| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| package org.apache.commons.math3.transform; |
| |
| import java.util.Arrays; |
| import java.util.Collection; |
| |
| import org.apache.commons.math3.analysis.UnivariateFunction; |
| import org.apache.commons.math3.analysis.function.Sin; |
| import org.apache.commons.math3.analysis.function.Sinc; |
| import org.apache.commons.math3.exception.MathIllegalStateException; |
| import org.apache.commons.math3.util.FastMath; |
| import org.junit.Assert; |
| import org.junit.Test; |
| import org.junit.runner.RunWith; |
| import org.junit.runners.Parameterized; |
| import org.junit.runners.Parameterized.Parameters; |
| |
| /** |
| * Test case for fast cosine transformer. |
| * <p> |
| * FCT algorithm is exact, the small tolerance number is used only to account |
| * for round-off errors. |
| * |
| */ |
| @RunWith(value = Parameterized.class) |
| public final class FastCosineTransformerTest |
| extends RealTransformerAbstractTest { |
| |
| private DctNormalization normalization; |
| |
| private final int[] invalidDataSize; |
| |
| private final double[] relativeTolerance; |
| |
| private final int[] validDataSize; |
| |
| public FastCosineTransformerTest(final DctNormalization normalization) { |
| this.normalization = normalization; |
| this.validDataSize = new int[] { |
| 2, 3, 5, 9, 17, 33, 65, 129 |
| }; |
| this.invalidDataSize = new int[] { |
| 128 |
| }; |
| this.relativeTolerance = new double[] { |
| 1E-15, 1E-15, 1E-14, 1E-13, 1E-13, 1E-12, 1E-11, 1E-10 |
| }; |
| } |
| |
| /** |
| * Returns an array containing {@code true, false} in order to check both |
| * standard and orthogonal DCTs. |
| * |
| * @return an array of parameters for this parameterized test |
| */ |
| @Parameters |
| public static Collection<Object[]> data() { |
| final DctNormalization[] normalization = DctNormalization.values(); |
| final Object[][] data = new DctNormalization[normalization.length][1]; |
| for (int i = 0; i < normalization.length; i++){ |
| data[i][0] = normalization[i]; |
| } |
| return Arrays.asList(data); |
| } |
| |
| @Override |
| RealTransformer createRealTransformer() { |
| return new FastCosineTransformer(normalization); |
| } |
| |
| @Override |
| int getInvalidDataSize(final int i) { |
| return invalidDataSize[i]; |
| } |
| |
| @Override |
| int getNumberOfInvalidDataSizes() { |
| return invalidDataSize.length; |
| } |
| |
| @Override |
| int getNumberOfValidDataSizes() { |
| return validDataSize.length; |
| } |
| |
| @Override |
| double getRelativeTolerance(final int i) { |
| return relativeTolerance[i]; |
| } |
| |
| @Override |
| int getValidDataSize(final int i) { |
| return validDataSize[i]; |
| } |
| |
| @Override |
| UnivariateFunction getValidFunction() { |
| return new Sinc(); |
| } |
| |
| @Override |
| double getValidLowerBound() { |
| return 0.0; |
| } |
| |
| @Override |
| double getValidUpperBound() { |
| return FastMath.PI; |
| } |
| |
| @Override |
| double[] transform(final double[] x, final TransformType type) { |
| final int n = x.length; |
| final double[] y = new double[n]; |
| final double[] cos = new double[2 * (n - 1)]; |
| for (int i = 0; i < cos.length; i++) { |
| cos[i] = FastMath.cos(FastMath.PI * i / (n - 1.0)); |
| } |
| int sgn = 1; |
| for (int j = 0; j < n; j++) { |
| double yj = 0.5 * (x[0] + sgn * x[n - 1]); |
| for (int i = 1; i < n - 1; i++) { |
| yj += x[i] * cos[(i * j) % cos.length]; |
| } |
| y[j] = yj; |
| sgn *= -1; |
| } |
| final double s; |
| if (type == TransformType.FORWARD) { |
| if (normalization == DctNormalization.STANDARD_DCT_I) { |
| s = 1.0; |
| } else if (normalization == DctNormalization.ORTHOGONAL_DCT_I) { |
| s = FastMath.sqrt(2.0 / (n - 1.0)); |
| } else { |
| throw new MathIllegalStateException(); |
| } |
| } else if (type == TransformType.INVERSE) { |
| if (normalization == DctNormalization.STANDARD_DCT_I) { |
| s = 2.0 / (n - 1.0); |
| } else if (normalization == DctNormalization.ORTHOGONAL_DCT_I) { |
| s = FastMath.sqrt(2.0 / (n - 1.0)); |
| } else { |
| throw new MathIllegalStateException(); |
| } |
| } else { |
| /* |
| * Should never occur. This clause is a safeguard in case other |
| * types are used to TransformType (which should not be done). |
| */ |
| throw new MathIllegalStateException(); |
| } |
| TransformUtils.scaleArray(y, s); |
| return y; |
| } |
| |
| /* |
| * Additional tests. |
| */ |
| |
| /** Test of transformer for the ad hoc data. */ |
| @Test |
| public void testAdHocData() { |
| FastCosineTransformer transformer; |
| transformer = new FastCosineTransformer(DctNormalization.STANDARD_DCT_I); |
| double result[], tolerance = 1E-12; |
| |
| double x[] = { |
| 0.0, 1.0, 4.0, 9.0, 16.0, 25.0, 36.0, 49.0, 64.0 |
| }; |
| double y[] = |
| { |
| 172.0, -105.096569476353, 27.3137084989848, -12.9593152353742, |
| 8.0, -5.78585076868676, 4.68629150101524, -4.15826451958632, |
| 4.0 |
| }; |
| |
| result = transformer.transform(x, TransformType.FORWARD); |
| for (int i = 0; i < result.length; i++) { |
| Assert.assertEquals(y[i], result[i], tolerance); |
| } |
| |
| result = transformer.transform(y, TransformType.INVERSE); |
| for (int i = 0; i < result.length; i++) { |
| Assert.assertEquals(x[i], result[i], tolerance); |
| } |
| |
| TransformUtils.scaleArray(x, FastMath.sqrt(0.5 * (x.length - 1))); |
| |
| transformer = new FastCosineTransformer(DctNormalization.ORTHOGONAL_DCT_I); |
| result = transformer.transform(y, TransformType.FORWARD); |
| for (int i = 0; i < result.length; i++) { |
| Assert.assertEquals(x[i], result[i], tolerance); |
| } |
| |
| result = transformer.transform(x, TransformType.INVERSE); |
| for (int i = 0; i < result.length; i++) { |
| Assert.assertEquals(y[i], result[i], tolerance); |
| } |
| } |
| |
| /** Test of parameters for the transformer. */ |
| @Test |
| public void testParameters() |
| throws Exception { |
| UnivariateFunction f = new Sin(); |
| FastCosineTransformer transformer; |
| transformer = new FastCosineTransformer(DctNormalization.STANDARD_DCT_I); |
| |
| try { |
| // bad interval |
| transformer.transform(f, 1, -1, 65, TransformType.FORWARD); |
| Assert.fail("Expecting IllegalArgumentException - bad interval"); |
| } catch (IllegalArgumentException ex) { |
| // expected |
| } |
| try { |
| // bad samples number |
| transformer.transform(f, -1, 1, 1, TransformType.FORWARD); |
| Assert |
| .fail("Expecting IllegalArgumentException - bad samples number"); |
| } catch (IllegalArgumentException ex) { |
| // expected |
| } |
| try { |
| // bad samples number |
| transformer.transform(f, -1, 1, 64, TransformType.FORWARD); |
| Assert |
| .fail("Expecting IllegalArgumentException - bad samples number"); |
| } catch (IllegalArgumentException ex) { |
| // expected |
| } |
| } |
| |
| /** Test of transformer for the sine function. */ |
| @Test |
| public void testSinFunction() { |
| UnivariateFunction f = new Sin(); |
| FastCosineTransformer transformer; |
| transformer = new FastCosineTransformer(DctNormalization.STANDARD_DCT_I); |
| double min, max, result[], tolerance = 1E-12; |
| int N = 9; |
| |
| double expected[] = |
| { |
| 0.0, 3.26197262739567, 0.0, -2.17958042710327, 0.0, |
| -0.648846697642915, 0.0, -0.433545502649478, 0.0 |
| }; |
| min = 0.0; |
| max = 2.0 * FastMath.PI * N / (N - 1); |
| result = transformer.transform(f, min, max, N, TransformType.FORWARD); |
| for (int i = 0; i < N; i++) { |
| Assert.assertEquals(expected[i], result[i], tolerance); |
| } |
| |
| min = -FastMath.PI; |
| max = FastMath.PI * (N + 1) / (N - 1); |
| result = transformer.transform(f, min, max, N, TransformType.FORWARD); |
| for (int i = 0; i < N; i++) { |
| Assert.assertEquals(-expected[i], result[i], tolerance); |
| } |
| } |
| } |