Example usage for java.util HashMap containsKey

List of usage examples for java.util HashMap containsKey

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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:frequencyanalysis.FrequencyAnalysis.java

public static List<Item> findRepeatedFreq(String input) {
    HashMap repeatedCount = new HashMap<String, Integer>();

    for (int i = 0; i < input.length(); i++) {
        if (i + 1 < input.length() && input.charAt(i) == input.charAt(i + 1)) {
            String key = String.valueOf(input.charAt(i)) + String.valueOf(input.charAt(i + 1));

            if (!repeatedCount.containsKey(key)) {
                repeatedCount.put(key, 1);
            } else {
                int tempCount = (int) repeatedCount.get(key);
                tempCount++;//w  ww  .  ja  v  a 2  s . c  om
                repeatedCount.put(key, tempCount);
            }
        }
    }

    return sortByValue(repeatedCount);
}

From source file:com.ibm.bi.dml.hops.globalopt.GDFEnumOptimizer.java

private static void rSetRuntimePlanConfig(Plan p, HashMap<Long, Plan> memo) {
    ExecType CLUSTER = OptimizerUtils.isSparkExecutionMode() ? ExecType.SPARK : ExecType.MR;

    //basic memoization including containment check 
    if (memo.containsKey(p.getNode().getID())) {
        Plan pmemo = memo.get(p.getNode().getID());
        if (!p.getInterestingProperties().equals(pmemo.getInterestingProperties())) {
            //replace plan in memo with new plan
            //TODO this would require additional cleanup in special cases
            if (_resolve.resolveMismatch(pmemo.getRewriteConfig(), p.getRewriteConfig()))
                memo.put(p.getNode().getID(), p);
            //logging of encounter plan mismatch
            LOG.warn("Configuration mismatch on shared node (" + p.getNode().getHop().getHopID()
                    + "). Falling back to heuristic '" + _resolve.getName() + "'.");
            LOG.warn(p.getInterestingProperties().toString());
            LOG.warn(memo.get(p.getNode().getID()).getInterestingProperties());
            _planMismatches++;//from   w  w  w .  j a va  2s.c o  m
            return;
        }
    }

    //set plan configuration
    Hop hop = p.getNode().getHop();
    if (hop != null) {
        RewriteConfig rc = p.getRewriteConfig();
        //set exec type
        hop.setForcedExecType(rc.getExecType());
        //set blocksizes and reblock
        hop.setRowsInBlock(rc.getBlockSize());
        hop.setColsInBlock(rc.getBlockSize());
        if (rc.getExecType() == CLUSTER) //after blocksize update
        {
            //TODO double check dataop condition - side effect from plan validity
            boolean reblock = HopRewriteUtils.alwaysRequiresReblock(hop)
                    || (hop.hasMatrixInputWithDifferentBlocksizes() && !(hop instanceof DataOp));
            hop.setRequiresReblock(reblock);
        } else
            hop.setRequiresReblock(false);
    }

    //process childs
    if (p.getChilds() != null)
        for (Plan c : p.getChilds())
            rSetRuntimePlanConfig(c, memo);

    //memoization (mark as processed)
    memo.put(p.getNode().getID(), p);
}

From source file:com.act.reachables.Network.java

public static JSONArray get(MongoDB db, Set<Node> nodes, Set<Edge> edges) throws JSONException {
    // init the json object with structure:
    // {//from  w  ww . j  a  va2 s . com
    //   "nodeMapping":[
    //     { "name":"Myriel", "group":1 }, ...
    //   ],
    //   "links":[
    //     { "source":1, "target":0, "value":1 }, ...
    //   ]
    // }
    // nodeMapping.group specifies the node color
    // links.value specifies the edge weight
    JSONArray json = new JSONArray();

    HashMap<Long, Set<Node>> treenodes = new HashMap<Long, Set<Node>>();
    HashMap<Long, Set<Edge>> treeedges = new HashMap<Long, Set<Edge>>();
    for (Node n : nodes) {
        Long k = (Long) n.getAttribute("under_root");
        if (!treenodes.containsKey(k)) {
            treenodes.put(k, new HashSet<Node>());
            treeedges.put(k, new HashSet<Edge>());
        }
        treenodes.get(k).add(n);
    }

    for (Edge e : edges) {
        Long k = (Long) e.getAttribute("under_root");
        if (!treeedges.containsKey(k)) {
            throw new RuntimeException("Fatal: Edge found rooted under a tree (under_root) that has no node!");
        }
        treeedges.get(k).add(e);
    }

    for (Long root : treenodes.keySet()) {
        JSONObject tree = new JSONObject();
        HashMap<Node, Integer> nodeOrder = new HashMap<Node, Integer>();
        tree.put("nodeMapping", nodeListObj(db, treenodes.get(root), nodeOrder /*inits this ordering*/));
        tree.put("links", edgeListObj(treeedges.get(root), nodeOrder /* uses the ordering */));

        json.put(tree);
    }

    return json;

}

From source file:com.example.common.ApiRequestFactory.java

/**
 * Generate the API XML request body/*  ww  w. j av  a  2  s . co m*/
 */
@SuppressWarnings("unchecked")
private static String generateXmlRequestBody(Object params) {

    if (params == null) {
        return "<request version=\"2\"></request>";
    }

    HashMap<String, Object> requestParams;
    if (params instanceof HashMap) {
        requestParams = (HashMap<String, Object>) params;
    } else {
        return "<request version=\"2\"></request>";
    }

    final StringBuilder buf = new StringBuilder();

    // TODO: add local_version parameter if exist
    // 2010/12/29 update version to 2 to get comments from bbs
    buf.append("<request version=\"2\"");
    if (requestParams.containsKey("local_version")) {
        buf.append(" local_version=\"" + requestParams.get("local_version") + "\" ");
        requestParams.remove("local_version");
    }
    buf.append(">");

    // add parameter node
    final Iterator<String> keySet = requestParams.keySet().iterator();
    while (keySet.hasNext()) {
        final String key = keySet.next();

        if ("upgradeList".equals(key)) {
            buf.append("<products>");
            List<PackageInfo> productsList = (List<PackageInfo>) requestParams.get(key);
            for (PackageInfo info : productsList) {
                buf.append("<product package_name=\"").append(info.packageName);
                buf.append("\" version_code=\"").append(info.versionCode).append("\"/>");
            }
            buf.append("</products>");
            continue;
        } else if ("appList".equals(key)) {
            buf.append("<apps>");
            List<UpgradeInfo> productsList = (List<UpgradeInfo>) requestParams.get(key);
            for (UpgradeInfo info : productsList) {
                buf.append("<app package_name=\"").append(info.pkgName);
                buf.append("\" version_code=\"").append(info.versionCode);
                buf.append("\" version_name=\"").append(info.versionName);
                buf.append("\" app_name=\"").append(wrapText(info.name));
                //                    buf.append("\" md5=\"").append(info.md5);
                buf.append("\"/>");
            }
            buf.append("</apps>");
            continue;
        }

        buf.append("<").append(key).append(">");
        buf.append(requestParams.get(key));
        buf.append("</").append(key).append(">");
    }

    // add the enclosing quote
    buf.append("</request>");
    return buf.toString();
}

From source file:org.hfoss.posit.web.Communicator.java

/**
 * cleanup the item key,value pairs so that we can receive and save to the internal database
 * @param rMap//from w  ww  .  j  av a  2 s  . c  om
 */
public static void cleanupOnReceive(HashMap<String, Object> rMap) {
    rMap.put(PositDbHelper.FINDS_SYNCED, PositDbHelper.FIND_IS_SYNCED);
    rMap.put(PositDbHelper.FINDS_GUID, rMap.get("barcode_id"));
    //rMap.put(PositDbHelper.FINDS_GUID, rMap.get("barcode_id"));

    rMap.put(PositDbHelper.FINDS_PROJECT_ID, projectId);
    if (rMap.containsKey("add_time")) {
        rMap.put(PositDbHelper.FINDS_TIME, rMap.get("add_time"));
        rMap.remove("add_time");
    }
    if (rMap.containsKey("images")) {
        if (Utils.debug)
            Log.d(TAG, "contains image key");
        rMap.put(PositDbHelper.PHOTOS_IMAGE_URI, rMap.get("images"));
        rMap.remove("images");
    }
}

From source file:edu.illinois.cs.cogcomp.transliteration.CSPTransliteration.java

public static double GetBestProbability(int position, String originalWord1, String word1, String word2,
        CSPModel model, HashMap<Triple<Integer, String, String>, Double> memoizationTable) {
    double result;
    Triple<Integer, String, String> v = new Triple<Integer, String, String>(position, word1, word2);
    if (memoizationTable.containsKey(v)) {
        return memoizationTable.get(v); //we've been down this road before
    }// ww w.j  a  va  2  s  . c  o  m

    result = 0;

    if (word1.length() == 0 && word2.length() == 0)
        return 1; //perfect null-to-null alignment

    int maxSubstringLength1f = Math.min(word1.length(), model.maxSubstringLength);
    int maxSubstringLength2f = Math.min(word2.length(), model.maxSubstringLength);

    String[] leftContexts = WikiTransliteration.GetLeftFallbackContexts(originalWord1, position,
            Math.max(model.segContextSize, model.productionContextSize));

    double minProductionProbability1 = 1;

    for (int i = 1; i <= maxSubstringLength1f; i++) //for each possible substring in the first word...
    {
        minProductionProbability1 *= model.minProductionProbability;

        String substring1 = word1.substring(0, i);
        String[] rightContexts = WikiTransliteration.GetRightFallbackContexts(originalWord1, position + i,
                Math.max(model.segContextSize, model.productionContextSize));

        double segProb;
        if (model.segProbs.size() == 0)
            segProb = 1;
        else {
            segProb = 0;
            for (int k = model.productionContextSize; k >= 0; k--) {
                Triple<String, String, String> v5 = new Triple<>(leftContexts[k], substring1, rightContexts[k]);
                if (model.segProbs.containsKey(v5)) {
                    segProb = model.segProbs.get(v5);
                    break;
                }
            }
        }

        double minProductionProbability2 = 1;
        for (int j = 1; j <= maxSubstringLength2f; j++) //foreach possible substring in the second
        {
            minProductionProbability2 *= model.minProductionProbability;

            if ((word1.length() - i) * model.maxSubstringLength >= word2.length() - j
                    && (word2.length() - j) * model.maxSubstringLength >= word1.length() - i) //if we get rid of these characters, can we still cover the remainder of word2?
            {
                double minProductionProbability;
                if (model.smoothMode == CSPModel.SmoothMode.BySource)
                    minProductionProbability = minProductionProbability1;
                else if (model.smoothMode == CSPModel.SmoothMode.ByMax)
                    minProductionProbability = Math.min(minProductionProbability1, minProductionProbability2);
                else //if (model.smoothMode == SmoothMode.BySum)
                    minProductionProbability = minProductionProbability1 * minProductionProbability2;

                String substring2 = word2.substring(0, j);
                //Pair<Triple<String, String, String>, String> production = new Pair<Triple<String, String, String>, String>(new Triple<String, String, String>(leftProductionContext, substring1, rightProductionContext), substring2);

                double prob;
                if (model.productionProbs.size() == 0)
                    prob = 1;
                else {
                    prob = 0;
                    for (int k = model.productionContextSize; k >= 0; k--) {
                        Pair<Triple<String, String, String>, String> v4 = new Pair<>(
                                new Triple<>(leftContexts[k], substring1, rightContexts[k]), substring2);
                        if (model.productionProbs.containsKey(v4)) {
                            prob = model.productionProbs.get(v4);
                            break;
                        }

                    }

                    prob = Math.max(prob, minProductionProbability);
                }

                double remainder = prob * GetBestProbability(position + i, originalWord1, word1.substring(i),
                        word2.substring(j), model, memoizationTable);

                if (remainder > result)
                    result = remainder; //maximize

                //record this remainder in our results
                //result.x += remainder.x * prob * segProb;
                //result.y += remainder.y * segProb;
            }
        }
    }

    memoizationTable.put(new Triple<>(position, word1, word2), result);
    return result;
}

From source file:org.opendatakit.survey.android.provider.SubmissionProvider.java

@SuppressWarnings("unchecked")
private static final void putElementValue(HashMap<String, Object> dataMap, ColumnDefinition defn,
        Object value) {//  ww  w  .j a va  2s  . c  om
    List<ColumnDefinition> nesting = new ArrayList<ColumnDefinition>();
    ColumnDefinition cur = defn.getParent();
    while (cur != null) {
        nesting.add(cur);
        cur = cur.getParent();
    }

    HashMap<String, Object> elem = dataMap;
    for (int i = nesting.size() - 1; i >= 0; --i) {
        cur = nesting.get(i);
        if (elem.containsKey(cur.getElementName())) {
            elem = (HashMap<String, Object>) elem.get(cur.getElementName());
        } else {
            elem.put(cur.getElementName(), new HashMap<String, Object>());
            elem = (HashMap<String, Object>) elem.get(cur.getElementName());
        }
    }
    elem.put(defn.getElementName(), value);
}

From source file:net.doubledoordev.backend.webserver_old.methods.Post.java

/**
 * Handle post requests from the login page
 *//*from   ww  w  .j  a  v a2  s  .co  m*/
private static void handleLogin(HashMap<String, Object> dataObject, NanoHTTPD.HTTPSession session,
        Map<String, String> map) {
    if (map.containsKey("username") && map.containsKey("password")) {
        User user = Settings.getUserByName(map.get("username"));
        if (user != null && user.verify(map.get("password"))) {
            session.getCookies().set(COOKIE_KEY, user.getUsername() + "|" + user.getPasshash(), 30);
            dataObject.put("user", user);
        } else
            dataObject.put("message", "Login failed.");
    } else if (map.containsKey("logout")) {
        session.getCookies().delete(COOKIE_KEY);
        dataObject.remove("user");
    } else if (dataObject.containsKey("user") && map.containsKey("oldPassword")
            && map.containsKey("newPassword")) {
        User user = (User) dataObject.get("user");
        if (user.updatePassword(map.get("oldPassword"), map.get("newPassword"))) {
            session.getCookies().set(COOKIE_KEY, user.getUsername() + "|" + user.getPasshash(), 30);
        } else
            dataObject.put("message", "Old password was wrong.");
    } else
        dataObject.put("message", "Form error.");
}

From source file:gov.nih.nci.rembrandt.web.helper.PCAAppletHelper.java

public static String generateParams(String sessionId, String taskId) {
    String htm = "";
    DecimalFormat nf = new DecimalFormat("0.0000");

    try {/*from   w  w w .j  ava2s  .  c  o  m*/
        //retrieve the Finding from cache and build the list of PCAData points
        PrincipalComponentAnalysisFinding principalComponentAnalysisFinding = (PrincipalComponentAnalysisFinding) businessTierCache
                .getSessionFinding(sessionId, taskId);

        ArrayList<PrincipalComponentAnalysisDataPoint> pcaData = new ArrayList();

        Collection<ClinicalFactorType> clinicalFactors = new ArrayList<ClinicalFactorType>();
        List<String> sampleIds = new ArrayList();
        Map<String, PCAresultEntry> pcaResultMap = new HashMap<String, PCAresultEntry>();

        List<PCAresultEntry> pcaResults = principalComponentAnalysisFinding.getResultEntries();
        for (PCAresultEntry pcaEntry : pcaResults) {
            sampleIds.add(pcaEntry.getSampleId());
            pcaResultMap.put(pcaEntry.getSampleId(), pcaEntry);
        }

        Collection<SampleResultset> validatedSampleResultset = ClinicalDataValidator
                .getValidatedSampleResultsetsFromSampleIDs(sampleIds, clinicalFactors);

        if (validatedSampleResultset != null) {
            String id;
            PCAresultEntry entry;

            for (SampleResultset rs : validatedSampleResultset) {
                id = rs.getBiospecimen().getSpecimenName();
                entry = pcaResultMap.get(id);
                PrincipalComponentAnalysisDataPoint pcaPoint = new PrincipalComponentAnalysisDataPoint(id,
                        entry.getPc1(), entry.getPc2(), entry.getPc3());
                String diseaseName = rs.getDisease().getValueObject();
                if (diseaseName != null) {
                    pcaPoint.setDiseaseName(diseaseName);
                } else {
                    pcaPoint.setDiseaseName(DiseaseType.NON_TUMOR.name());
                }
                GenderDE genderDE = rs.getGenderCode();
                if (genderDE != null) {
                    String gt = genderDE.getValueObject();
                    if (gt != null) {
                        GenderType genderType = GenderType.valueOf(gt);
                        if (genderType != null) {
                            pcaPoint.setGender(genderType);
                        }
                    }
                }
                Long survivalLength = rs.getSurvivalLength();
                if (survivalLength != null) {
                    //survival length is stored in days in the DB so divide by 30 to get the 
                    //approx survival in months
                    double survivalInMonths = survivalLength.doubleValue() / 30.0;
                    pcaPoint.setSurvivalInMonths(survivalInMonths);
                }
                pcaData.add(pcaPoint);
            }
        }

        //make a hashmap
        // [key=group] hold the array of double[][]s
        HashMap<String, ArrayList> hm = new HashMap();

        //now we should have a collection of PCADataPts
        double[][] pts = new double[pcaData.size()][3];
        for (int i = 0; i < pcaData.size(); i++) {
            //just create a large 1 set for now
            //are we breaking groups by gender or disease?
            PrincipalComponentAnalysisDataPoint pd = pcaData.get(i);

            pts[i][0] = pd.getPc1value();
            pts[i][1] = pd.getPc2value();
            pts[i][2] = pd.getPc3value();
            ArrayList<double[]> al;

            try {
                if (hm.containsKey(pd.getDiseaseName())) {
                    //already has it, so add this one
                    al = (ArrayList) hm.get(pd.getDiseaseName());
                } else {
                    al = new ArrayList();
                    hm.put(pd.getDiseaseName(), new ArrayList());
                }
                if (!al.contains(pts[i])) {
                    al.add(pts[i]);
                }
                hm.put(pd.getDiseaseName(), al);
            } catch (Exception e) {
                System.out.print(e.toString());
            }
        }
        int r = hm.size();
        if (r == 1) {
        }
        //hm should now contain a hashmap of all the disease groups

        //generate the param tags
        htm += "<param name=\"key\" value=\"" + taskId + "\" >\n";
        htm += "<param name=\"totalPts\" value=\"" + pts.length + "\" >\n";
        htm += "<param name=\"totalGps\" value=\"" + hm.size() + "\" >\n";
        int ii = 0;
        for (Object k : hm.keySet()) {
            String key = k.toString();
            //for each group

            Color diseaseColor = Color.GRAY;
            if (DiseaseType.valueOf(key) != null) {
                DiseaseType disease = DiseaseType.valueOf(key);
                diseaseColor = disease.getColor();
            }

            ArrayList<double[]> al = hm.get(key);
            htm += "<param name=\"groupLabel_" + ii + "\" value=\"" + key + "\" >\n";
            htm += "<param name=\"groupCount_" + ii + "\" value=\"" + al.size() + "\" >\n";
            htm += "<param name=\"groupColor_" + ii + "\" value=\"" + diseaseColor.getRGB() + "\" >\n";
            int jj = 0;
            for (double[] d : al) {
                String comm = nf.format(d[0]) + "," + nf.format(d[1]) + "," + nf.format(d[2]);
                String h = "<param name=\"pt_" + ii + "_" + jj + "\" value=\"" + comm + "\">\n";
                htm += h;
                jj++;
            }
            ii++;
        }
        /*
         //for bulk rendering
        for(int i=0; i<pts.length; i++)   {
           String comm = String.valueOf(pts[i][0]) + "," +
           String.valueOf(pts[i][1]) + "," +
           String.valueOf(pts[i][2]);
                   
           String h = "<param name=\"pt_"+i+"\" value=\""+ comm +"\">\n";
           //htm += h;
        }
        */

    } //try
    catch (Exception e) {

    }

    return htm;
}

From source file:edu.illinois.cs.cogcomp.transliteration.CSPTransliteration.java

public static Pair<Double, Double> GetProbability(int position, String originalWord1, String word1,
        String word2, CSPModel model,
        HashMap<Triple<Integer, String, String>, Pair<Double, Double>> memoizationTable) {
    Pair<Double, Double> result;
    Triple<Integer, String, String> v = new Triple<>(position, word1, word2);
    if (memoizationTable.containsKey(v)) {
        return memoizationTable.get(v);
    }/*  ww w .  j a v  a 2  s .c om*/

    result = new Pair<>(0.0, 0.0);

    if (word1.length() == 0 && word2.length() == 0) //record probabilities
    {
        result.setFirst(1.0); //null -> null is always a perfect alignment
        result.setSecond(1.0);
        return result; //end of the line
    }

    int maxSubstringLength1f = Math.min(word1.length(), model.maxSubstringLength);
    int maxSubstringLength2f = Math.min(word2.length(), model.maxSubstringLength);

    String[] leftContexts = WikiTransliteration.GetLeftFallbackContexts(originalWord1, position,
            Math.max(model.segContextSize, model.productionContextSize));

    double minProductionProbability1 = 1;

    for (int i = 1; i <= maxSubstringLength1f; i++) //for each possible substring in the first word...
    {
        minProductionProbability1 *= model.minProductionProbability;

        String substring1 = word1.substring(0, i);
        String[] rightContexts = WikiTransliteration.GetRightFallbackContexts(originalWord1, position + i,
                Math.max(model.segContextSize, model.productionContextSize));

        double segProb;
        if (model.segProbs.size() == 0)
            segProb = 1;
        else {
            segProb = 0;
            for (int k = model.productionContextSize; k >= 0; k--) {

                Triple<String, String, String> v2 = new Triple<>(leftContexts[k], substring1, rightContexts[k]);
                if (model.segProbs.containsKey(v2)) {
                    segProb = model.segProbs.get(v2);
                    break;
                }
            }
        }

        double minProductionProbability2 = 1;
        for (int j = 1; j <= maxSubstringLength2f; j++) //foreach possible substring in the second
        {
            minProductionProbability2 *= model.minProductionProbability;

            if ((word1.length() - i) * model.maxSubstringLength >= word2.length() - j
                    && (word2.length() - j) * model.maxSubstringLength >= word1.length() - i) //if we get rid of these characters, can we still cover the remainder of word2?
            {
                double minProductionProbability;
                if (model.smoothMode == CSPModel.SmoothMode.BySource)
                    minProductionProbability = minProductionProbability1;
                else if (model.smoothMode == CSPModel.SmoothMode.ByMax)
                    minProductionProbability = Math.min(minProductionProbability1, minProductionProbability2);
                else //if (model.smoothMode == SmoothMode.BySum)
                    minProductionProbability = minProductionProbability1 * minProductionProbability2;

                String substring2 = word2.substring(0, j);
                //Pair<Triple<String, String, String>, String> production = new Pair<Triple<String, String, String>, String>(new Triple<String, String, String>(leftProductionContext, substring1, rightProductionContext), substring2);

                double prob;
                if (model.productionProbs.size() == 0)
                    prob = 1;
                else {
                    prob = 0;
                    for (int k = model.productionContextSize; k >= 0; k--) {
                        Pair<Triple<String, String, String>, String> v3 = new Pair<>(
                                new Triple<>(leftContexts[k], substring1, rightContexts[k]), substring2);
                        if (model.productionProbs.containsKey(v3)) {
                            prob = model.productionProbs.get(v3);
                            break;
                        }
                    }

                    prob = Math.max(prob, minProductionProbability);
                }

                Pair<Double, Double> remainder = GetProbability(position + i, originalWord1, word1.substring(i),
                        word2.substring(j), model, memoizationTable);

                //record this remainder in our results
                result.setFirst(result.getFirst() + remainder.getFirst() * prob * segProb);
                result.setSecond(result.getSecond() + remainder.getSecond() * segProb);

            }
        }
    }

    memoizationTable.put(new Triple<>(position, word1, word2), result);
    return result;
}