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authorRene Ladan <rene@FreeBSD.org>2025-01-01 10:59:24 +0000
committerRene Ladan <rene@FreeBSD.org>2025-01-01 10:59:24 +0000
commitdd41e117edf69a86b861eaedcd016835c6d7e8d1 (patch)
tree318c81564a12ba8870a90093ff253c3728450a82
parentda97d2cf3d6563de7d4a6b6ddeec1e2f30abab53 (diff)
-rw-r--r--MOVED1
-rw-r--r--science/Makefile1
-rw-r--r--science/py-nilearn/Makefile45
-rw-r--r--science/py-nilearn/distinfo3
-rw-r--r--science/py-nilearn/pkg-descr10
5 files changed, 1 insertions, 59 deletions
diff --git a/MOVED b/MOVED
index b3f4f1a83b12..d6a993e3bd05 100644
--- a/MOVED
+++ b/MOVED
@@ -3810,3 +3810,4 @@ net-mgmt/zabbix64-frontend||2025-01-01|Has expired: Zabbix 6.4 is expected to re
net-mgmt/zabbix64-server||2025-01-01|Has expired: Zabbix 6.4 is expected to reach EoL on December 31, 2024
www/webtrees20|www/webtrees21|2025-01-01|Has expired: Uses obsolete PHP version; use www/webtrees21 or www/webtrees22 instead
dns/py-idna_ssl||2025-01-01|Has expired: Upstream repository has been archived on Oct 22, 2020
+science/py-nilearn||2025-01-01|Has expired: Depends on expired devel/py-codecov
diff --git a/science/Makefile b/science/Makefile
index 36e82d0f138c..df34c6dbc9e0 100644
--- a/science/Makefile
+++ b/science/Makefile
@@ -380,7 +380,6 @@
SUBDIR += py-netcdf-flattener
SUBDIR += py-nglview
SUBDIR += py-nibabel
- SUBDIR += py-nilearn
SUBDIR += py-obspy
SUBDIR += py-oddt
SUBDIR += py-openEMS
diff --git a/science/py-nilearn/Makefile b/science/py-nilearn/Makefile
deleted file mode 100644
index 008f15971e7b..000000000000
--- a/science/py-nilearn/Makefile
+++ /dev/null
@@ -1,45 +0,0 @@
-PORTNAME= nilearn
-DISTVERSION= 0.11.1
-CATEGORIES= science python
-MASTER_SITES= PYPI
-PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
-
-MAINTAINER= yuri@FreeBSD.org
-COMMENT= Statistical learning for neuroimaging in Python
-WWW= https://nilearn.github.io/
-
-LICENSE= BSD3CLAUSE
-LICENSE_FILE= ${WRKSRC}/LICENSE
-
-DEPRECATED= Depends on expired devel/py-codecov
-EXPIRATION_DATE=2024-12-31
-
-BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}hatch-vcs>0:devel/py-hatch-vcs@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}hatchling>0:devel/py-hatchling@${PY_FLAVOR}
-RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}codecov>0:devel/py-codecov@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}joblib>=1.2.0:devel/py-joblib@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}lxml>0:devel/py-lxml@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}matplotlib>0:math/py-matplotlib@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}nibabel>=5.2.0:science/py-nibabel@${PY_FLAVOR} \
- ${PYNUMPY} \
- ${PYTHON_PKGNAMEPREFIX}packaging>0:devel/py-packaging@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}pandas>0:math/py-pandas@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}requests>=2.25.0:www/py-requests@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}scikit-learn>=1.4.0:science/py-scikit-learn@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}scipy>=1.8.0:science/py-scipy@${PY_FLAVOR} \
- bash:shells/bash
-TEST_DEPENDS= ${PYTHON_PKGNAMEPREFIX}pytest>0:devel/py-pytest@${PY_FLAVOR} \
- ${PYTHON_PKGNAMEPREFIX}pytest-cov>=0:devel/py-pytest-cov@${PY_FLAVOR}
-
-USES= python shebangfix
-USE_PYTHON= pep517 autoplist
-
-SHEBANG_FILES= nilearn/datasets/tests/data/list_archive_contents.sh \
- nilearn/plotting/glass_brain_files/plot_align_svg.py
-
-NO_ARCH= yes
-
-do-test:
- @cd ${WRKSRC} && ${PYTHON_CMD} -m pytest -rs -v
-
-.include <bsd.port.mk>
diff --git a/science/py-nilearn/distinfo b/science/py-nilearn/distinfo
deleted file mode 100644
index 8f13c7435820..000000000000
--- a/science/py-nilearn/distinfo
+++ /dev/null
@@ -1,3 +0,0 @@
-TIMESTAMP = 1735072241
-SHA256 (nilearn-0.11.1.tar.gz) = a01df08fc6c8ded3cd6fb7a211634603ad46a6df780504b6d05222c2e7a972fe
-SIZE (nilearn-0.11.1.tar.gz) = 12481586
diff --git a/science/py-nilearn/pkg-descr b/science/py-nilearn/pkg-descr
deleted file mode 100644
index 5e85ecdb88ba..000000000000
--- a/science/py-nilearn/pkg-descr
+++ /dev/null
@@ -1,10 +0,0 @@
-Nilearn enables approachable and versatile analyses of brain volumes. It
-provides statistical and machine-learning tools, with instructive documentation
-& open community.
-
-It supports general linear model (GLM) based analysis and leverages the
-scikit-learn Python toolbox for multivariate statistics with applications such
-as predictive modelling, classification, decoding, or connectivity analysis.
-
-Nilearn now includes the functionality of Nistats. Here's a guide to replacing
-Nistats imports to work in Nilearn.