Скачать или смотреть How to Plot from Two Separate Subfolders in Matlab onto the Same Figure

Learn how to effectively plot data from two distinct subfolders in Matlab, utilizing legends to distinguish between phases. This guide provides clear instructions and sample code!
---
This video is based on the question https://stackoverflow.com/q/76780513/ asked by the user 'Chaz69631' ( https://stackoverflow.com/u/22179535/ ) and on the answer https://stackoverflow.com/a/76782755/ provided by the user 'Jimbo' ( https://stackoverflow.com/u/764365/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How do I plot from two separate subfolders in Matlab onto the same plot?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Plot from Two Separate Subfolders in Matlab onto the Same Figure

If you've ever found yourself juggling data spread across multiple subfolders in Matlab, you're not alone. Many users encounter this issue, especially when organizing experimental data or results from simulations. One common scenario involves plotting data from separate phases stored in distinct folders and needing to visualize them on the same plot.

In this guide, we will explore how to take data stored in two subfolders and create engaging plots that allow for easy comparison of results. Specifically, we will learn how to plot text files containing data from Phase1 and Phase2, ensuring that our legends clearly indicate which datasets correspond to which phase.

Understanding the Structure

You may have your data organized in a system like this:

C:\Users\Name\OneDrive\Desktop\Outputs\Data\Phase1\out\Stats

C:\Users\Name\OneDrive\Desktop\Outputs\Data\Phase2\out\Stats

Inside each Stats folder, you have ten .txt files (numbered 1.txt to 10.txt). Each file contains similar data dimensions, which simplifies our plotting process considerably.

The Plotting Strategy

We'll break down the plotting process into several key steps:

1. Setting Up Directories

We need to define our directory paths where the data files are saved. Use the following code snippet to specify these paths:

[[See Video to Reveal this Text or Code Snippet]]

2. Looping Through Files

By iterating from 1 to 10, we can load and plot each corresponding file from both directories. Here's how to do that:

[[See Video to Reveal this Text or Code Snippet]]

3. Cleaning Up the Legend

One common pitfall involves cluttering the plot with unnecessary path information in the legend. Always ensure your legends concisely represent the datasets. By properly defining legends, we can provide a more readable visualization:

[[See Video to Reveal this Text or Code Snippet]]

Future Considerations

As you continue developing your project, you might want to expand your plotting capabilities. One idea is to incorporate dropdowns for user selection of the phase or files to plot. This feature would enhance user interactivity and make your application more versatile.

For future expansions:

Consider dynamically generating dropdown menus that allow users to select which .txt file they wish to plot.

Think about grouping your data in such a way that future phases or datasets are as easy to access and plot as the current setup.

By following these steps, you can efficiently visualize data from multiple folders in Matlab without losing clarity or getting lost in complex file paths. With a clear legend and structured plotting approach, your analysis can be both effective and visually appealing.

To summarize the flow:

Define your data directories.

Use a loop to read and plot your files.

Keep your legend clean and informative.

With this foundation, you’re well on your way to mastering data visualization in Matlab!