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Suspect is a Python package for processing MR spectroscopy data. It supports reading data from most common formats (with more on the way) and many different algorithms for core processing steps. Suspect allows researchers to build custom data processing scripts from reliable, modular building blocks and easily share their techniques with other labs around the world.
Installation
Suspect itself is a pure Python package and is easy to install with pip. However it does depend on various other packages, some of which are not so easy to install.
Obtain Python and the SciPy stack:
Suspect requires Python 3 and makes heavy use of numpy and other parts of the Scientific Python stack. The easiest way to obtain this, along with a large number of other useful scientific packages, is to download the free Anaconda package. Alternatively check here for other ways to install these core packages.
Install suspect
pip install suspect will automatically download and install the latest version of suspect, along with all remaining other dependencies.
Getting Started
Suspect is still a young package and we are working hard to get useful examples out there. Documentation for the project is available at http://suspect.readthedocs.io/en/latest/
Contributing
If you are interested in helping out with any part of suspect or the OpenMRSLab project, we would love to hear from you.
License
Suspect is released under the MIT license
2 maintainers
Release files for suspect 0.6.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| suspect-0.6.2.tar.gz | 62.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| suspect-0.6.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 137.0 kB
Release files / suspect-0.6.2.tar.gz
| Download URL | suspect-0.6.2.tar.gz |
|---|---|
| Size | 62.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/6.1.0 CPython/3.13.7
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Signed by GitHub Actions, verified by PyPI on Feb 10, 2026.
Transparency logRelease files / suspect-0.6.2-py3-none-any.whl
| Download URL | suspect-0.6.2-py3-none-any.whl |
|---|---|
| Size | 75.0 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Feb 10, 2026.
Transparency log
