neuron_morphology.morphology module

class neuron_morphology.morphology.Morphology(nodes, node_id_cb, parent_id_cb)

Bases: sphinx.ext.autodoc.importer._MockObject

Methods

__call__(self, \*args, \*\*kw)	Call self as a function.
breadth_first_traversal(self, visit[, …])	Apply a function to each node of a connected graph in breadth-first order
depth_first_traversal(self, visit[, …])	Apply a function to each node of a connected graph in depth-first order
get_compartment_surface_area(self, compartment)	Calculate the surface area of a single compartment.
get_compartment_volume(self, compartment)	Calculate the volume of a single compartment.
get_root(self)	Return the first found root node If the input SWC file does not have any root node, it will return None
get_roots_for_analysis(self[, root, node_types])	Returns a list of all trees to be analyzed, based on the supplied root.
get_soma(self)	Return one soma node labeled with SOMA If the input SWC file does not have any node labeled with SOMA, it will return None
swap_nodes_edges(self[, merge_cb, …])	Build a new tree whose nodes are the edges of this tree and vice-versa
validate(self[, strict])	Validate the neuron morphology in

build_intermediate_nodes
children_of
clone
euclidean_distance
get_branch_order_for_node
get_branch_order_for_segment
get_branching_nodes
get_children
get_children_of_node_by_types
get_compartment_for_node
get_compartment_length
get_compartment_midpoint
get_compartments
get_dimensions
get_leaf_nodes
get_max_id
get_node_by_types
get_non_soma_nodes
get_number_of_trees
get_root_for_tree
get_root_id
get_roots
get_roots_for_nodes
get_segment_length
get_segment_list
get_tree_list
has_type
is_node_at_beginning_of_segment
is_node_at_end_of_segment
is_soma_child
midpoint
node_by_id
parent_of

breadth_first_traversal(self, visit, neighbor_cb=None, start_id=None)

Apply a function to each node of a connected graph in breadth-first order

Parameters:

visit : callable

Will be applied to each node. Signature must be visit(node). Return is ignored.

neighbor_cb : callable, optional

Will be used during traversal to find the next nodes to be visited. Signature must be neighbor_cb(node id) -> list of node_ids. Defaults to self.child_ids.

start_id : hashable, optional

Begin the traversal from this node. Defaults to self.get_root_id().

Notes

assumes rooted, acyclic

build_intermediate_nodes(self, make_intermediates_cb, set_parent_id_cb)

children_of(self, node)

clone(self)

depth_first_traversal(self, visit, neighbor_cb=None, start_id=None)

Apply a function to each node of a connected graph in depth-first order

Parameters:

visit : callable

Will be applied to each node. Signature must be visit(node). Return is ignored.

neighbor_cb : callable, optional

Will be used during traversal to find the next nodes to be visited. Signature must be neighbor_cb(node_id) -> list of node_ids. Defaults to self.child_ids.

start_id : hashable, optional

Begin the traversal from this node. Defaults to self.get_root_id().

Notes

assumes rooted, acyclic

static euclidean_distance(node1, node2)

get_branch_order_for_node(self, node)

get_branch_order_for_segment(self, segment)

get_branching_nodes(self, node_types=None)

get_children(self, node, node_types=None)

get_children_of_node_by_types(self, node, node_types)

get_compartment_for_node(self, node, node_types=None)

get_compartment_length(self, compartment)

get_compartment_midpoint(self, compartment)

get_compartment_surface_area(self, compartment: Sequence[Dict]) → float

Calculate the surface area of a single compartment. Treats the compartment as a circular conic frustum and calculates its lateral surface area. This is:

pi * (r_1 + r_2) * sqrt( (r_2 - r_1) ** 2 + L ** 2 )

Parameters:

compartment : two-long sequence. Each element is a node and must have

3d position data (“x”, “y”, “z”) and a “radius”

Returns:

The surface area of the sides of the compartment

get_compartment_volume(self, compartment: Sequence[Dict]) → float

Calculate the volume of a single compartment. Treats the compartment as a circular conic frustum and calculates its volume as:

pi * L * (r_1 ** 2 + r_1 * r_2 + r_2 ** 2) / 3

Parameters:

compartment : two-long sequence. Each element is a node and must have

3d position data (“x”, “y”, “z”) and a “radius”

Returns:

The volume of the compartment

get_compartments(self, nodes=None, node_types=None)

get_dimensions(self, node_types=None)

get_leaf_nodes(self, node_types=None)

get_max_id(self)

get_node_by_types(self, node_types=None)

get_non_soma_nodes(self)

get_number_of_trees(self, nodes=None)

get_root(self)

Return the first found root node If the input SWC file does not have any root node, it will return None

Parameters:

morphology: Morphology object

Returns:

Root node object

get_root_for_tree(self, tree_number)

get_root_id(self)

get_roots(self)

get_roots_for_analysis(self, root=None, node_types=None)

Returns a list of all trees to be analyzed, based on the supplied root. These trees are the list of all children of the root, if root is not None, and the root node of all trees in the morphology if root is None.

Parameters:

morphology: Morphology object

root: dict

This is the node from which to count branches under. When root=None,

all separate trees in the morphology are returned.

node_types: list (AXON, BASAL_DENDRITE, APICAL_DENDRITE)

Type to restrict search to

Returns:

Array of Node objects

get_roots_for_nodes(self, nodes)

get_segment_length(self, segment)

get_segment_list(self, node_types=None)

get_soma(self)

Return one soma node labeled with SOMA If the input SWC file does not have any node labeled with SOMA, it will return None

Parameters:

morphology: Morphology object

Returns:

Soma node object

get_tree_list(self)

has_type(self, node_type)

is_node_at_beginning_of_segment(self, node)

is_node_at_end_of_segment(self, node)

is_soma_child(self, node)

static midpoint(node1, node2)

node_by_id(self, node_id)

parent_of(self, node)

swap_nodes_edges(self, merge_cb=None, parent_id_cb=None, make_root_cb=None, start_id=None)

Build a new tree whose nodes are the edges of this tree and vice-versa

Parameters:

merge_cb : callable, optional

parent_id_cb : callable, optional

make_root_cb : callable, optional

start_id : hashable, optional

Notes

assumes rooted, acyclic

validate(self, strict=False)

Validate the neuron morphology in

[bits, radius, resample, type, structure]