Examples of UniformRealDistribution

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

65
66
67
68
69
70
71
72
        final RandomGenerator rng = new Well44497b(seed);
        slope = a;
        intercept = b;
        error = new NormalDistribution(rng, 0, sigma,
                                       NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        x = new UniformRealDistribution(rng, lo, hi,
                                        UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

58
59
60
61
62
63
64
65
        this.radius = radius;
        cX = new NormalDistribution(rng, x, xSigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        cY = new NormalDistribution(rng, y, ySigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI,
                                         UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
            = new BicubicSplineInterpolatingFunction(xval, yval, zval,
                                                     dZdX, dZdY, dZdXdY);
        double x, y;

        final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed.
        final UniformRealDistribution distX
            = new UniformRealDistribution(rng, xval[0], xval[xval.length - 1]);
        final UniformRealDistribution distY
            = new UniformRealDistribution(rng, yval[0], yval[yval.length - 1]);

        final int numSamples = 50;
        final double tol = 6;
        for (int i = 0; i < numSamples; i++) {
            x = distX.sample();
            for (int j = 0; j < numSamples; j++) {
                y = distY.sample();
//                 System.out.println(x + " " + y + " " + f.value(x, y) + " " + bcf.value(x, y));
                Assert.assertEquals(f.value(x, y),  bcf.value(x, y), tol);
            }
//             System.out.println();
        }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
        BivariateFunction bcf = new BicubicSplineInterpolatingFunction(xval, yval, zval,
                                                                       dZdX, dZdY, dZdXdY);
        double x, y;

        final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed.
        final UniformRealDistribution distX
            = new UniformRealDistribution(rng, xval[0], xval[xval.length - 1]);
        final UniformRealDistribution distY
            = new UniformRealDistribution(rng, yval[0], yval[yval.length - 1]);

        final double tol = 224;
        for (int i = 0; i < sz; i++) {
            x = distX.sample();
            for (int j = 0; j < sz; j++) {
                y = distY.sample();
//                 System.out.println(x + " " + y + " " + f.value(x, y) + " " + bcf.value(x, y));
                Assert.assertEquals(f.value(x, y),  bcf.value(x, y), tol);
            }
//             System.out.println();
        }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
        BivariateGridInterpolator interpolator = new PiecewiseBicubicSplineInterpolator();
        BivariateFunction p = interpolator.interpolate(xval, yval, zval);
        double x, y;

        final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed.
        final UniformRealDistribution distX = new UniformRealDistribution( rng, xval[0], xval[xval.length - 1] );
        final UniformRealDistribution distY = new UniformRealDistribution( rng, yval[0], yval[yval.length - 1] );

        final int numSamples = 50;
        final double tol = 2e-14;
        for ( int i = 0; i < numSamples; i++ )
        {
            x = distX.sample();
            for ( int j = 0; j < numSamples; j++ )
            {
                y = distY.sample();
//                 System.out.println(x + " " + y + " " + f.value(x, y) + " " + p.value(x, y));
                Assert.assertEquals(f.value(x, y),  p.value(x, y), tol);
            }
//             System.out.println();
        }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
        BivariateGridInterpolator interpolator = new PiecewiseBicubicSplineInterpolator();
        BivariateFunction p = interpolator.interpolate(xval, yval, zval);
        double x, y;

        final RandomGenerator rng = new Well19937c(1234567L); // "tol" depends on the seed.
        final UniformRealDistribution distX = new UniformRealDistribution( rng, xval[0], xval[xval.length - 1] );
        final UniformRealDistribution distY = new UniformRealDistribution( rng, yval[0], yval[yval.length - 1] );

        final int numSamples = 50;
        final double tol = 5e-13;
        for ( int i = 0; i < numSamples; i++ )
        {
            x = distX.sample();
            for ( int j = 0; j < numSamples; j++ )
            {
                y = distY.sample();
//                 System.out.println(x + " " + y + " " + f.value(x, y) + " " + p.value(x, y));
                Assert.assertEquals(f.value(x, y),  p.value(x, y), tol);
            }
//             System.out.println();
        }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
            actual = interpolation.value( currentX );
            assertTrue( Precision.equals( expected, actual ) );
        }

        final RandomGenerator rng = new Well19937c( 1234567L ); // "tol" depends on the seed.
        final UniformRealDistribution distX =
            new UniformRealDistribution( rng, xValues[0], xValues[xValues.length - 1] );

        double sumError = 0;
        for ( int i = 0; i < numberOfSamples; i++ )
        {
            currentX = distX.sample();
            expected = f.value( currentX );
            actual = interpolation.value( currentX );
            sumError += FastMath.abs( actual - expected );
            assertEquals( expected, actual, maxTolerance );
        }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

57
58
59
60
61
62
63
64
        this.radius = radius;
        cX = new NormalDistribution(rng, x, xSigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        cY = new NormalDistribution(rng, y, ySigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        tP = new UniformRealDistribution(rng, 0, MathUtils.TWO_PI,
                                         UniformRealDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
    }
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

96
97
98
99
100
101
102
103
104
105
106
107
        double[] permuted = new double[10];
        RandomDataGenerator random = new RandomDataGenerator();

        // Generate 10 distinct random values
        for (int i = 0; i < 10; i++) {
            final RealDistribution u = new UniformRealDistribution(i + 0.5, i + 0.75);
            original[i] = u.sample();
        }

        // Generate a random permutation, making sure it is not the identity
        boolean isIdentity = true;
        do {
View Full Code Here

Examples of org.apache.commons.math3.distribution.UniformRealDistribution

40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
*/
@Deprecated
public class PolynomialFitterTest {
    @Test
    public void testFit() {
        final RealDistribution rng = new UniformRealDistribution(-100, 100);
        rng.reseedRandomGenerator(64925784252L);

        final LevenbergMarquardtOptimizer optim = new LevenbergMarquardtOptimizer();
        final PolynomialFitter fitter = new PolynomialFitter(optim);
        final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
        final PolynomialFunction f = new PolynomialFunction(coeff);

        // Collect data from a known polynomial.
        for (int i = 0; i < 100; i++) {
            final double x = rng.sample();
            fitter.addObservedPoint(x, f.value(x));
        }

        // Start fit from initial guesses that are far from the optimal values.
        final double[] best = fitter.fit(new double[] { -1e-20, 3e15, -5e25 });
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.