def mat_to_ply():
fol = '/homes/5/npeled/space1/Angelique/Lionel Recon/'
files = glob.glob(op.join(fol, 'Iso*.mat'))
avg_fname = op.join(fol, 'blender', 'mean_vertices.npy')
if not op.isfile(avg_fname):
vertices_avg = []
for f in files:
print(f)
m = utils.read_mat_file_into_bag(f)
vertices_avg.append(np.mean(m.vertices.T / 10, 0))
m.clear()
vertices_avg = np.mean(vertices_avg)
np.save(avg_fname, vertices_avg)
else:
vertices_avg = np.load(avg_fname)
for f in files:
print(f)
m = utils.read_mat_file_into_bag(f)
ply_fname = utils.change_fname_extension(f, 'ply')
utils.write_ply_file(m.vertices.T / 10.0 - vertices_avg , m.faces.T, ply_fname, True)
m.clear()
def read_psd_mat_file(subject, psd_fname, stim_channel):
x = utils.read_mat_file_into_bag(psd_fname)
labels = get_labels(x)
data = x.psd if 'psd' in x else x.Psd
if 'time' in x:
time = x.time.reshape((x.time.shape[1]))
else:
time = None
freqs = [(0, 4), (4, 8), (8, 15), (15, 30), (30, 55), (65, 100)]
# plt.plot(time, psd[0, 0, :])
# plt.show()
out_fol = op.join(BLENDER_ROOT_DIR, subject, 'electrodes')
utils.make_dir(out_fol)
np.savez(op.join(out_fol, 'psd_{}'.format(stim_channel)), labels=labels, psd=data, time=time, freqs=freqs)
def get_labels(x=None, mat_fname=''):
if mat_fname != '':
x = utils.read_mat_file_into_bag(mat_fname)
if x is None:
raise Exception('x is None!')
labels = x['Label']
labels = labels.reshape((len(labels)))
fix_labels = []
for label in labels:
label = label[0]
elecs = label.split('-')
group, elc1_name = utils.elec_group_number(elecs[0], False)
_, elc2_name = utils.elec_group_number(elecs[1], False)
fix_labels.append('{0}{2}-{0}{1}'.format(group, elc1_name, elc2_name))
return sorted(fix_labels, key=utils.natural_keys)
def get_labels(x=None, mat_fname=''):
if mat_fname != '':
x = utils.read_mat_file_into_bag(mat_fname)
if x is None:
raise Exception('x is None!')
labels = x['Label']
labels = labels.reshape((len(labels)))
fix_labels = []
for label in labels:
label = label[0]
elecs = label.split('-')
group, elc1_name = utils.elec_group_number(elecs[0], False)
_, elc2_name = utils.elec_group_number(elecs[1], False)
fix_labels.append('{0}{2}-{0}{1}'.format(group, elc1_name, elc2_name))
return sorted(fix_labels, key=utils.natural_keys)
def read_new_psd_mat_file(subject, psd_fname, stim_channel, labels):
x = utils.read_mat_file_into_bag(psd_fname)
psd = None
freqs = [(0, 4), (4, 8), (8, 15), (15, 30), (30, 55), (65, 100)]
F = len(freqs)
for ind, field in enumerate(['P{}'.format(ind) for ind in range(1, F + 1)]):
if psd is None:
T, L = x[field].shape
psd = np.zeros((F, T, L))
psd[ind, :, :] = x[field]
del x
time = range(psd.shape[1])
# plt.plot(time, psd[0, 0, :])
# plt.show()
out_fol = op.join(BLENDER_ROOT_DIR, subject, 'electrodes')
utils.make_dir(out_fol)
np.savez(op.join(out_fol, 'psd_{}'.format(stim_channel)), labels=labels, psd=psd, time=time, freqs=freqs)
def read_psd_mat_file(subject, psd_fname, stim_channel):
x = utils.read_mat_file_into_bag(psd_fname)
labels = get_labels(x)
data = x.psd if 'psd' in x else x.Psd
if 'time' in x:
time = x.time.reshape((x.time.shape[1]))
else:
time = None
freqs = [(0, 4), (4, 8), (8, 15), (15, 30), (30, 55), (65, 100)]
# plt.plot(time, psd[0, 0, :])
# plt.show()
out_fol = op.join(BLENDER_ROOT_DIR, subject, 'electrodes')
utils.make_dir(out_fol)
np.savez(op.join(out_fol, 'psd_{}'.format(stim_channel)),
labels=labels,
psd=data,
time=time,
freqs=freqs)
def read_new_psd_mat_file(subject, psd_fname, stim_channel, labels):
x = utils.read_mat_file_into_bag(psd_fname)
psd = None
freqs = [(0, 4), (4, 8), (8, 15), (15, 30), (30, 55), (65, 100)]
F = len(freqs)
for ind, field in enumerate(['P{}'.format(ind)
for ind in range(1, F + 1)]):
if psd is None:
T, L = x[field].shape
psd = np.zeros((F, T, L))
psd[ind, :, :] = x[field]
del x
time = range(psd.shape[1])
# plt.plot(time, psd[0, 0, :])
# plt.show()
out_fol = op.join(BLENDER_ROOT_DIR, subject, 'electrodes')
utils.make_dir(out_fol)
np.savez(op.join(out_fol, 'psd_{}'.format(stim_channel)),
labels=labels,
psd=psd,
time=time,
freqs=freqs)
