In this tutorial, we will learn how to plot a MATLAB file (.mat) in Python. MATLAB is a high-level technical computing language whereas Python is a general-purpose programming language. In several instances, those accustomed to MATLAB may wish to bring their data (saved in .mat files) into Python for further manipulation.
For that, we will use Python’s Scipy library to load the .mat file, and Matplotlib to plot the data.
Step 1: Installing necessary Python libraries
The first step to import your .mat file into Python is by installing the necessary libraries such as Scipy and Matplotlib. To install these libraries, open your terminal and type the following commands:
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pip install scipy pip install matplotlib |
Step 2: Importing the libraries
Once you have installed Scipy and Matplotlib, you need to import them into your Python script using the import command.
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import scipy.io import matplotlib.pyplot as plt |
Step 3: Loading the .mat file
In this step, we will load the .mat file using the scipy.io.loadmat() function. Just replace ‘myfile.mat’ with your .mat file name.
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mat = scipy.io.loadmat('myfile.mat') |
Step 4: Exploring the .mat file content
Now, you can explore your .mat file content by simply printing the variable with the print() function.
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print(mat) |
Step 5: Plotting the data
Once you have explored your .mat file content, you can plot the data using pyplot from the matplotlib library. Below is the code snippet to plot the data.
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data = mat['YourVariable'] # Replace 'YourVariable' with variable inside your mat file plt.plot(data) plt.show() |
Below is the full code
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import scipy.io import matplotlib.pyplot as plt # Load the .mat file mat = scipy.io.loadmat('myfile.mat') # Print the content of the .mat file print(mat) #Plot the data data = mat['YourVariable'] plt.plot(data) plt.show() |
In Conclusion
In this tutorial, we learned how to use Python to import, explore, and plot data from a MATLAB .mat file with the help of Scipy and Matplotlib libraries. The mentioned steps in this tutorial guide you on how to bridge the gap between MATLAB and Python, giving you the flexibility to manipulate and visualize your data conveniently.