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The WIND Toolkit Highly Scalable Data Service (HSDS) API examples provide example python software notebooks (software) and a javascript visualization that demonstrate use of the HDF Group's HSDS API utilizing data for NREL's WIND Toolkit.
QnD is a pure Python package for working with binary files. It has built-in support for HDF5, NetCDF3, and PDB formats. It provides a Pythonic, dict-like interface, and allows easy movement among time-like "records". Both reading and writing are enabled. The HDF and NetCDF capabilities rely on external libraries, while the PDB support is part of QnD itself and entirely in Python. QnD works under Python 2 and 3. For interactive use, much less typing is involved than for some other packages.
This dataset comprises of the input files and other files required for Advanced Terrestrial Simulator (ATS) simulations at 7 catchments across the continental United States. ATS is an integrated surface-subsurface hydrology model. We include Jupyter notebooks (within scripts folder) for individual catchments showing information (including data sources, river network, soil, geology, landuse types etc.) on preparing the machine readable input files. ATS observation output files are provided in the output folder. Figures and analyses (.xlsx sheets) are also provided. The catchments include, Taylor River Upstream (Colorado); (b) Cossatot River (Arkansas); (c) Panther Creek (Alabama); (d) Little Tennessee River (North Carolina and Georgia); (e) Mayo River (Virginia); (f) Flat Brook (New Jersey); (g) Neversink River headwaters (New York). Readme files are provided inside the directories providing more details. Files types include: .xml, .h5, .xlsx, .png, .ipynb, .py, .nc, .txt. All of the files types can be accessed by open source software, details on software requirements are following: .xml (any text editors including notepad and textedit), .h5 (in python using hdf libraries), .xlsx (WPS Office Spreadsheets, OpenOffice Calc, LibreOffice Calc, Microsoft Office etc.), .png (any image viewer), .ipynb (Jupyter notebook), .py (any text editors including notepad and textedit), .nc (using python or other open source software).
Fiber optic files in *.hdf format, acquired in the Devine Fracture Pilot Site East well, using Fotech interrogator. There was no change in channel spacing or acquisition settings during the project. Channel spacing is 0.68 m.
Delta-Rice is an HDF5 (The HDF Group et al., 2020) filter plugin that was developed to compress digitized detector signals recorded by the Nab experiment (Fry et al., 2019), a fundamental neutron physics experiment. This is a two-step process where incoming data is passed through a pre-processing filter and then compressed with Rice coding. A routine for determining the optimal pre-processing filter for a dataset is provided along with an example GPU deployment. When applied to data collected by the Nab data acquisition system, this method produced output files 29% their initial size, and was able to do so with an average read/write throughput in excess of 2 GB/s on a single CPU. Compared to the widely used Gzip compression routine, Delta-Rice reduces the file size by 33% more with over an order of magnitude increase in read/write throughput. Delta-Rice is available on CPU to users through the HDF5 library.
VERAIO is a set of utility codes used to provide a common set of input and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA HDF output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the Quality Assurance Program Plan (QAPP) (VERA-QA-001), and VERA Software Quality Assurance Plan (VERA-QA-002).
VERAIO is a set of utility codes used to provide a common set of inputs and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes, so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA hierarchical data format (HDF) output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the quality assurance program plan (QAPP) (VERA-QA-001) and the VERA Software Quality Assurance Plan (VERA-QA-002).
This report documents the work performed to address several defects and features request related to the restart capability in MPACT. The following defects were fixed as a part of this milestone: • #3616 (Defect) Error in MPACT Restart Files with BPRs, • #3637 (Defect) Restart with Semi-PC Yields Inconsistent Results, • #3652 (Defect) Fix Incorrect Exposure Value on HDF File After Restart, • #3777 (Defect) Fix State Point Number when Using Restart File, • #3986 (Defect) Pin Exposures are Incorrect, • #4106 (Defect) Pin Exposures Equal to Zero After Restart, and • #4288 (Defect) Core Average Exposure Wrong when Reading Restart Files. The new features that were added are: • Axial Re-meshing capability, • Incorporation of MAMBA-1D data necessary to restart coupled MPACT/CTF/MAMBA calculations, and • Addition of state variables to the restart file. Numerous tests were also implemented to verify and protect these features and this report was prepared to document the work performed.
We present an extremely deep CO(1–0) observation of a confirmed z = 1.62 galaxy cluster. We detect two spectroscopically confirmed cluster members in CO(1–0) with signal-to-noise ratio >5. Both galaxies have log(M{sub ⋆}/M{sub ⊙}) > 11 and are gas rich, with M{sub mol}/(M{sub ⋆}+M{sub mol}) ∼ 0.17–0.45. One of these galaxies lies on the star formation rate (SFR)–M{sub ⋆} sequence, while the other lies an order of magnitude below. We compare the cluster galaxies to other SFR-selected galaxies with CO measurements and find that they have CO luminosities consistent with expectations given their infrared luminosities. We also find that they have gas fractions and star formation efficiencies (SFE) comparable to what is expected from published field galaxy scaling relations. The galaxies are compact in their stellar light distribution, at the extreme end for all high-redshift star-forming galaxies. However, their SFE is consistent with other field galaxies at comparable compactness. This is similar to two other sources selected in a blind CO survey of the HDF-N. Despite living in a highly quenched protocluster core, the molecular gas properties of these two galaxies, one of which may be in the process of quenching, appear entirely consistent with field scaling relations between the molecular gas content, stellar mass, star formation rate, and redshift. We speculate that these cluster galaxies cannot have any further substantive gas accretion if they are to become members of the dominant passive population in z<1 clusters.
The Data Systems Panel identified three critical functionalities of a Space Physics Data System (SPDS): the delivery of self-documenting data, the existence of a matrix of translators between various standard formats (IDFS, CDF, netCDF, HDF, TENNIS, UCLA flat file, and FITS), and a network-based capability for browsing and examining inventory records for the system's data holdings. The recommendations resulting from the workshop include the philosophy, funding, and objectives of a SPDS. Access to quality data is seen as the most important objective by the Policy Panel, with curation and information about the data being integral parts of any accessible data set. The Data Issues Panel concluded that the SPDS can supply encouragement, guidelines, and ultimately provide a mechanism for financial support for data archiving, restoration, and curation. The Software Panel of the SPDS focused on defining the requirements and priorities for SPDS to support common data analysis and data visualization tools and packages.
This program was initiated to replace labor-intensive ply-by-ply layup of composite I-beam posts and angle stiffeners used in the Space Station Freedom (SSF) rack structure. Hot drape forming (HDF) has been successfully implemented by BCAG for 777 composite I-stringers and by Bell Helicopter/Textron for the V-22 I-stingers. The two companies utilize two vastly different approaches to the I-beam fabrication process. A drape down process is used by Bell Helicopter where the compacted ply charge is placed on top of a forming mandrel and heated. When the heated ply charge reached a set temperature, vacuum pressure is applied and the plies are formed over the mandrel. The BCAG 777 process utilizes an inverted forming process where the ply stack is placed on a forming table and the mandrel is inverted and placed upon the ply stack. A heating and vacuum bladder underneath the ply stack form the play stack up onto the mandrels after reaching the temperature setpoint. Both methods have their advantages, but the drape down process was selected for SSF because it was more versatile and could be fabricated from readily available components.
This document provides brief reports, or case studies, on a number of investigations and data set development activities sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1 is a comparison with the atmospheric correction of Coastal Zone Color Scanner (CZCS) data using two independent radiative transfer formulations. Chapter 2 is a study on lunar reflectance at the SeaWiFS wavelengths which was useful in establishing the SeaWiFS lunar gain. Chapter 3 reports the results of the first ground-based solar calibration of the SeaWiFS instrument. The experiment was repeated in the fall of 1993 after the instrument was modified to reduce stray light; the results from the second experiment will be provided in the next case studies volume. Chapter 4 is a laboratory experiment using trap detectors which may be useful tools in the calibration round-robin program. Chapter 5 is the original data format evaluation study conducted in 1992 which outlines the technical criteria used in considering three candidate formats, the hierarchical data format (HDF), the common data format (CDF), and the network CDF (netCDF). Chapter 6 summarizes the meteorological data sets accumulated during the first three years of CZCS operation which are being used for initial testing of the operational SeaWiFS algorithms and systems and would be used during a second global processing of the CZCS data set. Chapter 7 describes how near-real time surface meteorological and total ozone data required for the atmospheric correction algorithm will be retrieved and processed. Finally, Chapter 8 is a comparison of surface wind products from various operational meteorological centers and field observations. Surface winds are used in the atmospheric correction scheme to estimate glint and foam radiances.
Software was developed with NASA support to aid in the analysis and display of the massive amounts of data generated from satellites, observational field programs, and from model simulations. This software was developed in the context of the PATHFINDER (Probing ATmospHeric Flows in an Interactive and Distributed EnviRonment) Project. The overall aim of this project is to create a flexible, modular, and distributed environment for data handling, modeling simulations, data analysis, and visualization of atmospheric and fluid flows. Software completed with NASA support includes GEMPAK analysis, data handling, and display modules for which collaborators at NASA had primary responsibility, and prototype software modules for three-dimensional interactive and distributed control and display as well as data handling, for which NSCA was responsible. Overall process control was handled through a scientific and visualization application builder from Silicon Graphics known as the Iris Explorer. In addition, the GEMPAK related work (GEMVIS) was also ported to the Advanced Visualization System (AVS) application builder. Many modules were developed to enhance those already available in Iris Explorer including HDF file support, improved visualization and display, simple lattice math, and the handling of metadata through development of a new grid datatype. Complete source and runtime binaries along with on-line documentation is available via the World Wide Web at: http://redrock.ncsa.uiuc.edu/ PATHFINDER/pathre12/top/top.html.
Envision is an interactive environment that provides researchers in the earth sciences convenient ways to manage, browse, and visualize large observed or model data sets. Its main features are support for the netCDF and HDF file formats, an easy to use X/Motif user interface, a client-server configuration, and portability to many UNIX workstations. The Envision package also provides new ways to view and change metadata in a set of data files. It permits a scientist to conveniently and efficiently manage large data sets consisting of many data files. It also provides links to popular visualization tools so that data can be quickly browsed. Envision is a public domain package, freely available to the scientific community. Envision software (binaries and source code) and documentation can be obtained from either of these servers: ftp://vista.atmos.uiuc.edu/pub/envision/ and ftp://csrp.tamu.edu/pub/envision/. Detailed descriptions of Envision capabilities and operations can be found in the User's Guide and Reference Manuals distributed with Envision software.
PATHFINDER is a software effort to create a flexible, modular, collaborative, and distributed environment for studying atmospheric, astrophysical, and other fluid flows in the evolving networked metacomputer environment of the 1990s. It uses existing software, such as HDF (Hierarchical Data Format), DTM (Data Transfer Mechanism), GEMPAK (General Meteorological Package), AVS, SGI Explorer, and Inventor to provide the researcher with the ability to harness the latest in desktop to teraflop computing. Software modules developed during the project are available in the public domain via anonymous FTP from the National Center for Supercomputing Applications (NCSA). The address is ftp.ncsa.uiuc.edu, and the directory is /SGI/PATHFINDER.
Two data products from the Total Ozone Mapping Spectrometer (TOMS) onboard Nimbus-7 have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The instrument measures backscattered Earth radiance and incoming solar irradiance; their ratio is used in ozone retrievals. Changes in the instrument sensitivity are monitored by a spectral discrimination technique using measurements of the intrinsically stable wavelength dependence of derived surface reflectivity. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values, solar zenith angles, and optical paths. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and drift is less than 1.0 percent per decade. The Level-2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level-3 product contains daily total ozone amount and reflectivity in a I - degree latitude by 1.25 degrees longitude grid. The Level-3 product also is available on CD-ROM. Detailed descriptions of both HDF data files and the CD-ROM product are provided.
Two data products from the Total Ozone Mapping Spectrometer (ADEOS/TOMS) have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The ADEOS/ TOMS began taking measurements on September 11, 1996, and ended on June 29, 1997. The instrument measured backscattered Earth radiance and incoming solar irradiance; their ratio was used in ozone retrievals. Changes in the reflectivity of the solar diffuser used for the irradiance measurement were monitored using a carousel of three diffusers, each exposed to the degrading effects of solar irradiation at different rates. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values, solar zenith angles, and optical paths. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and the drift is less than 0.5 percent over the 9-month data record. The Level 2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level 3 product contains daily total ozone and reflectivity in a 1-degree latitude by 1.25 degrees longitude grid. The Level 3 files containing estimates of UVB at the Earth surface and tropospheric aerosol information will also be available. Detailed descriptions of both HDF data files and the CDROM product are provided.
Two data products from the Earth Probe Total Ozone Mapping Spectrometer (EP/TOMS) have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The EP/ TOMS began taking measurements on July 15, 1996. The instrument measures backscattered Earth radiance and incoming solar irradiance; their ratio is used in ozone retrievals. Changes in the reflectivity of the solar diffuser used for the irradiance measurement are monitored using a carousel of three diffusers, each exposed to the degrading effects of solar irradiation at different rates. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and the drift is less than 0.5 percent over the first year of data. The Level-2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level-3 product contains daily total ozone and reflectivity in a 1-degree latitude by 1.25 degrees longitude grid. Level-3 files containing estimates of LTVB at the Earth surface and tropospheric aerosol information are also available, Detailed descriptions of both HDF data-files and the CD-ROM product are provided.