This repository contains the Python code used for data processing, statistical analysis and visualization described in the following paper:

Belteki G, Morley CJ. High-frequency oscillatory ventilation with volume guarantee: a single-centre experience. Arch Dis Child Fetal Neonatal Ed. 2019 Jul;104(4):F384-F389. doi: 10.1136/archdischild-2018-315490. Epub 2018 Sep 14. PubMed PMID: 30217870.

Link to the paper: https://fn.bmj.com/content/104/4/F384.abstract

Contact: gusztav.belteki@addenbrookes.nhs.uk; gbelteki@aol.com

The outputs (numbers, tables, graphs) of the cells of the Jupyter Notebooks (.ipynb files) have been suppressed in order to comply with copyrights. Some of the corresponding data and graphs can be found in the paper and its only supplementary material.

This code can be viewed in any web browser. If the code is displayed (rendered) in Github, copy and paste the URL (web adress) of the Notebook into nbviewer (https://nbviewer.jupyter.org) for a read-only display.

To run the code, you need to use Jupyter. The raw ventilator data are not shared but the user can run this code on his or her own data obtained in the same format.

Packages required to run this Notebook:

Python version: 3.5.3

IPython version: 5.3.0

pandas version: 0.20.1

matplotlib version: 2.0.2

NumPy version: 1.12.1

SciPy version: 0.19.0

I recommend downloading these packages using the freely availably Anaconda built: https://www.continuum.io/downloads

The Notebook also depends on the supplied helper files which should be in the same directory as the .ipynb notebook files.

gb_loader.py

gb_stats.py

gb_transform.py

gb_visualizer.py