List of usage examples for java.util HashMap entrySet
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From source file:it.polito.tellmefirst.web.rest.clients.ClientEpub.java
private void removeChapterFromString(HashMap lhm, String uselessText) { LOG.debug("[removeChapter] - BEGIN"); Set set = lhm.entrySet(); Iterator i = set.iterator();/*w w w .j a v a2s. c o m*/ while (i.hasNext()) { Map.Entry me = (Map.Entry) i.next(); if (me.getValue().toString().contains(uselessText)) { i.remove(); } } LOG.debug("[removeChapter] - END"); }
From source file:com.thoratou.exact.processors.ExactProcessor.java
private void writeSources(HashMap<String, List<PathStep>> mergedMap) throws IOException, ClassNotFoundException, ExactException { //use all annotation data to generate parsing files for (Map.Entry<String, List<PathStep>> entryList : mergedMap.entrySet()) { VelocityEngine engine = new VelocityEngine(); //needed it avoid global instead of local variable modification engine.setProperty(RuntimeConstants.VM_CONTEXT_LOCALSCOPE, true); //read file into JAR InputStream configStream = getClass().getResourceAsStream("/xmlreader.vm"); BufferedReader configReader = new BufferedReader(new InputStreamReader(configStream, "UTF-8")); String className = entryList.getKey(); List<PathStep> steps = entryList.getValue(); VelocityContext context = new VelocityContext(); context.put("class", className); //logger.info("class : "+className); //ugly temp code String[] split = className.split("\\."); StringBuffer packageBuffer = new StringBuffer(); for (int i = 0; i < split.length - 1; i++) { packageBuffer.append(split[i]); if (i != split.length - 2) { packageBuffer.append("."); }/* w w w . java 2 s . c o m*/ } String packageName = packageBuffer.toString(); //logger.info("package : "+packageName); context.put("package", packageName); String simpleName = split[split.length - 1]; //logger.info("simpleclass : "+simpleName); context.put("simpleclass", simpleName); context.put("steps", steps); context.put("kindmap", PathStep.ReverseKindMap); context.put("startmap", PathStep.ReverseStartMap); context.put("typemap", PathStep.ReverseTypeMap); context.put("listtypemap", PathStep.ReverseListTypeMap); context.put("indentutil", new IndentUtil()); context.put("processingutil", new ProcessingUtil()); Set<String> bomList = new HashSet<String>(); registerBomListFromSteps(steps, bomList); context.put("bomlist", bomList); Set<String> extensionList = new HashSet<String>(); Map<String, ExtensionVelocityData> extensionMap = new HashMap<String, ExtensionVelocityData>(); registerExtensionListFromSteps(steps, extensionList, extensionMap); context.put("extensionlist", extensionList); context.put("extensionmap", extensionMap); logger.info("input velocity data : " + className + " , " + steps.toString()); //StringWriter writer = new StringWriter(); //String packagePath = packageName.replace(".","/"); //String fullFile = packagePath+"/"+simpleName+"XmlReader.java"; //logger.info(fullFile); Filer filer = processingEnv.getFiler(); JavaFileObject sourceFile = filer.createSourceFile(className + "XmlReader"); Writer sourceWriter = sourceFile.openWriter(); engine.evaluate(context, sourceWriter, "", configReader); sourceWriter.close(); sourceFile.delete(); //logger.info("final velocity data : "+writer.getBuffer().toString()); } }
From source file:it.polito.tellmefirst.web.rest.clients.ClientEpub.java
private void removeChapter(HashMap lhm, String chapterTitle) { LOG.debug("[removeChapter] - BEGIN"); Set set = lhm.entrySet(); Iterator i = set.iterator();//from w w w . ja va2 s .c om while (i.hasNext()) { Map.Entry me = (Map.Entry) i.next(); if (me.getKey().toString().equals(chapterTitle)) { LOG.info("Remove useless chapter: " + me.getKey().toString()); i.remove(); } } LOG.debug("[removeChapter] - END"); }
From source file:com.jci.job.repo.JobRepoImpl.java
@Override public synchronized BatchUpdateRes batchUpdate(BatchUpdateReq request) { int errorCount = 0; int successCount = 0; BatchUpdateRes response = new BatchUpdateRes(); String erpName = request.getErpName(); HashMap<String, List<PoEntity>> tableNameToEntityMap = request.getTableNameToEntityMap(); List<String> errorList = new ArrayList<>(); List<String> successList = new ArrayList<>(); CloudTable cloudTable = null;//from www.j ava 2 s. c om PoEntity entity = null; String tableName = null; for (Map.Entry<String, List<PoEntity>> entry : tableNameToEntityMap.entrySet()) { try { cloudTable = azureStorage.getTable(entry.getKey()); tableName = entry.getKey(); } catch (Exception e) { LOG.error("### Exception in JobRepoImpl.batchUpdate.getTable ###" + e); response.setError(true); response.setMessage("The Application has encountered an error! Table does not exist !"); throw errorService.createException(JobException.class, e, ErrorEnum.ERROR_TABLE_NOT_FOUND, entry.getKey()); } // Define a batch operation. TableBatchOperation batchOperation = new TableBatchOperation(); List<PoEntity> value = entry.getValue(); for (int i = 0; i < value.size(); i++) { entity = value.get(i); //counter= counter+1; entity.setGlobalId(request.getGlobalId()); entity.setUserName(request.getUserName()); entity.setComment(request.getComment()); if (request.isSuccess()) {//Means we are updating(success) status for pos which has been successfully processed to e2open entity.setSupplierDeliveryState(Constants.STATUS_SUCCESS); successCount = successCount + 1; successList.add(entity.getRowKey()); } else {//Request is for error status update entity.setSupplierDeliveryState(Constants.STATUS_ERROR); errorCount = errorCount + 1; errorList.add(entity.getRowKey()); } batchOperation.insertOrMerge(entity); if (i != 0 && (i % batchSize) == 0) { try { cloudTable.execute(batchOperation); batchOperation.clear(); } catch (Exception e) { response.setError(true); response.setMessage("The Application has encountered an error!"); if (request.isSuccess()) { successCount = successCount - 1; } else { errorCount = errorCount - 1; } LOG.error("### Exception in JobRepoImpl.batchUpdate.execute ###" + e); continue; } } } if (batchOperation.size() > 0) { try { cloudTable.execute(batchOperation); } catch (Exception e) { response.setError(true); response.setMessage("The Application has encountered an error!"); if (request.isSuccess()) { successCount = successCount - 1; } else { errorCount = errorCount - 1; } LOG.error("### Exception in JobRepoImpl.batchUpdate.execute ###" + e); continue; } } } response.setErrorList(errorList); response.setSuccessList(successList); updateMiscEntity(erpName, tableName, successCount, errorCount); return response; }
From source file:de.tudarmstadt.tk.statistics.importer.ExternalResultsReader.java
public static void readMUGCCV(String filePath) { String outFileName = "AggregatedTrainTest.csv"; logger.log(Level.INFO, String.format("Importing data from directory %s.", filePath)); // Method requires input directory. Check this condition. File directory = new File(filePath); if (directory.isDirectory()) { System.err.println("Please specify a file. Aborting."); return;/*from ww w .ja va 2 s . c o m*/ } //Empty previous output file, if there was one File outputFile = new File(directory.getParentFile(), outFileName); if (outputFile.exists()) { outputFile.delete(); } try { String header = "Train;Test;Classifier;FeatureSet;Measure;Value"; PrintWriter out = new PrintWriter(new FileWriter(outputFile, true)); out.println(header); out.close(); } catch (IOException e) { System.err.println("Error while writing aggregated Train-Test file."); e.printStackTrace(); } ArrayList<String> outputRows = new ArrayList<String>(); // iterate all rows List<String[]> inputRowsFirstFile = new ArrayList<>(); inputRowsFirstFile = readAndCheckCSV(filePath, ';'); // first: order by train set ArrayList<ExternalResults> extResults = new ArrayList<>(); for (int i = 0; i < inputRowsFirstFile.size(); i++) { ExternalResults results = new ExternalResults(); // identify current train/test split String[] datasetNames = inputRowsFirstFile.get(i)[0].split(","); results.trainSetName = datasetNames[0].replace("CV: ", "").replace(" ", ""); // set classifier name results.classifierParameters = inputRowsFirstFile.get(i)[1]; // read feature set results.featureSetName = inputRowsFirstFile.get(i)[2]; // read classification results results.recall = Double.parseDouble(inputRowsFirstFile.get(i)[3]); results.fMeasure = Double.parseDouble(inputRowsFirstFile.get(i)[4]); results.precision = Double.parseDouble(inputRowsFirstFile.get(i)[5]); results.accuracy = Double.parseDouble(inputRowsFirstFile.get(i)[10]) / 100; extResults.add(results); } HashMap<String, ArrayList<ExternalResults>> extResultsByTrainTestFeature = new HashMap<>(); // order by test set for (ExternalResults result : extResults) { String IdKey = result.trainSetName + result.testSetName + result.featureSetName; if (extResultsByTrainTestFeature.containsKey(IdKey)) { extResultsByTrainTestFeature.get(IdKey).add(result); } else { extResultsByTrainTestFeature.put(IdKey, new ArrayList<ExternalResults>()); extResultsByTrainTestFeature.get(IdKey).add(result); } } ArrayList<ExternalResults> aggregatedResults = new ArrayList<>(); // aggregate results or keep as are for (Entry<String, ArrayList<ExternalResults>> trainTestSplit : extResultsByTrainTestFeature.entrySet()) { ExternalResults aggrResult = new ExternalResults(); double recall = 0; double fMeasure = 0; double precision = 0; double accuracy = 0; int nrClassifiers = 0; // for all entries that are from the same train/test split and use the same feature set -> aggregate results for (ExternalResults result : trainTestSplit.getValue()) { aggrResult.testSetName = result.testSetName; aggrResult.trainSetName = result.trainSetName; aggrResult.classifierParameters = result.classifierParameters; aggrResult.featureSetName = result.featureSetName; recall += result.recall; fMeasure += result.fMeasure; precision += result.precision; accuracy += result.accuracy; nrClassifiers++; } aggrResult.accuracy = (accuracy / nrClassifiers); aggrResult.fMeasure = (fMeasure / nrClassifiers); aggrResult.recall = (recall / nrClassifiers); aggrResult.precision = (precision / nrClassifiers); aggregatedResults.add(aggrResult); } // write values of measure for (ExternalResults result : aggregatedResults) { String outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Percent Correct", result.accuracy); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted Precision", result.precision); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted Recall", result.recall); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted F-Measure", result.fMeasure); outputRows.add(outputRow); } // Write aggregated data to a new file try { PrintWriter out = new PrintWriter(new FileWriter(outputFile, true)); for (String s : outputRows) { out.println(s); } out.close(); } catch (IOException e) { System.err.println("Error while writing aggregated Train-Test file."); e.printStackTrace(); } logger.log(Level.INFO, String.format("Finished import. The aggregated data was written to %s.", outFileName)); }
From source file:cr.ac.siua.tec.services.impl.RTServiceImpl.java
/** * Builds a string with the structure needed to post a new ticket to RT REST API. *//*from w ww. j a v a 2 s . c o m*/ public String getTicketParamsString(HashMap<String, String> formValues) { formValues.remove("g-recaptcha-response"); StringBuilder sb = new StringBuilder(); //Manually appends the queue, subject and requestor fields. sb.append("Queue: " + formValues.get("Queue") + "\n"); sb.append("Subject: Solicitado por " + formValues.get("RequestorName") + "\n"); sb.append("Requestor: " + formValues.get("Requestor") + "\n"); formValues.remove("Queue"); formValues.remove("Requestor"); formValues.remove("RequestorName"); //Iterates through all custom fields. String fieldName, fieldValue; for (Map.Entry<String, String> entry : formValues.entrySet()) { fieldName = entry.getKey(); fieldValue = entry.getValue(); String lines[] = fieldValue.split("\n"); if (lines.length > 1) { fieldValue = ""; for (String line : lines) fieldValue += " " + line + "\n"; } sb.append("CF-" + fieldName + ": " + fieldValue + "\n"); } return sb.toString(); }
From source file:de.tudarmstadt.tk.statistics.importer.ExternalResultsReader.java
public static void readMUGCTrainTest(String filePath) { String outFileName = "AggregatedTrainTest.csv"; logger.log(Level.INFO, String.format("Importing data from directory %s.", filePath)); // Method requires input directory. Check this condition. File directory = new File(filePath); if (directory.isDirectory()) { System.err.println("Please specify a file. Aborting."); return;// w w w . j a va 2 s .c o m } //Empty previous output file, if there was one File outputFile = new File(directory.getParentFile(), outFileName); if (outputFile.exists()) { outputFile.delete(); } try { String header = "Train;Test;Classifier;FeatureSet;Measure;Value"; PrintWriter out = new PrintWriter(new FileWriter(outputFile, true)); out.println(header); out.close(); } catch (IOException e) { System.err.println("Error while writing aggregated Train-Test file."); e.printStackTrace(); } ArrayList<String> outputRows = new ArrayList<String>(); // iterate all rows List<String[]> inputRowsFirstFile = new ArrayList<>(); inputRowsFirstFile = readAndCheckCSV(filePath, ';'); // first: order by train set ArrayList<ExternalResults> extResults = new ArrayList<>(); for (int i = 0; i < inputRowsFirstFile.size(); i++) { ExternalResults results = new ExternalResults(); // identify current train/test split String[] datasetNames = inputRowsFirstFile.get(i)[0].replace("TRAIN:", "").replace("TEST:", "") .split(","); results.trainSetName = datasetNames[0].replace(" ", ""); results.testSetName = datasetNames[1].replace(" ", ""); // set classifier name results.classifierParameters = inputRowsFirstFile.get(i)[1]; // read feature set results.featureSetName = inputRowsFirstFile.get(i)[2]; // read classification results results.recall = Double.parseDouble(inputRowsFirstFile.get(i)[3]); results.fMeasure = Double.parseDouble(inputRowsFirstFile.get(i)[4]); results.precision = Double.parseDouble(inputRowsFirstFile.get(i)[5]); results.accuracy = Double.parseDouble(inputRowsFirstFile.get(i)[10]) / 100; extResults.add(results); } HashMap<String, ArrayList<ExternalResults>> extResultsByTrainTestFeature = new HashMap<>(); // order by test set for (ExternalResults result : extResults) { String IdKey = result.trainSetName + result.testSetName + result.featureSetName; if (extResultsByTrainTestFeature.containsKey(IdKey)) { extResultsByTrainTestFeature.get(IdKey).add(result); } else { extResultsByTrainTestFeature.put(IdKey, new ArrayList<ExternalResults>()); extResultsByTrainTestFeature.get(IdKey).add(result); } } ArrayList<ExternalResults> aggregatedResults = new ArrayList<>(); // aggregate results or keep as are for (Entry<String, ArrayList<ExternalResults>> trainTestSplit : extResultsByTrainTestFeature.entrySet()) { ExternalResults aggrResult = new ExternalResults(); double recall = 0; double fMeasure = 0; double precision = 0; double accuracy = 0; int nrClassifiers = 0; // for all entries that are from the same train/test split and use the same feature set -> aggregate results for (ExternalResults result : trainTestSplit.getValue()) { aggrResult.testSetName = result.testSetName; aggrResult.trainSetName = result.trainSetName; aggrResult.classifierParameters = result.classifierParameters; aggrResult.featureSetName = result.featureSetName; recall += result.recall; fMeasure += result.fMeasure; precision += result.precision; accuracy += result.accuracy; nrClassifiers++; } aggrResult.accuracy = (accuracy / nrClassifiers); aggrResult.fMeasure = (fMeasure / nrClassifiers); aggrResult.recall = (recall / nrClassifiers); aggrResult.precision = (precision / nrClassifiers); aggregatedResults.add(aggrResult); } // write values of measure for (ExternalResults result : aggregatedResults) { String outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Percent Correct", result.accuracy); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted Precision", result.precision); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted Recall", result.recall); outputRows.add(outputRow); outputRow = String.format("%s;%s;%s;%s;%s;%s", result.trainSetName, result.testSetName, "0", result.featureSetName, "Weighted F-Measure", result.fMeasure); outputRows.add(outputRow); } // Write aggregated data to a new file try { PrintWriter out = new PrintWriter(new FileWriter(outputFile, true)); for (String s : outputRows) { out.println(s); } out.close(); } catch (IOException e) { System.err.println("Error while writing aggregated Train-Test file."); e.printStackTrace(); } logger.log(Level.INFO, String.format("Finished import. The aggregated data was written to %s.", outFileName)); }
From source file:com.chargebee.CSV.PhoneBook.PhoneBook2.PhoneBook.java
private void display(HashMap<String, ArrayList> map) { Scanner sc = new Scanner(System.in); System.out.println("Search by : name/number?"); String choice = sc.nextLine(); System.out.println("Enter the " + choice + " : "); String param = sc.nextLine(); if (choice.toLowerCase().equalsIgnoreCase("name")) { for (String key : map.keySet()) { if (key.toLowerCase().contains(param)) { ArrayList<Person> tempo = new ArrayList(); tempo = map.get(key);//from ww w . j a v a 2s .c om for (Person p : tempo) { p.print(); } } } } else if (choice.toLowerCase().equalsIgnoreCase("number")) { for (Map.Entry<String, ArrayList> entry : map.entrySet()) { ArrayList<Person> tempo = new ArrayList(); tempo = entry.getValue(); for (Person p : tempo) { if (p.getPhone().getHomeNumber().equalsIgnoreCase(param) || p.getPhone().getMobileNumber().equalsIgnoreCase(param) || p.getPhone().getWorkNumber().equalsIgnoreCase(param)) { p.print(); break; } System.out.println("Phone Number not found!!"); } } } else { System.out.println("Invalid Choice!!"); } }
From source file:iddb.core.IDDBService.java
public void saveServerBanPermissions(Server server, HashMap<Long, Long> perm) throws ApplicationError { if (server.getBanPermissions() != null) server.getBanPermissions().clear(); for (Entry<Long, Long> p : perm.entrySet()) { server.setBanPermission(p.getKey(), p.getValue()); }/*w ww . j a v a 2 s . co m*/ try { serverDAO.saveBanPermissions(server); } catch (DAOException e) { throw new ApplicationError(e); } }
From source file:com.google.gwt.emultest.java.util.IdentityHashMapTest.java
public void testEntrySetEntrySetterNonString() { HashMap hashMap = new HashMap(); Integer key = 1;/*from w w w. j a va 2 s . c o m*/ hashMap.put(key, 2); Set entrySet = hashMap.entrySet(); Entry entry = (Entry) entrySet.iterator().next(); entry.setValue(3); assertEquals(3, hashMap.get(key)); hashMap.put(key, 4); assertEquals(4, entry.getValue()); assertEquals(1, hashMap.size()); }