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Plotting Direction Fields in Matlab and Maxima – a Short Tutorial
Plotting direction fields in Matlab and Maxima – a short tutorial Luis Carvalho Introduction A first order differential equation can be expressed as dx x0(t) = = f(t; x) (1) dt where t is the independent variable and x is the dependent variable (on t). Note that the equation above is in normal form. The difficulty in solving equation (1) depends clearly on f(t; x). One way to gain geometric insight on how the solution might look like is to observe that any solution to (1) should be such that the slope at any point P (t0; x0) is f(t0; x0), since this is the value of the derivative at P . With this motivation in mind, if you select enough points and plot the slopes in each of these points, you will obtain a direction field for ODE (1). However, it is not easy to plot such a direction field for any function f(t; x), and so we must resort to some computational help. There are many computational packages to help us in this task. This is a short tutorial on how to plot direction fields for first order ODE’s in Matlab and Maxima. Matlab Matlab is a powerful “computing environment that combines numeric computation, advanced graphics and visualization” 1. A nice package for plotting direction field in Matlab (although resourceful, Matlab does not provide such facility natively) can be found at http://math.rice.edu/»dfield, contributed by John C. Polking from the Dept. of Mathematics at Rice University. To install this add-on, simply browse to the files for your version of Matlab and download them. -
CAS (Computer Algebra System) Mathematica
CAS (Computer Algebra System) Mathematica- UML students can download a copy for free as part of the UML site license; see the course website for details From: Wikipedia 2/9/2014 A computer algebra system (CAS) is a software program that allows [one] to compute with mathematical expressions in a way which is similar to the traditional handwritten computations of the mathematicians and other scientists. The main ones are Axiom, Magma, Maple, Mathematica and Sage (the latter includes several computer algebras systems, such as Macsyma and SymPy). Computer algebra systems began to appear in the 1960s, and evolved out of two quite different sources—the requirements of theoretical physicists and research into artificial intelligence. A prime example for the first development was the pioneering work conducted by the later Nobel Prize laureate in physics Martin Veltman, who designed a program for symbolic mathematics, especially High Energy Physics, called Schoonschip (Dutch for "clean ship") in 1963. Using LISP as the programming basis, Carl Engelman created MATHLAB in 1964 at MITRE within an artificial intelligence research environment. Later MATHLAB was made available to users on PDP-6 and PDP-10 Systems running TOPS-10 or TENEX in universities. Today it can still be used on SIMH-Emulations of the PDP-10. MATHLAB ("mathematical laboratory") should not be confused with MATLAB ("matrix laboratory") which is a system for numerical computation built 15 years later at the University of New Mexico, accidentally named rather similarly. The first popular computer algebra systems were muMATH, Reduce, Derive (based on muMATH), and Macsyma; a popular copyleft version of Macsyma called Maxima is actively being maintained. -
Sage Tutorial (Pdf)
Sage Tutorial Release 9.4 The Sage Development Team Aug 24, 2021 CONTENTS 1 Introduction 3 1.1 Installation................................................4 1.2 Ways to Use Sage.............................................4 1.3 Longterm Goals for Sage.........................................5 2 A Guided Tour 7 2.1 Assignment, Equality, and Arithmetic..................................7 2.2 Getting Help...............................................9 2.3 Functions, Indentation, and Counting.................................. 10 2.4 Basic Algebra and Calculus....................................... 14 2.5 Plotting.................................................. 20 2.6 Some Common Issues with Functions.................................. 23 2.7 Basic Rings................................................ 26 2.8 Linear Algebra.............................................. 28 2.9 Polynomials............................................... 32 2.10 Parents, Conversion and Coercion.................................... 36 2.11 Finite Groups, Abelian Groups...................................... 42 2.12 Number Theory............................................. 43 2.13 Some More Advanced Mathematics................................... 46 3 The Interactive Shell 55 3.1 Your Sage Session............................................ 55 3.2 Logging Input and Output........................................ 57 3.3 Paste Ignores Prompts.......................................... 58 3.4 Timing Commands............................................ 58 3.5 Other IPython -
Titular Capítulo
Jornadas In-Red 2014 Universitat Politècnica de València Doi************** Experiencias de aplicación de la simulación empleando software libre y gratuito en la enseñanza de las ingenierías de la rama industrial Asunción Santafé Morosa, José M. Gozálvez Zafrillaa, Javier Navarro Laboulaisa, Salvador Cardona Navarretea, Rafael Miró Herreroa, Juan Carlos García Díazb a Departamento de Ingeniería Química y Nuclear, Universitat Politècnica de Valencia, [email protected] b Departamento de Estadística e Investigación Operativa, Universitat Politècnica de Valencia. Resumen En este trabajo se presentan las experiencias de utilización de software libre y gratuito llevadas a cabo por el Equipo de Innovación y Calidad Educativa ASEI (Aplicación de la Simulación en la Enseñanza de la Ingeniería) en asignaturas de las áreas de Ingeniería Química, Nuclear y Estadística que requieren la utilización de software de cálculo y herramientas de simulación. El software libre puede ser utilizado como una herramienta en metodologías docentes basadas en el uso de la simulación en el aula de teoría o bien como una forma de disminuir los costes en la enseñanza y aportar nuevos valores. Adecuadamente empleadas, las metodologías basadas en el uso de programas de simulación pueden estimular la capacidad de autoaprendizaje del alumno. En esta comunicación se muestran ejemplos del amplio abanico de aplicaciones de software que se pueden utilizar sin representar coste para la Universidad y posteriormente para la empresa. Palabras clave: competencias, formación, metodologías activas, simulación, software libre. 2014, Universitat Politècnica de València 1 I Jornadas In-Red (2014): 1-9 Experiencias de aplicación de la simulación empleando software libre y gratuito en la enseñanza de las ingenierías de la rama industrial 1. -
Highlighting Wxmaxima in Calculus
mathematics Article Not Another Computer Algebra System: Highlighting wxMaxima in Calculus Natanael Karjanto 1,* and Husty Serviana Husain 2 1 Department of Mathematics, University College, Natural Science Campus, Sungkyunkwan University Suwon 16419, Korea 2 Department of Mathematics Education, Faculty of Mathematics and Natural Science Education, Indonesia University of Education, Bandung 40154, Indonesia; [email protected] * Correspondence: [email protected] Abstract: This article introduces and explains a computer algebra system (CAS) wxMaxima for Calculus teaching and learning at the tertiary level. The didactic reasoning behind this approach is the need to implement an element of technology into classrooms to enhance students’ understanding of Calculus concepts. For many mathematics educators who have been using CAS, this material is of great interest, particularly for secondary teachers and university instructors who plan to introduce an alternative CAS into their classrooms. By highlighting both the strengths and limitations of the software, we hope that it will stimulate further debate not only among mathematics educators and software users but also also among symbolic computation and software developers. Keywords: computer algebra system; wxMaxima; Calculus; symbolic computation Citation: Karjanto, N.; Husain, H.S. 1. Introduction Not Another Computer Algebra A computer algebra system (CAS) is a program that can solve mathematical problems System: Highlighting wxMaxima in by rearranging formulas and finding a formula that solves the problem, as opposed to Calculus. Mathematics 2021, 9, 1317. just outputting the numerical value of the result. Maxima is a full-featured open-source https://doi.org/10.3390/ CAS: the software can serve as a calculator, provide analytical expressions, and perform math9121317 symbolic manipulations. -
Programming for Computations – Python
15 Svein Linge · Hans Petter Langtangen Programming for Computations – Python Editorial Board T. J.Barth M.Griebel D.E.Keyes R.M.Nieminen D.Roose T.Schlick Texts in Computational 15 Science and Engineering Editors Timothy J. Barth Michael Griebel David E. Keyes Risto M. Nieminen Dirk Roose Tamar Schlick More information about this series at http://www.springer.com/series/5151 Svein Linge Hans Petter Langtangen Programming for Computations – Python A Gentle Introduction to Numerical Simulations with Python Svein Linge Hans Petter Langtangen Department of Process, Energy and Simula Research Laboratory Environmental Technology Lysaker, Norway University College of Southeast Norway Porsgrunn, Norway On leave from: Department of Informatics University of Oslo Oslo, Norway ISSN 1611-0994 Texts in Computational Science and Engineering ISBN 978-3-319-32427-2 ISBN 978-3-319-32428-9 (eBook) DOI 10.1007/978-3-319-32428-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2016945368 Mathematic Subject Classification (2010): 26-01, 34A05, 34A30, 34A34, 39-01, 40-01, 65D15, 65D25, 65D30, 68-01, 68N01, 68N19, 68N30, 70-01, 92D25, 97-04, 97U50 © The Editor(s) (if applicable) and the Author(s) 2016 This book is published open access. Open Access This book is distributed under the terms of the Creative Commons Attribution-Non- Commercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, a link is provided to the Creative Commons license and any changes made are indicated. -
Linux Mint Debian Edition (LMDE) Di Giorgio Beltrammi
Guida a Linux Mint Debian Edition Guida a Linux Mint Debian Edition (LMDE) di Giorgio Beltrammi 1 2 Guida a Linux Mint Debian Edition 3 4 Guida a Linux Mint Debian Edition INDICE INTRODUZIONE ¼................................. 9 Note di Consultazione ¼........................ 9 Linux Mint Debian Edition ¼.................... 11 Per utenti Windows ¼........................... 17 DOWNLOAD & MASTERIZZAZIONE .................... 23 Download & Masterizzazione ¼................... 23 Download....................................... 25 Checksum....................................... 27 LIVE & INSTALLAZIONE ¼......................... 29 Cos©è un sistema Live.......................... 29 Partizionamento ¼.............................. 33 Installazione ¼................................ 39 Postinstallazione.............................. 47 Personalizzare Mint............................ 53 PERSONALE...................................... 61 Applicazioni d©avvio ¼......................... 61 Applicazioni preferite......................... 65 Gestione File.................................. 67 Scorciatoie Tastiera.......¼................... 69 Tecnologie Assistive........................... 71 ASPETTO & STILE................................ 73 Aspetto........................................ 73 Impostazioni del Desktop....................... 79 Menu Principale................................ 81 Salvaschermo................................... 85 INTERNET & RETE................................ 87 Bluetooth...................................... 87 5 Condivisione -
They Have Very Good Docs At
Intro to the Julia programming language Brendan O’Connor CMU, Dec 2013 They have very good docs at: http://julialang.org/ I’m borrowing some slides from: http://julialang.org/blog/2013/03/julia-tutorial-MIT/ 1 Tuesday, December 17, 13 Julia • A relatively new, open-source numeric programming language that’s both convenient and fast • Version 0.2. Still in flux, especially libraries. But the basics are very usable. • Lots of development momentum 2 Tuesday, December 17, 13 Why Julia? Dynamic languages are extremely popular for numerical work: ‣ Matlab, R, NumPy/SciPy, Mathematica, etc. ‣ very simple to learn and easy to do research in However, all have a “split language” approach: ‣ high-level dynamic language for scripting low-level operations ‣ C/C++/Fortran for implementing fast low-level operations Libraries in C — no productivity boost for library writers Forces vectorization — sometimes a scalar loop is just better slide from ?? 2012 3 Bezanson, Karpinski, Shah, Edelman Tuesday, December 17, 13 “Gang of Forty” Matlab Maple Mathematica SciPy SciLab IDL R Octave S-PLUS SAS J APL Maxima Mathcad Axiom Sage Lush Ch LabView O-Matrix PV-WAVE Igor Pro OriginLab FreeMat Yorick GAUSS MuPad Genius SciRuby Ox Stata JLab Magma Euler Rlab Speakeasy GDL Nickle gretl ana Torch7 slide from March 2013 4 Bezanson, Karpinski, Shah, Edelman Tuesday, December 17, 13 Numeric programming environments Core properties Dynamic Fast? and math-y? C/C++/ Fortran/Java − + Matlab + − Num/SciPy + − R + − Older table: http://brenocon.com/blog/2009/02/comparison-of-data-analysis-packages-r-matlab-scipy-excel-sas-spss-stata/ Tuesday, December 17, 13 - Dynamic vs Fast: the usual tradeof - PL quality: more subjective. -
Teaching Dynamical Systems with Maxima 1. Mechanics For
125 Teaching Dynamical Systems with Maxima Jaime E. Viliate University of Porto, Faculty of Engineering Rua Dr. Roberto Frias, Porto 42OO-~65, Portugal, villatec~fe.up.pt WWW home page: http://viliate.org/ We report on our experience in teaching a dynamical systems course to second year engineering students. The course has been taught with a hands-on ap proach, using a Computer Algebra System: Maxima. We have developed some additional programs to help students explore the dynamics of the systems, in a more intuitiva way and without losing too much time with computer program ming. The result has been very encouraging; students are better motivated using this approach, as compared to the more traditional methods that we used in the past. 1. Mechanics for Engineering students Our engineering students in the University of Porto have to take two courses in Physics during their first. or second year of studies. The first course is a course on Newtonian mechanics. When they attend that course, they have already taken one or two semesters of calculus, and during their high-school studies they must have already studied particle kinematics and dynamics. The main goal of the first course in physics is then to solve the equations of motion for some mechanical systems; for example, for a one-dimensional system the equations of motion are: (1) .F(x,v) (2) where x is the position, v the speed, m the mass and F is the total external force, which might depend on x and v. In general, equations 1 and 2 lead to a non-linear system. -
Maxima by Example: Ch. 1, Getting Started ∗
Maxima by Example: Ch. 1, Getting Started ¤ Edwin L. Woollett Contents 1 Getting Started 2 1.1 Introduction . 2 1.1.1 What is Maxima? . 2 1.2 Using the XMaxima Interface . 2 1.2.1 Using Console - Command Line Maxima . 3 1.2.2 Text Editors . 3 1.2.3 The Maxima Manual . 3 1.3 Expressions in Maxima . 4 1.3.1 Operators in Maxima . 4 1.3.2 Numbers in Maxima . 5 1.3.3 Variables in Maxima . 6 1.3.4 Constants in Maxima . 7 1.3.5 Rational Expressions in Maxima, rat(...) . 8 1.4 List Creation and Manipulation . 9 1.4.1 The Maxima List and the Lisp List . 10 1.4.2 cons, endcons, append . 10 1.4.3 makelist and map . 11 1.4.4 Anonymous Unnamed Function lamda . 14 1.4.5 Accessing List Elements Using part(...) or Bracket Pairs . 15 1.4.6 Creating a List of Fractional Values . 15 1.5 Data Files: Read, Write, Fit, and Plot . 15 1.5.1 le search . 15 1.5.2 le search maxima . 16 1.5.3 maxima-init.mac and maxima userdir . 17 1.5.4 Viewing a File with printle . 18 1.5.5 Creating a Data File using with stdout . 18 1.5.6 Creating a List from a Data File: read nested list . 18 1.5.7 Write List to Data File with write data . 19 1.5.8 Using Random Numbers to Create Noisy Data . 19 1.5.9 Using lsquares estimates for a Fit . 21 1.5.10 Nested List $ Matrix using apply and substpart . -
CAS Maxima Workbook
CAS Maxima Workbook Roland Salz January 7, 2021 Vers. 0.3.6 This work is published under the terms of the Creative Commons (CC) BY-NC-ND 4.0 license. You are free to: Share — copy and redistribute the material in any medium or format Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. NonCommercial — You may not use the material for commercial purposes. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. As an exception to the above stated terms, the Maxima team is free to incorporate any material from this work into the official Maxima manual, and to remix, transform, or build upon this material within the official Maxima manual, to be published under its own license terms. No attribution is required in this case. Copyright © Roland Salz 2018-2021 No warranty whatsoever is given for the correctness or completeness of the information provided. Maple, Mathematica, Windows, and YouTube are registered trademarks. This project is work in progress. Comments and suggestions for improvement are welcome. Roland Salz Braunsberger Str. 26 D-44809 Bochum [email protected] i In some cases the objective is clear, and the results are surprising. Richard J. Fateman ii Preface Maxima was developed from 1968-1982 at MIT (Massachusetts Institute of Tech- nology) as the first comprehensive computer algebra system (CAS). -
Methods of Using Mobile Internet Devices in the Formation of The
217 Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects Yevhenii O. Modlo1[0000-0003-2037-1557], Serhiy O. Semerikov2,3,4[0000-0003-0789-0272], Stanislav L. Bondarevskyi3[0000-0003-3493-0639], Stanislav T. Tolmachev3[0000-0002-5513-9099], Oksana M. Markova3[0000-0002-5236-6640] and Pavlo P. Nechypurenko2[0000-0001-5397-6523] 1 Kryvyi Rih Metallurgical Institute of the National Metallurgical Academy of Ukraine, 5, Stephana Tilhy Str., Kryvyi Rih, 50006, Ukraine [email protected] 2 Kryvyi Rih State Pedagogical University, 54, Gagarina Ave., Kryvyi Rih, 50086, Ukraine [email protected], [email protected] 3 Kryvyi Rih National University, 11, Vitaliy Matusevych Str., Kryvyi Rih, 50027, Ukraine [email protected], [email protected], [email protected] 3 Institute of Information Technologies and Learning Tools of NAES of Ukraine, 9, M. Berlynskoho Str., Kyiv, 04060, Ukraine Abstract. An analysis of the experience of professional training bachelors of electromechanics in Ukraine and abroad made it possible to determine that one of the leading trends in its modernization is the synergistic integration of various engineering branches (mechanical, electrical, electronic engineering and automation) in mechatronics for the purpose of design, manufacture, operation and maintenance electromechanical equipment. Teaching mechatronics provides for the meaningful integration of various disciplines of professional and practical training bachelors of electromechanics based on the concept of modeling and technological integration of various organizational forms and teaching methods based on the concept of mobility. Within this approach, the leading learning tools of bachelors of electromechanics are mobile Internet devices (MID) – a multimedia mobile devices that provide wireless access to information and communication Internet services for collecting, organizing, storing, processing, transmitting, presenting all kinds of messages and data.