def load_modules_or_scalars(self, params):
if not params.mat:
self.error_dialog('You must specify a valid matrix file')
return
if params.whichkind == 'scalars' and not params.measure_name:
self.error_dialog('Cannot leave scalar name blank. cvu uses '
'this value as a dictionary index')
return
import preprocessing
try:
ci = preprocessing.loadmat(params.mat,
field=params.field_name,
is_adjmat=False)
except (CVUError, IOError) as e:
self.error_dialog(str(e))
return
if params.mat_order:
try:
init_ord, bads = preprocessing.read_ordering_file(
params.mat_order)
except (IndexError, UnicodeDecodeError) as e:
self.error_dialog(str(e))
return
#delete the bads
if not params.ignore_deletes:
ci = np.delete(ci, bads)
#perform the swapping
try:
ci_ord = preprocessing.adj_sort(init_ord, self.labnam)
except CVUError as e:
self.error_dialog(str(e))
return
except KeyError as e:
self.error_dialog('Field not found: %s' % str(e))
return
ci = ci[ci_ord]
try:
ci = np.reshape(ci, (self.nr_labels, ))
except ValueError as e:
self.error_dialog('The %s file is of size %i after deletions, but '
'the dataset has %i regions' %
(params.whichkind, len(ci), self.nr_labels))
return
if params.whichkind == 'modules':
import bct
self.modules = bct.ci2ls(ci)
self.nr_modules = len(self.modules)
elif params.whichkind == 'scalars':
self.save_scalar(params.measure_name, ci)
params._increment_scalar_count()
def preproc(args):
import preprocessing as pp
#load label names from specified text file for ordering
labnam,_ = pp.read_ordering_file(args['parcorder'])
#load adjacency matrix and put entries in order of labnam
adj = pp.loadmat(args['adjmat'],args['field'])
adj = pp.flip_adj_ord(adj, args['adjorder'], labnam)
#load surface for visual display
surf_fname = os.path.join(
args['subjdir'],args['subject'],'surf','lh.%s'%args['surftype'])
srf, geom_format = pp.loadsurf(surf_fname,args['surftype'])
#load parcellation and vertex positions
labels = pp.loadannot(
geom_format,
args['parc'], args['subject'], args['subjdir'], labnam=labnam,
surf_type=args['surftype'], surf_struct=srf, quiet=args['quiet'])
#calculate label positions from vertex positions
if args['subject']=='fsavg5':
lab_pos,labv = pp.calcparc(labels,labnam,quiet=args['quiet'],
parcname=args['parc'])
else:
lab_pos,labv = pp.calcparc(labels,labnam,quiet=args['quiet'],
parcname=args['parc'],subjdir=args['subjdir'],
subject=args['subject'],
lhsurf=srf.lh_verts,rhsurf=srf.rh_verts)
dataset_name='sample_data'
from utils import DisplayMetadata
sample_metadata=DisplayMetadata(subject_name=args['subject'],
parc_name=args['parc'],adj_filename=args['adjmat'])
from dataset import Dataset
sample_dataset=Dataset(dataset_name,lab_pos,labnam,srf,labv,
adj=adj,soft_max_edges=args['maxedges'],
gui=ErrorHandler(args['quiet']))
# pass an ErrorHandler as the current GUI to handle errors. Replace it later.
# Package dataloc and modality into tuple for passing
exec_script = args['script']
return sample_dataset,sample_metadata,exec_script
def load_modules_or_scalars(self,params):
if not params.mat:
self.error_dialog('You must specify a valid matrix file'); return
if params.whichkind=='scalars' and not params.measure_name:
self.error_dialog('Cannot leave scalar name blank. cvu uses '
'this value as a dictionary index'); return
import preprocessing
try:
ci=preprocessing.loadmat(params.mat, field=params.field_name,
is_adjmat=False)
except (CVUError,IOError) as e: self.error_dialog(str(e)); return
if params.mat_order:
try:
init_ord, bads = preprocessing.read_ordering_file(
params.mat_order)
except (IndexError,UnicodeDecodeError) as e:
self.error_dialog(str(e)); return
#delete the bads
if not params.ignore_deletes:
ci=np.delete(ci,bads)
#perform the swapping
try:
ci_ord = preprocessing.adj_sort(init_ord, self.labnam)
except CVUError as e: self.error_dialog(str(e)); return
except KeyError as e:
self.error_dialog('Field not found: %s'%str(e)); return
ci=ci[ci_ord]
try:
ci=np.reshape(ci,(self.nr_labels,))
except ValueError as e:
self.error_dialog('The %s file is of size %i after deletions, but '
'the dataset has %i regions' %
(params.whichkind, len(ci), self.nr_labels)); return
if params.whichkind=='modules':
import bct
self.modules=bct.ci2ls(ci)
self.nr_modules=len(self.modules)
elif params.whichkind=='scalars':
self.save_scalar(params.measure_name,ci)
params._increment_scalar_count()