{% set version = '2.3.0' %}

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

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

source:
  url:
    - {{ cran_mirror }}/src/contrib/seminr_{{ version }}.tar.gz
    - {{ cran_mirror }}/src/contrib/Archive/seminr/seminr_{{ version }}.tar.gz
  sha256: 4a23c9149f814dc5ce9a1b81b157876bfe695618e5a45a7ae9ce97467713f35c

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/

requirements:
  build:
    - {{ posix }}zip               # [win]

  host:
    - r-base
    - r-diagrammer >=1.0.6
    - r-diagrammersvg >=0.1
    - r-glue
    - r-knitr
    - r-lavaan
    - r-rmarkdown
    - r-testthat
    - r-webp

  run:
    - r-base
    - r-diagrammer >=1.0.6
    - r-diagrammersvg >=0.1
    - r-glue
    - r-knitr
    - r-lavaan
    - r-rmarkdown
    - r-testthat
    - r-webp

test:
  commands:
    # You can put additional test commands to be run here.
    - $R -e "library('seminr')"           # [not win]
    - "\"%R%\" -e \"library('seminr')\""  # [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://CRAN.R-project.org/package=seminr
  license: GPL-3
  summary: A powerful, easy to syntax for specifying and estimating complex Structural Equation
    Models. Models can be estimated using Partial Least Squares Path Modeling or Covariance-Based
    Structural Equation Modeling or covariance based Confirmatory Factor Analysis. Methods
    described in Ray, Danks, and Valdez (2021).
  license_family: GPL3
  license_file:
    - '{{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3'

extra:
  recipe-maintainers:
    - katietz

# The original CRAN metadata for this package was:

# Package: seminr
# Type: Package
# Title: Building and Estimating Structural Equation Models
# Version: 2.3.0
# Date: 2022-01-04
# Authors@R: c(person("Soumya", "Ray", email = "soumya.ray@gmail.com", role = c("aut", "ths")), person("Nicholas Patrick", "Danks", email = "nicholasdanks@hotmail.com", role = c("aut","cre")), person("Andre", "Calero Valdez", role = "aut", email = "andrecalerovaldez@gmail.com"), person("Juan Manuel Velasquez", "Estrada", role = "ctb"), person("James", "Uanhoro", role = "ctb", email = "James.uanhoro@gmail.com"), person("Johannes", "Nakayama", role = "ctb", email = "johannes.nakayama@rwth-aachen.de"), person("Lilian", "Koyan", role = "ctb", email = "lilian.kojan@rwth-aachen.de"), person("Laura", "Burbach", role = "ctb", email = "laura.burbach@rwth-aachen.de"), person("Arturo Heynar", "Cano Bejar", role = "ctb", email = "arturocano997@gmail.com"), person("Susanne", "Adler", role = "ctb", email = "susanne.adler@ovgu.de") )
# Description: A powerful, easy to syntax for specifying and estimating complex Structural Equation Models. Models can be estimated using Partial Least Squares Path Modeling or Covariance-Based Structural Equation Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021).
# Imports: parallel, lavaan, glue, knitr, testthat, rmarkdown, DiagrammeR (>= 1.0.6), DiagrammeRsvg (>= 0.1), webp
# License: GPL-3
# Depends: R (>= 3.5.0)
# LazyData: TRUE
# RoxygenNote: 7.1.2
# Enhances: rsvg (>= 2.1), semPlot, vdiffr
# VignetteBuilder: knitr
# Encoding: UTF-8
# NeedsCompilation: no
# Packaged: 2022-01-04 04:46:34 UTC; danksnicholas
# Author: Soumya Ray [aut, ths], Nicholas Patrick Danks [aut, cre], Andre Calero Valdez [aut], Juan Manuel Velasquez Estrada [ctb], James Uanhoro [ctb], Johannes Nakayama [ctb], Lilian Koyan [ctb], Laura Burbach [ctb], Arturo Heynar Cano Bejar [ctb], Susanne Adler [ctb]
# Maintainer: Nicholas Patrick Danks <nicholasdanks@hotmail.com>
# Repository: CRAN
# Date/Publication: 2022-01-04 12:10:02 UTC

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