Example usage for java.util HashMap containsKey

List of usage examples for java.util HashMap containsKey

  1. HOME
  2. Java
  3. java
  4. java.util.*
  5. HashMap
  6. containsKey

Introduction

In this page you can find the example usage for java.util HashMap containsKey.

Prototype

public boolean containsKey(Object key)

Source Link

Document

Returns true if this map contains a mapping for the specified key.

Usage

From source file:DIA_Umpire_Quant.DIA_Umpire_ProtQuant.java

private static void SaintOutput(LCMSID protID, LCMSID IDsummary, FragmentSelection fragselection,
        FileWriter interactionfile, String filename, String samplename, HashMap<String, String> PreyID,
        int quanttype) throws IOException {
    for (String key : protID.ProteinList.keySet()) {
        if (IDsummary.ProteinList.containsKey(key)) {
            ProtID protein = IDsummary.ProteinList.get(key);
            float abundance = 0f;

            if (quanttype == 1) {
                abundance = protein.GetAbundanceByMS1_IBAQ();
            } else if (quanttype == 2) {
                abundance = protein.GetAbundanceByTopCorrFragAcrossSample(
                        fragselection.TopPeps.get(protein.getAccNo()), fragselection.TopFrags);
            }//from  w w w  .j a  v a  2s.  c  om
            if (abundance > 0) {
                interactionfile.write(FilenameUtils.getBaseName(filename) + "\t" + samplename + "\t"
                        + protein.getAccNo() + "\t" + abundance + "\n");
                if (!PreyID.containsKey(protein.getAccNo())) {
                    PreyID.put(protein.getAccNo(), /*protein.Sequence.length()+"\t"+*/ protein.GetGeneName());
                }
            }
        }
    }
}

From source file:com.bluexml.side.forms.generator.alfresco.chiba.FormGenerator.java

public boolean shouldGenerate(HashMap<String, List<IFile>> modelsInfo, String id_metamodel) {
    return modelsInfo.containsKey(ClazzPackage.eNS_URI) || modelsInfo.containsKey(FormPackage.eNS_URI);
}

From source file:com.concursive.connect.web.modules.calendar.portlets.main.SaveEventInviteesAction.java

private boolean scheduleDimdimMeeting(Connection db, MeetingInviteesBean meetingInviteesBean)
        throws SQLException {
    Meeting meeting = meetingInviteesBean.getMeeting();

    if (!StringUtils.hasText(meeting.getDimdimUrl()) || !StringUtils.hasText(meeting.getDimdimUsername())
            || !StringUtils.hasText(meeting.getDimdimPassword())) {
        meeting.addError("inviteesError", "Missing Dimdim credentials");
        return false;
    }// w  w w . jav a  2 s.  co  m

    HashMap<String, String> resultMap = DimDimUtils.processDimdimMeeting(meetingInviteesBean, null);
    if (resultMap.containsKey(DimDimUtils.DIMDIM_CODE_SUCCESS)) {
        String dimdimMeetingId = resultMap.get(DimDimUtils.DIMDIM_CODE_SUCCESS);
        meeting.setDimdimMeetingId(dimdimMeetingId);
        meeting.update(db);
        return true;
    }
    meeting.addError("inviteesError", resultMap.get(resultMap.keySet().toArray()[0]));
    return false;
}

From source file:com.twosigma.beakerx.chart.ChartDetails.java

protected GraphicsActionObject getDetailsFromMessage(HashMap content) {
    GraphicsActionObject ret = null;//  www .  j  a  v a2s .  c o  m

    if (content.containsKey("params")) {

        HashMap params = (HashMap) content.get("params");

        if (params.containsKey("type")) {

            String type = (String) params.get("type");
            switch (type) {

            case "CategoryGraphicsActionObject": {
                ret = new CategoryGraphicsActionObject();
                CategoryGraphicsActionObject retObject = (CategoryGraphicsActionObject) ret;
                if (params.containsKey("category")) {
                    retObject.setCategory((int) params.get("category"));
                }
                if (params.containsKey("series")) {
                    retObject.setSeries((int) params.get("series"));
                }
            }
                break;

            case "CombinedPlotActionObject": {
                ret = new CombinedPlotActionObject();
                CombinedPlotActionObject retObject = (CombinedPlotActionObject) ret;
                if (params.containsKey("subplotIndex")) {
                    retObject.setSubplotIndex((int) params.get("subplotIndex"));
                }
                if (params.containsKey("index")) {
                    retObject.setIndex((int) params.get("index"));
                }
            }
                break;

            case "XYGraphicsActionObject": {
                ret = new XYGraphicsActionObject();
                XYGraphicsActionObject retObject = (XYGraphicsActionObject) ret;
                if (params.containsKey("index")) {
                    retObject.setIndex((int) params.get("index"));
                }
            }
                break;
            }

            if (params.containsKey("actionType")) {
                CommActions value = CommActions.getByAction((String) params.get("actionType"));
                ret.setActionType(value);
            }

            if (params.containsKey("tag")) {
                ret.setTag((String) params.get("tag"));
            }

            if (params.containsKey("key")) {
                ret.setKey((String) params.get("key"));
            }

        }
    }
    return ret;
}

From source file:controller.PresentatieController.java

@RequestMapping(value = { "/presentatie/inschrijven" }, method = RequestMethod.POST)
public @ResponseBody String register(@RequestBody Long id) throws JSONException {
    System.out.println(id);//from  ww  w  . ja va2 s .c o  m

    JSONObject output = new JSONObject();
    output.put("success", false);

    Presentation p = presentationRepository.findOne(id);
    if (p == null) {
        output.put("message", "Kan de presentatie niet vinden.");
        return output.toString();
    }

    //check for free spots
    if (p.getAttendees().size() == p.getLocation().getCapacity()) {
        output.put("message", "Er is geen plaats meer vrij");
        return output.toString();
    }

    //check if user is already attending presentation at this timeframe
    Authentication auth = SecurityContextHolder.getContext().getAuthentication();
    User user = (User) auth.getPrincipal();

    if (!(user instanceof Student)) {
        output.put("message", "Enkel studenten kunnen zich inschrijven voor een presentatie");
        return output.toString();
    }

    Student student = (Student) user;
    HashMap<Date, List<TimeFrame>> timeframes = new HashMap<>();

    for (GuestRequest gr : student.getGuestRequests()) {
        Presentation pr = gr.getPresentation();
        if (!timeframes.containsKey(pr.getDate())) {
            timeframes.put(pr.getDate(), new ArrayList<TimeFrame>());
            timeframes.get(pr.getDate()).add(pr.getTimeFrame());
        }

        if (!timeframes.get(pr.getDate()).contains(pr.getTimeFrame())) {
            timeframes.get(pr.getDate()).add(pr.getTimeFrame());
        } else {
            output.put("message", "U heeft zich al ingeschreven voor een presentatie op hetzelfde tijdstip");
            return output.toString();
        }
    }

    GuestRequest n = new GuestRequest();
    n.setPresentation(p);
    n.setStudent(student);
    student.getGuestRequests().add(n);

    //p.getAttendees().add(student);        
    //presentationRepository.flush();

    guestRequestRepository.saveAndFlush(n);

    output.put("success", true);
    return output.toString();
}

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 w ww  . ja v  a  2  s . co  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: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;/*from   w w w .ja  v  a2 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:hu.ppke.itk.nlpg.purepos.decoder.BeamedViterbi.java

private void update(HashMap<NGram<Integer>, Node> beam, NGram<Integer> newState, Double newWeight,
        Node fromNode) {//from   w w  w  .j a  v a  2s.  c  o  m

    if (!beam.containsKey(newState)) {
        // logger.trace("\t\t\tAS: " + newNGram + " from " + context
        // + " with " + newValue);

        beam.put(newState, new Node(newState, newWeight, fromNode));

    } else if (beam.get(newState).getWeight() < newWeight) {
        // logger.trace("\t\t\tUS: " + old + " to " + newNGram + " from "
        // + context + " with " + newValue);
        beam.get(newState).setPrevious(fromNode);
        beam.get(newState).setWeight(newWeight);
    } else {
        // logger.trace("\t\t\tNU: " + old + " to " + newNGram + " from "
        // + context + " with " + newValue);
    }
}

From source file:de.hybris.platform.mpintgordermanagement.interceptor.OrderEntryPrepareInterceptor.java

@Override
public void onPrepare(OrderEntryModel orderEntrymodel, InterceptorContext ctx) throws InterceptorException {
    String threadLocalKey = "entriedOnce-" + orderEntrymodel.getEntryNumber();
    HashMap<String, String> contextThreadLocalMap = contextThreadLocal.get();
    if (contextThreadLocalMap.containsKey(threadLocalKey)) {
        return;// w  w  w. j a v a2s .c o  m
    }
    contextThreadLocalMap.put(threadLocalKey, "true");

    if (orderEntrymodel instanceof TmallOrderEntryModel) {
        final TmallOrderEntryModel tmallOrderEntryModel = (TmallOrderEntryModel) orderEntrymodel;
        try {
            onPrepareTmallOrderEntry(tmallOrderEntryModel);
        } catch (Exception e) {
            log.error("Handle order entry status mapping service failed for " + orderEntrymodel, e);
            logMessage(Boolean.FALSE, "Sync status to hybris", tmallOrderEntryModel,
                    "Sync status to hybris failed due to unknown reason:" + e.getMessage());
        }
    }
    contextThreadLocalMap.remove(threadLocalKey);
}

From source file:com.dalamar.watcher.TrainStationWatcher.java

public void diffWithDB() {

    ArrayList<LateTrain> trainsInDB = (ArrayList<LateTrain>) ltd.clear().betweenDates(date, date).station(name)
            .executeQuery();/*w  ww .jav  a2s  .  c o m*/

    LateTrain[] trains = null;
    try {
        trains = fetchLateTrains();
    } catch (IOException ex) {
        Logger.getLogger(TrainStationWatcher.class.getName()).log(Level.SEVERE, null, ex);
    }

    if (trains == null)
        return;

    if (trainsInDB.isEmpty()) {
        for (LateTrain tr : trains) {
            tr.setToStation(name);
            tr.setDateCaptured(date); // temporary for test. please fix later to Calendar.getInstance().getTime();
            ltd.save(tr);
        }
    }

    else {
        HashMap<String, LateTrain> trainNumToTrain = getTrainMap(trainsInDB);
        for (LateTrain tr : trains) {
            if (trainNumToTrain.containsKey(tr.getTrainNumber())) {
                diffSingleTrain(tr, trainNumToTrain);
            } else {
                tr.setToStation(this.name);
                tr.setDateCaptured(date);// temporary for test. please fix later to Calendar.getInstance().getTime();
                ltd.save(tr);
            }
        }
    }

    rectifyInDB();

}