Title
Guidelines for data analysis scripts.
Abstract
Unorganized heaps of analysis code are a growing liability as data analysis pipelines are getting longer and more complicated. This is worrying, as neuroscience papers are getting retracted due to programmer error. this paper, some guidelines are presented that help keep analysis code well organized, easy to understand and convenient to work with: 1. Each analysis step is one script 2. A script either processes a single recording, or aggregates across recordings, never both 3. One master script to run the entire analysis 4. Save all intermediate results 5. Visualize all intermediate results 6. Each parameter and filename is defined only once 7. Distinguish files that are part of the official pipeline from other scripts In addition to discussing the reasoning behind each guideline, an example analysis pipeline is presented as a case study to see how each guideline translates into code.
Year
Venue
DocType
2019
arXiv: Software Engineering
Journal
Volume
Citations 
PageRank 
abs/1904.06163
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Marijn van Vliet1215.55