PhenoFit

**PhenoFit ** is a Python-based interactive GUI tool for fitting double logistic curves to vegetation index time-series data (such as GCC, NDVI, EVI, ExG, RGBVI).
It is designed specifically for crop phenology research using PhenoCam, UAV, or satellite data.

📋 Table of Contents

• Features
• Requirements
• Installation
• Getting Started
• Step-by-Step Usage Guide
• Screenshots
• Output Files
• License
• Author & Contact

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🌟 Features

• Double logistic curve fitting with GUI
• Slider and spin box control of parameters
• Smart initial parameter estimation
• SOS, EOS, and Peak annotations
• Grouping visualization for crop stages
• Constrained optimization with fallback logic
• Export of fitted values and plots

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🧰 Requirements

• Python 3.7 or higher
• Packages:
  • pyqt5
  • matplotlib
  • numpy
  • pandas
  • scipy
  • scikit-learn
  • openpyxl

Install all at once:

pip install -r requirements.txt

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🛠 Installation

1. Install Python

Go to https://www.python.org/downloads/ and install Python 3.7+

Make sure to check “Add Python to PATH” during installation.

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2. Clone the Repository

git clone https://github.com/ItsAkashPandey/PhenoFit.git
cd PhenoFit

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3. Install Dependencies

pip install -r requirements.txt

If you face any issues, try using a virtual environment:

python -m venv venv
venv\Scripts\activate    # On Windows
# or
source venv/bin/activate   # On Linux/Mac

pip install -r requirements.txt

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🚀 Getting Started

Run the Application

python PhenoFit_Pro.py

The GUI will open.

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📚 Step-by-Step Usage Guide

1. Load Main Data

• Click Load Data File
• Select your .csv or .xlsx file with columns like DAS, GCC, NDVI, etc.
• Choose X (time axis) and Y (index) columns

2. (Optional) Load Grouping Data

• Click Load Grouping Data
• Load an Excel file with:
  • Start column (required)
  • End column (optional)
  • Label (stage names like "Tillering", "Heading")
  • Color (optional)

3. Adjust Parameters

You can:

• Use sliders for rough tuning
• Use spin boxes for exact values
• Lock any parameter using checkboxes

4. Optimize Curve

• Click Optimize Fit
• The app will try fitting the best double logistic curve
• Ensures biologically meaningful constraints like SOS < EOS

5. Visualize SOS, EOS, Peak

Check or uncheck the box: "Show SOS/EOS/Peak" to toggle markers.

6. Export Result

• Click Download Graph + Excel
• This will save:
  • .xlsx file with observed + fitted data
  • .png high-res image of the curve

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🖼 Screenshots

1. Opening Window

2. Load Main Data (Provided in Example Data)

3. Fit the Curve using parameters/Optimization

4. Load Grouping

5. Select Grouping Parameters

6. Toggle On/Off Parameters (SOS/EOS/Peak in Graph)

7. Save Graph and Fitted Parameters

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📂 Output Files

• Excel Output (.xlsx):
  • Sheet 1: Observed + Fitted values
  • Sheet 2: Parameters used
  • Sheet 3: Grouping stages (if provided)
• PNG Output (.png):
  • High-quality plot image

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📜 License

This project is licensed under the CC BY-NC-ND 4.0 License.
You may use and share this work with proper credit, but modification and commercial use are prohibited without permission.

For commercial inquiries or special permissions, contact:
Akash Kumar – akash_k@ce.iitr.ac.in

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👤 Author & Contact

Akash Kumar
PhD Scholar, Geomatics Engineering, IIT Roorkee
Research Focus: Remote Sensing, Crop Phenology, PhenoCam, AI
Email: akash_k@ce.iitr.ac.in

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📣 Feedback & Issues

If you find any bug or want a new feature, open an issue at:

👉 https://github.com/ItsAkashPandey/PhenoFit/issues