Integration of Scilab

Integration of Scilab with C and Python

Reference Link: Spoken Tutorial - Scilab Integration

1. Integration of Scilab with C

You can interface Scilab with C by using the Scilab API (also known as the Scilab gateway). The API allows a C program to call Scilab functions.

Steps to integrate Scilab with C:

1. Install Scilab: Ensure you have Scilab installed on your system.
   
   

2. Scilab Gateway API: You need the Scilab gateway, which is available as a shared library (libscilab).
   
   

3. Writing C Code:
   
   

   • First, include Scilab headers.
     
     

   • Then use functions like scilabStart(), scilabEvalString(), etc., to interact with Scilab.
     
     

Example of a simple C program that calls a Scilab function:

#include <stdio.h>

#include "scilab_gateway.h"

int main() {

    // Start Scilab engine

    if (scilabStart()) {

        printf("Scilab started successfully.\n");

        // Execute Scilab code

        scilabEvalString("disp('Hello from Scilab!');");

        // Terminate Scilab engine

        scilabTerminate();

    } else {

        printf("Scilab start failed.\n");

    }

    return 0;

}

4. Compile and Link the C Code:
   
   

   • Link the Scilab libraries during compilation. This is typically done using gcc or another C compiler, ensuring the Scilab library paths are included.
     
     

gcc -o my_program my_program.c -lscilab

5. 
   

6. Run the Program: Once compiled, run the program, and it should invoke Scilab's function.
   
   

2. Integration of Scilab with Python

You can use the Python Scilab interface, called pyScilab, or use the subprocess module to call Scilab scripts from Python.

Method 1: Using PyScilab

Install PyScilab: You can install it using the following command:

pip install pyScilab

Call Scilab from Python: Here’s an example where Python calls a Scilab function using pyScilab:

from pyScilab import Scilab

# Initialize Scilab

scilab = Scilab()

# Run a simple command in Scilab

scilab.eval('disp("Hello from Scilab!")')

# Optionally, you can retrieve data from Scilab

scilab.eval('x = 5')

result = scilab.get('x')

print(f'Result from Scilab: {result}')

Method 2: Using subprocess to execute Scilab scripts

This method involves using Python's subprocess to run Scilab scripts as external processes.

Create a Scilab Script: Save a Scilab script, for example my_script.sci, that contains your desired Scilab code.

// my_script.sci

disp("Hello from Scilab!");

Call Scilab from Python:

import subprocess

# Call the Scilab script using subprocess

subprocess.run(['scilab', '-headless', '-f', 'my_script.sci'])

This will execute the Scilab script as an external process.

3. Using Scilab as an Embedded Library

If you need to use Scilab directly as an embedded library, you can link the Scilab libraries to your program (e.g., C, C++, or Java). Scilab provides various interfaces to embed Scilab as a library, allowing you to call Scilab functions directly.

• Scilab Embedded Library: You can download the Scilab embedded library from the Scilab website and follow their documentation for integration into your C++ or Java projects.
  
  

Conclusion

Depending on your preferred programming language, you can integrate Scilab into your project using:

• The API in C for direct interaction.
  
  

• Interfacing with Python via pyScilab or subprocess.
  
  

• Embedding Scilab directly into larger applications.
  
  

Each approach has its own use cases, so select the one that best suits your needs!