{% set version = "1.0.0" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/grf_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/grf/grf_{{ version }}.tar.gz
  sha256: d013eb7d84ad345651d14944ee2e6e74d1a62e7d068f91ee8e2efa8a1c8ff145

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:
    - r-base
    - r-dicekriging
    - r-matrix
    - r-rcpp >=0.12.15
    - r-rcppeigen
    - r-lmtest
    - r-sandwich >=2.4_0
  run:
    - r-base
    - {{native}}gcc-libs         # [win]
    - r-dicekriging
    - r-matrix
    - r-rcpp >=0.12.15
    - r-rcppeigen
    - r-lmtest
    - r-sandwich >=2.4_0

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

about:
  home: https://github.com/grf-labs/grf
  license: GPL-3
  summary: A pluggable package for forest-based statistical estimation and inference. GRF currently
    provides methods for non-parametric least-squares regression, quantile regression,
    and treatment effect estimation (optionally using instrumental variables).
  license_family: GPL3
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

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

# Package: grf
# Title: Generalized Random Forests
# Version: 0.10.4
# Authors@R: c( person("Julie", "Tibshirani", role = c("aut", "cre"), email = "jtibs@cs.stanford.edu"), person("Susan", "Athey", role = "aut"), person("Rina", "Friedberg", role = "ctb"), person("Vitor", "Hadad", role = "ctb"), person("David", "Hirshberg", role = "ctb"), person("Luke", "Miner", role = "ctb"), person("Erik", "Sverdrup", role = "ctb"), person("Stefan", "Wager", role = "aut"), person("Marvin", "Wright", role = "ctb") )
# BugReports: https://github.com/grf-labs/grf/issues
# Description: A pluggable package for forest-based statistical estimation and inference. GRF currently provides methods for non-parametric least-squares regression, quantile regression, and treatment effect estimation (optionally using instrumental variables).
# Depends: R (>= 3.3.0)
# License: GPL-3
# LinkingTo: Rcpp, RcppEigen
# Imports: DiceKriging, lmtest, Matrix, methods, Rcpp (>= 0.12.15), sandwich (>= 2.4-0)
# RoxygenNote: 6.1.1
# Suggests: DiagrammeR, testthat,
# SystemRequirements: GNU make
# URL: https://github.com/grf-labs/grf
# NeedsCompilation: yes
# Packaged: 2019-09-03 01:26:53 UTC; jtibshirani
# Author: Julie Tibshirani [aut, cre], Susan Athey [aut], Rina Friedberg [ctb], Vitor Hadad [ctb], David Hirshberg [ctb], Luke Miner [ctb], Erik Sverdrup [ctb], Stefan Wager [aut], Marvin Wright [ctb]
# Maintainer: Julie Tibshirani <jtibs@cs.stanford.edu>
# Repository: CRAN
# Date/Publication: 2019-09-03 12:30:02 UTC
