Tutorials update
Michaël Baudin
michael.baudin at scilab.org
Mon Dec 20 17:09:30 CET 2010
Hi,
We have recently updated two documents which are provided to the Scilab
community under the "Creative Commons License". These documents are
provided in the Tutorials section of the scilab.org website :
http://www.scilab.org/support/documentation/tutorials
In "Introduction to Scilab" (updated 11/2010), we have added many
exercises, and their answers. More than 10 sections were added,
including "Issues with floating point integers", "Levels in the call
stack", "Matrices are dynamic", "Debugging with pause", "Contour plots",
and many more. Many thanks to Artem Glebov, who translated this document
into Russian and proofread the document.
In "Scilab is not naive" (updated 12/2010), we have added many exercises
in "Complex Division" and "Quadratic equation", with their answers. We
have udpated the "Why sin(pi) is rounded" and fixed many typos.
Best regards,
Michaël Baudin
PS
"Introduction to Scilab"
Overview of Scilab features to get familiar with this environment.
The goal is to present the core of skills necessary to start with
Scilab. In the first part, we present how to get and install this
software on our computer. We also present how to get some help with the
provided in-line documentation and also thanks to web resources and
forums. In the remaining sections, we present the Scilab language,
especially its structured programming features. We present an important
feature of Scilab, that is the management of real matrices and overview
the linear algebra library. The definition of functions and the
elementary management of input and output variables is presented. We
present Scilab graphics features and show how to create a 2D plot, how
to configure the title and the legend and how to export that plot into a
vectorial or bitmap format.
"Scilab is not naive"
Most of the time, the mathematical formula is directly used in the
Scilab source code. But, in many algorithms, some additional work is
performed, which takes into account the fact that the computer does not
process mathematical real values, but performs computations with their
floating point representation. The goal of this article is to show that,
in many situations, Scilab is not naive and use algorithms which have
been specifically tailored for floating point computers. We analyze in
this article the particular case of the quadratic equation, the complex
division and the numerical derivatives. In each example, we show that
the naive algorithm is not sufficiently accurate, while Scilab
implementation is much more robust.
--
Michaël Baudin
Ingénieur de développement
michael.baudin at scilab.org
-------------------------
Consortium Scilab - Digiteo
Domaine de Voluceau - Rocquencourt
B.P. 105 - 78153 Le Chesnay Cedex
Tel. : 01 39 63 56 87 - Fax : 01 39 63 55 94
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