Basics of Python-MATLAB Integration - 12.2 | 12. Integrating SciLab/MATLAB with Python for Scientific Computing | IT Workshop (Sci Lab/MATLAB)
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12.2 - Basics of Python-MATLAB Integration

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Interactive Audio Lesson

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Introduction to MATLAB Engine API

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0:00
Teacher
Teacher

Today, we'll explore the MATLAB Engine API for Python. This API allows us to start MATLAB from Python and use MATLAB's powerful computational engines directly in our Python environment.

Student 1
Student 1

How do we start using the MATLAB Engine API?

Teacher
Teacher

Great question! First, we need to install it. We navigate to the 'matlabroot/extern/engines/python' folder in our command line and execute `python setup.py install`.

Student 2
Student 2

What does 'matlabroot' refer to?

Teacher
Teacher

Good inquiry! 'matlabroot' is the directory where MATLAB is installed, which includes various toolboxes and APIs. Now, let’s see how we can start a MATLAB session from Python.

Student 3
Student 3

What would a simple command look like for starting MATLAB?

Teacher
Teacher

You would use `import matlab.engine` and then `eng = matlab.engine.start_matlab()`. Remember this as a key format: `import` followed by `start_matlab()`.

Student 4
Student 4

Got it! Can you summarize this session?

Teacher
Teacher

Sure! We discussed the MATLAB Engine API, installation steps, and basic commands to start MATLAB from Python. Always remember to locate MATLAB's installation directory for proper setup.

Calling MATLAB Functions from Python

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Teacher

Now let’s dive into how we can call MATLAB functions from Python and the importance of data type conversion.

Student 1
Student 1

What are the main data types we need to take care of?

Teacher
Teacher

MATLAB supports several data types like basic numeric types, arrays such as `matlab.double`, and strings. We must convert our Python data into these formats.

Student 3
Student 3

Can you show us a code example?

Teacher
Teacher

Yes! Let’s create a 2D array with `a = matlab.double([[1, 2, 3], [4, 5, 6]])`, then to sum it in MATLAB, you would call `b = eng.sum(a, 1)`. Can you repeat that structure?

Student 4
Student 4

Sure! It’s `matlab.double` for arrays and then use `eng.function_name()`.

Teacher
Teacher

Exactly! Always remember, converting data types is crucial to avoid errors when calling functions.

Executing MATLAB Scripts in Python

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Teacher
Teacher

Lastly, let’s discuss how we can execute MATLAB scripts directly from Python.

Student 1
Student 1

What about passing parameters to MATLAB scripts?

Teacher
Teacher

Excellent point! You can pass parameters to the MATLAB workspace using commands like `eng.workspace['x'] = 42`. This assigns the value 42 to a variable `x` in MATLAB.

Student 2
Student 2

What's the next step after assigning a variable?

Teacher
Teacher

You can then execute your script with `eng.run('myscript.m', nargout=0)`. `nargout=0` means you’re not expecting any output back. Can anyone tell me why this is important?

Student 3
Student 3

It reduces memory usage if we aren't returning values.

Teacher
Teacher

Correct! Finally, you can retrieve values from MATLAB’s workspace using something like `result = eng.workspace['y']`.

Introduction & Overview

Read a summary of the section's main ideas. Choose from Basic, Medium, or Detailed.

Quick Overview

This section outlines the basics of integrating Python with MATLAB, including the use of the MATLAB Engine API for Python and fundamental methods for calling MATLAB functions and executing scripts.

Standard

The integration of Python with MATLAB is facilitated through the MATLAB Engine API for Python, enabling users to interact seamlessly between the two languages. This section discusses installation, basic usage, and methods for data type conversion, exemplified by calling MATLAB functions and executing MATLAB scripts directly from Python.

Detailed

Basics of Python-MATLAB Integration

This section focuses on the foundational techniques for integrating Python with MATLAB, leveraging the MATLAB Engine API. It specifies how to set up the integration by installing the engine API and showcases its capabilities in bridging Python scripts with MATLAB functionalities.

Key Points Covered:

  1. MATLAB Engine API for Python: MATLAB offers an official API allowing Python scripts to initiate and interact with a MATLAB session. Installation involves navigating to the appropriate directory and running python setup.py install.
  2. Basic Usage in Python: Users can import matlab.engine, start a MATLAB session, and directly call MATLAB functions, as demonstrated by calculating the square root of 16 in MATLAB through Python.
  3. Calling MATLAB Functions: Data types between Python and MATLAB must be convertible for efficient communication. The MATLAB engine supports various data types including basic numeric types, arrays (matlab.double, matlab.int32), and strings.
  4. MATLAB Example: The section illustrates a simple example where a 2D array is created in Python and summed in MATLAB to demonstrate data interaction.
  5. Executing MATLAB Scripts: MATLAB .m scripts can be executed within Python, allowing dynamic parameter passing and data retrieval using the MATLAB workspace.

Overall, this section serves as a vital introduction to employing MATLAB's numerical capabilities within a Python environment, enhancing scientific computing workflows.

Audio Book

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MATLAB Engine API for Python

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• MATLAB provides an official Python API that allows Python scripts to start and interact with a MATLAB session.

• Installation:

cd "matlabroot/extern/engines/python"
python setup.py install

• Basic usage in Python:

import matlab.engine
eng = matlab.engine.start_matlab()
result = eng.sqrt(16.0)
print(result)

Detailed Explanation

The MATLAB Engine API allows Python developers to call MATLAB functions from their Python scripts. It enables seamless integration between the two programming environments. To use this API, you first need to install it using the command line. The commands given install the required MATLAB engine for Python. Once installed, you can import the matlab.engine module and start a MATLAB session using start_matlab(). Within this session, you can call MATLAB functions directly. For example, using eng.sqrt(16.0) calculates the square root of 16 and returns the result.

Examples & Analogies

Imagine you are a chef who has both a kitchen and a bakery. The kitchen represents Python, where you have flexibility and ease of use. The bakery represents MATLAB, where you have specialized tools for baking. By using a special bridge (the MATLAB Engine API), you can easily send ingredients back and forth between the two spaces to create delicious dishes (perform mathematical computations) without having to change where you work.

Calling MATLAB Functions from Python

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• Data types must be converted between Python and MATLAB.

• MATLAB engine supports:
- Basic numeric types
- Arrays (matlab.double, matlab.int32, etc.)
- Strings and cell arrays

• Example:

a = matlab.double([[1, 2, 3], [4, 5, 6]])
b = eng.sum(a, 1)

Detailed Explanation

To call MATLAB functions from Python, you need to ensure that data types are compatible. MATLAB and Python have different internal representations for data types. The MATLAB Engine supports basic numeric types, arrays, and strings, among others. When you want to send data from Python to MATLAB, you convert it into a format that MATLAB understands, such as matlab.double for numerical arrays. The example shows how to create a MATLAB array in Python and then call the sum function to get the sum along the specified dimension.

Examples & Analogies

Think of it like learning a new language. If you want to send a message (data) to a friend who speaks a different language (MATLAB), you have to translate your message into their language (convert data types). In this case, Python is like you when you use your native language, and MATLAB is your friend who understands only certain terms (data types). Thus, you need to communicate in a way that they understand.

Definitions & Key Concepts

Learn essential terms and foundational ideas that form the basis of the topic.

Key Concepts

  • Integration: The process of allowing different programming languages to work together, notably Python and MATLAB in this context.

  • Installation: The steps needed to set up the MATLAB Engine API for use within Python.

  • Function Calling: Techniques for invoking MATLAB functions and handling data types.

  • Script Execution: Running MATLAB scripts from Python and managing workspace variables.

Examples & Real-Life Applications

See how the concepts apply in real-world scenarios to understand their practical implications.

Examples

  • Calling the square root function in MATLAB via Python: result = eng.sqrt(16.0).

  • Creating a MATLAB array in Python: a = matlab.double([[1, 2], [3, 4]]) and summing the rows: b = eng.sum(a, 1).

  • Running a MATLAB script with numeric variables set through Python workspace.

Memory Aids

Use mnemonics, acronyms, or visual cues to help remember key information more easily.

🎵 Rhymes Time

  • To run MATLAB from Python, it’s quite sublime, just import and start, it won't waste your time!

📖 Fascinating Stories

  • Imagine a scientist who uses Python for data but has MATLAB for heavy calculations. They get the best of both worlds by using the MATLAB Engine API – bridging their two favorite tools seamlessly!

🧠 Other Memory Gems

  • To remember the process of calling functions: 'FADS' - Functions, Arrays, Data types, Scripts.

🎯 Super Acronyms

MAPI - MATLAB API for Python Integration.

Flash Cards

Review key concepts with flashcards.

Glossary of Terms

Review the Definitions for terms.

  • Term: MATLAB Engine API

    Definition:

    An interface that allows Python programs to call MATLAB functions and execute MATLAB scripts.

  • Term: Data Type Conversion

    Definition:

    The process of converting data types from Python formats to MATLAB formats and vice versa for compatibility.

  • Term: Workspace

    Definition:

    The environment in which variables are stored and can be manipulated in MATLAB.