Automated Spectral Deconvolution Codes for Quantitative Dye Tracing

This repository provides a set of Python scripts for processing and analyzing dye-tracer data using a deconvolution-based approach.

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File Overview and Execution Order

1. Peak_fitter_so.py
   This function file must be located in the same directory as std_water.py and btc_so.py.
   It is called internally by these scripts to perform peak fitting during data processing.

2. std_water.py
   This script processes all dye standard samples prepared in water.
   It computes a linear correlation between dye concentration and peak area, which is then used to calibrate water samples for each campaign.

3. btc_so.py
   This script generates breakthrough curves (BTCs) for all water samples in every campaign.
   Results are automatically saved in a folder named btc/, with subfolders created for each campaign.

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Input Data

All dye water sample data (including dye standards) can be downloaded from HydroShare at the following link:

🔗 Spectrofluorophotometer Dye Water Samples

Before running the scripts, ensure that the directory paths in your code correspond to the final locations of these files on your computer.

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Output Location

By default, btc_so.py will create a folder named results/ in the working directory defined in the script.
You may modify this directory path to specify a different output location if desired.

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Workflow Summary

1. Place all three scripts (Peak_fitter_so.py, std_water.py, btc_so.py) in the same directory.
2. Run std_water.py to calibrate dye concentration relationships.
3. Run btc_so.py to generate BTC curves for all campaigns.
4. Review the results saved in the automatically generated results/ and btc/ folders.

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Requirements

• Python 3.8+
• Common scientific libraries:
  numpy, pandas, scipy, matplotlib

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License

This project is licensed under the MIT License.
© 2025 Yoon Research Group, University of Florida