neuron_morphology.features.intrinsic

Module Contents

Functions

num_tips(data: Data, node_types: Optional[List] = None) Calculate number of tips
num_nodes(data: Data, node_types: Optional[List] = None) Calculate number of nodes of a given type
child_ids_by_type(node_id, morphology, node_types=None) Helper function for the traversal functions
calculate_branches_from_root(morphology, root, node_types=None) Calculate the number of branches of a specific neuron type
num_branches(data: Data, node_types: Optional[List] = None) Calculate number of branches
calculate_mean_fragmentation_from_root(morphology, root, node_types=None) Calculate the mean fragmentation from a root
mean_fragmentation(data: Data, node_types: Optional[List] = None) Calculate the mean number of compartments per branch
calculate_max_branch_order_from_root(morphology, root, node_types=None) Calculate the greatest number of branches encountered among all
max_branch_order(data: Data, node_types: Optional[List] = None) Calculate mean fragmentation
neuron_morphology.features.intrinsic.num_tips(data: Data, node_types: Optional[List] = None)

Calculate number of tips

Parameters:
data: Data Object containing a morphology
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.num_nodes(data: Data, node_types: Optional[List] = None)

Calculate number of nodes of a given type

Parameters:
data: Data Object containing a morphology
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.child_ids_by_type(node_id, morphology, node_types=None)

Helper function for the traversal functions

neuron_morphology.features.intrinsic.calculate_branches_from_root(morphology, root, node_types=None)

Calculate the number of branches of a specific neuron type in a morphology. A branch is defined as being between two bifurcations or between a bifurcation and a tip if a node has three or more children, it is treated as succesive bifurcations, e.g a trifurcation: _/_/__ creates 4 branches since the branch between the two bifurcations counts

Parameters:
morphology: a morphology object
root: the root node to traverse from
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.num_branches(data: Data, node_types: Optional[List] = None)

Calculate number of branches

Parameters:
data: Data Object containing a morphology
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.calculate_mean_fragmentation_from_root(morphology, root, node_types=None)

Calculate the mean fragmentation from a root in a morphology. Mean fragmentation is the number of compartments over the number of branches. A branch is defined as being between two bifurcations or between a bifurcation and a tip if a node has three or more children, it is treated as succesive bifurcations, e.g a trifurcation: _/_/__ creates 4 branches since the branch between the two bifurcations counts

Parameters:
morphology: a morphology object
root: the root node to traverse from
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.mean_fragmentation(data: Data, node_types: Optional[List] = None)

Calculate the mean number of compartments per branch

Parameters:
data: Data Object containing a morphology
node_types: a list of node types (see neuron_morphology constants)
neuron_morphology.features.intrinsic.calculate_max_branch_order_from_root(morphology, root, node_types=None)

Calculate the greatest number of branches encountered among all directed paths from the morphology’s root to its leaves. A branch is defined as a root->leaf ordered path for which:

  1. the first node on the path is either
    1. a bifurcation (has > 1 children)
    2. the root node
  2. the last node on the path is either
    1. a bifurcation
    2. a leaf node (has 0 children)
Parameters:
morphology: the reconstruction whose max branch order will be

calculated

root: treat this node as root
node_types: If not None, consider only root->leaf paths whose leaf

nodes are among these types (see neuron_morphology constants)
Returns:
The greatest branch count encountered among all considered root->leaf
paths
neuron_morphology.features.intrinsic.max_branch_order(data: Data, node_types: Optional[List] = None)

Calculate mean fragmentation

Parameters:
data: Data Object containing a morphology
node_types: a list of node types (see neuron_morphology constants)