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meta.yaml
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{% set version = '2.6.1' %}
{% set posix = 'm2-' if win else '' %}
{% set native = 'm2w64-' if win else '' %}
package:
name: r-rann
version: {{ version|replace("-", "_") }}
source:
url:
- {{ cran_mirror }}/src/contrib/RANN_{{ version }}.tar.gz
- {{ cran_mirror }}/src/contrib/Archive/RANN/RANN_{{ version }}.tar.gz
sha256: b299c3dfb7be17aa41e66eff5674fddd2992fb6dd3b10bc59ffbf0c401697182
build:
merge_build_host: True # [win]
number: 4
rpaths:
- lib/R/lib/
- lib/
requirements:
build:
- cross-r-base {{ r_base }} # [build_platform != target_platform]
- {{ 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
run:
- r-base
- {{ native }}gcc-libs # [win]
test:
commands:
- $R -e "library('RANN')" # [not win]
- "\"%R%\" -e \"library('RANN')\"" # [win]
about:
home: https://github.com/jefferis/RANN
license: GPL-3.0-or-later
summary: Finds the k nearest neighbours for every point in a given dataset in O(N log N) time
using Arya and Mount's ANN library (v1.1.3). There is support for approximate as
well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The
distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1'
for the same functionality using the L1 (Manhattan, taxicab) metric.
license_family: GPL3
license_file:
- {{ environ["PREFIX"] }}/lib/R/share/licenses/GPL-3
extra:
recipe-maintainers:
- conda-forge/r
# Package: RANN
# Title: Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric
# Author: Sunil Arya and David Mount (for ANN), Samuel E. Kemp, Gregory Jefferis
# Maintainer: Gregory Jefferis <jefferis@gmail.com>
# Copyright: ANN library is copyright University of Maryland and Sunil Arya and David Mount. See file COPYRIGHT for details.
# Description: Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' for the same functionality using the L1 (Manhattan, taxicab) metric.
# URL: https://github.com/jefferis/RANN
# BugReports: https://github.com/jefferis/RANN/issues
# Encoding: UTF-8
# License: GPL (>= 3)
# Suggests: testthat
# Version: 2.6.1
# RoxygenNote: 6.1.1
# NeedsCompilation: yes
# Packaged: 2019-01-08 19:24:15 UTC; jefferis
# Repository: CRAN
# Date/Publication: 2019-01-08 20:00:04 UTC