ee509ff4f3
corresponding HDF5 operations. re: github issue https://github.com/Unidata/netcdf-c/issues/908 also in reference to https://github.com/pydata/xarray/issues/2004 The netcdf-c library has implemented the nc_get_vars and nc_put_vars operations as element at a time. This has resulted in very slow operation. This pr attempts to improve the situation for netcdf-4/hdf5 files by using the slab operations provided by the hdf5 library. The new implementation passes the get/put vars stride information down to the hdf5 slab operations. The result appears to improve performance significantly. Some simple tests on large 2-D arrays shows speedups in excess of 150. Misc. other changes: 1. fix bug in ncgen/semantics.c; using a list's allocated length instead of actual length. 2. Added a temporary hook in the netcdf library plus a performance test case (tst_varsperf.c) to estimate the speedup. After users have had some experience with this, I will remove it, probably after the 4.7 release.
Unidata NetCDF
About
The Unidata network Common Data Form (netCDF) is an interface for scientific data access and a freely-distributed software library that provides an implementation of the interface. The netCDF library also defines a machine-independent format for representing scientific data. Together, the interface, library, and format support the creation, access, and sharing of scientific data. The current netCDF software provides C interfaces for applications and data. Separate software distributions available from Unidata provide Java, Fortran, Python, and C++ interfaces. They have been tested on various common platforms.
Properties
NetCDF files are self-describing, network-transparent, directly
accessible, and extendible. Self-describing means that a netCDF file
includes information about the data it contains. Network-transparent
means that a netCDF file is represented in a form that can be accessed
by computers with different ways of storing integers, characters, and
floating-point numbers. Direct-access means that a small subset of a
large dataset may be accessed efficiently, without first reading through
all the preceding data. Extendible means that data can be appended to
a netCDF dataset without copying it or redefining its structure.
Use
NetCDF is useful for supporting access to diverse kinds of scientific data in heterogeneous networking environments and for writing application software that does not depend on application-specific formats. For information about a variety of analysis and display packages that have been developed to analyze and display data in netCDF form, see
More information
For more information about netCDF, see
Latest releases
You can obtain a copy of the latest released version of netCDF software for various languages:
Copyright
Copyright and licensing information can be found here, as well as in the COPYRIGHT file accompanying the software
Installation
To install the netCDF-C software, please see the file INSTALL in the netCDF-C distribution, or the (usually more up-to-date) document:
Documentation
A language-independent User's Guide for netCDF, and some other language-specific user-level documents are available from:
- Language-independent User's Guide
- NetCDF-C Tutorial
- Fortran-90 User's Guide
- Fortran-77 User's Guide
- netCDF-Java/Common Data Model library
- netCDF4-python
A mailing list, netcdfgroup@unidata.ucar.edu, exists for discussion of the netCDF interface and announcements about netCDF bugs, fixes, and enhancements. For information about how to subscribe, see the URL
Feedback
We appreciate feedback from users of this package. Please send comments, suggestions, and bug reports to support-netcdf@unidata.ucar.edu.