autorad

View on PyPIReverse Dependencies (0)

0.2.6 autorad-0.2.6-py3-none-any.whl

Wheel Details

Project: autorad
Version: 0.2.6
Filename: autorad-0.2.6-py3-none-any.whl
Download: [link]
Size: 82117
MD5: a14e83208155c20c4ec688c10346fcd6
SHA256: 173e71a9179513c66d118cf88ee36c5dab01a2315b3bf3f3b06598c4882997ec
Uploaded: 2023-02-19 12:29:52 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: autorad
Version: 0.2.6
Summary: Radiomics-related modules for extraction and experimenting
Author: Piotr Woznicki
Author-Email: piotr.a.woznicki[at]gmail.com
Home-Page: https://github.com/pwoznicki/AutoRadiomics
Project-Url: Bug Tracker, https://github.com/pwoznicki/AutoRadiomics
License: Apache 2.0
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Requires-Dist: pyradiomics (==3.0.1)
Requires-Dist: scikit-learn (==1.2.0)
Requires-Dist: SimpleITK (==2.1.1.2)
Requires-Dist: pandas (==1.4.2)
Requires-Dist: scipy (==1.9)
Requires-Dist: pyyaml (==6.0)
Requires-Dist: statsmodels (==0.13.2)
Requires-Dist: mlflow (==2.0.1)
Requires-Dist: nibabel (==3.2.1)
Requires-Dist: matplotlib (==3.5)
Requires-Dist: xnat (==0.4.2)
Requires-Dist: tqdm (==4.62.3)
Requires-Dist: pqdm (>=0.2.0)
Requires-Dist: Boruta (==0.3)
Requires-Dist: xgboost (==1.6.0)
Requires-Dist: imbalanced-learn (==0.9.1)
Requires-Dist: optuna (==2.10.0)
Requires-Dist: plotly (==5.5)
Requires-Dist: shap (==0.41)
Requires-Dist: scikit-image (==0.19)
Requires-Dist: streamlit (~=1.15); extra == "app"
Requires-Dist: jupytext (~=1.14); extra == "app"
Requires-Dist: coverage (~=6.2); extra == "dev"
Requires-Dist: great-expectations; extra == "dev"
Requires-Dist: pytest (~=6.2); extra == "dev"
Requires-Dist: hypothesis (~=6.36); extra == "dev"
Requires-Dist: black (~=22.10); extra == "dev"
Requires-Dist: flake8 (~=4.0); extra == "dev"
Requires-Dist: isort (~=5.10); extra == "dev"
Requires-Dist: pre-commit (~=2.17); extra == "dev"
Requires-Dist: streamlit (~=1.15); extra == "dev"
Requires-Dist: jupytext (~=1.14); extra == "dev"
Requires-Dist: mkdocs (==1.4.2); extra == "dev"
Requires-Dist: mkdocs-material (==8.5.10); extra == "dev"
Requires-Dist: mkdocstrings[python] (==0.19.0); extra == "dev"
Requires-Dist: mkdocs (==1.4.2); extra == "docs"
Requires-Dist: mkdocs-material (==8.5.10); extra == "docs"
Requires-Dist: mkdocstrings[python] (==0.19.0); extra == "docs"
Provides-Extra: app
Provides-Extra: dev
Provides-Extra: docs
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 4333 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.38.4)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
autorad/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/__main__.py sha256=MO8_I16vk8mnJHxfD1W97dmLEzHtbyezD8v3-KU4ads 857
autorad/config/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/config/config.py sha256=MCf11ii00iynJcOBZeVv3cB3YrdIss0kN5TQWuwCKIw 2875
autorad/config/pyradiomics_feature_names.json sha256=UvZqR_WWvY44FZ9ejpyHUyTrOksFF95UjbVgWXbc_A8 3212
autorad/config/type_definitions.py sha256=XeHhrcv5toe8E_pNLGDOzRNCjs4LJBYkT1HMX-Mwmzs 71
autorad/config/pyradiomics_params/CT_Baessler.yaml sha256=PVZTdDHsTSbv0yP8LVI6HOsBZZ_WdC2ksLMT8fqjDuc 2346
autorad/config/pyradiomics_params/CT_default.yaml sha256=7UQZerCua4EkA_j-5osbDXabKebPXHh2eEcoP-fPvz8 890
autorad/config/pyradiomics_params/CT_default_feature_map.yaml sha256=fG1CKdrAO4fChFPZpq-YayzcgUYr1cJ7sAHpgfKP4ZQ 896
autorad/config/pyradiomics_params/MR_default.yaml sha256=i1DEEWh_JENnePWYVbfyZfAOV8qI_MVryQ-Sfpo_fp0 2330
autorad/data/__init__.py sha256=oWHDEM2P5qICoZkd8oR85qDfTurQ5JgCWL-OoYgZ3cw 138
autorad/data/dataset.py sha256=rc3U4lSgBQRmmrMtVI5b_nII-fVfeAExgxeSXf9obIM 16572
autorad/evaluation/__init__.py sha256=sIrlxraTHUOdxp4GNpZuImKhNinNcV7onbz5HXfkPfQ 58
autorad/evaluation/eval_utils.py sha256=9vrus5WtPP9ORRS9iW3N2eDeQwzXTfXA7B3SOWJ7h40 1369
autorad/evaluation/evaluate.py sha256=tXJZSrIRuMY33Tk5RdBOHmOn2aXfqyIo_N5nMWLV0XQ 2271
autorad/evaluation/metrics.py sha256=m1ZCpcB0Raee7zq5NVJkVv483J1AZgQh8EGSF0jPc1k 1630
autorad/external/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/external/delong.py sha256=CAlqkFFNvSKozBP1jORMkDc9ZqEhSFiygHWQySbgUI4 5468
autorad/external/download_WORC.py sha256=APcLEvhEZyCf36KZz4wiZ-0U283Q6c5o0cc7M47D8Pw 6607
autorad/feature_extraction/__init__.py sha256=7u9kXnOdNFE6qJJKvKc150GI3upDxerDSVleAM87SMU 40
autorad/feature_extraction/core.py sha256=dm9_g47cX1Ekqn_8XURM50cI5i59Z4-C9zLwIPHM9N8 1059
autorad/feature_extraction/extractor.py sha256=f_xHNUohEKnW2WYyidibNyhe5WPTsuh-AmvsglfBGa8 8662
autorad/feature_extraction/voxelbased.py sha256=dhJL6XRXypoxzozoo0bBr_hU8SJc-vbYBzGMN4EwXWw 1237
autorad/feature_selection/__init__.py sha256=Kz78DyH3OonN5tvMMwFP4p8CZ_6iVBpf-7hh4AugHiM 160
autorad/feature_selection/selector.py sha256=5c_4BHJ6T96Y5mCEhLEPMpCaeEyYGk9XPQydIiEFffE 4989
autorad/inference/__init__.py sha256=y0U8MjvCuuAJ9VsmmU_SQcogRkcJhSkLZlCe6CqzhFg 28
autorad/inference/infer.py sha256=6wWp4YAJnxo4bntWLgeWcIAgkXEfF9gyCXlxbKkRPmM 5260
autorad/inference/infer_utils.py sha256=ZA8H77ddOAy6iwOsfV61VrEdNQ2t-n5d_TLaMOomnTA 2086
autorad/models/__init__.py sha256=JAQs20KlJgc_0vfleZE-A-AF37QijHAheaqX6TtNGZo 37
autorad/models/classifier.py sha256=3ESzYwF1Avdl4RhhrwLS6s9UCosTCLVwbraqDjwx3ec 7408
autorad/models/optuna_params.py sha256=8Z86xqw6MrmmM73AJ8cBqUwfctKU8QO3qKXQopDzpzo 3704
autorad/preprocessing/__init__.py sha256=5xWFC2VYcwHFd0bHCaUDbQ11f1KFIWBNxU4ye-pTTx4 61
autorad/preprocessing/oversample_utils.py sha256=DtDShhaZeYgpdErjvSmOFRYGccUz7VrhO-2NisgQOGU 1070
autorad/preprocessing/preprocess.py sha256=AJtyU1aw8eR3FUyBurSA4q4vfzlkugqqQiF6WhavlJc 9853
autorad/registration/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/segmentation/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/segmentation/utils.py sha256=vl7ABr623fgcQq1p-9rDBq0tnkOcLHhd4lBDEBGJ-yc 770
autorad/training/__init__.py sha256=2KAnTalXhycwBktTDchyXZAN2GA1XhJVTNA7jj20eps 68
autorad/training/optimizer.py sha256=XVI7c_UtYgegW9mwdCtTciqHrq561lHn3W6e6CWCPKE 4776
autorad/training/train_utils.py sha256=s9VMY4_1UufDQqouUDWczmNRzLT0wACiAH6E_JfM4NQ 1284
autorad/training/trainer.py sha256=ScNNufCdcXqkPez9n9-QSXsGzsK94-mO8qSYw32vBwk 7386
autorad/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/utils/conversion.py sha256=1k05FDYVgvQIbpYTcLVfur_G-iJFbhpM6qcv71L4Xjg 1428
autorad/utils/extraction_utils.py sha256=_CcIjCRy9C05At9q0xWdVIuvS_QSZ8piUUVdb5ptJH8 260
autorad/utils/io.py sha256=3WvTv3_B_KNC0ZmbftzPG_7cBm6U_g4C7a5cP6s5KHI 3880
autorad/utils/mlflow_utils.py sha256=8GO7HYE17-_kw8tsJLNL_XVajpH0uJ3qY2PpQiJbk84 2536
autorad/utils/preprocessing.py sha256=guf7vKI8uNCQsCKwugHEUC0cljwb_o1tJjuSWaGplxo 5999
autorad/utils/spatial.py sha256=Uv3kf8gkH-ECn24MZdc2Qy1Ynhv_dRniuzSvtrxT8K4 14909
autorad/utils/splitting.py sha256=kOY0db0XQAY7ZoHyvfTsydPBhfYna3XTbArCVEowJIg 4370
autorad/utils/statistics.py sha256=v2XtdDIZ7HES6F5PIRJa__RAwvr6X6wunIs5AyWATxo 3646
autorad/utils/testing.py sha256=d2mVUhrDKxYZn06ABDYPoSySJbl8gPtQAk7zIk8cO00 2454
autorad/utils/utils.py sha256=CgkoHHMzKPfPJeWb5W1Ck9Nywr0HR4eSc1q0b3nMIZo 1325
autorad/visualization/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/visualization/matplotlib_utils.py sha256=e1sbNqcNuFqbDsjVamKA7rHjyUZEPnisgvMEL4i1DeY 3753
autorad/visualization/plot_volumes.py sha256=ia5t8BhOcB4lvS1LPmtfXu5ASHdpF49duMionypfiVg 11633
autorad/visualization/plotly_utils.py sha256=vFgvupjJfTHj3c02BUPTmrn7kluXH19dwhEtxJ5byJM 4486
autorad/webapp/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/webapp/app.py sha256=kV0A5_QhrV2OtEHucf5wuT3HSvAUOWF7tP0sGt0zzdQ 2556
autorad/webapp/extraction_utils.py sha256=Rgf6pl9iYrJnD0RQjaZdXDqo15nYxwhfF14BHGxTIqI 5814
autorad/webapp/extractor.py sha256=6MBl-KCSeHMTz31tPlLZC7FHMgrbt2htjYmgcmWK3NM 2219
autorad/webapp/paths_example.csv sha256=rdhbUAr8av3lPuOiEtrvm6v_5NRE1QRNF56FKwSdfvY 236
autorad/webapp/segmentation_utils.py sha256=dey4rwwjJZD9csa1Q18OmKsTlbGxKH_hf--sfCsRk94 4609
autorad/webapp/st_read.py sha256=08f_xp-MPfa2PLTgbJ2eo85gdjYKmeQntAWYEKqqN6c 5818
autorad/webapp/st_utils.py sha256=jQC0BLbMUJvXqA9R4Cd7givTlUszRQBfajd8arUB9bo 4255
autorad/webapp/validation_utils.py sha256=VXOlP1e7ck0I19QcEVAN5kUpTvV3wfnPxOA9TpO4y5U 367
autorad/webapp/webapp_config.py sha256=4P0eAKCNG57D9z_6BT-bEg3z9g50FpNgKygTSC7qKIA 190
autorad/webapp/templates/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/webapp/templates/segmentation/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
autorad/webapp/templates/segmentation/nnunet_code.py.jinja sha256=67uL2p4HiVWiBy0JOdAgaD4_5Oh4lgVEzMzysspqYPI 1161
autorad/webapp/templates/segmentation/pretrained_models.json sha256=GIowESLr2xhVOtrbNg6rWthU8DoZQsgaZfkGGfvHJDQ 8899
autorad-0.2.6.dist-info/LICENSE sha256=vK_m0DW9Apx3H7kE3ag8U1d4zebnj8V9czlahOxapS4 11348
autorad-0.2.6.dist-info/METADATA sha256=Rdwg6wNPgKTBilBCCQ8T7CZ95XOFUQ8y_K5ybEh9MUc 6509
autorad-0.2.6.dist-info/WHEEL sha256=2wepM1nk4DS4eFpYrW1TTqPcoGNfHhhO_i5m4cOimbo 92
autorad-0.2.6.dist-info/entry_points.txt sha256=LwAZ_ZIlG5feZFJPXcut17bA66JgNBqEf-VbezwFdvQ 158
autorad-0.2.6.dist-info/top_level.txt sha256=BYeMYih9YzJpknvZ-IxNxuu_6osxV6S0fLNhiorltrs 8
autorad-0.2.6.dist-info/RECORD

top_level.txt

autorad

entry_points.txt

dicom_to_nifti = autorad.utils.preprocessing:dicom_app
nrrd_to_nifti = autorad.utils.preprocessing:nrrd_app
utils = autorad.utils.utils:app