List of usage examples for java.util Collections shuffle
@SuppressWarnings({ "rawtypes", "unchecked" })
public static void shuffle(List<?> list, Random rnd)
From source file:com.github.cc007.sciencespinoffsquiz.web.controllers.RequestController.java
@RequestMapping(value = "/quiz", method = RequestMethod.GET) public String quiz(@ModelAttribute("userid") String userId, @ModelAttribute("answer") String answer, @ModelAttribute("random") String random, @ModelAttribute("questionNr") String questionNr, @ModelAttribute("language") String language, @ModelAttribute("gender") String gender, @ModelAttribute("ageGroup") String ageGroup, @ModelAttribute("restart") String restart, ModelMap map) { long newRandom; GameStatisticsStorage gss;/*from w w w. j a va2 s.c om*/ LanguagesController lc; System.out.println("Incoming request:"); if ("restart".equals(restart)) { System.out.println(" Restart quiz"); map.put("quizredirect", "<meta http-equiv=\"refresh\" content=\"0;url=/ScienceSpinoffsQuiz/quiz\" />"); return "index"; } if (!"".equals(userId) && IntegerChecker.isInteger(userId)) { gss = new DatabaseStorage(Integer.parseInt(userId)); System.out.println(" UserId is set."); } else { System.out.println(" UserId is not set yet.\n"); if ("".equals(language)) { return "index"; } lc = new LanguagesController(language); if ("".equals(gender)) { map.put("language", language); map.put("genderQuestion", lc.getText("GenderQuestion")); map.put("male", lc.getText("Male")); map.put("female", lc.getText("Female")); return "gender"; } if ("".equals(ageGroup)) { map.put("language", language); map.put("gender", gender); map.put("ageGroupQuestion", lc.getText("AgeGroupQuestion")); map.put("younger", lc.getText("Younger")); map.put("older", lc.getText("Older")); return "agegroup"; } //TODO create id gss = new DatabaseStorage(); gss.setGender(gender); gss.setAgeGroup(ageGroup); userId = gss.getUserId() + ""; gss.saveStatistics(); } if (!"".equals(random) && IntegerChecker.isInteger(random)) { System.out.println(" Random is set."); newRandom = Long.parseLong(random); } else { System.out.println(" Random was not set"); newRandom = System.currentTimeMillis(); } System.out.println(" Retrieving question..."); String xmlFileName = "questions_en.xml"; if (!"".equals(language)) { lc = new LanguagesController(language); switch (language.toLowerCase()) { case "nederlands": xmlFileName = "questions_nl.xml"; break; case "english": xmlFileName = "questions_en.xml"; break; } } else { lc = new LanguagesController("English"); } QuestionPool qp = new QuestionPool(xmlFileName); int newQuestionNr = 0; if (!"".equals(questionNr) && IntegerChecker.isInteger(questionNr)) { newQuestionNr = Integer.parseInt(questionNr); System.out.println(" Question is set."); } else { System.out.println(" No question set: assuming first question."); } List<Question> questions = qp.getQuestions(); Collections.shuffle(questions, new Random(newRandom)); if (newQuestionNr >= questions.size()) { map.put("endQuiz", lc.getText("EndQuiz")); map.put("restartQuiz", lc.getText("RestartQuiz")); return "endquiz"; } Question q = questions.get(newQuestionNr); if (!"".equals(answer)) { Answer givenAnswer = Answer.fromString(answer); boolean right = givenAnswer != null && q.getRightAnswer().equalsAnswer(givenAnswer); System.out.println("Store result in database"); gss.setScore(q.getId(), right); gss.saveStatistics(); System.out.println(" Prepare explanation webview"); map.put("explanation", q.getExplanation()); if (right) { map.put("questionText", lc.getText("RightAnswer") + q.getRightAnswer().toString()); } else { map.put("questionText", lc.getText("WrongAnswer") + q.getRightAnswer().toString()); } map.put("userid", userId); map.put("random", newRandom + ""); map.put("questionNr", newQuestionNr + 1 + ""); map.put("language", language); map.put("imgName", q.getExplanationImage()); map.put("nextQuestion", lc.getText("NextQuestion")); map.put("restartQuiz", lc.getText("RestartQuiz")); return "explanation"; } System.out.println(" Prepare question in webview"); map.put("question", q.getQuestion()); map.put("answerA", q.getAnswerA()); map.put("answerB", q.getAnswerB()); map.put("answerC", q.getAnswerC()); map.put("userid", userId); map.put("random", newRandom + ""); map.put("questionNr", newQuestionNr + ""); map.put("language", language); System.out.println("Request handled.\n"); return "question"; }
From source file:cerrla.modular.ModularPolicy.java
/** * Evaluates the rules of this policy (with recursion). * // w w w . jav a2 s . c o m * @param observations * The relational observations for the state. * @param policyActions * The collection to add the actions to. * @param activatedActions * The actions the RLGG rules return. * @param actionsFound * The number of actions found so far. * @param actionsRequired * The number of actions required to return. * @return The resultant actions. * @throws Exception * Should something go awry... */ private void evaluateInternalPolicy(RRLObservations observations, PolicyActions policyActions, MultiMap<String, String[]> activatedActions, int actionsFound, int actionsRequired) throws Exception { firedLastStep_.clear(); // Run the cover state method to possibly scan this state (depending on // current RLGG rules and scan intervals). List<RelationalRule> coveredRules = ceDistribution_.coverState(this, observations, activatedActions, episodeGoalReplacements_); // If the policy is empty, store the rules in it. if (coveredRules != null && !coveredRules.isEmpty()) { Collections.shuffle(coveredRules, RRLExperiment.random_); // Add any new rules to the policy for (RelationalRule gr : coveredRules) { policyRules_.add(gr); policySize_++; } // Add parameters to the rule. parameterArgs(transformGoalReplacements(observations.getGoalReplacements())); } // If the goal has been achieved, don't evaluate this policy if (goalAchievedCurrently_) return; // Evaluate the rules/policies recursively. Rete state = observations.getState(); Iterator<PolicyItem> iter = policyRules_.iterator(); while (iter.hasNext() && actionsFound < actionsRequired) { Object polObject = iter.next(); if (polObject instanceof RelationalRule) { // Evaluate the rule RelationalRule polRule = (RelationalRule) polObject; Collection<FiredAction> firedActions = evaluateRule(polRule, state, observations.getValidActions(polRule.getActionPredicate()), null, true); policyActions.addFiredRule(firedActions, this); actionsFound += firedActions.size(); // If this rule created a sub-goal, mark the goal achieved. if (childrenPolicies_.containsKey(polRule)) { for (ModularSubGoal modSubGoal : childrenPolicies_.get(polRule)) { if (!firedActions.isEmpty()) modSubGoal.setGoalAchieved(true); else modSubGoal.setGoalAchieved(false); } } } else if (polObject instanceof ModularSubGoal) { // Evaluate the internal policy. ModularPolicy internalPolicy = ((ModularSubGoal) polObject).getModularPolicy(); if (internalPolicy != null) internalPolicy.evaluateInternalPolicy(observations, policyActions, activatedActions, actionsFound, actionsRequired); } } }
From source file:ch.blinkenlights.android.vanilla.MediaUtils.java
/** * Shuffle a Song list using Collections.shuffle(). * * @param albumShuffle If true, preserve the order of songs inside albums. *//*from w w w. j av a 2s. c o m*/ public static void shuffle(List<Song> list, boolean albumShuffle) { int size = list.size(); if (size < 2) return; Random random = getRandom(); if (albumShuffle) { List<Song> tempList = new ArrayList<Song>(list); Collections.sort(tempList); // Build map of albumId to start index in sorted list Map<Long, Integer> albumStartIndices = new HashMap<Long, Integer>(); int index = 0; for (Song song : tempList) { if (!albumStartIndices.containsKey(song.albumId)) { albumStartIndices.put(song.albumId, index); } index++; } //Extract album list and shuffle List<Long> shuffledAlbums = new ArrayList<Long>(albumStartIndices.keySet()); Collections.shuffle(shuffledAlbums, random); //Build Song list from album list list.clear(); for (Long albumId : shuffledAlbums) { int songIndex = albumStartIndices.get(albumId); Song song = tempList.get(songIndex); do { list.add(song); songIndex++; if (songIndex < size) { song = tempList.get(songIndex); } else { break; } } while (albumId == song.albumId); } } else { Collections.shuffle(list, random); } }
From source file:edu.byu.nlp.crowdsourcing.ModelInitializationTest.java
public static String jsonInstances(long seed) { List<String> jsonInstances = Lists.newArrayList( "{\"batch\": 0, \"data\":\"ABCD\", \"endTime\":5, \"label\":\"0\", \"source\":1, \"startTime\":0 }", // label "{\"batch\": 1, \"data\":\"ABCD\", \"endTime\":6, \"annotation\":\"0\", \"annotator\":\"A\", \"source\":1, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":7, \"annotation\":\"1\", \"annotator\":\"B\", \"source\":1, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":8, \"annotation\":\"0\", \"annotator\":\"B\", \"source\":1, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 0, \"data\":\"ABCD\", \"endTime\":1, \"label\":\"1\", \"source\":2, \"startTime\":0 }", // label "{\"batch\": 1, \"data\":\"ABCD\", \"endTime\":2, \"annotation\":\"0\", \"annotator\":\"A\", \"source\":2, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":3, \"annotation\":\"1\", \"annotator\":\"B\", \"source\":2, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":4, \"annotation\":\"1\", \"annotator\":\"B\", \"source\":2, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 0, \"data\":\"ABCD\", \"endTime\":9, \"label\":\"0\", \"source\":3, \"startTime\":0 }", // label "{\"batch\": 1, \"data\":\"ABCD\", \"endTime\":10, \"annotation\":\"1\", \"annotator\":\"A\", \"source\":3, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":11, \"annotation\":\"0\", \"annotator\":\"B\", \"source\":3, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 2, \"data\":\"ABCD\", \"endTime\":12, \"annotation\":\"0\", \"annotator\":\"B\", \"source\":3, \"startTime\":0 }", // annotation to the same doc "{\"batch\": 0, \"data\":\"ABCD\", \"endTime\":13, \"label\":\"0\", \"source\":4, \"startTime\":0 }" // label );/*from w w w . ja v a 2 s . c o m*/ Random rand = new Random(seed); Collections.shuffle(jsonInstances, rand); // try different orderings return "[ \n" + Joiner.on(", \n").join(jsonInstances) + "]"; }
From source file:org.apache.solr.handler.component.AlfrescoHttpShardHandlerFactory.java
/** * Creates a randomized list of urls for the given shard. * * @param shard the urls for the shard, separated by '|' * @return A list of valid urls (including protocol) that are replicas for the shard *///from www. j a v a 2s . com public List<String> makeURLList(String shard) { List<String> urls = StrUtils.splitSmart(shard, "|", true); // convert shard to URL for (int i = 0; i < urls.size(); i++) { urls.set(i, buildUrl(urls.get(i))); } // // Shuffle the list instead of use round-robin by default. // This prevents accidental synchronization where multiple shards could get in sync // and query the same replica at the same time. // if (urls.size() > 1) Collections.shuffle(urls, r); return urls; }
From source file:iDynoOptimizer.MOEAFramework26.src.org.moeaframework.core.PRNG.java
/** * Shuffles the elements of the specified list by invoking the * {@link Collections#shuffle} method with the internal {@link Random} in * this PRNG./*from w w w. j a va 2 s . c om*/ * * @param <T> the type of elements stored in the list * @param list the list to be shuffled */ public static <T> void shuffle(List<T> list) { Collections.shuffle(list, random); }
From source file:edu.mssm.crover.tables.writers.LibSVMWriter.java
/** * Run cross-validation with k folds./* w ww . ja v a 2 s .c o m*/ * * @param k Number of folds for cross validation. Typical values are 5 or 10. * @return Evaluation measures. */ public EvaluationMeasure crossValidation(final int k) { assert tableScanned : " Must process rows of input table first."; assert k <= numberOfTrainingExamples : "Number of folds must be less or equal to number of training examples."; final IntList indices = new IntArrayList(); for (int f = 0; f < k; ++f) { for (int i = 0; i < numberOfTrainingExamples / k; ++i) { indices.add(f); } } Collections.shuffle(indices, randomAdapter); final int[] splitIndex = new int[numberOfTrainingExamples]; indices.toArray(splitIndex); final ContingencyTable ctable = new ContingencyTable(); for (int f = 0; f < k; ++f) { // use each fold as test set while the others are the training set: final IntSet trainingSet = new IntArraySet(); final IntSet testSet = new IntArraySet(); for (int i = 0; i < numberOfTrainingExamples; i++) { // assign each training example to a fold: if (f == splitIndex[i]) { testSet.add(i); } else { trainingSet.add(i); } } // System.out.println("trainingSet: " + trainingSet.toString()); // System.out.println("splitSpecificTestSet: " + splitSpecificTestSet.toString()); final svm_problem currentTrainingSet = splitProblem(problem, trainingSet); final svm_model looModel = svm.svm_train(currentTrainingSet, parameters); final ContingencyTable ctableMicro = new ContingencyTable(); for (final int testInstanceIndex : testSet) { // for each test example: final double decision = svm.svm_predict(looModel, problem.x[testInstanceIndex]); final double trueLabel = problem.y[testInstanceIndex]; ctable.observeDecision(trueLabel, decision); ctableMicro.observeDecision(trueLabel, decision); } ctableMicro.average(); // System.out.println("microaverage: " + convertToEvalMeasure(ctableMicro)); } ctable.average(); // System.out.println("macroaverage: "+convertToEvalMeasure(ctable)); return convertToEvalMeasure(ctable); }
From source file:org.elasticsearch.client.sniff.ElasticsearchNodesSnifferTests.java
private static SniffResponse buildSniffResponse(ElasticsearchNodesSniffer.Scheme scheme) throws IOException { int numNodes = RandomNumbers.randomIntBetween(getRandom(), 1, 5); List<Node> nodes = new ArrayList<>(numNodes); JsonFactory jsonFactory = new JsonFactory(); StringWriter writer = new StringWriter(); JsonGenerator generator = jsonFactory.createGenerator(writer); generator.writeStartObject();//from w w w . j a va 2s . c om if (getRandom().nextBoolean()) { generator.writeStringField("cluster_name", "elasticsearch"); } if (getRandom().nextBoolean()) { generator.writeObjectFieldStart("bogus_object"); generator.writeEndObject(); } generator.writeObjectFieldStart("nodes"); for (int i = 0; i < numNodes; i++) { String nodeId = RandomStrings.randomAsciiOfLengthBetween(getRandom(), 5, 10); String host = "host" + i; int port = RandomNumbers.randomIntBetween(getRandom(), 9200, 9299); HttpHost publishHost = new HttpHost(host, port, scheme.toString()); Set<HttpHost> boundHosts = new HashSet<>(); boundHosts.add(publishHost); if (randomBoolean()) { int bound = between(1, 5); for (int b = 0; b < bound; b++) { boundHosts.add(new HttpHost(host + b, port, scheme.toString())); } } int numAttributes = between(0, 5); Map<String, List<String>> attributes = new HashMap<>(numAttributes); for (int j = 0; j < numAttributes; j++) { int numValues = frequently() ? 1 : between(2, 5); List<String> values = new ArrayList<>(); for (int v = 0; v < numValues; v++) { values.add(j + "value" + v); } attributes.put("attr" + j, values); } Node node = new Node(publishHost, boundHosts, randomAsciiAlphanumOfLength(5), randomAsciiAlphanumOfLength(5), new Node.Roles(randomBoolean(), randomBoolean(), randomBoolean()), attributes); generator.writeObjectFieldStart(nodeId); if (getRandom().nextBoolean()) { generator.writeObjectFieldStart("bogus_object"); generator.writeEndObject(); } if (getRandom().nextBoolean()) { generator.writeArrayFieldStart("bogus_array"); generator.writeStartObject(); generator.writeEndObject(); generator.writeEndArray(); } boolean isHttpEnabled = rarely() == false; if (isHttpEnabled) { nodes.add(node); generator.writeObjectFieldStart("http"); generator.writeArrayFieldStart("bound_address"); for (HttpHost bound : boundHosts) { generator.writeString(bound.toHostString()); } generator.writeEndArray(); if (getRandom().nextBoolean()) { generator.writeObjectFieldStart("bogus_object"); generator.writeEndObject(); } generator.writeStringField("publish_address", publishHost.toHostString()); if (getRandom().nextBoolean()) { generator.writeNumberField("max_content_length_in_bytes", 104857600); } generator.writeEndObject(); } List<String> roles = Arrays.asList(new String[] { "master", "data", "ingest" }); Collections.shuffle(roles, getRandom()); generator.writeArrayFieldStart("roles"); for (String role : roles) { if ("master".equals(role) && node.getRoles().isMasterEligible()) { generator.writeString("master"); } if ("data".equals(role) && node.getRoles().isData()) { generator.writeString("data"); } if ("ingest".equals(role) && node.getRoles().isIngest()) { generator.writeString("ingest"); } } generator.writeEndArray(); generator.writeFieldName("version"); generator.writeString(node.getVersion()); generator.writeFieldName("name"); generator.writeString(node.getName()); if (numAttributes > 0) { generator.writeObjectFieldStart("attributes"); for (Map.Entry<String, List<String>> entry : attributes.entrySet()) { if (entry.getValue().size() == 1) { generator.writeStringField(entry.getKey(), entry.getValue().get(0)); } else { for (int v = 0; v < entry.getValue().size(); v++) { generator.writeStringField(entry.getKey() + "." + v, entry.getValue().get(v)); } } } generator.writeEndObject(); } generator.writeEndObject(); } generator.writeEndObject(); generator.writeEndObject(); generator.close(); return SniffResponse.buildResponse(writer.toString(), nodes); }
From source file:jenkins.security.apitoken.ApiTokenStatsTest.java
@Test @SuppressWarnings("unchecked") public void testInternalComparator() throws Exception { List<ApiTokenStats.SingleTokenStats> tokenStatsList = Arrays.asList( createSingleTokenStatsByReflection("A", null, 0), createSingleTokenStatsByReflection("B", "2018-05-01 09:10:59.234", 2), createSingleTokenStatsByReflection("C", "2018-05-01 09:10:59.234", 3), createSingleTokenStatsByReflection("D", "2018-05-01 09:10:59.235", 1)); Field field = ApiTokenStats.SingleTokenStats.class.getDeclaredField("COMP_BY_LAST_USE_THEN_COUNTER"); field.setAccessible(true);/*ww w . j a va 2 s . com*/ Comparator<ApiTokenStats.SingleTokenStats> comparator = (Comparator<ApiTokenStats.SingleTokenStats>) field .get(null); // to be not impacted by the declaration order Collections.shuffle(tokenStatsList, new Random(42)); tokenStatsList.sort(comparator); List<String> idList = tokenStatsList.stream().map(ApiTokenStats.SingleTokenStats::getTokenUuid) .collect(Collectors.toList()); assertThat(idList, contains("A", "B", "C", "D")); }
From source file:it.uniroma2.sag.kelp.learningalgorithm.classification.dcd.DCDLearningAlgorithm.java
@Override public void learn(Dataset dataset) { if (isFairness() && cp == cn) { float positiveExample = dataset.getNumberOfPositiveExamples(label); float negativeExample = dataset.getNumberOfNegativeExamples(label); cp = cn * negativeExample / positiveExample; }//from ww w . ja va 2s .co m List<Example> vecs = dataset.getExamples(); float[] alpha = new float[vecs.size()]; float[] y = new float[vecs.size()]; float bias = 0; double[] Qhs = new double[vecs.size()];// Q hats double[] U = new double[vecs.size()]; double[] D = new double[vecs.size()]; for (int i = 0; i < dataset.getNumberOfExamples(); i++) { Example ei = dataset.getExamples().get(i); y[i] = getY(ei); U[i] = getU(ei); D[i] = getD(ei); Vector vecI = (Vector) dataset.getExamples().get(i).getRepresentation(representation); Qhs[i] = vecI.innerProduct(vecI) + D[i]; if (useBias) Qhs[i] += 1.0; } if (this.getPredictionFunction().getModel().getHyperplane() == null) { this.getPredictionFunction().getModel().setHyperplane(dataset.getZeroVector(representation)); } Vector w = this.getPredictionFunction().getModel().getHyperplane(); // Vector v0 = (Vector) dataset.getExamples().get(0) // .getRepresentation(representation); // Vector w = v0.getZeroVector(); List<Integer> A = new ArrayList<Integer>(); for (int i = 0; i < dataset.getNumberOfExamples(); i++) { A.add(i); } Random rand = new Random(seed); for (int t = 0; t < maxIterations; t++) { Collections.shuffle(A, rand); for (int i : A) { // * Performs steps a, b, and c of the DCD algorithms 1 and 2 Vector vecI = (Vector) dataset.getExamples().get(i).getRepresentation(representation); // a final double G = y[i] * (w.innerProduct(vecI) + bias) - 1 + D[i] * alpha[i]; // b final double PG; if (alpha[i] == 0) PG = Math.min(G, 0); else if (alpha[i] == U[i]) PG = Math.max(G, 0); else PG = G; // c if (PG != 0) { float alphaOld = alpha[i]; alpha[i] = (float) Math.min(Math.max(alpha[i] - G / Qhs[i], 0), U[i]); float scale = (alpha[i] - alphaOld) * y[i]; w.add(scale, vecI); if (useBias) bias += scale; } } } this.classifier.getModel().setHyperplane(w); this.classifier.getModel().setRepresentation(representation); if (useBias) this.classifier.getModel().setBias(bias); else this.classifier.getModel().setBias(0); }