{% set version = '2.62' %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

package:
  name: r-bdgraph
  version: {{ version|replace("-", "_") }}

source:
  url:
    - {{ cran_mirror }}/src/contrib/BDgraph_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/BDgraph/BDgraph_{{ version }}.tar.gz
  sha256: 7e5de4406f4a7873bf948852291d2851a2ab312288467687dd5c0392b2723bac

build:
  merge_build_host: True  # [win]
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/

requirements:
  build:
    - {{ compiler('c') }}              # [not win]
    - {{ compiler('m2w64_c') }}        # [win]
    - {{ compiler('cxx') }}            # [not win]
    - {{ compiler('m2w64_cxx') }}      # [win]
    - {{posix}}filesystem        # [win]
    - {{posix}}make
    - {{posix}}sed               # [win]
    - {{posix}}coreutils         # [win]
    - {{posix}}zip               # [win]
  host:
    - libopenblas
    - llvm-openmp                # [osx]
    - _openmp_mutex              # [linux]
    - r-base
    - r-igraph
  run:
    - libopenblas
    - llvm-openmp                # [osx]
    - _openmp_mutex              # [linux]
    - r-base
    - {{native}}gcc-libs         # [win]
    - r-igraph

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

about:
  home: https://www.uva.nl/profile/a.mohammadi
  license: GPL-2
  summary: Statistical tools for Bayesian structure learning in undirected graphical models for
    continuous, discrete, and mixed data. The package is implemented the recent improvements
    in the Bayesian graphical models literature, including Mohammadi and Wit (2015)
    <doi:10.1214/14-BA889>, Mohammadi and Wit (2019) <doi:10.18637/jss.v089.i03>.
  license_family: GPL2
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2'

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

# Package: BDgraph
# Version: 2.62
# Date: 2019-12-05
# Title: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
# Author: Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>, Ernst Wit [aut] <https://orcid.org/0000-0002-3671-9610>, Adrian Dobra [ctb]
# Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>
# URL: https://www.uva.nl/profile/a.mohammadi
# Description: Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi and Wit (2019) <doi:10.18637/jss.v089.i03>.
# Imports: igraph
# License: GPL (>= 2)
# Repository: CRAN
# NeedsCompilation: yes
# Packaged: 2019-12-05 17:16:34 UTC; reza
# Date/Publication: 2019-12-05 18:40:10 UTC
