def i_neurites(self, iterator_type, mapping=None, tree_filter=None):
'''Returns a mapped iterator to all the neuron's neurites
Provides access to all the elements of all the neurites
in one iteration sequence.
Parameters:
iterator_type: type of the iteration (segment, section, triplet...)
mapping: optional function to apply to the iterator's target.
tree_filter: optional top level filter on properties of neurite tree objects.
'''
return tr.i_chain(self.neurites, iterator_type, mapping, tree_filter)
def bounding_box(self):
'''Return 3D bounding box of a neuron
Returns:
2D numpy array of [[min_x, min_y, min_z], [max_x, max_y, max_z]]
'''
# Get the bounding coordinates of the neurites
nmin_xyz, nmax_xyz = (np.array([np.inf, np.inf, np.inf]),
np.array([np.NINF, np.NINF, np.NINF]))
for p in tr.i_chain(self.neurites, tr.ipreorder, lambda p: p):
nmin_xyz = np.minimum(p[:COLS.R], nmin_xyz)
nmax_xyz = np.maximum(p[:COLS.R], nmax_xyz)
# Get the bounding coordinates of the soma
smin_xyz = np.array(self.soma.center) - self.soma.radius
smax_xyz = np.array(self.soma.center) + self.soma.radius
return np.array([np.minimum(smin_xyz, nmin_xyz),
np.maximum(smax_xyz, nmax_xyz)])
