<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>nick-gauthier.r-universe.dev</title><link>https://nick-gauthier.r-universe.dev</link><description>Recent package updates in nick-gauthier</description><generator>R-universe</generator><image><url>https://github.com/nick-gauthier.png</url><title>R packages by nick-gauthier</title><link>https://nick-gauthier.r-universe.dev</link></image><lastBuildDate>Thu, 15 Oct 2026 21:33:48 GMT</lastBuildDate><item><title>[flmnh-ai] hipergator 0.1.0</title><author>nicolas.gauthier@ufl.edu (Nicolas Gauthier)</author><description>Simple interface for submitting and managing SLURM jobs on
the University of Florida HiPerGator cluster. Provides
authentication, data transfer, job submission, monitoring, and
result retrieval with configuration management for streamlined
workflows.</description><link>https://github.com/r-universe/flmnh-ai/actions/runs/38821912368</link><pubDate>Thu, 15 Oct 2026 21:33:48 GMT</pubDate><r:package>hipergator</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://flmnh-ai.r-universe.dev</r:repository><r:upstream>https://github.com/flmnh-ai/hipergator</r:upstream></item><item><title>[flmnh-ai] globalhex 0.0.0.9000</title><author>nicolas.gauthier@ufl.edu (Nicolas Gauthier)</author><description>An experimental package exposing a small, H3-shaped R API
over modern DGGRID hierarchical indexes, using a bundled copy
of DGGRID. The default grid is the equal-area IGEO7 grid with
Z7 digit-string indexes. ISEA3H with Z3 indexes and a partial
compatibility path through dggridR are also supported. Large
cell datasets can be aggregated through the hierarchy and
plotted with viewport-aware level of detail before polygon
geometry is constructed, with automatic raster rendering for
large display layers. Optional raster helpers provide exact
area-weighted extraction and fast cell-center sampling from
modern terra rasters.</description><link>https://github.com/r-universe/flmnh-ai/actions/runs/38821917656</link><pubDate>Thu, 15 Oct 2026 21:08:09 GMT</pubDate><r:package>globalhex</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://flmnh-ai.r-universe.dev</r:repository><r:upstream>https://github.com/flmnh-ai/globalhex</r:upstream><r:article><r:source>globalhex.Rmd</r:source><r:filename>globalhex.html</r:filename><r:title>Getting started with globalhex</r:title><r:created>2026-10-15 17:47:31</r:created><r:modified>2026-10-15 17:47:31</r:modified></r:article><r:article><r:source>plotting.Rmd</r:source><r:filename>plotting.html</r:filename><r:title>Mapping large datasets</r:title><r:created>2026-10-15 17:47:31</r:created><r:modified>2026-10-15 19:10:22</r:modified></r:article><r:article><r:source>rasters-and-polygons.Rmd</r:source><r:filename>rasters-and-polygons.html</r:filename><r:title>Rasters and polygons</r:title><r:created>2026-10-15 17:47:31</r:created><r:modified>2026-10-15 17:47:31</r:modified></r:article></item><item><title>[flmnh-ai] yersinia 0.1.0</title><author>nicolas.gauthier@ufl.edu (Nick Gauthier)</author><description>A toolkit for plague transmission modeling using
stochastic compartmental models. Implements carcass-based
transmission dynamics (Didelot et al. 2017) with spatial
structure and multi-host dynamics for epidemiological research.</description><link>https://github.com/r-universe/flmnh-ai/actions/runs/39770582923</link><pubDate>Tue, 22 Sep 2026 20:13:43 GMT</pubDate><r:package>yersinia</r:package><r:version>0.1.0</r:version><r:status>failure</r:status><r:repository>https://flmnh-ai.r-universe.dev</r:repository><r:upstream>https://github.com/flmnh-ai/yersinia</r:upstream></item><item><title>[flmnh-ai] petrographer 0.0.0.9000</title><author>nicolas.gauthier@ufl.edu (Nicolas Gauthier)</author><description>Automated petrographic analysis of thin section images
using deep learning models. Provides tools for training RF-DETR
detection and segmentation models, running predictions with
SAHI (Slicing Aided Hyper Inference), calculating morphological
properties, and analyzing results. Supports both local and HPC
training workflows with seamless R-Python integration via
reticulate.</description><link>https://github.com/r-universe/flmnh-ai/actions/runs/39106666958</link><pubDate>Tue, 21 Apr 2026 17:27:24 GMT</pubDate><r:package>petrographer</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://flmnh-ai.r-universe.dev</r:repository><r:upstream>https://github.com/flmnh-ai/petrographer</r:upstream><r:article><r:source>analyzing-predictions.qmd</r:source><r:filename>analyzing-predictions.html</r:filename><r:title>Analyzing Predictions</r:title><r:created>2026-04-21 15:53:56</r:created><r:modified>2026-04-21 15:53:56</r:modified></r:article><r:article><r:source>training-models.qmd</r:source><r:filename>training-models.html</r:filename><r:title>Training Custom Models</r:title><r:created>2025-10-14 01:04:27</r:created><r:modified>2026-04-21 15:53:56</r:modified></r:article><r:article><r:source>whole-slide-basics.qmd</r:source><r:filename>whole-slide-basics.html</r:filename><r:title>Whole-Slide Prediction Basics</r:title><r:created>2025-10-14 01:04:27</r:created><r:modified>2026-04-21 15:53:56</r:modified></r:article></item><item><title>[flmnh-ai] tidyvec 0.1.0</title><author>nicolas.gauthier@ufl.edu (Nicolas Gauthier)</author><description>A lightweight vector database for storing and querying
embeddings within the tidyverse framework. Supports multimodal
(text and image) embeddings, nearest neighbor search, and
visualization, all with a tidyverse-friendly API.</description><link>https://github.com/r-universe/flmnh-ai/actions/runs/38125613084</link><pubDate>Thu, 16 Oct 2025 00:36:01 GMT</pubDate><r:package>tidyvec</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://flmnh-ai.r-universe.dev</r:repository><r:upstream>https://github.com/flmnh-ai/tidyvec</r:upstream><r:article><r:source>getting-started.Rmd</r:source><r:filename>getting-started.html</r:filename><r:title>Getting Started with TidyVec</r:title><r:created>2025-02-25 18:49:18</r:created><r:modified>2025-10-16 00:29:21</r:modified></r:article></item></channel></rss>