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add R volumodel rangebuilder and modeva
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ocefpaf committed Jul 10, 2024
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52 changes: 52 additions & 0 deletions recipes/r-modeva/meta.yaml
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{% set version = "3.17" %}
{% set name = "modeva" %}

package:
name: r-{{ name }}
version: '{{ version }}'

source:
url: https://cran.r-project.org/src/contrib/modEvA_{{ version }}.tar.gz
sha256: f27ba3da0bbbb61d57e188cbfdf1804d412b8ba256ddfa5fef7da261e5d8f3b0

build:
number: 0
noarch: generic
merge_build_host: true # [win]
script: R CMD INSTALL --build .
rpaths:
- lib/R/lib/
- lib/

requirements:
host:
- r-base
- r-terra >1.5-50
run:
- r-base
- r-terra >1.5-50

test:
commands:
- $R -e "library('modEvA')" # [not win]
- "\"%R%\" -e \"library('modEvA')\"" # [win]

about:
home: http://modeva.r-forge.r-project.org/
summary: |
Analyses species distribution models and evaluates their performance.
It includes functions for variation partitioning, extracting variable importance,
computing several metrics of model discrimination and calibration performance,
optimizing prediction thresholds based on a number of criteria,
performing multivariate environmental similarity surface (MESS) analysis,
and displaying various analytical plots.
Initially described in Barbosa et al. (2013) <doi:10.1111/ddi.12100>.
license: GPL-3.0-only
license_family: GPL3
license_file:
- '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

extra:
recipe-maintainers:
- conda-forge/r
- ocefpaf
70 changes: 70 additions & 0 deletions recipes/r-rangebuilder/meta.yaml
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{% set version = "2.1" %}
{% set name = "rangebuilder" %}
{% set posix = "m2-" if win else "" %}
{% set native = "m2w64-" if win else "" %}

package:
name: r-{{ name }}
version: '{{ version }}'

source:
url: https://cran.r-project.org/src/contrib/rangeBuilder_{{ version }}.tar.gz
sha256: fceee76e8ee2841261a49b4a36c8966224913def895acd3a15d42dee6acd02e5

build:
number: 0
merge_build_host: true # [win]
script: R CMD INSTALL --build .
rpaths:
- lib/R/lib/
- lib/

requirements:
build:
- cross-r-base {{ r_base }} # [build_platform != target_platform]
- autoconf # [not win]
- "{{ compiler('c') }}" # [not win]
- "{{ stdlib('c') }}" # [not win]
- "{{ compiler('m2w64_c') }}" # [win]
- "{{ stdlib('m2w64_c') }}" # [win]
- "{{ compiler('cxx') }}" # [not win]
- "{{ compiler('m2w64_cxx') }}" # [win]
- posix # [win]
host:
- r-base
- r-Rcpp >=0.12.9
- r-alphahull >=2.5
- r-pbapply
- r-rnaturalearth
- r-sf
- r-stringi
- r-terra
- r-units
run:
- r-base
- r-Rcpp >=0.12.9
- r-alphahull >=2.5
- r-pbapply
- r-rnaturalearth
- r-sf
- r-stringi
- r-terra
- r-units

test:
commands:
- $R -e "library('rangeBuilder')" # [not win]
- "\"%R%\" -e \"library('rangeBuilder')\"" # [win]

about:
home: https://github.com/ptitle/rangeBuilder
summary: Provides tools for filtering occurrence records, generating alpha-hull-derived range polygons and mapping species distributions.
license: GPL-3.0-or-later
license_family: GPL3
license_file:
- {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3

extra:
recipe-maintainers:
- conda-forge/r
- ocefpaf
64 changes: 64 additions & 0 deletions recipes/r-volumodel/meta.yaml
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{% set version = "0.2.1" %}
{% set name = "volumodel" %}

package:
name: r-{{ name }}
version: '{{ version }}'

source:
url:
- https://cran.r-project.org/src/contrib/voluModel_{{ version }}.tar.gz
- https://cran.r-project.org/src/contrib/Archive/voluModel/voluModel_{{ version }}.tar.gz
sha256: 8fd558baa1d8ec5c31710693ee9576100cc4beb0cbd5b30750913f2df57a78ce

build:
number: 0
noarch: generic
merge_build_host: true # [win]
script: R CMD INSTALL --build .
rpaths:
- lib/R/lib/
- lib/

requirements:
host:
- r-base
- r-dplyr
- r-fields
- r-ggplot2
- r-ggtext
- r-modeva
- r-rangebuilder >=2.0
- r-sf
- r-terra
- r-viridisLite
run:
- r-base
- r-dplyr
- r-fields
- r-ggplot2
- r-ggtext
- r-modeva
- r-rangebuilder >=2.0
- r-sf
- r-terra
- r-viridisLite

test:
commands:
- $R -e "library('voluModel')" # [not win]
- "\"%R%\" -e \"library('voluModel')\"" # [win]

about:
home: https://hannahlowens.github.io/voluModel/
summary: Facilitates modeling species' ecological niches and geographic distributions based on occurrences and environments that have a vertical as well as horizontal component, and projecting models into three-dimensional geographic space. Working in three dimensions is useful in an aquatic context when the organisms one wishes to model can be found across a wide range of depths in the water column. The package also contains functions to automatically generate marine training model training regions using machine learning, and interpolate and smooth patchily sampled environmental rasters using
thin plate splines. Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) <doi:10.1038/ncomms11484>. Nychka D, Furrer R, Paige J, Sain S (2021) <doi:10.5065/D6W957CT>. Pateiro-Lopez B, Rodriguez-Casal A (2022) <https://CRAN.R-project.org/package=alphahull>.
license: GPL-3.0-only
license_family: GPL3
license_file:
- '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

extra:
recipe-maintainers:
- conda-forge/r
- ocefpaf

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