def MultiNiftiOverlap(niftiPath1, coordsPath, subject_id, subjects_dir):
#for whatever reason, it seems that left and right are switched here.
# at least this is what I infer from the nifti. Right side niftis
# have lower x values than left side niftis, which one wouldnt usualy
# expect, but whatever. It serves as the appropriate check
niftiVol = nib.load(niftiPath1)
niftiData = niftiVol.get_data()
nonZeros = np.nonzero(niftiData)
niftiDimensions = niftiData.shape
xDim = niftiDimensions[1]
averageXcoord = np.mean(nonZeros[0])
if averageXcoord < xDim / 2:
side = 'lh'
else:
side = 'rh'
print(niftiPath1)
brain = Brain(subject_id=subject_id,
hemi=side,
surf="inflated",
background="white",
subjects_dir=subjects_dir)
#set this up for each system, I guess
os.environ['FREESURFER_HOME'] = '/Applications/freesurfer/'
os.environ['SUBJECTS_DIR'] = subjects_dir
#print os.environ['SUBJECTS_DIR']
steps = [float(i) for i in [0, 8, .1]]
#NOTE: FIBER 2 IS ACTUALLY THE ECOG PLOT HERE.
epi_img = nib.load(niftiPath1)
epi_img_data = epi_img.get_fdata()
np.unique(epi_img_data.data)
#unique, counts = np.unique(epi_img_data.data, return_counts=True)
#dict(zip(unique, counts))
fib1_surf_data = io.project_volume_data(filepath=niftiPath1,
hemi=side,
subject_id=subject_id,
projsum='max',
smooth_fwhm=5,
projmeth='dist',
projarg=steps)
#fib1_surf_data = io.project_volume_data(filepath=niftiPath1, hemi=side, subject_id=subject_id, projsum='max', smooth_fwhm=5)
#Just scale the data I guess? Something is being messed with in the data.
#fib1Max=max(fib1_surf_data)
#thresh1=np.median(fib1_surf_data[np.nonzero(fib1_surf_data)])
#print(thresh1)
#coords2=[]
coords = readcsv(coordsPath)
#padCoord=np.zeros((1,3))
#coords2=np.concatenate((coords,padCoord),axis=0)
fsPath = subjects_dir + subject_id + '/'
interpolatedCoords = interpolate_coords_to_GM(fsPath, coords)
#interpolatedCoords=rewarp_coords(fsPath,coords)
brain.add_data(fib1_surf_data,
0,
1000,
150,
colormap="hsv",
alpha=.68,
hemi=side)
# colorwords=['red',
# 'blue',
# 'green',
# 'black',
# 'purple',
# 'cyan',
# 'yellow',
# 'pink'
# 'orange']
#
# coordsSize=interpolatedCoords.shape
#
# print(interpolatedCoords)
# for iCoords in range(coordsSize[0]):
brain.add_foci(interpolatedCoords,
map_surface='white',
color="black",
scale_factor=.5)
# print(interpolatedCoords[iCoords])
# print(colorwords[iCoords])
# brain.add_foci(interpolatedCoords[iCoords], map_surface='white', color=colorwords[iCoords], scale_factor=.5)
figdir = os.path.join(subjects_dir, subject_id, 'Figures/')
filename1 = os.path.basename(niftiPath1)
#i have no idea why this picks the first ., but it works.
filedotIndex1 = filename1.index('.')
coordName = os.path.basename(coordsPath)
coordName = coordName.replace('.csv', '')
filetitle1 = filename1[0:filedotIndex1] + '_' + coordName
if not os.path.exists(figdir):
os.makedirs(figdir)
#views=[(-45,27.5),(-45,90),(45,90),(-90,135),(-225,27.5),(-315,27.5),(-45,-27.5),(-135,-27.5),(-225,-27.5),(-315,-27.5),(0,0),(0,-27.5),(0,27.5)]
if side == 'rh':
views = [(-45, 27.5), (-45, 110), (45, 90), (-90, 135), (-315, 27.5),
(90, -180), (0, 27.5), (-100, 80), (-120, 105), (0, 90),
(90, 90)]
else:
views = [(-135, 27.5), (-135, 110), (135, 90), (90, -135),
(315, -27.5), (90, -180), (0, -27.5), (100, -80), (120, -105),
(0, -90), (90, 90)]
for iviews in np.arange(len(views)):
mayavi.mlab.view(azimuth=views[iviews][0], elevation=views[iviews][1])
figName = filetitle1 + str(iviews) + '.png'
curFileName = os.path.join(figdir, figName)
brain.save_single_image(curFileName)
labels[52], labels[53],
labels[68], labels[69]]
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
left_b = Brain(subject_id, hemi, surf)
# If the label lives in the normal place in the subjects directory,
# you can plot it by just using the name
for lbl in labels_list[::2]:
left_b.add_label(lbl, color="#2E2E2E")
left_b.add_label(lbl, borders=True, color="#F2F2F2")
left_b.save_single_image("left_hemi.png")
subject_id = "fsaverage"
hemi = "rh"
surf = "inflated"
right_b = Brain(subject_id, hemi, surf)
# If the label lives in the normal place in the subjects directory,
# you can plot it by just using the name
for lbl in labels_list[1::2]:
right_b.add_label(lbl, color="#2E2E2E")
right_b.add_label(lbl, borders=True, color="#F2F2F2")
right_b.save_single_image("right_hemi.png")
