Package ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.filters

Examples of ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.filters.Filter

39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
    @Override
    public void reconstructInplace(double[] data, int approxLength) {
        Assert.checkNotNull(data, "Data vector can`t be null.");

        Filter lowReconstructionFilter = filtersFactory.getLowReconstructionFilter();
        Filter highReconstructionFilter = filtersFactory.getHighReconstructionFilter();
       
//        while(approxLength <= data.length/2) {
            double[] approximation = new double[approxLength];
            System.arraycopy(data, 0, approximation, 0, approxLength);

            double[] extendedApproximation = new Extensioner(approximation)
                    .schedule(new CopyElementToBegin(0))
                    .schedule(new AddLastToEnd())
                    .execute();

            extendedApproximation = sampler.upsample(extendedApproximation);
            extendedApproximation = MathUtils.convolve(extendedApproximation, lowReconstructionFilter.getCoeff());
            extendedApproximation = windower.window(extendedApproximation, 2, approximation.length * 2 + 2);

            double[] details = new double[approxLength]; //must have same length with approximation
            System.arraycopy(data, approxLength, details, 0, approxLength);
            double[] extendedDetails = new Extensioner(details)
                    .schedule(new CopyElementToBegin(1))
                    .schedule(new AddLastToEnd())
                    .execute();

            extendedDetails = sampler.upsample(extendedDetails);
            extendedDetails = MathUtils.convolve(extendedDetails, highReconstructionFilter.getCoeff());
            extendedDetails = windower.window(extendedDetails, 4, details.length * 2 + 4);

            for (int index = 0; index < approxLength * 2; index++) {
              data[index] = extendedApproximation[index] + extendedDetails[index];
            }
View Full Code Here
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
     *
     * @param data vector with approximation and details.
     * @param endIndex index where details start and approximations ended.
     */
    private void decomposeInplace1Lvl(double[] data, int endIndex) {
        Filter lowDecompositionFilter  = filtersFactory.getLowDecompositionFilter();
        Filter highDecompositionFilter = filtersFactory.getHighDecompositionFilter();

        double[] approximation = new double[endIndex]; //working only with approximation coefficients
        System.arraycopy(data, 0, approximation, 0, endIndex);

        double[] temp = new Extensioner(approximation)
                .schedule(new MirrorExtension(1))
                .execute();

        //TODO ugly but need one more element...
        double[] extended = new double[temp.length + 1];
        System.arraycopy(temp, 0, extended, 0, temp.length);
        extended[extended.length - 1] = approximation[approximation.length - 3];

        /* Here in "extended" we have extended data to reduce boundary effect */

        temp = MathUtils.convolve(extended, lowDecompositionFilter.getCoeff());
        temp = sampler.downsample(temp);
        temp = windower.window(temp, 2, endIndex / 2 + 2);

        double[] temp2 = MathUtils.convolve(extended, highDecompositionFilter.getCoeff());
        temp2 = sampler.downsample(temp2);
        temp2 = windower.window(temp2, 1, endIndex / 2 + 1);

        System.arraycopy(temp, 0, data, 0, temp.length);
        System.arraycopy(temp2, 0, data, temp.length, temp2.length);
View Full Code Here
43
44
45
46
47
48
49
50
51
52
53
54
55
     * Test of decomposeLow method, of class CyclicWrappingTransformStrategy.
     */
    @Test
    public void testDecomposeLowWithFilterLength2() {
        double[] data = {11.1, 22.2, 33.3, 44.4, 55.5, 66.6};
        Filter lowDecompositionFilter = new Filter(new double[]{1, 1});
        double[] expResult = {55.5, 99.9, 77.7};
        decomposeLowWithAssert(data, lowDecompositionFilter, expResult);

        lowDecompositionFilter = new Filter(new double[]{15.54, 18.2});
        expResult = new double[]{921.521999999999, 1670.549999999999, 1384.613999999999};
        decomposeLowWithAssert(data, lowDecompositionFilter, expResult);
    }
View Full Code Here
64
65
66
67
68
69
70
71
72
73
     * Test of decomposeHigh method, of class CyclicWrappingTransformStrategy.
     */
    @Test
    public void testDecomposeHigh() {
        double[] data = {46.2000, 565.8000, 12.1200, 163.5670, 123.1230, 90.8700, 18.3400, 1};
        Filter highDecompositionFilter = new Filter(new double[]{1.12, 1.21, 2.123, 12.2, 14.1, 7.8, 4.7});
        double[] expResult = {8009.72259, 7188.673029, 4216.37072,1546.0581};

        decomposeHighWithAssert(data, highDecompositionFilter, expResult);
    }
View Full Code Here
84
85
86
87
88
89
90
91
92
93
94
95
    @Test
    public void testReconstructEvenVectorWithFilterLength2() {
        double[] approximation = {5, 9, 7};
        double[] details = {-1, -1, 5};

        Filter lowReconstructionFilter = new Filter(new double[]{1, 1});
        Filter highReconstructionFilter = new Filter(new double[]{1, -1});

        double[] expResult = {2, 4, 6, 8, 10, 12};
        double[] result = instance.reconstruct(approximation, details, lowReconstructionFilter, highReconstructionFilter);
        assertArrayEquals(expResult, result, 0);
View Full Code Here
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
    @Test
    public void testDecomposeReconstructForHaarFilters() {
        HaarFiltersFactory factory = new HaarFiltersFactory();
        double[] data = {20,10,15,12,14,18,40,32,14,14};
        Filter lowDec  = factory.getLowDecompositionFilter();
        Filter highDec = factory.getHighDecompositionFilter();

        double[] lowExpect = {17.6776695296636, 18.38477631085, 41.01219330881975,
                              32.52691193458118, 24.04163056034261};
        double[] low = decomposeLowWithAssert(data, lowDec, lowExpect);

        double[] highExpect = {-3.535533905932737, -1.41421356237309, -15.55634918610404,
                               12.72792206135785, -4.242640687119268};
        double[] high = decomposeLowWithAssert(data, highDec, highExpect);

        Filter lowRec = factory.getLowReconstructionFilter();
        Filter highRec = factory.getHighReconstructionFilter();
        double[] recon = instance.reconstruct(low, high, lowRec, highRec);
        assertArrayEquals(data, recon, DOBLE_COMPARISON_DELTA);

        data = new double[]{23.25, 12.23, 56.124, 76.34, 642.12, 4.1, 87.9};
        lowExpect = new double[]{48.333576921225, 508.027938011286, 65.053823869162, 16.440232662587};
View Full Code Here
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
     * Test of extend method, of class Extensioner.
     */
    @Test
    public void testExtendEnd() {
        double[] data = {1, 2, 3, 4};
        Filter filter = new Filter(new double[]{2, 8, 4, -1});

        double[] result = new Extensioner(data)
                .schedule(new CyclicEndExtension(filter.getLength()))
                .execute();
        double[] expected = {1, 2, 3, 4, 1, 2, 3, 4};
        assertEquals(expected.length, result.length);
        assertArrayEquals(expected, result, 0);

        data = new double[]{1, 2, 3};
        result = new Extensioner(data)
                .schedule(new ZeroPaddingToEven())
                .schedule(new CyclicEndExtension(filter.getLength()))
                .execute();
        expected = new double[]{1, 2, 3, 0, 1, 2, 3, 0};
        assertEquals(expected.length, result.length);
        assertArrayEquals(expected, result, 0);
    }
View Full Code Here
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
     * Test of extend method, of class Extensioner.
     */
    @Test
    public void testExtendBeginning() {
        double[] data = {1, 2, 3, 4};
        Filter filter = new Filter(new double[]{2, 8});

        double[] result = new Extensioner(data)
                .schedule(new CyclicBeginExtension(filter.getLength()))
                .execute();

        assertEquals(data.length + filter.getCoeff().length, result.length);

        double[] expected = {3, 4, 1, 2, 3, 4};

        assertArrayEquals(expected, result, 0);
    }
View Full Code Here
85
86
87
88
89
90
91
92
93
94
95
96
97
98
    }

    @Test
    public void testEndExtensionWhenFilterLongButDataSmall() {
        double[] data = {1, 2};
        Filter filter = new Filter(new double[]{1, 1, 1, 1, 1, 1, 1});

        double[] result = new Extensioner(data)
                .schedule(new CyclicEndExtension(filter.getLength()))
                .execute();

        double[] expected = {1, 2, 1, 2, 1, 2, 1, 2, 1};
        assertArrayEquals(expected, result, 0);
    }
View Full Code Here
98
99
100
101
102
103
104
105
106
107
108
109
110
111
    }

    @Test
    public void testBeginExtensionWhenFilterLongButDataSmall() {
        double[] data = {1, 2};
        Filter filter = new Filter(new double[]{1, 1, 1, 1, 1, 1, 1});

        double[] result = new Extensioner(data)
                .schedule(new CyclicBeginExtension(filter.getLength()))
                .execute();

        double[] expected = {2, 1, 2, 1, 2, 1, 2, 1, 2};
        assertArrayEquals(expected, result, 0);
    }
View Full Code Here
TOP

Related Classes of ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.filters.Filter

  • ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.transforms.legall.impl.LeGallWaveletTransform
  • ru.ifmo.diplom.kirilchuk.jawelet.dwt.transforms.strategies.impl.CyclicWrappingTransformStrategyTest
  • ru.ifmo.diplom.kirilchuk.jawelet.util.extensioner.ExtensionerTest
    • Copyright © 2018 www.massapicom. 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.