def create_trans(subject, db_fs, db_bv, fname_out):
"""
Get transformations of the surface from a file that containes filename
matrix transformations
"""
trans_list = []
trans_name = [
op.join(db_fs, '{0}/mri/transforms/{0}_orig_TO_meshes.trm'), 'inv ' +
op.join(db_fs, '{0}/mri/transforms/orig_{0}_TO_Scanner_Based.trm'),
op.join(
db_bv,
'{0}/t1mri/default_acquisition/registration/RawT1-{0}_default_acquisition_TO_Scanner_Based.trm'
)
]
for name in trans_name:
split = name.split()
inv_bool = ('inv' == split[0])
if inv_bool:
name = split[1]
else:
name = split[0]
print(name)
format_name = name.format(subject)
print(format_name)
# if not os.path.exists(format_name):
# print("error, {} is not an existing path, will try to add \
# subject_dir {}".format(format_name, database))
#
# format_name = os.path.join(database, format_name)
# print(format_name)
# assert os.path.exists(format_name), "Breaking, even when add \
# subject_dir, file {} do not exists".format(name)
with open(format_name, 'r') as matfile:
lines = matfile.read().strip().split("\n")
lines_list = [l.split() for l in lines]
translation = lines_list.pop(0)
# transpose the rotations
transpose = list(zip(*lines_list))
# append translations
transpose.append(translation)
# create the matrix
mat_str = np.array(list(zip(*transpose)))
mat = mat_str.astype(np.float)
mat = np.vstack([mat, [0, 0, 0, 1]])
if inv_bool:
mat = inv(mat)
# add line por computing translation
trans_list.append(mat)
trans = None
for trans_cour in trans_list:
if trans is None:
trans = trans_cour
else:
trans = np.dot(trans, trans_cour)
if fname_out.endswith('fif'):
write_trans(fname_out, trans)
else:
with open(fname_out, 'w') as matfile:
# un autre nom semblerait judiceiux pour eviter la confuction
# avec le matfile de la partie precedente de la fonction
for i in range(len(trans)):
for j in range(len(trans[i])):
matfile.write(str(trans[i][j]) + ' ')
matfile.write('\n')
return trans
def create_trans(subject, fname, fname_out):
"""
Get transformations of the surface from a file that containes filename matrix transformations
"""
trans_list = []
with open(fname, 'r') as textfile:
trans_name = textfile.read().strip().split("\n")
for name in trans_name:
split = name.split()
inv_bool = ('inv' == split[0])
if inv_bool:
name = split[1]
else:
name = split[0]
name = name.format(subject)
with open(name, 'r') as matfile:
lines = matfile.read().strip().split("\n")
lines_list = [l.split() for l in lines]
translation = lines_list.pop(0)
#transpose the rotations
transpose = list(zip(*lines_list))
#append translations
transpose.append(translation)
#create the matrix
mat_str = np.array(list(zip(*transpose)))
#mat_str= np.array(lines_list)
mat = mat_str.astype(np.float)
mat = np.vstack([mat, [0, 0, 0, 1]])
if inv_bool:
mat = inv(mat)
#add line por computing translation
trans_list.append(mat)
res = None
trans = None
for trans_cour in trans_list:
if trans is None:
trans = trans_cour
else:
trans = np.dot(trans, trans_cour)
if fname_out.endswith('fif'):
write_trans(fname_out, trans)
else:
with open(fname_out, 'w') as matfile:
for i in range(len(trans)):
for j in range(len(trans[i])):
matfile.write(str(trans[i][j]) + ' ')
matfile.write('\n')
return trans
def create_trans(subject, fname, fname_out):
"""
Get transformations of the surface from a file that containes filename matrix transformations
"""
trans_list = []
with open(fname, 'r') as textfile:
trans_name = textfile.read().strip().split('\n')
for name in trans_name:
split = name.split()
inv_bool = ('inv' == split[0])
if inv_bool:
name = split[1]
else:
name = split[0]
name = name.format(subject)
with open(name, 'r') as matfile:
lines = matfile.read().strip().split('\r')
lines_list = [l.split() for l in lines]
translation = lines_list.pop(0)
# transpose the rotations
transpose = list(zip(*lines_list))
# append translations
transpose.append(translation)
# create the matrix
mat_str = np.array(list(zip(*transpose)))
mat = mat_str.astype(np.float)
mat = np.reshape(mat, (3, 4), order='F')
mat = np.vstack([mat, [1, 0, 0, 0]])
mat = np.transpose(mat)
mat = np.rot90(mat, 3)
# Neer to rotate
if inv_bool:
mat = inv(mat)
# add line por computing translation
trans_list.append(mat)
res = None
trans = None
# Why do we need the next loop?
for trans_cour in trans_list:
if trans is None:
trans = trans_cour
else:
trans = np.dot(trans, trans_cour)
if fname_out.endswith('fif'):
# Create Transform class
X = mne.Transform(1, 2, trans)
write_trans(fname_out, X)
else:
with open(fname_out, 'w') as matfile:
for i in range(len(trans)):
for j in range(len(trans[i])):
matfile.write(str(trans[i][j]) + ' ')
matfile.write('\n')
return trans
def contAvg_headpos(condition, method='median', folder=[], summary=False):
"""
Calculate average transformation from dewar to head coordinates, based
on the continous head position estimated from MaxFilter
Parameters
----------
condition : str
String containing part of common filename, e.g. "task" for files
task-1.fif, task-2.fif, etc. Consistent naiming of files is mandatory!
method : str
How to calculate "average, "mean" or "median" (default = "median")
folder : str
Path to input files. Default = current dir.
Returns
-------
MNE-Python transform object
4x4 transformation matrix
"""
# Check that the method works
method = method.lower()
if method not in ['median', 'mean']:
raise RuntimeError(
'Wrong method. Must be either \"mean\" or "median"!')
if not condition:
raise RuntimeError('You must provide a conditon!')
# Get and set folders
if not folder:
rawdir = getcwd() # [!] Match up with bash script !
else:
rawdir = folder
print(rawdir)
quatdir = op.join(rawdir, 'quat_files')
mean_trans_folder = op.join(rawdir, 'trans_files')
if not op.exists(mean_trans_folder): # Make sure output folder exists
mkdir(mean_trans_folder)
mean_trans_file = op.join(mean_trans_folder, condition + '-trans.fif')
if op.isfile(mean_trans_file):
warnings.warn(
'N"%s\" already exists is %s. Delete if you want to rerun' %
(mean_trans_file, mean_trans_folder), RuntimeWarning)
return
# Change to subject dir
files2combine = find_condition_files(quatdir, condition)
files2combine.sort()
if not files2combine:
raise RuntimeError('No files called \"%s\" found in %s' %
(condition, quatdir))
allfiles = []
for ff in files2combine:
fl = ff.split('_')[0]
tmplist = [f for f in listdir(quatdir) if fl in f and '_quat' in f]
#Fix order
if len(tmplist) > 1:
tmplist.sort()
if any("-" in f for f in tmplist):
firstfile = tmplist[
-1] # The file without a number will always be last!
tmpfs = sorted(tmplist[:-1],
key=lambda a: int(re.split('-|.fif', a)[-2])
) # Assuming consistent naming!!!
tmplist[0] = firstfile
tmplist[1:] = tmpfs
allfiles = allfiles + tmplist
if len(allfiles) > 1:
print('Files used for average head pos:')
for ib in range(len(allfiles)):
print('{:d}: {:s}'.format(ib + 1, allfiles[ib]))
else:
print('Will find average head pos in %s' % files2combine)
# LOAD DATA
# raw = read_raw_fif(op.join(quatdir,firstfile), preload=True, allow_maxshield=True, verbose=False).pick_types(meg=False, chpi=True)
# Use files2combine instead of allfiles as MNE will find split files automatically.
for idx, ffs in enumerate(files2combine):
if idx == 0:
raw = read_raw_fif(op.join(quatdir, ffs),
preload=True,
allow_maxshield=True).pick_types(meg=False,
chpi=True)
else:
raw.append(
read_raw_fif(op.join(quatdir, ffs),
preload=True,
allow_maxshield=True).pick_types(meg=False,
chpi=True))
quat, times = raw.get_data(return_times=True)
gof = quat[6, ] # Godness of fit channel
# fs = raw.info['sfreq']
# In case "record raw" started before "cHPI"
if np.any(gof < 0.98):
begsam = np.argmax(gof > 0.98)
raw.crop(tmin=raw.times[begsam])
quat = quat[:, begsam:].copy()
times = times[begsam:].copy()
# Make summaries
if summary:
plot_movement(quat, times, dirname=rawdir, identifier=condition)
total_dist_moved(quat,
times,
write=True,
dirname=rawdir,
identifier=condition)
# Get continous transformation
print('Reading transformation. This will take a while...')
H = np.empty([4, 4, len(times)]) # Initiate transforms
init_rot_angles = np.empty([len(times), 3])
for i, t in enumerate(times):
Hi = np.eye(4, 4)
Hi[0:3, 3] = quat[3:6, i].copy()
Hi[:3, :3] = quat_to_rot(quat[0:3, i])
init_rot_angles[i, :] = rotation_angles(Hi[:3, :3])
assert (np.sum(Hi[-1]) == 1.0) # sanity check result
H[:, :, i] = Hi.copy()
if method in ["mean"]:
H_mean = np.mean(H, axis=2) # stack, then average over new dim
mean_rot_xfm = rotation3d(*tuple(
np.mean(init_rot_angles,
axis=0))) # stack, then average, then make new xfm
elif method in ["median"]:
H_mean = np.median(H, axis=2) # stack, then average over new dim
mean_rot_xfm = rotation3d(*tuple(
np.median(init_rot_angles,
axis=0))) # stack, then average, then make new xfm
H_mean[:3, :3] = mean_rot_xfm
assert (np.sum(H_mean[-1]) == 1.0) # sanity check result
# Create the mean structure and save as .fif
mean_trans = raw.info['dev_head_t'] # use the last info as a template
mean_trans['trans'] = H_mean.copy()
# Write file
write_trans(mean_trans_file, mean_trans)
print("Wrote " + mean_trans_file)
return mean_trans
def initAvg_headpos(condition=[], folder=[]):
"""
Write the average head position based of the initial fit of several
independent files and save to a trans fif file
Parameters
----------
condition : str
String containing part of common filename, e.g. "task" for files
task_a.fif, task_b.fif, etc. Consistent naiming of files is mandatory!
If no condition is provided, it will average all files in folder.
folder : str
Path to input files. Default = current dir.
Returns
-------
None
"""
if not folder:
rawdir = getcwd()
else:
rawdir = folder
# Change to subject dir
if not condition:
files2combine = listdir(rawdir)
print('Using all files in %s' % rawdir)
else:
files2combine = glob.glob('%s*' % condition)
if not files2combine:
print('No files called \"%s\" found in %s' % (condition, rawdir))
return
elif len(files2combine) < 2:
warnings.warn(
'Only one file, please check!',
RuntimeWarning) # [!!!] should it just copy the initial headpos?
# Define output
mean_trans_folder = path.join(rawdir, 'trans_files')
if not path.exists(mean_trans_folder):
mkdir(mean_trans_folder)
mean_trans_file = path.join(mean_trans_folder, condition + '-trans.fif')
if op.isfile(mean_trans_file):
warnings.warn(
'N"%s\" already exists is %s. Delete if you want to rerun' %
(mean_trans_file, mean_trans_folder), RuntimeWarning)
return
files2combine = [f for f in files2combine
if '.fif' in f] # Make sure only fif files
files2combine.sort()
print('Files used for average head pos:')
for ib in range(len(files2combine)):
print('{:d}: {:s}'.format(ib + 1, files2combine[ib]))
init_xfm = []
init_rot = []
for ff in files2combine:
fname = path.join(rawdir, ff) # first file is enough NOT ANYMORE!
with warnings.catch_warnings(
): # suppress some annoying warnings for now
warnings.simplefilter("ignore")
info = Raw(fname,
preload=False,
verbose=False,
allow_maxshield=True).info
print(
'Ignore the warning above. We\'ll run MaxFilter in a few moments...'
)
init_xfm += [info['dev_head_t']['trans']]
# translations: info['dev_head_t']['trans'][:, 3][:-1]
init_rot += [info['dev_head_t']['trans'][:3, :3]]
mean_init_xfm = np.mean(np.stack(init_xfm),
axis=0) # stack, then average over new dim
init_rot_angles = [rotation_angles(m) for m in init_rot]
mean_init_rot_xfm = rotation3d(*tuple(
np.mean(np.stack(init_rot_angles),
axis=0))) # stack, then average, then make new xfm
assert (np.sum(mean_init_xfm[-1]) == 1.0) # sanity check result
mean_trans = info['dev_head_t'] # use the last info as a template
mean_trans['trans'] = mean_init_xfm # replace the transformation
mean_trans[
'trans'][:3, :3] = mean_init_rot_xfm # replace the rotation part
mean_init_headpos = mean_trans['trans'][:-1, -1] # meters
print('Mean head position (device coords): ({:.1f}, {:.1f}, {:.1f}) mm'.\
format(*tuple(mean_init_headpos*1e3)))
print('Discrepancies from mean:')
for ib, xfm in enumerate(init_xfm):
diff = 1e3 * (xfm[:-1, -1] - mean_init_headpos)
rmsdiff = np.linalg.norm(diff)
print('\tSession {:d}: norm {:.1f} mm ({:.1f}, {:.1f}, {:.1f}) mm '.\
format(ib + 1, rmsdiff, *tuple(diff)))
mean_rots = rotation_angles(
mean_trans['trans'][:3, :3]) # these are in radians
mean_rots_deg = tuple([180. * rot / np.pi
for rot in mean_rots]) # convert to deg
print('Mean head rotations (around x, y & z axes): ({:.1f}, {:.1f}, {:.1f}) deg'.\
format(*mean_rots_deg))
print('Block discrepancies from mean:')
for ib, rot in enumerate(init_rot):
cur_rots = rotation_angles(rot)
diff = tuple([
180. * cr / np.pi - mr for cr, mr in zip(cur_rots, mean_rots_deg)
])
print('\tSession {:d}: ({:.1f}, {:.1f}, {:.1f}) deg '.\
format(ib + 1, *tuple(diff)))
# Write trans file
write_trans(mean_trans_file, mean_trans)
print("Wrote " + mean_trans_file)
def contAvg_headpos(condition, method='median', folder=[]):
"""
Calculate average transformation from dewar to head coordinates, based
on the continous head position estimated from MaxFilter
Parameters
----------
condition : str
String containing part of common filename, e.g. "task" for files
task-1.fif, task-2.fif, etc. Consistent naiming of files is mandatory!
method : str
How to calculate "average, "mean" or "median" (default = "median")
folder : str
Path to input files. Default = current dir.
Returns
-------
MNE-Python transform object
4x4 transformation matrix
"""
# Check that the method works
if method not in ['median', 'mean']:
raise RuntimeError(
'Wrong method. Must be either \"mean\" or "median"!')
if not condition:
raise RuntimeError('You must provide a conditon!')
# Get and set folders
if not folder:
rawdir = getcwd() # [!] Match up with bash script !
else:
rawdir = folder
print(rawdir)
quatdir = op.join(rawdir, 'quat_files')
mean_trans_folder = op.join(rawdir, 'trans_files')
if not op.exists(mean_trans_folder): # Make sure output folder exists
mkdir(mean_trans_folder)
mean_trans_file = op.join(mean_trans_folder, condition + '-trans.fif')
if op.isfile(mean_trans_file):
raise RuntimeError(
'N"%s\" already exists is %s. Delete aif you want to rerun' %
(mean_trans_file, mean_trans_folder))
# Change to subject dir
# files2combine = glob.glob('%s*' % condition)
files2combine = [
f for f in listdir(quatdir) if condition in f and '_quat' in f
]
if not files2combine:
raise RuntimeError('No files called \"%s\" found in %s' %
(condition, quatdir))
elif len(files2combine) > 1:
print('Files used for average head pos:')
for ib in range(len(files2combine)):
print('{:d}: {:s}'.format(ib + 1, files2combine[ib]))
else:
print('Will find average head pos in %s' % files2combine)
# LOAD DATA
for idx, ffs in enumerate(files2combine):
# print op.join(quatdir,ffs)
if idx == 0:
raw = read_raw_fif(op.join(quatdir, ffs),
preload=True,
allow_maxshield=True).pick_types(meg=False,
chpi=True)
else:
raw.append(
read_raw_fif(op.join(quatdir, ffs),
preload=True,
allow_maxshield=True).pick_types(meg=False,
chpi=True))
quat, times = raw.get_data(return_times=True)
gof = quat[6, ] # Godness of fit channel
fs = raw.info['sfreq']
# In case "record raw" started before "cHPI"
if np.any(gof < 0.98):
begsam = np.argmax(gof > 0.98)
raw.crop(tmin=raw.times[begsam])
quat = quat[:, begsam:].copy()
times = times[begsam:].copy()
# Get continous transformation
print('Reading transformation. This will take a while...')
H = np.empty([4, 4, len(times)]) # Initiate transforms
init_rot_angles = np.empty([len(times), 3])
for i, t in enumerate(times):
Hi = np.eye(4, 4)
Hi[0:3, 3] = quat[3:6, i].copy()
Hi[:3, :3] = quat_to_rot(quat[0:3, i])
init_rot_angles[i, :] = rotation_angles(Hi[:3, :3])
assert (np.sum(Hi[-1]) == 1.0) # sanity check result
H[:, :, i] = Hi.copy()
if method in ["mean"]:
H_mean = np.mean(H, axis=2) # stack, then average over new dim
mean_rot_xfm = rotation3d(*tuple(
np.mean(init_rot_angles,
axis=0))) # stack, then average, then make new xfm
elif method in ["median"]:
H_mean = np.median(H, axis=2) # stack, then average over new dim
mean_rot_xfm = rotation3d(*tuple(
np.median(init_rot_angles,
axis=0))) # stack, then average, then make new xfm
H_mean[:3, :3] = mean_rot_xfm
assert (np.sum(H_mean[-1]) == 1.0) # sanity check result
# Create the mean structure and save as .fif
mean_trans = raw.info['dev_head_t'] # use the last info as a template
mean_trans['trans'] = H_mean.copy()
# plot_alignment(raw.info,subject='0406',subjects_dir='/home/mikkel/PD_motor/fs_subjects_dir/',dig=True, meg='helmet')
# Write file
write_trans(mean_trans_file, mean_trans)
print("Wrote " + mean_trans_file)
return mean_trans
if len(sys.argv) != 3:
print("usage: {} subject $ds".format(sys.argv[0]))
sys.exit(1)
subject = sys.argv[1]
dsname = sys.argv[2]
try:
FShome = os.environ['FREESURFER_HOME']
except KeyError:
print("You must set the FREESURFER_HOME environment variable!")
sys.exit(1)
try:
Subjdir = os.environ['SUBJECTS_DIR']
except KeyError:
Subjdir = op.join(FShome, "subjects")
print("Note: Using the default SUBJECTS_DIR:", Subjdir)
name = op.join(Subjdir, subject, "bem", "{}-fiducials.fif".format(subject))
fids = read_fiducials(name)
fidc = _fiducial_coords(fids[0])
raw = read_raw_ctf(dsname, clean_names = True, preload = False)
fidd = _fiducial_coords(raw.info['dig'])
xform = fit_matched_points(fidd, fidc, weights = [1, 10, 1])
t = Transform(FIFF.FIFFV_COORD_HEAD, FIFF.FIFFV_COORD_MRI, xform)
name = op.join(Subjdir, subject, "bem", "{}-trans.fif".format(subject))
write_trans(name, t)