CAPy: Circadian Analysis Python

Table of Contents

• Features
• Screenshots
• Installation
• Usage
• Prerequisites
• License

Features

• Data Import: Load collected activity data (see below for correct formatting)
• Session Management: Save and load sessions to preserve your work.
• Analysis Options:
  • Generate single and double actograms.
  • Generate periodograms.
  • Calculate onset, offset, acrophase, and bathyphase times.
  • Save results to CSV for further analysis.
• Interactive Plots:
  • Drag and adjust markers on actograms to refine analysis.
  • Real-time updates to results upon adjustments.
• Customizable Parameters:
  • Use only a section of the data.
  • Set threshold percentiles for activity detection.
  • Define inactivity and activity durations (N and M hours).
  • Choose to use calculated free running period (tau) or manually set values.

Installation

We recomend using anaconda for ease of instillation

1. Clone the Repository

   git clone https://github.com/Arthurmayo/CAPy.git
   

2. Navigate to the file location

   cd C:path\to\where\you\cloned
   

3. Create an environment with dependencies

   conda env create -f CAPy_env.yaml
   

4. Activate conda environment

   conda activate CAPy
   

5. Run the Application

   python gui.py
   

Usage

1. Launch the Application

   Run python gui.py in your terminal.

2. Load Data Files

   

   • Data must be in the above format with a .csv extension to work in CAPy
   • Click on "Select Main Data File" to load your primary activity CSV file.

3. Configure Analysis Parameters

   • Choose the section of time to be used for your data in DD:HH format, or leave blank to use the whole data set
   • Choose to use the calculated tau or manually enter a tau value.
   • Set threshold percentile, N hours of inactivity, and M hours of activity.
   • Select tasks such as generating actograms, plotting Fourier analysis, saving results to CSV, or performing comparisons.

4. Run Analysis

   Click on "Run Analysis" to perform the selected tasks.

5. Interact with Results

   • View generated plots in the "Plots" tab.
   • Drag markers on actograms to adjust onset, offset, acrophase, and bathyphase times.

6. Save and Load Sessions

   • Use "Save Session" to save your current state.
   • Use "Load Session" to resume work from a previous session.

Prerequisites

• Python 3.6 or higher
• Packages:
  • PyQt5
  • pandas
  • matplotlib
  • numpy
  • scipy

Note: Ensure all dependencies are installed as per the Installation section.

License

This project is licensed under the MIT License.