:mod:`neuron_morphology.features.intrinsic`
===========================================

.. py:module:: neuron_morphology.features.intrinsic


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   neuron_morphology.features.intrinsic.num_tips
   neuron_morphology.features.intrinsic.num_nodes
   neuron_morphology.features.intrinsic.child_ids_by_type
   neuron_morphology.features.intrinsic.calculate_branches_from_root
   neuron_morphology.features.intrinsic.num_branches
   neuron_morphology.features.intrinsic.calculate_mean_fragmentation_from_root
   neuron_morphology.features.intrinsic.mean_fragmentation
   neuron_morphology.features.intrinsic.calculate_max_branch_order_from_root
   neuron_morphology.features.intrinsic.max_branch_order


.. function:: 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)**
           ..














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.. function:: 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)**
           ..














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.. function:: child_ids_by_type(node_id, morphology, node_types=None)

   Helper function for the traversal functions
















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.. function:: 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)**
           ..














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.. function:: 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)**
           ..














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.. function:: 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)**
           ..














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.. function:: 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)**
           ..














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.. function:: 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
           a. a bifurcation (has > 1 children)
           b. the root node
       2. the last node on the path is either
           a. a bifurcation
           b. 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
           ..













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.. function:: 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)**
           ..














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