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Software

An official USGS software project is code reviewed and approved at the bureau-level for distribution.

Filter Total Items: 921

D-Claw - A library for the simulation of granular-fluid flows, v1.0.0 D-Claw - A library for the simulation of granular-fluid flows, v1.0.0

D-Claw is a software library for the simulation of dense granular flows over spatially variable topography. D-Claw builds on clawpack, is written in Fortran, and has a python wrapper. The code is hosted on code.usgs.gov and mirrored on github. D-Claw is supported on Linux/Unix only.

Code for the analysis of fish deformity, erosion, lesion, tumor, and parasite anomalies (DELT) in the Chesapeake Bay Watershed, USA Code for the analysis of fish deformity, erosion, lesion, tumor, and parasite anomalies (DELT) in the Chesapeake Bay Watershed, USA

This repository provides the R scripts and stan files to fit hierarchical logistic regression models, using a regularized horseshoe prior on regression coefficients, to examine spatial drivers of DELT occurrence in fishes in the Chesapeake Bay Watershed, USA.

wildcat 1.1.0 wildcat 1.1.0

This release allows users to select the CRS of exported files, and to specify alternate configuration files. The release also updates wildcat’s backend for compatibility with pfdf 3+. Documentation: https://ghsc.code-pages.usgs.gov/lhp/wildcat/ Release Notes: https://ghsc.code-pages.usgs.gov/lhp/wildcat/resources/release-notes/1.1.0.html

Landscape transcriptomics identify Landscape transcriptomics identify

Rapid heating events, such as heatwaves, are becoming more frequent and intense as a result of climate change. Importantly, such extreme weather events can be more important drivers of extirpation and selection than changes in annual or seasonal averages and they pose a particularly large threat to poikilothermic organisms. In this study, we evaluate the thermal stress response of a...

DeepFaune New England DeepFaune New England

This repository contains code for training and running the DeepFaune New England (DFNE) model for species classification in trail camera imagery. This model is a re-trained version of the DeepFaune model for classifying European species in trial cameras, fine-tuned to classify taxa from northeastern North America. The DFNE model takes as input cropped images of each animal, which can be...
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