Examples of org.geotools.coverage.Category

org.geotools.coverage.Category
A category delimited by a range of sample values. A categogy may be either qualitative or quantitative. For exemple, a classified image may have a qualitative category defining sample value {@code 0}as water. An other qualitative category may defines sample value {@code 1}as forest, etc. An other image may define elevation data as sample values in the range {@code [0..100]}. The later is a quantitative category, because sample values are related to some measurement in the real world. For example, elevation data may be related to an altitude in metres through the following linear relation: altitude = sample value×100. Some image mixes both qualitative and quantitative categories. For example, images of Sea Surface Temperature (SST) may have a quantitative category for temperature with values ranging from 2 to 35°C, and three qualitative categories for cloud, land and ice.
All categories must have a human readable name. In addition, quantitative categories may define a transformation between sample values s and geophysics values x. This transformation is usually (but not always) a linear equation of the form:
x = {@linkplain GridSampleDimension#getOffset() offset} + {@linkplain GridSampleDimension#getScale() scale}×s
More general equation are allowed. For example, SeaWiFS images use a logarithmic transform. General transformations are expressed with a {@link MathTransform1D} object. In the special case where the transformationis a linear one (as in the formula above), then a {@code Category} objectmay be understood as the interval between two breakpoints in the JAI's {@linkplain javax.media.jai.operator.PiecewiseDescriptor piecewise} operation.
All {@code Category} objects are immutable and thread-safe. @since 2.1 @source $URL$ @version $Id$ @author Martin Desruisseaux (IRD) @see GridSampleDimension @see javax.media.jai.operator.PiecewiseDescriptor

                categoryXS[i] = categoryArray[indexOfQuantitative];
            }
            if (categoryArray == null) {
                continue;
            }
            final Category oldCategory = categoryArray[indexOfQuantitative];
            final Unit<?>  oldUnit     = sampleDim.getUnits();
            final Category newCategory = deriveCategory(categoryXS, parameters);
            final Unit<?>  newUnit     = deriveUnit(unitXS, parameters);
            if (newCategory == null) {
                return null;
            }
            if (!oldCategory.equals(newCategory) || !Utilities.equals(oldUnit, newUnit)) {

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            }
            ranges[i] = categories[i].getRange();
        }
        final NumberRange range = deriveRange(ranges, parameters);
        if (range != null) {
            final Category category = categories[PRIMARY_SOURCE_INDEX];
            return new Category(category.getName(), category.getColors(),
                                category.geophysics(false).getRange(), range).geophysics(true);
        }
        return null;
    }

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        final BufferedImage      image;  // The GridCoverage's data.
        final WritableRaster    raster;  // The image's data as a raster.
        final Rectangle2D       bounds;  // The GridCoverage's envelope.
        final GridSampleDimension band;  // The only image's band.
        band = new GridSampleDimension("Temperature", new Category[] {
            new Category("No data",     null, 0),
            new Category("Land",        null, 1),
            new Category("Cloud",       null, 2),
            new Category("Temperature", null, BEGIN_VALID, 256, SCALE, OFFSET)
        }, CELSIUS);
        image  = new BufferedImage(120, 80, BufferedImage.TYPE_BYTE_INDEXED);
        raster = image.getRaster();
        for (int i=raster.getWidth(); --i>=0;) {
            for (int j=raster.getHeight(); --j>=0;) {

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        // no data management
        final GridSampleDimension sd = (GridSampleDimension) gc.getSampleDimension(0);
        final List<Category> categories = sd.getCategories();
        double inNoData = Double.NaN;
        if (categories != null) {
            Category candidate;
            final String noDataName = Vocabulary.format(VocabularyKeys.NODATA);
            for (Category category : categories) {
                candidate = category;
                final String name = candidate.getName().toString();
                if (name.equalsIgnoreCase("No Data") || name.equalsIgnoreCase(noDataName)) {
                    inNoData = candidate.getRange().getMaximum();
                    break;
                }
            }
        }
        return inNoData;

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    } catch (ParseException ex1) {
      uom = null;
    }


    
    final Category nan =
        new Category(Vocabulary.format(VocabularyKeys.NODATA), new Color[] { new Color(0, 0, 0, 0) },
        NumberRange.create(0, 0), NumberRange.create((short) -9999,
            (short) -9999));
    final GridSampleDimension band = new GridSampleDimension(
        "digital-elevation", new Category[] { nan }, uom);

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        final ColorModel cm = image.getColorModel();
        final int numBands = sm.getNumBands();
        final GridSampleDimension[] bands = new GridSampleDimension[numBands];
        // setting bands names.


        Category noDataCategory = null;
        final Map<String, Double> properties = new HashMap<String, Double>();        
        if (!Double.isNaN(noData)) {
            noDataCategory = new Category(
                    Vocabulary.formatInternational(VocabularyKeys.NODATA),
                    new Color[] { new Color(0, 0, 0, 0) }, NumberRange.create(
                            noData, noData), NumberRange.create(noData, noData));
            properties.put("GC_NODATA", new Double(noData));
        }

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        final double offset,
        final Unit<?> unit ) {
      super(
          description,
          !Double.isNaN(nodata) ? new Category[] {
            new Category(
                Vocabulary.formatInternational(VocabularyKeys.NODATA),
                new Color[] {
                  new Color(
                      0,
                      0,
                      0,
                      0)
                },
                NumberRange.create(
                    nodata,
                    nodata),
                NumberRange.create(
                    nodata,
                    nodata))
          } : null,
          unit);
      this.nodata = nodata;
      this.minimum = minimum;
      this.maximum = maximum;
      this.scale = scale;
      this.offset = offset;
      this.unit = unit;
      this.type = type;
      this.color = color;
      bkg = new Category(
          "Background",
          TRANSPARENT,
          0);
    }

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            boolean nodataConfigured = configuredNoDataValues != null
                    && configuredNoDataValues.length > 0;
            // custom categories
            if (categories != null) {
                this.customCategories = new ArrayList<Category>(categories.size());
                Category wrapped = null;
                for (Category category : categories) {
                    wrapped = category;
                    if (Category.NODATA.getName().equals(category.getName())) {
                        if (category.isQuantitative()) {
                            // Get minimum and maximum value
                            double minimum = nodataConfigured ? configuredNoDataValues[0]
                                    : category.getRange().getMinimum();
                            double maximum = nodataConfigured ? configuredNoDataValues[0]
                                    : category.getRange().getMaximum();
                            if (Double.isNaN(minimum) && Double.isNaN(maximum)) {
                                // Create a qualitative category
                                wrapped = new Category(Category.NODATA.getName(),
                                        category.getColors()[0], minimum);
                            } else {
                                // Create the wrapped category
                                wrapped = new Category(Category.NODATA.getName(),
                                        category.getColors(), NumberRange.create(minimum, maximum),
                                        category.getSampleToGeophysics());
                            }
                        }
                    }

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        nullValues.add(noData2);
        coverageDim.setNullValues(nullValues);


        // Qualitative nodata category
        GridSampleDimension sampleDim = new GridSampleDimension("original",
                new Category[] { new Category(
                        Vocabulary.formatInternational(VocabularyKeys.NODATA),
                        new Color(0, 0, 0, 0), 0) }, null);


        // Wrap the dimension
        GridSampleDimension wrappedDim = new WrappedSampleDimension(sampleDim, coverageDim);


        // Ensure nodata are correct
        double[] noData = wrappedDim.getNoDataValues();
        assertEquals(2, noData.length);
        assertEquals(noData1, noData[0], DELTA);
        assertEquals(noData2, noData[1], DELTA);


        // Extract categories
        List<Category> categories = wrappedDim.getCategories();


        // Ensure NoData Category is present
        Category category = categories.get(0);
        assertTrue(category.getName().equals(Category.NODATA.getName()));


        // Check that it does not contain sampleToGeophisics and that the Range contains only NaN
        assertNull(category.getSampleToGeophysics());
        assertEquals(category.geophysics(true).getRange().getMinimum(), Double.NaN, DELTA);
        assertEquals(category.geophysics(true).getRange().getMaximum(), Double.NaN, DELTA);


        // Quantitative nodata category
        sampleDim = new GridSampleDimension("original", new Category[] { new Category(
                Vocabulary.formatInternational(VocabularyKeys.NODATA), new Color[] { new Color(0,
                        0, 0, 0) }, NumberRange.create(-9999, -9999), NumberRange.create(-9999,
                        -9999)) }, null);


        // Wrap the dimension
        wrappedDim = new WrappedSampleDimension(sampleDim, coverageDim);


        // Ensure nodata are correct
        noData = wrappedDim.getNoDataValues();
        assertEquals(2, noData.length);
        assertEquals(noData1, noData[0], DELTA);
        assertEquals(noData2, noData[1], DELTA);


        // Extract categories
        categories = wrappedDim.getCategories();


        // Ensure NoData Category is present
        category = categories.get(0);
        assertTrue(category.getName().equals(Category.NODATA.getName()));


        // Check if it contains sampleToGeophisics and the Range contains the first nodata defined
        assertNotNull(category.getSampleToGeophysics());
        assertEquals(category.geophysics(true).getRange().getMinimum(), noData1, DELTA);
        assertEquals(category.geophysics(true).getRange().getMaximum(), noData1, DELTA);
    }

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            final List<Category> categories = sd[i].getCategories();
            if (categories != null && categories.size() >= 1) {
        writer.write("<nullValues>\n");
        for (Iterator<Category> it = sd[i].getCategories().iterator(); it
            .hasNext();) {
          Category cat = (Category) it.next();
          if ((cat != null)
              && cat.getName().toString().equalsIgnoreCase(
                  "no data")) {
            double min = cat.getRange().getMinimum();
            double max = cat.getRange().getMaximum();
            writer.write("<value>" + min + "</value>\n");
            if (min != max)
              writer.write("<value>" + max + "</value>\n");
          }
        }

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