# This file created by conda-build 3.18.11
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Sun Dec 22 23:06:18 2019
# ------------------------------------------------

package:
    name: r-arrapply
    version: '2.1'
source:
    sha256: 671c1e53b418191950cf6ddad56ef28d61dd1f367b69e6f570390354228fc763
    url:
        - https://cran.r-project.org/src/contrib/Archive/arrApply/arrApply_2.1.tar.gz
        - https://cran.r-project.org/src/contrib/arrApply_2.1.tar.gz
build:
    merge_build_host: true
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r35haf2acee_0
requirements:
    build:
        - m2-bash 4.3.042 5
        - m2-coreutils 8.25 102
        - m2-filesystem 2016.04 4
        - m2-gcc-libs 5.3.0 4
        - m2-gmp 6.1.0 3
        - m2-libbz2 1.0.6 3
        - m2-libiconv 1.14 3
        - m2-libintl 0.19.7 4
        - m2-make 4.1 5
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-sed 4.2.2 3
        - m2-zip 3.0 2
        - m2w64-binutils 2.25.1 5
        - m2w64-bzip2 1.0.6 6
        - m2w64-crt-git 5.0.0.4636.2595836 2
        - m2w64-gcc 5.3.0 6
        - m2w64-gcc-ada 5.3.0 6
        - m2w64-gcc-fortran 5.3.0 6
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gcc-objc 5.3.0 6
        - m2w64-gmp 6.1.0 2
        - m2w64-headers-git 5.0.0.4636.c0ad18a 2
        - m2w64-isl 0.16.1 2
        - m2w64-libiconv 1.14 6
        - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-make 4.1.2351.a80a8b8 2
        - m2w64-mpc 1.0.3 3
        - m2w64-mpfr 3.1.4 4
        - m2w64-pkg-config 0.29.1 2
        - m2w64-toolchain 5.3.0 7
        - m2w64-toolchain_win-64 2.4.0 0
        - m2w64-tools-git 5.0.0.4592.90b8472 2
        - m2w64-windows-default-manifest 6.4 3
        - m2w64-winpthreads-git 5.0.0.4634.697f757 2
        - m2w64-zlib 1.2.8 10
        - msys2-conda-epoch 20160418 1
    host:
        - _r-mutex 1.0.1 anacondar_1
        - libblas 3.8.0 7_h8933c1f_netlib
        - m2w64-bwidget 1.9.10 2
        - m2w64-bzip2 1.0.6 6
        - m2w64-expat 2.1.1 2
        - m2w64-fftw 3.3.4 6
        - m2w64-flac 1.3.1 3
        - m2w64-gcc-libgfortran 5.3.0 6
        - m2w64-gcc-libs 5.3.0 7
        - m2w64-gcc-libs-core 5.3.0 7
        - m2w64-gettext 0.19.7 2
        - m2w64-gmp 6.1.0 2
        - m2w64-gsl 2.1 2
        - m2w64-libiconv 1.14 6
        - m2w64-libjpeg-turbo 1.4.2 3
        - m2w64-libogg 1.3.2 3
        - m2w64-libpng 1.6.21 2
        - m2w64-libsndfile 1.0.26 2
        - m2w64-libtiff 4.0.6 2
        - m2w64-libvorbis 1.3.5 2
        - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
        - m2w64-libxml2 2.9.3 4
        - m2w64-mpfr 3.1.4 4
        - m2w64-openblas 0.2.19 1
        - m2w64-pcre 8.38 2
        - m2w64-speex 1.2rc2 3
        - m2w64-speexdsp 1.2rc3 3
        - m2w64-tcl 8.6.5 3
        - m2w64-tk 8.6.5 3
        - m2w64-tktable 2.10 5
        - m2w64-wineditline 2.101 5
        - m2w64-xz 5.2.2 2
        - m2w64-zlib 1.2.8 10
        - msys2-conda-epoch 20160418 1
        - r-base 3.5.1 hfa6e2cd_1011
        - r-rcpp 1.0.3 r35h796a38f_0
        - r-rcpparmadillo 0.9.800.3.0 r35h796a38f_0
    run:
        - libblas >=3.8.0,<4.0a0
        - m2w64-gcc-libs
        - r-base >=3.5,<3.6.0a0
        - r-rcpp >=0.12.0
        - r-rcpparmadillo
test:
    commands:
        - '"%R%" -e "library(''arrApply'')"'
about:
    home: https://CRAN.R-project.org/package=arrApply
    license: GPL-2
    license_family: GPL2
    license_file:
        - D:\bld\r-arrapply_1577056142719\_h_env/lib/R/share/licenses/GPL-2
    summary: 'High performance variant of apply() for a fixed set of functions. Considerable
        speedup is a trade-off for universality, user defined functions cannot be
        used with this package. However, 21 most currently employed functions are
        available for usage. They can be divided in three types: reducing functions
        (like mean(), sum() etc., giving a scalar when applied to a vector), mapping
        function (like normalise(), cumsum() etc., giving a vector of the same length
        as the input vector) and finally, vector reducing function (like diff() which
        produces result vector of a length different from the length of input vector).
        Optional or mandatory additional arguments required by some functions (e.g.
        norm type for norm() or normalise() functions) can be passed as named arguments
        in ''...''.'
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - conda-forge/r
        - sgsokol
