# This file created by conda-build 2.1.18
# meta.yaml template originally from:
# /recipe_root, last modified Fri Dec 29 05:24:31 2017
# ------------------------------------------------

package:
    name: mkl_random
    version: 1.0.1
source:
    sha256: 686b3129f8a5aab079bc03c02a41019994e67d32e6df535bd3b87a186e5f144f
    url: https://github.com/IntelPython/mkl_random/archive/v1.0.1.tar.gz
build:
    noarch: ''
    noarch_python: false
    number: '0'
    string: py35_0
requirements:
    build:
        - xz 5.2.3 0
        - ca-certificates 2017.11.5 0
        - setuptools 38.2.4 py35_0
        - openssl 1.0.2n 0
        - readline 7.0 0
        - openblas 0.2.20 6
        - cython 0.27.3 py35_0
        - mkl-include 2018.0.1 hc7b2577_4
        - zlib 1.2.11 0
        - tk 8.6.7 0
        - certifi 2017.11.5 py35_0
        - numpy 1.11.3 py35_blas_openblas_203
        - blas 1.1 openblas
        - libgfortran 3.0.0 1
        - mkl 2018.0.1 h19d6760_4
        - python 3.5.4 3
        - ncurses 5.9 10
        - sqlite 3.20.1 2
        - mkl-devel 2018.0.1 hf16a5b4_4
        - intel-openmp 2018.0.0 hc7b2577_8
        - toolchain 2.1.2 0
    run:
        - python
        - mkl
        - numpy >=1.11
test:
    commands:
        - nosetests -v mkl_random
    imports:
        - mkl_random
        - mkl_random.mklrand
    requires:
        - nose
about:
    description: NumPy-based implementation of random number generation sampling using
        Intel (R) Math Kernel Library, mirroring numpy.random, but exposing all choices
        of sampling algorithms available in MKL.
    home: http://github.com/IntelPython/mkl_random
    license: BSD 3-Clause
    license_file: LICENSE.txt
    summary: Intel (R) MKL-powered package for sampling from common probability distributions
        into NumPy arrays.
extra:
    final: true
    recipe-maintainers:
        - oleksandr-pavlyk
