Wheelodex » Projects » ageml

ageml

View on PyPI — Reverse Dependencies (0)

0.1.0 ageml-0.1.0-py3-none-any.whl

Wheel Details

Project: ageml
Version: 0.1.0
Filename: ageml-0.1.0-py3-none-any.whl
Download: [link]
Size: 44358
MD5: 9e9537df980a52d04759f47ae89e50cd
SHA256: fe33506572a20e33831c8b12170a46c4fda443aef30ea647587795235c4e4b0e
Uploaded: 2024-04-17 15:55:58 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: ageml
Version: 0.1.0
Summary: AgeML is a Python package for Age Modelling with Machine Learning made easy.
Author: Computational Neuroimaging Lab Bilbao, IIS Biobizkaia
Maintainer: jorge.garcia.condado
Maintainer-Email: jorgegarciacondado[at]gmail.com
Home-Page: https://github.com/compneurobilbao/ageml
Project-Url: Repository, https://github.com/compneurobilbao/ageml
License: Apache 2.0
Keywords: Machine Learning,Age Modelling,Brain Age
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8,<3.12
Requires-Dist: coverage-conditional-plugin (<0.8.0,>=0.7.0)
Requires-Dist: matplotlib (==3.5)
Requires-Dist: numpy (==1.24)
Requires-Dist: pandas (==2.0)
Requires-Dist: pillow (<11.0.0,>=10.2.0)
Requires-Dist: scikit-learn (==1.3)
Requires-Dist: scipy (==1.10)
Requires-Dist: statsmodels (==0.14.0)
Requires-Dist: xgboost (<3.0.0,>=2.0.3)
Description-Content-Type: text/markdown
[Description omitted; length: 6469 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.7.0
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
ageml/__init__.py sha256=hJyiJyPLX3W-5XBX13T4-i0nINyq5WkxMRCW32Gmz04 213
ageml/__main__.py sha256=5fFVScZc8g-IJ3pojjd0loQXtu4xb8KMCdAs_NR9lag 151
ageml/commands.py sha256=KFD-UqGRrsPmcOLp3kuiDdmNGQyhJ0sBWCS1Kv6KFlk 12575
ageml/datasets/.gitkeep sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
ageml/datasets/__init__.py sha256=d3eVVqtsZmKkBfWa_3I_FJZf2IU4JSPux42k3XCRElM 47
ageml/datasets/synthetic_covariates.csv sha256=1ESRn_V36J00Q2uoPpY2Y7lOt-eaan-uY-VPvqNBgUo 4005
ageml/datasets/synthetic_features.csv sha256=oExSKJdUwTHPhcIkuhCh5OahpqCjKtAGhhdtMHuSEM0 7529
ageml/datasets/synthetic_test_data.py sha256=MpDQQARZzm0DjlimMrH0phiKLnPU2jwaqZRLcfTu8l4 5428
ageml/messages.py sha256=LJbwJUQJ0AkHdJ8R7ZtjSkuSb9xj_8cJh0QrsTvgatM 6687
ageml/modelling.py sha256=52jMbVWon9aNuOfne2gLBH1nEGRBleeiwTrTrI9w2WM 22472
ageml/processing.py sha256=WUYQzotQFfz9ZIMxj8EUNUAX76JfgsxDElq3Y6iSmCc 1835
ageml/ui.py sha256=-20RRZXAKn2OZdCKNE28YfXzkOElFufYE_IEpVmsvQA 65573
ageml/utils.py sha256=uMIzkVa2csBKVMDnbT2o7FPqjNpAwX-GKiQHQROPS4s 2918
ageml/visualizer.py sha256=Yh1M4sMjX3vtxfg0tMO4ex_rO3th8ZEzJE38y5Bgg54 12384
ageml-0.1.0.dist-info/LICENSE sha256=psuoW8kuDP96RQsdhzwOqi6fyWv0ct8CR6Jr7He_P_k 10173
ageml-0.1.0.dist-info/METADATA sha256=duAIouDFNoXpy4m-rBH6-J1y7IbxrxjvlZbG3FY3XD0 7721
ageml-0.1.0.dist-info/WHEEL sha256=d2fvjOD7sXsVzChCqf0Ty0JbHKBaLYwDbGQDwQTnJ50 88
ageml-0.1.0.dist-info/entry_points.txt sha256=MPMTNQCB7FHGsiG8ssm7rTPizTQUmjLiNxEwKgCRing 231
ageml-0.1.0.dist-info/RECORD — —

entry_points.txt

[console_scripts]
ageml = ageml.__main__:main
clinical_classify = ageml.commands:clinical_classify
clinical_groups = ageml.commands:clinical_groups
factor_correlation = ageml.commands:factor_correlation
model_age = ageml.commands:model_age