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Most of the examples in Drasil require an ODE solver. In Drasil we don't have information set up about an ODE library for Julia. Thus, enabling `Bundled` inputs in Julia (via structs) isn't actually…
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I am trying to solve this system of ODEs
```
from sympy import *
RC, t, C, Vs, L, R1, V0, I0 = symbols("RC t C Vs L R1 V0 I0")
V= Function("V")
I = Function("I")
system = [Eq(V(t).diff(t), -1/…
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Serialize SBML ODEs to diffrax/Jax format.
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Need a capability for solving ODEs at the centroid of the element. This will involve adding material property storage for that point as well.
This should essentially mirror the NodalKernel capabilit…
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### Describe the desired feature
This was again brought to my attention by https://forums.wesnoth.org/viewtopic.php?p=694156#p694156, and is actually more an idea than an actual request: I think we c…
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Hi, I am absolutely new to diffrax and trying to get the basics of it (great work by the way).
I am a bit confused concerning the syntax for solving systems of ODEs. In the documentation discussin…
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Develop material for a ~2hr workshop (slides, etc) and try and run that in the MRC centre. Cover basic use - not sure if both odes and stochastic models make sense. Some theory (the graph stuff in p…
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It would be nice to build the transformation equations for these kinds of things https://docs.sciml.ai/latest/extras/sensitivity_math/ directly from the IR since that would make it much faster by avoi…
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This analysis is to find out whether using the single-ODE parametrisation of the closed-population SIR leads to a substantial gain/loss in two respects:
(i) Computational: are there differences in…
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At the moment, `desolve` behaves like this even with trivial separable ODEs:
```
sage: t = var('t')
sage: y=function('y')(t)
sage: desolve(diff(y,t)-y^2,y)
-1/y(t) == _C + t
sage: desolve(diff(y,t)…