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isebenius / MIND

This repository contains a Python implementation of Morphometric INverse Divergence (MIND) calculation for the estimation of structural similarity networks in the brain
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Error Reading MGH Files #3

Open smile0227 opened 4 months ago

smile0227 commented 4 months ago

Dear Sebenius, I apologize for any inconvenience caused by reaching out to you. I am currently encountering an issue with retrieving cortical thickness values for each vertex within every brain region after smoothing. Below is the code I am using:

_surf_dir = 'K:/NC11' features = [('K:/NC11/surf/lh.thickness.fwhm10.fsaverage.mgh','K:/NC11/surf/rh.thickness.fwhm10.fsaverage.mgh')] parcellation = 'aparc' vertex_data, regions, features_used = get_vertex_df(surf_dir, features, parcellation)_

However, I am encountering the following error: _hemi_data[i + 1] = hemi_data_dict[feature] ValueError: could not broadcast input array from shape (163842,) into shape (138345,)_ It seems that this error arises from the dimensions of .thickness.fwhm10.fsaverage.mgh being 1638421, while lh.aparc.annot has dimensions of 138345*1.

Would you happen to have any insights on how to resolve this issue? Looking forward to your response. Best regards, Yanxi 2024.05.07

smile0227 commented 4 months ago

Dear Sebenius, I apologize for any inconvenience caused by reaching out to you. I am currently encountering an issue with retrieving cortical thickness values for each vertex within every brain region after smoothing. Below is the code I am using:

_surf_dir = 'K:/NC11' features = [('K:/NC11/surf/lh.thickness.fwhm10.fsaverage.mgh','K:/NC11/surf/rh.thickness.fwhm10.fsaverage.mgh')] parcellation = 'aparc' vertex_data, regions, features_used = get_vertex_df(surf_dir, features, parcellation)_

However, I am encountering the following error: _hemi_data[i + 1] = hemi_data_dict[feature] ValueError: could not broadcast input array from shape (163842,) into shape (138345,) It seems that this error arises from the dimensions of .thickness.fwhm10.fsaverage.mgh being 163842_1, while lh.aparc.annot has dimensions of 138345*1.

Would you happen to have any insights on how to resolve this issue? Looking forward to your response. Best regards, Yanxi 2024.05.07

I think I understand now. I should read lh.aparc.annot in the fsaverage space instead of individual space.