phenobooth-analysis

Analysis of phenobooth data from a library screen.

Requirements

• Anaconda
• Python 3 (comes included in Anaconda)
• Git (or any Git client of your choice, e.g. Github Desktop)

Installation

• Create an anaconda environment called phenobooth-analysis, with Jupyter Notebook installed in it.
• Clone locally this repository.
• From an anaconda terminal, cd to this repository's root and then do:

  conda activate phenobooth-analysis  # activates the new environment
  pip install -r requirements.txt     # installs all dependencies
  conda install -c anaconda graphviz  # Needs to be conda-installed
  type nul > .env                     # creates a .env file for storing passwords
  jupyter notebook                    # runs the jupyter notebook engine

Repository Structure

|- code/            # all programmatic code relating to the project
|  +- templates/    # scripts for generating template files
|
|- data/            # all data from the study
|  |- raw_internal/ # raw data generated in-lab or by collaborators, will not be altered
|  |- raw_external/ # data from third-party sources, databases etc, will not be altered
|  |- intermediate/ # intermediate data on its way from raw to final
|  +- final/        # final data for figures/visualizations
|
|- doc/             # documentation for the study and other explanatory material
|
|- results          # all output from workflows and analyses
|  |- figures/      # graphs, likely designated for manuscript figures
|  +- pictures/     # diagrams, images, and other non-graph graphics
|
|- .env             # file to store passwords and usernames needed for the scripts. This
|                     will not get synced to GitHub.
|- .gitignore       # files that will not sync to Github
|- LICENSE          # license
|- README.md        # the top level description of content
|- requirements.txt # the requirements file for reproducing the analysis environment,
|                     e.g. generated with `pip freeze > requirements.txt`
+- to-dos.md        # pending things that are yet to be done

Navigate to each folder's README.md to learn more about the corresponding section.

Acknowledgments

The initial file and directory structure of this project was developed by a group of participants in the Reproducible Science Curriculum Workshop, held at NESCent in December 2014. The structure is based on, and heavily follows the one proposed by Noble 2009, with a few but small modifications. The original repository has been modified by Martin Engqvist and the one presented here differs in some ways.