Just thought I'd provide this fyi of hdf5 to the community. As an aside, These are interesting times with the impact of the new Numpy/Scipy and it's revitalized, communitized development. I look forward to the near future when I'll have the time to assist the Carabos crew in development of some of the hdf5 features (and datamining technique modules, etc., maybe?) not yet provided in PyTables. My respects to the crew.
Dieter. xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx http://hdf.ncsa.uiuc.edu/newsletters/newsletter87.html -------------------------------------------------------------------------- To subscribe/unsubscribe to the hdfnews mailing list, please send your request to [EMAIL PROTECTED] with the appropriate command (e.g. subscribe hdfnews, unsubscribe hdfnews, help) in the *body* of the message. -------------------------------------------------------------------------- Newsletter #87 April 20, 2006 CONTENTS ******************************* . Release of HDF5 1.8.0 Alpha 1 * * - New Features * Visit the HDF home page * * for up-to-date information * * * * http://hdf.ncsa.uiuc.edu/ * * * ******************************* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Release of HDF5 1.8.0 Alpha 1 ============================= The Alpha 1 release of HDF5 1.8.0 is now available from: http://hdf.ncsa.uiuc.edu/HDF5/release/alpha/obtain518.html Please note that this is an alpha release and not a formal release. We are making this available for users who are interested in trying out new features in the HDF5 1.8.0 release. The 1.8.0 release represents a major update in the HDF5 library and utilities. Many new capabilities have been added, along with improved performance. However, the HDF5 1.8.0 Alpha 1 release does NOT include all functions that will be in the final 1.8.0 release, and some features (function names, behavior) MAY CHANGE before the final 1.8.0 release. In this release: - Not all features are included. - Not all platforms have been tested. - The backward and forward compatibility of the software has NOT been tested. New Features ------------ The new features available in HDF5 1.8.0 are described here. To obtain more information about these new features, be sure to read the "What's New in HDF5 1.8.0-alpha1" document located at: http://hdf.ncsa.uiuc.edu/HDF5/doc_1.8pre/WhatsNew180.html The "What's New in HDF5 1.8.0-alpha1" document also includes information about features in the Alpha 1 release that may change, as well as features that are not yet in the Alpha 1 release, but will be in the final 1.8.0 release. The following features are stable and available in HDF5 1.8.0-alpha 1: o Collective Chunk I/O in Parallel: The library now attempts to use the MPI collective mode when performing I/O on chunked datasets when using the parallel I/O file driver. o New Chunked Dataset Filters: These new I/O filters allow better compression of certain types of data: - N-Bit Filter: This filter compresses data which uses N-bit datatypes. - Scale+Offset Filter: This filter compresses scalar (integer and floating-point) datatypes that stay within a range. o Transforms on Data Transfer: This feature allows arithmetic operations (add/subtract/multiply/divide) to be performed on data elements as they are being written to/read from a file. o Text-to-datatype and datatype-to-text conversions: This feature enables the creation of a datatype from a text definition of that datatype and the creation of a formal text definition from a datatype. The text definition is in DDL format. H5LTtext_to_dtype() creates an HDF5 datatype based on a text description and returns a datatype identifier. Given a datatype identifier, H5LTdtype_to_text() creates a DDL description of a datatype. o Support for Integer-to-Floating-point Conversion: It is now possible for the HDF5 library to convert between integer and floating-point datatypes. o Revised Datatype Conversion Exception Handling: It is now possible for an application to have greater control over exceptional circumstances (range errors, etc.) during datatype conversion. o Serialized Datatypes and Dataspaces: A set of routines has been added to serialize or deserialize HDF5 datatypes and dataspaces. These routines allow datatype and dataspace information to be transmitted between processes or stored in non-HDF5 files. o NULL Dataspace: A new type of dataspace has been added, which allows datasets without any elements to be described. o Extendible ID API: A new set of ID management routines has been added, which allows an application to use the HDF5 ID-to-object mapping routines. o Re-implementation of the Metadata Cache: The metadata cache has been re-implemented to reduce the cache memory requirements when working with complex HDF5 files and to improve performance. New functions have also been added for managing the metadata cache. o High-Level Fortran APIs: Fortran APIs have been added for HDF5 Lite (H5LT), HDF5 Image (H5IM), and HDF5 Table (H5TB). o New High-Level APIs: A Packet Table API has been added to the high-level interfaces. These routines are designed to allow variable-length records to be added to tables easily. o A Dimension Scales API has been added to the high-level interfaces. o Tool Improvements: One new tool has been added, and existing tools were enhanced. - h5stat, a new tool, is still in development and may change. It allows HDF5 files to be analyzed in various ways to determine useful statistics about objects in the file. - Improved speed of h5dump: Performance improvements have been made to h5dump to speed it up when dealing with files that have large numbers of objects. o Better UNIX/Linux Portability: This release now uses the latest GNU auto tools (autoconf, automake, and libtool) to provide much better portability between many machine and OS configurations. Building the HDF5 distribution can now be performed in parallel (with the gmake "-j" flag), speeding up the process of building, testing and installing the HDF5 distribution. Many other improvements have gone into the build infrastructure as well. ------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid0709&bid&3057&dat1642 _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
