center_anchor = 1
if subject_id == 'lausanne125':
parc_file = os.path.join(
'/Applications/freesurfer/subjects/', subject_id, 'label',
hemi + '.myaparc_' + str(parc_scale) + '.annot')
elif subject_id == 'fsaverage':
parc_file = os.path.join(
'/Users/lindenmp/Google-Drive-Penn/work/research_projects/normative_neurodev_cs_t1/figs_support/Parcellations/FreeSurfer5.3/fsaverage/label/',
hemi + '.Schaefer2018_' + str(parc_scale) +
'Parcels_17Networks_order.annot')
brain_plot(roi_data,
parcel_names,
parc_file,
fig_str,
subject_id=subject_id,
hemi=hemi,
color='coolwarm',
center_anchor=center_anchor)
# # Figures
# In[18]:
f, ax = plt.subplots(1)
f.set_figwidth(1)
f.set_figheight(1)
limit = 3
sns.heatmap(np.zeros((1, 1)),
annot=False,
for pc in np.arange(0,n_components):
roi_data = pca.components_[pc,:]
for hemi in ('lh', 'rh'):
fig_str = hemi + '_' + metric + '_pc_' + str(pc)
figs_to_delete.append('ventral_'+fig_str)
figs_to_delete.append('med_'+fig_str)
figs_to_delete.append('lat_'+fig_str)
if subject_id == 'lausanne125':
parc_file = os.path.join('/Applications/freesurfer/subjects/', subject_id, 'label', hemi + '.myaparc_' + str(parc_scale) + '.annot')
elif subject_id == 'fsaverage':
parc_file = os.path.join('/Users/lindenmp/Google-Drive-Penn/work/research_projects/normative_neurodev_cs_t1/figs_support/Parcellations/FreeSurfer5.3/fsaverage/label/',
hemi + '.Schaefer2018_' + str(parc_scale) + 'Parcels_17Networks_order.annot')
# project subject's data to vertices
brain_plot(roi_data, parcel_names, parc_file, fig_str, subject_id = subject_id, hemi = hemi, surf = 'inflated', showcolorbar = False)
# In[21]:
for pc in np.arange(0,n_components):
f, axes = plt.subplots(2, 2)
f.set_figwidth(3)
f.set_figheight(4)
plt.subplots_adjust(wspace=0, hspace=-0.465)
print(metric, pc)
# column 0:
fig_str = 'lh_'+metric+'_pc_'+str(pc)+'.png'
try:
if subject_id == 'lausanne125':
parc_file = os.path.join(
'/Applications/freesurfer/subjects/', subject_id, 'label',
hemi + '.myaparc_' + str(parc_scale) + '.annot')
elif subject_id == 'fsaverage':
parc_file = os.path.join(
'/Users/lindenmp/Dropbox/Work/ResProjects/NormativeNeuroDev_CrossSec_T1/figs_support/Parcellations/FreeSurfer5.3/fsaverage/label/',
hemi + '.Schaefer2018_' + str(parc_scale) +
'Parcels_17Networks_order.annot')
# project subject's data to vertices
brain_plot(roi_data,
parcel_names,
parc_file,
fig_str,
subject_id=subject_id,
hemi=hemi,
surf='inflated',
center_anchor=1,
color='hot')
# In[37]:
for pheno in phenos:
for metric in metrics:
for hemi in ('lh', 'rh'):
print(pheno, metric)
# Plots of univariate pheno correlation
fig_str = hemi + '_' + pheno + '_' + metric + '_z'
roi_data = df_pheno_z.loc[pheno].filter(regex=metric,
axis=0)['coef'].values