=======================
Scipionn Toolkit
=======================
This package provides a neural network environment integrating the deep learning algorithms needed by `scipion-em-flexutils <https://github.com/scipion-em/scipion-em-flexutils>`_ plugin
==========================
Included Networks
==========================
- **Zernike3Deep**: Semi-classical neural network to analyze continuous heterogeneity with the Zernike3D basis
- **DeepNMA**: Semi-classical neural network with automatic NMA selection directly from images to analyze continuous heterogeneity
- **HomoSIREN**: Neural network homogeneous reconstruction for real space
- **HetSIREN**: Neural network heterogeneous reconstruction for real space
- **DeepPose**: Particle pose and shift refinement with neural networks
- **FlexConsensus**: Consensus neural network for conformational landscapes
==========================
Installation
==========================
The Flexutils-Tensorflow toolkit relies on Conda and Pip for its correct installation.
Before installing, Conda must be set in the PATH variable so it can be discovered during the installation. Once this requirement is met, the package can be either installed with ``pip install scipionn-toolkit`` or with ``pip install -e path/to/cloned/scipionn-toolkit`` after cloning this repository.
We recommend adding the flag `-v` to pip installation command to have a better tracking of the installation.
Raw data
{
"_id": null,
"home_page": "",
"name": "scipionn-toolkit",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "scipion continuous-heterogeneity imageprocessing xmipp",
"author": "David Herreros",
"author_email": "dherreros@cnb.csic.es",
"download_url": "https://files.pythonhosted.org/packages/4f/d2/892402ace4500cc17e8268b3b29e2738cd9238692db347f1d7cad394d694/scipionn-toolkit-1.0.4.tar.gz",
"platform": null,
"description": "=======================\nScipionn Toolkit\n=======================\n\nThis package provides a neural network environment integrating the deep learning algorithms needed by `scipion-em-flexutils <https://github.com/scipion-em/scipion-em-flexutils>`_ plugin\n\n==========================\nIncluded Networks\n==========================\n\n- **Zernike3Deep**: Semi-classical neural network to analyze continuous heterogeneity with the Zernike3D basis\n- **DeepNMA**: Semi-classical neural network with automatic NMA selection directly from images to analyze continuous heterogeneity\n- **HomoSIREN**: Neural network homogeneous reconstruction for real space\n- **HetSIREN**: Neural network heterogeneous reconstruction for real space\n- **DeepPose**: Particle pose and shift refinement with neural networks\n- **FlexConsensus**: Consensus neural network for conformational landscapes\n\n==========================\nInstallation\n==========================\n\nThe Flexutils-Tensorflow toolkit relies on Conda and Pip for its correct installation.\n\nBefore installing, Conda must be set in the PATH variable so it can be discovered during the installation. Once this requirement is met, the package can be either installed with ``pip install scipionn-toolkit`` or with ``pip install -e path/to/cloned/scipionn-toolkit`` after cloning this repository.\n\nWe recommend adding the flag `-v` to pip installation command to have a better tracking of the installation.\n\n\n",
"bugtrack_url": null,
"license": "",
"summary": "Xmipp neural network utilities for flexibility",
"version": "1.0.4",
"split_keywords": [
"scipion",
"continuous-heterogeneity",
"imageprocessing",
"xmipp"
],
"urls": [
{
"comment_text": "Release of Flexutils-Tensorflow-Toolkit",
"digests": {
"blake2b_256": "c8c27fccf32d7fe24622bf59f6174bedf4d11b96e7a01f2b1bd0d32095dfa608",
"md5": "13dc489949f965235608c528767f7c30",
"sha256": "cd5ce580265f281132aeb260a37fa9934f6f0d901905b1f1c2aa02c444a1e5eb"
},
"downloads": -1,
"filename": "scipionn_toolkit-1.0.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "13dc489949f965235608c528767f7c30",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 14817,
"upload_time": "2023-03-27T11:36:31",
"upload_time_iso_8601": "2023-03-27T11:36:31.356275Z",
"url": "https://files.pythonhosted.org/packages/c8/c2/7fccf32d7fe24622bf59f6174bedf4d11b96e7a01f2b1bd0d32095dfa608/scipionn_toolkit-1.0.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "Release of Flexutils-Tensorflow-Toolkit",
"digests": {
"blake2b_256": "4fd2892402ace4500cc17e8268b3b29e2738cd9238692db347f1d7cad394d694",
"md5": "2b6a87a631c40d53bf6b3dbbe4aa9868",
"sha256": "458e12ebafe143954f7ef62f9dd0946e9003ceb0c50dc7fdd8f9ac54dbcb5875"
},
"downloads": -1,
"filename": "scipionn-toolkit-1.0.4.tar.gz",
"has_sig": false,
"md5_digest": "2b6a87a631c40d53bf6b3dbbe4aa9868",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 16441,
"upload_time": "2023-03-27T11:36:33",
"upload_time_iso_8601": "2023-03-27T11:36:33.507459Z",
"url": "https://files.pythonhosted.org/packages/4f/d2/892402ace4500cc17e8268b3b29e2738cd9238692db347f1d7cad394d694/scipionn-toolkit-1.0.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-03-27 11:36:33",
"github": false,
"gitlab": false,
"bitbucket": false,
"lcname": "scipionn-toolkit"
}
JSON