Visualization of Complex Function Graphs in Augmented Reality

Total Page:16

File Type:pdf, Size:1020Kb

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. ii Dedication Dedicated to everybody who took more than a year to finish his/her master thesis. iii Acknowledgments I want to thank everybody who made this work possible, first of all my family, Barbara, the people I live with, my friends and my colleagues who supported my all the time. This work would also have been impossible without the work of my supervisor Hannes Kaufmann and Dieter Schmalstieg who guided me into the world of VR, the people of the VR-group in Vienna and Graz and the computer graphics institute with its master and the CGClub. iv Table of Contents Abstract................................................................................................... ii Dedication.............................................................................................. iii Acknowledgments...................................................................................iv List of Figures........................................................................................ vii 1 Introduction...........................................................................................1 1.1 Motivation.............................................................................................................. 1 1.2 Applications...........................................................................................................2 1.2.1 Math Education............................................................................................. 2 1.2.2 Electrical Engineering Math......................................................................... 2 1.2.3 Filter Design Math.........................................................................................2 2 Related Work........................................................................................ 4 2.1 Complex Function Visualization...........................................................................4 2.1.1 Applications................................................................................................... 4 2.1.2 Web Based Complex Function Visualization................................................6 2.1.3 Visualizations Generated by Existing Software............................................7 2.2 Augmented Reality..............................................................................................12 2.2.1 Science education with AR and VR.............................................................12 2.3 Visualization in Scene Graph APIs.....................................................................14 3 Technological Foundations..................................................................16 3.1 Inventor and Coin3D...........................................................................................16 3.1.1 Nodes............................................................................................................16 3.2 Studierstube.........................................................................................................17 4 The Complex Function Graph Visualization Node Kit for Inventor......18 4.1 The Framework's Design.....................................................................................18 4.1.1 A Visualization Task.....................................................................................18 4.1.2 Function Graph Specific Visualization Task...............................................19 4.1.3 Dimensionality Issues.................................................................................20 4.1.4 Domain Set Issues....................................................................................... 21 4.2 Implementation..................................................................................................22 4.2.1 Overview of Implemented Classes..............................................................22 4.2.1.1 SoComplexFunctionGraphVisualization Internals............................ 23 4.2.1.2 SoComplexFunctionEvaluator Internals............................................24 4.2.2 Domain Set Input........................................................................................25 4.2.2.1 SoComplexDomainSubSet_0D.......................................................... 26 4.2.2.2 SoComplexDomainSubSet_1D_RegularLine....................................26 v 4.2.2.3 SoComplexDomainSubSet_1D_RegularCircle..................................27 4.2.2.4 SoComplexDomainSubSet_2D_RegularRectangular.......................27 4.2.2.5 SoComplexDomainSubSet_2D_RegularPolar..................................28 4.2.2.6 domainSubSetList input.....................................................................29 4.2.3 Function Input............................................................................................29 4.2.4 Parameter Input......................................................................................... 30 4.2.5 Mapping Input.............................................................................................31 4.2.5.1 Graph Space Components (Source Vector)........................................32 4.2.5.2 Visualization Space Components (Target Vector).............................33 4.2.5.3 SoMappingGraphPropertyToVizFeature with scale and offset.........35 4.2.6 GraphVisualization Configuration Input...................................................36 4.2.6.1 Custom Point Objects..........................................................................36 4.2.6.2 Line and Arc Connectors.................................................................... 37 4.2.6.3 Array Dissolvers..................................................................................38 4.2.7 VizObjectDefinitionState............................................................................38 5 User Interfaces and Example Setups................................................... 43 5.1 Immersive Setup................................................................................................. 43 5.1.1 Immersive Setup User Instructions............................................................44 5.2 Desktop Setup.....................................................................................................45 5.2.1 Desktop Setup User Instructions................................................................45 6 Usage Examples...................................................................................47 6.1 Exploring the Process of Fractals Calculation (Iterative Complex Functions). 47 6.1.1 Experiment Nr. 1..........................................................................................47 6.1.2 Experiment Nr. 2......................................................................................... 51 6.2 Z-Tranform and Transfer Functions of Digital Filters...................................... 56 7 Conclusion........................................................................................... 61 7.1 Findings................................................................................................................61 7.2 Future Work........................................................................................................62 Appendix A: A Survey on Function Plotters............................................63 A.1 Function Plotter Applications........................................................................... 64 A.2 Web-based Function Plotters........................................................................... 68 A.2.1 Server Side Plot Image Generators........................................................... 68 A.2.2 Java/Flash Applets....................................................................................69 A.3 Generic Data Plotters.........................................................................................71
Recommended publications
  • GPU-Based Visualization of Domain-Coloured Algebraic Riemann Surfaces
    GPU-based visualization of domain-coloured algebraic Riemann surfaces Stefan Kranich∗ 11 November 2015 Abstract We examine an algorithm for the visualization of domain-coloured Riemann surfaces of plane algebraic curves. The approach faithfully reproduces the topology and the holomorphic structure of the Riemann surface. We discuss how the algorithm can be implemented efficiently in OpenGL with geometry shaders, and (less efficiently) even in WebGL with multiple render targets and floating point textures. While the generation of the surface takes noticeable time in both implementations, the visualization of a cached Riemann surface mesh is possible with interactive performance. This allows us to visually explore otherwise almost unimaginable mathematical objects. As examples, we look at the complex square root and the folium of Descartes. For the folium of Descartes, the visualization reveals features of the algebraic curve that are not obvious from its equation. 1 Introduction 1.1 Mathematical background The following basic example illustrates what we would like to visualize. Example 1.1. Let y be the square root of x, p y = x: If x is a non-negative real number, we typically define y as the non-negative real arXiv:1507.04571v3 [cs.GR] 10 Nov 2015 number whose square equals x, i.e. we always choose the non-negative solution of the equation y2 − x = 0 (1) p as y = x. For negative real numbers x, no real number y solves Equation 1. However, if we define the imaginary unit i as a number with the property that i2 = −1 then the square root of x becomes the purely imaginary number y = ipjxj: ∗Zentrum Mathematik (M10), Technische Universit¨atM¨unchen, 85747 Garching, Germany; E-mail address: [email protected] 1 Im Im Re Re Figure 1.2: When a complex number (black points) runs along a circle centred at the origin of the complex plane, its square roots (white points) move at half the angular velocity (left image).
    [Show full text]
  • 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.
    [Show full text]
  • 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 ×Ó×ØÒÞÐ 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 × Ò×ØÐÐ ¿¿ ½½º ÓÑ × Ò×ØÐÐÒÓ 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 × Ò×ØÐÐ 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 ÖÛÐРгÒØÚÖÙ× 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 ×ØÖÙÞÓÒ 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 Ò×ØÐÐÞÓÒ ÏÒÓÛ×È ÃÍÙÒØÙ º½¼ ½¿¿ 40.1.
    [Show full text]
  • 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
    [Show full text]
  • Domain Coloring of Complex Functions
    Domain Coloring of Complex Functions Contents 1 Introduction Not only in mathematic we are confronted with graphs of all possible data sets. In economics and science we want to present the results by plotting their function graph inside a optimal coordinate system. In complex analysis we work with holomorphic functions which are complex differen- tiable. Like in real analysis we are interesting to plot such functions as graph inside a optimal coordinate systems. The graph of holomorphic functions is a subset of the four-dimensional coordinate system. But we are limited to three dimension, because we do not know how to draw objects in higher dimensional spaces. Therefore we are forced to construct a methode to visualize such functions. In this sec- tion we give a short overview of the domain coloring which allows us to visualize the graph of complex funtions by using colors. First we give a overview of complex analysis and holomorphic function. After we have presented the main idea behind the domain coloring we discuss a example to understand the main concept of domain coloring. 1 2 Introduction to Complex Analysis 2 Introduction to Complex Analysis In this section we give a short review of the main idea of complex analysis which we need to understand the methode of domain coloring. The reader should familiar with the construction of complex numbers and the representation of such numbers with polar coordinates. In complex anlysis we work with complex function which consist of three parts: first, a set D ⊂ C of input values, which is called the domain of the function, second, the range of f in C and third, for every input value x 2 D, a unique function value f(x) in the range of f.
    [Show full text]
  • Domain Coloring of Complex Functions
    Domain Coloring of Complex Functions Konstantin Poelke and Konrad Polthier 1 Introduction 2 What is a Function? Let us briefly recap the definition of a Visualizing functions is an omnipresent function to fix terminology. A function f task in many sciences and almost every day consists of three parts: first, a set D of in- we are confronted with diagrams in news- put values, which is called the domain of the papers and magazines showing functions of function, second, a set Y called the range of all possible flavours. Usually such func- f and third, for every input value x ∈ D, tions are visualized by plotting their func- a unique value y ∈ Y , called the function tion graph inside an appropriate coordinate value of f at x, denoted f(x). The set Γ(f) system, with the probably most prominent of all pairs (a, f(a)), a ∈ D, is a subset of choice being the cartesian coordinate sys- the product set D × Y and called the func- tem. This allows us to get an overall im- tion graph of f. pression of the function’s behaviour as well One particular type of functions that are as to detect certain distinctive features such widely used in engineering and physics are as minimal or maximal points or points complex functions, i.e. functions f : D ⊆ where the direction of curvature changes. C → Y ⊆ C whose domain and range In particular, we can “see” the dependence are subsets of the complex numbers, and between input and output. However, this we will focus on complex functions in the technique is limited to three dimensions, following.
    [Show full text]
  • Security Systems Services World Report
    Security Systems Services World Report established in 1974, and a brand since 1981. www.datagroup.org Security Systems Services World Report Database Ref: 56162 This database is updated monthly. Security Systems Services World Report SECURITY SYSTEMS SERVICES WORLD REPORT The Security systems services Report has the following information. The base report has 59 chapters, plus the Excel spreadsheets & Access databases specified. This research provides World Data on Security systems services. The report is available in several Editions and Parts and the contents and cost of each part is shown below. The Client can choose the Edition required; and subsequently any Parts that are required from the After-Sales Service. Contents Description ....................................................................................................................................... 5 REPORT EDITIONS ........................................................................................................................... 6 World Report ....................................................................................................................................... 6 Regional Report ................................................................................................................................... 6 Country Report .................................................................................................................................... 6 Town & Country Report ......................................................................................................................
    [Show full text]
  • Pipenightdreams Osgcal-Doc Mumudvb Mpg123-Alsa Tbb
    pipenightdreams osgcal-doc mumudvb mpg123-alsa tbb-examples libgammu4-dbg gcc-4.1-doc snort-rules-default davical cutmp3 libevolution5.0-cil aspell-am python-gobject-doc openoffice.org-l10n-mn libc6-xen xserver-xorg trophy-data t38modem pioneers-console libnb-platform10-java libgtkglext1-ruby libboost-wave1.39-dev drgenius bfbtester libchromexvmcpro1 isdnutils-xtools ubuntuone-client openoffice.org2-math openoffice.org-l10n-lt lsb-cxx-ia32 kdeartwork-emoticons-kde4 wmpuzzle trafshow python-plplot lx-gdb link-monitor-applet libscm-dev liblog-agent-logger-perl libccrtp-doc libclass-throwable-perl kde-i18n-csb jack-jconv hamradio-menus coinor-libvol-doc msx-emulator bitbake nabi language-pack-gnome-zh libpaperg popularity-contest xracer-tools xfont-nexus opendrim-lmp-baseserver libvorbisfile-ruby liblinebreak-doc libgfcui-2.0-0c2a-dbg libblacs-mpi-dev dict-freedict-spa-eng blender-ogrexml aspell-da x11-apps openoffice.org-l10n-lv openoffice.org-l10n-nl pnmtopng libodbcinstq1 libhsqldb-java-doc libmono-addins-gui0.2-cil sg3-utils linux-backports-modules-alsa-2.6.31-19-generic yorick-yeti-gsl python-pymssql plasma-widget-cpuload mcpp gpsim-lcd cl-csv libhtml-clean-perl asterisk-dbg apt-dater-dbg libgnome-mag1-dev language-pack-gnome-yo python-crypto svn-autoreleasedeb sugar-terminal-activity mii-diag maria-doc libplexus-component-api-java-doc libhugs-hgl-bundled libchipcard-libgwenhywfar47-plugins libghc6-random-dev freefem3d ezmlm cakephp-scripts aspell-ar ara-byte not+sparc openoffice.org-l10n-nn linux-backports-modules-karmic-generic-pae
    [Show full text]
  • Una Introducción Al Método De Dominio Colorado Con Geogebra Para
    101 Una introducción al método de dominio colorado con GeoGebra para la visualización y estudio de funciones complejas Uma introdução ao método do domínio colorado com GeoGebra para visualizar e estudar funções complexas An introduction the method domain coloring with GeoGebra for visualizing and studying complex JUAN CARLOS PONCE CAMPUZANO1 0000-0003-4402-1332 researchgate.net/profile/Juan_Ponce_Campuzano geogebra.org/u/jcponce http://dx.doi.org/10.23925/2237-9657.2020.v9i1p101-119 RESUMEN Existen diversos métodos para visualizar funciones complejas, tales como graficar por separado sus componentes reales e imaginarios, mapear o transformar una región, el método de superficies analíticas y el método de dominio coloreado. Este último es uno de los métodos más recientes y aprovecha ciertas características del color y su procesamiento digital. La idea básica es usar colores, luminosidad y sombras como dimensiones adicionales, y para visualizar números complejos se usa una función real que asocia a cada número complejo un color determinado. El plano complejo puede entonces visualizarse como una paleta de colores construida a partir del esquema HSV (del inglés Hue, Saturation, Value – Matiz, Saturación, Valor). Como resultado, el método de dominio coloreado permite visualizar ceros y polos de funciones, ramas de funciones multivaluadas, el comportamiento de singularidades aisladas, entre otras propiedades. Debido a las características de GeoGebra en cuanto a los colores dinámicos, es posible implementar en el software el método de dominio coloreado para visualizar y estudiar funciones complejas, lo cual se explica en detalle en el presente artículo. Palabras claves: funciones complejas, método de dominio coloreado, colores dinámicos. RESUMO Existem vários métodos para visualizar funções complexas, como plotar seus componentes reais e imaginários separadamente, mapear ou transformar uma região, o método de superfície analítica e o método de domínio colorido.
    [Show full text]
  • Domando Al Escritor, Edición 2016
    Domando al Escritor Edición 2016 LibreOfice™Writer para escritores Ricardo Gabriel Berlasso Domando al escritor LibreOfice™ Writer para escritores Ricardo Gabriel Berlasso © 2016 Ricardo Gabriel Berlasso Esta obra se distribuye bajo licencia Creative Commons Atribución-Compartir!gual 4.0 Internacional (CC B&-'A 4.0( %)* +,,creativecommons.or",licenses/by-sa,#.0,( Atribución+ -sted debe darle cr.dito a esta obra de manera adecuada/ pro orcionando un enlace a la licencia/ e indicando si se )an reali0ado cambios$ 1uede )acerlo en cual2uier forma ra0onable/ pero no de forma tal 2ue sugiera 2ue usted o su uso tienen el apoyo del licenciante$ Compartir Igual+ 'i usted me0cla/ transforma o crea nuevo material a partir de esta obra/ usted podr4 distribuir su contribución siempre 2ue utilice la misma licencia 2ue la obra ori"inal. No hay restricciones adicionales: -sted no puede aplicar t.rminos legales ni medidas tecnológicas 2ue restrinjan legalmente a otros )acer cual2uier uso permitido por la licencia. 5ibre6ffice es una marca de The Document Foundation$ A ac)e 6pen6ffice es una marca de Apache Software Foundation$ Cual2uier otra marca mencionada en este libro pertenece a sus respectivos propietarios. Este libro )a sido editado utili0ando 5ibre6ffice 8riter 9.0 y 9$1$ 5a ortada )a sido editada en 5ibre6ffice :ra; 9.0$ 5as principales fuentes tipo"r4ficas utili0adas son 5ibertinus 'ans, 5ibertinus 'eri3/ 5ibertinus =eyboard, Linux Libertine G, Linux Biolinum G y Deja?u Sans Mono$ La última versión de este libro se encuentra siempre en la siguiente dirección: https://elpinguinotolkiano. ordpress.com/domando!al!escritor!"/ Índice de contenido A. Introducción # $rólogo, "&#' ( A.1 Convenciones utili)adas en este libro ## A.2 Nociones generales #( 2$1 Ae>to vs.
    [Show full text]
  • Free Software for Engineers
    Indian Linux Users© Group, Chennai (ILUGC) in association with Thiagarajar College of Engineering, Madurai presents Free Software for Engineers by Shakthi Kannan MS Thiagarajar College of Engineering, Madurai GNU/Linux Programming ● C ● C++ ● Assembly ● Java ● Bash scripting ● Perl ● Python ● GUI Programming (GTK / Qt) ● Tcl/Tk GNU/Linux IDE/Text Editors ● Eclipse ● Anjuta ● KDevelop ● DrPython ● vi/vim ● GNU Emacs ● Pico / Nano ● Kate ● Kwrite ● gedit Eclipse IDE Source: http://ometer.com/eclipse-shots/eclipse-metacity.png What Software Tools? GNU/Linux Software Tools ● GNU C Compiler (gcc) ● GNU Assembler (gas) ● GNU C++ compiler (g++) ● GNU Debugger (gdb) ● Data Display Debugger (ddd) ● Java SDK ● Python ● Tcl Source: http://www.gnu.org/software/ddd/registers.jpg Java with Eclipse Source: http://www.depeupleur.com/blog/TT_blog/archives/000011.html GNU/Linux Math Tools ● Scilab ● r-project ● pspp ● IT++ ● GSL ● GNU Octave ● gnuplot ● LabPlot ● LaTeX Source: http://gnuplot.sourceforge.net/screenshots/figs/term-mouse-X11.png r-project Source: http://www.r-project.org/screenshots/desktop.jpg GNU/Linux EDA Tools ● Alliance ● gEDA ● PCB Tool ● EE Tool ● TkGate ● XCircuit ● gerbv ● gputils ● vlsi Source: http://www.tkgate.org/fig/scopewin.gif gEDA Source: http://www.geda.seul.org/screenshots/screenshot-qschem1.png PCB Source: http://bach.ece.jhu.edu/~haceaton/pcb/pcb_screen.gif TkGate Source: http://www.tkgate.org/fig/2.0/main.gif Gerber Viewer Source: http://gerbv.sourceforge.net/screenshot2.png What about Hardware? GNU/Linux Simulators/Emulators
    [Show full text]
  • Gifi Methods for Optimal Scaling in R: the Package Homals
    JSS Journal of Statistical Software August 2009, Volume 31, Issue 4. http://www.jstatsoft.org/ Gifi Methods for Optimal Scaling in R: The Package homals Jan de Leeuw Patrick Mair University of California, Los Angeles WU Wirtschaftsuniversit¨at Wien Abstract Homogeneity analysis combines the idea of maximizing the correlations between vari- ables of a multivariate data set with that of optimal scaling. In this article we present methodological and practical issues of the R package homals which performs homogeneity analysis and various extensions. By setting rank constraints nonlinear principal compo- nent analysis can be performed. The variables can be partitioned into sets such that homogeneity analysis is extended to nonlinear canonical correlation analysis or to predic- tive models which emulate discriminant analysis and regression models. For each model the scale level of the variables can be taken into account by setting level constraints. All algorithms allow for missing values. Keywords: Gifi methods, optimal scaling, homogeneity analysis, correspondence analysis, non- linear principal component analysis, nonlinear canonical correlation analysis, homals, R. 1. Introduction In recent years correspondence analysis (CA) has become a popular descriptive statistical method to analyze categorical data (Benz´ecri 1973; Greenacre 1984; Gifi 1990; Greenacre and Blasius 2006). Due to the fact that the visualization capabilities of statistical software have increased during this time, researchers of many areas apply CA and map objects and variables (and their respective categories) onto a common metric plane. Currently, R (R Development Core Team 2009) offers a variety of routines to compute CA and related models. An overview of functions and packages is given in Mair and Hatzinger (2007).
    [Show full text]