A wrapper for generating Docker commands using regular sMRIPrep syntax
Project description
sMRIprep is a structural magnetic resonance image pre-processing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting.
This is a lightweight Python wrapper to run sMRIPrep. It generates the appropriate Docker commands, providing an intuitive interface to running the sMRIPrep workflow in a Docker environment. Docker must be installed and running. This can be checked running
docker info
Please report any feedback to our GitHub repository and do not forget to credit all the authors of software that sMRIPrep uses.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file smriprep-docker-0.6.0rc3.tar.gz.
File metadata
- Download URL: smriprep-docker-0.6.0rc3.tar.gz
- Upload date:
- Size: 6.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.8.0 tqdm/4.45.0 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f6ead2f45ad43209acce7c7d0d013b3245941a13d5e6f58f5b0ea8afa7591bde
|
|
| MD5 |
04887f773fec91f7a3bc3c8473e22ecb
|
|
| BLAKE2b-256 |
ba0d5c3a9e5099e277b30f59c1d44b0617d80384c46eea514695c6b96ae618c1
|
File details
Details for the file smriprep_docker-0.6.0rc3-py2.py3-none-any.whl.
File metadata
- Download URL: smriprep_docker-0.6.0rc3-py2.py3-none-any.whl
- Upload date:
- Size: 19.5 MB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.4.0 requests-toolbelt/0.8.0 tqdm/4.45.0 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9074836af715d5f66e2c0b04a5aaac40a53c9ee7fc470ab214169fd481530731
|
|
| MD5 |
db2eb2fe25f57e894f5e3f749143286b
|
|
| BLAKE2b-256 |
837c37e5df69ea4d0ed2ed9101e73721adbbea8c7db81d5469dac58b63b3d2f0
|
