{% set version = '0.73.1' %}

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

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

source:
  fn: lsa_{{ version }}.tar.gz
  url:
    - https://cran.r-project.org/src/contrib/lsa_{{ version }}.tar.gz
    - https://cran.r-project.org/src/contrib/Archive/lsa/lsa_{{ version }}.tar.gz

  sha256: e585da8992fa6d8f86067bdaf7b1456b9b5eb4695327faec8521e609c5d0c8a9

build:
  number: 0
  skip: true  # [win32]

  rpaths:
    - lib/R/lib/
    - lib/

requirements:
  build:
    - r-base
    - r-snowballc

  run:
    - r-base
    - r-snowballc

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

about:
  home: https://CRAN.R-project.org/package=lsa
  license: GPL (>= 2)
  summary: The basic idea of latent semantic analysis (LSA) is,  that text do have a higher order
    (=latent semantic) structure which,  however, is obscured by word usage (e.g. through
    the use of synonyms  or polysemy). By using conceptual indices that are derived
    statistically  via a truncated singular value decomposition (a two-mode factor analysis)  over
    a given document-term matrix, this variability problem can be overcome.
  license_family: GPL3
  license_file: '{{ environ["PREFIX"] }}\/lib\/R\/share\/licenses\/GPL-3'  # [unix]
  license_file: '{{ environ["PREFIX"] }}\R\share\licenses\GPL-3'  # [win]
extra:
   recipe-maintainers:
    - MathiasHaudgaard
    - FrodePedersen
    - ArneKr
    - johanneskoester
    - bgruening
    - daler
    - jdblischak
