{% set version = '1.3-7' %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/RoughSets_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/RoughSets/RoughSets_{{ version }}.tar.gz
  sha256: 72425127b4e645188d6c139b7356e76d81ddc15803bbb03b4cc198a918e8d63c

build:
  merge_build_host: True  # [win]
  number: 1
  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:
    - r-base
    - r-rcpp
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-rcpp

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

about:
  home: https://github.com/janusza/RoughSets
  license: GPL-2.0-or-later
  summary: "Implementations of algorithms for data analysis based on the rough set theory (RST)
    and the fuzzy rough set theory (FRST). We not only provide implementations for the
    basic concepts of RST and FRST but also popular algorithms that derive from those
    theories. The methods included in the package can be divided into several categories
    based on their functionality: discretization, feature selection, instance selection,
    rule induction and classification based on nearest neighbors. RST was introduced
    by Zdzis\u0142aw Pawlak in 1982 as a sophisticated mathematical tool to model and
    process imprecise or incomplete information. By using the indiscernibility relation
    for objects/instances, RST does not require additional parameters to analyze the
    data. FRST is an extension of RST. The FRST combines concepts of vagueness and indiscernibility
    that are expressed with fuzzy sets (as proposed by Zadeh, in 1965) and RST."
  license_family: GPL2
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-2'

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

# Package: RoughSets
# Maintainer: Christoph Bergmeir <c.bergmeir@decsai.ugr.es>
# License: GPL (>= 2)
# Encoding: UTF-8
# Title: Data Analysis Using Rough Set and Fuzzy Rough Set Theories
# Authors@R: c(person("Andrzej", "Janusz", role = "aut", email = "janusza@mimuw.edu.pl"), person("Lala Septem", "Riza", role = "aut", email = "lala_s_riza@yahoo.com"), person("Dominik", "Slezak", role = "ctb"), person("Chris", "Cornelis", role = "ctb"), person("Francisco", "Herrera", role = "ctb"), person("Jose Manuel", "Benitez", role = "ctb"), person("Christoph", "Bergmeir", role = c("ctb", "cre"), email = "c.bergmeir@decsai.ugr.es"), person("Sebastian", "Stawicki", role = "ctb"))
# Description: Implementations of algorithms for data analysis based on the rough set theory (RST) and the fuzzy rough set theory (FRST). We not only provide implementations for the basic concepts of RST and FRST but also popular algorithms that derive from those theories. The methods included in the package can be divided into several categories based on their functionality: discretization, feature selection, instance selection, rule induction and classification based on nearest neighbors. RST was introduced by Zdzisaw Pawlak in 1982 as a sophisticated mathematical tool to model and process imprecise or incomplete information. By using the indiscernibility relation for objects/instances, RST does not require additional parameters to analyze the data. FRST is an extension of RST. The FRST combines concepts of vagueness and indiscernibility that are expressed with fuzzy sets (as proposed by Zadeh, in 1965) and RST.
# Version: 1.3-7
# URL: https://github.com/janusza/RoughSets
# Date: 2019-12-15
# Suggests: class
# LinkingTo: Rcpp
# Depends: Rcpp
# RoxygenNote: 6.1.0
# NeedsCompilation: yes
# Packaged: 2019-12-14 23:22:40 UTC; bergmeir
# Author: Andrzej Janusz [aut], Lala Septem Riza [aut], Dominik Slezak [ctb], Chris Cornelis [ctb], Francisco Herrera [ctb], Jose Manuel Benitez [ctb], Christoph Bergmeir [ctb, cre], Sebastian Stawicki [ctb]
# Repository: CRAN
# Date/Publication: 2019-12-15 06:30:19 UTC
