Example usage for java.lang Double NaN

Introduction

In this page you can find the example usage for java.lang Double NaN.

Prototype

double NaN

To view the source code for java.lang Double NaN.

Click Source Link

Document

A constant holding a Not-a-Number (NaN) value of type double .

Usage

From source file:Main.java

public static void main(String[] args) {

    System.out.println(Double.NaN);
}

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From source file:Main.java

public static void main(String[] args) {
    System.out.printf("%.2e %n", Double.NaN);
    System.out.printf("%.2f %n", Double.POSITIVE_INFINITY);
    System.out.printf("%.2g %n", Double.NEGATIVE_INFINITY);
    System.out.printf("%(f %n", Double.POSITIVE_INFINITY);
    System.out.printf("%(f %n", Double.NEGATIVE_INFINITY);
}

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From source file:Calculator.java

public static void main(String[] args) {
    System.out.println("type something like: 1+3");
    Scanner scanner = new Scanner(System.in);
    double n1 = Double.NaN;
    double n2 = Double.NaN;
    String operation = null;//from   ww w. ja  v  a 2s. co  m

    try {
        n1 = scanner.nextDouble();
        operation = scanner.next();
        n2 = scanner.nextDouble();
        double result = calculate(n1, n2, operation);
        System.out.printf("%s %s  %s  = %.2f%n", n1, operation, n2, result);
    }

    catch (Exception e) {
        System.out.println("An invalid expression.");
    }
}

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From source file:InfNaN.java

public static void main(String[] argv) {
    double d = 123;
    double e = 0;
    if (d / e == Double.POSITIVE_INFINITY)
        System.out.println("Check for POSITIVE_INFINITY works");
    double s = Math.sqrt(-1);
    if (s == Double.NaN)
        System.out.println("Comparison with NaN incorrectly returns true");
    if (Double.isNaN(s))
        System.out.println("Double.isNaN() correctly returns true");
}

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From source file:FloatCmp.java

public static void main(String[] argv) {
    double da = 3 * .3333333333;
    double db = 0.99999992857;

    // Compare two numbers that are expected to be close.
    if (da == db) {
        System.out.println("Java considers " + da + "==" + db);
        // else compare with our own equals method
    } else if (equals(da, db, 0.0000001)) {
        System.out.println("True within epsilon " + EPSILON);
    } else {/*w w  w.  java  2 s .  c o  m*/
        System.out.println(da + " != " + db);
    }

    // Show that comparing two NaNs is not a good idea:
    double d1 = Double.NaN;
    double d2 = Double.NaN;
    if (d1 == d2)
        System.err.println("Comparing two NaNs incorrectly returns true.");
    if (!new Double(d1).equals(new Double(d2)))
        System.err.println("Double(NaN).equal(NaN) incorrectly returns false.");
}

---

From source file:ca.mcgill.networkdynamics.geoinference.evaluation.CrossValidationScorer.java

public static void main(String[] args) throws Exception {

    if (args.length != 4) {
        System.out.println("java CVS predictions-dir/ " + "cv-gold-dir/ results.txt error-sample.tsv");
        return;//from www.j  a va2 s  . c  om
    }

    File predDir = new File(args[0]);
    File cvDir = new File(args[1]);

    TDoubleList errors = new TDoubleArrayList(10_000_000);
    TLongSet locatedUsers = new TLongHashSet(10_000_000);
    TLongSet allUsers = new TLongHashSet(10_000_000);
    TLongObjectMap<TDoubleList> userToErrors = new TLongObjectHashMap<TDoubleList>();

    TLongDoubleMap tweetIdToError = new TLongDoubleHashMap(10_000_000);
    TLongObjectMap<double[]> idToPredLoc = new TLongObjectHashMap<double[]>();

    int tweetsSeen = 0;
    int tweetsLocated = 0;

    BufferedReader cvBr = new BufferedReader(new FileReader(new File(cvDir, "folds.info.tsv")));
    for (String foldLine = null; (foldLine = cvBr.readLine()) != null;) {
        String[] cols = foldLine.split("\t");
        String foldName = cols[0];

        System.out.printf("Scoring results for fold %s%n", foldName);

        File foldPredictionsFile = new File(predDir, foldName + ".results.tsv.gz");

        File goldLocFile = new File(cvDir, foldName + ".gold-locations.tsv");

        if (foldPredictionsFile.exists()) {
            BufferedReader br = Files.openGz(foldPredictionsFile);
            for (String line = null; (line = br.readLine()) != null;) {
                String[] arr = line.split("\t");
                long id = Long.parseLong(arr[0]);
                idToPredLoc.put(id, new double[] { Double.parseDouble(arr[1]), Double.parseDouble(arr[2]) });
            }
            br.close();
        }

        System.out.printf("loaded predictions for %d tweets; " + "scoring predictions%n", idToPredLoc.size());

        BufferedReader br = new BufferedReader(new FileReader(goldLocFile));
        for (String line = null; (line = br.readLine()) != null;) {
            String[] arr = line.split("\t");
            long id = Long.parseLong(arr[0]);
            long userId = Long.parseLong(arr[1]);

            allUsers.add(userId);
            tweetsSeen++;

            double[] predLoc = idToPredLoc.get(id);
            if (predLoc == null)
                continue;

            tweetsLocated++;
            locatedUsers.add(userId);

            double[] goldLoc = new double[] { Double.parseDouble(arr[2]), Double.parseDouble(arr[3]) };

            double dist = Geometry.getDistance(predLoc, goldLoc);
            errors.add(dist);
            tweetIdToError.put(id, dist);

            TDoubleList userErrors = userToErrors.get(userId);
            if (userErrors == null) {
                userErrors = new TDoubleArrayList();
                userToErrors.put(userId, userErrors);
            }
            userErrors.add(dist);

        }
        br.close();
    }

    errors.sort();
    System.out.println("Num errors to score: " + errors.size());

    double auc = 0;
    double userCoverage = 0;
    double tweetCoverage = tweetsLocated / (double) tweetsSeen;
    double medianMaxUserError = Double.NaN;
    double medianMedianUserError = Double.NaN;

    if (errors.size() > 0) {
        auc = computeAuc(errors);
        userCoverage = locatedUsers.size() / ((double) allUsers.size());
        TDoubleList maxUserErrors = new TDoubleArrayList(locatedUsers.size());
        TDoubleList medianUserErrors = new TDoubleArrayList(locatedUsers.size());
        for (TDoubleList userErrors : userToErrors.valueCollection()) {
            userErrors.sort();
            maxUserErrors.add(userErrors.get(userErrors.size() - 1));
            medianUserErrors.add(userErrors.get(userErrors.size() / 2));
        }

        maxUserErrors.sort();
        medianMaxUserError = maxUserErrors.get(maxUserErrors.size() / 2);

        medianUserErrors.sort();
        medianMedianUserError = medianUserErrors.get(medianUserErrors.size() / 2);

        // Compute CDF
        int[] errorsPerKm = new int[MAX_KM];
        for (int i = 0; i < errors.size(); ++i) {
            int error = (int) (Math.round(errors.get(i)));
            errorsPerKm[error]++;
        }

        // The accumulated sum of errors per km
        int[] errorsBelowEachKm = new int[errorsPerKm.length];
        for (int i = 0; i < errorsBelowEachKm.length; ++i) {
            errorsBelowEachKm[i] = errorsPerKm[i];
            if (i > 0)
                errorsBelowEachKm[i] += errorsBelowEachKm[i - 1];
        }

        final double[] cdf = new double[errorsBelowEachKm.length];
        double dSize = errors.size(); // to avoid casting all the time
        for (int i = 0; i < cdf.length; ++i)
            cdf[i] = errorsBelowEachKm[i] / dSize;
    }

    PrintWriter pw = new PrintWriter(new File(args[2]));
    pw.println("AUC\t" + auc);
    pw.println("user coverage\t" + userCoverage);
    pw.println("tweet coverage\t" + tweetCoverage);
    pw.println("median-max error\t" + medianMaxUserError);
    pw.close();

    // Choose a random sampling of 10K tweets to pass on to the authors
    // here.        
    PrintWriter errorsPw = new PrintWriter(args[3]);
    TLongList idsWithErrors = new TLongArrayList(tweetIdToError.keySet());
    idsWithErrors.shuffle(new Random());
    // Choose the first 10K
    for (int i = 0, chosen = 0; i < idsWithErrors.size() && chosen < 10_000; ++i) {

        long id = idsWithErrors.get(i);
        double[] prediction = idToPredLoc.get(id);
        double error = tweetIdToError.get(id);
        errorsPw.println(id + "\t" + error + "\t" + prediction[0] + "\t" + prediction[1]);
        ++chosen;
    }
    errorsPw.close();
}

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From source file:Main.java

public static double getDouble(Node aNode, String attr) {
    return getDouble(aNode, attr, Double.NaN);
}

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From source file:Main.java

public static Double quotient(Double d1, Double d2) {
    if (d1 == null)
        return Double.valueOf(0);
    if (d2 == null)
        return Double.NaN;
    return d1 / d2;
}

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From source file:Main.java

/**
 * @param nums Any descendant of Number (Integer, Short, Double, Float, etc)
 * @return The mean of the number, or Double.NaN if the list is empty.
 *//*w ww  .j  a va 2  s.  co m*/
public static double mean(Collection<? extends Number> nums) {
    if (nums == null || nums.isEmpty()) {
        return Double.NaN;
    }
    double sum = 0.0;
    for (Number n : nums) {
        sum += n.doubleValue();
    }
    return sum / nums.size();
}

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From source file:Main.java

/**
 * DOC bZhou Comment method "computePercent".
 * /* w  ww .j a  v a  2 s .  c  o  m*/
 * @param userCount
 * @param count
 * @return
 */
private static String computePercent(double userCount, double count) {
    double result = userCount / count;
    return result != Double.NaN ? String.valueOf(result) : null;
}

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