circaPy 0.1.6

For analysing circadian activity data

CircaPy

CircaPy is a python module for circadian analysis of activity data. It was developed using laboratory rodents data but is applicable across species and monitoring devices.

A limited version is available as an interactive website

Getting Started

Install circapy from pip

pip install circapy

This will install circaPy in your current python environment. Package dependencies are listed in the pyproject.toml file

Using circaPy

circaPy provides a set of functions to analyse and plot the most common methods of circadian analysis.

Create some test data

import pandas as pd
import numpy as np
import circaPy.activity as act

# Create a sample dataset with time-series activity data
index = pd.date_range(start='2024-01-01', periods=86400, freq="10s")
values = np.random.randint(0, 100, size=(len(index),2))

df = pd.DataFrame(values, index=index)

Calculate IV

# Use circaPy's calculate_IV function to compute Interdaily Variability
iv = act.calculate_IV(df)

# Print the result
print(f"Interdaily Variability (IV). Col 0: {iv[0]:.4f}")

Plot actogram

# Use circaPy plot_actogram
import circaPy.plots as cpp

cpp.plot_actogram(df, showfig=True)

Contributing

1. Fork this repository
2. Create branch git checkout -b <branch-name>
3. Create uv environment uv sync
4. Use uv to run test suite with make test
5. Make your changes and commit them git commit -m <commit-message>
6. PR back to the development branch
   • ensure tests are passing, will be required to merge into development branch.

Authors

• Angus Fisk
  • [e-mail]
• Ayobami Fawole
  • [e-mail]

Licence

• Available under GNU general public licence