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0.0.0 CNTools-0.0.0-py3-none-any.whl

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Project: CNTools
Version: 0.0.0
Filename: CNTools-0.0.0-py3-none-any.whl
Download: [link]
Size: 16992
MD5: 06a5c0c7675353df6b5c5ef700b8e694
SHA256: 70e1a6cae4b5b7ad1408a38bf8641a0973cfd1a3edecaa8ae5a4acf4a257f68c
Uploaded: 2023-09-01 00:06:16 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: CNTools
Version: 0.0.0
Summary: A package for identifying cellular neighborhoods
Author-Email: Yicheng Tao <yctao[at]umich.com>
Maintainer-Email: Yicheng Tao <yctao[at]umich.com>
Project-Url: Repository, https://github.com/liu-bioinfo-lab/CNTools
License: MIT License Copyright (c) 2022 yctao7 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Keywords: cellular neighborhoods
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Requires-Dist: gdown (==4.6.4)
Requires-Dist: jupyter (==1.0.0)
Requires-Dist: matplotlib (==3.4.2)
Requires-Dist: networkx (==2.6.2)
Requires-Dist: numpy (==1.20.3)
Requires-Dist: pandas (==1.2.4)
Requires-Dist: pip (==22.3.1)
Requires-Dist: python (==3.8.13)
Requires-Dist: python-louvain (==0.15)
Requires-Dist: scikit-learn (==0.24.2)
Requires-Dist: scipy (==1.6.2)
Requires-Dist: seaborn (==0.11.2)
Requires-Dist: shapely (==1.8.4)
Requires-Dist: statsmodels (==0.12.2)
Requires-Dist: tensorly (==0.5.1)
Requires-Dist: tqdm (==4.62.1)
Requires-Dist: spatial-lda (==0.1.3)
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 3594 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.41.2)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
dataset.py sha256=8NDvFygY6LJAr6kLkBDpm0e9RI-ZX3LLE25dU89XDuI 3528
identify.py sha256=uBziM-2n-a8GYVQroWWtSaqMvvcfpnw7X7cGHzXGB3g 8671
load.py sha256=SAmcgx2tUzY2dP7huqaGtdATZbzHKNSEzcfKTmrIKUE 1502
identification/CC.py sha256=5y-lQ7yh_Ra1FP5XHszfGZu4rskbnMFXnDDYDrSl5dY 1005
identification/CFIDF.py sha256=cdgSZkYwLhLXqWuZWKXGdxrmeVUwyfo6F-fjtu6vUyY 3619
identification/CNE.py sha256=UpJEp3ZavECTKKwB1OjpBft7SstnA4K43QjMyj_VVqY 1755
identification/Spatial_LDA.py sha256=rblvgK2itrvN9gdHTwx7Cy06CI2l7ISweq0xtzjl_dI 2385
identification/__init__.py sha256=vFnBHTYfm-sL6l2NTYCEd17lPo0nBt4Edha9yi4j7Yk 151
preprocessing/CRC.py sha256=ZK21lQZ9X0jMJmBGCaCdEw6ZizX9W9f46WToAie9vXs 488
preprocessing/HLT.py sha256=hmHm5EYXa1SAsuYsqLBYHd_vISg9-hp1bfZUbdBDXqA 1065
preprocessing/T2D.py sha256=C4GKpdeBnNZ2gTfkv62tEFrVXEHqP_xTxm1dK6xhRm8 1104
preprocessing/__init__.py sha256=Mq87DNI4D9voaKb4WwqmCoGlt-13xu__xnYu7KB-4r0 31
smoothing/HMRF.py sha256=9uqi5Oqo9e0h0uyYC_aSJHFCwMSWIL69RqUlZ0_G9ME 4247
smoothing/Naive.py sha256=uh9kpBduCidChvkyRalDBVe6sZNQwIeuPv90gQskepQ 2764
smoothing/__init__.py sha256=RFgfONFAZKEtYtb32dT7kPeLkI6kHJFTXh2zarxSjNU 77
CNTools-0.0.0.dist-info/LICENSE sha256=66JqCUyqnjfBZa9LJJar7WMwmTVEZbWDlMBsJq9pK4k 1063
CNTools-0.0.0.dist-info/METADATA sha256=Nb5Tsu8Xz7ru5txVZHuQX3uZ1QyCBlGPa1qQ7dphAS0 5912
CNTools-0.0.0.dist-info/WHEEL sha256=yQN5g4mg4AybRjkgi-9yy4iQEFibGQmlz78Pik5Or-A 92
CNTools-0.0.0.dist-info/top_level.txt sha256=bKX_fx0LJLeFRHx6sfUx5Pi6txCclx4GKYT4E5y6IeE 61
CNTools-0.0.0.dist-info/RECORD — —

top_level.txt

dataset
identification
identify
load
preprocessing
smoothing