Wheelodex » Projects » pymdma » pymdma-0.1.7-py3-none-any.whl

pymdma

View on PyPI — Reverse Dependencies (0)

0.1.7 pymdma-0.1.7-py3-none-any.whl

Wheel Details

Project: pymdma
Version: 0.1.7
Filename: pymdma-0.1.7-py3-none-any.whl
Download: [link]
Size: 128618
MD5: b4d7c909f3f5c443269b592c6aab2f7e
SHA256: 298ddcb0f88c0a2585efc53612cd59b1663eb1c02217ea3d98fb1b73c1665d02
Uploaded: 2025-01-31 15:25:36 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: pymdma
Version: 0.1.7
Summary: Multimodal Data Metrics for Auditing real and synthetic data
Author: Fraunhofer AICOS
Author-Email: no-reply[at]aicos.fraunhofer.pt
Maintainer: Ivo Façoco
Maintainer-Email: ivo.facoco[at]aicos.fraunhofer.pt
Home-Page: https://github.com/fraunhoferportugal/pymdma
Project-Url: Documentation, https://pymdma.readthedocs.io/en/latest/
Project-Url: Repository, https://github.com/fraunhoferportugal/pymdma
License: LGPL-3.0-or-later
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.9,<3.13
Requires-Dist: fastdtw (<0.4.0,>=0.3.4); extra == "time-series" or extra == "all"
Requires-Dist: gudhi (<=4.0.0,>=3.9.0); extra == "tabular" or extra == "all"
Requires-Dist: loguru (<0.8.0,>=0.7.2)
Requires-Dist: matplotlib (<4.0.0,>=3.4.3)
Requires-Dist: numba (<0.80.0,>=0.60.0); extra == "tabular" or extra == "all"
Requires-Dist: numpy (<2.5.0,>=1.22.0)
Requires-Dist: opencv-python (<4.15.0.0,>=4.10.0.84); extra == "image" or extra == "all"
Requires-Dist: pandas (<3.0.0,>=2.0.0); extra == "tabular" or extra == "all"
Requires-Dist: piq (<1.0.0,>=0.8.0)
Requires-Dist: pot (<0.10.0,>=0.9.4)
Requires-Dist: pycanon (==1.0.1.post2); extra == "tabular" or extra == "all"
Requires-Dist: pycocotools (>=2.0.8); extra == "image" or extra == "all"
Requires-Dist: pydantic (<3.0.0,>=2.8.2)
Requires-Dist: python-dotenv (<2.0.0,>=1.0.0)
Requires-Dist: scikit-learn (>1.4.0)
Requires-Dist: scipy (<2.0.0,>=1.6.0); extra == "tabular" or extra == "all"
Requires-Dist: spacy (<4.0.0,>=3.7.4); extra == "tabular" or extra == "all"
Requires-Dist: statsmodels (<0.15.0,>=0.14.4); extra == "tabular" or extra == "time-series" or extra == "all"
Requires-Dist: torch (<2.9.0,>=2.1.0)
Requires-Dist: torchvision (<0.26.0,>=0.15.2); extra == "image" or extra == "all"
Requires-Dist: transformers (<5.0.0,>=4.43.2); extra == "tabular" or extra == "all"
Requires-Dist: tsfel (>0.1.7); extra == "time-series" or extra == "all"
Requires-Dist: umap-learn (<0.6.0,>=0.5.5); extra == "tabular" or extra == "all"
Requires-Dist: wfdb (<5.0.0,>=4.1.2); extra == "time-series" or extra == "all"
Requires-Dist: word2number (<1.5.0,>=1.1.0); extra == "tabular" or extra == "all"
Provides-Extra: all
Provides-Extra: image
Provides-Extra: tabular
Provides-Extra: time-series
Description-Content-Type: text/markdown
[Description omitted; length: 10925 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.9.1
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
pymdma/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/__main__.py sha256=6T9XpwyI5rI--uKwN0CPhGgq_9rzsAqSNocuyiKI5Qk 64
pymdma/cli.py sha256=a9DkBDfQ4ZCq-J2TCCAuMPqnO1MJFzh1ESFzUngl6Ng 8746
pymdma/common/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/common/compute.py sha256=TKm3vdFMkiWFm47Qdm4f-Pd_HiDnHyq8L5PTEodQEKM 8627
pymdma/common/definitions.py sha256=VaFQFdootNRXcVJ8j4nRUZHQ6HNEerGmv3Imj6xt9x4 2078
pymdma/common/output.py sha256=JQ0HkfB1Sy0pDKx8MU-SJtLcOWXgK1LE2FDP7AeMfN8 11060
pymdma/common/selection.py sha256=VJJtL9zIpfZMKz6JqI4Wv3kUqBL5MFr2s8Nl5JokAYs 12729
pymdma/common/settings.py sha256=Wcu4a_fTj8iHOSRX3_FBHBDp_3Vd6oWkVP1kQ0pE9qg 823
pymdma/common/viz.py sha256=5p8fIma5wtRWBHC-rqBb-vVi1HcB2RjGo5gFMbvDGho 3416
pymdma/config.py sha256=6TagEud1mtkCcysj8n9eWkZkEk2MFA794VswznWECOg 1866
pymdma/constants.py sha256=SLHtUR6Bo-uk9a6Vl2tv14Dd6sO0jPKX1ypAMrS0NXQ 1998
pymdma/general/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/functional/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/functional/distance.py sha256=fs2ZOouxbkRjR2m1Em96d0vxw5d8Lzq8I48AQtEp5eM 6176
pymdma/general/functional/ratio.py sha256=V2tC54OG8PrKtJGlLCPOkiV7weWgBPkAfGxdbUDj43c 3396
pymdma/general/measures/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/measures/external/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/measures/external/piq.py sha256=f9BMvBSQuVzg3wb1j6Egk0whCQlqKgaJUpNkA8ha2Sk 13059
pymdma/general/measures/prd.py sha256=5KCqG5GjDNNccyqI00Pw7ekRWWiX7Kvkktt-59gsULE 10685
pymdma/general/measures/prdc.py sha256=K_WV1V-akSILG_1lzji_uomkDaW4n2Spmf8cwKd4VNA 19313
pymdma/general/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/models/kernels.py sha256=0GsdyQ4NPRdwyLRt-bbXS3o39FAmCdOXJpwPH1EWoZU 6187
pymdma/general/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/general/utils/util.py sha256=iDkgdql4oPhnGnd45ieXmMZE7eg2h7wWBuyV7F9a8qo 6160
pymdma/image/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/data/parsers.py sha256=-BNu17KUo97rWphQetF3Sv1T8X_P9HALmosdx0etSuU 249
pymdma/image/data/simple_dataset.py sha256=9QIDsJ2Ud9MwlhrRusz5YrTQ1Pgm8nrX6ohUFnJ81TQ 1153
pymdma/image/input_layer.py sha256=5CTcJsyeiznMgJbrtACOEW2QO9zNJ9kbnTEdpx3TyeE 9981
pymdma/image/measures/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/measures/input_val/__init__.py sha256=jETGkMIhhQBuZBQDl3JsHGBhSXnoRMAe_VIo6jERUp4 591
pymdma/image/measures/input_val/annotation/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/measures/input_val/annotation/coco.py sha256=X6oFBXFVz_n3PNMRxFYCkgBAjLsEy0MbbOomLFyFUIA 17544
pymdma/image/measures/input_val/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/measures/input_val/data/dom.py sha256=DAP-BEHL_Jb56j2Hqd4KyYlC-QZi1nHJoB2MH9ZYck0 9329
pymdma/image/measures/input_val/data/no_reference.py sha256=MrPieMp2Pv7ZshUI905rD7sQgfI4aoS5PcYGolP_xrI 23652
pymdma/image/measures/input_val/data/psnr.py sha256=BBceChG_BuvGGK5BFXas8DpLdb0rXbECRGEJqwGFwz4 4386
pymdma/image/measures/input_val/data/ssim.py sha256=l24zlshf73MEdxAzMi1QQnhrvVvyTStTeeZtTrLP6L4 9944
pymdma/image/measures/synthesis_val/__init__.py sha256=tqEzdo5RNmJz1pLZeD6F6awVsq_VN7gozGvIwB4S3zc 614
pymdma/image/measures/synthesis_val/feature/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/measures/synthesis_val/feature/_shared.py sha256=s-22-0WKsJRtUvbmNzy1waLio88M06elvmw7yTyO6pc 568
pymdma/image/measures/synthesis_val/feature/giqa.py sha256=tuNLl7jkJ40q01LyxWiZLddPxS6opmKh_n1RXFKPDhg 4096
pymdma/image/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/models/extractor.py sha256=9GphoZXuXl-ECQTpDwvpoPWoYuyoFtXIWEa-N56NlEQ 7100
pymdma/image/models/features.py sha256=wSGT9N6mwKY3xGeoo0Kw-VjpZsgogUL2urVKRBJdC4o 881
pymdma/image/models/imagenet.py sha256=Fc4J8EvXop7I3tV-KaEixkM21bruuLxJXMF14wxhwsM 2523
pymdma/image/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/image/utils/processing.py sha256=wK_bwe6Z-aDLTpXJSLILp5jPQSGEE6Ri0K7N_tJIo8w 2108
pymdma/tabular/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/data/harmonize.py sha256=jHyd-ZtqvdJuIL-uUm-cTqNOPRtRtZNnAkZlYKqyiPs 13264
pymdma/tabular/data/load.py sha256=UC5dfK5kA6Y39DeZ8Re-vyu4DeSNADqjgvvZbxTYeOY 17214
pymdma/tabular/data/utils.py sha256=heq-US_lZOz2ZHh3rCZ4oghXvBjY9XQ6uqk96iu-dac 5881
pymdma/tabular/embeddings/__init__.py sha256=BOTSEWycSKZ8sDTcWJWtAuipEShZbKdnR8hqhDzCD9E 792
pymdma/tabular/embeddings/embed.py sha256=mA07ZDFTxsrfKTLM4sMcwoF_SJb3QhXNhiYQWW6rPfg 11500
pymdma/tabular/embeddings/scale.py sha256=V2-FQifQxH0jLBKozYrPzuLmzOOIL546IJ89cdxlAlY 5306
pymdma/tabular/embeddings/utils.py sha256=g5D2d3dB7yb2BbpSLH7rV-It_uDlFc5iLgI7F9l7_zk 2147
pymdma/tabular/input_layer.py sha256=TtIZnqD8fkpP1t6toXfCcCfe1VMxYkLPx5j915RV0kk 10529
pymdma/tabular/measures/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/measures/input_val/__init__.py sha256=EXD43xu-ZBF_yZi3uXVN2FC4a84IR6pFp2NjD-jaskQ 466
pymdma/tabular/measures/input_val/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/measures/input_val/data/privacy.py sha256=OVa4XVnT3Q4xS84n58YaC7rGhnqbHM7ZQY-1dogZ4qs 3987
pymdma/tabular/measures/input_val/data/quality.py sha256=EmxKfYURwY3M1st4q3XujxZnsCp-XhIu3czzYbd-_-I 27931
pymdma/tabular/measures/synthesis_val/__init__.py sha256=UdFvYW3M1RTOtilZeKKfM5cjSvfYH77y43S4lCB3RIk 720
pymdma/tabular/measures/synthesis_val/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/measures/synthesis_val/data/similarity.py sha256=7JSE705Ff2-kdZA5C7eMVA9uZhrCGiDHKyyLbUlX5Ik 17881
pymdma/tabular/measures/synthesis_val/data/utility.py sha256=r8OLwimXGwDYrKOUJ8ftWibpcZvjrKa8zQP9-SdWzF0 5558
pymdma/tabular/measures/synthesis_val/feature/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/measures/synthesis_val/feature/_shared.py sha256=U5ePj0vNQ6ikfUuAZh--kNFt3qwPFB_iUXXmwgpWbYY 221
pymdma/tabular/measures/synthesis_val/feature/privacy.py sha256=Z1yX6w1ceOWHQM6Lu1pji8yc0proODFYHApAcYCjQp4 6890
pymdma/tabular/measures/utils_inp.py sha256=ChbDzEIl9O5bWb38HspfUTC40pMFH9xB8mclGIaPdI0 14046
pymdma/tabular/measures/utils_syn.py sha256=B66eRMR-tLv7rg9sEnmsObktVJRAu6HIcl5aDmABalY 11751
pymdma/tabular/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/tabular/models/classification.py sha256=BBHPK2Nwtge9MXBXlI8DYUQlzyqPTpXAe2iztQSuSxk 1330
pymdma/tabular/models/regression.py sha256=wvjUTrrhIEBV_3yBgd-T6P3Q0o4J173TZC497tUM6ps 1316
pymdma/time_series/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/data/simple_dataset.py sha256=cOmufj_O7HxN_QEOibzVk4qODL7JVInd8uGj_irXzgs 3356
pymdma/time_series/input_layer.py sha256=0djJb5ODHj2OwPpNEu_tnOb50PEAG5q6SHyZ6rfPJFU 9684
pymdma/time_series/measures/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/measures/input_val/__init__.py sha256=7Abp62rIOqLPQT80EfPUobxGHzI_tThgaSzXkOU9QGQ 112
pymdma/time_series/measures/input_val/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/measures/input_val/data/quality.py sha256=DjWGLSYfnYZyxxaj2tQ0DnpI9lBauk0Yvo6TnnUbSyo 4324
pymdma/time_series/measures/synthesis_val/__init__.py sha256=mOtlOJu6RvGeTpUS4_pSnyjENMiBZhKcABEv1x7GkUE 797
pymdma/time_series/measures/synthesis_val/data/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/measures/synthesis_val/data/reference.py sha256=TVfwSXklyVhAwqEaaNIDMw8EWMH1DHMIros6_i2X77M 8484
pymdma/time_series/measures/synthesis_val/feature/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/measures/synthesis_val/feature/_shared.py sha256=NG12jlCa3PCGobasD6a75KImu1cweiauVCsVAFs9HLg 726
pymdma/time_series/measures/synthesis_val/feature/distance.py sha256=4xiWVQn8HlQkkcjDkykkNFd2cbsadFJXvLQZQnGNH10 12510
pymdma/time_series/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma/time_series/utils/extract_features.py sha256=YWwI-uWbb-jCpcwOKeAbbnPKYKCT08_YBglgytU56LY 4391
pymdma/time_series/visualization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
pymdma-0.1.7.dist-info/AUTHORS.md sha256=IGYkXr1FliEx4wU0JjARcz60Zmt9nYxujk1yVKMdoP0 599
pymdma-0.1.7.dist-info/LICENSE sha256=HsgJcjrOgQqt9AiQlFNXKXeL7ymIRrsgPC0u_gJz9tE 7654
pymdma-0.1.7.dist-info/METADATA sha256=0ZK3iZn1H1rIp7NR0xVSPdfmib7xoDFPawZgNXGzivk 13926
pymdma-0.1.7.dist-info/WHEEL sha256=Nq82e9rUAnEjt98J6MlVmMCZb-t9cYE2Ir1kpBmnWfs 88
pymdma-0.1.7.dist-info/entry_points.txt sha256=mg_5zn_F9YMYShfiIbGuCjE3DgkIlW88VQ-13qBD9Yg 42
pymdma-0.1.7.dist-info/RECORD — —

entry_points.txt

[console_scripts]
pymdma = pymdma.cli:main