# -*- coding: utf-8; mode: tcl; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- vim:fenc=utf-8:ft=tcl:et:sw=4:ts=4:sts=4 PortSystem 1.0 PortGroup python 1.0 PortGroup github 1.0 github.setup pymc-devs pymc 5.18.0 v github.tarball_from archive revision 0 name py-pymc supported_archs noarch platforms {darwin any} license Apache-2 maintainers {reneeotten @reneeotten} openmaintainer description Probabilistic Programming in Python: Bayesian Modeling and \ Probabilistic Machine Learning with Aesara long_description PyMC (formerly PyMC3) is a Python package for Bayesian \ statistical modeling focusing on advanced Markov chain \ Monte Carlo (MCMC) and variational inference (VI) algorithms. \ Its flexibility and extensibility make it applicable to a \ large suite of problems. checksums rmd160 4e78503885eadaa084ecf31c8825610d3c0ef1ba \ sha256 f9b1e0f9e9a368a24463fe2bf010a4a17dc073852a75d83a809f7f3dfaeb26cf \ size 6869214 python.versions 310 311 312 if {${name} ne ${subport}} { conflicts py${python.version}-pymc3 depends_build-append \ port:py${python.version}-versioneer depends_lib-append \ port:py${python.version}-arviz \ port:py${python.version}-cachetools \ port:py${python.version}-cloudpickle \ port:py${python.version}-fastprogress \ port:py${python.version}-numpy \ port:py${python.version}-pandas \ port:py${python.version}-pytensor \ port:py${python.version}-scipy \ port:py${python.version}-typing_extensions if {${python.version} < 311} { depends_lib-append \ port:py${python.version}-tomli } } github.livecheck.regex {([0-9.]+)}