neat.SOVTree.construct_net

SOVTree.construct_net(dz=50.0, dx=10.0, eps=0.0001, use_hist=False, add_lin_terms=True, improve_input_impedance=False, pprint=False)[source]

Construct a Neural Evaluation Tree (NET) for this cell. The locations for which impedance values are computed are stored under the name net eval

Parameters:

  • dz (float) – the impedance step for the NET model derivation

  • dx (float) – the distance step to evaluate the impedance matrix

  • eps (float) – the cutoff threshold in relative importance below which modes are truncated

  • use_hist (bool) – whether or not to use histogram segmentations to find well separated parts of the dendritic tree (such ass apical tree)

  • add_lin_terms – take into account that the optained NET will be used in conjunction with linear terms

Returns:

The neural evaluation tree (Wybo et al., 2019) associated with the morphology.

Return type:

neat.NETree