Project for converting data from ctd and mooring to netcdf

The goal of this project is to convert CTD profiles into seperate and a combined netcdf file that can be published.

Dependencies

Made on a MacOs python in requirements.yml install dependencies in a virtual environment code here

conda env create -f requirements.yml

Usage

You should be able to use python and know how virtual environments work conda activate deep_water

1. Put CTD data in data/raw
2. Run ctd_monthly.py

Project Structure

The project structure distinguishes three kinds of folders:

• read-only (RO): not edited by either code or researcher
• human-writeable (HW): edited by the researcher only.
• project-generated (PG): folders generated when running the code; these folders can be deleted or emptied and will be completely reconstituted as the project is run.

.
├── .gitignore
├── LICENSE
├── README.md
├── requirements.txt
├── data               <- All project data, ignored by git
│   ├── processed      <- The final, canonical data sets for modeling. (PG)
│   ├── raw            <- The original, immutable data dump. (RO)
│   └── temp           <- Intermediate data that has been transformed. (PG)
├── docs               <- Documentation notebook for users (HW)
│   ├── manuscript     <- Manuscript source, e.g., LaTeX, Markdown, etc. (HW)
│   └── reports        <- Other project reports and notebooks (e.g. Jupyter, .Rmd) (HW)
├── img                <- Where the figures are for README and insight
├── results
│   ├── figures        <- Figures for the manuscript or reports (PG)
│   └── output         <- Other output for the manuscript or reports (PG)
└── src                <- Source code for this project (HW)

Add a citation file

Create a citation file for your repository using cffinit

License

This project is licensed under the terms of the MIT License.

Origin of the project structure (from workshop)

This simple project structure template repository is adapted from the Good Enough Project Cookiecutter template by Barbara Vreede (2019). If you plan to develop a package, check the template repository for a Python package.