git: 204bf4f79bb3 - main - math/py-umap-learn: New port: Uniform Manifold Approximation and Projection
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Date: Sat, 06 Aug 2022 17:29:42 UTC
The branch main has been updated by yuri: URL: https://cgit.FreeBSD.org/ports/commit/?id=204bf4f79bb3dae6cf25004bcdde6a74d84fafd3 commit 204bf4f79bb3dae6cf25004bcdde6a74d84fafd3 Author: Yuri Victorovich <yuri@FreeBSD.org> AuthorDate: 2022-08-06 17:10:03 +0000 Commit: Yuri Victorovich <yuri@FreeBSD.org> CommitDate: 2022-08-06 17:25:33 +0000 math/py-umap-learn: New port: Uniform Manifold Approximation and Projection --- math/Makefile | 1 + math/py-umap-learn/Makefile | 24 ++++++++++++++++++++++++ math/py-umap-learn/distinfo | 3 +++ math/py-umap-learn/pkg-descr | 9 +++++++++ 4 files changed, 37 insertions(+) diff --git a/math/Makefile b/math/Makefile index b81548a27218..39f6fafd12bd 100644 --- a/math/Makefile +++ b/math/Makefile @@ -984,6 +984,7 @@ SUBDIR += py-timple SUBDIR += py-topologic SUBDIR += py-triangle + SUBDIR += py-umap-learn SUBDIR += py-uncertainties SUBDIR += py-unyt SUBDIR += py-vincenty diff --git a/math/py-umap-learn/Makefile b/math/py-umap-learn/Makefile new file mode 100644 index 000000000000..2b8aaa06ab1b --- /dev/null +++ b/math/py-umap-learn/Makefile @@ -0,0 +1,24 @@ +PORTNAME= umap-learn +DISTVERSION= 0.5.3 +CATEGORIES= math python +MASTER_SITES= CHEESESHOP +PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} + +MAINTAINER= yuri@FreeBSD.org +COMMENT= Uniform Manifold Approximation and Projection + +LICENSE= BSD3CLAUSE + +RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}numba>=0.49:devel/py-numba@${PY_FLAVOR} \ + ${PYNUMPY} \ + ${PYTHON_PKGNAMEPREFIX}pynndescent>=0.5:math/py-pynndescent@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}scikit-learn>=0.22:science/py-scikit-learn@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}scipy>=1.0:science/py-scipy@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}tqdm>=3.4.0:misc/py-tqdm@${PY_FLAVOR} + +USES= python:3.6+ +USE_PYTHON= distutils autoplist pytest + +NO_ARCH= yes + +.include <bsd.port.mk> diff --git a/math/py-umap-learn/distinfo b/math/py-umap-learn/distinfo new file mode 100644 index 000000000000..b635e5ad4192 --- /dev/null +++ b/math/py-umap-learn/distinfo @@ -0,0 +1,3 @@ +TIMESTAMP = 1659803954 +SHA256 (umap-learn-0.5.3.tar.gz) = dbd57cb181c2b66d238acb5635697526bf24c798082daed0cf9b87f6a3a6c0c7 +SIZE (umap-learn-0.5.3.tar.gz) = 88193 diff --git a/math/py-umap-learn/pkg-descr b/math/py-umap-learn/pkg-descr new file mode 100644 index 000000000000..b3f23e964533 --- /dev/null +++ b/math/py-umap-learn/pkg-descr @@ -0,0 +1,9 @@ +Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction +technique that can be used for visualisation similarly to t-SNE, but also for +general non-linear dimension reduction. The algorithm is founded on three +assumptions about the data: +* The data is uniformly distributed on a Riemannian manifold; +* The Riemannian metric is locally constant (or can be approximated as such); +* The manifold is locally connected. + +WWW: https://github.com/lmcinnes/umap