def main_segments(swc_matirx):
neuron = Neuron(swc_matirx)
branch_order = tree_util.branch_order(neuron.parent_index)
distance_from_parent = neuron.distance_from_parent()
main, parent_main_point, neural, euclidean = \
neuron.get_neural_and_euclid_lenght_main_point(branch_order, distance_from_parent)
branch_branch, branch_die, die_die, initial_with_branch = \
neuron.branching_type(main, parent_main_point)
ind_main = nodes_laying_toward_soma(
neuron.parent_index, np.array(np.append(branch_die, die_die)))
main_seg = np.zeros(len(neuron.parent_index))
main_seg[ind_main] = 1
return main_seg.astype(int)
def topological_depth(swc_matirx):
neuron = Neuron(swc_matirx)
branch_order = tree_util.branch_order(neuron.parent_index)
distance_from_parent = neuron.distance_from_parent()
main, parent_main_point, neural, euclidean = \
neuron.get_neural_and_euclid_lenght_main_point(branch_order, distance_from_parent)
reg_neuron = Neuron(subsample.regular_subsample(swc_matirx))
topo_depth = np.zeros(swc_matirx.shape[0])
depth_main = neuron_util.dendogram_depth(reg_neuron.parent_index)
topo_depth[main] = depth_main
for i in range(1, swc_matirx.shape[0]):
b = True
par = i
while b:
(index, ) = np.where(main == par)
if len(index) != 0:
topo_depth[i] = topo_depth[main[index]]
b = False
par = neuron.parent_index[par]
return topo_depth