NetCDF and HDF5
Download as PPT, PDF2 likes7,102 views
NetCDF and HDF5 are data formats and software libraries used for scientific data. NetCDF began in 1989 and allows for array-oriented data with dimensions, variables, and attributes. NetCDF-4 introduced new features while maintaining backward compatibility. It uses HDF5 for data storage and can read HDF4/HDF5 files. NetCDF provides APIs for C, Fortran, Java, and is widely used for earth science and climate data. It supports conventions, parallel I/O, and reading many data formats.
![Using OPeNDAP Client
In order to access DAP data sources, you
need a special format URL:
[limit=5]http://test.opendap.org/dods/dts/te
st.32.X?windW[0:10:2]&CS02.light>
Location of data source and its part, where
X is one of "dds", "das", or "dods"
Constraints on what part of the data source
is to be sent.](https://image.slidesharecdn.com/netcdf4tutorialws14-140217091014-phpapp01/85/NetCDF-and-HDF5-11-320.jpg)
![Parallel I/O C Example
nc_create_par(FILE, NC_NETCDF4|NC_MPIIO, comm, info,
&ncid);
nc_def_dim(ncid, "d1", DIMSIZE, dimids);
nc_def_dim(ncid, "d2", DIMSIZE, &dimids[1]);
nc_def_var(ncid, "v1", NC_INT, NDIMS, dimids, &v1id);
/* Set up slab for this process. */
start[0] = mpi_rank * DIMSIZE/mpi_size;
start[1] = 0; count[0] = DIMSIZE/mpi_size;
count[1] = DIMSIZE;
nc_var_par_access(ncid, v1id, NC_INDEPENDENT);
nc_put_vara_int(ncid, v1id, start, count,
&data[mpi_rank*QTR_DATA]);](https://image.slidesharecdn.com/netcdf4tutorialws14-140217091014-phpapp01/85/NetCDF-and-HDF5-29-320.jpg)
![C API
nc_create(FILE_NAME, NC_CLOBBER, &ncid);
nc_def_dim(ncid, "x", NX, &x_dimid);
nc_def_dim(ncid, "y", NY, &y_dimid);
dimids[0] = x_dimid;
dimids[1] = y_dimid;
nc_def_var(ncid, "data", NC_INT, NDIMS,
dimids, &varid);
nc_enddef(ncid);
nc_put_var_int(ncid, varid, &data_out[0][0]);
nc_close(ncid);](https://image.slidesharecdn.com/netcdf4tutorialws14-140217091014-phpapp01/85/NetCDF-and-HDF5-31-320.jpg)
NetCDF and HDF5
- 1. NetCDF and HDF5 Ed Hartnett, Unidata/UCAR, 2010
- 2. Unidata • Mission: To provide the data services, tools, and cyberinfrastructure leadership that advance Earth system science, enhance educational opportunities, and broaden participation.
- 3. Unidata Software • NetCDF – data format and libraries. • NetCDF-Java/common data model – reads many data formants (HDF5, HDF4, GRIB, BUFR, many more). • THREDDS – Data server for cataloging and serving data. • IDV – Integrated Data Viewer • IDD/LDM – Peer to peer data distribution. • UDUNITS – Unit conversions.
- 4. What is NetCDF? NetCDF is a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. First released in 1989. NetCDF-4.0 (June, 2008) introduces many new features, while maintaining full code and data compatibility.
- 5. The NetCDF-4 Project • Does not indicate any lack of commitment or compatibility for classic formats. • Uses HDF5 as data storage layer. • Also provides read-only access to some HDF4, HDF5 archives. • Parallel I/O for high performance computing.
- 8. Commitment to Backward Compatibility Because preserving access to archived data for future generations is sacrosanct: • NetCDF-4 provides both read and write access to all earlier forms of netCDF data. • Existing C, Fortran, and Java netCDF programs will continue to work after recompiling and relinking. • Future versions of netCDF will continue to support both data access compatibility and API compatibility.
- 9. Who Uses NetCDF? • NetCDF is widely used in University Earth Science community. • Used for IPCC data sets. • Used by NASA and other large data producers.
- 10. The OPeNDAP Client OPenDAP (http://www.opendap.org/) is a widely supported protocol for access to remote data Defined and maintained by the OPenDAP organization Designed to serve as intermediate format for accessing a wide variety of data sources. Client is now built into netCDF C library.
- 11. Using OPeNDAP Client In order to access DAP data sources, you need a special format URL: [limit=5]http://test.opendap.org/dods/dts/te st.32.X?windW[0:10:2]&CS02.light> Location of data source and its part, where X is one of "dds", "das", or "dods" Constraints on what part of the data source is to be sent.
- 12. NetCDF Data Models The netCDF data model, consisting of variables, dimensions, and attributes (the classic model), has been expanded in version 4.0. The enhanced 4.0 model adds expandable dimensions, strings, 64-bit integers, unsigned integers, groups and user-defined types. The 4.0 release also adds some features that need not use the enhanced model, like compression, chunking, endianness control, checksums, parallel I/O.
- 13. NetCDF Classic Model • Contains dimensions, variables, and attributes.
- 15. Enhanced Model
- 16. NetCDF Enhanced Model A netCDF-4 file can organize variable, dimensions, and attributes in groups, which can be nested. Attribute Attribute Attribute Attribute Attribute Attribute Attribute Attribute Variable Attribute Attribute Attribute Attribute Variable Variable Attribute Attribute Variable Attribute Attribute Variable
- 17. Reasons to Use Classic Model • Provides compatibility with existing netCDF programs. • Still possible to use chunking, parallel I/O, compression, endianness control. • Simple and powerful data model.
- 18. Accessing HDF5 Data with NetCDF NetCDF (starting with version 4.1) provides read-only access to existing HDF5 files if they do not violate some rules: Must not use circular group structure. HDF5 reference type (and some other more obscure types) are not understood. Write access still only possible with netCDF4/HDF5 files.
- 19. Reading HDF5 with NetCDF Before netCDF-4.1, HDF5 files had to use creation ordering and dimension scales in order to be understood by netCDF-4. Starting with netCDF-4.1, read-only access is possible to HDF5 files with alphabetical ordering and no dimension scales. (Created by HDF5 1.6 perhaps.) HDF5 may have dimension scales for all dimensions, or for no dimensions (not for just some of them).
- 20. Accessing HDF4 Data with NetCDF Starting with version 4.1, netCDF will be able to read HDF4 files created with the “Scientific Dataset” (SD) API. This is read-only: NetCDF can't write HDF4! The intention is to make netCDF software work automatically with important HDF4 scientific data collections.
- 21. Confusing: HDF4 Includes NetCDF v2 API •A netCDF V2 API is provided with HDF4 which writes SD data files. • This must be turned off at HDF4 install-time if netCDF and HDF4 are to be linked in the same application. • There is no easy way to use both HDF4 with netCDF API and netCDF with HDF4 read capability in the same program.
- 22. Building NetCDF for HDF5/HDF4 Access This is only available for those who also build netCDF with HDF5. HDF4, HDF5, zlib, and other compression libraries must exist before netCDF is built. Build like this: ./configure –with-hdf5=/home/ed –enable-hdf4
- 23. Building User Programs with HDF5/HDF4 Access Include locations of netCDF, HDF5, and HDF4 include directories: -I/loc/of/netcdf/include -I/loc/of/hdf5/include -I/loc/of/hdf4/include The HDF4 and HDF5 libraries (and associated libraries) are needed and must be linked into all netCDF applications. The locations of the lib directories must also be provided: -L/loc/of/netcdf/lib -L/loc/of/hdf5/lib -L/loc/of/hdf4/lib -lmfhdf -ldf -ljpeg -lhdf5_hl -lhdf5 -lz
- 24. Using HDF4 You don't need to identify the file as HDF4 when opening it with netCDF, but you do have to open it read-only. The HDF4 SD API provides a named, shared dimension, which fits easily into the netCDF model. The HDF4 SD API uses other HDF4 APIs, (like vgroups) to store metadata. This can be confusing when using the HDF4 data dumping tool hdp.
- 25. HDF4 MODIS File ncdumped ../ncdump/ncdump -h MOD29.A2000055.0005.005.2006267200024.hdf netcdf MOD29.A2000055.0005.005.2006267200024 { dimensions: Coarse_swath_lines_5km:MOD_Swath_Sea_Ice = 406 ; Coarse_swath_pixels_5km:MOD_Swath_Sea_Ice = 271 ; Along_swath_lines_1km:MOD_Swath_Sea_Ice = 2030 ; Cross_swath_pixels_1km:MOD_Swath_Sea_Ice = 1354 ; variables: float Latitude(Coarse_swath_lines_5km:MOD_Swath_Sea_Ice, Coarse_swath_pixels_5km:MOD_Swath_Sea_Ice) ; Latitude:long_name = "Coarse 5 km resolution latitude" ; Latitude:units = "degrees" ; ...
- 26. Accessing HDF4-EOS Data with NetCDF • Data can be read, but netCDF does not (yet) understand how to break down the StructMetadata attribute into useful information. // global attributes: :HDFEOSVersion = "HDFEOS_V2.9" ; :StructMetadata.0 = "GROUP=SwathStructurentGROUP=SWATH_1nttSwathNam e="MOD_Swath_Sea_Ice"nttGROUP=DimensionntttOBJE CT=Dimension_1nttttDimensionName="Coarse_swath_lines _5km"nttttSize=406ntttEND_OBJECT=Dimension_1nttt OBJECT=Dimension_2nttttDimensionName="Coarse_swath _pixels_5km"nttttSize=271nttt...
- 27. Contribute Code to Write HDF4? Some programmers use the netCDF v2 API to write HDF4 files. It would not be too hard to write the glue code to allow the v2 API -> HDF4 output from the netCDF library. The next step would be to allow netCDF v3/v4 API code to write HDF4 files. Writing HDF4 seems like a low priority to our users. I would be happy to help any user who would like to undertake this task.
- 28. Parallel I/O with NetCDF • Parallel I/O allows many processes to read/write netCDF data at the same time. • Used properly, parallel I/O allows users to overcome I/O bottlenecks in high performance computing environments. • A parallel I/O file system is required for much improvement in I/O throughput. • NetCDF-4 can use parallel I/O with netCDF4/HDF5 files, or netCDF classic files (with pnetcdf library).
- 29. Parallel I/O C Example nc_create_par(FILE, NC_NETCDF4|NC_MPIIO, comm, info, &ncid); nc_def_dim(ncid, "d1", DIMSIZE, dimids); nc_def_dim(ncid, "d2", DIMSIZE, &dimids[1]); nc_def_var(ncid, "v1", NC_INT, NDIMS, dimids, &v1id); /* Set up slab for this process. */ start[0] = mpi_rank * DIMSIZE/mpi_size; start[1] = 0; count[0] = DIMSIZE/mpi_size; count[1] = DIMSIZE; nc_var_par_access(ncid, v1id, NC_INDEPENDENT); nc_put_vara_int(ncid, v1id, start, count, &data[mpi_rank*QTR_DATA]);
- 30. NetCDF APIs The netCDF core library is written in C and Java. Fortran 77 is “faked” when netCDF is built – actually C functions are called by Fortran 77 API. A C++ API also calls the C API, a new C++ API us under development to support netCDF4 more fully.
- 31. C API nc_create(FILE_NAME, NC_CLOBBER, &ncid); nc_def_dim(ncid, "x", NX, &x_dimid); nc_def_dim(ncid, "y", NY, &y_dimid); dimids[0] = x_dimid; dimids[1] = y_dimid; nc_def_var(ncid, "data", NC_INT, NDIMS, dimids, &varid); nc_enddef(ncid); nc_put_var_int(ncid, varid, &data_out[0][0]); nc_close(ncid);
- 32. Fortran API call check( nf90_create(FILE_NAME, NF90_CLOBBER, ncid) ) call check( nf90_def_dim(ncid, "x", NX, x_dimid) ) call check( nf90_def_dim(ncid, "y", NY, y_dimid) ) dimids = (/ y_dimid, x_dimid /) call check( nf90_def_var(ncid, "data", NF90_INT, dimids, varid) ) call check( nf90_enddef(ncid) ) call check( nf90_put_var(ncid, varid, data_out) ) call check( nf90_close(ncid) )
- 33. New C++ API (cxx4) Existing C++ API works with netCDF-4 classic model files. The existing API was written before many features of C++ became standard, and thus needed updating. A new C++ API has been partially developed . You can build the new API (which is not complete!) with --enable-cxx4.
- 34. Java API dataFile = NetcdfFileWriteable.createNew(filename, false); // Create netCDF dimensions, Dimension xDim = dataFile.addDimension("x", NX ); Dimension yDim = dataFile.addDimension("y", NY ); ArrayList dims = new ArrayList(); // define dimensions dims.add( xDim); dims.add( yDim); ...
- 35. Tools • ncdump – ASCII or NcML dump of data file. • ncgen – Take ASCII or NcML and create data file. • nccopy – Copy a file, changing format, compression, chunking, etc.
- 36. Conventions The NetCDF User's Guide recommends some conventions (ex. "units" and "Conventions" attributes). Conventions are published agreements about how data of a particular type should be represented to foster interoperability. Most conventions use attributes. Use of an existing convention is highly recommended. Use the CF Conventions, if applicable. A netCDF file should use the global "Conventions" attribute to identify which conventions it uses.
- 37. Climate and Forecast Conventions The CF Conventions are becoming a widely used standard for atmospheric, ocean, and climate data. The NetCDF Climate and Forecast (CF) Metadata Conventions, Version 1.3, describes consensus representations for climate and forecast data using the netCDF-3 data model.
- 38. LibCF − The NetCDF CF Library supports the creation of scientific data files conforming to the CF conventions, using the netCDF API. − Now distributed with netCDF. − Now home of GRIDSPEC: A standard for the description of grids used in Earth System models, developed by V. Balaji, GFDL, proposed as a Climate and Forecast (CF) convention.
- 39. UDUNITS The Unidata units library, udunits, supports conversion of unit specifications between formatted and binary forms, arithmetic manipulation of unit specifications, and conversion of values between compatible scales of measurement. Now being distributed with netCDF.
- 40. NetCDF 4.1.2 Release • Performance improvements: much faster file opens (factor of 200 speedup). • Better memory handling, much better testing for leaks and memory errors in netCDF and HDF5. • nccopy now can compress and re-chunk data. • Refactoring of dispatch layer (invisible to user).
- 41. NetCDF Future Plans • By “plans” we really mean “aspirations.” • We us agile programming, with aggressive refactoring, and heavy reliance on automatic testing. • Our highest priority is fixing bugs so that we do not have a bug-list to maintain and prioritize.
- 42. Plans: Fortran Refactor • We plan a complete Fortran re-factor within the next year. • Fortan 90 and Fortran 77 backward compatibility will be preserved. No user code will need to be rewritten. • Fortan 90 compilers will be required (even for F77 API code). Fortran 77 compilers will not work with netCDF releases after the refactor. • Fortran 90 API will be rewritten with Fortran 2003 C interoperability features. Fortran 77 API will be rewritten in terms of Fortran 90 API.
- 43. Plans: Windows Port • Recent refactoring of netCDF architecture requires (yet another) Windows port. This is planned for the end of 2010. • Windows ports are not too hard, but require a detailed knowledge of Microsoft's latest changes and developments of the Windows platform. • I invite collaboration with any Windows programmer who would like to help with the Windows port.
- 44. Plans: Virtual Files • There are some uses (including LibCF/GRIDSPEC) for disk-less netCDF files – that is, files which exist only in memory. • I am experimenting with this now – interested users should contact me at: ed@unidata.ucar.edu
- 45. Plans: More Formats • The NetCDF Java library can read many formats that are a mystery to the C-based library. • Recent refactoring of the netCDF architecture makes it easier to support additional formats. • We would like to support GRIB and BUFR next. We seek collaboration with interested users.
- 46. NetCDF Team – Russ Rew • Vision. • nccopy • classic library
- 47. NetCDF Team – Ed Hartnett • • • • • NetCDF-4 Release engineering Parallel I/O LibCF Fortran libraries
- 48. NetCDF Team – Dennis Heimbigner • Opendap client. • New ncdump/ncgen • Some netCDF-Java
- 49. NetCDF Team – John Caron • NetCDF-Java • Common Data Model
- 50. Support Send bug reports to: support-netcdf@unidata.ucar.edu Your support email will enter a support tracking system which will ensure that it does not get lost. But it may take us a while to solve your problem...
- 51. Snapshot Releases and Daily Testing • Automatic daily test runs at Unidata ensure that our changes don't break netCDF. • Test results available on-line at NetCDF web site. • Daily snapshot release provided so users can get latest code, and iterate fixes with netCDF developers.
- 52. NetCDF Workshop • Annual netCDF workshop is a good place to learn the latest developments in netCDF, and talk to netCDF developers. • October 28-29, 2010, and swanky Mesa Lab at NCAR – great views, mountain trails, without the usual riffraff. • Preceded by data format summit.