This folder contains the savsnet Python module, containing Python functions to analyse SAVSNet data. The functions are generic, and other users may find them useful.

The savsnet/prev_ts_GP module contains functions that build a Binomial regression model with a Gaussian process linear predictor to model a timeseries of Binomial random variables (e.g. prevalence). See docstrings for each function for further details. For convenience, the module may be run as a script, for example:

$ python savsnet/prev_ts_GP.py -c trauma -s dog cat -i 1000 -o pred myData.csv

where myData.csv is a CSV file containing (minimally) a 'Date' column (ISO format), 'Consult_reason', and 'Species' columns.

See

$ python savsnet/prev_ts_GP.py --help

for further details.

The savsnet/plot_ts_GP module contains functions for plotting posterior predictive distributions from savsnet/prev_ts_GP output. Documentation for individuals functions are contained in the docstrings. For convenience, the module may be run as a script, for example:

$ python savsnet/plot_ts_GP.py -d myData.csv -s dog cat -c trauma -p pred_dog_trauma.pkl pred_cat_trauma.pkl -o gpFigure.pdf

See

$ python savsnet/plot_ts_GP.py --help 

for further details.

The savsnet/logistic2D module contains functions for spatial smoothing of case occurrence at point locations, using an inducing point approximation to a logistic geostatistical model with stationary mean and Matérn ($k=3/2$) covariance function. This is called by the logisticKrige.py Python script such as:

$ python logistic_krige.py -i 5000 -s '2020-03-04' -p gadm36_GBR.gpkg myData.csv

where myData.csv is a CSV file containing at least the headings consult_date (ISO date format), person_easting and person_northing (in rectangular coordinates), and case (1 or 0 denoting positive or negative for a given condition). The script runs the logistic geostatistic model, writes the posterior to a Python pickle file and the posterior mean to a GeoTIFF file.

See

$ python logisticKrige.py --help

for information on further arguments.

This software is release under the MIT license. Please refer to the LICENSE file contained in the same directory as this file for further details.