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physemg

The C.U.T. Using B.U.L.K.: Exploring the Relationship Between Muscle Contraction and Weight Lifted Using an EMG.

Description

Data is found in /data. Figures are found in /figures. Code is all within /preanalysis.ipynb.

Setup

For this project, Python 3 version 3.9.18 is used. Other versions may also work. It is also assumed that LaTeX is setup correctly for pdf generation. This varies system to system, so instructions are not listed here.

It is recommended to use a virtual environment. For example,

/usr/bin/env python3 -m venv venv
source venv/bin/activate

To check the Python version,

python3 --version

should output some supported Python 3 version.

Requirements are found in /requirements.txt. These can be installed as follows.

pip install -r requirements.txt

Usage

Export Notebook

To generate to pdf,

jupyter nbconvert --execute preanalysis.ipynb --to pdf

Other output formats can be specified similarly e.g. html.

jupyter nbconvert --execute preanalysis.ipynb --to html

See nbconvert documentation for other output options.

Figures

The notebook generates the following figures:

  • alldata.png: Data displayed in 4 x 5 grid.
  • allrangecentral.png: Data subsetted into ranges with measures of central tendencies calculated, then fit with linear fit.
  • allrangedata.png: Data subsetted into ranges, then fit with linear fit.
  • allrangeloglog.png: Data subsetted into ranges, then taking log and log-log regression.
  • e20data.png: Example dataset: Ena 20 lbs.
  • e20ranges.png: Example dataset with ranges: Ena 20 lbs.
  • ealldata.png: Example dataset with ranges over all weights: Ena.
  • k17data.png: Example erroneous dataset: Khanh 17.5 lbs.