https://github.com/feromond/fft_rust

Small project to help me learn Rust and develop skills
https://github.com/feromond/fft_rust

fft learning rust scientific-computing scientific-visualization signal-processing

Last synced: about 8 hours ago
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Small project to help me learn Rust and develop skills

• Host: GitHub
• URL: https://github.com/feromond/fft_rust
• Owner: Feromond
• License: mit
• Created: 2023-04-06T20:33:41.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-08-11T06:46:42.000Z (3 months ago)
• Last Synced: 2024-08-11T07:43:52.688Z (3 months ago)
• Topics: fft, learning, rust, scientific-computing, scientific-visualization, signal-processing
• Language: Rust
• Homepage:
• Size: 1.92 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# FFT_Rust

## Hobby Project By: _Jacob Mish_

  Table of Contents

  


    


      About The Project

    

    


      Release Notes

      


        
Pre-v1

        
Pre-v2

        
Alpha_v1

      

    

    


      References

    

    

    

  


## About The Project

This project aims to create a dynamic fast fourier transform tool which can plot any raw signal and the associated amplitude spectrum after FFT.

To install all required python packages run:

`python -m pip install -r requirements.txt`

Then to run the front end GUI version with this python setup, run:

`streamlit run FileLoader.py`

## Release Notes:

#### Pre-release v1:



  

  

  



- Created a base simple version of the program with static initial inputs to test and validate the program functions.

- Plotting functionality is able to dynamically adjust plot x and y dimensions based on the input data, sampling rates, and number of points.

- Future implementation will begin to add forms of user input or potential implement basic file reading to process more interesting data.

#### Pre-release v2:

- Updated project to dynamically update plot windows and axis based on input data.

- Changed the signal from a simple pre-configured sinusoid to instead be read in from a file containing some complex raw signal.

- Adjusted all static parameters to dynamically compute based on the input raw signal file.

- Future implementations will start to work with the users inputs and will also handle more filetypes better.

- Theoretical future implementation will be to work on handling errors and exceptions better, as well as overall code optimization and redundancy reduction.

#### Alpha-release v1:

- Utilized python streamlit for the front-end of the application to allow for file uploading and displaying of the results

- Currently do not have much error handling for invalid data structures within files.

- Columns must still be in specific order for the data to plot correctly, hopefully in a future version I will add a way to self identify which column is most likely to be the "time" and which is the measured amplitudes.

- Added argument handling so when running the binary, a specific file can be referenced and it will process it. Still defaults to "sample_dataset/sample_data.txt" if there is no argument provided. Will not run without that file in the correct directory.

**Run the Streamlit Front-End Version**: Clone this repo locally and then ensure you have a python version with streamlit installed. Then within the project directory write

```

streamlit run FileLoader.py

```

If there is some error occuring, a temporary solution could be to recompile the rust binary release locally. This can be done within the project directory using

```

cargo build --release

```

### References

[Rustfft](https://docs.rs/rustfft/latest/rustfft/)