Example usage for java.lang Math PI

Introduction

In this page you can find the example usage for java.lang Math PI.

Prototype

double PI

To view the source code for java.lang Math PI.

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Document

The double value that is closer than any other to pi, the ratio of the circumference of a circle to its diameter.

Usage

From source file:Main.java

public static final float degToRad(final float degree) {
    return (float) (Math.PI / 180.0f * degree);
}

From source file:Main.java

public static double degreesToRadians(double degrees) {
    return (degrees * Math.PI / 180.0);
}

From source file:Main.java

public static int To360Degrees(double rot) {
    return (int) Math.round(rot / Math.PI * 180);
}

From source file:Main.java

public static double radians2angle(double radians) {
    return 180f * radians / Math.PI;
}

From source file:Main.java

public static final float radToDeg(final float rad) {
    return (float) (180.0f / Math.PI * rad);
}

From source file:Main.java

public static double[] geoToMercator(double[] g) {
    double d = g[0] * Math.PI / 180, m = g[1] * Math.PI / 180, l = 6378137, k = 0.0818191908426,
            f = k * Math.sin(m);//from   w ww. ja v  a 2s . co m
    double h = Math.tan(Math.PI / 4 + m / 2), j = Math.pow(Math.tan(Math.PI / 4 + Math.asin(f) / 2), k),
            i = h / j;
    // return new DoublePoint(Math.round(l * d), Math.round(l *
    // Math.log(i)));
    return new double[] { l * d, l * Math.log(i) };
}

From source file:Main.java

public static float clampAngle(float angle) {
    float res = angle % (float) (Math.PI * 2);
    if (res < 0) {
        res += Math.PI * 2;//from  w ww.jav a2  s  .c o m
    }
    return res;
}

From source file:edu.oregonstate.eecs.mcplan.ml.KernelPrincipalComponentsAnalysis.java

public static void main(final String[] args) throws FileNotFoundException {
    final File root = new File("test/KernelPrincipalComponentsAnalysis");
    root.mkdirs();/*from w w  w.j av a2s . c  o m*/
    final int seed = 42;
    final int N = 30;
    final RandomGenerator rng = new MersenneTwister(seed);
    final ArrayList<RealVector> data = new ArrayList<RealVector>();
    final ArrayList<RealVector> shuffled = new ArrayList<RealVector>();

    //      final double[][] covariance = new double[][] { {1.0, 0.0},
    //                                          {0.0, 1.0} };
    //      final MultivariateNormalDistribution p = new MultivariateNormalDistribution(
    //         rng, new double[] { 0.0, 0.0 }, covariance );
    //      final MultivariateNormalDistribution q = new MultivariateNormalDistribution(
    //         rng, new double[] { 10.0, 0.0 }, covariance );
    //
    //      for( int i = 0; i < N; ++i ) {
    //         data.add( new ArrayRealVector( p.sample() ) );
    //         data.add( new ArrayRealVector( q.sample() ) );
    //      }
    //      Fn.shuffle( rng, data );

    final double sigma = 0.01;
    final double[][] covariance = new double[][] { { sigma, 0.0 }, { 0.0, sigma } };
    final MultivariateNormalDistribution p = new MultivariateNormalDistribution(rng, new double[] { 0.0, 0.0 },
            covariance);

    for (final double r : new double[] { 1.0, 3.0, 5.0 }) {
        for (int i = 0; i < N; ++i) {
            final double theta = i * 2 * Math.PI / N;
            final double[] noise = p.sample();
            final RealVector v = new ArrayRealVector(
                    new double[] { r * Math.cos(theta) + noise[0], r * Math.sin(theta) + noise[1] });
            data.add(v);
            shuffled.add(v);
        }
    }
    Fn.shuffle(rng, shuffled);

    final Csv.Writer data_writer = new Csv.Writer(new PrintStream(new File(root, "data.csv")));
    for (final RealVector v : data) {
        for (int i = 0; i < v.getDimension(); ++i) {
            data_writer.cell(v.getEntry(i));
        }
        data_writer.newline();
    }
    data_writer.close();

    System.out.println("[Training]");
    final int Ncomponents = 2;
    final KernelPrincipalComponentsAnalysis<RealVector> kpca = new KernelPrincipalComponentsAnalysis<RealVector>(
            shuffled, new RadialBasisFunctionKernel(0.5), 1e-6);
    System.out.println("[Finished]");
    for (int i = 0; i < Ncomponents; ++i) {
        System.out.println(kpca.eigenvectors.get(i));
    }

    System.out.println("Transformed data:");
    final KernelPrincipalComponentsAnalysis.Transformer<RealVector> transformer = kpca
            .makeTransformer(Ncomponents);
    final Csv.Writer transformed_writer = new Csv.Writer(new PrintStream(new File(root, "transformed.csv")));
    for (final RealVector u : data) {
        final RealVector v = transformer.transform(u);
        System.out.println(v);
        for (int i = 0; i < v.getDimension(); ++i) {
            transformed_writer.cell(v.getEntry(i));
        }
        transformed_writer.newline();
    }
    transformed_writer.close();
}

From source file:Main.java

static int calculateRadius(int count, float length) {
    return (int) ((count + 1) * length / Math.PI);
}

From source file:Main.java

private static double rad(double _) {
    return _ * Math.PI / 180f;
}