A Unifying API for Calling the 'Unity' '3D' Video Game Engine

Functions for the creation and manipulation of scenes and objects within the 'Unity' '3D' video game engine (< https://unity.com/>). Specific focuses include the creation and import of terrain data and 'GameObjects' as well as scene management.

Interface to Species Occurrence Data Sources

A programmatic interface to many species occurrence data sources, including Global Biodiversity Information Facility ('GBIF'), 'iNaturalist', 'eBird', Integrated Digitized 'Biocollections' ('iDigBio'), 'VertNet', Ocean 'Biogeographic' Information System ('OBIS'), and Atlas of Living Australia ('ALA'). Includes functionality for retrieving species occurrence data, and combining those data.

Landscape Visualizations in R and 'Unity'

Functions for the retrieval, manipulation, and visualization of 'geospatial' data, with an aim towards producing '3D' landscape visualizations in the 'Unity' '3D' rendering engine. Functions are also provided for retrieving elevation data and base map tiles from the 'USGS' National Map < https://apps.nationalmap.gov/services/>.

Print Maps, Draw on Them, Scan Them Back in

Enables preparation of maps to be printed and drawn on. Modified maps can then be scanned back in, and hand-drawn marks converted to spatial objects.

Interface with the United Nations Comtrade API

Interface with and extract data from the United Nations 'Comtrade' API < https://comtradeplus.un.org/>. 'Comtrade' provides country level shipping data for a variety of commodities, these functions allow for easy API query and data returned as a tidy data frame.

A Test Environment for Database Requests

Testing and documenting code that communicates with remote databases can be painful. Although the interaction with R is usually relatively simple (e.g. data(frames) passed to and from a database), because they rely on a separate service and the data there, testing them can be difficult to set up, unsustainable in a continuous integration environment, or impossible without replicating an entire production cluster. This package addresses that by allowing you to make recordings from your database interactions and then play them back while testing (or in other contexts) all without needing to spin up or have access to the database your code would typically connect to.

Deterministic Categorization of Items Based on External Code Data

Fast categorization of items based on external code data identified by regular expressions. A typical use case considers patient with medically coded data, such as codes from the International Classification of Diseases ('ICD') or the Anatomic Therapeutic Chemical ('ATC') classification system. Functions of the package relies on a triad of objects: (1) case data with unit id:s and possible dates of interest; (2) external code data for corresponding units in (1) and with optional dates of interest and; (3) a classification scheme ('classcodes' object) with regular expressions to identify and categorize relevant codes from (2). It is easy to introduce new classification schemes ('classcodes' objects) or to use default schemes included in the package. Use cases includes patient categorization based on 'comorbidity indices' such as 'Charlson', 'Elixhauser', 'RxRisk V', or the 'comorbidity-polypharmacy' score (CPS), as well as adverse events after hip and knee replacement surgery.

Parse Messy Geographic Coordinates

Parse messy geographic coordinates from various character formats to decimal degree numeric values. Parse coordinates into their parts (degree, minutes, seconds); calculate hemisphere from coordinates; pull out individually degrees, minutes, or seconds; add and subtract degrees, minutes, and seconds. C++ code herein originally inspired from code written by Jeffrey D. Bogan, but then completely re-written.

'OpenStreetMap' API

Interface to 'OpenStreetMap API' for fetching and saving data from/to the 'OpenStreetMap' database (< https://wiki.openstreetmap.org/wiki/API_v0.6>).

Efficiently Retrieve and Process Satellite Imagery

Downloads spatial data from spatiotemporal asset catalogs ('STAC'), computes standard spectral indices from the Awesome Spectral Indices project (Montero et al. (2023) ) against raster data, and glues the outputs together into predictor bricks. Methods focus on interoperability with the broader spatial ecosystem; function arguments and outputs use classes from 'sf' and 'terra', and data downloading functions support complex 'CQL2' queries using 'rstac'.