searchlights is a Python package that provides precomputed searchlights for surface-based analysis of fMRI data.
It only depends on NumPy.
Installation
The package can be installed with pip:
python -m pip install searchlights
Example usage
The surface-based fMRI data we usually use (e.g., Feilong et al., 2018) are in fsaverage space, downsampled to a lower resolution (icoorder5, approximately 3 mm vertex spacing).
The surface has 9372 vertices for the left hemisphere, and 9370 vertices for the right hemisphere.
The code below shows how to get the searchlights for the left hemisphere with a 20 mm radius.
import numpy as np
from searchlights import get_searchlights
sls = get_searchlights('l', 20, 'fsaverage')
See the documentation for more examples and details.
Metadata
Release files for searchlights 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| searchlights-0.2.0.tar.gz | 30.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| searchlights-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 61.4 MB
Release files / searchlights-0.2.0.tar.gz
| Download URL | searchlights-0.2.0.tar.gz |
|---|---|
| Size | 30.7 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
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Release files / searchlights-0.2.0-py3-none-any.whl
| Download URL | searchlights-0.2.0-py3-none-any.whl |
|---|---|
| Size | 30.7 MB |
| Tags | Python 3 |
|
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? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
|