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<!doctype HTML public "-//W3C//DTD HTML 4.0 Frameset//EN">
<html>
<head>
<title>Chapter 2: The HDF5 Library and Programming Model</title>
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<table x-use-null-cells\
align="right"\
width="240"\
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<span class="TableHead">Chapter Contents</span></td>\
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<tr valign="top"> \
<td class="tocTableContentCell2"> \
<a href="#Intro">1.</a></td>\
<td class="tocTableContentCell3">\
<a href="#Intro">Introduction</a></td> \
</tr>\
<tr valign="top"> \
<td class="tocTableContentCell2"> \
<a href="#ProgModel">2.</a></td>\
<td class="tocTableContentCell3">\
<a href="#ProgModel">Programming Model</a><br />\
<font size="-1">\
\
<a href="#CreateFile">Create file</a>\
<br /> \
\
<a href="#CreateDataset">Create dataset</a>\
<br /> \
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<a href="#CloseObject">Close objects</a>\
<br /> \
\
<a href="#WriteRead">Write and read</a>\
<br /> \
\
<a href="#PartialWR">Partial write/read</a>\
<br /> \
\
<a href="#GetInfo">Get information</a>\
<br /> \
\
<a href="#CreateCDType">Create compound</a>\
<br /> \
\
<a href="#CreateCDType">datatype</a>\
<br /> \
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<a href="#ExtendChunked">Create extendable or</a>\
<br /> \
\
<a href="#ExtendChunked">chunked dataset</a>\
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<a href="#IOPipeline">3.</a></td>\
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<a href="#IOPipeline">Data Transfer Pipeline</a>\
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<a href="#Appendix">10</a></td>\
<td class="tocTableContentCell4"><a href="#Appendix">Appendix</a></td>\
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<table x-use-null-cells
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width="240"
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<td class="tocTableHeaderCell">
<span class="TableHead">Chapter Contents</span></td>
</tr>
<tr valign="top">
<td class="tocTableContentCell">
<a href="#Intro">1. Introduction</a>
<br />
<a href="#AbstractDMod">2. Abstract Data Model</a>
<br />
<a href="#SModel">3. HDF5 Storage Model</a>
<br />
<a href="#LibPModel">4. Library and</a>
<br />
<a href="#LibPModel">Programming Model</a>
<br />
<a href="#IOPipeline">3. Data Transfer Pipeline</a>
<br />
<a href="#Structure">HDF5 File</a>
</td>
</tr>
</table>
-->
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<div align="center">
<a name="TOP">
<h2>Chapter 2<br /><font size="6">The HDF5 Library and Programming Model</font></h2>
</a>
</div>
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<a name="Intro">
<h3>2.1. Introduction</h3>
</a>
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<p>The HDF5 Library implements the HDF5 abstract data model and storage
model. These models were described in the preceding chapter,
“<a href="03_DataModel.html">The HDF5 Data Model</a>”. </p>
<p>Two major objectives of the HDF5 products are to provide tools
that can be used on as many computational platforms as possible
(portability), and to provide a reasonably object-oriented data model
and programming interface. </p>
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Explain? E.g., Java is portable,
but there are many platforms on which it does not run.
] ] ]</span>
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<p>To be as portable as possible, the HDF5 Library is implemented in
portable C. C is not an object-oriented language, but the library uses
several mechanisms and conventions to implement an object model.</p>
<p>One mechanism the HDF5 library uses is to implement the objects
as data structures. To refer to an object, the HDF5 library implements
its own pointers. These pointers are called identifiers.
An identifier is then used to invoke operations on a specific instance
of an object. For example, when a group is opened,
the API returns a group identifier. This identifier is a reference to that
specific group and will be used to invoke future operations on that group.
The identifier is valid only within the context it is created
and remains valid until it is closed or the file is closed.
This mechanism is essentially the same as the mechanism that C++ or
other object-oriented languages use to refer to objects except that the
syntax is C. </p>
<p>Similarly, object-oriented languages collect all the methods for
an object in a single name space. An example is the methods of a C++ class.
The C language does not have any such mechanism,
but the HDF5 Library simulates this through its API naming convention.
API function names begin with a common prefix that is related to the
class of objects that the function operates on.
The table below lists the HDF5 objects and the standard prefixes
used by the corresponding HDF5 APIs.
For example, functions that operate on datatype objects all have names
beginning with H5T.</p>
<!-- NEW PAGE -->
<table width="300" cellspacing="0" align="center" cellpadding="0">
<tr valign="bottom">
<td colspan="2" align="left" valign="bottom">
<b>Table 1. The HDF5 API naming scheme</b></td>
</tr>
<tr><td colspan="2"><hr color="green" size="3" /></td></tr>
<tr valign="top">
<td>
<b>Prefix </b></td>
<td>
<b>Operates on </b></td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5A</td>
<td>Attributes </td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5D</td>
<td>Datasets </td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5E</td>
<td>Error reports</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5F</td>
<td>Files</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5G</td>
<td>Groups</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5I</td>
<td>Identifiers</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5L</td>
<td>Links</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5O</td>
<td>Objects</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5P</td>
<td>Property lists</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5R</td>
<td>References</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5S</td>
<td>Dataspaces</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5T</td>
<td>Datatypes</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>H5Z</td>
<td>Filters</td>
</tr>
<tr><td colspan="2"><hr color="green" size="3" /></td></tr>
</table>
<br />
<!-- NEW PAGE -->
<a name="ProgModel">
<h3>2.2. The HDF5 Programming Model</h3>
</a>
<p>In this section we introduce the HDF5
<span class="termDefinition">programming model</span> by means of
a series of short code samples. These samples illustrate a broad
selection of common HDF5 tasks. More details are provided in the
following chapters and in the
<a href="../RM/RM_H5Front.html" TARGET="H5DocWin">
<cite>HDF5 Reference Manual</cite></a></p>
<!-- editingComment
<span class="editingComment"><p>[ [ [
The following is based on text from the old "Intro to HDF5"
and presumably needs some technical verification.
] ] ]</span>
-->
<a name="CreateFile">
<h4>2.2.1. Creating an HDF5 File</h4></a>
<p>Before an HDF5 file can be used or referred to in any manner,
it must be explicitly created or opened. When the need for access to
a file ends, the file must be closed. The example below provides a C
code fragment illustrating these steps. In this example, the values
for the file creation property list and the file access property list
are set to the defaults <code>H5P_DEFAULT</code>.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
hid_t file; /* declare file identifier */
/*
* Create a new file using H5F_ACC_TRUNC
* to truncate and overwrite any file of the same name,
* default file creation properties, and
* default file access properties.
* Then close the file.
*/
file = H5Fcreate(FILE, H5F_ACC_TRUNC, H5P_DEFAULT, H5P_DEFAULT);
status = H5Fclose(file); </pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 1. Creating and closing an HDF5 file</b>
<hr color="green" size="3"/></td>
<!-- formerly Figure 1-->
</tr>
</table>
<br />
<p>Note: If there is a possibility that a file of the declared name
already exists and you wish to open a new file regardless of that
possibility, the flag <code>H5F_ACC_TRUNC</code> will cause the
operation to overwrite the previous file. If the operation should
fail in such a circumstance, use the flag <code>H5F_ACC_EXCL</code>
instead.</p>
<a name="CreateDataset">
<h4>2.2.2. Creating and Initializing a Dataset</h4></a>
<p>The essential objects within a dataset are datatype and dataspace.
These are independent objects and are created separately from any dataset
to which they may be attached. Hence, creating a dataset requires,
at a minimum, the following steps:</p>
<ol>
<li>Create and initialize a dataspace for the dataset</li>
<li>Define a datatype for the dataset</li>
<li>Create and initialize the dataset</li>
</ol>
<!-- NEW PAGE -->
<p>The code in the example below illustrates the execution of these steps.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
hid_t dataset, datatype, dataspace; /* declare identifiers */
/*
* Create a dataspace: Describe the size of the array and
* create the dataspace for a fixed-size dataset.
*/
dimsf[0] = NX;
dimsf[1] = NY;
dataspace = H5Screate_simple(RANK, dimsf, NULL);
/*
* Define a datatype for the data in the dataset.
* We will store little endian integers.
*/
datatype = H5Tcopy(H5T_NATIVE_INT);
status = H5Tset_order(datatype, H5T_ORDER_LE);
/*
* Create a new dataset within the file using the defined
* dataspace and datatype and default dataset creation
* properties.
* NOTE: H5T_NATIVE_INT can be used as the datatype if
* conversion to little endian is not needed.
*/
dataset = H5Dcreate(file, DATASETNAME, datatype, dataspace,
H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); </pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 2. Create a dataset</b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<a name="CloseObject">
<h4>2.2.3. Closing an Object </h4></a>
<p>An application should close an object such as a datatype, dataspace,
or dataset once the object is no longer needed.
Since each is an independent object, each must be released
(or closed) separately. This action is frequently referred to as
<span class="termDefinition">releasing the object’s identifier</span>.
The code in the example below <!-- formerly Figure 3 -->closes the
datatype, dataspace, and dataset that were created in the preceding
section.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
H5Tclose(datatype);
H5Dclose(dataset);
H5Sclose(dataspace);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 3. Close an object</b>
<hr color="green" size="3"/></td>
<!-- formerly Figure 3 -->
</tr>
</table>
<br />
<p>There is a long list of HDF5 Library items that return a unique
identifier when the item is created or opened. Each time that one of
these items is opened, a unique identifier is returned. Closing a file
does not mean that the groups, datasets, or other open items are also
closed. Each opened item must be closed separately. </p>
<!-- FOR USE WITH ELECTRONIC VERSION --------------------------------->
<p>For more information, see
<a href="../Advanced/UsingIdentifiers/index.html">“Using Identifiers”</a>
in the “Advanced Topics” page.</p>
<!-- FOR USE WITH ELECTRONIC VERSION --------------------------------->
<!-- FOR USE WITH PRINT VERSION --------------------------------------
<p>For more information, see “Using Identifiers” in the
“Additional Resources” chapter.</p>
<!-- FOR USE WITH PRINT VERSION -------------------------------------->
<a name="ClosingAFileNotes">
<h4>How Closing a File Effects Other Open Structural Elements</h4></a>
<p>Every structural element in an HDF5 file can be opened, and these
elements can be opened more than once. Elements range in size from
the entire file down to attributes. When an element is opened, the
HDF5 Library returns a unique identifier to the application. Every
element that is opened must be closed. If an element was opened more
than once, each identifier that was returned to the application must
be closed. For example, if a dataset was opened twice, both dataset
identifiers must be released (closed) before the dataset can be
considered closed. Suppose an application has opened a file, a group in
the file, and two datasets in the group. In order for the file to be
totally closed, the file, group, and datasets must each be closed.
Closing the file before the group or the datasets will not effect the
state of the group or datasets: the group and datasets will still be
open.</p>
<p>There are several exceptions to the above general rule. One is when
the <code>H5close</code> function is used. <code>H5close</code> causes a
general shutdown of the library: all data is written to disk, all
identifiers are closed, and all memory used by the library is
cleaned up. Another exception occurs on parallel processing systems.
Suppose on a parallel system an application has opened a file, a
group in the file, and two datasets in the group. If the application
uses the <code>H5Fclose</code> function to close the file, the call
will fail with an error. The open group and datasets must be closed
before the file can be closed. A third exception is when the file
access property list includes the property <code>H5F_CLOSE_STRONG</code>.
This property closes any open elements when the file is closed with
<code>H5Fclose</code>. For more information, see the
<a href="../RM/RM_H5P.html#Property-SetFcloseDegree">
<code>H5Pset_fclose_degree</code></a> function in the
<cite>HDF5 Reference Manual</cite>.</p>
<a name="WriteRead">
<h4>2.2.4. Writing or Reading a Dataset to or from a File</h4></a>
<p>Having created the dataset, the actual data can be written
with a call to <code>H5Dwrite</code>. See the example below.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Write the data to the dataset using default transfer
* properties.
*/
status = H5Dwrite(dataset, H5T_NATIVE_INT, H5S_ALL, H5S_ALL,
H5P_DEFAULT, data);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 4. Writing a dataset</b>
<hr color="green" size="3"/></td>
<!-- formerly Figure 4 -->
</tr>
</table>
<br />
<p>Note that the third and fourth <code>H5Dwrite</code> parameters in
the above example describe the dataspaces in memory and in the file,
respectively. For now, these are both set to <code>H5S_ALL</code> which
indicates that the entire dataset is to be written.
The selection of partial datasets and the use of differing dataspaces
in memory and in storage will be discussed later in this chapter and
in more detail elsewhere in this guide.</p>
<p>Reading the dataset from storage is similar to writing the dataset to
storage. To read an entire dataset, substitute <code>H5Dread</code> for
<code>H5Dwrite</code> in the above example.</p>
<a name="PartialWR">
<h4>2.2.5. Reading and Writing a Portion of a Dataset</h4>
</a>
<p>The previous section described writing or reading an entire
dataset. HDF5 also supports access to portions of a dataset. These parts of
datasets are known as <span class="termDefinition">selections</span>.
<p>The simplest type of selection is a
<span class="termDefinition">simple hyperslab</span>. This is
an <span class="codeVar">n</span>-dimensional rectangular sub-set of
a dataset where <span class="codeVar">n</span> is equal to the
dataset’s rank. Other available selections include
a more complex hyperslab with user-defined stride and block size,
a list of independent points, or the union of any of these.</p>
<p>The figure below <!-- formerly Figure 5 -->shows several
sample selections.</p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="center">
<hr color="green" size="3"/>
<img src="Images/Pmodel_fig5_a.jpg"><br />
<img src="Images/Pmodel_fig5_b.jpg"><br />
<img src="Images/Pmodel_fig5_c.jpg"><br />
<img src="Images/Pmodel_fig5_d.jpg"><br />
<img src="Images/Pmodel_fig5_e.jpg"><br />
</td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left" >
<b>Figure 1. Dataset selections</b><br />
<!-- formerly Figure 5. -->
Selections can take the form of a simple hyperslab,
a hyperslab with user-defined stride and block,
a selection of points, or a union of any of these forms.
<!--
<span class="editingComment"><br />[ [ [
Edit figures to retain...
upper left,
maybe a second simple hyperslab,
2nd left,
box on right (3-D point),
and an interesting-looking union.
None of the text in the JPEGs need be retained.
Use new figure filenames as we are holding the current figure for possible reuse elsewhere.
<br />
If it's not already been done, remember that the original figure is to be used, in toto,
in the "Memory<-->Disk Data Transfer" discussion, with "Key" to add characters '(hyperslab)'
immediately to the right of the hyperslab icon.
] ] ]</span>
-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<p>Selections and hyperslabs are portions of a dataset.
As described above, a <span class="termDefinition">simple hyperslab</span>
is a rectangular array of data elements with the same rank as the
dataset’s dataspace. Thus, a simple hyperslab is a
logically contiguous collection of points within the dataset. </p>
<p>The more general case of a <span class="termDefinition">hyperslab</span>
can also be a regular pattern of points or blocks within the dataspace.
Four parameters are required to describe a general hyperslab: the
starting coordinates, the block size, the stride or space between
blocks, and the number of blocks. These parameters are each expressed
as a one-dimensional array with length equal to the rank of the dataspace
and are described in the table below
<!-- formerly table 2-->.</p>
<table width="600" cellspacing="0" align="center" cellpadding="0">
<tr valign="bottom">
<td colspan="2" align="left" valign="bottom">
<b>Table 2. Hyperslab parameters</b>
</td>
</tr>
<tr><td colspan="2"><hr color="green" size="3" /></td></tr>
<tr valign="top">
<td>
<b>Parameter </b></td>
<td>
<b>Definition</b></td>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td><code><i>start</i></code></td>
<td>
The coordinates of the starting location of the hyperslab
in the dataset’s dataspace.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td><code><i>block</i></code></td>
<td>
The size of each block to be selected from the dataspace.
If the <code>block</code> parameter is set to NULL,
the block size defaults to a single element in each dimension,
as if the block array was set to all <code>1</code>s (all ones).
This will result in the selection of
a uniformly spaced set of <code>count</code> points
starting at <code>start</code> and
on the interval defined by <code>stride</code>.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td><code><i>stride</i></code></td>
<td>
The number of elements separating the starting point of each element
or block to be selected.
If the <code>stride</code> parameter is set to NULL,
the stride size defaults to 1 (one) in each dimension
and no elements are skipped.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td><code><i>count</i></code></td>
<td>
The number of elements or blocks to select along each dimension.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="3" /></td></tr>
</table>
<br />
<h4>Reading Data into a Differently Shaped Memory Block</h4>
<p>For maximum flexibility in user applications, a selection in storage
can be mapped into a differently-shaped selection in memory. All that
is required is that the two selections contain the same number of data
elements. In this example, we will first define the selection to be
read from the dataset in storage, and then we will define the
selection as it will appear in application memory.</p>
<p>Suppose we want to read a 3 x 4 hyperslab from a two-dimensional
dataset in a file beginning at the dataset element <1,2>.
The first task is to create the dataspace that describes the
overall rank and dimensions of the dataset in the file and to
specify the position and size of the in-file hyperslab that we
are extracting from that dataset. See the code below.
<!-- formerly Figure 6--></p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Define dataset dataspace in file.
*/
dataspace = H5Dget_space(dataset); /* dataspace identifier */
rank = H5Sget_simple_extent_ndims(dataspace);
status_n = H5Sget_simple_extent_dims(dataspace, dims_out, NULL);
/*
* Define hyperslab in the dataset.
*/
offset[0] = 1;
offset[1] = 2;
count[0] = 3;
count[1] = 4;
status = H5Sselect_hyperslab(dataspace, H5S_SELECT_SET, offset, NULL,
count, NULL);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 5. Define the selection to be read from storage </b>
<!-- formerly Figure 6.-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>The next task is to define a dataspace in memory.
Suppose that we have in memory a three-dimensional 7 x 7 x 3 array
into which we wish to read the two-dimensional 3 x 4 hyperslab
described above and that we want the memory selection to begin at
the element <3,0,0> and reside in the plane of the first two
dimensions of the array. Since the in-memory dataspace is
three-dimensional, we have to describe the in-memory selection as
three-dimensional. Since we are keeping the selection in the plane
of the first two dimensions of the in-memory dataset, the in-memory
selection will be a 3 x 4 x 1 array defined as <3,4,1>. </p>
<!-- NOT EDITED TO..... ----->
<p>Notice that we must describe two things: the dimensions of the
in-memory array, and the size and position of the hyperslab that we
wish to read in. The code below <!--formerly Figure 7 -->illustrates
how this would be done.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Define memory dataspace.
*/
dimsm[0] = 7;
dimsm[1] = 7;
dimsm[2] = 3;
memspace = H5Screate_simple(RANK_OUT,dimsm,NULL);
/*
* Define memory hyperslab.
*/
offset_out[0] = 3;
offset_out[1] = 0;
offset_out[2] = 0;
count_out[0] = 3;
count_out[1] = 4;
count_out[2] = 1;
status = H5Sselect_hyperslab(memspace, H5S_SELECT_SET, offset_out, NULL,
count_out, NULL);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 6. Define the memory dataspace and selection </b>
<hr color="green" size="3"/></td>
<!-- formerly Figure 7.-->
</tr>
</table>
<br />
<p>The hyperslab defined in the code above has the following parameters:
<code>start=(3,0,0)</code>, <code>count=(3,4,1)</code>, stride and
block size are <code>NULL</code>.</p>
<!-- .....TO HERE ----->
<h4>Writing Data into a Differently Shaped Disk Storage Block</h4>
<p>Now let’s consider the opposite process of
writing a selection from memory to a selection in a dataset in a file.
Suppose that the source dataspace in memory is a 50-element,
one-dimensional array called <code>vector</code>
<!-- formerly Figure 8-->
and that the source selection is a 48-element simple hyperslab
that starts at the second element of <code>vector</code>.
See the figure below.</p>
<table width="400" cellspacing="0" align="center">
<tr valign="top">
<td align="center">
<hr color="green" size="3"/>
<tr>
<td align="center"><br />
<table align="center" border="1">
<tr valign="top" align="center">
<td> <code>-1</code> </td>
<td> <code>1</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>...</code> </td>
<td> <code>49</code> </td>
<td> <code>50</code> </td>
<td> <code>-1</code> </td>
</tr>
</table>
</td></tr>
</td></tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left" >
<b>Figure 2. A one-dimensional array</b>
<!-- formerly Figure 8-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<p>Further suppose that we wish to write this data to the file as
a series of 3 x 2-element blocks in a two-dimensional dataset,
skipping one row and one column between blocks.
Since the source selection contains 48 data elements and
each block in the destination selection contains 6 data elements,
we must define the destination selection with 8 blocks.
We will write 2 blocks in the first dimension and 4 in the second.
The code below <!-- formerly Figure 9 --> shows how to achieve this
objective.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/* Select the hyperslab for the dataset in the file, using 3 x 2 blocks,
* a (4,3) stride, a (2,4) count, and starting at the position (0,1).
*/
start[0] = 0; start[1] = 1;
stride[0] = 4; stride[1] = 3;
count[0] = 2; count[1] = 4;
block[0] = 3; block[1] = 2;
ret = H5Sselect_hyperslab(fid, H5S_SELECT_SET, start, stride, count, block);
/*
* Create dataspace for the first dataset.
*/
mid1 = H5Screate_simple(MSPACE1_RANK, dim1, NULL);
/*
/*
* Select hyperslab.
* We will use 48 elements of the vector buffer starting at the second element.
* Selected elements are 1 2 3 . . . 48
*/
start[0] = 1;
stride[0] = 1;
count[0] = 48;
block[0] = 1;
ret = H5Sselect_hyperslab(mid1, H5S_SELECT_SET, start, stride, count, block);
/*
* Write selection from the vector buffer to the dataset in the file.
*
ret = H5Dwrite(dataset, H5T_NATIVE_INT, mid1, fid, H5P_DEFAULT, vector)</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 7. The destination selection
<!-- formerly Figure 9--></b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<a name="GetInfo">
<h4>2.2.6. Getting Information about a Dataset</h4>
</a>
<p>Although reading is analogous to writing, it is often first necessary
to query a file to obtain information about the dataset to be read.
For instance, we often need to determine the datatype associated with a
dataset, or its dataspace (i.e., rank and dimensions).
As illustrated in the code example below <!--formerly Figure 10-->,
there are several <span class="termDefinition">get</span> routines for
obtaining this information.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Get datatype and dataspace identifiers,
* then query datatype class, order, and size, and
* then query dataspace rank and dimensions.
*/
datatype = H5Dget_type (dataset); /* datatype identifier */
class = H5Tget_class (datatype);
if (class == H5T_INTEGER) printf("Dataset has INTEGER type \n");
order = H5Tget_order (datatype);
if (order == H5T_ORDER_LE) printf("Little endian order \n");
size = H5Tget_size (datatype);
printf ("Size is %d \n", size);
dataspace = H5Dget_space (dataset); /* dataspace identifier */
/* Find rank and retrieve current and maximum dimension sizes */
rank = H5Sget_simple_extent_dims (dataspace, dims, max_dims);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 8. Routines to get dataset parameters
<!--formerly Figure 10--></b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<a name="CreateCDType">
<h4>2.2.7. Creating and Defining Compound Datatypes</h4></a>
<p>A <span class="termDefinition">compound datatype</span> is a
collection of one or more data elements. Each element might be an
atomic type, a small array, or another compound datatype. </p>
<p>The provision for nested compound datatypes allows these structures
to become quite complex. An HDF5 compound datatype has some similarities
to a C struct or a Fortran common block. Though not originally designed
with databases in mind, HDF5 compound datatypes are sometimes used
in a way that is similar to a database record. Compound datatypes
can become either a powerful tool or a complex and difficult-to-debug
construct. Reasonable caution is advised.</p>
<p>To create and use a compound datatype,
you need to create a datatype with class
<span class="termDefinition">compound</span> (<code>H5T_COMPOUND</code>)
and specify the total size of the data element in bytes.
A compound datatype consists of zero or more uniquely named members.
Members can be defined in any order but must occupy non-overlapping regions
within the datum. The table below <!-- formerly
Table 3 -->lists the properties of compound datatype members.</p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center" cellpadding="0">
<tr valign="bottom">
<td colspan="2" align="left" valign="bottom">
<b>Table 3. Compound datatype member properties</b></td>
</tr>
<tr><td colspan="2"><hr color="green" size="2" /></td></tr>
<tr valign="top">
<td width="20%"><b>Parameter</b></td>
<td width="80%"><b>Definition</b></td>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>Index</td>
<td>An index number between zero and N-1, where N is the number of
members in the compound. The elements are indexed in the order of
their location in the array of bytes.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>Name</td>
<td>A string that must be unique within the members
of the same datatype.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>Datatype</td>
<td>An HDF5 datatype.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td>Offset</td>
<td>A fixed byte offset which defines the location of the first
byte of that member in the compound datatype.</td>
</tr>
<tr><td colspan="2"><hr color="green" size="2" /></td></tr>
</table>
<br />
<p>Properties of the members of a compound datatype are
defined when the member is added to the compound type. These
properties cannot be modified later. </p>
<h4>Defining Compound Datatypes</h4>
<p>Compound datatypes must be built out of other datatypes.
To do this, you first create an empty compound datatype and specify
its total size. Members are then added to the compound datatype
in any order. </p>
<p>Each member must have a descriptive name. This is the
key used to uniquely identify the member within the
compound datatype. A member name in an HDF5 datatype does
not necessarily have to be the same as the name of the
corresponding member in the C struct in memory although
this is often the case. You also do not need to define all the
members of the C struct in the HDF5 compound datatype
(or vice versa). </p>
<p>Usually a C struct will be defined to hold a data
point in memory, and the offsets of the members in memory
will be the offsets of the struct members from the beginning
of an instance of the struct. The library defines the macro
that computes the offset of member <code>m</code> within a
struct variable <code>s</code>.: </p>
<dir><code>HOFFSET(s,m)</code></dir>
<p>The code below <!-- formerly Figure 11 -->shows an example in
which a compound datatype is created to describe complex numbers
whose type is defined by the <code>complex_t</code> struct.</p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
Typedef struct {
double re; /*real part */
double im; /*imaginary part */
} complex_t;
complex_t tmp; /*used only to compute offsets */
hid_t complex_id = H5Tcreate (H5T_COMPOUND, sizeof tmp);
H5Tinsert (complex_id, "real", HOFFSET(tmp,re),
H5T_NATIVE_DOUBLE);
H5Tinsert (complex_id, "imaginary", HOFFSET(tmp,im),
H5T_NATIVE_DOUBLE);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 9. A compound datatype for complex numbers</b>
<!-- formerly Figure 11-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- editingComment
<span class="editingComment">
<p>For more information about Datatypes, see Chapter ???.
</span>
-->
<a name="ExtendChunked">
<h4>2.2.8. Creating and Writing Extendable Datasets</h4>
</a>
<p>An extendable dataset is one whose dimensions can grow.
One can define an HDF5 dataset to have certain initial
dimensions with the capacity to later increase the size
of any of the initial dimensions. For example, the figure below
<!-- formerly Figure 12 -->shows a 3 x 3 dataset (a)
which is later extended to be a 10 x 3 dataset by adding 7
rows (b), and further extended to be a 10 x 5 dataset by
adding two columns (c).</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="center">
<hr color="green" size="3"/>
<table width="80%" cellspacing="0" class="fullImgTable" align="center">
<tr>
<td align="center"><br />
<table align="center">
<tr>
<td valign="middle" align="center" width="45%">
<table align="center" border="1">
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
</table>
a) Initially, 3 x 3
<br /> <br />
<table align="center" border="1">
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
</tr>
</table>
b) Extend to 10 x 3
</td>
<td valign="middle" align="center" width="55%">
<code> </code>
</td>
<td valign="middle" align="center" width="55%">
<table align="center" border="1">
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>1</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
<tr>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>2</code> </td>
<td> <code>3</code> </td>
<td> <code>3</code> </td>
</tr>
</table>
c) Extend to 10 x 5
</tr>
</table>
</td></tr>
</table>
</td></tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left" >
<b>Figure 3. Extending a dataset</b>
<!-- formerly Figure 12-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>HDF5 requires the use of chunking when defining
extendable datasets. Chunking makes it possible to extend
datasets efficiently without having to reorganize contiguous
storage excessively. </p>
<p>To summarize, an extendable dataset requires two conditions:</p>
<ol>
<li>Define the dataspace of the dataset as unlimited in
all dimensions that might eventually be extended</li>
<li>Enable chunking in the dataset creation properties</li>
</ol>
<p>For example, suppose we wish to create a dataset similar
to the one shown in the figure above<!-- formerly Figure 12-->.
We want to start with a 3 x 3 dataset, and then later we will
extend it. To do this, go through the steps below.</p>
<p>First, declare the dataspace to have unlimited dimensions. See
the code shown below. Note the use of the predefined constant
<code>H5S_UNLIMITED</code> to specify that a dimension is
unlimited.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
Hsize_t dims[2] = {3, 3}; /* dataset dimensions
at the creation time */
hsize_t maxdims[2] = {H5S_UNLIMITED, H5S_UNLIMITED};
/*
* Create the data space with unlimited dimensions.
*/
dataspace = H5Screate_simple(RANK, dims, maxdims);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 10. Declaring a dataspace with unlimited dimensions</b>
<!-- formerly Figure 13-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>Next, set the dataset creation property list to
enable chunking. See the code below.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
hid_t cparms;
hsize_t chunk_dims[2] ={2, 5};
/*
* Modify dataset creation properties to enable chunking.
*/
cparms = H5Pcreate (H5P_DATASET_CREATE);
status = H5Pset_chunk(cparms, RANK, chunk_dims);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 11. Enable chunking
<!-- formerly Figure 14--></b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<p>The next step is to create the dataset. See the code below.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Create a new dataset within the file using cparms
* creation properties.
*/
dataset = H5Dcreate(file, DATASETNAME, H5T_NATIVE_INT, dataspace,
H5P_DEFAULT, cparms, H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 12. Create a dataset
<!-- formerly Figure 15--></b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>Finally, when the time comes to extend the size of
the dataset, invoke <code>H5Dextend</code>. Extending
the dataset along the first dimension by seven rows
leaves the dataset with new dimensions of <10,3>. See the
code below.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Extend the dataset. Dataset becomes 10 x 3.
*/
dims[0] = dims[0] + 7;
size[0] = dims[0];
size[1] = dims[1];
status = H5Dextend (dataset, size);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 13. Extend the dataset by seven rows</b>
<!-- formerly Figure 16-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<a name="Groups">
<h4>2.2.9. Creating and Working with Groups</h4>
</a>
<p>Groups provide a mechanism for organizing meaningful
and extendable sets of datasets within an HDF5 file. The H5G
API provides several routines for working with groups. </p>
<h4>Creating a Group</h4>
<p>With no datatype, dataspace, or storage layout to define,
creating a group is considerably simpler than creating a
dataset. For example, the following code creates a group
called <code>Data</code> in the root group of
<code>file</code>.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Create a group in the file.
*/
grp = H5Gcreate(file, "/Data", H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 14. Create a group</b>
<!-- formerly Figure 17-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<p>A group may be created within another group by providing
the absolute name of the group to the <code>H5Gcreate</code> function
or by specifying its location. For example, to create the
group <code>Data_new</code> in the group <code>Data</code>, you might use
the sequence of calls shown below.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Create group "Data_new" in the group "Data" by specifying
* absolute name of the group.
*/
grp_new = H5Gcreate(file, "/Data/Data_new", H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);
or
/*
* Create group "Data_new" in the "Data" group.
*/
grp_new = H5Gcreate(grp, "Data_new", H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 15. Create a group within a group</b>
<!-- formerly Figure 18-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>This first parameter of <code>H5Gcreate</code> is a location
identifier. <code>file</code> in the first example specifies only
the file. <code>grp</code> in the second example specifies
a particular group in a particular file. Note that in
this instance, the group identifier <code>grp</code> is
used as the first parameter in the <code>H5Gcreate</code>
call so that the relative name of <code>Data_new</code>
can be used.</p>
<p>The third parameter of <code>H5Gcreate</code> optionally specifies
how much file space to reserve to store the names of objects that
will be created in this group. If a non-positive value is supplied,
the library provides a default size.</p>
<p>Use <code>H5Gclose</code> to close the group and release
the group identifier. </p>
<!-- NEW PAGE -->
<h4>Creating a Dataset within a Group</h4>
<p>As with groups, a dataset can be created in a particular group
by specifying either its absolute name in the file or its relative
name with respect to that group. The next code excerpt
uses the absolute name.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Create the dataset "Compressed_Data" in the group Data using the
* absolute name. The dataset creation property list is modified
* to use GZIP compression with the compression effort set to 6.
* Note that compression can be used only when the dataset is
* chunked.
*/
dims[0] = 1000;
dims[1] = 20;
cdims[0] = 20;
cdims[1] = 20;
dataspace = H5Screate_simple(RANK, dims, NULL);
plist = H5Pcreate(H5P_DATASET_CREATE);
H5Pset_chunk(plist, 2, cdims);
H5Pset_deflate(plist, 6);
dataset = H5Dcreate(file, "/Data/Compressed_Data",
H5T_NATIVE_INT, dataspace, H5P_DEFAULT, plist, H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 16. Create a dataset within
a group using an absolute name </b>
<!-- formerly Figure 19-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>Alternatively, you can first obtain an identifier for
the group in which the dataset is to be created, and then
create the dataset with a relative name.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Open the group.
*/
grp = H5Gopen(file, "Data", H5P_DEFAULT);
/*
* Create the dataset "Compressed_Data" in the "Data" group
* by providing a group identifier and a relative dataset
* name as parameters to the H5Dcreate function.
*/
dataset = H5Dcreate(grp, "Compressed_Data", H5T_NATIVE_INT,
dataspace, H5P_DEFAULT, plist, H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 17. Create a dataset within a group using a relative name</b>
<!-- formerly Figure 20-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<h4>Accessing an Object in a Group</h4>
<p>Any object in a group
can be accessed by its absolute or relative name. The
first code snippet below illustrates the use of the absolute
name to access the dataset <code>Compressed_Data</code> in
the group <code>Data</code> created in the examples above.
The second code snippet illustrates the use of the
relative name.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Open the dataset "Compressed_Data" in the "Data" group.
*/
dataset = H5Dopen(file, "/Data/Compressed_Data", H5P_DEFAULT);
</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 18. Accessing a group using its absolute name</b>
<!-- formerly Figure 21-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<br />
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Open the group "data" in the file.
*/
grp = H5Gopen(file, "Data", H5P_DEFAULT);
/*
* Access the "Compressed_Data" dataset in the group.
*/
dataset = H5Dopen(grp, "Compressed_Data", H5P_DEFAULT);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 19. Accessing a group using its relative name</b>
<!-- formerly Figure 22-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<!-- NEW PAGE -->
<a name="Attrs">
<h4>2.2.10. Working with Attributes</h4>
</a>
<p>An attribute is a small dataset that is attached to
a normal dataset or group. Attributes share many of the
characteristics of datasets, so the programming model for
working with attributes is similar in many ways to the
model for working with datasets. The primary differences
are that an attribute must be attached to a dataset or a
group and sub-setting operations cannot be performed on
attributes. </p>
<p>To create an attribute belonging to a particular
dataset or group, first create a dataspace for the attribute
with the call to <code>H5Screate</code>, and then create the
attribute using <code>H5Acreate</code>. For example, the
code shown below creates an attribute called
<code>Integer_attribute</code> that is a member of a dataset
whose identifier is <code>dataset</code>. The attribute identifier is
<code>attr2</code>. <code>H5Awrite</code> then sets the value of
the attribute of that of the integer variable point.
<code>H5Aclose</code> then releases the attribute
identifier.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
Int point = 1; /* Value of the scalar attribute */
/*
* Create scalar attribute.
*/
aid2 = H5Screate(H5S_SCALAR);
attr2 = H5Acreate(dataset, "Integer attribute", H5T_NATIVE_INT, aid2,
H5P_DEFAULT, H5P_DEFAULT);
/*
* Write scalar attribute.
*/
ret = H5Awrite(attr2, H5T_NATIVE_INT, &point);
/*
* Close attribute dataspace.
*/
ret = H5Sclose(aid2);
/*
* Close attribute.
*/
ret = H5Aclose(attr2); </pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 20. Create an attribute</b>
<!-- formerly Figure 23-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>To read a scalar attribute whose name and datatype
are known, first open the attribute using
<code>H5Aopen_by_name</code>, and then use <code>H5Aread</code>
to get its value. For example, the code shown below reads a scalar
attribute called <code>Integer_attribute</code> whose
datatype is a native integer and whose parent dataset
has the identifier <code>dataset</code>.</p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Attach to the scalar attribute using attribute name, then read and
* display its value.
*/
attr = H5Aopen_by_name(file_id, dataset_name, "Integer attribute",
H5P_DEFAULT, H5P_DEFAULT);
ret = H5Aread(attr, H5T_NATIVE_INT, &point_out);
printf("The value of the attribute \"Integer attribute\" is %d \n", point_out);
ret = H5Aclose(attr);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 21. Read a known attribute</b>
<!-- formerly Figure 24-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>To read an attribute whose characteristics are
not known, go through these steps. First, query the file to
obtain information about the attribute such as its name,
datatype, rank, and dimensions, and then read the attribute. The
following code opens an attribute by its index value using
<code>H5Aopen_by_idx</code>, and then it reads in information about
the datatype with <code>H5Aread</code>.</p>
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="left">
<hr color="green" size="3"/>
<pre>
/*
* Attach to the string attribute using its index, then read and display the value.
*/
attr = H5Aopen_by_idx(file_id, dataset_name, index_type, iter_order, 2,
H5P_DEFAULT, H5P_DEFAULT);
atype = H5Tcopy(H5T_C_S1);
H5Tset_size(atype, 4);
ret = H5Aread(attr, atype, string_out);
printf("The value of the attribute with the index 2 is %s \n", string_out);</pre></td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left">
<b>Example 22. Read an unknown attribute
<!-- formerly Figure 25--></b>
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>In practice, if the characteristics of attributes
are not known, the code involved in accessing and processing
the attribute can be quite complex. For this reason, HDF5
includes a function called <code>H5Aiterate</code>. This function
applies a user-supplied function to each of a set of attributes.
The user-supplied function can contain the code that
interprets, accesses, and processes each attribute.</p>
<!-- NEW PAGE -->
<a name="IOPipeline">
<h3>2.3. The Data Transfer Pipeline</h3>
</a>
<!-- editingComment
<span class="editingComment">[ [ [
This section needs to be reviewed in detail by QAK and others.
] ] ]<
br><br />
[ [ [
There probably should be a whole chapter on data transfer,
selection, transformation, etc.}</em>
] ] ]</span>
-->
<p>The HDF5 Library implements data transfers between
different storage locations. At the lowest levels, the
HDF5 Library reads and writes blocks of bytes to and from
storage using calls to the virtual file layer (VFL) drivers.
In addition to this, the HDF5 Library manages caches of metadata
and a data I/O pipeline. The data I/O pipeline applies compression
to data blocks, transforms data elements, and implements selections. </p>
<p>A substantial portion of the HDF5 Library’s work is in
transferring data from one environment or media to another. This
most often involves a transfer between system memory and a storage
medium. Data transfers are affected by compression, encryption,
machine-dependent differences in numerical representation, and other
features. So, the bit-by-bit arrangement of a given dataset is
often substantially different in the two environments.</p>
<p>Consider the representation on disk of a compressed and
encrypted little-endian array as compared to the same array
after it has been read from disk, decrypted, decompressed, and loaded
into memory on a big-endian system. HDF5 performs all of the
operations necessary to make that transition during the I/O
process with many of the operations being handled by the VFL
and the data transfer pipeline.</p>
<p>The figure below <!-- formerly Figure 26 -->provides a simplified
view of a sample data transfer with four stages. Note that the
modules are used only when needed. For example, if the data is
not compressed, the compression stage is omitted.</p>
<!-- NEW PAGE -->
<table width="600" cellspacing="0" align="center">
<tr valign="top">
<td align="center">
<hr color="green" size="3"/>
<img src="Images/Pmodel_fig26.JPG" height="75%" width="95%">
</td>
</tr>
<tr><td><hr color="green" size="1" /></td></tr>
<tr valign="top">
<td align="left" >
<b>Figure 4. A data transfer from storage to memory</b>
<!-- formerly Figure 26-->
<hr color="green" size="3"/></td>
</tr>
</table>
<br />
<p>For a given I/O request, different combinations of
actions may be performed by the pipeline. The library
automatically sets up the pipeline and passes data through
the processing steps. For example, for a <em>read</em> request
(from disk to memory), the library must determine which
logical blocks contain the requested data elements and fetch
each block into the library’s cache. If the data needs to be
decompressed, then the compression algorithm is applied to
the block after it is read from disk. If the data is a selection,
the selected elements are extracted from the data block after it
is decompressed. If the data needs to be transformed (for example,
byte swapped), then the data elements are transformed after
decompression and selection.</p>
<p>While an application must sometimes set up some elements
of the pipeline, use of the pipeline is normally transparent to
the user program. The library determines what must be done
based on the metadata for the file, the object, and the
specific request. An example of when an application might be required
to set up some elements in the pipeline is if the application used
a custom error-checking algorithm. </p>
<!-- editingComment
<span class="editingComment">
For more details of the pipeline, see [citeit].</p>
</span>
-->
<p>In some cases, it is necessary to pass parameters to
and from modules in the pipeline or among other parts
of the library that are not directly called through the
programming API. This is accomplished through the use of
dataset transfer and data access property lists. </p>
<p>The VFL provides an interface whereby user applications
can add custom modules to the data transfer pipeline. For example,
a custom compression algorithm can be used with the HDF5 Library
by linking an appropriate module into the pipeline through the
VFL. This requires creating an appropriate wrapper for the
compression module
<!-- editingComment
<span class="editingComment">[ [ [
[cite filter doc and ref manual]
] ] ]</span>
-->
and registering it with the library with <code>H5Zregister</code>.
The algorithm can then be applied to a dataset with an
<code>H5Pset_filter</code> call which will add the algorithm to the
selected dataset’s transfer property list.</p>
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