# automatically generated by g-sorcery
# please do not edit this file

EAPI=8

REALNAME="${PN}"
LITERALNAME="${PN}"
REALVERSION="${PV}"
DIGEST_SOURCES="yes"
PYTHON_COMPAT=( python{3_11,3_12,3_13,3_14} )
DISTUTILS_USE_PEP517=standalone

inherit python-r1 gs-pypi

DESCRIPTION="Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework"

HOMEPAGE="https://github.com/jameschapman19/cca_zoo"
LICENSE="MIT"
SRC_URI="https://files.pythonhosted.org/packages/source/${REALNAME::1}/${REALNAME}/${REALNAME//-/_}-${REALVERSION}.tar.gz"
SOURCEFILE="${REALNAME//-/_}-${REALVERSION}.tar.gz"
RESTRICT="test"

SLOT="0"
KEYWORDS="~amd64 ~x86"

IUSE="deep probabilistic"
DEPENDENCIES="<dev-python/scikit-learn-2.0.0[${PYTHON_USEDEP}]
	dev-python/tensorly[${PYTHON_USEDEP}]
	dev-python/tqdm[${PYTHON_USEDEP}]
	probabilistic? ( dev-python/jax[${PYTHON_USEDEP}] )
	probabilistic? ( dev-python/numpyro[${PYTHON_USEDEP}] )
	probabilistic? ( dev-python/arviz[${PYTHON_USEDEP}] )
	probabilistic? ( dev-python/funsor[${PYTHON_USEDEP}] )
	deep? ( dev-python/torch[${PYTHON_USEDEP}] )
	deep? ( dev-python/torch[${PYTHON_USEDEP}] )
	deep? ( dev-python/lightning[${PYTHON_USEDEP}] )"
BDEPEND="${DEPENDENCIES}"
RDEPEND="${DEPENDENCIES}"