marisco 0.1.1

MARIS companion package and tutorials

marisco

The IAEA Marine Radioactivity Information System (MARIS) allows free access to users to search and download the results of measurements of radioactivity in seawater, biota, sediment and suspended matter. MARIS is maintained and developed by the IAEA Environmental Laboratories in Monaco.

The present Python package provides command-line utilities to:

1. Encode harvested datasets as NetCDF or .csv formats
2. Interact with the IAEA Open Data platform soon available
3. Provide data preprocessing pipelines for ad-hoc datasets
4. …

Prerequisites

We recommend to use the “Mamba” python package manager to create a clean and “deterministic” python environment.

Once installed, a typical Mamba workflow could be:

# Create an isolated env. with your prefered python version
mamba create -n name-of-your-env python=3.9 

# Then
mamba activate name-of-your-env
mamba install your-packages-of-interest
mamba deactivate # To quit your environment

Install & configuration

Now, to install marisco simply run

pip install marisco

Once successfully installed, run the following command:

maris_init

This script will create a .marisco/ directory containing various configuration/configurable files in your /home directory including:

• cdl.toml: MARIS NetCDF4 CDL (Common Data Language.
• configs.toml: contains several configurable constants, default paths, …
• lut/: directory containing several MARIS DB nomenclature files
• maris-template.nc: MARIS NetCDF4 template generated from the cdl and use to encode MARIS datasets

Notes: conda/mamba installer will be also available soon.

How to use

Command line utilities

All commands accept a -h argument to get access to its documentation.

maris_init

Create configuration files, MARIS NetCDF CDL (Common Data Language) and donwload required lookup tables (nomenclatures).

maris_create_nc_template

Generate MARIS NetCDF template to be used when encoding datasets

maris_netcdfy

Encode MARIS dataset as NetCDF using Jupyter Notebook handlers

Positional arguments:

• data: Path to dataset to encode
• nb_in: Path to Jupyter noteboook (NetCDF handler) to execute
• nc_out: Path to generated NetCDF4

Example:

maris_netcdfy _data/xls/tepco/coastal_water.xlsx nbs/handlers/tepco.ipynb _data/output/tepco.nc