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'''Scilab''' (http://scilab.org, http://scilab.in) is an open source scientific software package for numerical computations.  It has an extremely reliable and efficiently coded numerical library.  It is also a high productivity tool: Through its interpreted language, one can quickly develop the code required to solve problems.  Typically, if it takes ten lines of C code for some calculation, Scilab would require only one for the same purpose.   
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Scilab (http://scilab.org, http://scilab.in, http://scilab.cn) is an open source scientific software package for numerical computations.  It has an extremely reliable and efficiently coded numerical library.  It is also a high productivity tool: Through its interpreted language, one can quickly develop the code required to solve problems.  Typically, if it takes ten lines of C code for some calculation, Scilab would require only one for the same purpose.   
+
  
 
Scilab runs on all popular operating systems.  Since 1994, it has been distributed freely along with the source code via the Internet.  It is useful for students at school, college and <span class="plainlinks">[http://www.netlook.com.br/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">roupas da moda</span>] research level.  It is also useful for researchers and professionals.
 
Scilab runs on all popular operating systems.  Since 1994, it has been distributed freely along with the source code via the Internet.  It is useful for students at school, college and <span class="plainlinks">[http://www.netlook.com.br/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">roupas da moda</span>] research level.  It is also useful for researchers and professionals.
  
−
IIT Bombay is leading the effort to popularise Scilab in India.  This is part of the Free and Open source Software for Science and Engineering Education (FOSSEE) project, supported by the National Mission on Education through ICT of MHRD (http://spoken-tutorial.org/NMEICT-Intro).
+
IIT Bombay is leading the effort to popularise Scilab in India.  This is part of the Free and Open source Software for Science and Engineering Education (FOSSEE) project, supported by the National Mission on Education through ICT of MHRD.
  
 
IIT Bombay is using Spoken Tutorials (http://spoken-tutorial.org) to create learning material for FOSS.  This is the main page for the organisation of the scripts required for Scilab spoken tutorials.  We invite the Scilab user community to participate in this activity.
 
IIT Bombay is using Spoken Tutorials (http://spoken-tutorial.org) to create learning material for FOSS.  This is the main page for the organisation of the scripts required for Scilab spoken tutorials.  We invite the Scilab user community to participate in this activity.
  
 +
'''Learners''': All Science and Engineering Students.
 +
 +
 +
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<blockquote style="background-color: lemonchiffon; border: solid thin grey;">
 +
The Spoken Tutorial Effort for Scilab is being contributed by Shalini Shrivastava, Rupak Rokade, Anuradha Amruthkar, Manas Ranjan Das, Mukul Kulkarni, Shamika Mohanan, Lavitha Pereira from IIT Bombay.
 +
 +
</blockquote>
 
__TOC__
 
__TOC__
  
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=General Information=
 
=General Information=
 
This topic will include all functionality in Scilab that <span class="plainlinks">[http://thebeginnerslens.com/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">iphone photography</span>] is not domain specific- functionality that is required across several domains.  
 
This topic will include all functionality in Scilab that <span class="plainlinks">[http://thebeginnerslens.com/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">iphone photography</span>] is not domain specific- functionality that is required across several domains.  
−
== Why Scilab ==
 
−
 
 
==Basic Level Introduction to Scilab==
 
==Basic Level Introduction to Scilab==
 
This level will include a set of tutorials that are required to be known in order to qualify as "Scilab Literate". The tutorials here will teach programming <span class="plainlinks">[http://www.bestpills4weightloss.com/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">weight loss pills</span>]
 
This level will include a set of tutorials that are required to be known in order to qualify as "Scilab Literate". The tutorials here will teach programming <span class="plainlinks">[http://www.bestpills4weightloss.com/ <span style="color:black;font-weight:normal; text-decoration:none!important; background:none!important; text-decoration:none;">weight loss pills</span>]
 
fundamentals and the most commonly used Scilab functionality- Matrix operations and Plotting.  
 
fundamentals and the most commonly used Scilab functionality- Matrix operations and Plotting.  
−
#  Installing   
+
#  '''Installing'''  
 
#* Show where to download from and how to decide which version to choose  
 
#* Show where to download from and how to decide which version to choose  
 
#* Windows installation  
 
#* Windows installation  
Line 27: Line 32:
 
#* Mac
 
#* Mac
 
#* Compilation from source can come as a part of a more advanced tutorial
 
#* Compilation from source can come as a part of a more advanced tutorial
−
# Getting Started: Basic Housekeeping
+
# '''Getting Started'''
 
#* Expressions: Show mathematical expressions with numbers  
 
#* Expressions: Show mathematical expressions with numbers  
 
#* Variables
 
#* Variables
Line 35: Line 40:
 
#* suppressing output(;)
 
#* suppressing output(;)
 
#* help,clc
 
#* help,clc
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# Matrix Operations
+
#'''Vector Operations'''
−
#Vector Operations  
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#*Define vector
−
#* Define vector
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#*Calculate length of a vector.
−
# Matrix Operations
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#*Perform mathematical operations on Vectors such as addition,subtraction and multiplication.
−
#* Square matrices
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#*Define a matrix.
−
#* det(Q), diag(Q)
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#*Calculate size of a matrix.
−
#* Matrix generation: zeros(3,4), ones(2,5), eye(4,4), diag([1 2 3]), rand(2,3).
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#*Perform mathematical operations on Matrices such as addition, subtraction and multiplication.
−
#* Ranges: 1:4, 2:2:8, linspace(1, 9, 5) (linspace is to be explained in Plotting 2D graphs tutorial)
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#'''Matrix Operations'''
−
#* Elementary row operations
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#*Access the elements of Matrix
−
#* Solving equations
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#*Determine the determinant, inverse and eigen values of a matrix.
−
# Conditional Branching  
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#*Define special matrices.
−
#* Explain booleans
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#*Perform elementary row operations.
−
#* First explain 'if' and 'then' with the example
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#*Solve the system of linear equations.
−
#* Now explain the use of the 'else' keyword
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#''' Conditional Branching'''
−
#* Now explain the use of the 'elseif' keyword
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#*'if' and 'then' with the example  
−
#* Say that if there are several branches, it may be clearer to use the 'select' keyword.
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#*use of the 'else' keyword  
−
#* Give example for select
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#*use of the 'elseif' keyword  
−
#* Branching can be based on satisfaction of combination of multiple conditions as well   
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#*example for select
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# Iteration  
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#''' Iteration'''
−
#* Explain syntax of 'for' statement- tell that the variable iterates over a list/vector/matrix  
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#* Explain syntax of 'for' statement- tell that the variable iterates over a list/vector/matrix (or an expression that evaluates to any of these).
−
#* Break condition.
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#* Give example: for i = 1:5, disp (i), end
−
#* continue condition.  
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#* Then explain break condition. Use example: for i = 1:10, disp(i), if (i==5), break, end, end
−
#* while condition.  
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#* Then explain continue condition. Use example: for i = 1:10, if (i<=5) then continue, else disp(i), end, end
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#* break, continue condition with example in while loop.
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#* Explain while condition.
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# Plotting 2D graphs  
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#* Give example: i = 0; while(i <=5), i = i + 1; d
 +
# '''Scripts and Functions'''
 +
#*Introduction to the file formats in Scilab.  
 +
#*SCRIPT files.
 +
#*sce versus .sci
 +
#*Inline functions.
 +
# ''' Plotting 2D graphs'''
 
#* About linspace: linspace is a linearly spaced vector.
 
#* About linspace: linspace is a linearly spaced vector.
 
#* Plot a simple graph: x=linspace(12,34,10), y=linspace(-.1,2,10), plot(x,y)
 
#* Plot a simple graph: x=linspace(12,34,10), y=linspace(-.1,2,10), plot(x,y)
 
#* plot2d  
 
#* plot2d  
−
#* Using clf() clear the graphic window.  
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#* Use of "clf()".  
 
#* Configure the title for the plot
 
#* Configure the title for the plot
 
#* Configure a legend  
 
#* Configure a legend  
 
#* Divide a graphic window into a matrix of sub-windows using subplot(mnp)
 
#* Divide a graphic window into a matrix of sub-windows using subplot(mnp)
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# Scripts and Functions
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#''' Xcos introduction'''
−
#* Explain that one often repeats a set of commands- in which case it is helpful to save that set of commands for future or repeated use. The commands can be saved as scripts or functions.  
+
#*What is XCOS.
−
#* Change directory to the desktop. Open the scilab editor and type the commands (each on a new line)
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#*What is palette.
−
#* Save the above file to the desktop. Then open the same file using a regular text editor such as notepad to show that it is indeed a text file. Now load the file into scilab using the scilab editor's execute menu option.  
+
#*To collect the blocks from the palette and connect them to construct the block diagram.
−
#* Change the value of a to 5 in the editor, save and close it. Now execute the script directly from the scilab interpreter using exec.  
+
#*Set the parameters of different blocks.
−
#* Functions: Show the syntax of functions, explain the function keyword, input arguments and the structure of output arguments when there is more than one argument.  
+
#*To setup the simulation parameters.
−
#* Show the following function in the editor: .  
+
#*Simulate the constructed block diagram.
−
#* Inline functions.
+
−
#* .sce versus .sci: These are just conventions.
+
−
# Input and Output
+
−
#* Console input and output.
+
−
#* Reading and writing in files: Do a = rand(20, 1)
+
−
#** Text files:
+
−
#*** Output- write()
+
−
#*** Input- read()
+
−
#** Binary files
+
−
#*** Output- save()
+
−
#*** Input- load()
+
  
 
==Advanced Level Scilab==
 
==Advanced Level Scilab==
−
# File Handling- Scilab File handling
+
# '''File Handling- Scilab File handling'''
 
#* Writing to a file using write()
 
#* Writing to a file using write()
 
#* Reading from a file using read()
 
#* Reading from a file using read()
 
#* Opening an existing file using mopen()
 
#* Opening an existing file using mopen()
 
#* Closing an already opened file using mclose()
 
#* Closing an already opened file using mclose()
−
# File Handling- User Defined Input and Output in Scilab
+
# '''File Handling- User Defined Input and Output in Scilab'''
 
#* Input Function
 
#* Input Function
 
#* mprintf()
 
#* mprintf()
 
#* save() and load()
 
#* save() and load()
 
#* Used to quit scilab midway through calculation and continue at later stage
 
#* Used to quit scilab midway through calculation and continue at later stage
−
# Numerical methods- Integration
+
# '''Numerical methods- Integration'''
−
# Numerical methods- Solving Non- linear Equations
+
#* Develop Scilab code for different Composite Numerical Integration algorithms
−
# Numerical methods- Gauss Elimination Method and Gauss Jordan Method
+
#* Divide the integral into equal intervals
−
# Numerical methods-  Iterative Methods
+
#* Apply the algorithm to each interval
−
# Numerical methods-  Interpolation
+
#* Calculate the composite value of the integral
−
# Numerical methods- ODE- Euler methods
+
# '''Numerical methods- Solving Non- linear Equations'''
−
# Numerical methods- ODE- Applications
+
#*Learn how to solve nonlinear equations using numerical methods
−
# Optimization Using Karmarkar Functions
+
#*Learn Bisection method
 +
#*Learn Secant method
 +
#*Learn how to develop Scilab code for solving nonlinear equations
 +
# '''Numerical methods- Gaussian Methods'''
 +
#* Explain Gauss Elimination method algorithm
 +
#* Explain code for Gauss Elimination method and solve an example using this code
 +
#* Explain Gauss Jordan method algorithm
 +
#* Explain code for Gauss Jordan method and solve an example using this code
 +
# '''Numerical methods-  Iterative Methods'''
 +
#*Solve system of linear equations using iterative methods
 +
#*Use Jacobi and Gauss Seidel iterative methods
 +
#*Learn how to iterate until we converge at the solution
 +
#*Learn how Gauss Seidel method is faster than Jacobi method
 +
#*Develop Scilab code for these two methods to solve linear equations
 +
#'''Numerical methods-  Interpolation'''
 +
#*Develop Scilab code for different Numerical Interpolation algorithms
 +
#*Calculate new value of function from given data points
 +
# '''Numerical methods- ODE- Euler methods'''
 +
#*Solve ODEs using Euler and Modified Euler methods
 +
#*Develop Scilab code to solve ODEs
 +
# '''Numerical methods- ODE- Applications'''
 +
#*Use Scilab ode function
 +
#*Solve typical examples of ODEs
 +
#*Plot the solution
 +
#*examples Motion of simple pendulum Van der Pol equation
 +
#*Lorenz system
 +
# ''' Optimization Using Karmarkar Functions'''
 
#* About Optimization
 
#* About Optimization
 
#* Use of Scilab function Karmarkar in Optimization
 
#* Use of Scilab function Karmarkar in Optimization
−
# Optimization of Non-linear Functions
+
#'''Digital Signal Processing'''
−
# Digital Signal Processing
+
#* Plotting continuous and discrete sine wave.
−
# Filter Design-  Windowing Techniques
+
#* Plotting step function.
−
# Filter Design- Window Based FIR Filter
+
#* Plotting ramp function.
−
# Filter Design-  IIR Digital Filter
+
# '''Control systems'''
−
# Filter Design- Applying Digital Filter
+
#*Define a continuous time system: second and higher order
−
# Control systems
+
#*Response plot for step input
−
# Discrete systems
+
#*Response plot for sine input
−
#  Calling User Defined Functions in XCOS
+
#*Bode plot
 +
#*Study numer and denom Scilab functions
 +
#*Plot poles and zeros of function
 +
# '''Discrete systems'''
 +
#*Define discrete time system variable z
 +
#*Define first order discrete time system
 +
#*Explain ones, flts, dscr, ss2tf functions
 +
#  '''Calling User Defined Functions in XCOS'''
 
#* Write a squaring function
 
#* Write a squaring function
 
#* Use of scifunc block in XCOS
 
#* Use of scifunc block in XCOS
 
#* Use of MUX block
 
#* Use of MUX block
 
#* Call functions having multiple inputs and output
 
#* Call functions having multiple inputs and output
−
tutorials on Control Systems
+
#Simulating a PID controller using XCOS
−
 
+
#* Modifying firstorder.xcos file to implement a PID controller
−
Representing control systems and their properties
+
#* Closing the loop
−
# [[First order systems]] (1)
+
#* Setting PID gains and observing its response
−
#* Defining a system
+
#* Plotting the required data
−
#* Simulating the system
+
#Developing Scilab Toolbox for calling external C libraries
−
#** Step test
+
#* Compiling an external C library
−
#** Sine test (at two different frequencies)
+
#* Generating shared library
−
#* Root locus
+
#* Copying the shared library to Scilab Toolbox
−
#* Bode plot
+
#* Interfacing the shared library with Scilab
−
#* Nyquist plot (1)
+
#* Understanding the important code sections for interfacing
−
# [[Second order systems]] (2)
+
#* Building a Scilab Toolbox using this library
−
#* Underdamped system
+
#* Loading the toolbox
−
#** Defining the system
+
#* Executing an example in help
−
#** Roots of denominator
+
#* Verification of results
−
#* Step test
+
#* Understanding how to write Help for Toolbox functions
−
# [[Other system representations]] (3)
+
# Developing Scilab Toolbox for calling Python and its functions
−
#* Discrete time systems (3)
+
#* About Scithon toolbox
−
#** Defining a system
+
#* About header folder
−
#** Simulating the system (step test)
+
#* Interfacing between Scilab and Python
−
#** Bode plot
+
#* Files used for starting the python instance and overloaded virtual functions
−
#** Root locus
+
#* Links to understand the code inside the PyVar.CPP file
−
#* Discretizing continuous time systems (3)
+
#* About Builder script of scithon toolbox
−
# [[State space representation]] (4)
+
#* About Gateway functions
−
#* Defining the system and initial state
+
#* How to build a toolbox
−
#* Simulating the system
+
#* How to load a toolbox
−
#* Plotting output state and internal state
+
#* Demo on how to execute the python functions in Scilab
−
#* Root locus
+
−
#* Conversion to transfer function
+
−
#** Compare roots of denominator of answer with eigenvalues of A matrix.
+
−
# [[Multiple subsystems]] (5)
+
−
<!--
+
−
System modeling and control:-->
+
−
# [[Modeling a system]] (6)
+
−
#*       Obtain ODE representation of a system
+
−
#*        Laplace transform representation of the system
+
−
#*        Comparison with a second order model (obtain natural freq. and damping factor)
+
−
#    [[Analyzing the system]] (7)
+
−
#*       Open loop step response
+
−
#*        Step response with unity feedback
+
−
#*        Steady state error: open loop system as well as unity feedback system
+
−
#*        Root locus and finding the gain from a point on the root locus.  
+
−
#   [[Controlling the system]] (8)
+
−
#*       Proportional control
+
−
#*           Deciding the parameters to be achieved (overshoot/rise time, etc)
+
−
#*           Determining corresponding system parameters (natural freq., damping factor)
+
−
#*           Obtaining location of corresponding point on root locus and gain there
+
−
#*            Building and simulating the proportional controller
+
−
#  [[Other Controllers]]  (9)
+
−
#* PI Control
+
−
#* PD Control
+
−
#* PID Control
+
−
#* Comparing all controllers
+
−
 
+
−
==Robotics==
+
−
# rtss Toolbox
+
−
==Signal Processing==
+
−
#Signal Processing Basics
+
−
#Audio processing
+
−
#Image Processing
+
−
#Fourier Transforms
+
−
=Other Topics=
+
−
 
+
−
==Ordinary Differential Equations==
+
−
[http://spoken-tutorial.org/wiki/index.php/Scilab/Scripts-1 (Spoken Tutorial-1 Scripts)]<ol>
+
−
 
+
−
<li>[[/ Introduction to ODEs /Introduction to ODEs/|Introduction to ODEs]]
+
−
*<p>Use <math>\frac{dx}{dt} = sin(2t)</math> as the first order example and solve using ode.</p>
+
−
**System:
+
−
  <source lang="scilab" line start="1">
+
−
  function dx = f(t, x)
+
−
        dx = sin(2∗t) ;
+
−
  endfunction
+
−
</source>
+
−
 
+
−
*2nd order differntial equation, Lotka Volterra equation example,
+
−
*Using champ to show arrows.
+
−
*With input (nonlinear input/state system). van der Pol oscillator?
+
−
 
+
−
*3rd order, show example and plot.
+
−
 
+
−
*One example for discrete time system (difference equation) (of order 2)
+
−
 
+
−
*Show points evolving in plane.
+
−
*Linear system: syslin
+
−
 
+
−
*Solution:
+
−
  <source lang="scilab" line start="1">
+
−
  t0 = 0
+
−
  x0 = −0.5
+
−
  t = 0:0.1:5;
+
−
  x = ode( x0 , t0 , t , f ) ;
+
−
  plot2d(t , x)
+
−
</source>
+
−
</li>
+
−
<li> [[/ Using ODEOPTIONSs /Using ODEOPTIONS/|Using ODEOPTIONS]]</li>
+
−
<li> [[Implicit Differential Equations/Implicit Differential Equations/|Implicit Differential Equations]]</li>
+
−
</ol>
+
−
 
+
−
 
+
−
===Boundary Value Problems===
+
−
===Difference Equations===
+
−
===Differential Algebraic Equations===
+
−
===Partial Differential Equations===
+
−
 
+
−
==Linear Algebra==
+
−
 
+
−
Revise linsolve.
+
−
 
+
−
spec, det, generalized eigenvalue (spec)
+
−
 
+
−
inv and pinv (pseudo inverse), svd, companion-form
+
−
 
+
−
trace, sum of eigenvalues almost same as trace (similarly determinant and product of eigenvalues)
+
−
 
+
−
==Optimization==
+
−
==Probability and Statistics==
+
−
==Scilab Toolboxes==
+
−
<nowiki>Symbolic toolbox</nowiki> [http://spoken-tutorial.org/wiki/index.php/Scilab_Symbolic_Toolbox Scripts]
+
−
<nowiki>Scilab Wavelet toolbox</nowiki> [http://spoken-tutorial.org/wiki/index.php/Scilab_wavelet_toolbox Scripts]
+
−
 
+
−
==Special Functions==
+
−
#Bessel functions
+
−
#[[Beta function]]
+
−
#*Definition
+
−
#*beta(m,n)=beta(n,m)
+
−
#*beta(m,n)=gamma(m)*gamma(n)/gamma(m+n)
+
−
#[[Gamma function]]
+
−
#*Definition
+
−
#*gamma(1), gamma(0)
+
−
#*gamma(n+1)=n!
+
−
#*gamma(11/2), gamma(1/2)
+
−
#Error function
+
−
#Legendre functions
+
−
 
+
−
==Least squares fit, splines==
+
−
==Polynomial interpolation==
+
−
 
+
−
Close relation between interpolation and van der Monde matrix
+
−
 
+
−
Subset of columns of van der Monde matrix will correspond to lower degree fit.
+
−
 
+
−
Solvability of over-determined equations perhaps not possible.
+
−
 
+
−
Pseude inverse corresponds to "least squares fit" of specified degree.
+
−
 
+
−
==Data Handling==
+
−
# Databases
+
−
# XMLLab
+
−
==Web Interface for Scilab (W3 Scilab)==
+

Latest revision as of 15:41, 21 October 2020

Scilab (http://scilab.org, http://scilab.in) is an open source scientific software package for numerical computations. It has an extremely reliable and efficiently coded numerical library. It is also a high productivity tool: Through its interpreted language, one can quickly develop the code required to solve problems. Typically, if it takes ten lines of C code for some calculation, Scilab would require only one for the same purpose.

Scilab runs on all popular operating systems. Since 1994, it has been distributed freely along with the source code via the Internet. It is useful for students at school, college and roupas da moda research level. It is also useful for researchers and professionals.

IIT Bombay is leading the effort to popularise Scilab in India. This is part of the Free and Open source Software for Science and Engineering Education (FOSSEE) project, supported by the National Mission on Education through ICT of MHRD.

IIT Bombay is using Spoken Tutorials (http://spoken-tutorial.org) to create learning material for FOSS. This is the main page for the organisation of the scripts required for Scilab spoken tutorials. We invite the Scilab user community to participate in this activity.

Learners: All Science and Engineering Students.


The Spoken Tutorial Effort for Scilab is being contributed by Shalini Shrivastava, Rupak Rokade, Anuradha Amruthkar, Manas Ranjan Das, Mukul Kulkarni, Shamika Mohanan, Lavitha Pereira from IIT Bombay.

Note: Each numbered topic corresponds to a single spoken tutorial. Each bulleted point corresponds to a command or topic that must be covered organic nuts in the given spoken tutorial.


General Information

This topic will include all functionality in Scilab that iphone photography is not domain specific- functionality that is required across several domains.

Basic Level Introduction to Scilab

This level will include a set of tutorials that are required to be known in order to qualify as "Scilab Literate". The tutorials here will teach programming weight loss pills fundamentals and the most commonly used Scilab functionality- Matrix operations and Plotting.

  1. Installing
    • Show where to download from and how to decide which version to choose
    • Windows installation
    • Linux installation (using package manager- show only Debian/Ubuntu as example (sudo apt-get install scilab) as well as generic binary)
    • Mac
    • Compilation from source can come as a part of a more advanced tutorial
  2. Getting Started
    • Expressions: Show mathematical expressions with numbers
    • Variables
    • Diary command
    • Define symbolic constants.
    • Basic functions
    • suppressing output(;)
    • help,clc
  3. Vector Operations
    • Define vector
    • Calculate length of a vector.
    • Perform mathematical operations on Vectors such as addition,subtraction and multiplication.
    • Define a matrix.
    • Calculate size of a matrix.
    • Perform mathematical operations on Matrices such as addition, subtraction and multiplication.
  4. Matrix Operations
    • Access the elements of Matrix
    • Determine the determinant, inverse and eigen values of a matrix.
    • Define special matrices.
    • Perform elementary row operations.
    • Solve the system of linear equations.
  5. Conditional Branching
    • 'if' and 'then' with the example
    • use of the 'else' keyword
    • use of the 'elseif' keyword
    • example for select
  6. Iteration
    • Explain syntax of 'for' statement- tell that the variable iterates over a list/vector/matrix (or an expression that evaluates to any of these).
    • Give example: for i = 1:5, disp (i), end
    • Then explain break condition. Use example: for i = 1:10, disp(i), if (i==5), break, end, end
    • Then explain continue condition. Use example: for i = 1:10, if (i<=5) then continue, else disp(i), end, end
    • Explain while condition.
    • Give example: i = 0; while(i <=5), i = i + 1; d
  7. Scripts and Functions
    • Introduction to the file formats in Scilab.
    • SCRIPT files.
    • sce versus .sci
    • Inline functions.
  8. Plotting 2D graphs
    • About linspace: linspace is a linearly spaced vector.
    • Plot a simple graph: x=linspace(12,34,10), y=linspace(-.1,2,10), plot(x,y)
    • plot2d
    • Use of "clf()".
    • Configure the title for the plot
    • Configure a legend
    • Divide a graphic window into a matrix of sub-windows using subplot(mnp)
  9. Xcos introduction
    • What is XCOS.
    • What is palette.
    • To collect the blocks from the palette and connect them to construct the block diagram.
    • Set the parameters of different blocks.
    • To setup the simulation parameters.
    • Simulate the constructed block diagram.

Advanced Level Scilab

  1. File Handling- Scilab File handling
    • Writing to a file using write()
    • Reading from a file using read()
    • Opening an existing file using mopen()
    • Closing an already opened file using mclose()
  2. File Handling- User Defined Input and Output in Scilab
    • Input Function
    • mprintf()
    • save() and load()
    • Used to quit scilab midway through calculation and continue at later stage
  3. Numerical methods- Integration
    • Develop Scilab code for different Composite Numerical Integration algorithms
    • Divide the integral into equal intervals
    • Apply the algorithm to each interval
    • Calculate the composite value of the integral
  4. Numerical methods- Solving Non- linear Equations
    • Learn how to solve nonlinear equations using numerical methods
    • Learn Bisection method
    • Learn Secant method
    • Learn how to develop Scilab code for solving nonlinear equations
  5. Numerical methods- Gaussian Methods
    • Explain Gauss Elimination method algorithm
    • Explain code for Gauss Elimination method and solve an example using this code
    • Explain Gauss Jordan method algorithm
    • Explain code for Gauss Jordan method and solve an example using this code
  6. Numerical methods- Iterative Methods
    • Solve system of linear equations using iterative methods
    • Use Jacobi and Gauss Seidel iterative methods
    • Learn how to iterate until we converge at the solution
    • Learn how Gauss Seidel method is faster than Jacobi method
    • Develop Scilab code for these two methods to solve linear equations
  7. Numerical methods- Interpolation
    • Develop Scilab code for different Numerical Interpolation algorithms
    • Calculate new value of function from given data points
  8. Numerical methods- ODE- Euler methods
    • Solve ODEs using Euler and Modified Euler methods
    • Develop Scilab code to solve ODEs
  9. Numerical methods- ODE- Applications
    • Use Scilab ode function
    • Solve typical examples of ODEs
    • Plot the solution
    • examples Motion of simple pendulum Van der Pol equation
    • Lorenz system
  10. Optimization Using Karmarkar Functions
    • About Optimization
    • Use of Scilab function Karmarkar in Optimization
  11. Digital Signal Processing
    • Plotting continuous and discrete sine wave.
    • Plotting step function.
    • Plotting ramp function.
  12. Control systems
    • Define a continuous time system: second and higher order
    • Response plot for step input
    • Response plot for sine input
    • Bode plot
    • Study numer and denom Scilab functions
    • Plot poles and zeros of function
  13. Discrete systems
    • Define discrete time system variable z
    • Define first order discrete time system
    • Explain ones, flts, dscr, ss2tf functions
  14. Calling User Defined Functions in XCOS
    • Write a squaring function
    • Use of scifunc block in XCOS
    • Use of MUX block
    • Call functions having multiple inputs and output
  15. Simulating a PID controller using XCOS
    • Modifying firstorder.xcos file to implement a PID controller
    • Closing the loop
    • Setting PID gains and observing its response
    • Plotting the required data
  16. Developing Scilab Toolbox for calling external C libraries
    • Compiling an external C library
    • Generating shared library
    • Copying the shared library to Scilab Toolbox
    • Interfacing the shared library with Scilab
    • Understanding the important code sections for interfacing
    • Building a Scilab Toolbox using this library
    • Loading the toolbox
    • Executing an example in help
    • Verification of results
    • Understanding how to write Help for Toolbox functions
  17. Developing Scilab Toolbox for calling Python and its functions
    • About Scithon toolbox
    • About header folder
    • Interfacing between Scilab and Python
    • Files used for starting the python instance and overloaded virtual functions
    • Links to understand the code inside the PyVar.CPP file
    • About Builder script of scithon toolbox
    • About Gateway functions
    • How to build a toolbox
    • How to load a toolbox
    • Demo on how to execute the python functions in Scilab

Contributors and Content Editors

Lavitha Pereira, Minal, Nancyvarkey, PoojaMoolya, Pratik kamble

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