JETDNN: a Python package using Deep Neural Networks (DNNs) to find H-mode plasma pedestal heights from multiple engineering parameters.
Project description
The author of this package has not provided a project description
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
JETDNN-1.3.1.tar.gz
(8.3 kB
view details)
Built Distribution
JETDNN-1.3.1-py3-none-any.whl
(10.4 kB
view details)
File details
Details for the file JETDNN-1.3.1.tar.gz
.
File metadata
- Download URL: JETDNN-1.3.1.tar.gz
- Upload date:
- Size: 8.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 636da96fd56b01f92f66119a66d086f95ee49b9bddc94dd254a5b55fd3857a7d |
|
MD5 | ec6aca7c2478834de9d7f1c6866ad042 |
|
BLAKE2b-256 | a159fb3f0eb1543028ee40e8292bebe83ec5e668ec8ab39e9562427d670e8d66 |
File details
Details for the file JETDNN-1.3.1-py3-none-any.whl
.
File metadata
- Download URL: JETDNN-1.3.1-py3-none-any.whl
- Upload date:
- Size: 10.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 07278567eb68c2c637e6e2042f2e5a82399392f918f9762d9ac1b5c234f2e6cf |
|
MD5 | 8bc332ad8d4a8507e1afcd0bf8c1e4a3 |
|
BLAKE2b-256 | f4096c46db0f443693489b8db67f9f7dbcd2282e3da5d3be644ea54640179445 |