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How would I got about saving a figure generated using composting as svg ?
Below I try savefig() but it saves the layers (here ROI labels and borders) as images, so editing in an svg editor later (for example changing color/thickness/size of ROI borders or labels) is not possible. The colorbar is saved as a separate layer which can be edited.
Without compositing, I can use make_svg(), which saves the ROIs (labels and borders) as paths(?) in a layer, so they are still editable. I don't think make_svg() supports composting since it requires braindata as the input (doesn't work with a figure already plotted).
I use composting for the ROIs but also to hilight a specific voxels (for example in seed-based analysis) and sometimes to separately plot different parts of the data (using composite.add_data()).
Cheers
importcorteximportmatplotlib.pyplotaspltimportnumpyasnp# Create a random volumevolume=cortex.Volume.random(subject='S1', xfmname='fullhead')
# Create basic figure, with rois, labels, sulci all offfig=cortex.quickflat.make_figure(volume,
with_curvature=True,
with_rois=False,
with_labels=False,
with_sulci=False)
# Add sulci in light yellow_=cortex.quickflat.composite.add_sulci(fig, volume,
with_labels=False,
linewidth=2,
linecolor=(0.9, 0.85, 0.5))
# Add all rois, with a particular color scheme:_=cortex.quickflat.composite.add_rois(fig, volume,
with_labels=False,
linewidth=1,
linecolor=(0.8, 0.8, 0.8))
# Highlight face- and body-selective ROIs:_=cortex.quickflat.composite.add_rois(fig, volume,
roi_list=['FFA', 'EBA', 'OFA'], # (This defaults to all rois if not specified)with_labels=True,
linewidth=5,
linecolor=(0.9, 0.5, 0.5),
roifill=(0.9, 0.5, 0.5),
fillalpha=0.35,
dashes=(5, 3) # Dash length & gap btw dashes
)
plt.savefig('chk.svg',format='svg')
plt.imshow()
The text was updated successfully, but these errors were encountered:
Hi guys,
How would I got about saving a figure generated using composting as svg ?
Below I try savefig() but it saves the layers (here ROI labels and borders) as images, so editing in an svg editor later (for example changing color/thickness/size of ROI borders or labels) is not possible. The colorbar is saved as a separate layer which can be edited.
Without compositing, I can use make_svg(), which saves the ROIs (labels and borders) as paths(?) in a layer, so they are still editable. I don't think make_svg() supports composting since it requires braindata as the input (doesn't work with a figure already plotted).
I use composting for the ROIs but also to hilight a specific voxels (for example in seed-based analysis) and sometimes to separately plot different parts of the data (using composite.add_data()).
Cheers
The text was updated successfully, but these errors were encountered: