Individualized single-subject networks from T1 mri features such as cortical thickness and gray matter density; graynet
1 maintainer
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1 maintainer
Release files for graynet 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| graynet-0.1.2.tar.gz | 8.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| graynet-0.1.2-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 19.4 kB
Release files / graynet-0.1.2.tar.gz
| Download URL | graynet-0.1.2.tar.gz |
|---|---|
| Size | 8.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
37dc06196bedeb14527b8e0f7fe6614cb035b89aa72108bbd39c824886fae78a
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BLAKE2b-256 checksum How to use checksums |
ec56459476f530d0bbad58f981a488dec94dba69075c73d595319362355b5cd6
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / graynet-0.1.2-py2-none-any.whl
| Download URL | graynet-0.1.2-py2-none-any.whl |
|---|---|
| Size | 10.9 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
a8b5168f9d6a2ab0b9a8725ec67f35e4e1a458bef57bcc65053dff9e0841f51f
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BLAKE2b-256 checksum How to use checksums |
cf2151d21c421a07b369dc8a646526bc85dca79c8ba323123cdb8e702558460e
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for graynet 0.1.2
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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