Examples of ucar.nc2.dataset.NetcdfDataset

ucar.nc2.dataset.NetcdfDataset
NetcdfDataset extends the netCDF API, adding standard attribute parsing such as scale and offset, and explicit support for Coordinate Systems. A NetcdfDataset wraps a NetcdfFile, or is defined by an NcML document.

Be sure to close the dataset when done, best practice is to enclose in a try/finally block:
```
 NetcdfDataset ncd = null; try { ncd = NetcdfDataset.openDataset(fileName); ... } finally { ncd.close(); } 
```
By default NetcdfDataset is opened with all enhancements turned on. The default "enhance mode" can be set through setDefaultEnhanceMode(). One can also explicitly set the enhancements you want in the dataset factory methods. The enhancements are:
- ScaleMissing : process scale/offset/missing attributes, and automatically convert the data.
- ScaleMissingDefer : process scale/offset/missing attributes, but dont automatically convert the data. You can call VariableEnhanced.convertScaleOffsetMissing() on the data manually.
- CoordSystem : extract CoordinateSystem using the CoordSysBuilder plug-in mechanism
- ConvertEnums : automaticlly convert enum values to their corresponding Strings. If you want to do this manually, you can call Variable.lookupEnumString() manually.
Automatic ScaleMissing processing has some overhead, and if you need maximum performance, but still want to use scale/offset/missing value handling, open the NetcdfDataset with ScaleMissingDefer. The VariableDS data type is not promoted, and the data is not converted on a read, but you can call the convertScaleOffsetMissing() routines which will do the conversion on a point-by-point basis. @author caron @see ucar.nc2.NetcdfFile

        if (!isCollection) { // open up atomic dataset for info
          log.info("Opening dataset to get global attributes");
          //--- if not a dataset collection then 
          //--- open and check global attributes for metadata conventions
          try {
            NetcdfDataset ncD = NetcdfDataset.openDataset("thredds:"+ds.getCatalogUrl());
            Attribute mdCon = ncD.findGlobalAttributeIgnoreCase("metadata_conventions");
            if (mdCon != null) {
              List<Attribute> ga = ncD.getGlobalAttributes(); 
              for (Attribute att : ga ) {
                                if(log.isDebugEnabled()) log.debug("Attribute found "+att.toString());
                //--- TODO: Attach the attributes to the metadata node
                //--- for conversion into the ISO record by an xslt
              }
            } else {
                            if(log.isDebugEnabled()) log.debug("No global attribute with metadata conventions found");
            }
            ncD.close();
          } catch (Exception e) {
            log.info("Exception raised in netcdfDataset ops: "+e);
            e.printStackTrace();
          }
        }

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    @Override
    public GridGeometry[] getGridGeometries() throws IOException {
        if (geometries == null) {
            List<CoordinateSystem> systems = null;
            if (file instanceof NetcdfDataset) {
                final NetcdfDataset ds = (NetcdfDataset) file;
                final EnumSet<NetcdfDataset.Enhance> mode = EnumSet.copyOf(ds.getEnhanceMode());
                if (mode.add(NetcdfDataset.Enhance.CoordSystems)) {
                    ds.enhance(mode);
                }
                systems = ds.getCoordinateSystems();
            }
            geometries = new GridGeometry[(systems != null) ? systems.size() : 0];
            for (int i=0; i<geometries.length; i++) {
                geometries[i] = new GridGeometryWrapper(systems.get(i));
            }

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     * @param  name The file name as one of the above-cited constants.
     * @return The decoder for the given name.
     * @throws IOException If an error occurred while opening the file.
     */
    protected Decoder createDecoder(final String name) throws IOException {
        return new DecoderWrapper(LISTENERS, new NetcdfDataset(open(name)));
    }

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     * @throws IOException Should never happen.
     */
    @Test
    public void testUCAR() throws IOException {
        final Metadata metadata;
        final Decoder input = new DecoderWrapper(TestCase.LISTENERS, new NetcdfDataset(open(NCEP)));
        try {
            metadata = new MetadataReader(input).read();
        } finally {
            input.close();
        }

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     * @param input the input object.
     * @return the dataset or <code>null</code>.
     * @throws IOException
     */
    private NetcdfDataset extractDataset( Object input ) throws IOException {
        NetcdfDataset dataset = null;
        if (input instanceof URIImageInputStream) {
            URIImageInputStream uriInStream = (URIImageInputStream) input;
            dataset = NetcdfDataset.acquireDataset(uriInStream.getUri().toString(), null);
        }
        if (input instanceof URL) {

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        }
        if (source instanceof URIImageInputStream) {
            URIImageInputStream uriInStream = (URIImageInputStream) source;
            try {
                // TODO perhaps it would be better to not make an online check. Might be slowing down.
                NetcdfDataset openDataset = NetcdfDataset.acquireDataset(uriInStream.getUri().toString(), null);
                openDataset.close();
                return true;
            } catch (IOException e) {
                return false;
            }
        }

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    @Test
    public void polyphemus() throws Exception {


        // acquire dataset
        final NetcdfDataset dataset = NetcdfDataset.openDataset(TestData.url(this, "O3-NO2.nc")
                .toExternalForm());
        assertNotNull(dataset);
        final List<CoordinateAxis> cvs = dataset.getCoordinateAxes();
        assertNotNull(cvs);
        assertSame(4, cvs.size());


        //
        // cloud_formations is short
        //
        Dimension dim = dataset.findDimension("time");
        assertNotNull(dim);
        assertEquals("time", dim.getShortName());


        // check type
        CoordinateAxis coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        Class<?> binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Date.class, binding);
        CoordinateVariable<?> cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertSame(Date.class, cv.getType());


        List<?> list = cv.read();
        assertNotNull(list);
        assertEquals(2, list.size());


        final GregorianCalendar cal = new GregorianCalendar(NetCDFTimeUtilities.UTC_TIMEZONE);
        cal.set(2012, 3, 1, 0, 0, 0);
        cal.set(GregorianCalendar.MILLISECOND, 0);
        assertEquals(cal.getTime(), cv.getMinimum());
        assertEquals(list.get(0), cv.getMinimum());


        cal.set(2012, 3, 1, 1, 0, 0);
        assertEquals(cal.getTime(), cv.getMaximum());
        assertEquals(list.get(1), cv.getMaximum());
        assertEquals(2, cv.getSize());
        assertEquals("hours since 2012-04-01 0:00:00", cv.getUnit());
        CoordinateReferenceSystem crs = cv.getCoordinateReferenceSystem();
        assertNotNull(crs);
        assertTrue(crs instanceof TemporalCRS);
        //
        // lat is float
        //
        dim = dataset.findDimension("z");
        assertNotNull(dim);
        assertEquals("z", dim.getShortName());


        // check type
        coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Float.class, binding);


        cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        list = cv.read();
        assertNotNull(list);
        assertEquals(2, list.size());


        assertSame(Float.class, cv.getType());
        assertEquals(10f, cv.getMinimum());
        assertEquals(450f, cv.getMaximum());
        assertEquals(list.get(0), cv.getMinimum());
        assertEquals(list.get(1), cv.getMaximum());
        assertEquals(2, cv.getSize());
        assertEquals("meters", cv.getUnit());


        crs = cv.getCoordinateReferenceSystem();
        assertNotNull(crs);
        assertTrue(crs instanceof VerticalCRS);


        dataset.close();


    }

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        //
        // IASI does not have time or runtime, it only contains double variables besides lat e long
        //


        // acquire dataset
        final NetcdfDataset dataset = NetcdfDataset.openDataset(TestData.url(this,
                "IASI_C_EUMP_20121120062959_31590_eps_o_l2.nc").toExternalForm());
        assertNotNull(dataset);
        final List<CoordinateAxis> cvs = dataset.getCoordinateAxes();
        assertNotNull(cvs);
        assertSame(8, cvs.size());


        //
        // cloud_formations is short
        //
        Dimension dim = dataset.findDimension("cloud_formations");
        assertNotNull(dim);
        assertEquals("cloud_formations", dim.getShortName());


        // check type
        CoordinateAxis coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        Class<?> binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Short.class, binding);
        CoordinateVariable<?> cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertSame(Short.class, cv.getType());
        assertEquals((short) 0, cv.getMinimum());
        assertEquals((short) 2, cv.getMaximum());
        assertEquals(3, cv.getSize());
        assertEquals("level", cv.getUnit());


        //
        // lat is float
        //
        dim = dataset.findDimension("lat");
        assertNotNull(dim);
        assertEquals("lat", dim.getShortName());


        // check type
        coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Float.class, binding);
        cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertNotNull(cv);
        assertSame(Float.class, cv.getType());
        assertEquals(-77.327934f, cv.getMinimum());
        assertEquals(89.781555f, cv.getMaximum());
        assertEquals(766, cv.getSize());
        assertEquals("degrees_north", cv.getUnit());
        assertTrue(cv.isRegular());
        assertEquals(cv.getMinimum(), cv.getStart());
        assertEquals(0.2184437770469516, cv.getIncrement());


        //
        // lon is float
        //
        dim = dataset.findDimension("lon");
        assertNotNull(dim);
        assertEquals("lon", dim.getShortName());


        // check type
        coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Float.class, binding);
        cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertNotNull(cv);
        assertEquals("degrees_east", cv.getUnit());


        //
        // pressure_levels_ozone is Double
        //
        dim = dataset.findDimension("nlo");
        assertNotNull(dim);
        assertEquals("nlo", dim.getShortName());


        // check type
        coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Double.class, binding);
        cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertNotNull(cv);
        assertEquals("Pa", cv.getUnit());


        //
        // pressure_levels_ozone is Double
        //
        dim = dataset.findDimension("nlt");
        assertNotNull(dim);
        assertEquals("nlt", dim.getShortName());


        // check type
        coordinateAxis = dataset.findCoordinateAxis(dim.getShortName());
        assertNotNull(coordinateAxis);
        assertTrue(coordinateAxis instanceof CoordinateAxis1D);
        binding = CoordinateVariable.suggestBinding((CoordinateAxis1D) coordinateAxis);
        assertNotNull(binding);
        assertSame(Double.class, binding);
        cv = CoordinateVariable.create((CoordinateAxis1D) coordinateAxis);
        assertNotNull(cv);
        assertEquals("Pa", cv.getUnit());


        dataset.close();


    }

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     *                 if some error occur while opening the dataset.
     * @throws {@link IllegalArgumentException}
     *                 in case the specified input is a directory
     */
    public static NetcdfDataset getDataset(Object input) throws IOException {
        NetcdfDataset dataset = null;
        if (input instanceof File) {
          final File file= (File) input;
            if (!file.isDirectory())
                dataset = NetcdfDataset.acquireDataset(file.getPath(), null);
            else

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    }


    @Test
    public void testNoValid2DVariable() throws Exception {
        final File file = TestData.file(this, "noVars.nc");
        NetcdfDataset dataset = NetcdfDataset.acquireDataset(file.getAbsolutePath(), null);
        List<Variable> variables = dataset.getVariables();
        boolean speedVariableIsPresent = false;
        String speedVariableName = "";


        for (Variable variable : variables) {
            if (variable.getShortName().equals("spd")) {
                speedVariableIsPresent = true;
                speedVariableName = variable.getFullName();
                break;
            }
        }


        assertTrue(speedVariableIsPresent);


        final NetCDFImageReaderSpi unidataImageReaderSpi = new NetCDFImageReaderSpi();
        assertTrue(unidataImageReaderSpi.canDecodeInput(file));
        NetCDFImageReader reader = null;
        try {


            // sample dataset containing a water_speed variable having
            // only time, depth dimensions. No lon/lat dims are present
            // resulting into variable not usable.
            reader = (NetCDFImageReader) unidataImageReaderSpi.createReaderInstance();
            reader.setInput(file);
            final List<Name> names = reader.getCoveragesNames();


            boolean isSpeedCoverageAvailable = false;
            for (Name name : names) {
                if (name.toString().equals(speedVariableName)) {
                    isSpeedCoverageAvailable = true;
                    break;
                }
            }
            // Checking that only "mask" variable is found
            assertFalse(isSpeedCoverageAvailable);
        } finally {
            if (dataset != null) {
                dataset.close();
            }


            if (reader != null) {
                try {
                    reader.dispose();

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