Allow derivimplicit
to use finite differences.
#1444
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In NOCMODL
derivimplicit
uses finite differences to compute eachelement of the Jacobian. In stead we try to use SymPy, however, if it
fails, e.g. because it encounters an opaque function, we allow it to use
a finite difference instead.
When SymPy can't compute a derivative analytically, it replaces it
with a
Derivative({func}, ({variable}, {n}))
, which represents then
th derivative offunc
w.r.t.variable
.In this PR we crawl SymPy's AST to find
Derivative
objects, andreplace them with a finite difference. The step-with is the same
as used in NEURON for computing the elements of the Jacobian.
Additionally, there's some code to enable computing the
\Delta x
.