wbplot 1.0.3

A package for automated plotting of neuroimaging maps using Connectome Workbench.

#wbplot Automated plotting of neuroimaging maps from Python using Connectome Workbench.

This package is intended for users who want to generate images which illustrate scalar data on a brain surface, from within their Python scripts.

Installation

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Step 1. Make sure you have Connectome Workbench v1.3+ installed.

• If running wb_view from a terminal yields command not found, see https://www.humanconnectome.org/software/connectome-workbench/
• If you have Workbench 1.2 or below installed, you will get an error message

Step 2. Install wbplot and dependencies.

• Clone the repository and install manually: git clone https://github.com/jbburt/wbplot.git
• Or just use pip: pip install wbplot

Usage

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Assuming x is a NumPy array containing scalar values mapped onto each of the 360 parcels in the Human Connectome Project's MMP1.0 parcellation:

from wbplot import pscalar
pscalar("/path/to/image.png", x)

Assuming y is a NumPy array containing dense scalar values mapped onto the 59412 surface vertices in a standard bilateral 32k surface mesh:

from wbplot import dscalar
dscalar("/path/to/image.png", y)

Notes

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• wbplot currently only supports cortical data. Parcellated data must also be in the HCP MMP1.0 parcellation. Dense data must be registered to a standard 32k surface mesh.
• Down the line I'd be open to adding subcortical support and other functionality if anyone ever actually uses this package.
• More detailed explanations of the functionality can be found in the scripts in the examples directory.

Change Log

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• 1.0 Initial release.
• 1.0.1 Small error in README.
• 1.0.2 Error in MANIFEST.in -- not all necessary data files included in build.
• 1.0.3 Entirely changed the way data are read from and written to, to circumnavigate permissions issues.