{% set version = '1.1.0' %}

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

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/micompr_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/micompr/micompr_{{ version }}.tar.gz
  sha256: c99ae3e296b216a7849019d30b2a801bc0cffa413f2cf6f585a8e35acbd05d63

build:
  merge_build_host: True  # [win]
  # If this is a new build for the same version, increment the build number.
  number: 0
  # no skip
  noarch: generic

  # This is required to make R link correctly on Linux.
  rpaths:
    - lib/R/lib/
    - lib/

# Suggests: biotools, MVN (>= 5.0), deseasonalize, testthat (>= 0.8), knitr, roxygen2, devtools
requirements:
  build:
    - {{posix}}zip               # [win]

  host:
    - r-base

  run:
    - r-base

test:
  commands:
    # You can put additional test commands to be run here.
    - $R -e "library('micompr')"           # [not win]
    - "\"%R%\" -e \"library('micompr')\""  # [win]

  # You can also put a file called run_test.py, run_test.sh, or run_test.bat
  # in the recipe that will be run at test time.

  # requires:
    # Put any additional test requirements here.

about:
  home: https://github.com/fakenmc/micompr
  license: MIT
  summary: A procedure for comparing multivariate samples associated with different groups. It
    uses principal component analysis to convert multivariate observations into a set
    of linearly uncorrelated statistical measures, which are then compared using a number
    of statistical methods. The procedure is independent of the distributional properties
    of samples and automatically selects features that best explain their differences,
    avoiding manual selection of specific points or summary statistics. It is appropriate
    for comparing samples of time series, images, spectrometric measures or similar
    multivariate observations.
  license_family: MIT
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/MIT'
    - LICENSE

extra:
  recipe-maintainers:
    - katietz

# The original CRAN metadata for this package was:

# Package: micompr
# Title: Multivariate Independent Comparison of Observations
# Version: 1.1.0
# Date: 2018-03-09
# Authors@R: person("Nuno", "Fachada", email = "faken@fakenmc.com", role = c("aut", "cre"))
# Maintainer: Nuno Fachada <faken@fakenmc.com>
# Description: A procedure for comparing multivariate samples associated with different groups. It uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. The procedure is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. It is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations.
# Depends: R (>= 3.3.0)
# Imports: utils, graphics, methods, stats
# Suggests: biotools, MVN (>= 5.0), deseasonalize, testthat (>= 0.8), knitr, roxygen2, devtools
# License: MIT + file LICENSE
# URL: https://github.com/fakenmc/micompr
# BugReports: https://github.com/fakenmc/micompr/issues
# LazyData: true
# Encoding: UTF-8
# VignetteBuilder: knitr
# RoxygenNote: 6.0.1
# NeedsCompilation: no
# Packaged: 2018-03-09 16:27:30 UTC; nfachada
# Author: Nuno Fachada [aut, cre]
# Repository: CRAN
# Date/Publication: 2018-03-09 16:36:22 UTC

# See
# https://docs.conda.io/projects/conda-build for
# more information about meta.yaml
