neat.SOVTree.constructNET

SOVTree.constructNET(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

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