def _load_adjmat_check(self):
acw=self.adjmat_chooser_window
if not acw.finished: return
import preprocessing as pp
adj_struct = pp.process_adj(acw.ctl,self)
if adj_struct is None: return #preprocessing returned an error
adj,soft_max_edges,adj_filename = adj_struct
acw.ctl.ds_ref._load_adj(adj, soft_max_edges, acw.ctl.require_ls,
acw.ctl.suppress_extra_rois)
self.controller.update_display_metadata(acw.ctl.ds_ref.name,
adj_filename=adj_filename)
def _load_adjmat_check(self):
acw = self.adjmat_chooser_window
if not acw.finished: return
import preprocessing as pp
adj_struct = pp.process_adj(acw.ctl, self)
if adj_struct is None: return #preprocessing returned an error
adj, soft_max_edges, adj_filename = adj_struct
acw.ctl.ds_ref._load_adj(adj, soft_max_edges, acw.ctl.require_ls,
acw.ctl.suppress_extra_rois)
self.controller.update_display_metadata(acw.ctl.ds_ref.name,
adj_filename=adj_filename)
def load_adj(matrix, dataset, ordering=None, ignore_deletes=False, max_edges=0,
field_name=None, required_rois=[], suppress_extra_rois=False):
"""
Loads a matrix. This function is a scripting helper. In other words,
instead of clicking on the GUI or simulating button presses, this
function is provided for scripting purposes to just simulate the
process of loading a matrix into a dataset.
Parameters
----------
matrix : str | instance(np.ndarray)
Filename of an adjacency matrix in a supported format (numpy, matlab,
or plaintext). Can also be a numpy matrix.
dataset : instance(cvu.dataset.Dataset)
The dataset into which to place this adjacency matrix
ordering : None | str | list(str)
Filename of an ordering file describing the matrix order. Default
value is None. If None, matrix is assumed to be in parcellation order.
Can just be a list of label names.
ignore_deletes : bool
If True, 'delete' entries in the ordering file are ignored.
Default value is False.
max_edges : int
Default 0. Leave as default or see wiki documentation.
field_name : None | str
Needed to tell the field name of a matlab matrix. Required for
matlab matrices, otherwise ignored
required_rois : list(str)
A list of ROIs whose labels must be shown in the circle plot.
The default value is the empty list, signifying no restrictions.
suppress_extra_rois : bool
If true, only the ROIs in required_rois are shown on the circle
plot.
"""
# '''
#Loads a matrix. This function is meant to be a scripting helper. In
#other words, instead of clicking on the GUI buttons (or simulating button
#presses) one could provide the requisite files for this operation inside a
#script by just calling this function).
#
#Arguments:
# matrix, Filename of an adjacency matrix in a supported format
# (numpy, matlab, plaintext). Can also just be a numpy
# matrix.
# dataset, A reference to the dataset that should contain this
# ordering, Filename of an ordering file. Defaults to None. If None,
# the matrix is assumed to be in parcellation order. Can also
# simply be a list of ROIs.
# ignore_deletes If true, 'delete' entries in the ordering file are
# ignored. Defaults to false.
# max_edges A number. Defaults to 0. If in doubt see wiki documentation.
# field_name Only needed for matlab .mat files. Specifies the field name
# of the matrix.
# required_rois A list of ROIs that must be included in the circle plot.
# Defaults to the empty list.
# suppress_extra_rois If true, only the ROIs in required_rois are shown
# on the circle plot.
#
#Returns:
# None
# '''
gui = globals()['self'] #explicitly allow dynamic scope
err_handler = ErrorHandler(quiet=True)
from preprocessing import process_adj
from options_struct import AdjmatChooserParameters
from dataset import Dataset
if not isinstance(dataset, Dataset):
print "must supply a valid dataset!"
return
adjmat_params = AdjmatChooserParameters(adjmat = matrix,
adjmat_order = ordering, ignore_deletes = ignore_deletes,
max_edges=max_edges, field_name=field_name, require_ls=required_rois,
suppress_extra_rois=suppress_extra_rois, ds_ref = dataset)
adj_struct = process_adj(adjmat_params, err_handler)
if adj_struct is None: #preprocessing errored out
return
adj, soft_max_edges, _ = adj_struct
dataset._load_adj(adj, soft_max_edges, required_rois, suppress_extra_rois)
gui.controller.update_display_metadata(dataset.name,
adj_filename=matrix if isinstance(matrix,str) else 'custom')