The Labplot Handbook
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Work Package 2 Collection of Requirements for OS
Consortium for studying, evaluating, and supporting the introduction of Open Source software and Open Data Standards in the Public Administration Project acronym: COSPA Wor k Package 2 Collection of requirements for OS applications and ODS in the PA and creation of a catalogue of appropriate OS/ODS Solutions D eliverable 2. 1 Catalogue of available Open Source tools for the PA Contract no.: IST-2002-2164 Project funded by the European Community under the “SIXTH FRAMEWORK PROGRAMME” Work Package 2, Deliverable 2.1 - Catalogue of available Open Source tools for the PA Project Acronym COSPA Project full title A Consortium for studying, evaluating, and supporting the introduction of Open Source software and Open Data Standards in the Public Administration Contract number IST-2002-2164 Deliverable 2.1 Due date 28/02/2004 Release date 15/10/2005 Short description WP2 focuses on understanding the OS tools currently used in PAs, and the ODS compatible with these tools. Deliverable D2.1 contains a Catalogue of available open source tools for the PA, including information about the OS currently in use inside PAs, the administrative and training requirements of the tools. Author(s) Free University of Bozen/Bolzano Contributor(s) Conecta, IBM, University of Sheffield Project Officer Tiziana Arcarese Trond Arne Undheim European Commission Directorate-General Information Society Directorate C - Unit C6- eGovernment, BU 31 7/87 rue de la Loi 200 - B-1049 Brussels - Belgium 26/10/04 Version 1.3a page 2/353 Work Package 2, Deliverable 2.1 - Catalogue of available Open Source tools for the PA Disclaimer The views expressed in this document are purely those of the writers and may not, in any circumstances, be interpreted as stating an official position of the European Commission. -
Visualization of Complex Function Graphs in Augmented Reality
M A G I S T E R A R B E I T Visualization of Complex Function Graphs in Augmented Reality ausgeführt am Institut für Softwaretechnik und Interaktive Systeme der Technischen Universität Wien unter der Anleitung von Univ.Ass. Mag. Dr. Hannes Kaufmann durch Robert Liebo Brahmsplatz 7/11 1040 Wien _________ ____________________________ Datum Unterschrift Abstract Understanding the properties of a function over complex numbers can be much more difficult than with a function over real numbers. This work provides one approach in the area of visualization and augmented reality to gain insight into these properties. The applied visualization techniques use the full palette of a 3D scene graph's basic elements, the complex function can be seen and understood through the location, the shape, the color and even the animation of a resulting visual object. The proper usage of these visual mappings provides an intuitive graphical representation of the function graph and reveals the important features of a specific function. Augmented reality (AR) combines the real world with virtual objects generated by a computer. Using multi user AR for mathematical visualization enables sophisticated educational solutions for studies dealing with complex functions. A software framework that has been implemented will be explained in detail, it is tailored to provide an optimal solution for complex function graph visualization, but shows as well an approach to visualize general data sets with more than 3 dimensions. The framework can be used in a variety of environments, a desktop setup and an immersive setup will be shown as examples. Finally some common tasks involving complex functions will be shown in connection with this framework as example usage possibilities. -
Bring Down the Two-Language Barrier with Julia Language for Efficient
AbstractSDRs: Bring down the two-language barrier with Julia Language for efficient SDR prototyping Corentin Lavaud, Robin Gerzaguet, Matthieu Gautier, Olivier Berder To cite this version: Corentin Lavaud, Robin Gerzaguet, Matthieu Gautier, Olivier Berder. AbstractSDRs: Bring down the two-language barrier with Julia Language for efficient SDR prototyping. IEEE Embedded Systems Letters, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. 10.1109/LES.2021.3054174. hal-03122623 HAL Id: hal-03122623 https://hal.archives-ouvertes.fr/hal-03122623 Submitted on 27 Jan 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. AbstractSDRs: Bring down the two-language barrier with Julia Language for efficient SDR prototyping Corentin LAVAUD∗, Robin GERZAGUET∗, Matthieu GAUTIER∗, Olivier BERDER∗. ∗ Univ Rennes, CNRS, IRISA, [email protected] Abstract—This paper proposes a new methodology based glue interface [8]. Regarding programming semantic, low- on the recently proposed Julia language for efficient Software level languages (e.g. C++/C, Rust) offers very good runtime Defined Radio (SDR) prototyping. SDRs are immensely popular performance but does not offer a good prototyping experience. as they allow to have a flexible approach for sounding, monitoring or processing radio signals through the use of generic analog High-level languages (e.g. -
Gnuplot Programming Interview Questions and Answers Guide
Gnuplot Programming Interview Questions And Answers Guide. Global Guideline. https://www.globalguideline.com/ Gnuplot Programming Interview Questions And Answers Global Guideline . COM Gnuplot Programming Job Interview Preparation Guide. Question # 1 What is Gnuplot? Answer:- Gnuplot is a command-driven interactive function plotting program. It can be used to plot functions and data points in both two- and three-dimensional plots in many different formats. It is designed primarily for the visual display of scientific data. gnuplot is copyrighted, but freely distributable; you don't have to pay for it. Read More Answers. Question # 2 How to run gnuplot on your computer? Answer:- Gnuplot is in widespread use on many platforms, including MS Windows, linux, unix, and OSX. The current source code retains supports for older systems as well, including VMS, Ultrix, OS/2, MS-DOS, Amiga, OS-9/68k, Atari ST, BeOS, and Macintosh. Versions since 4.0 have not been extensively tested on legacy platforms. Please notify the FAQ-maintainer of any further ports you might be aware of. You should be able to compile the gnuplot source more or less out of the box on any reasonable standard (ANSI/ISO C, POSIX) environment. Read More Answers. Question # 3 How to edit or post-process a gnuplot graph? Answer:- This depends on the terminal type you use. * X11 toolkits: You can use the terminal type fig and use the xfig drawing program to edit the plot afterwards. You can obtain the xfig program from its web site http://www.xfig.org. More information about the text-format used for fig can be found in the fig-package. -
SEISGAMA: a Free C# Based Seismic Data Processing Software Platform
Hindawi International Journal of Geophysics Volume 2018, Article ID 2913591, 8 pages https://doi.org/10.1155/2018/2913591 Research Article SEISGAMA: A Free C# Based Seismic Data Processing Software Platform Theodosius Marwan Irnaka, Wahyudi Wahyudi, Eddy Hartantyo, Adien Akhmad Mufaqih, Ade Anggraini, and Wiwit Suryanto Seismology Research Group, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara Bulaksumur, Yogyakarta 55281, Indonesia Correspondence should be addressed to Wiwit Suryanto; [email protected] Received 4 July 2017; Accepted 24 December 2017; Published 30 January 2018 Academic Editor: Filippos Vallianatos Copyright © 2018 Teodosius Marwan Irnaka et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Seismic refection is one of the most popular methods in geophysical prospecting. Nevertheless, obtaining high resolution and accurate results requires a sophisticated processing stage. Tere are many open-source seismic refection data processing sofware programs available; however, they ofen use a high-level programming language that decreases its overall performance, lacks intuitive user-interfaces, and is limited to a small set of tasks. Tese shortcomings reveal the need to develop new sofware using a programming language that is natively supported by Windows5 operating systems, which uses a relatively medium-level programming language (such as C#) and can be enhanced by an intuitive user interface. SEISGAMA was designed to address this need and employs a modular concept, where each processing group is combined into one module to ensure continuous and easy development and documentation. -
Linux: Come E Perchх
ÄÒÙÜ Ô ©2007 mcz 12 luglio 2008 ½º I 1. Indice II ½º Á ¾º ¿º ÈÖÞÓÒ ½ º È ÄÒÙÜ ¿ º ÔÔÖÓÓÒÑÒØÓ º ÖÒÞ ×ÓרÒÞÐ ÏÒÓÛ× ¾½ º ÄÒÙÜ ÕÙÐ ×ØÖÙÞÓÒ ¾ º ÄÒÙÜ ÀÖÛÖ ×ÙÔÔ ÓÖØØÓ ¾ º È Ð ÖÒÞ ØÖ ÖÓ ÓØ Ù×Ö ¿½ ½¼º ÄÒÙÜ × ÒרÐÐ ¿¿ ½½º ÓÑ × ÒרÐÐÒÓ ÔÖÓÖÑÑ ¿ ½¾º ÒÓÒ ØÖÓÚÓ ÒÐ ×ØÓ ÐÐ ×ØÖÙÞÓÒ ¿ ½¿º Ó׳ ÙÒÓ ¿ ½º ÓÑ × Ð ××ØÑ ½º ÓÑ Ð ½º Ð× Ñ ½º Ð Ñ ØÐ ¿ ½º ÐÓ ½º ÓÑ × ÒרÐÐ Ð ×ØÑÔÒØ ¾¼º ÓÑ ÐØØÖ¸ Ø×Ø ÐÖ III Indice ¾½º ÓÑ ÚÖ Ð ØÐÚ×ÓÒ ¿ 21.1. Televisioneanalogica . 63 21.2. Televisione digitale (terrestre o satellitare) . ....... 64 ¾¾º ÐÑØ ¾¿º Ä 23.1. Fotoritocco ............................. 67 23.2. Grafica3D.............................. 67 23.3. Disegnovettoriale-CAD . 69 23.4.Filtricoloreecalibrazionecolori . .. 69 ¾º ×ÖÚ Ð ½ 24.1.Vari.................................. 72 24.2. Navigazionedirectoriesefiles . 73 24.3. CopiaCD .............................. 74 24.4. Editaretesto............................. 74 24.5.RPM ................................. 75 ¾º ×ÑÔ Ô ´ËÐе 25.1.Montareundiscoounapenna . 77 25.2. Trovareunfilenelsistema . 79 25.3.Vedereilcontenutodiunfile . 79 25.4.Alias ................................. 80 ¾º × ÚÓÐ×× ÔÖÓÖÑÑÖ ½ ¾º ÖÓÛ×Ö¸ ÑÐ ººº ¿ ¾º ÖÛÐÐ Ð³ÒØÚÖÙ× Ð ÑØØÑÓ ¾º ÄÒÙÜ ½ ¿¼º ÓÑ ØÖÓÚÖ ÙØÓ ÖÖÑÒØ ¿ ¿½º Ð Ø×ØÙÐ Ô Ö Ð ×ØÓÔ ÄÒÙÜ ¿¾º ´ÃµÍÙÒØÙ¸ ÙÒ ×ØÖÙÞÓÒ ÑÓÐØÓ ÑØ ¿¿º ËÙÜ ÙÒ³ÓØØÑ רÖÙÞÓÒ ÄÒÙÜ ½¼½ ¿º Á Ó Ò ÄÒÙÜ ½¼ ¿º ÃÓÒÕÙÖÓÖ¸ ÕÙ×ØÓ ½¼ ¿º ÃÓÒÕÙÖÓÖ¸ Ñ ØÒØÓ Ô Ö ½½¿ 36.1.Unaprimaocchiata . .114 36.2.ImenudiKonqueror . .115 36.3.Configurazione . .116 IV Indice 36.4.Alcuniesempidiviste . 116 36.5.Iservizidimenu(ServiceMenu) . 119 ¿º ÃÓÒÕÙÖÓÖ Ø ½¾¿ ¿º à ÙÒ ÖÖÒØ ½¾ ¿º à ÙÒ ÐÙ×ÓÒ ½¿½ ¼º ÓÒÖÓÒØÓ ÒרÐÐÞÓÒ ÏÒÓÛ×È ÃÍÙÒØÙ º½¼ ½¿¿ 40.1. -
Computeralgebra & Visualisierung
Computeralgebra & Visualisierung Alexander Weiße Institut fur¨ Physik, Universit¨at Greifswald, Germany http://theorie2.physik.uni-greifswald.de/member/weisse/casvis/index.html Zwei Gruppen: Dienstag+Donnerstag 10-12 Uhr, Raum A 202 Gliederung Grundlagen UNIX & GNU/Linux Typische Anwendungen Computeralgebra-Systeme Einfuhrung¨ & Uberblick¨ Maxima Maple Axiom Graphische Darstellung von Daten Gnuplot Grace LabPlot Numerische Werkzeuge & Graphik Octave Visualization Toolkit (VTK) Matlab & Scilab Fortgeschrittene Themen & Erganzungen¨ Animation Software fur¨ Prasentationen¨ Computer I Schematischer Aufbau eines Rechners I Was macht ein Betriebsystem? I Verwaltet Ressourcen des Rechners: I Umfaßt Programme fur¨ Steuerung und Zugriff auf Hardware (Speicher, Laufwerke, Netzwerk, . ) I Verteilt Arbeitsleistung der CPU und Speicher auf verschiedene Programme Betriebssystem GNU/Linux I Urahn: Unix I Betriebssystem, 1969 entwickelt bei AT&T / Bell Labs I Weit verbeitet im akademischen Umfeld (zusammen mit der Programmiersprache C) I Ausgelegt auf Portabilit¨at, Multi-Tasking- und Multi-User-Betrieb I Besteht aus einem Kern und vielen Programmen, die uber¨ einen Kommandozeilen-Interpreter gesteuert werden I 1991: Ausgehend vom Unix-System Minix entwickelt Linus Torvalds ein Betriebsystem fur¨ PCs mit Intel 80386 Prozessor. Zusammen mit der freien Software aus dem GNU Projekt entsteht GNU/Linux I Was bedeutet “freie Software”? Nach Definition der Free Software Foundation soll der Nutzer das Recht haben, I das Programm zu jedem Zweck auszufuhren,¨ I -
Julia: a Modern Language for Modern ML
Julia: A modern language for modern ML Dr. Viral Shah and Dr. Simon Byrne www.juliacomputing.com What we do: Modernize Technical Computing Today’s technical computing landscape: • Develop new learning algorithms • Run them in parallel on large datasets • Leverage accelerators like GPUs, Xeon Phis • Embed into intelligent products “Business as usual” will simply not do! General Micro-benchmarks: Julia performs almost as fast as C • 10X faster than Python • 100X faster than R & MATLAB Performance benchmark relative to C. A value of 1 means as fast as C. Lower values are better. A real application: Gillespie simulations in systems biology 745x faster than R • Gillespie simulations are used in the field of drug discovery. • Also used for simulations of epidemiological models to study disease propagation • Julia package (Gillespie.jl) is the state of the art in Gillespie simulations • https://github.com/openjournals/joss- papers/blob/master/joss.00042/10.21105.joss.00042.pdf Implementation Time per simulation (ms) R (GillespieSSA) 894.25 R (handcoded) 1087.94 Rcpp (handcoded) 1.31 Julia (Gillespie.jl) 3.99 Julia (Gillespie.jl, passing object) 1.78 Julia (handcoded) 1.2 Those who convert ideas to products fastest will win Computer Quants develop Scientists prepare algorithms The last 25 years for production (Python, R, SAS, DEPLOY (C++, C#, Java) Matlab) Quants and Computer Compress the Scientists DEPLOY innovation cycle collaborate on one platform - JULIA with Julia Julia offers competitive advantages to its users Julia is poised to become one of the Thank you for Julia. Yo u ' v e k i n d l ed leading tools deployed by developers serious excitement. -
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. -
An Introduction to S and the Hmisc and Design Libraries
An Introduction to S and The Hmisc and Design Libraries Carlos Alzola, MS Statistical Consultant 501 SE Glyndon Street Vienna, Va 22180 [email protected] Frank Harrell, PhD Professor of Biostatistics Department of Biostatistics Vanderbilt University School of Medicine S-2323 Medical Center North Nashville, Tn 37232 [email protected] http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RS November 16, 2004 ii Updates to this document may be obtained from biostat.mc.vanderbilt.edu/twiki/pub/Main/RS/sintro.pdf. Contents 1 Introduction 1 1.1 S, S-Plus, R, and Source References ........................... 1 1.1.1 R ........................................... 4 1.2 Starting S .......................................... 4 1.2.1 UNIX/Linux .................................... 4 1.2.2 Windows ...................................... 5 1.3 Commands vs. GUIs .................................... 7 1.4 Basic S Commands ..................................... 7 1.5 Methods for Entering and Saving S Commands ..................... 9 1.5.1 Specifying System File Names in S ........................ 11 1.6 Differences Between S and SAS .............................. 11 1.7 A Comparison of UNIX/Linux and Windows for Running S .............. 18 1.8 System Requirements ................................... 19 1.9 Some Useful System Tools ................................. 19 2 Objects, Getting Help, Functions, Attributes, and Libraries 25 2.1 Objects ........................................... 25 2.2 Getting Help ........................................ 25 2.3 -
Introduction to Matlab
Introduction to Numerical Libraries Shaohao Chen High performance computing @ Louisiana State University Outline 1. Introduction: why numerical libraries? 2. Fast Fourier transform: FFTw 3. Linear algebra libraries: LAPACK 4. Krylov subspace solver: PETSc 5. GNU scientific libraries: GSL 1. Introduction It is very easy to write bad code! • Loops : branching, dependencies • I/O : resource conflicts, • Memory : long fetch-time • Portability : code and data portable? • Readability : Can you still understand it? A solution: look for existing libraries! Why numerical libraries? • Many functions or subroutines you need may have already been coded by others. Just use them. • Not necessary to code every line by yourself. • Check available libs before starting to write your program. • Save your time and efforts! Advantages of using numerical libraries: • Computing optimizations • Portability • Easy to debug • Easy to read What you will learn in this training • General knowledge of numerical libs. • How to check available libs on HPC systems and the web. • How to use numerical libs on HPC systems. • Basic programming with numerical libs. List of notable numerical libraries • Linear Algebra Package (LAPACK): computes matrix and vector operations. [Fortran] • Fastest Fourier Transform in the West (FFTW): computes Fourier and related transforms. [C/C++] • GNU Scientific Library (GSL): provides a wide range of mathematical routines. [C/C++] • Portable, Extensible Toolkit for Scientific Computation (PETSc): a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. [C/C++] • NumPy: adds support for the manipulation of large, multi-dimensional arrays and matrices; also includes a large collection of high-level mathematical functions. -
Fastest Fourier Transform in the West
Fastest Fourier Transform in the West Devendra Ghate and Nachi Gupta [email protected], [email protected] Oxford University Computing Laboratory MT 2006 Internal Seminar – p. 1/33 Cooley-Tukey Algorithm for FFT N 1 2πi − nk Xk = X xne− N ; k = 0; : : : ; N − 1 n=0 2 If we solve for Xk directly then O(N ) operations required for the solution. If N = p × q, then this transformation can be split into two separate transformations... ...recursively, we get the FFT algorithm. N If N is split into r intervals of r each then the complexity is r × N × logr N. This can be generalised to mixed-radix algorithms. MT 2006 Internal Seminar – p. 2/33 Overview of FFT algorithms Cooley-Tukey FFT algorithm (popularized in 1965), known by Gauss in 1805. Prime-factor FFT algorithm ± a.k.a. Good-Thomas (1958-1963), N = N1N2 becomes 2D N1 by N2 DFT for only relatively prime N1; N2. Bruun's FFT algorithm (1978, generalized to arbitrary even composite sizes by H. Murakami in 1996), recursive polynomial factorization approach. Rader's FFT algorithm (1968), for prime size by expressing DFT as a convolution. Bluestein's FFT algorithm (1968) ± a.k.a. chirp z-transform algorithm (1969), for prime sizes by expressing DFT as a convolution. Rader-Brenner (1976) ± Cooley-Tukey like, but purely imag twiddle factors MT 2006 Internal Seminar – p. 3/33 What is FFTW? FFTW is a package for computing a one or multidimensional complex discrete Fourier transform (DFT) of arbitrary size. At the heart of FFTW lies a philosophy geared towards speed, portability, and elegance – achieved via an adaptive software architecture.