🧠 hippunfold_plot

This package provides plotting functions for hippocampal surface maps from HippUnfold (https://github.com/khanlab/hippunfold), wrapping the Nilearn (https://nilearn.github.io) plotting functions (matplotlib engine) to achieve this.

Note: these plotting functions are distinct from those in HippoMaps (https://github.com/MICA-MNI/hippomaps), which use VTK wrappers and have a number of limitations therein.

This package is new and still under active development so suggestions and pull-requests are welcome!

📦 Installation

To install the package, simply run:

pip install hippunfold_plot

🚀 Usage

Here are some examples of how to use the plot_hipp_surf function to visualize hippocampal surface maps.

Example 1: Plot Both Hemispheres

from hippunfold_plot.plotting import plot_hipp_surf
from hippunfold_plot.utils import get_resource_path

#get subfields for demonstrating plotting
label_gii = get_resource_path('tpl-avg_label-hippdentate_density-{density}_subfields.label.gii')
density = '1mm'

# Plot dorsal view
fig = plot_hipp_surf(label_gii.format(density=density), hemi=None, density=density, view='dorsal')

# Plot ventral view
fig = plot_hipp_surf(label_gii.format(density=density), hemi=None, density=density, view='ventral')

Example 2: Plot Left and Right Hemispheres Separately

from hippunfold_plot.plotting import plot_hipp_surf
from hippunfold_plot.utils import get_resource_path

#get subfields for demonstrating plotting
label_gii = get_resource_path('tpl-avg_label-hippdentate_density-{density}_subfields.label.gii')
density = '1mm'

# Plot left hemisphere
fig = plot_hipp_surf(label_gii.format(density=density), hemi='left', density=density, view='dorsal')

# Plot right hemisphere
fig = plot_hipp_surf(label_gii.format(density=density), hemi='right', density=density, view='dorsal')

Example 3: Plot unfolded and canonical space separately

from hippunfold_plot.plotting import plot_hipp_surf
from hippunfold_plot.utils import get_resource_path

#get subfields for demonstrating plotting
label_gii = get_resource_path('tpl-avg_label-hippdentate_density-{density}_subfields.label.gii')
density = '1mm'

# Plot left hemisphere in unfolded space
fig = plot_hipp_surf(label_gii.format(density=density), space='unfold', density=density, view='dorsal')

# Plot left hemisphere in canonical space
fig = plot_hipp_surf(label_gii.format(density=density), space='canonical', density=density, view='dorsal')

🛠️ Functions

plot_hipp_surf

Plot hippocampal surface map.

This function plots a surface map of the hippocampus, which can be a label-hippdentate shape.gii, func.gii, or a Vx1 array (where V is the number of vertices in the hippocampus and dentate). Any arguments that can be supplied to nilearn's plot_surf() can also be applied here, overriding the defaults set below.

Parameters

• surf_map (str or array-like): The surface map to plot. This can be a file path to a .gii file or a Vx1 array.
• density (str, optional): The density of the surface map. Can be 'unfoldiso', '0p5mm', '1mm', or '2mm'. Default is '0p5mm'.
• hemi (str, optional): The hemisphere to plot. Can be 'left', 'right', or None (in which case both are plotted). Default is 'left'.
• space (str, optional): The space of the surface map. Can be 'canonical', 'unfold', or None (in which case both are plotted). Default is None.
• figsize (tuple, optional): The size of the figure. Default is (12, 8).
• dpi (int, optional): The resolution of the figure in dots per inch. Default is 300.
• vmin (float, optional): The minimum value for the color scale. Default is None.
• vmax (float, optional): The maximum value for the color scale. Default is None.
• colorbar (bool, optional): Whether to display a colorbar. Default is False.
• colorbar_shrink (float, optional): The shrink factor for the colorbar. Default is 0.25.
• cmap (str or colormap, optional): The colormap to use. Default is None.
• view (str, optional): The view of the surface plot. Default is 'dorsal'.
• avg_method (str, optional): The method to average the data. Default is 'median'.
• bg_on_data (bool, optional): Whether to display the background on the data. Default is True.
• alpha (float, optional): The alpha transparency level. Default is 0.1.
• darkness (float, optional): The darkness level of the background. Default is 2.
• axes (matplotlib.axes.Axes or list of matplotlib.axes.Axes, optional): Axes to plot on. If None, new axes will be created. If a single axis is provided, it will be used for a single plot. If multiple plots are to be made, a list of axes should be provided.
• figure (matplotlib.figure.Figure, optional): The figure to plot on. If None, a new figure will be created.
• **kwargs (dict): Additional arguments to pass to nilearn's plot_surf().

Returns

• figure (matplotlib.figure.Figure): The figure object.

Notes

By default, this function will plot one hemisphere (left by default) in both canonical and unfolded space. Both surfaces can be plotted with hemi=None, but the same surf_map will be plotted on both.

🧪 Testing

To run the tests, including unit tests and docstring tests, use the following command:

python -m unittest discover -s . -p "test_*.py"

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

🙌 Contributing

We welcome contributions and feedback! Please make a PR or post an issue.

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Happy plotting! 🎉