R Observatory: Metrics for FINN version 0.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

FINN

0.1.0Package record

Forest Informed Neural Networks

0packages depend

953downloads / year

22.4%test coverage

13/13flavors OK

Overview

About

Maintained by Yannek KäberCRAN page ↗GitHub ↗Website ↗Issues ↗

A hybrid dynamic forest (gap) model (FINN) that can be configured as a fully mechanistic, process-based model, like classic forest gap models, or with its demographic processes (growth, mortality, regeneration) replaced by deep neural networks (DNNs), or any combination of the two. Provides functions to define a model and its mechanistic or empirical components, calibrate it to forest inventory data, and interpret the calibrated processes. FINN is implemented with the 'torch' package, which supplies GPU support and the automatic differentiation used to calibrate the model by stochastic gradient descent; no knowledge of 'torch' is required. The hybrid modeling approach is described in Pichler and Käber (2026) doi:10.1111/2041-210x.70347.

Changes in 0.1.0

First public release.

FINN is a differentiable forest gap model: a cohort-based dynamic vegetation

model whose demographic processes (competition, growth, mortality, regeneration)

can each be a mechanistic function, a neural network, or a mixture of the two,

all calibrated end-to-end by gradient descent.

Highlights of the current interface:

finn() assembles a model from one process per demographic component, each built with createProcess() (mechanistic) or createHybrid() (neural network).
simulateForest() runs a model forward; fit() calibrates one to data and predict() scores it, returning patch- and site-level results.
Per-response likelihoods: Gaussian ("mse"/"gaussian"), Poisson, negative binomial, and a "binomial" likelihood for mortality that takes a closed-cohort count pair (n_at_risk, n_died).

Show all changes in 0.1.0Hide the rest of the changes in 0.1.0

weights = "auto" (the default in fit()) scales each loss by its intercept-only baseline, so the six responses are commensurable and every term reads as a fraction of its own null deviance.
Data helpers makeObsData(), resolveSiteIDs() and makeInitCohorts() turn a raw tree list into FINN's input tables.
Model interpretation with ALE(), summary(), feature_importance() and conditionalEffects().

See the vignettes for a guided tour: *Introduction to FINN*, *Plausible

succession from a handful of species*, *Preparing your data for FINN*, *Fitting

FINN to forest inventory data*, and *Mortality*.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("FINN", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("FINNverse/FINN")

Development version from FINNverse/FINN. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-finn

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-FINN

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-FINN

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 5.5 min · r-oldrel-macos-x86_64

Status changes

OK13 OKNow
OK8 OK2026-08-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.0

READMEYes · 353 wordsVignettesYes · 5 · staticNEWSYes · 67% structured · mentions 0.1.0Citation fileNoWebsiteYes · pkgdown

Help pages: 40 (6 internal)includes a package overview page
Examples that run: 100%12 run in a plain check (3 of them under a condition)
Exported functions with examples: 33%
Documented parameters: 99%
Return-value docs: 100%
Help pages citing references: 8%

Vignettes (5)

How these are measured

Downloads

953

CRAN downloads in the past year

Rank #11,399 · ~3/day · ~79/mo

Releases R versions

Daily download trend is not available in this view yet.

26930 days

95390 days

9531 year

Compare downloads with other packages →

Also on41 r2u1 autocran

How downloads are counted

Repository

finnverse/finn ↗Organization: FINNverse

4Stars

1Forks

9Open issues

0Open PRs

0Releases

706Commits

2Commit identities

License file reads as GPL-3.0 · 706 commits · Last activity 2026-09-22 · +33.3% stars, 30d · Default branch at 0.2.0, ahead of CRAN 0.1.0 (checked 2026-10-25)

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 367
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2026-08-10 · 32026-10-21 · 4

How these are measured

PracticesBeta

11 development-tooling and community-health practices detected across 7 families in the upstream repository

Checks run against github.com/finnverse/finn on 2026-10-25.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (1)

Contributing guide

Docs source (3)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-08-11

pkgdown site last built 2026-08-11

Reproducibility and dev environment (1)

data-raw/

Show all practicesHide 3 practices

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

Git structural (1)

.gitattributes

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Claude Codefirst seen 2026-06-22
Seen in the repository: .claude, .claude/skills, CLAUDE.md
Named in .Rbuildignore: .claude
Named in .gitignore: .claude, CLAUDE.local.md

From outside contributors

Claude Code
Pull requests: 2 from outside contributors, first on 2026-09-08

How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

12 external dependencies (excludes base and recommended)

Installing FINN adds 32 packages (16 with compiled code, 25 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, torch 1.9 MB.

Depends (1)

R >= 4.1.0

Imports (10)

abind clistatsutilsdata.table coro Rcpp torch ggplot2 glue

LinkingTo (1)

Rcpp

Suggests (3)

testthat knitr rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (2)

Yannek Käber

Author, Maintainer since 0.1.0 (2026)

Maximilian Pichler

Author

Releases (1)

0.1.0Latest
record
2026-08-09 · current release
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-08-09
Total releases: 1 / 1 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.1.0
Download size: 3.7 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("FINN")

Format

Käber, Y., & Pichler, M. (2026). FINN: Forest Informed Neural Networks (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.FINN

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for FINN version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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