def dist_calc_matrix(surf, cortex, labels, exceptions = ['Unknown', 'Medial_wall'], verbose = True):
"""
Calculate exact geodesic distance along cortical surface from set of source nodes.
"labels" specifies the freesurfer label file to use. All values will be used other than those
specified in "exceptions" (default: 'Unknown' and 'Medial_Wall').
returns:
dist_mat: symmetrical nxn matrix of minimum distance between pairs of labels
rois: label names in order of n
"""
cortex_vertices, cortex_triangles = surf_keep_cortex(surf, cortex)
# remove exceptions from label list:
label_list = sd.load.get_freesurfer_label(labels, verbose = False)
rs = np.where([a not in exceptions for a in label_list])[0]
rois = [label_list[r] for r in rs]
if verbose:
print("# of regions: " + str(len(rois)))
# calculate distance from each region to all nodes:
dist_roi = []
for roi in rois:
source_nodes = sd.load.load_freesurfer_label(labels, roi)
translated_source_nodes = translate_src(source_nodes, cortex)
dist_roi.append(gdist.compute_gdist(cortex_vertices, cortex_triangles,
source_indices = translated_source_nodes))
if verbose:
print(roi)
dist_roi = np.array(dist_roi)
# Calculate min distance per region:
dist_mat = []
for roi in rois:
source_nodes = sd.load.load_freesurfer_label(labels, roi)
translated_source_nodes = translate_src(source_nodes, cortex)
dist_mat.append(np.min(dist_roi[:,translated_source_nodes], axis = 1))
dist_mat = np.array(dist_mat)
return dist_mat, rois
def dist_calc(surf, cortex, src):
"""
Calculate exact geodesic distance along cortical surface from set of source nodes.
"""
import gdist
from utils import surf_keep_cortex, translate_src, recort
vertices, triangles = surf_keep_cortex(surf, cortex)
src_new = translate_src(src, cortex)
data = gdist.compute_gdist(vertices, triangles, source_indices=src_new)
dist = recort(data, surf, cortex)
del data
return dist
def dist_calc(surf, cortex, source_nodes):
"""
Calculate exact geodesic distance along cortical surface from set of source nodes.
"dist_type" specifies whether to calculate "min", "mean", "median", or "max" distance values
from a region-of-interest. If running only on single node, defaults to "min".
"""
cortex_vertices, cortex_triangles = surf_keep_cortex(surf, cortex)
translated_source_nodes = translate_src(source_nodes, cortex)
data = gdist.compute_gdist(cortex_vertices, cortex_triangles, source_indices = translated_source_nodes)
dist = recort(data, surf, cortex)
del data
return dist
def zone_calc(surf, cortex, src):
"""
Calculate closest nodes to each source node using exact geodesic distance along the cortical surface.
"""
cortex_vertices, cortex_triangles = surf_keep_cortex(surf, cortex)
dist_vals = np.zeros((len(source_nodes), len(cortex_vertices)))
for x in range(len(source_nodes)):
translated_source_nodes = translate_src(source_nodes[x], cortex)
dist_vals[x, :] = gdist.compute_gdist(cortex_vertices, cortex_triangles, source_indices = translated_source_nodes)
data = np.argsort(dist_vals, axis=0)[0, :] + 1
zone = recort(data, surf, cortex)
del data
return zone
def zone_calc(surf, cortex, src):
"""
Calculate closest nodes to each source node using exact geodesic distance along the cortical surface.
"""
import gdist
from utils import surf_keep_cortex, translate_src, recort
vertices, triangles = surf_keep_cortex(surf, cortex)
dist_vals = np.zeros((len(src), len(vertices)))
for x in range(len(src)):
src_new = translate_src(src[x], cortex)
dist_vals[x, :] = gdist.compute_gdist(vertices,
triangles,
source_indices=src_new)
data = np.argsort(dist_vals, axis=0)[0, :] + 1
zone = recort(data, surf, cortex)
del data
return zone