{% set version = "1.2.2" %}
{% set name = "SparseArray" %}
{% set bioc = "3.18" %}

package:
  name: 'bioconductor-{{ name|lower }}'
  version: '{{ version }}'
source:
  url:
    - 'https://bioconductor.org/packages/{{ bioc }}/bioc/src/contrib/{{ name }}_{{ version }}.tar.gz'
    - 'https://bioconductor.org/packages/{{ bioc }}/bioc/src/contrib/Archive/{{ name }}/{{ name }}_{{ version }}.tar.gz'
    - 'https://bioarchive.galaxyproject.org/{{ name }}_{{ version }}.tar.gz'
    - 'https://depot.galaxyproject.org/software/bioconductor-{{ name|lower }}/bioconductor-{{ name|lower }}_{{ version }}_src_all.tar.gz'
  md5: a73b2e316ce8135de81af01a9a9610ec
build:
  number: 0
  rpaths:
    - lib/R/lib/
    - lib/
  run_exports: '{{ pin_subpackage("bioconductor-sparsearray", max_pin="x") }}'
# Suggests: DelayedArray, testthat, knitr, rmarkdown, BiocStyle
requirements:
  host:
    - 'bioconductor-biocgenerics >=0.48.0,<0.49.0'
    - 'bioconductor-iranges >=2.36.0,<2.37.0'
    - 'bioconductor-matrixgenerics >=1.14.0,<1.15.0'
    - 'bioconductor-s4arrays >=1.2.0,<1.3.0'
    - 'bioconductor-s4vectors >=0.40.0,<0.41.0'
    - 'bioconductor-xvector >=0.42.0,<0.43.0'
    - r-base
    - r-matrix
    - r-matrixstats
    - libblas
    - liblapack
  run:
    - 'bioconductor-biocgenerics >=0.48.0,<0.49.0'
    - 'bioconductor-iranges >=2.36.0,<2.37.0'
    - 'bioconductor-matrixgenerics >=1.14.0,<1.15.0'
    - 'bioconductor-s4arrays >=1.2.0,<1.3.0'
    - 'bioconductor-s4vectors >=0.40.0,<0.41.0'
    - 'bioconductor-xvector >=0.42.0,<0.43.0'
    - r-base
    - r-matrix
    - r-matrixstats
  build:
    - {{ compiler('c') }}
    - make
test:
  commands:
    - '$R -e "library(''{{ name }}'')"'
about:
  home: 'https://bioconductor.org/packages/{{ bioc }}/bioc/html/{{ name }}.html'
  license: Artistic-2.0
  summary: 'Efficient in-memory representation of multidimensional sparse arrays'
  description: 'The SparseArray package is an infrastructure package that provides an array-like container for efficient in-memory representation of multidimensional sparse data in R. The package defines the SparseArray virtual class and two concrete subclasses: COO_SparseArray and SVT_SparseArray. Each subclass uses its own internal representation of the nonzero multidimensional data, the "COO layout" and the "SVT layout", respectively. SVT_SparseArray objects mimic as much as possible the behavior of ordinary matrix and array objects in base R. In particular, they suppport most of the "standard matrix and array API" defined in base R and in the matrixStats package from CRAN.'

