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<TITLE>HDF5 Tutorial - Introductory Topics Questions with Answers
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<PRE>
Section 2: HDF File Organization
================================
1. Name and describe the two primary objects that can be stored in an HDF5
file:
Answer:
Group: A grouping structure containing zero or more HDF5 objects, together
with supporting metadata.
Dataset: A multidimensional array of data elements, together with
supporting metadata.
2. What is an attribute?
Answer: An HDF attribute is a user-defined HDF5 structure that provides extra
information about an HDF5 object.
3. Give the path name for an object called "harry" that is a member of a
group called "dick," which in turn is a member of the root group.
Answer: /dick/harry
Section 3: The HDF5 API
=======================
Describe the purpose of each of the following HDF5 APIs:
H5A, H5D, H5E, F5F, H5G, H5T, H5Z
H5A: Attribute access and manipulation routines.
H5D: Dataset access and manipulation routines.
H5E: Error handling routines.
F5F: File access routines.
H5G: Routines for creating and operating on groups.
H5T: Routines for creating and manipulating the datatypes of dataset elements.
H5Z: Data compression routines.
Section 4: Creating an HDF File
===============================
1. What two HDF5 routines must be called in order to create an HDF5 file?
Answer: H5Fcreate and H5Fclose.
2. What include file must be included in any file that uses the HDF5 library.
Answer: hdf5.h must be included because it contains definitions and
declarations used by the library.
3. An HDF5 file is never completely empty because as soon as an HDF5 file
is created, it automatically contains a certain primary object. What is
that object?
Answer: The root group.
Section 5: Creating a Dataset
=============================
1. Name and describe two major datatype categories.
Answer: atomic datatype - An atomic datatype cannot be decomposed into
smaller units at the API level.
compound datatype - A compound datatype is a collection of atomic/
compound datatypes, or small arrays of such types.
2. List the HDF5 atomic datatypes. Give an example of a predefined datatype.
Answer: There are six HDF5 atomic datatypes: integer, floating point,
date and time, character string, bit field, opaque.
H5T_IEEE_F32LE - 4-byte little-endian, IEEE floating point,
H5T_NATIVE_INT - native integer
3. What does the dataspace describe? What are the major characteristics of the
simple dataspace?
Answer: The dataspace describes the dimensionality of the dataset. It is
characterized by its rank and dimension sizes.
4. What information needs to be passed to the H5Dcreate function, i.e.
what information is needed to describe a dataset at creation time?
Answer: dataset location, name, dataspace, datatype, and creation properties.
Section 6: Reading from/Writing to a Dataset
============================================
1. What are six pieces of information which need to be specified for
reading and writing a dataset?
Answer: A dataset, a dataset's datatype and dataspace in memory, the
dataspace in the file, the transfer properties and data buffer.
2. Why are both the memory dataspace and file dataspace needed for
read/write operations, but only the memory datatype is specified for the
datatype?
Answer: A dataset's file datatype is specified at creation time and cannot be
changed. Both file and memory dataspaces are needed for performing
subsetting and partial I/O operations.
3. What does the line DATASPACE { SIMPLE (4 , 6 ) / ( 4 , 6 ) } in Fig 6.1
means?
Answer: It means that the dataset "dset" has a simple dataspace with the
current dimensions (4,6) and the maximum size of the dimensions (4,6).
Section 7: Creating an Attribute
================================
1. What is an attribute?
Answer: An attribute is a dataset attached to an object. It describes the
nature and/or the intended usage of the object.
2. Can partial I/O operations be performed on attributes?
Answer: No
Section 8: Creating a Group
===========================
What are the two primary objects that can be included in
a group?
Answer: A group and a dataset
Section 9: Creating Groups using Absolute/Relative Names
========================================================
1. Group names can be specified in two "ways". What are these
two types of group names that you can specify?
Answer: relative and absolute
2. You have a dataset named "moo" in the group "boo", which is
in the group "foo", which in turn, is in the root group. How would
you specify an absolute name to access this dataset?
Answer: /foo/boo/moo
Section 10: Creating Datasets in Groups
=======================================
Describe a way to access the dataset "moo" described in the previous section
(Section 9, question 2), using a relative and absolute pathname.
Answers: 1. Access the group, "/foo", and get the group ID.
Access the group "boo" using the group ID obtained in Step 1.
Access the dataset "moo" using the group ID in Step 2.
gid = H5Gopen (file_id, "/foo", 0); /* absolute path */
gid1 = H5Gopen (gid, "boo", 0); /* relative path */
did = H5Dopen (gid1, "moo"); /* relative path */
2. Access the group, "/foo", and get the group ID.
Access the dataset "boo/moo", with the group ID just obtained.
gid = H5Gopen (file_id, "/foo", 0); /* absolute path */
did = H5Dopen (gid, "boo/moo"); /* relative path */
3. Access the dataset with an absolute path.
did = H5Dopen (file_id, "/foo/boo/moo"); /* absolute path */
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