Metadata-Version: 2.3
Name: circStudio
Version: 1.0.9
Summary: A Python toolkit for smoothing, modeling, and analyzing actigraphy time series.
Keywords: actigraphy,actimetry,wearables,rhythm analysis,time-series,circadian,ultradian,chronobiology,sleep,cosinor,rest-activity,biological rhythms,functional modeling
Author: Daniel Marques, Nuno Morais, Cátia Reis
Author-email: Daniel Marques <daniel.marques@gimm.pt>, Nuno Morais <nuno.morais@nms.unl.pt>, Cátia Reis <catia.reis@medicina.ulisboa.pt>
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         PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
         
         #### 17. Interpretation of Sections 15 and 16.
         
         If the disclaimer of warranty and limitation of liability provided
         above cannot be given local legal effect according to their terms,
         reviewing courts shall apply local law that most closely approximates
         an absolute waiver of all civil liability in connection with the
         Program, unless a warranty or assumption of liability accompanies a
         copy of the Program in return for a fee.
         
         END OF TERMS AND CONDITIONS
         
         ### How to Apply These Terms to Your New Programs
         
         If you develop a new program, and you want it to be of the greatest
         possible use to the public, the best way to achieve this is to make it
         free software which everyone can redistribute and change under these
         terms.
         
         To do so, attach the following notices to the program. It is safest to
         attach them to the start of each source file to most effectively state
         the exclusion of warranty; and each file should have at least the
         "copyright" line and a pointer to where the full notice is found.
         
         ```
             <one line to give the program's name and a brief idea of what it does.>
             Copyright (C) <year>  <name of author>
         
             This program is free software: you can redistribute it and/or modify
             it under the terms of the GNU General Public License as published by
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             (at your option) any later version.
         
             This program is distributed in the hope that it will be useful,
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             You should have received a copy of the GNU General Public License
             along with this program.  If not, see <https://www.gnu.org/licenses/>.
         ```
         
         Also add information on how to contact you by electronic and paper
         mail.
         
         If the program does terminal interaction, make it output a short
         notice like this when it starts in an interactive mode:
         
         ```
             <program>  Copyright (C) <year>  <name of author>
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             This is free software, and you are welcome to redistribute it
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         ```
         
         The hypothetical commands \`show w' and \`show c' should show the
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         You should also get your employer (if you work as a programmer) or
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         the GNU GPL, see <https://www.gnu.org/licenses/>.
         
         The GNU General Public License does not permit incorporating your
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Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Dist: lmfit>=1.3.4,<2
Requires-Dist: pandas>=2.3.3,<3
Requires-Dist: numpy>=2.4.1,<3
Requires-Dist: scipy>=1.17.0,<2
Requires-Dist: statsmodels>=0.14.6,<1
Requires-Dist: plotly>=6.5.2,<7
Requires-Dist: seaborn>=0.13.2,<1
Requires-Dist: matplotlib>=3.10.8,<4
Requires-Dist: pyexcel>=0.7.4,<1
Requires-Dist: pyexcel-ods
Requires-Dist: pingouin
Requires-Python: >=3.12
Project-URL: Homepage, https://github.com/djmarques/circStudio
Project-URL: Issues, https://github.com/djmarques/circStudio/issues
Description-Content-Type: text/x-rst

**circStudio**
================

**circStudio** is a Python package for preprocessing, modeling, and analyzing actigraphy time series. It
enables users to read activity, light and temperature recordings collected by a wide range of actigraphy
devices, and provides conversion modules for commonly used systems (e.g., ActTrust, Actiwatch).

In addition to signal processing and common actigraphy-derived metrics, **circStudio** incorporates
mathematical models of circadian rhythms and algorithms for automatic sleep detection. This enables
users not only to characterize rest-activity patterns, but also to simulate circadian phase dynamics,
predicting sleep timing, and link actigraphy-derived signals to underlying physiological processes.

Core functionalities
--------------------

Cleaning and preprocessing raw actigraphy data
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

- Format-agnostic and flexible ``Raw`` class for importing actigraphy recordings
- Dedicated conversion modules for commonly used actigraphy file formats
- Automatic truncation of invalid or incomplete sequences at the beginning and/or end of recordings
- Detection of non-wear periods with optional imputation strategies for missing data

Common actigraphy-derived metrics
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Compute standard activity- and light-derived metrics, including:

- **Interdaily Stability (IS)**
- **Intradaily Variability (IV)**
- **Rest–activity rhythm metrics**
- **Time Above Threshold (TAT)**
- **Mean Light Timing (MLiT)**

Mathematical models of circadian rhythms
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A defining feature of ``circStudio`` is the inclusion of several mathematical models of
of circadian rhythms. Implemented models include:

- **Forger model**
- **Jewett model**
- **Hannay Single-Population (HannaySP)**
- **Hannay Two-Population (HannayTP)**
- **Hilaire 2007 model**
- **Skeldon 2023 model**
- **Breslow 2013 model** (melatonin dynamics)

These models enable users to:

- Predict circadian phase (Dim Light Melatonin Onset, DLMO) given a light schedule
- Model melatonin dynamics
- Infer sleep timing and circadian misalignment
- Integrate physiology-driven modeling with actigraphy-derived data

Design philosophy
-----------------

``circStudio`` unifies two complementary approaches to circadian research: data-driven actigraphy analysis and
mechanistic circadian modeling.

The package integrates preprocessing, rhythm quantification, and sleep detection capabilities from ``pyActigraphy``
with mathematical models of circadian dynamics provided by the ``circadian`` package.

By bridging actigraphy signal processing,  rhythm metrics, and physiology-based modeling, ``circStudio`` enables
researchers to move seamlessly from raw actigraphy recordings to predictions of circadian phase, sleep timing, and
circadian misalignment.

Citation
========

Citation of the original papers:

Hammad G, Reyt M, Beliy N, Baillet M, Deantoni M, Lesoinne A, et al. (2021) pyActigraphy: Open-source python package
for actigraphy data visualization and analysis. PLoS Comput Biol 17(10): e1009514.
https://doi.org/10.1371/journal.pcbi.1009514

Hammad, G., Wulff, K., Skene, D. J., Münch, M., & Spitschan, M. (2024). Open-Source Python Module for the Analysis of
Personalized Light Exposure Data from Wearable Light Loggers and Dosimeters.
LEUKOS, 20(4), 380–389. https://doi.org/10.1080/15502724.2023.2296863

Tavella, F., Hannay, K., & Walch, O. (2023). Arcascope/circadian: Refactoring of readers and metrics modules, Zenodo,
v1.0.2. https://doi.org/10.5281/zenodo.8206871

License
=======

This project keeps the same license as **pyActigraphy**, the GNU GPL-3.0 License.

Acknowledgments
===============

Sincere thanks to the following teams:

* The developers of the original **pyActigraphy** package, whose work laid the foundation for this project (https://github.com/ghammad/pyActigraphy).
* The authors of the **circadian** package, whose original implementation of light-informed models was crucial for our implementation (https://github.com/Arcascope/circadian).