Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (12.5%) to scientific vocabulary
Repository
Fast tomographic reconstruction
Basic Info
- Host: GitHub
- Owner: cnpem
- License: gpl-3.0
- Language: C
- Default Branch: master
- Size: 13.4 MB
Statistics
- Stars: 1
- Watchers: 4
- Forks: 0
- Open Issues: 0
- Releases: 2
Metadata Files
README.md
SSC-RAFT: Reconstruction Algorithms for Tomography
Authors
- Eduardo X. Miqueles, LNLS/CNPEM
- Paola Ferraz, LNLS/CNPEM
Contributors
- Larissa M. Moreno, LNLS/CNPEM
- João F. G. de Albuquerque Oliveira, LNLS/CNPEM
- Alan Zanoni Peixinho, LNLS/CNPEM
- Yuri Rossi Tonin, LNLS/CNPEM
Past contributors
- Otávio M. Paiano
- Gilberto Martinez Jr.
- Giovanni Baraldi
- Janito Vaqueiro Ferreira Filho
- Fernando S. Furusato
- Matheus F. Sarmento, LNLS/CNPEM
- Nikoley Koshev
- Elias Helou
Acknowledgements
We would like to acknowledge the Brazilian Ministry of Science, Technology, and Innovation MCTI for supporting this work through the Brazilian Center for Research in Energy and Materials (CNPEM). We want to thank Petrobras (Manhattan Project) - ID 2021/00018-3 for funding part of this project - and Mogno beamline from Sirius, for many fruitful discussion about the reconstruction strategies. We also thank FAPESP/CEPID 2013/07375-0 for funding Nikolay Koshev, and FAPESP 2016/16238-4 for funding Gilberto Martinez Jr.
Contact
Sirius Scientific Computing Team: gcc@lnls.br
Documentation
The package documentation can be found on the GCC website https://gcc.lnls.br/ssc/ssc-raft/index.html inside the CNEPM network.
Also, the HTML documentation can be found in the source directory ./docs/build/index.html and can be opened with your preferred brownser.
Install
This package uses C, C++, CUDA and Python3.
See bellow for full requirements.
The library sscRaft can be installed with form the source code or by pip/git if inside the CNPEM network.
GITHUB
One can clone our public github repository and install the latest version by:
bash
git clone https://github.com/cnpem/ssc-raft.git
cd ssc-raft
make clean && make
For a specific version, one can use:
bash
git clone https://github.com/cnpem/ssc-raft.git --branch v<version> --single-branch
cd ssc-raft
make clean && make
The <version> is the version of the sscRaft to be installed. Example, to install version 3.1.1
bash
git clone https://github.com/cnpem/ssc-raft.git --branch v3.1.1 --single-branch
cd ssc-raft
make clean && make
Source code from Zenodo
The source code can be downloaded from zenodo website under the DOI:10.5281/zenodo.10988342.
After download the ssc-raft-v<version>.tar.gz with the source files, one can decompress by
bash
tar -xvf ssc-raft-v<version>.tar.gz
To compile the source files, enter the follwing command inside the folder
bash
make clean && make
PIP
Warning: This installation option is available only inside the CNPEM network.
One can install the latest version of sscRaft directly from the pip server
```bash
pip install sscRaft==
```
Where <version> is the version number of the sscRaft
bash
pip install sscRaft==3.0.3 --index-url https://gitlab.cnpem.br/api/v4/projects/1978/packages/pypi/simple
GITLAB
Warning: For this installation option is available only inside the CNPEM network.
One can clone our gitlab repository and install the latest version by:
bash
git clone https://gitlab.cnpem.br/GCC/ssc-raft.git
cd ssc-raft
make clean && make
For a specific version, one can use:
bash
git clone https://gitlab.cnpem.br/GCC/ssc-raft.git --branch v<version> --single-branch
cd ssc-raft
make clean && make
The <version> is the version of the sscRaft to be installed. Example, to install version 3.1.1
bash
git clone https://gitlab.cnpem.br/GCC/ssc-raft.git --branch v3.1.1 --single-branch
cd ssc-raft
make clean && make
Memory
Be careful using GPU functions due to memory allocation.
Requirements
Before installation, you will need the following packages installed:
CUDA >= 10.0.0CC++Python >= 3.8.0PIPlibcurl4-openssl-dev
This package supports nvidia GPUs with capabilities 7.0 or superior and a compiler with support to c++17.
The following modules are used:
CUBLASCUFFTPTHREADSCMAKE>=3.10
The following Python3 modules are used:
scikit-build>=0.17.0setuptools>=64.0.0numpyscikit-image >=0.19.3scipymatplotlibSharedArrayh5py
Uninstall
To uninstall sscRaft use the command, independent of the instalation method,
bash
pip uninstall sscRaft
Owner
- Name: Brazilian Center for Research in Energy and Materials (CNPEM)
- Login: cnpem
- Kind: organization
- Location: Brazil
- Website: https://cnpem.br/
- Repositories: 1
- Profile: https://github.com/cnpem
GitHub Events
Total
- Release event: 5
- Watch event: 1
- Delete event: 5
- Member event: 1
- Push event: 114
- Create event: 17
Last Year
- Release event: 5
- Watch event: 1
- Delete event: 5
- Member event: 1
- Push event: 114
- Create event: 17
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- actions/checkout v2 composite
- zenodraft/action 0.13.3 composite
- Pygments >=2.14.0
- SharedArray *
- click >=8.0.4
- colorama >=0.4.5
- h5py *
- matplotlib *
- mdurl >=0.1.0
- numpy <2
- rich >=12.6.0
- scikit-image >=0.19.3
- scipy *
- shellingham >=1.5.0
- tqdm *
- typer >=0.9.0
- typing_extensions >=4.1.1
- uuid *