{% set version = "0.1.5" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/proxyC_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/proxyC/proxyC_{{ version }}.tar.gz
  sha256: e63dc4f20d16c27404cc5aad5b6f0478c7b1e347cc25988735156ad205612b95

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-matrix >=1.2
    - r-rcpp >=0.12.12
    - r-rcpparmadillo >=0.7.600.1.0
    - r-rcppparallel
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-matrix >=1.2
    - r-rcpp >=0.12.12
    - r-rcpparmadillo >=0.7.600.1.0
    - r-rcppparallel

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

about:
  home: https://CRAN.R-project.org/package=proxyC
  license: GPL-3
  summary: ' Computes proximity between rows or columns of large matrices efficiently in C++.
    Functions are optimised for large sparse matrices using the Armadillo and Intel
    TBB libraries. Among several built-in similarity/distance measures, computation
    of correlation, cosine similarity and Euclidean distance is particularly fast. '
  license_family: GPL3
  license_file: '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

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

# Package: proxyC
# Type: Package
# Title: Computes Proximity in Large Sparse Matrices
# Version: 0.1.4
# Authors@R: c( person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = c("cre", "aut", "cph"),  comment = c(ORCID = "0000-0001-6519-5265")), person("Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-3641-729X")) )
# Description:  Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.
# Encoding: UTF-8
# LazyData: true
# LinkingTo: Rcpp, RcppParallel, RcppArmadillo (>= 0.7.600.1.0)
# BugReports: https://github.com/koheiw/proxyC/issues
# SystemRequirements: C++11
# License: GPL-3
# Depends: R (>= 3.1.0), methods
# Imports: Matrix (>= 1.2), Rcpp (>= 0.12.12), RcppParallel
# Suggests: testthat, proxy
# RoxygenNote: 6.1.1
# NeedsCompilation: yes
# Packaged: 2019-06-04 22:10:35 UTC; kohei
# Author: Kohei Watanabe [cre, aut, cph] (<https://orcid.org/0000-0001-6519-5265>), Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>)
# Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>
# Repository: CRAN
# Date/Publication: 2019-06-04 22:40:03 UTC
