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DOE OSTI2014

VERAOUT - VERA HDF5 Output Specification (Revision 1)

This document describes the revised specification (Revision 1) for the format of the common VERA Output file (VERAOUT). VERAOUT is a binary HDF5 file that all of the physics codes in VERA-CS produce. Having all physics codes write to a single file simplifies post-processing and data comparison. The edits and format written to the VERAOUT file is described below. This specification covers common scalar and array data typically produced by neutronic and fuel performance codes. This document will be periodically revised to add additional data as more physics codes and/or more data is added to VERA-CS. A version number is written to the HDF file to keep track of different versions of the VERAOUT so that backwards compatibility may be maintained. A sample VERAOUT reader has been written to serve as an example for users wishing to do data postprocessing. Information on this program is included below.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Converting the MCNP Runtape to HDF5

The current runtape in MCNP is a Fortran unformatted IO dump of approximately 800 variables used for restarting an MCNP simulation. This format has a number of technical issues for those who interact with it. First, Fortran unformatted IO is not guaranteed to be portable. As a result, a runtape generated on one machine is not necessarily readable on another. Second, for users who wish to extract data from the runtape, there is no simple approach. It is impossible to extract one variable without knowing the size and position of every other one. Finally, the runtape itself is not backwards compatible such that a future version of MCNP could open it. Users are expected to keep around versions of MCNP that are compatible with saved runtapes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Simplifying Analysis of Hierarchical HDF5 and NetCDF4 Files with Xarray-Datatree

NASA’s Earth Observing System Data and Information System (EOSDIS) contains thousands of Earth science datasets from satellites, models, and field campaigns. EOSDIS data are stored in formats that are well supported by the Earth Science community. These formats include the Hierarchical Data Format (HDF), with derivative flavors such as HDF-5 and the Network Common Data Format (NetCDF-4). The HDF specification allows for a directory-like hierarchy within a single file, known as "groups". Observational data and associated metadata within a single file can be distributed amongst multiple internal groups, which can also be nested to multiple levels. Working with datasets that have a group hierarchical structure can be difficult because of the nested structure of groups. Widely used packages, such as xarray, have data models that do not accommodate the hierarchical structure within HDF files, requiring users to traverse the file and open different HDF groups as separate, unrelated objects. Xarray-datatree is a Python package developed to solve the difficulty of traversing HDFs with a hierarchical group structure by creating a tree-like hierarchical data structure in xarray. The tree-like structure allows each group to be accessed once a DataTree object is instantiated. The migration of xarray-datatree into the xarray core library will reduce barriers to accessing Earth science data by eliminating the need to understand and traverse the specific hierarchy of a grouped HDF file.

Eni Awowale↗