From 9344ec1396b7151262e9b4ac48c72020e2b03e7e Mon Sep 17 00:00:00 2001 From: Jim Hahn Date: Mon, 2 Aug 2021 16:36:26 -0400 Subject: Use lombok in apex-pdp #5 Updated examples thru integration-executor-test. Issue-ID: POLICY-3391 Change-Id: Idc707146a646d05720675a787761c199484048e9 Signed-off-by: Jim Hahn --- .../adaptive/concepts/AnomalyDetection.java | 88 ++-------------------- .../apex/examples/adaptive/concepts/AutoLearn.java | 41 ++-------- .../adaptive/model/AdaptiveDomainModelSaver.java | 11 +-- ...alyDetectionPolicyDecideTaskSelectionLogic.java | 5 +- 4 files changed, 19 insertions(+), 126 deletions(-) (limited to 'examples/examples-adaptive/src/main/java') diff --git a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java index b0cff91d0..10c3610ba 100644 --- a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java +++ b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AnomalyDetection.java @@ -2,6 +2,7 @@ * ============LICENSE_START======================================================= * Copyright (C) 2016-2018 Ericsson. All rights reserved. * Modifications Copyright (c) 2021 Nordix Foundation. + * Modifications Copyright (C) 2021 AT&T Intellectual Property. All rights reserved. * ================================================================================ * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -26,11 +27,17 @@ import java.util.ArrayList; import java.util.LinkedList; import java.util.List; import lombok.EqualsAndHashCode; +import lombok.Getter; +import lombok.Setter; +import lombok.ToString; /** * The Class AnomalyDetection is used as a Java context for Adaptive anomaly detection in the adaptive domain. */ +@Getter +@Setter @EqualsAndHashCode +@ToString public class AnomalyDetection implements Serializable { private static final long serialVersionUID = -823013127095523727L; @@ -69,60 +76,6 @@ public class AnomalyDetection implements Serializable { } } - /** - * Indicates if this is the first round of the algorithm. - * - * @return true if this is the first round of the algorithm - */ - public boolean getFirstRound() { - return firstRound; - } - - /** - * Sets the first round indicator of the algorithm. - * - * @param firstRound the first round indicator of the algorithm - */ - public void setFirstRound(final boolean firstRound) { - this.firstRound = firstRound; - } - - /** - * Gets the frequency value of the algorithm. - * - * @return the frequency value of the algorithm - */ - public int getFrequency() { - return frequency; - } - - /** - * Sets the frequency value of the algorithm. - * - * @param frequency the frequency value of the algorithm - */ - public void setFrequency(final int frequency) { - this.frequency = frequency; - } - - /** - * Gets the anomaly score values of the algorithm. - * - * @return the anomaly score values of the algorithm - */ - public List getAnomalyScores() { - return anomalyScores; - } - - /** - * Sets the anomaly score values of the algorithm. - * - * @param anomalyScores the anomaly score values of the algorithm - */ - public void setAnomalyScores(final List anomalyScores) { - this.anomalyScores = anomalyScores; - } - /** * Check if the anomaly score values of the algorithm are set. * @@ -139,24 +92,6 @@ public class AnomalyDetection implements Serializable { anomalyScores = null; } - /** - * Gets the frequency forecasted by the algorithm. - * - * @return the frequency forecasted by the algorithm - */ - public List getFrequencyForecasted() { - return frequencyForecasted; - } - - /** - * Sets the frequency forecasted by the algorithm. - * - * @param frequencyForecasted the frequency forecasted by the algorithm - */ - public void setFrequencyForecasted(final List frequencyForecasted) { - this.frequencyForecasted = frequencyForecasted; - } - /** * Check if the frequency forecasted by the algorithm is set. * @@ -172,13 +107,4 @@ public class AnomalyDetection implements Serializable { public void unsetFrequencyForecasted() { frequencyForecasted = null; } - - /** - * {@inheritDoc}. - */ - @Override - public String toString() { - return "AnomalyDetection [firstRound=" + firstRound + ", frequency=" + frequency + ", anomalyScores=" - + anomalyScores + ", frequencyForecasted=" + frequencyForecasted + "]"; - } } diff --git a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java index 60c4d96d9..1760f910d 100644 --- a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java +++ b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/concepts/AutoLearn.java @@ -2,6 +2,7 @@ * ============LICENSE_START======================================================= * Copyright (C) 2016-2018 Ericsson. All rights reserved. * Modifications Copyright (c) 2021 Nordix Foundation. + * Modifications Copyright (C) 2021 AT&T Intellectual Property. All rights reserved. * ================================================================================ * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -25,12 +26,16 @@ import java.io.Serializable; import java.util.ArrayList; import java.util.List; import lombok.EqualsAndHashCode; +import lombok.Getter; +import lombok.Setter; import lombok.ToString; /** * The Class AutoLearn is used as a Java context for Adaptive auto-learning of trends towards a fixed value in the * adaptive domain. */ +@Getter +@Setter @EqualsAndHashCode @ToString public class AutoLearn implements Serializable { @@ -70,24 +75,6 @@ public class AutoLearn implements Serializable { } } - /** - * Gets the average difference values of the algorithm. - * - * @return the average difference values of the algorithm - */ - public List getAvDiffs() { - return avDiffs; - } - - /** - * Sets the average difference values of the algorithm. - * - * @param avDiffs the average difference values of the algorithm - */ - public void setAvDiffs(final List avDiffs) { - this.avDiffs = avDiffs; - } - /** * Check if the average difference values of the algorithm are set. * @@ -104,24 +91,6 @@ public class AutoLearn implements Serializable { avDiffs = null; } - /** - * Gets the count values of the algorithm. - * - * @return the count values of the algorithm - */ - public List getCounts() { - return counts; - } - - /** - * Sets the count values of the algorithm. - * - * @param counts the count values of the algorithm - */ - public void setCounts(final List counts) { - this.counts = counts; - } - /** * Check if the count values of the algorithm are set. * diff --git a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java index 83a42ac8d..0ebff497c 100644 --- a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java +++ b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/AdaptiveDomainModelSaver.java @@ -2,6 +2,7 @@ * ============LICENSE_START======================================================= * Copyright (C) 2016-2018 Ericsson. All rights reserved. * Modifications Copyright (C) 2019 Nordix Foundation. + * Modifications Copyright (C) 2021 AT&T Intellectual Property. All rights reserved. * ================================================================================ * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,6 +22,8 @@ package org.onap.policy.apex.examples.adaptive.model; +import lombok.AccessLevel; +import lombok.NoArgsConstructor; import org.onap.policy.apex.model.basicmodel.concepts.ApexException; import org.onap.policy.apex.model.basicmodel.handling.ApexModelSaver; import org.onap.policy.apex.model.policymodel.concepts.AxPolicyModel; @@ -32,17 +35,11 @@ import org.slf4j.ext.XLoggerFactory; * * @author Liam Fallon (liam.fallon@ericsson.com) */ +@NoArgsConstructor(access = AccessLevel.PRIVATE) public final class AdaptiveDomainModelSaver { // Logger for this class private static final XLogger LOGGER = XLoggerFactory.getXLogger(AdaptiveDomainModelSaver.class); - /** - * Private default constructor to prevent subclassing. - */ - private AdaptiveDomainModelSaver() { - // Prevent subclassing - } - /** * Write the AADM model to args[0]. * diff --git a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicyDecideTaskSelectionLogic.java b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicyDecideTaskSelectionLogic.java index 6b61e822b..e059c9810 100644 --- a/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicyDecideTaskSelectionLogic.java +++ b/examples/examples-adaptive/src/main/java/org/onap/policy/apex/examples/adaptive/model/java/AnomalyDetectionPolicyDecideTaskSelectionLogic.java @@ -2,6 +2,7 @@ * ============LICENSE_START======================================================= * Copyright (C) 2016-2018 Ericsson. All rights reserved. * Modifications Copyright (C) 2020-2021 Nordix Foundation. + * Modifications Copyright (C) 2021 AT&T Intellectual Property. All rights reserved. * ================================================================================ * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -144,7 +145,7 @@ public class AnomalyDetectionPolicyDecideTaskSelectionLogic { } anomalyDetection.setFrequency(frequency); - if (unsetfirstround && anomalyDetection.getFirstRound()) { + if (unsetfirstround && anomalyDetection.isFirstRound()) { anomalyDetection.setFirstRound(false); } @@ -160,7 +161,7 @@ public class AnomalyDetectionPolicyDecideTaskSelectionLogic { anomalyDetection.getFrequencyForecasted().set(frequency, forecastedValue); // anomaly score is ignored in the first frequency period - if (!anomalyDetection.getFirstRound()) { + if (!anomalyDetection.isFirstRound()) { ((LinkedList) anomalyDetection.getAnomalyScores()).addLast(anomalyScore); } -- cgit 1.2.3-korg