Using MATLAB with Python

Summary

This video tutorial explores the integration between MATLAB and Python, showcasing how to call Python functions from MATLAB and vice versa. It uses a weather data example from openweathermap.org, demonstrating the use of Python's 'weather.pi' module within MATLAB. The video guides through fetching and parsing weather data, converting Python dictionaries to MATLAB structs, and utilizing MATLAB functions like 'plot'. It also covers creating a MATLAB machine learning model for air quality prediction and how to expose this model to Python using the Engine API, allowing for a seamless workflow between the two programming environments.

Takeaways

• 🔗 MATLAB provides two-way integration with Python, allowing for flexible interaction between the two programming environments.
• 💻 The video uses Python 3.7 and demonstrates how to call Python functions from MATLAB and vice versa.
• 🌐 Data from a web service, openweathermap.org, is used to illustrate the integration between MATLAB and Python.
• 📚 MATLAB can call Python functions, create Python objects, and work with both base Python and installed packages.
• 📊 The script showcases how to convert Python dictionaries into MATLAB structs and handle data type conversions.
• 📈 MATLAB's `plot` function can be used to visualize data after converting it from Python types to MATLAB types.
• 🔧 The video provides a step-by-step guide on how to use a machine learning model in MATLAB to predict air quality based on weather conditions.
• 🛠️ MATLAB functions can be packaged to be used in Python, demonstrating the seamless integration between the two languages.
• 📓 The video uses a Jupyter Notebook to demonstrate calling MATLAB from Python using the Engine API.
• 🔚 The script concludes with instructions on shutting down the MATLAB engine started by the Engine API in the Jupyter Notebook.

Q & A

What is the purpose of the video on using MATLAB with Python?

The purpose of the video is to demonstrate how to integrate MATLAB with Python, showing how to call Python functions from MATLAB and how to call MATLAB functions from Python.

Which Python distribution is used in the video for integration with MATLAB?

Python 3.7 is used in the video for the integration with MATLAB.

What is the web service used in the example to get weather data?

The web service used in the example to get weather data is openweathermap.org.

What is the name of the Python module created by the speaker's colleague that interfaces with the weather web service?

The name of the Python module is 'weather.pi'.

How can one check their Python installation in MATLAB?

One can check their Python installation in MATLAB using the 'pyenv' command.

What is the basic syntax for calling a Python function from MATLAB?

The basic syntax for calling a Python function from MATLAB is 'py.<package or module name>.<function name>'.

How does MATLAB handle the conversion of Python dictionaries to MATLAB structs?

MATLAB automatically converts most of the data in a Python dictionary into MATLAB types, but for specific types like strings and date times, standard MATLAB functions like 'string', 'datetime' are used for conversion.

What function is used in the video to predict air quality based on weather conditions?

The 'predict air quality' function is used to predict air quality based on weather conditions.

How is the MATLAB function 'predict air quality' made accessible to Python?

The MATLAB function 'predict air quality' is made accessible to Python by packaging it into a function that can be called using the MATLAB Engine API for Python.

What is the first step to call MATLAB from Python using a Jupyter notebook?

The first step to call MATLAB from Python using a Jupyter notebook is to start a MATLAB engine in the background using the Engine API.

How is the MATLAB session that was started for communication with Python shut down in the video?

The MATLAB session started by the Engine API is shut down at the end of the Jupyter notebook session.

Outlines

00:00

🐍 Integrating MATLAB with Python

This video introduces the integration of MATLAB with Python, highlighting the two-way communication between the two programming languages. It discusses the compatibility of MATLAB with common Python distributions, using Python 3.7 as an example. The video demonstrates how to invoke Python functions from MATLAB and vice versa, utilizing a hypothetical Python module 'weather.pi' that interfaces with a web service to fetch and parse JSON data. The tutorial covers basic commands in MATLAB to check Python installation, specify Python versions, and call Python functions and objects. It also shows how to convert Python data types to MATLAB data types for further processing within MATLAB.

Keywords

💡MATLAB

MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. In the video, MATLAB is used to demonstrate how to interact with Python, showcasing its capability to call Python functions and how it can be used for data analysis and plotting.

💡Python

Python is a widely used high-level programming language known for its readability and versatility. It's extensively used in various domains, including web development, data analysis, artificial intelligence, and scientific computing. The video focuses on the integration of Python with MATLAB, highlighting how Python modules and functions can be utilized within MATLAB environments.

💡Integration

Integration in this context refers to the process of combining MATLAB and Python functionalities to work together seamlessly. The video demonstrates two-way integration: calling Python from MATLAB and vice versa, which is crucial for leveraging the strengths of both languages in a single workflow.

💡OpenWeatherMap

OpenWeatherMap is a web service that provides weather data. In the video, it's used as an example to show how to fetch and parse weather data using a Python module, which is then integrated with MATLAB for further analysis.

💡JSON

JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for humans to read and write and easy for machines to parse and generate. The video script mentions that the 'get current weather' function in the weather module gets the current weather conditions in JSON format, which is then parsed into a Python dictionary.

💡Python Dictionary

A Python dictionary is a collection of key-value pairs. In the video, the parsed weather data from OpenWeatherMap is returned as a Python dictionary, which is then converted into a MATLAB struct for further processing within MATLAB.

💡MATLAB Struct

A MATLAB struct is a data structure that can store data of different types in named fields. The video explains how to convert a Python dictionary into a MATLAB struct, which allows for the use of MATLAB's built-in functions to manipulate the data.

💡Data Conversion

Data conversion refers to the process of transforming data from one format to another. The video illustrates how to convert Python data types, such as strings, lists, and arrays, into MATLAB data types like strings, cell arrays, and arrays, which is essential for using the data with MATLAB functions.

💡Machine Learning Model

A machine learning model is a system that learns from data and improves its predictions over time through algorithms. In the video, a MATLAB machine learning model is used to predict air quality based on weather conditions, demonstrating the application of MATLAB in predictive analytics.

💡Engine API

The Engine API in MATLAB allows for the creation and control of MATLAB engines from external programs, such as Python. The video shows how to start a MATLAB engine in the background for Python to communicate with, enabling the execution of MATLAB functions from within a Python environment.

💡Jupyter Notebook

A Jupyter Notebook is an open-source web application that allows creation and sharing of documents containing live code, equations, visualizations, and narrative text. In the video, a Jupyter Notebook is used to demonstrate how to call MATLAB functions from Python, showcasing the interactive nature of data analysis.

Highlights

Matlab offers two-way integration with Python, allowing for flexible interaction between the two programming languages.

Matlab is compatible with common Python distributions, and the video uses Python 3.7 for demonstration.

A Python module named 'weather.pi' is used to interact with a web service and parse JSON data.

The video demonstrates how to call Python functions from Matlab using the 'py' command.

Matlab can call Python functions, create Python objects, and work with both base Python and installed packages.

An example is provided on how to call the square root function from the Python 'math' package.

The 'get_current_weather' function in the 'weather' module fetches current weather data in JSON format.

The 'parse_current_json' function converts JSON data into a Python dictionary.

Python dictionaries can be converted into Matlab structs, with automatic type conversion for most data.

Matlab functions like 'double', 'string', and 'datetime' are used to convert Python types to Matlab types.

The 'getforecast' function is used to obtain a series of predicted weather conditions.

Python lists and arrays are converted into Matlab arrays using the 'double' function.

The video shows how to use a machine learning model in Matlab to predict air quality based on weather conditions.

The model is loaded from a '.map' file, current data is formatted, and the 'predict' method is called for air quality prediction.

A Matlab function 'predict_air_quality' is created for use in Python, encapsulating the model's prediction process.

The video demonstrates calling Matlab from Python using a Jupyter notebook and the Engine API.

Matlab functions can be called from Python after starting a Matlab session in the background.

The video concludes with shutting down the Matlab session started by the Engine API.

The Matlab documentation provides further information and examples on integrating Matlab and Python.

Transcripts

hello and welcome to this video on using

matlab with python

matlab provides flexible two-way

integration with many programming

languages including python

in this video we will see how to call

python for matlab

and how to call matlab from python

matlab works with common python

distributions

for this video i will be using python

3.7

in this example we'll be using data from

a web service at openweathermap.org

let's suppose i have a colleague who

works in python she has created a module

called weather.pi

that reads from the web service and

parses the json data returned

of course we can also do that in matlab

but let's use this module as an example

let's see how to call her python

functions from matlab

let's start with some basics in matlab

you can check your python installation

using the pi

env command if you have multiple python

versions installed

you can use this command to specify

which python you want to use

matlab can call python functions and

create python objects from base python

from packages you have installed and

from your own python code

all python functions have the same basic

syntax

py followed by the package or module

name

followed by the function name here is an

example call to the square root function

in the python math package

now let's see how to use my colleague's

weather module we'll start by getting

the data for today

the get current weather function in the

weather module gets the current weather

conditions in json format

the parse current json function then

returns that data as a python dictionary

let's convert the python dictionary into

a matlab struct

notice that most of the data gets

automatically converted into matlab

types

however the city and current time are

returned as python strings

we'd like the city to be a matlab string

and the current time to be a matlab date

time

we can do that using standard matlab

functions like double

string and date time now let's call the

getforecast function which returns a

series of predicted weather conditions

over the next few days

we can see that the current time is

returned as a python list

and the other values are returned as

python arrays

converting arrays or lists is also

simple

the matlab double function will convert

the python array into a matlab array

to convert the current time values we

first convert the python list to a

matlab cell array

then convert each element of the cell

array into a string

then use the matlab datetime function to

convert those strings into date times

once we have the data as matlab data

types we can call other matlab functions

like plot

for more information on the mapping

between matlab data types and python

data types

search the matlab documentation for

python data type

now let's suppose i've created a machine

learning model that takes a set of

weather conditions

and returns a prediction of the air

quality i'll use my model to predict air

quality for the current conditions

let's see how that works there are three

steps load the model from a map file

take the current data from my python

call and convert it into a format

expected by the model call the predict

method of the model to get the expected

air quality

my python colleague wants to make use of

my air quality model in her python code

to give this to my colleague i package

it up

into a function called predict air

quality

the function does the same three steps

as above it loads the model

converts the data and calls the model's

predict method

now we have a matlab function that uses

the model to predict the air quality

let's see how my colleague would use it

in python

we'll demonstrate how to call matlab

from python using a jupyter notebook

the first step is to use the engine api

to start a matlab running in the

background for python to communicate

with

once the matlab is running we can call

any matlab function on the path

now we can use the get current weather

and parse current json functions

from the weather module just like we did

in matlab to get the current weather

conditions

then we can call the matlab function

predict air quality

to get the predictive results the last

step is to shut down the matlab started

by the engine api at the beginning of

our notebook

well that's it for this video on using

matlow with python

there's a lot more information in the

matlab documentation including many

examples

just search the documentation for python

thanks for watching