• Trity Course Scilab IoT

    Scilab for the Internet of Things

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  • Trity Course RPi IoT

    Raspberry Pi for the Internet of Things (with Pi-3)

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  • Trity Course Scilab AI

    Artificial Intelligence with Scilab

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  • Trity Course Scilab NCV

    Numerical Computation and Visualization with Scilab

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  • Trity Course Scilab IP

    Scilab for Image Processing and Computer Vision

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  • Trity Course Scilab BDA

    Big Data Training Series : Practical Guide to Big Data Analytics with Pig Latin, Hive and Scilab

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  • Trity Course Scilab DM

    Scilab for Data Mining

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  • Python Deep Learning

    Python for Machine and Deep Learning

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Scilab Courses

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Scilab is an open source, cross-platform numerical computational package and a high-level, numerically oriented programming language. It can be used for signal and image processing, statistical analysis, Internet of Things, data mining, etc. In Trity Technologies we have developed more than 20 courses based on Scilab since last few years.

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Raspberry Pi Courses

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The Raspberry Pi is a series of credit card–sized single-board computers developed in the United Kingdom by the Raspberry Pi Foundation with the intent to promote the teaching of basic computer science in schools and developing countries. Our very first Raspberry Pi Training is the aplication in IoT, and we are extending the training into other fields from time to time. 

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E4Coder - Automatic Code Generation

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E4Coder is a set of tools that can be used to simulate control algorithms and to generate code for embedded microcontrollers running with or without a realtime operating system. Our course focus on using the block diagram for algorithms development and the codes would be automatically generated and downloaded into the embedded boards such as Arduino Uno. A mobile robot application would be used for the training for practical hands-on. 

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Java Interaction Mechanism in Scilab


Expanding the Power of Scilab with JAVA Libraries

Scilab could interface with other languages and this makes it more powerful and effective.

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Scilab provides an interface to directly interact with Java external objects from Scilab, and makes powerful Scilab become even more complete!”

Course Synopsisscilabinternal
Scilab provides interfacing mechanisms to other languages such as C/C++, Java, R, Python, etc.This makes the Scilab could perform beyond it boundary and allows the programmers to take advantages from the strengths from both programming languages. For example, there are tonnes of open source Java libraries available in the internet, which could be called from Scilab, and Scilab libraries for data import and analysis definitely will help the programmers or researchers to get their work done much faster with the advantages of these 2 programming languages.
This course is conducted in a workshop-like manner, with a balance mix of theory and hands-on coding and simulation in Scilab. Extensive exercises are provided throughout the course to cover every angle of algorithm design and implementation using Scilab.


Course Objectivesjavacodes

This two-day course provides a practical introduction on how to complete the Java codes and call it from Scilab, as well as how to call Java classes to enhance the Scilab capabilities in data processing and analysis.

Who Must Attend

Scilab programmers who wish to use Java libraries, and Java programmers who wish to explore how Scilab could help in enhancing the experience of Java programming.


A basic knowledge of programming language.

What you will learn

Writing simple Java program and call it from Scilab, and use the available powerful libraries from internet and link it to Scilab.



Course Outline


Introduction to Java

  • what is java? (Object oriented programming)
  • who developed java? (james gosling)
  • why learn java? why is it popular? (large library, platform independent etc )

Integration with Scilab

  • Background/history
  • Started as user contributed module, JIMS
  • Installed via ATOMS
  • Officially added to Scilab from version 5.5 onwards with some adjustments

Installation of Java

  • Java Development kit
  • setting system variables
  • Some simple java tests on the command prompt

Basics of Java (using Scilab)

How java works

  • An object is created using a java class(instances)
  • The functions (methods) and variables (fields) of the object are then used for the operations
  • The output is returned to the user (numbers, a string statement, graphs etc etc)

Compiling a simple Java File

  • Compiling and importing the file into Scilab
  • Calling the Java Class into Scilab

Importing existing java classes

  • Need to set javaclasspath first before importing

Using Java Class Fields & Methods

  • jgetfields – to get the public fields
  • jgetmethods – to get public methods
  • private fields and methods cannot be accessed

Sending inputs to Java

  • Sending and retrieving strings, doubles, arrays to Java objects

Data Import

  • Importing data using java
  • Importing data using Scilab (mgetl, read)

Case Study 1: Integrating with Open Source Java Chart Library - JFreeChart

  • Understanding the JFreeChart Library
  • Running the JFreeChart examples
  • Replicating the examples inside Scilab
  • Using Scilab programming in the example
  • Utilising JFreeChart's special charts in Scilab

Case Study 2: : Integrating with Open Source Java Text to Speech Library - freetts

  • Understanding the freetts library
  • Running the freetts examples
  • Convert the example to Scilab programming
  • Sound from Scilab

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