prosnet
A software package for developing classification models that predict physical behaviour postures.
Science Score: 10.0%
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓Committers with academic emails
1 of 2 committers (50.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (17.1%) to scientific vocabulary
Keywords
Repository
A software package for developing classification models that predict physical behaviour postures.
Basic Info
Statistics
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
- Releases: 0
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Metadata Files
readme.md
ProsNet
A software package for developing classification models that predict physical behaviour postures.
Explore the docs »
🤔 About The Project
This respository contains the sotware package and models described in the publication:
A Machine Learning Classification Model for Monitoring the Daily Physical Behaviour of Lower-Limb Amputees" (Griffiths et al., 2021).
The code works with data export from the activPAL activtiy monitor palt.com
Here are the main uses for this software:
- Estimate physical behaviour postures from shank accelerometer data
- Process shank accelerometer data along with thigh accelerometer event data to create a labeled dataset for training:
- Machine learning classifiers from heuristic features
- Deep learning classifiers from windowed acceleration data
- Re-create the model development process used in Griffiths et al. (2021)
- Experiment with new model development
- Estimate non-wear periods from accelerometer data
See the example scripts for each of these use cases.
Built With
🚀 Getting Started
Test out the package and start processing data.
💻 Prerequisites
You need these pre-installed on your device to get started.
- Python: A useful resource for installing python - instructions
- Pipenv: A package management tool that automatically creates and manages a virtualenv for your projects, as well as adds/removes packages from your Pipfile as you install/uninstall packages. It also generates the ever-important Pipfile.lock, which is used to produce deterministic builds. This package can be installed using:
sh pip install pipenv
Installation
- Open your terminal/shell and navigate to the directory where you want to install this software
- Clone the repo
sh git clone https://github.com/Ben-Jamin-Griff/ProsNet.git - Move into repo
sh cd ProsNet - Install Python packages
sh pipenv install
🗺️ Exploring The Package
Make sure you completed the installation steps and then run the following command:
Unix/maxOS
sh python3 examples/shallow_examples/example_1.pyWindows
sh py examples\shallow_examples\example_1.py
This shows some of the basic functionality of the package. Look through the other examples or dive into the src folder to see what's happening under the hood.
🤝 Contributing
Contributions are what make the open source community such an amazing place. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
License
Distributed under the MIT License. See LICENSE for more information.
Author
👤 Benjamin Griffiths
Owner
- Name: Benjamin Griffiths
- Login: Ben-Jamin-Griff
- Kind: user
- Location: Remote
- Website: https://github.com/Ben-Jamin-Griff
- Twitter: Ben_Jamin_Griff
- Repositories: 7
- Profile: https://github.com/Ben-Jamin-Griff
AI Engineer
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Committers
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Top Committers
| Name | Commits | |
|---|---|---|
| Benjamin Griffiths | d****0@g****m | 150 |
| Benjamin Griffiths | B****s@s****k | 1 |
Committer Domains (Top 20 + Academic)
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Last synced: 9 months ago
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Packages
- Total packages: 1
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Total downloads:
- pypi 31 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 5
- Total maintainers: 1
pypi.org: prosnet
A package for processing activPAL activity monitor data.
- Homepage: https://github.com/Ben-Jamin-Griff/ProsNet
- Documentation: https://prosnet.readthedocs.io/
- License: MIT License
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Latest release: 0.0.5
published about 4 years ago
Rankings
Maintainers (1)
Dependencies
- matplotlib *
- numba *
- pandas *
- prosnet *
- requests *
- resampy *
- scipy *
- seaborn *
- uos-activpal *
- certifi ==2021.10.8
- charset-normalizer ==2.0.7
- cycler ==0.10.0
- idna ==3.3
- kiwisolver ==1.3.2
- llvmlite ==0.37.0
- matplotlib ==3.4.3
- numba ==0.54.1
- numpy ==1.20.3
- pandas ==1.3.3
- pillow ==8.4.0
- prosnet ==0.0.2
- pyparsing ==2.4.7
- python-dateutil ==2.8.2
- pytz ==2021.3
- requests ==2.26.0
- scipy ==1.7.1
- seaborn ==0.11.2
- six ==1.16.0
- uos-activpal ==0.2.2
- urllib3 ==1.26.7
- matplotlib *
- numba *
- numpy *
- pandas *
- requests *
- scipy *
- seaborn *
- sklearn *
- uos-activpal *