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DOI

Simons CMAP Article: Case Study

This repository contains a few Python scripts demonstrating how to retrieve and colocalize data sets. The resulting colocalized data sets are then used to train a predictive machine learning model for sea surface cell abundance of Cyanobacteria Prochlorococcus, Synechococcus, and Picoeukaryotes.

Usage

Before running any of the scripts, register at https://simonscmap.com/ and get an API_KEY. Store your API_KEY in the ./config/config.py file.

collect.py retrieves a predefined list of data sets that contain measurements of Cyanobacteria abundances. The retrieved data sets are stored at ./data/ directory in form of csv files.

colocalize.py colocalizes the retrieved data sets with a given number of ancillary environmental variables. The colocalized data sets are stored at ./data/colocalied/ directory in form of csv files.

compiler.py concatenates the colocalized data sets in form of a single csv file at ./data/compiled/ directory.

Dependency

pycmap

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