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java.lang.Objectncsa.hdf.object.HObject
ncsa.hdf.object.Dataset
ncsa.hdf.object.ScalarDS
ncsa.hdf.object.h5.H5ScalarDS
public class H5ScalarDS
H5ScalarDS describes a 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).
Field Summary | |
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static long |
serialVersionUID
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Fields inherited from class ncsa.hdf.object.ScalarDS |
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INTERLACE_LINE, INTERLACE_PIXEL, INTERLACE_PLANE, isFillValueConverted |
Fields inherited from class ncsa.hdf.object.HObject |
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separator |
Constructor Summary | |
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H5ScalarDS(FileFormat theFile,
java.lang.String theName,
java.lang.String thePath)
Constructs an instance of a H5ScalarDS object with specific name and path. |
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H5ScalarDS(FileFormat theFile,
java.lang.String theName,
java.lang.String thePath,
long[] oid)
Deprecated. Not for public use in the future. Using H5ScalarDS(FileFormat, String, String) |
Method Summary | |
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void |
clear()
Clears memory held by the dataset, such as data buffer. |
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 H5ScalarDS |
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 in a file. |
void |
extend(long[] newDims)
H5Dset_extent verifies that the dataset is at least of size size, extending it if necessary. |
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. |
java.lang.String |
getPaletteName(int idx)
Get the name of a specific image palette from file. |
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 |
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clearData, convertFromUnsignedC, convertToUnsignedC, getFillValue, getImageDataRange, getInterlace, isDefaultImageOrder, isImage, isImageDisplay, isText, isTrueColor, isUnsigned, setIsImage, setIsImageDisplay, setPalette |
Methods inherited from class ncsa.hdf.object.Dataset |
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byteToString, 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 |
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equalsOID, getFID, getFile, getFileFormat, getFullName, getLinkTargetObjName, getName, getOID, getPath, setLinkTargetObjName, setPath, toString |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
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public static final long serialVersionUID
HObject.serialVersionUID
,
Constant Field ValuesConstructor Detail |
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public H5ScalarDS(FileFormat theFile, java.lang.String theName, java.lang.String thePath)
For example, in H5ScalarDS(h5file, "dset", "/arrays/"), "dset" is the name of the dataset, "/arrays" is the group path of the dataset.
theFile
- the file that contains the data object.theName
- the name of the data object, e.g. "dset".thePath
- the full path of the data object, e.g. "/arrays/".@Deprecated public H5ScalarDS(FileFormat theFile, java.lang.String theName, java.lang.String thePath, long[] oid)
H5ScalarDS(FileFormat, String, String)
Method Detail |
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public boolean hasAttribute()
DataFormat
public void init()
Dataset
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();
init
in class Dataset
public void clear()
Dataset
clear
in class Dataset
public Dataset copy(Group pgroup, java.lang.String dstName, long[] dims, java.lang.Object buff) throws java.lang.Exception
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.
copy
in class Dataset
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.
java.lang.Exception
public byte[] readBytes() throws HDF5Exception
Dataset
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.
readBytes
in class Dataset
HDF5Exception
public java.lang.Object read() throws HDF5Exception
Dataset
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.
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[]}.
read
in class Dataset
HDF5Exception
#getData()}
public void write(java.lang.Object buf) throws HDF5Exception
Dataset
write
in class Dataset
buf
- the data to write
HDF5Exception
public java.util.List getMetadata() throws HDF5Exception
DataFormat
Metadata such as attributes are stored in a List.
HDF5Exception
public java.util.List getMetadata(int... attrPropList) throws HDF5Exception
HDF5Exception
public void writeMetadata(java.lang.Object info) throws java.lang.Exception
DataFormat
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.
info
- the metadata to write.
java.lang.Exception
public void removeMetadata(java.lang.Object info) throws HDF5Exception
DataFormat
info
- the metadata to delete.
HDF5Exception
public int open()
HObject
open
in class HObject
HObject.close(int)
public void close(int did)
HObject
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.
close
in class HObject
did
- The object identifier.public byte[][] getPalette()
ScalarDS
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.
getPalette
in class ScalarDS
public java.lang.String getPaletteName(int idx)
ScalarDS
A scalar dataset may have multiple palettes attached to it. getPaletteName(int idx) returns the name of a specific palette identified by its index.
getPaletteName
in class ScalarDS
idx
- the index of the palette to retrieve the name.
public byte[][] readPalette(int idx)
ScalarDS
A scalar dataset may have multiple palettes attached to it. readPalette(int idx) returns a specific palette identified by its index.
readPalette
in class ScalarDS
idx
- the index of the palette to read.public static H5ScalarDS 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
The following example shows how to create a string dataset using this function.
H5File file = new H5File("test.h5", H5File.CREATE); int max_str_len = 120; Datatype strType = new H5Datatype(Datatype.CLASS_STRING, max_str_len, -1, -1); int size = 10000; long dims[] = { size }; long chunks[] = { 1000 }; int gzip = 9; String strs[] = new String[size]; for (int i = 0; i < size; i++) strs[i] = String.valueOf(i); file.open(); file.createScalarDS("/1D scalar strings", null, strType, dims, null, chunks, gzip, strs); try { file.close(); } catch (Exception ex) { }
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. maxdims is set to dims
if maxdims = null.chunks
- the chunk size of the dataset. No chunking if chunk = null.gzip
- the level of the gzip compression. No compression if gzip<=0.data
- the array of data values.
java.lang.Exception
public byte[] getPaletteRefs()
ScalarDS
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".
getPaletteRefs
in class ScalarDS
public Datatype getDatatype()
Dataset
getDatatype
in class Dataset
public void setName(java.lang.String newName) throws java.lang.Exception
HObject
setName (String newName) changes the name of the object in the file.
setName
in class HObject
newName
- The new name of the object.
java.lang.Exception
public void extend(long[] newDims) throws HDF5Exception
HDF5Exception
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