ncsa.hdf.object.fits
Class FitsDataset

java.lang.Object
  ncsa.hdf.object.HObject
      ncsa.hdf.object.Dataset
          ncsa.hdf.object.ScalarDS
              ncsa.hdf.object.fits.FitsDataset

All Implemented Interfaces:

java.io.Serializable, DataFormat

public class FitsDataset
extends ScalarDS

FitsDataset describes an multi-dimension array of HDF5 scalar or atomic data types, such as byte, int, short, long, float, double and string, and operations performed on the scalar dataset

The library predefines a modest number of datatypes. For details, read The Datatype Interface (H5T)

Version:

1.1 9/4/2007

Author:

Peter X. Cao

See Also:

Serialized Form

Field Summary

static long

serialVersionUID

Fields inherited from class ncsa.hdf.object.ScalarDS

INTERLACE_LINE, INTERLACE_PIXEL, INTERLACE_PLANE, isFillValueConverted

Fields inherited from class ncsa.hdf.object.HObject

separator

Constructor Summary

FitsDataset(FileFormat fileFormat, nom.tam.fits.BasicHDU hdu, java.lang.String dName, long[] oid)
Constructs an FitsDataset object with specific netcdf variable.

Method Summary

void	close(int did) Closes access to the object.
Dataset	copy(Group pgroup, java.lang.String dstName, long[] dims, java.lang.Object buff) Creates a new dataset and writes the data buffer to the new dataset.
static FitsDataset	create(java.lang.String name, Group pgroup, Datatype type, long[] dims, long[] maxdims, long[] chunks, int gzip, java.lang.Object data) Creates a new dataset.
Datatype	getDatatype() Returns the datatype object of the dataset.
java.util.List	getMetadata() Retrieves the metadata such as attributes from file.
java.util.List	getMetadata(int... attrPropList)
byte[][]	getPalette() Returns the palette of this scalar dataset or null if palette does not exist.
byte[]	getPaletteRefs() Returns the byte array of palette refs.
boolean	hasAttribute() Check if the object has any attributes attached.
void	init() Retrieves datatype and dataspace information from file and sets the dataset in memory.
int	open() Opens an existing object such as dataset or group for access.
java.lang.Object	read() Reads the data from file.
byte[]	readBytes() Reads the raw data of the dataset from file to a byte array.
byte[][]	readPalette(int idx) Reads a specific image palette from file.
void	removeMetadata(java.lang.Object info) Deletes an existing metadata from this data object.
void	setName(java.lang.String newName) Sets the name of the object.
void	write(java.lang.Object buf) Writes a memory buffer to the dataset in file.
void	writeMetadata(java.lang.Object info) Writes a specific metadata (such as attribute) into file.

Methods inherited from class ncsa.hdf.object.ScalarDS

clearData, convertFromUnsignedC, convertToUnsignedC, getFillValue, getImageDataRange, getInterlace, getPaletteName, isDefaultImageOrder, isImage, isImageDisplay, isText, isTrueColor, isUnsigned, setIsImage, setIsImageDisplay, setPalette

Methods inherited from class ncsa.hdf.object.Dataset

byteToString, clear, convertFromUnsignedC, convertFromUnsignedC, convertToUnsignedC, convertToUnsignedC, getChunkSize, getCompression, getConvertByteToString, getData, getDimNames, getDims, getHeight, getMaxDims, getRank, getSelectedDims, getSelectedIndex, getSize, getStartDims, getStride, getWidth, isEnumConverted, isString, setConvertByteToString, setData, setEnumConverted, stringToByte, write

Methods inherited from class ncsa.hdf.object.HObject

equalsOID, getFID, getFile, getFileFormat, getFullName, getLinkTargetObjName, getName, getOID, getPath, setLinkTargetObjName, setPath, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

serialVersionUID

public static final long serialVersionUID

See Also:

Constant Field Values

Constructor Detail

FitsDataset

public FitsDataset(FileFormat fileFormat,
                   nom.tam.fits.BasicHDU hdu,
                   java.lang.String dName,
                   long[] oid)

Constructs an FitsDataset object with specific netcdf variable.

Parameters:

fileFormat - the netcdf file.

ncDataset - the netcdf variable.

oid - the unique identifier for this dataset.

Method Detail

hasAttribute

public boolean hasAttribute()

Description copied from interface: DataFormat

Check if the object has any attributes attached.

Returns:

true if it has any attribute(s), false otherwise.

copy

public Dataset copy(Group pgroup,
                    java.lang.String dstName,
                    long[] dims,
                    java.lang.Object buff)
             throws java.lang.Exception

Description copied from class: Dataset

Creates a new dataset and writes the data buffer to the new dataset.

This function allows applications to create a new dataset for a given data buffer. For example, users can select a specific interesting part from a large image and create a new image with the selection.

The new dataset retains the datatype and dataset creation properties of this dataset.

Specified by:

copy in class Dataset

Parameters:

pgroup - the group which the dataset is copied to.

dstName - the name of the new dataset.

dims - the dimension sizes of the the new dataset.

buff - the data values of the subset to be copied.

Returns:

the new dataset.

Throws:

java.lang.Exception

readBytes

public byte[] readBytes()
                 throws java.lang.Exception

Description copied from class: Dataset

Reads the raw data of the dataset from file to a byte array.

readBytes() reads raw data to an array of bytes instead of array of its datatype. For example, for an one-dimension 32-bit integer dataset of size 5, the readBytes() returns of a byte array of size 20 instead of an int array of 5.

readBytes() can be used to copy data from one dataset to another efficiently because the raw data is not converted to its native type, it saves memory space and CPU time.

Specified by:

readBytes in class Dataset

Returns:

the byte array of the raw data.

Throws:

java.lang.Exception

read

public java.lang.Object read()
                      throws java.lang.Exception

Description copied from class: Dataset

Reads the data from file.

read() reads the data from file to a memory buffer and returns the memory buffer. The dataset object does not hold the memobry buffer. To store the memory buffer in the dataset object, one must call getData().

By default, the whole dataset is read into memory. Users can also select subset to read. Subsetting is done in an implicit way.

How to Select a Subset

A selection is specified by three arrays: start, stride and count.

1. start: offset of a selection
2. stride: determining how many elements to move in each dimension
3. count: number of elements to select in each dimension

getStartDims(), getStartDims() and getSelectedDims() returns the start, stride and count arrays respectively. Applications can make a selection by changing the values of the arrays.

The following example shows how to make a subset. In the example, the dataset is a 4-dimensional array of [200][100][50][10], i.e. dims[0]=200; dims[1]=100; dims[2]=50; dims[3]=10;
We want to select every other data point in dims[1] and dims[2]

 int rank = dataset.getRank(); // number of dimension of the dataset
 long[] dims = dataset.getDims(); // the dimension sizes of the dataset
 long[] selected = dataset.getSelectedDims(); // the selected size of the dataet
 long[] start = dataset.getStartDims(); // the off set of the selection
 long[] stride = dataset.getStride(); // the stride of the dataset
 int[] selectedIndex = dataset.getSelectedIndex(); // the selected dimensions for display
 
 // select dim1 and dim2 as 2D data for display,and slice through dim0
 selectedIndex[0] = 1;
 selectedIndex[1] = 2;
 selectedIndex[1] = 0;
 
 // reset the selection arrays
 for (int i = 0; i < rank; i++) {
     start[i] = 0;
     selected[i] = 1;
     stride[i] = 1;
 }
 
 // set stride to 2 on dim1 and dim2 so that every other data points are selected.
 stride[1] = 2;
 stride[2] = 2;
 
 // set the selection size of dim1 and dim2
 selected[1] = dims[1] / stride[1];
 selected[2] = dims[1] / stride[2];
 
 // when dataset.getData() is called, the slection above will be used since
 // the dimension arrays are passed by reference. Changes of these arrays
 // outside the dataset object directly change the values of these array
 // in the dataset object.
 

For ScalarDS, the memory data buffer is an one-dimensional array of byte, short, int, float, double or String type based on the datatype of the dataset.

For CompoundDS, the meory data object is an java.util.List object. Each element of the list is a data array that corresponds to a compound field.

For example, if compound dataset "comp" has the following nested structure, and memeber datatypes

 comp --> m01 (int)
 comp --> m02 (float)
 comp --> nest1 --> m11 (char)
 comp --> nest1 --> m12 (String)
 comp --> nest1 --> nest2 --> m21 (long)
 comp --> nest1 --> nest2 --> m22 (double)
 

getData() returns a list of six arrays: {int[], float[], char[], Stirng[], long[] and double[]}.

Specified by:

read in class Dataset

Returns:

the data read from file.

Throws:

java.lang.Exception

See Also:

#getData()}

write

public void write(java.lang.Object buf)
           throws java.lang.Exception

Description copied from class: Dataset

Writes a memory buffer to the dataset in file.

Specified by:

write in class Dataset

Parameters:

buf - the data to write

Throws:

java.lang.Exception

getMetadata

public java.util.List getMetadata()
                           throws java.lang.Exception

Description copied from interface: DataFormat

Retrieves the metadata such as attributes from file.

Metadata such as attributes are stored in a List.

Returns:

the list of metadata objects.

Throws:

java.lang.Exception

writeMetadata

public void writeMetadata(java.lang.Object info)
                   throws java.lang.Exception

Description copied from interface: DataFormat

Writes a specific metadata (such as attribute) into file.

If an HDF(4&5) attribute exists in file, the method updates its value. If the attribute does not exists in file, it creates the attribute in file and attaches it to the object. It will fail to write a new attribute to the object where an attribute with the same name already exists. To update the value of an existing attribute in file, one needs to get the instance of the attribute by getMetadata(), change its values, and use writeMetadata() to write the value.

Parameters:

info - the metadata to write.

Throws:

java.lang.Exception

removeMetadata

public void removeMetadata(java.lang.Object info)
                    throws java.lang.Exception

Description copied from interface: DataFormat

Deletes an existing metadata from this data object.

Parameters:

info - the metadata to delete.

Throws:

java.lang.Exception

open

public int open()

Description copied from class: HObject

Opens an existing object such as dataset or group for access. The return value is an object identifier obtained by implementing classes such as H5.H5Dopen(). This function is needed to allow other objects to be able to access the object. For instance, H5File class uses the open() function to obtain object identifier for copyAttributes(int src_id, int dst_id) and other purposes. The open() function should be used in pair with close(int) function.

Specified by:

open in class HObject

Returns:

the object identifier if successful; otherwise returns a negative value.

See Also:

HObject.close(int)

close

public void close(int did)

Description copied from class: HObject

Closes access to the object.

Sub-classes must implement this interface because different data objects have their own ways of how the data resources are closed.

For example, H5Group.close() calls the ncsa.hdf.hdf5lib.H5.H5Gclose() method and closes the group resource specified by the group id.

Specified by:

close in class HObject

Parameters:

did - The object identifier.

init

public void init()

Description copied from class: Dataset

Retrieves datatype and dataspace information from file and sets the dataset in memory.

The init() is designed to support lazy operation in dataset object. When a data object is retrieved from file, the datatype, dataspace and raw data are not loaded into memory. When it is asked to read the raw data from file, init() is first called to get the datatype and dataspace information, then load the raw data from file.

init() is also used to reset selection of a dataset (start, stride and count) to the default, which is the entire dataset for 1D or 2D datasets. In the following example, init() at step 1) retrieve datatype and dataspace information from file. getData() at step 3) read only one data point. init() at step 4) reset the selection to the whole dataset. getData() at step 4) reads the values of whole dataset into memory.

 dset = (Dataset) file.get(NAME_DATASET);
 
 // 1) get datatype and dataspace information from file
 dset.init();
 rank = dset.getRank(); // rank = 2, a 2D dataset
 count = dset.getSelectedDims();
 start = dset.getStartDims();
 dims = dset.getDims();
 
 // 2) select only one data point
 for (int i = 0; i < rank; i++) {
     start[0] = 0;
     count[i] = 1;
 }
 
 // 3)  read one data point
 data = dset.getData();
 
 // 4)  reset to select the whole dataset
 dset.init();
 
 // 5) clean the memory data buffer
 dset.clearData();
 
 // 6) Read the whole dataset
 data = dset.getData();
 

Specified by:

init in class Dataset

getPalette

public byte[][] getPalette()

Description copied from class: ScalarDS

Returns the palette of this scalar dataset or null if palette does not exist.

Scalar dataset can be displayed as spreadsheet data or image. When a scalar dataset is chosen to display as an image, the palette or color table may be needed to translate a pixel value to color components (for example, red, green, and blue). Some scalar datasets have no palette and some datasets have one or more than one palettes. If an associated palette exists but not loaded, this interface retrieves the palette from the file and returns the palette. If the palette is loaded, it returnd the palette. It returns null if there is no palette assciated with the dataset.

Current implementation only supports palette model of indexed RGB with 256 colors. Other models such as YUV", "CMY", "CMYK", "YCbCr", "HSV will be supported in the future.

The palette values are stored in a two-dimensional byte array and arrange by color components of red, green and blue. palette[][] = byte[3][256], where, palette[0][], palette[1][] and palette[2][] are the red, green and blue components respectively.

Sub-classes have to implement this interface. HDF4 and HDF5 images use different libraries to retrieve the associated palette.

Specified by:

getPalette in class ScalarDS

Returns:

the 2D palette byte array.

readPalette

public byte[][] readPalette(int idx)

Description copied from class: ScalarDS

Reads a specific image palette from file.

A scalar dataset may have multiple palettes attached to it. readPalette(int idx) returns a specific palette identified by its index.

Specified by:

readPalette in class ScalarDS

Parameters:

idx - the index of the palette to read.

create

public static FitsDataset create(java.lang.String name,
                                 Group pgroup,
                                 Datatype type,
                                 long[] dims,
                                 long[] maxdims,
                                 long[] chunks,
                                 int gzip,
                                 java.lang.Object data)
                          throws java.lang.Exception

Creates a new dataset.

Parameters:

name - the name of the dataset to create.

pgroup - the parent group of the new dataset.

type - the datatype of the dataset.

dims - the dimension size of the dataset.

maxdims - the max dimension size of the dataset.

chunk - the chunk size of the dataset.

gzip - the level of the gzip compression.

data - the array of data values.

Returns:

the new dataset if successful. Otherwise returns null.

Throws:

java.lang.Exception

getPaletteRefs

public byte[] getPaletteRefs()

Description copied from class: ScalarDS

Returns the byte array of palette refs.

A palette reference is an object reference that points to the palette dataset.

For example, Dataset "Iceberg" has an attribute of object reference "Palette". The arrtibute "Palette" has value "2538" that is the object reference of the palette data set "Iceberg Palette".

Specified by:

getPaletteRefs in class ScalarDS

Returns:

null if there is no palette attribute attached to this dataset.

getDatatype

public Datatype getDatatype()

Description copied from class: Dataset

Returns the datatype object of the dataset.

Specified by:

getDatatype in class Dataset

Returns:

the datatype object of the dataset.

setName

public void setName(java.lang.String newName)
             throws java.lang.Exception

Description copied from class: HObject

Sets the name of the object.

setName (String newName) changes the name of the object in the file.

Overrides:

setName in class HObject

Parameters:

newName - The new name of the object.

Throws:

java.lang.Exception

getMetadata

public java.util.List getMetadata(int... attrPropList)
                           throws java.lang.Exception

Throws:

java.lang.Exception