Examples of Quantizer

jj2000.j2k.quantization.quantizer.Quantizer
This abstract class provides the general interface for quantizers. The input of a quantizer is the output of a wavelet transform. The output of the quantizer is the set of quantized wavelet coefficients represented in sign-magnitude notation (see below).
This class provides default implementation for most of the methods (wherever it makes sense), under the assumption that the image, component dimensions, and the tiles, are not modifed by the quantizer. If it is not the case for a particular implementation, then the methods should be overriden.

Sign magnitude representation is used (instead of two's complement) for the output data. The most significant bit is used for the sign (0 if positive, 1 if negative). Then the magnitude of the quantized coefficient is stored in the next M most significat bits. The rest of the bits (least significant bits) can contain a fractional value of the quantized coefficient. This fractional value is not to be coded by the entropy coder. However, it can be used to compute rate-distortion measures with greater precision.

The value of M is determined for each subband as the sum of the number of guard bits G and the nominal range of quantized wavelet coefficients in the corresponding subband (Rq), minus 1:

M = G + Rq -1

The value of G should be the same for all subbands. The value of Rq depends on the quantization step size, the nominal range of the component before the wavelet transform and the analysis gain of the subband (see Subband).

The blocks of data that are requested should not cross subband boundaries.

NOTE: At the moment only quantizers that implement the 'CBlkQuantDataSrcEnc' interface are supported.
@see Subband
org.geotools.image.palette.Quantizer
Analyzes a {@link RenderedImage} contents (using a Median Cut style algorithm) and builds anoptimal RGBA {@link ColorIndexer} that can be used to turn the RGBA image into a paletted one.
org.grouplens.lenskit.transform.quantize.Quantizer
uplens.org">GroupLens Research
org.wiigee.logic.Quantizer
This class implements a quantization component. In this case a k-mean-algorithm is used. In this case the initial values of the algorithm are ordered as two intersected circles, representing an abstract globe with k=14 elements. As a special feature the radius of this globe would be calculated dynamically before the training of this component. @author Benjamin 'BePo' Poppinga
ptolemy.actor.lib.Quantizer

Produce an output token on each firing with a value that is a quantized version of the input. The input and output types are both double.

The levels parameter contains an array of doubles specifying the quantization levels. The elements must be in an increasing order, or an exception will be thrown. The default value of levels is {-1.0, 1.0}.

Suppose u is the input, and levels = {a, b, c}, where a < b < c, then the output of the actor will be:

y = a, for u <= (b+a)/2;
y = b, for (b+a)/2 <

u <= (c+b)/2;

y = c, for u > (c+b)/2;

Thus, for the default levels, the output is (almost) the signum function of the input, or +1.0 if the input is positive, and -1.0 otherwise. This is almost the signum function because it outputs -1.0 if the input is zero.
This actor does not require that the quantization intervals be equal, i.e. we allow that (c-b) != (b-a).
@author Jie Liu @version $Id: Quantizer.java,v 1.45 2007/03/26 03:45:06 celaine Exp $ @since Ptolemy II 0.3 @Pt.ProposedRating Yellow (liuj) @Pt.AcceptedRating Yellow (yuhong)

Examples of jj2000.j2k.quantization.quantizer.Quantizer


        // Creates ForwardWT (forward wavelet transform)
        ForwardWT dwt = ForwardWT.createInstance(converter, j2kwparam);


        // Creates Quantizer
        Quantizer quant = Quantizer.createInstance(dwt,j2kwparam);


        // Creates ROIScaler
        ROIScaler rois = ROIScaler.createInstance(quant, j2kwparam);


        // Creates EntropyCoder

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Examples of org.geotools.image.palette.Quantizer

                // user provided palette?
                if (mapContent.getPalette() != null) {
                    indexer = new CachingColorIndexer(new LRUColorIndexer(icm, 1024));
                } else if (palettedFormatName.equalsIgnoreCase(format)) {
                    // build the palette and grab the optimized color indexer
                    indexer = new Quantizer(256).subsample().buildColorIndexer(image);
                }


                // if we have an indexer transform the image
                if (indexer != null) {
                    image = ColorIndexerDescriptor.create(image, indexer, null);

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Examples of org.geotools.image.palette.Quantizer

        if (!(canvas.getColorModel() instanceof IndexColorModel)) {
            // try to force a RGBA setup
            ImageWorker imageWorker = new ImageWorker(canvas);
            RenderedImage image = imageWorker.rescaleToBytes().forceComponentColorModel()
                    .getRenderedImage();
            ColorIndexer indexer = new Quantizer(256).subsample().buildColorIndexer(image);


            // if we have an indexer transform the image
            if (indexer != null) {
                image = ColorIndexerDescriptor.create(image, indexer, null);
            }

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Examples of org.grouplens.lenskit.transform.quantize.Quantizer

        SparseVector predictions = user.getPredictions();
        if (predictions == null) {
            return null;
        }


        Quantizer q = context.quantizer;


        // TODO Re-use accumulators
        MutualInformationAccumulator accum = new MutualInformationAccumulator(q.getCount());


        for (Pair<VectorEntry,VectorEntry> e: Vectors.fastIntersect(ratings, predictions)) {
            accum.count(q.index(e.getLeft().getValue()),
                        q.index(e.getRight().getValue()));
        }


        if (accum.getCount() > 0) {
            double ratingEntropy = accum.getV1Entropy();
            double predEntropy = accum.getV2Entropy();

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Examples of org.grouplens.lenskit.transform.quantize.Quantizer

 * @author <a href="http://www.grouplens.org">GroupLens Research</a>
 */
public class ValueArrayQuantizerTest {
    @Test
    public void testFindSingle() {
        Quantizer q = new ValueArrayQuantizer(new double[]{5.0});
        assertThat(q.getCount(), equalTo(1));
        assertThat(q.getIndexValue(0), equalTo(5.0));
        assertThat(q.index(2.5), equalTo(0));
        assertThat(q.index(5.0), equalTo(0));
    }

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Examples of org.grouplens.lenskit.transform.quantize.Quantizer

        assertThat(q.index(5.0), equalTo(0));
    }


    @Test
    public void testSomeElements() {
        Quantizer q = new ValueArrayQuantizer(new double[]{1.0, 2.0, 3.0, 4.0, 5.0});
        assertThat(q.getCount(), equalTo(5));
        assertThat(q.getIndexValue(0), equalTo(1.0));
        assertThat(q.index(2.5), equalTo(2));
        assertThat(q.index(5.0), equalTo(4));
        assertThat(q.index(1.73), equalTo(1));
    }

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Examples of org.wiigee.logic.Quantizer

      // initialize file and get values
      BufferedWriter out = new BufferedWriter(new FileWriter(name+".txt"));
      int numStates = m.getNumStates();
      int numObservations = m.getNumObservations();
      double defaultProbability = m.getDefaultProbability();
      Quantizer quantizer = m.getQuantizer();
      HMM hmm = m.getHMM();
      
      out.write("# numStates:");
      out.newLine();
      out.write(Integer.toString(numStates));
      out.newLine();
      
      out.write("# numObservations:");
      out.newLine();
      out.write(Integer.toString(numObservations));
      out.newLine();
      
      out.write("# defaultProbability:");
      out.newLine();
      out.write(Double.toString(defaultProbability));
      out.newLine();
      
      out.write("# Quantizer: Radius");
      out.newLine();
      out.write(Double.toString(quantizer.getRadius()));
      out.newLine();
      out.write("# Quantizer: MAP");
      out.newLine();
      double[][] map = quantizer.getHashMap();
      for(int v=0; v<map.length; v++) {
        double[] d = map[v];
        out.write(Double.toString(d[0])+", "+Double.toString(d[1])+", "+Double.toString(d[2]));
        out.newLine();
      }

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Examples of org.wiigee.logic.Quantizer

      }
      
      GestureModel ret = new GestureModel();
      ret.setDefaultProbability(defaultprobability);
      
      Quantizer quantizer = new Quantizer(numStates);
      quantizer.setUpManually(map, radius);
      ret.setQuantizer(quantizer);
      
      HMM hmm = new HMM(numStates, numObservations);
      hmm.setPi(pi);
      hmm.setA(a);

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Examples of ptolemy.actor.lib.Quantizer

        delay.delay.setToken(new DoubleToken(0.02));


        FIR fir = new FIR(this, "fir");
        fir.taps.setExpression("{0.7, 0.3}");


        Quantizer quan = new Quantizer(this, "Quantizer");
        Average accumulator = new Average(this, "accumulator");
        Sampler sampler = new Sampler(this, "sampler");
        Clock clk = new Clock(this, "ADClock");
        clk.offsets.setExpression("{0.0}");
        clk.period.setToken(new DoubleToken(1.0));

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