIN)) + MIN;
+ double rval = (((rand.nextGaussian() + 1) / 2) * (dmax - dmin)) + dmin;
triggerEvent.put("MonitoredValue", rval);
triggerEvent.put("LastMonitoredValue", 0);
@@ -207,13 +207,13 @@ public class TestAutoLearnTSLUseCase {
avcount = Math.min((avcount + 1), 20); // maintain average of only the last 20 values
avval = ((avval * (avcount - 1)) + val) / (avcount);
- distance = Math.abs(WANT - avval);
+ distance = Math.abs(dwant - avval);
if (distance < toleranceTileJump) {
- rval = (((rand.nextGaussian() + 1) / 2) * (MAX - MIN)) + MIN;
+ rval = (((rand.nextGaussian() + 1) / 2) * (dmax - dmin)) + dmin;
val = rval;
triggerEvent.put("MonitoredValue", val);
LOGGER.info("Iteration " + iteration + ": Average " + avval + " has become closer (" + distance
- + ") than " + toleranceTileJump + " to " + WANT + " so reseting val:\t\t\t\t\t\t\t\t" + val);
+ + ") than " + toleranceTileJump + " to " + dwant + " so reseting val:\t\t\t\t\t\t\t\t" + val);
avval = 0;
avcount = 0;
}
@@ -229,6 +229,6 @@ public class TestAutoLearnTSLUseCase {
}
public static void main(final String[] args) throws ApexException, InterruptedException, IOException {
- new TestAutoLearnTSLUseCase().TestAutoLearnTSL_main();
+ new TestAutoLearnTslUseCase().testAutoLearnTslMain();
}
}