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Sage Beginner's Guide
Sage Beginner's Guide

Sage Beginner's Guide: Unlock the full potential of Sage for simplifying and automating mathematical computing with this book and eBook

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Sage Beginner's Guide

Chapter 2. Installing Sage

Remember that you don't actually have to install Sage to start using it. You can start learning Sage by utilizing one of the free public notebook servers that can be found at http://www.sagenb.org/. However, if you find that Sage suits your needs, you will want to install a copy on your own computer. This will guarantee that Sage is always available to you, and it will reduce the load on the public servers so that others can experiment with Sage. In addition, your data will be more secure, and you can utilize more computing power to solve larger problems. This chapter will take you through the process of installing Sage on various platforms.

In this chapter we shall:

  • Install a binary version of Sage on Windows and install a binary version of Sage on OS X

  • Install a binary version of Sage on GNU/Linux

  • Compile Sage from source

Before you begin


At the moment, Sage is fully supported on certain versions of the following platforms: some Linux distributions (Fedora, openSUSE, Red Hat, and Ubuntu), Mac OS X, OpenSolaris, and Solaris. Sage is tested on all of these platforms before each release, and binaries are always available for these platforms. The latest list of supported platforms is available at http://wiki.sagemath.org/SupportedPlatforms. The page also contains information about platforms that Sage will probably run on, and the status of efforts to port Sage to various platforms.

When downloading Sage, the website attempts to detect which operating system you are using, and directs you to the appropriate download page. If it sends you to the wrong download page, use the "Download" menu at the top of the page to choose the correct platform. If you get stuck at any point, the official Sage installation guide is available at http://www.sagemath.org/doc/installation/.

Installing a binary version of Sage on Windows


Installing Sage on Windows is slightly more involved than installing a typical Windows program. Sage is a collection of over 90 different tools. Many of these tools are developed within a UNIX-like environment, and some have not been successfully ported to Windows. Porting programs from UNIX-like environments to Windows requires the installation of Cygwin (http://www.cygwin.com/), which provides many of the tools that are standard on a Linux system. Rather than attempting to port all of the necessary tools to Cygwin on Windows, the developers of Sage have chosen to distribute Sage as a virtual machine that can run on Windows with the use of the free VMWare Player. A port to Cygwin is in progress, and more information can be found at http://trac.sagemath.org/sage_trac/wiki/CygwinPort.

Downloading VMware Player

The VMWare Player can be found at http://www.vmware.com/products/player/. Clicking the Download link will direct you to a registration form...

Installing a binary version of Sage on OS X


On Mac OS X, you have the option of installing a pre-built binary application, or downloading the source code and compiling Sage yourself. One advantage of the pre-built binary is that it is very easy to install, because it contains everything you need to run Sage. Another advantage of the binary is that building Sage from source requires a lot of computational resources, and may take a long time on older machines. However, there are a number of disadvantages to prebuilt binaries. The binary download is quite large, and the installed files take up a lot of disk space. Many of the tools in the binary may be duplicates of tools you already have on your system. Pre-built binaries cannot be tuned to take advantage of the hardware features of a particular platform, so building Sage from source is preferred if you are looking for the best performance on CPU-intensive tasks. You will have to choose which method is right for you.

Downloading Sage

Download...

Installing a binary version of Sage on GNU/Linux


As with Mac OS X, you have the option of installing a pre-built binary application for your version of Linux, or downloading the source code and compiling Sage yourself. The same trade-offs apply to Linux. Keep in mind that the Sage team only distributes pre-build binaries for a few popular distributions. If you are using a different distribution, you'll have to compile Sage from source anyway. The following instructions will assume you are downloading a binary application. I will use Ubuntu as an example, but other versions of Linux should be very similar.

Note

Most modern Linux distributions use a package manager to install and remove software. Sage is not available as an officially supported package for any Linux distribution at this time. "Unofficial" packages have been created for Debian, Mandriva, Ubuntu, and possibly others, but they are unlikely to be up to date and may not work properly. An effort to integrate Sage with Gentoo Linux...

Building Sage from source


This section will describe how to build Sage from source code on OS X or Linux. Although Sage consists of nearly 100 packages, the build process hides much of the complexity. It is impossible to provide instructions for all of the platforms that can build Sage, but the following guidelines should cover most cases. The official documentation for building Sage from source is available at http://sagemath.org/doc/installation/source.html.

Prerequisites

In order to compile Sage, you will need about 2.5GB of free disk space, and the following tools must be installed:

  • GCC

  • g++

  • gfortran

  • make

  • m4

  • perl

  • ranlib

  • tar

  • readline and its development headers

  • ssh-keygen (only needed to run the notebook in secure mode)

  • latex (highly recommended, though not strictly required)

If you are running OS X (version 10.4 or later), install XCode to get all of these tools. XCode is available for free when you sign up as a developer at http://developer.apple.com/. Make sure that you have XCode version 2.4 or...

Summary


At this point, you should have a functioning Sage installation on your machine. In the next chapter, you'll learn the basics of using Sage.

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What you will learn

  • Download and install Sage, and learn how to use the command-line and notebook interface Learn the basics of Python programming Solve problems in linear algebra with vectors and matrices Visualize functions and data sets with publication-quality graphics Define, re-arrange, and simplify symbolic expressions Calculate integrals, derivatives, and transforms symbolically and numerically Solve ordinary differential equations (ODEs) and systems of ODEs Fit functions to data using unconstrained and constrained numerical optimization Apply object-oriented principles to simplify your code Speed up calculations with Numpy arrays Learn to use Sage as a toolbox for writing Python programs
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Table of Contents

10 Chapters
What Can You Do with Sage? Chevron down icon Chevron up icon
Installing Sage Chevron down icon Chevron up icon
Getting Started with Sage Chevron down icon Chevron up icon
Introducing Python and Sage Chevron down icon Chevron up icon
Vectors, Matrices, and Linear Algebra Chevron down icon Chevron up icon
Plotting with Sage Chevron down icon Chevron up icon
Making Symbolic Mathematics Easy Chevron down icon Chevron up icon
Solving Problems Numerically Chevron down icon Chevron up icon
Learning Advanced Python Programming Chevron down icon Chevron up icon
Where to go from here Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.9
(11 Ratings)
5 star 27.3%
4 star 54.5%
3 star 9.1%
2 star 0%
1 star 9.1%
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David Joyner Jun 16, 2011
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The book under review is a book on Sage, an open source mathematical software package started by William Stein, a mathematician at the University of Washington. It is very carefully written (either that, or very carefully reviewed by the Technical Reviewers!) and aimed, as the title suggests, at the beginner. However, it is assumed that the reader knows some undergraduate mathematics, say the level one obtains from getting an engineering degree. In fact, it has a bit of an applied slant with many examples from physics and engineering mathematics. This is a welcome contrast to the excellent Sage Tutorial (available free from the Sage website, sagemath.org) which has a more of a pure slant. It's nice to see a publisher like Packt Publishing take the risk of publishing a book like this on an open source software program which already has free documentation (in pdf or html form).There are 10 chapters and it's about 350 pages. Although Sage of course has color plotting, all figures in this book are in black and white, so the reader really must try out the Sage code given in the book to get the full effect. Each chapter features many "Time for action" Sage code examples (also conveniently listed in the table of contents at the front of the book), followed by a "What just happened?" section explaining in detail (and without computer code) what the example did. These make the book more useful to the beginner as well as for someone wanting a quick reference for one of the examples. All these examples use the command-line version of Sage (typing your commands into a terminal window at a sage: prompt) but there are several sections explaining the GUI version of Sage (typing your commands into a Mathematica-like "notebook cell") as well.Here is a chapter-by-chapter summary:The first chapter, "What can you do with Sage?", is a survey of some of Sage`s most commonly used capabilities. Examples such as solving a differential equations, plotting experimental data, and some simple example matrix computations are presented.The second chapter is "Installing Sage". This covers the steps you go though for a Mac OS, Windows, and Linux installation of Sage. Since this is scary for a number of users who are not very computer-savvy, it is nice an entire chapter is devoted to this.The third chapter, "Getting started with Sage", introduces the new Sage user to the user interface, basic Sage syntax, user-defined functions, and some of the available data types (such as strings and real number types)."Introducing Python and Sage", the fourth chapter, introduces syntax for Python lists, dictionaries, for loops, if-then statements, and also reading and writing to files. Sage is based on Python, a popular language used extensively in industry (at google among other places). This chapter introduces some very useful stuff, but is pretty basic if you know Python already.The 5th chapter is "Vectors, matrices and linear algebra". Sage has very wide functionality in linear algebra, with specialized packages for numerical computations for real and complex matrices, matrices over a finite field, or matrices having symbolic coefficients, such as functions of a variable x.Sage`s functionality in two-dimensional and three-dimensional plotting is described in the 6th chapter, "Plotting with Sage". There is 3-d "live-view" (i.e., you can use the mouse to rotate a plot of a surface or solid in 3-space), histogram plots, as well as simpler plots using Sage`s 2-d plotting package, matplotlib.Chapter 7 is "Making symbolic mathematics easy". Various topics are covered, from various calculus operations, such as limits, derivatives, integrals, and Laplace transforms, to exactsolutions to equations with variable coefficients, to infinite sums such as power series, to solving ordinary differential equations."Solving problems numerically" is the next chapter. This is the meat-and-potatoes for an applied mathematician. Sage includes many packages which have been developed to solve optimization problems, linear programming problems, numerical solutions of ordinary differential equations, numerical integration, and probability and statistics. These are introduced briefly in this chapter.The 9th chapter is "Learning advanced python programming". Here object-oriented programming is introduced by means of examples, and it is shown how Python handles errors and imports.The last chapter "Where to go from here" discusses selected miscellaneous advanced topics.Topics covered include: LaTeX, interactive plotting using the Sage notebook, as well as a fairly detailed example of analyzing colliding spheres in Sage from several different approaches.The book has a very good index and, overall I believe is a very welcomed addition to the literature of Sage books. Maybe it's just my generation, but to me it is a little expensive for a paperback. Because of that, and the fact that it is not as well-rounded as it could be, I'd rate it as 4.5 stars.
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Matthieu Brucher Jul 06, 2011
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I heard about Sage when I started learning Python, but I never quite gotten in the bandwagon. Now, this Beginner's Guide seems a good place to start.As with a lot of (all?) Packt Publishing Beginner's Guide, the book with a small introduction of what you can expect of the piece of software and its installation process on the three major platforms. Although for Windows the process is more complicated, the author gives the whole explanation, even on why the process is so complicated for this platform.Sage consists of several layers, Python being one of them, but there are many others. The book tries to dig a little bit further each time. The first "real" (i.e. outside the introductory and installation) chapter tackles the two main ways of using Sage, the interactive shell and the notebook. The different options and the basic usage are explained and illustrated with a lot of examples. The next step is mastering basic Python, which also done with the same efficiency as before.As Sage is mostly about math stuff, the book spends several chapters on the different APIs it offers to handle data. First, linear algebra and the different vectors and matrices are introduced, with a final reference to Numpy and its special arrays. Here is perhaps something lacking in this book: a reference to scipy. Indeed, scipy has a lot to offer in terms of linear algebgra, and it works with Numpy arrays. That being said, the common linear algebra issues will be solved by the Sage interface directly.A huge topic is graphics and scientific plots. The book exposes the different aspects of graphical Sage and also its main support package matplotlib. 3D graphics are also tackled, also they are only very recent in their current form in Matplotlib. It's a good surprise to see some examples here.From my point of view, the purpose of the whole book is the seventh chapter with the subject of symbolic math. The mathematical kernel can handle a lot of different input, rational numbers, trignometric expression, algebraic expressions, derivatives, integrals... Everything the Sage framework can handle is exposed. Also, if there is something it cannot directly handle, Sage can use numerical expressions to solve the issue (the eightth and final math chapter).The last two chapters are not on Sage directly, but more on Python and scientific publications. The Python programming chapter uses a war metaphor, and I guess there might have been another better and more adequate subject for Python programming. If you are used to Python, you may skip this one. The last one is about scientific publication, and eventually the optimization. This last topic is only touched, but it is given the necessary attention given the depth of Sage capabilities.Sometimes the book feels like a giant dictionnary of all the things you can do with Sage, and it actually is. And to find something, you may only have to browse the table of contents and get to the part you sought.Sage is an extraordinary beast, with pieces coming from a lot of different projects, and it's always difficult to know which project you are actually using. Sage acts like a wrapper for most applications, but once you need more, you can tap into the power of each subpackage. The book helps this process, with a good overview of Sage and a lot of real examples. There are some typos inside the book, but they are easily spotted if you mastered the previous chapter.
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Jerry L. Kreps Mar 03, 2012
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The latest release of the SAGE Math Engine was Jan 30, 2012, version 4.8.0. It has 11 PDF files documenting various aspects, but the primary documentation, "Reference.PDF" is 7,084 pages long. Composed of more than 100 Open Source math tools Integrated together seamlessly with a smooth and uniform user interface, written in Python, it is a dream to use. Its power and functionality is enhanced because it is free and freely updated. Although I've never used it, it has been reported that the user support community is pretty good as well.If you have FireFox running when you start SAGE FireFox will show a SAGE Notebook() tab, ready to create a new Notebook, or open an old one. There are plenty of video and graphical examples at the SAGE site that will give you examples of the power of the tool, and its ease of use.
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Marshall Hampton Jul 29, 2011
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I was asked by the publisher to review this book. They sent me a free copy; I have no other conflicts of interest. I am generally biased towards Sage itself ([...]), as an avid user and minor developer.Here on Amazon you can browse the table of contents, which gives a pretty good idea of the strengths of the book, namely basic computation and plotting, numerical calculations, and data analysis. The focus was an excellent choice considering what is already available. The current free Sage Tutorial ([...]) is oriented much more towards pure mathematicians. There is a Numerical Computing With Sage ([...]) as part of the standard documentation ([...]), but at the moment its quite short and nowhere near as helpful as Finch's book.I liked the style of the book a lot. There are many code examples that illustrate how to accomplish concrete tasks, along with good explanations of what they are doing. Many of these are things that are unfortunately far from obvious to a beginner (or even intermediate) Sage user. Despite using Sage heavily for the last five years, I learned some new things. The book is particularly strong in showing how to use Numpy, Scipy, and Matplotlib. Sage wraps a lot of the functionality of these projects, but if you want to do something that isn't included in the standard interfaces it can be quite mystifying.Chapter 9, "Learning Advanced Python Programming", might have been a little ambitious. There's nothing wrong with it, but its too short to provide enough. Fortunately there are a lot of good books, some of them free, that cover Python programming in much more depth. I would have preferred some of this space and effort to be devoted to using Cython and the @interact command, which are covered very briefly in Chapter 10.I teach several classes using Sage and I will definitely advertise this text as a useful optional supplement (I consider it a little too expensive to add on as a mandatory second text). It would be nice if some institutions considered using Sage instead of its commercial competitors such as Maple, Matlab, and Mathematica - you could probably give every student a copy of this book for the money saved from license fees!The only thing I disliked about the book was the quality of the illustrations. Sage output that was in LaTeX was not typeset, but instead looks as if a PNG was copied from a screenshot. Some of the examples would have benefited from being in color. The quality of the plots is also somewhat poor. This is not too big a deal if one is following along with Sage, since you can reproduce the figures. None of them are bad enough to obscure the content.Overall this is a very impressive and useful introduction to Sage that should help any beginning user a great deal.
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tama_mononoke Feb 24, 2012
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SageはPythonをベースとしたフリーの数式処理システムです。仕事でSageを使うこととなり、Sageのチュートリアルとマニュアルはホームページからダウンロードしました。これらのドキュメントはPythonを使ったことがない私にとっては分かりにくいものでした。そのため、手頃な入門書がないか探したところ、「Sage -- Beginner's guide」を見つけることができました。(それ以外の本は見つけることができませんでした。) 「Sage -- Beginner's guide」は、その名の通り、今までSageの名前も聞いたことのない初学者向けに書かれています。行列/ベクトル演算・数式処理・数値計算・グラフ描画等のSageの基本機能はもちろんのこと、配列(リスト)・ハッシュの使い方や、クラス定義の方法などのPythonに関する説明も丁寧に書かれています。 ただ、出力例・コード例に2,3ヶ所の間違いがあります。校正の不備だと思います。
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