/** @page IntroHDF5 Introduction to HDF5 Navigate back: \ref index "Main" / \ref GettingStarted
\section sec_intro_desc HDF5 Description HDF5 consists of a file format for storing HDF5 data, a data model for logically organizing and accessing HDF5 data from an application, and the software (libraries, language interfaces, and tools) for working with this format. \subsection subsec_intro_desc_file File Format HDF5 consists of a file format for storing HDF5 data, a data model for logically organizing and accessing HDF5 data from an application, and the software (libraries, language interfaces, and tools) for working with this format. \subsection subsec_intro_desc_dm Data Model The HDF5 Data Model, also known as the HDF5 Abstract (or Logical) Data Model consists of the building blocks for data organization and specification in HDF5. An HDF5 file (an object in itself) can be thought of as a container (or group) that holds a variety of heterogeneous data objects (or datasets). The datasets can be images, tables, graphs, and even documents, such as PDF or Excel:
\image html fileobj.png
The two primary objects in the HDF5 Data Model are groups and datasets. There are also a variety of other objects in the HDF5 Data Model that support groups and datasets, including datatypes, dataspaces, properties and attributes. \subsubsection subsec_intro_desc_dm_group Groups HDF5 groups (and links) organize data objects. Every HDF5 file contains a root group that can contain other groups or be linked to objects in other files.
There are two groups in the HDF5 file depicted above: Viz and SimOut. Under the Viz group are a variety of images and a table that is shared with the SimOut group. The SimOut group contains a 3-dimensional array, a 2-dimensional array and a link to a 2-dimensional array in another HDF5 file.
\image html group.png
Working with groups and group members is similar in many ways to working with directories and files in UNIX. As with UNIX directories and files, objects in an HDF5 file are often described by giving their full (or absolute) path names. \li / signifies the root group. \li /foo signifies a member of the root group called foo. \li /foo/zoo signifies a member of the group foo, which in turn is a member of the root group. \subsubsection subsec_intro_desc_dm_dset Datasets HDF5 datasets organize and contain the “raw” data values. A dataset consists of metadata that describes the data, in addition to the data itself:
In this picture, the data is stored as a three dimensional dataset of size 4 x 5 x 6 with an integer datatype. It contains attributes, Time and Pressure, and the dataset is chunked and compressed.
\image html dataset.png
Datatypes, dataspaces, properties and (optional) attributes are HDF5 objects that describe a dataset. The datatype describes the individual data elements. \subsection subsec_intro_desc_props Datatypes, Dataspaces, Properties and Attributes \subsubsection subsec_intro_desc_prop_dtype Datatypes The datatype describes the individual data elements in a dataset. It provides complete information for data conversion to or from that datatype.
In the dataset depicted, each element of the dataset is a 32-bit integer.
\image html datatype.png
Datatypes in HDF5 can be grouped into: \subsubsection subsec_intro_desc_prop_dspace Dataspaces A dataspace describes the layout of a dataset’s data elements. It can consist of no elements (NULL), a single element (scalar), or a simple array.
This image illustrates a dataspace that is an array with dimensions of 5 x 3 and a rank (number of dimensions) of 2.
\image html dataspace1.png
A dataspace can have dimensions that are fixed (unchanging) or unlimited, which means they can grow in size (i.e. they are extendible). There are two roles of a dataspace: \li It contains the spatial information (logical layout) of a dataset stored in a file. This includes the rank and dimensions of a dataset, which are a permanent part of the dataset definition. \li It describes an application’s data buffers and data elements participating in I/O. In other words, it can be used to select a portion or subset of a dataset.
The dataspace is used to describe both the logical layout of a dataset and a subset of a dataset.
\image html dataspace.png
\subsubsection subsec_intro_desc_prop_property Properties A property is a characteristic or feature of an HDF5 object. There are default properties which handle the most common needs. These default properties can be modified using the HDF5 Property List API to take advantage of more powerful or unusual features of HDF5 objects.
\image html properties.png
For example, the data storage layout property of a dataset is contiguous by default. For better performance, the layout can be modified to be chunked or chunked and compressed: \subsubsection subsec_intro_desc_prop_attr Attributes Attributes can optionally be associated with HDF5 objects. They have two parts: a name and a value. Attributes are accessed by opening the object that they are attached to so are not independent objects. Typically an attribute is small in size and contains user metadata about the object that it is attached to. Attributes look similar to HDF5 datasets in that they have a datatype and dataspace. However, they do not support partial I/O operations, and they cannot be compressed or extended. \subsection subsec_intro_desc_soft HDF5 Software The HDF5 software is written in C and includes optional wrappers for C++, FORTRAN (90 and F2003), and Java. The HDF5 binary distribution consists of the HDF5 libraries, include files, command-line utilities, scripts for compiling applications, and example programs. \subsubsection subsec_intro_desc_soft_apis HDF5 APIs and Libraries There are APIs for each type of object in HDF5. For example, all C routines in the HDF5 library begin with a prefix of the form H5*, where * is one or two uppercase letters indicating the type of object on which the function operates: \li @ref H5A Attribute Interface \li @ref H5D Dataset Interface \li @ref H5F File Interface The HDF5 High Level APIs simplify many of the steps required to create and access objects, as well as providing templates for storing objects. Following is a list of the High Level APIs: \li @ref H5LT – simplifies steps in creating datasets and attributes \li @ref H5IM – defines a standard for storing images in HDF5 \li @ref H5TB – condenses the steps required to create tables \li @ref H5DS – provides a standard for dimension scale storage \li @ref H5PT – provides a standard for storing packet data \subsubsection subsec_intro_desc_soft_tools Tools Useful tools for working with HDF5 files include: \li h5dump: A utility to dump or display the contents of an HDF5 File \li h5cc, h5c++, h5fc: Unix scripts for compiling applications \li HDFView: A java browser to view HDF (HDF4 and HDF5) files

h5dump

The h5dump utility displays the contents of an HDF5 file in Data Description Language (\ref DDLBNF110). Below is an example of h5dump output for an HDF5 file that contains no objects: \code $ h5dump file.h5 HDF5 "file.h5" { GROUP "/" { } } \endcode With large files and datasets the output from h5dump can be overwhelming. There are options that can be used to examine specific parts of an HDF5 file. Some useful h5dump options are included below: \code -H, --header Display header information only (no data) -d Display a dataset with a specified path and name -p Display properties -n Display the contents of the file \endcode

h5cc, h5fc, h5c++

The built HDF5 binaries include the h5cc, h5fc, h5c++ compile scripts for compiling applications. When using these scripts there is no need to specify the HDF5 libraries and include files. Compiler options can be passed to the scripts.

HDFView

The HDFView tool allows browsing of data in HDF (HDF4 and HDF5) files. \section sec_intro_pm Introduction to the HDF5 Programming Model and APIs The HDF5 Application Programming Interface is extensive, but a few functions do most of the work. To introduce the programming model, examples in Python and C are included below. The Python examples use the HDF5 Python APIs (h5py). See the Examples from "Learning the Basics" page for complete examples that can be downloaded and run for C, FORTRAN, C++, Java and Python. The general paradigm for working with objects in HDF5 is to: \li Open the object. \li Access the object. \li Close the object. The library imposes an order on the operations by argument dependencies. For example, a file must be opened before a dataset because the dataset open call requires a file handle as an argument. Objects can be closed in any order. However, once an object is closed it no longer can be accessed. Keep the following in mind when looking at the example programs included in this section: \subsection subsec_intro_pm_file Steps to create a file To create an HDF5 file you must: \li Specify property lists (or use the defaults). \li Create the file. \li Close the file (and property lists if needed). Example:
The following Python and C examples create a file, file.h5, and then close it. The resulting HDF5 file will only contain a root group:
\image html crtf-pic.png
Calling h5py.File with ‘w’ for the file access flag will create a new HDF5 file and overwrite an existing file with the same name. “file” is the file handle returned from opening the file. When finished with the file, it must be closed. When not specifying property lists, the default property lists are used:
Python \code import h5py file = h5py.File (‘file.h5’, ‘w’) file.close () \endcode
The H5Fcreate function creates an HDF5 file. #H5F_ACC_TRUNC is the file access flag to create a new file and overwrite an existing file with the same name, and #H5P_DEFAULT is the value specified to use a default property list.
C \code #include “hdf5.h” int main() { hid_t file_id; herr_t status; file_id = H5Fcreate ("file.h5", H5F_ACC_TRUNC, H5P_DEFAULT, H5P_DEFAULT); status = H5Fclose (file_id); } \endcode
\subsection subsec_intro_pm_dataset Steps to create a dataset As described previously, an HDF5 dataset consists of the raw data, as well as the metadata that describes the data (datatype, spatial information, and properties). To create a dataset you must: \li Define the dataset characteristics (datatype, dataspace, properties). \li Decide which group to attach the dataset to. \li Create the dataset. \li Close the dataset handle from step 3. Example:
The code excerpts below show the calls that need to be made to create a 4 x 6 integer dataset dset in a file dset.h5. The dataset will be located in the root group:
\image html crtdset.png
With Python, the creation of the dataspace is included as a parameter in the dataset creation method. Just one call will create a 4 x 6 integer dataset dset. A pre-defined Big Endian 32-bit integer datatype is specified. The create_dataset method creates the dataset in the root group (the file object). The dataset is close by the Python interface.
Python \code dataset = file.create_dataset("dset",(4, 6), h5py.h5t.STD_I32BE) \endcode
To create the same dataset in C, you must specify the dataspace with the #H5Screate_simple function, create the dataset by calling #H5Dcreate, and then close the dataspace and dataset with calls to #H5Dclose and #H5Sclose. #H5P_DEFAULT is specified to use a default property list. Note that the file identifier (file_id) is passed in as the first parameter to #H5Dcreate, which creates the dataset in the root group.
C \code // Create the dataspace for the dataset. dims[0] = 4; dims[1] = 6; dataspace_id = H5Screate_simple(2, dims, NULL); // Create the dataset. dataset_id = H5Dcreate (file_id, "/dset", H5T_STD_I32BE, dataspace_id, H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); // Close the dataset and dataspace status = H5Dclose(dataset_id); status = H5Sclose(dataspace_id); \endcode
\subsection subsec_intro_pm_write Writing to or reading from a dataset Once you have created or opened a dataset you can write to it:
Python \code data = np.zeros((4,6)) for i in range(4): for j in range(6): data[i][j]= i*6+j+1 dataset[...] = data <-- Write data to dataset data_read = dataset[...] <-- Read data from dataset \endcode
#H5S_ALL is passed in for the memory and file dataspace parameters to indicate that the entire dataspace of the dataset is specified. These two parameters can be modified to allow subsetting of a dataset. The native predefined datatype, #H5T_NATIVE_INT, is used for reading and writing so that HDF5 will do any necessary integer conversions:
C \code status = H5Dwrite (dataset_id, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, dset_data); status = H5Dread (dataset_id, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, dset_data); \endcode
\subsection subsec_intro_pm_group Steps to create a group An HDF5 group is a structure containing zero or more HDF5 objects. Before you can create a group you must obtain the location identifier of where the group is to be created. Following are the steps that are required: \li Decide where to put the group – in the “root group” (or file identifier) or in another group. Open the group if it is not already open. \li Define properties or use the default. \li Create the group. \li Close the group.
Creates attributes that are attached to the dataset dset
\image html crtgrp.png
The code below opens the dataset dset.h5 with read/write permission and creates a group MyGroup in the root group. Properties are not specified so the defaults are used:
Python \code import h5py file = h5py.File('dset.h5', 'r+') group = file.create_group ('MyGroup') file.close() \endcode
To create the group MyGroup in the root group, you must call #H5Gcreate, passing in the file identifier returned from opening or creating the file. The default property lists are specified with #H5P_DEFAULT. The group is then closed:
C \code group_id = H5Gcreate (file_id, "MyGroup", H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); status = H5Gclose (group_id); \endcode
\subsection subsec_intro_pm_attr Steps to create and write to an attribute To create an attribute you must open the object that you wish to attach the attribute to. Then you can create, access, and close the attribute as needed: \li Open the object that you wish to add an attribute to. \li Create the attribute \li Write to the attribute \li Close the attribute and the object it is attached to.
Creates attributes that are attached to the dataset dset
\image html crtatt.png
The dataspace, datatype, and data are specified in the call to create an attribute in Python:
Python \code dataset.attrs["Units"] = “Meters per second” <-- Create string attr_data = np.zeros((2,)) attr_data[0] = 100 attr_data[1] = 200 dataset.attrs.create("Speed", attr_data, (2,), “i”) <-- Create Integer \endcode
To create an integer attribute in C, you must create the dataspace, create the attribute, write to it and then close it in separate steps:
C \code hid_t attribute_id, dataspace_id; // identifiers hsize_t dims; int attr_data[2]; herr_t status; ... // Initialize the attribute data. attr_data[0] = 100; attr_data[1] = 200; // Create the data space for the attribute. dims = 2; dataspace_id = H5Screate_simple(1, &dims, NULL); // Create a dataset attribute. attribute_id = H5Acreate2 (dataset_id, "Units", H5T_STD_I32BE, dataspace_id, H5P_DEFAULT, H5P_DEFAULT); // Write the attribute data. status = H5Awrite(attribute_id, H5T_NATIVE_INT, attr_data); // Close the attribute. status = H5Aclose(attribute_id); // Close the dataspace. status = H5Sclose(dataspace_id); \endcode

Navigate back: \ref index "Main" / \ref GettingStarted @page HDF5Examples HDF5 Examples Example programs of how to use HDF5 are provided below. For HDF-EOS specific examples, see the examples of how to access and visualize NASA HDF-EOS files using Python, IDL, MATLAB, and NCL on the HDF-EOS Tools and Information Center page. \section secHDF5Examples Examples \li \ref LBExamples \li Examples by API \li Examples in the Source Code \li Other Examples \section secHDF5ExamplesCompile How To Compile For information on compiling in C, C++ and Fortran, see: \ref LBCompiling \section secHDF5ExamplesOther Other Examples IDL, MATLAB, and NCL Examples for HDF-EOS Examples of how to access and visualize NASA HDF-EOS files using IDL, MATLAB, and NCL. Miscellaneous Examples These (very old) examples resulted from working with users, and are not fully tested. Most of them are in C, with a few in Fortran and Java. Using Special Values These examples show how to create special values in an HDF5 application. */