Summary of Software Using HDF5 by Name (December 2017)
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Veusz Documentation Release 3.0
Veusz Documentation Release 3.0 Jeremy Sanders Jun 09, 2018 CONTENTS 1 Introduction 3 1.1 Veusz...................................................3 1.2 Installation................................................3 1.3 Getting started..............................................3 1.4 Terminology...............................................3 1.4.1 Widget.............................................3 1.4.2 Settings: properties and formatting...............................6 1.4.3 Datasets.............................................7 1.4.4 Text...............................................7 1.4.5 Measurements..........................................8 1.4.6 Color theme...........................................8 1.4.7 Axis numeric scales.......................................8 1.4.8 Three dimensional (3D) plots..................................9 1.5 The main window............................................ 10 1.6 My first plot............................................... 11 2 Reading data 13 2.1 Standard text import........................................... 13 2.1.1 Data types in text import.................................... 14 2.1.2 Descriptors........................................... 14 2.1.3 Descriptor examples...................................... 15 2.2 CSV files................................................. 15 2.3 HDF5 files................................................ 16 2.3.1 Error bars............................................ 16 2.3.2 Slices.............................................. 16 2.3.3 2D data ranges........................................ -
Introduction CFD General Notation System (CGNS)
CGNS Tutorial Introduction CFD General Notation System (CGNS) Christopher L. Rumsey NASA Langley Research Center Outline • Introduction • Overview of CGNS – What it is – History – How it works, and how it can help – The future • Basic usage – Getting it and making it work for you – Simple example – Aspects for data longevity 2 Introduction • CGNS provides a general, portable, and extensible standard for the description, storage, and retrieval of CFD analysis data • Principal target is data normally associated with computed solutions of the Navier-Stokes equations & its derivatives • But applicable to computational field physics in general (with augmentation of data definitions and storage conventions) 3 What is CGNS? • Standard for defining & storing CFD data – Self-descriptive – Machine-independent – Very general and extendable – Administered by international steering committee • AIAA recommended practice (AIAA R-101A-2005) • Free and open software • Well-documented • Discussion forum: [email protected] • Website: http://www.cgns.org 4 History • CGNS was started in the mid-1990s as a joint effort between NASA, Boeing, and McDonnell Douglas – Under NASA’s Advanced Subsonic Technology (AST) program • Arose from need for common CFD data format for improved collaborative analyses between multiple organizations – Existing formats, such as PLOT3D, were incomplete, cumbersome to share between different platforms, and not self-descriptive (poor for archival purposes) • Initial development was heavily influenced by McDonnell Douglas’ “Common -
Development of a Coupling Approach for Multi-Physics Analyses of Fusion Reactors
Development of a coupling approach for multi-physics analyses of fusion reactors Zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften (Dr.-Ing.) bei der Fakultat¨ fur¨ Maschinenbau des Karlsruher Instituts fur¨ Technologie (KIT) genehmigte DISSERTATION von Yuefeng Qiu Datum der mundlichen¨ Prufung:¨ 12. 05. 2016 Referent: Prof. Dr. Stieglitz Korreferent: Prof. Dr. Moslang¨ This document is licensed under the Creative Commons Attribution – Share Alike 3.0 DE License (CC BY-SA 3.0 DE): http://creativecommons.org/licenses/by-sa/3.0/de/ Abstract Fusion reactors are complex systems which are built of many complex components and sub-systems with irregular geometries. Their design involves many interdependent multi- physics problems which require coupled neutronic, thermal hydraulic (TH) and structural mechanical (SM) analyses. In this work, an integrated system has been developed to achieve coupled multi-physics analyses of complex fusion reactor systems. An advanced Monte Carlo (MC) modeling approach has been first developed for converting complex models to MC models with hybrid constructive solid and unstructured mesh geometries. A Tessellation-Tetrahedralization approach has been proposed for generating accurate and efficient unstructured meshes for describing MC models. For coupled multi-physics analyses, a high-fidelity coupling approach has been developed for the physical conservative data mapping from MC meshes to TH and SM meshes. Interfaces have been implemented for the MC codes MCNP5/6, TRIPOLI-4 and Geant4, the CFD codes CFX and Fluent, and the FE analysis platform ANSYS Workbench. Furthermore, these approaches have been implemented and integrated into the SALOME simulation platform. Therefore, a coupling system has been developed, which covers the entire analysis cycle of CAD design, neutronic, TH and SM analyses. -
Praktikum Iz Softverskih Alata U Elektronici
PRAKTIKUM IZ SOFTVERSKIH ALATA U ELEKTRONICI 2017/2018 Predrag Pejović 31. decembar 2017 Linkovi na primere: I OS I LATEX 1 I LATEX 2 I LATEX 3 I GNU Octave I gnuplot I Maxima I Python 1 I Python 2 I PyLab I SymPy PRAKTIKUM IZ SOFTVERSKIH ALATA U ELEKTRONICI 2017 Lica (i ostali podaci o predmetu): I Predrag Pejović, [email protected], 102 levo, http://tnt.etf.rs/~peja I Strahinja Janković I sajt: http://tnt.etf.rs/~oe4sae I cilj: savladavanje niza programa koji se koriste za svakodnevne poslove u elektronici (i ne samo elektronici . ) I svi programi koji će biti obrađivani su slobodan softver (free software), legalno možete da ih koristite (i ne samo to) gde hoćete, kako hoćete, za šta hoćete, koliko hoćete, na kom računaru hoćete . I literatura . sve sa www, legalno, besplatno! I zašto svake godine (pomalo) updated slajdovi? Prezentacije predmeta I engleski I srpski, kraća verzija I engleski, prezentacija i animacije I srpski, prezentacija i animacije A šta se tačno radi u predmetu, koji programi? 1. uvod (upravo slušate): organizacija nastave + (FS: tehnička, ekonomska i pravna pitanja, kako to uopšte postoji?) (≈ 1 w) 2. operativni sistem (GNU/Linux, Ubuntu), komandna linija (!), shell scripts, . (≈ 1 w) 3. nastavak OS, snalaženje, neki IDE kao ilustracija i vežba, jedan Python i jedan C program . (≈ 1 w) 4.L ATEX i LATEX 2" (≈ 3 w) 5. XCircuit (≈ 1 w) 6. probni kolokvijum . (= 1 w) 7. prvi kolokvijum . 8. GNU Octave (≈ 1 w) 9. gnuplot (≈ (1 + ) w) 10. wxMaxima (≈ 1 w) 11. drugi kolokvijum . 12. Python, IPython, PyLab, SymPy (≈ 3 w) 13. -
Tools and Resources
Tools and resources Software for research, analysis and writing can be costly to purchase, but free and/or Open Source software is often as good as, and sometimes better than, the commercial equivalent. Here we provide information and links for some of the best software tools of which we are aware. The Editor’s picks are highlighted. If you know of good free and/or Open Source tools that we haven’t mentioned, please let us know. Analysis, data presentation and statistics Bibliography, writing and research tools Data sources Geographical Information Systems Drawing, image editing and management Operating systems Analysis, data presentation and statistics camtrapR is for management of and data extraction from camera-trap photographs. It provides a workflow for storing and sorting camera-trap photographs, tabulates records of species and individuals, creates detection/non-detection matrices for occupancy and spatial capture–recapture analyses, and has simple mapping functions. Requires R, which is available for Windows, Mac and Linux. Density: spatially explicit capture–recapture uses the locations where animals are detected to fit a spatial model of the detection process, and hence to estimate population density unbiased by edge effects and incomplete detection. Requires R, which is available for Windows, Mac and Linux. Distance is for the design and analysis of distance sampling surveys of wildlife populations. Requires R, which is available for Windows, Mac and Linux, and is also available as separate Windows software. DotDotGoose is a tool to assist with the manual counting of objects in images. Rrequires Windows, Mac or Linuix. EstimateS computes biodiversity statistics, estimators, and indices based on biotic sampling data. -
Integrated Tool Development for Used Fuel Disposition Natural System Evaluation –
Integrated Tool Development for Used Fuel Disposition Natural System Evaluation – Phase I Report Prepared for U.S. Department of Energy Used Fuel Disposition Yifeng Wang & Teklu Hadgu Sandia National Laboratories Scott Painter, Dylan R. Harp & Shaoping Chu Los Alamos National Laboratory Thomas Wolery Lawrence Livermore National Laboratory Jim Houseworth Lawrence Berkeley National Laboratory September 28, 2012 FCRD-UFD-2012-000229 SAND2012-7073P DISCLAIMER This information was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness, of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. Government or any agency thereof. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy‘s National Nuclear Security Administration under contract DE-AC04-94AL85000. Integrated Tool Development for UFD Natural System Evaluation 9/1/2012 iii Integrated Tool Development for UFD Natural System Evaluation iv 9/1/2012 Integrated Tool Development for UFD Natural System Evaluation 9/1/2012 v Executive Summary The natural barrier system (NBS) is an integral part of a geologic nuclear waste repository. -
An Extensible Scientific Plotting Tool Based on Matplotlib.Journal of Open Research Software Open Research Software, 2(1): E1, DOI
Journal of Peters, N 2014 AvoPlot: An extensible scientific plotting tool based on matplotlib. Journal of open research software Open Research Software, 2(1): e1, DOI: http://dx.doi.org/10.5334/jors.ai SOFTWARE METAPAPER AvoPlot: An extensible scientific plotting tool based on matplotlib Nial Peters1 1 Geography Department, Cambridge University, Cambridge, United Kingdom AvoPlot is a simple-to-use graphical plotting program written in Python and making extensive use of the matplotlib plotting library. It can be found at http://code.google.com/p/avoplot/. In addition to providing a user-friendly interface to the powerful capabilities of the matplotlib library, it also offers users the pos- sibility of extending its functionality by creating plug-ins. These can import specific types of data into the interface and also provide new tools for manipulating them. In this respect, AvoPlot is a convenient platform for researchers to build their own data analysis tools on top of, as well as being a useful stan- dalone program. Keywords: plotting; data visualisation Funding Statement: Much of the initial development was conducted whilst on fieldwork supported by the Royal Geographical Society (with IBG) with a Geographical Fieldwork Grant, and support from Antofa- gasta plc via the University of Cambridge Centre for Latin American Studies. (1) Overview comprehensive graphical interface for creating and edit- ing plots, as well as providing a plug-in interface to allow Introduction users to load arbitrary data types and define new analysis The software was originally created as a real-time visuali- functions. However, Veusz implements its own plotting sation program for monitoring sulphur dioxide emissions backend which is unlikely to be as familiar to developers from volcanoes. -
Seven Keys for Practical Understanding and Use of CGNS
Seven keys for practical understanding and use of CGNS Marc Poinot∗ Christopher L. Rumseyy SAFRAN NASA Langley Research Center [email protected] [email protected] We present key features of the CGNS standard, focusing on its two main elements, the data model (CGNS/SIDS) and its implementations (CGNS/HDF5 and CGNS/Python). The data model is detailed to emphasize how the topological user oriented information, such as families, are separated from the actual meshing that could be split or modified during the CFD workflow, and how this topological information is traced during the meshing process. We also explain why the same information can be described in multiple ways and how to handle such alternatives in an application. Two implementations, using HDF5 and Python, are illustrated in several use examples, both for archival and interoperability purposes. The CPEX extension formalized process is explained to show how to add new features to the standard in a consensual way; we present some of the next extensions to come. Finally we conclude by showing how powerful a consensual public approach like CGNS can be, as opposed to a stand-alone private one. All throughout the paper, we demonstrate how the use of CGNS could be of great benefit for both the meshing and CFD solver communities. I. Introduction The CFD General Notation System12 (CGNS) is a public standard for the CFD community. It has had more than 20 years of feedback from users throughout the world in industry, universities, and government research labs. The CGNS name is now well known in the CFD community, but it is often only associated with the CGNS library (CGNS/MLL) used by CFD tools. -
Technical Notes All Changes in Fedora 13
Fedora 13 Technical Notes All changes in Fedora 13 Edited by The Fedora Docs Team Copyright © 2010 Red Hat, Inc. and others. The text of and illustrations in this document are licensed by Red Hat under a Creative Commons Attribution–Share Alike 3.0 Unported license ("CC-BY-SA"). An explanation of CC-BY-SA is available at http://creativecommons.org/licenses/by-sa/3.0/. The original authors of this document, and Red Hat, designate the Fedora Project as the "Attribution Party" for purposes of CC-BY-SA. In accordance with CC-BY-SA, if you distribute this document or an adaptation of it, you must provide the URL for the original version. Red Hat, as the licensor of this document, waives the right to enforce, and agrees not to assert, Section 4d of CC-BY-SA to the fullest extent permitted by applicable law. Red Hat, Red Hat Enterprise Linux, the Shadowman logo, JBoss, MetaMatrix, Fedora, the Infinity Logo, and RHCE are trademarks of Red Hat, Inc., registered in the United States and other countries. For guidelines on the permitted uses of the Fedora trademarks, refer to https:// fedoraproject.org/wiki/Legal:Trademark_guidelines. Linux® is the registered trademark of Linus Torvalds in the United States and other countries. Java® is a registered trademark of Oracle and/or its affiliates. XFS® is a trademark of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. All other trademarks are the property of their respective owners. Abstract This document lists all changed packages between Fedora 12 and Fedora 13. -
Getting Data Into Visit
LLNL-SM-446033 Getting Data Into VisIt July 2010 Version 2.0.0 Brad Whitlock wrence La Livermore National Laboratory ii DISCLAIMER This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trade- mark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Liver- more National Security, LLC, and shall not be used for advertising or product endorsement purposes. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory in part under Contract W-7405-Eng-48 and in part under Contract DE-AC52-07NA27344. iii iv Table of Contents Introduction Manual chapters . 2 Manual conventions . 2 Strategies . 2 Picking a strategy . 3 Definition of terms . 4 Creating compatible files Creating a conversion utility or extending a simulation . 7 Survey of database reader plug-ins. 9 BOV file format . 9 X-Y Curve file format. 12 Plain text ASCII files . -
Python for Data Analysis
CHAPTER 8 Plotting and Visualization Making plots and static or interactive visualizations is one of the most important tasks in data analysis. It may be a part of the exploratory process; for example, helping iden- tify outliers, needed data transformations, or coming up with ideas for models. For others, building an interactive visualization for the web using a toolkit like d3.js (http: //d3js.org/) may be the end goal. Python has many visualization tools (see the end of this chapter), but I’ll be mainly focused on matplotlib (http://matplotlib.sourceforge .net). matplotlib is a (primarily 2D) desktop plotting package designed for creating publica- tion-quality plots. The project was started by John Hunter in 2002 to enable a MAT- LAB-like plotting interface in Python. He, Fernando Pérez (of IPython), and others have collaborated for many years since then to make IPython combined with matplotlib a very functional and productive environment for scientific computing. When used in tandem with a GUI toolkit (for example, within IPython), matplotlib has interactive features like zooming and panning. It supports many different GUI backends on all operating systems and additionally can export graphics to all of the common vector and raster graphics formats: PDF, SVG, JPG, PNG, BMP, GIF, etc. I have used it to produce almost all of the graphics outside of diagrams in this book. matplotlib has a number of add-on toolkits, such as mplot3d for 3D plots and basemap for mapping and projections. I will give an example using basemap to plot data on a map and to read shapefiles at the end of the chapter. -
AIAA Paper 2012-1264
AIAA-2012-1264 50th AIAA Aerospace Sciences Meeting, January 9 – 12, 2012, Nashville, TN Recent Updates to the CFD General Notation System (CGNS) Christopher L. Rumsey∗ NASA Langley Research Center, Hampton, VA 23681 Bruce Wedan† Computational Engineering Solutions, San Ramon, CA 94582 Thomas Hauser‡ University of Colorado Boulder, Boulder, CO 80309 Marc Poinot§ ONERA - The French Aerospace Lab, F-92322 Chatillon, FRANCE The CFD General Notation System (CGNS)—a general, portable, and extensible standard for the storage and retrieval of computational fluid dynamics (CFD) analysis data—has been in existence for more than a decade (Version 1.0 was released in May 1998). Both structured and unstructured CFD data are covered by the standard, and CGNS can be easily extended to cover any sort of data imaginable, while retaining backward compatibility with existing CGNS data files and software. Although originally designed for CFD, it is readily extendable to any field of computational analysis. In early 2011, CGNS Version 3.1 was released, which added significant capabilities. This paper describes these recent enhancements and highlights the continued usefulness of the CGNS methodology. Glossary of Terms ADF CGNS Advanced Data Format, www.grc.nasa.gov/www/cgns/CGNS docs current/adf API Application Programming Interface CGIO CGNS low-level library, www.grc.nasa.gov/www/cgns/CGNS docs current/cgio CHLone CGNS special purpose C library (for HDF5 files only), chlone.sourceforge.net CGNS CFD General Notation System, cgns.org CGNSTalk CGNS user forum,