get_MRG_parameters

nrv.utils.get_MRG_parameters(diameter: float | ndarray[tuple[Any, ...], dtype[_ScalarT]], fit_all: bool = False) → tuple[8][source]

Compute the MRG geometrical parameters from interpolation of original data [1]

Note

The data used is stored in the MRG_data DataFrame, so it can be printed as follows
>>> print(nrv.MRG_data)
Parameters:

  • diameter (float) – diameter of the unmylinated axon to implement, in um

  • fit_all (bool) – if False, for diameters included in MRG_data, original data are used without interpollation

Returns:

  • g (float)

  • axonD (float)

  • nodeD (float)

  • paraD1 (float)

  • paraD2 (float)

  • deltax (float)

  • paralength2 (float)

  • nl (float)

Note

[1] McIntyre CC, Richardson AG, and Grill WM. Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. Journal of Neurophysiology 87:995-1006, 2002.