© 2006 The MathWorks, Inc. Implementing HDF5 in MATLAB Jeff Mather & Alec Rogers The MathWorks, Inc. 29 November 2006
Implementing HDF5 in MATLAB
Dec 18, 2014
The MathWorks introduced MATLAB support for HDF5 in 2002 via three high-level functions: HDF5INFO, HDF5READ, and HDF5WRITE. These functions worked well for their purpose-providing simple interfaces to a complicated file format-but MATLAB users requested finer control over their HDF5 files and the HDF5 library. MATLAB 7.3 (R2006b) adds this precise level of support for version 1.6.5 of the HDF5 library via a close mapping of the HDF5 C API to MATLAB function calls.
This presentation will briefly introduce the earlier, high-level HDF5 interface (and its limitations) before showing in detail the low-level HDF5 functions. It will show how to interact with the HDF5 library and files using the thirteen classes of functions in MATLAB, which encapsulate groupings of functionality found in the HDF5 C API. But because MATLAB is itself a higher-level language than C, we will also present MATLAB's extensions and modifications of the HDF5 C API that make it more MATLAB-like, work with defined values, and perform ID and memory management.
Wrapping a library like HDF5 requires a great deal of effort and design, and we will briefly present a general-purpose mechanism for creating close mappings between library interfaces and an application like MATLAB. One of our goals in this presentation is to facilitate communication with The HDF Group about how The MathWorks builds our HDF5 interfaces in order to ease adoption of future versions of the HDF5 library in large, general-purpose applications.
This presentation will briefly introduce the earlier, high-level HDF5 interface (and its limitations) before showing in detail the low-level HDF5 functions. It will show how to interact with the HDF5 library and files using the thirteen classes of functions in MATLAB, which encapsulate groupings of functionality found in the HDF5 C API. But because MATLAB is itself a higher-level language than C, we will also present MATLAB's extensions and modifications of the HDF5 C API that make it more MATLAB-like, work with defined values, and perform ID and memory management.
Wrapping a library like HDF5 requires a great deal of effort and design, and we will briefly present a general-purpose mechanism for creating close mappings between library interfaces and an application like MATLAB. One of our goals in this presentation is to facilitate communication with The HDF Group about how The MathWorks builds our HDF5 interfaces in order to ease adoption of future versions of the HDF5 library in large, general-purpose applications.
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
© 2
006
The
Mat
hWor
ks, I
nc.
Implementing HDF5 in MATLAB
Jeff Mather & Alec Rogers
The MathWorks, Inc.
29 November 2006
2
HDF4
1-1 mapping of C API first. (1998)
Customer requests for high-level functions.
HDFREAD, HDFWRITE, HDFINFO. (2000)
3
HDF5
High-level first. (2003)
Customer requests for lower-level functionality.
1-1 mapping of C API. (2006)
4
HDF4 / HDF5 APIs
API Supported by MATLAB
Customerapplication
Customerapplication
Customerapplication
Customerapplication
The World of HDF Applications
High-level access functions
5
HDF5READ
DATA = HDF5READ(FILENAME,DATASETNAME) returns in the variable DATA all data from the file FILENAME for the data set named DATASETNAME.
DATA has to be extremely general because of the wide variety of datatypes that HDF5 accomodates.
Simple access only:● No subsetting.● Limited datatype control.
More control needed to match the uniqueness of customer datasets and files.
6
HDF5INFO
FILEINFO = HDF5INFO(FILENAME) returns a structure whose fields contain information about the contents of an HDF5 file. FILENAME is a string that specifies the name of the HDF file.
7
HDF5WRITE
HDF5WRITE(FILENAME, LOCATION, DATASET) adds the data in DATASET to the HDF5 file named FILENAME. LOCATION defines where to write the DATASET in the file and resembles a Unix-style path. The data in DATASET is mapped to HDF5 datatypes using the rules below. . . .
HDF5WRITE is completely symmetric with HDF5READ.
The values in DATASET are cumbersome for non-native MATLAB types (e.g., arrays, compound, and references).
Objects disambiguate datatypes.
8
Customer HDF5 Requests
Library upgrades (1.4.5, 1.6.4, 1.6.5, 1.8) Better support for large data Hyperselection, chunking New platform support (Solaris 64, MacIntel) GZIP, SZIP compression HDF5 file interrogation Bitfield, date/time datatypes Data translators: HDF5 --> MATLAB
9
Use Cases
Read parts of an HDF5 dataset (a hyperslab).
10
Use Cases
Read complicated datatypes without the overhead of MATLAB objects for datasets.
mydata(1).Data(1).Data(1)
11
Use Cases
Allow users to extend our HDF5 functionality without waiting for us.
12
Use Cases
Be able to drop in new versions of the HDF5 library when they become available.
HDF5 1.8
13
Use Cases
Use a variety of esoteric HDF5 features at once:
“I'm trying to use HDF5 files [with] grouping features like compound data types, group links, and reference data types.”
14
Schedule
First draft specificationSept. 2005
Feature completeMay 2006
Final specificationFeb. 2006
Internal design reviews
March 2006
Iterative development
15
MATLAB is not C
[out1, out2] = function(in1, in2);
status = function(in1, in2, &out1, &out2);
Hmm . . . I might throw an error.
MATLAB
C
16
MATLAB is not C
mxArray
void * p_realvoid * p_complexsize_t dims[]size_t ndimsmxCLASS_ID type...
...
17
The Interface
H5Xfcn
C API
H5X.fcn
MATLAB API
AD
FG
ST
...
× 12ML
hid_t identifiers
Identifier objects
Exceptions
18
Special MATLAB Functions
H5ML.compare_values
H5ML.get_constant_names
H5ML.get_constant_value
H5ML.get_function_names
H5ML.get_mem_datatype
H5ML.hoffset
H5ML.sizeof
19
Library Model
HDF5 Library
LibraryConstants
LibraryProcedures
ProceduresParameters
Datatype Conversions
Lefthand to righthand mapping
20
Implementing the HDF5 Library
Step 1: Determine auto vs. manual conversion Step 2: Convert .h to .xml Step 3: Convert XML to C++ Step 4: Code manual functions Step 5: Integrate Step 6: Test
21
The conversion process
22
Converting XML to C++
// Definition#define ADD_PROCEDURE_1_5(name,pfn,ret,a1,a2,a3,a4,a5) \ addMethod(new LibraryProcedure_1_5< LibraryParameter_T<ret>, \ LibraryParameter_T<a1>, \ LibraryParameter_T<a2>, \ LibraryParameter_T<a3>, \ LibraryParameter_T<a4>, \ LibraryParameter_T<a5> > \ (name, atts, pfn));
23
Converting XML to C++
// Usage (x ~220 functions)atts.init(0,1,5,5);atts.setParamFlags(0, ParameterAttributes::OUTPUT, 1);atts.setParamFlags(1, ParameterAttributes::INPUT | ParameterAttributes::STRING_CONVERT, 1);atts.setParamFlags(2, ParameterAttributes::INPUT, 1);atts.setParamFlags(3, ParameterAttributes::INPUT | ParameterAttributes::STRING_CONVERT, 1);atts.setParamFlags(4, ParameterAttributes::INPUT | ParameterAttributes::STRING_CONVERT, 1);atts.setParamFlags(5, ParameterAttributes::INPUT | ParameterAttributes::STRING_CONVERT, 1);ADD_PROCEDURE_1_5("H5Acreate", H5Acreate, hid_t, hid_t, const char *, hid_t, hid_t, hid_t);
24
The HDF Group and The MathWorks
Continue to communicate future directions. Don't change the existing API functions. Communicate API functionality changes. Produce a machine parsable version of hdf5.h.
25
The Future
HDF5 MAT-File
● 64-bits for large arrays● Data subsetting on load● Type conversion on load● Parallel I/O?
Related Documents
