{% set version = "0.3.0" %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/fable_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/fable/fable_{{ version }}.tar.gz
  sha256: 2bb51f519ec60d4bb246168255832fbd213d1e0caed8c241b110e3d3e8eb426c

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-rcpp >=0.11.0
    - r-dplyr >=0.8.0
    - r-fabletools
    - r-rlang >=0.2.0
    - r-tidyr
    - r-tsibble >=0.8.0
  run:
    - r-base
    - {{ native }}gcc-libs         # [win]
    - r-rcpp >=0.11.0
    - r-dplyr >=0.8.0
    - r-fabletools
    - r-rlang >=0.2.0
    - r-tidyr
    - r-tsibble >=0.8.0

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

about:
  home: https://fable.tidyverts.org
  license: GPL-3
  summary: Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential  smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which
    provides the tools to evaluate, visualise, and combine models  in a workflow consistent with the tidyverse.
  license_family: GPL3
  license_file: {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3

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

# Package: fable
# Title: Forecasting Models for Tidy Time Series
# Version: 0.1.0
# Description: Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential  smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models  in a workflow consistent with the tidyverse.
# Authors@R:  c(person(given = "Mitchell", family = "O'Hara-Wild", email = "mail@mitchelloharawild.com", role = c("aut", "cre")), person(given = "Rob", family = "Hyndman", role = "aut"), person(given = "Earo", family = "Wang", role = "aut"), person(given = "Gabriel", family = "Caceres", role = "ctb", comment = "NNETAR implementation"))
# License: GPL-3
# URL: https://fable.tidyverts.org
# BugReports: https://github.com/tidyverts/fable/issues
# Depends: R (>= 3.4.0), fabletools
# Imports: Rcpp (>= 0.11.0), rlang (>= 0.2.0), stats, dplyr (>= 0.8.0), tsibble (>= 0.8.0), tidyr
# Suggests: covr, feasts, forecast, knitr, nnet, rmarkdown, spelling, testthat, tsibbledata
# LinkingTo: Rcpp (>= 0.11.0)
# VignetteBuilder: knitr
# ByteCompile: true
# Encoding: UTF-8
# Language: en-GB
# LazyData: true
# RoxygenNote: 6.1.1
# NeedsCompilation: yes
# Packaged: 2019-09-16 09:21:55 UTC; mitchell
# Author: Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Gabriel Caceres [ctb] (NNETAR implementation)
# Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
# Repository: CRAN
# Date/Publication: 2019-09-23 15:10:06 UTC
