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authorJason W. Bacon <jwb@FreeBSD.org>2023-12-29 16:18:01 +0000
committerJason W. Bacon <jwb@FreeBSD.org>2023-12-29 16:18:43 +0000
commitbfb9d85323b9c27d1c329a9230be3cf678763349 (patch)
tree09f6ad6c633a13e3b469b3143ba3c1af1cf45441
parent5874252d2d56ab87dfe2b87c492ce428aa33acbb (diff)
math/py-hmmlearn: Unsupervised learning of Hidden Markov Models
hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and similar models see seqlearn.
-rw-r--r--math/Makefile1
-rw-r--r--math/py-hmmlearn/Makefile37
-rw-r--r--math/py-hmmlearn/distinfo3
-rw-r--r--math/py-hmmlearn/pkg-descr3
4 files changed, 44 insertions, 0 deletions
diff --git a/math/Makefile b/math/Makefile
index 89953b27a37c..744598647931 100644
--- a/math/Makefile
+++ b/math/Makefile
@@ -951,6 +951,7 @@
SUBDIR += py-hdmedians
SUBDIR += py-hepstats
SUBDIR += py-heyoka
+ SUBDIR += py-hmmlearn
SUBDIR += py-igraph
SUBDIR += py-iminuit
SUBDIR += py-intspan
diff --git a/math/py-hmmlearn/Makefile b/math/py-hmmlearn/Makefile
new file mode 100644
index 000000000000..3baef7e19c21
--- /dev/null
+++ b/math/py-hmmlearn/Makefile
@@ -0,0 +1,37 @@
+PORTNAME= hmmlearn
+DISTVERSION= 0.3.0
+CATEGORIES= math python
+MASTER_SITES= PYPI
+PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
+
+MAINTAINER= jwb@FreeBSD.org
+COMMENT= Unsupervised learning and inference of Hidden Markov Models
+WWW= https://github.com/hmmlearn/hmmlearn
+
+LICENSE= BSD3CLAUSE
+LICENSE_FILE= ${WRKSRC}/LICENSE.txt
+
+BUILD_DEPENDS= wheel-${PYTHON_VER}:devel/py-wheel@${PY_FLAVOR} \
+ ${PYTHON_PKGNAMEPREFIX}setuptools_scm>=3.4.3:devel/py-setuptools_scm@${PY_FLAVOR} \
+ ${PYNUMPY} \
+ ${PYTHON_PKGNAMEPREFIX}scipy>=0.19:science/py-scipy@${PY_FLAVOR} \
+ ${PYTHON_PKGNAMEPREFIX}scikit-learn>=0.16:science/py-scikit-learn@${PY_FLAVOR} \
+ ${PYTHON_PKGNAMEPREFIX}pybind11>=0:devel/py-pybind11@${PY_FLAVOR}
+RUN_DEPENDS= ${PYNUMPY} \
+ ${PYTHON_PKGNAMEPREFIX}scipy>=0.19:science/py-scipy@${PY_FLAVOR} \
+ ${PYTHON_PKGNAMEPREFIX}scikit-learn>=0.16:science/py-scikit-learn@${PY_FLAVOR}
+
+USES= python
+USE_PYTHON= autoplist pep517 pytest
+
+post-stage:
+ @${STRIP_CMD} ${STAGEDIR}${PYTHON_SITELIBDIR}/hmmlearn/_hmmc.cpython-39.so
+
+# 2023-12-29: Tests currently fail due to known upstream issues
+do-test:
+ # setup.py builds directly to prefix by default, so we need to build
+ # again within the project for pytest to work
+ @(cd ${TEST_WRKSRC} && ${SETENV} ${TEST_ENV} ${PYTHON_CMD} setup.py develop)
+ (cd ${TEST_WRKSRC} && ${SETENV} ${TEST_ENV} pytest-${PYTHON_VER} --capture=no)
+
+.include <bsd.port.mk>
diff --git a/math/py-hmmlearn/distinfo b/math/py-hmmlearn/distinfo
new file mode 100644
index 000000000000..0e1fdc68387f
--- /dev/null
+++ b/math/py-hmmlearn/distinfo
@@ -0,0 +1,3 @@
+TIMESTAMP = 1703354335
+SHA256 (hmmlearn-0.3.0.tar.gz) = d13a91ea3695df881465e3d36132d7eef4e84d483f4ba538a4b46e24b5ea100f
+SIZE (hmmlearn-0.3.0.tar.gz) = 77889
diff --git a/math/py-hmmlearn/pkg-descr b/math/py-hmmlearn/pkg-descr
new file mode 100644
index 000000000000..1a2d7271b8c8
--- /dev/null
+++ b/math/py-hmmlearn/pkg-descr
@@ -0,0 +1,3 @@
+hmmlearn is a set of algorithms for unsupervised learning and inference
+of Hidden Markov Models. For supervised learning learning of HMMs and
+similar models see seqlearn.