Good. I hope you're still in an educational mood. The d_lambda rule is a rational basis for specifying the spatial discretization of a model. It involves setting nseg to a value that is a small fraction of the AC length constant at a high frequency. The rationale behind it is developed in the second half of this article

NEURON: a tool for neuroscientists

Hines, M.L. and Carnevale, N.T.

The Neuroscientist 7:123-135, 2001

Here's a revised preprint of that article

https://neuron.yale.edu/neuron/static/p ... e_rev2.pdf
and you'll find a bit of code that implements the rule on this page

https://neuron.yale.edu/neuron/static/d ... ambda.html
with instructions for how to use it with hoc. The "trick" for reusing this code with Python is simply

h.xopen("fixnseg.hoc")

h.geom_nseg()

If the model cell in question doesn't have a soma, comment out the

soma area(0.5)

statement in proc geom_nseg() (i.e. change it to

// soma area(0.5)

)