godesim
Simulate complex systems with a simple API.
Wrangle non-linear differential equations while writing maintainable, simple code.
Why Godesim?
ODE solvers seem to fill the niche of simple system solvers in your numerical packages such as scipy's odeint/solve_ivp.
Among these integrators there seems to be room for a solver that offers simulation interactivity such as modifying the differential equations during simulation based on events such as a rocket stage separation.
Installation
Requires Go.
go get github.com/soypat/godesim
Progress
Godesim is in early development and will naturally change as it is used more. The chart below shows some features that are planned or already part of godesim.
| Status legend | Planned | Started | Prototype | Stable | Mature |
|---|---|---|---|---|---|
| Legend symbol |
|
|
|
|
|
| Features | Status | Notes |
|---|---|---|
| Non-linear solvers |
|
Suite of ODE solvers available. |
| Non-autonomous support |
|
U vector which need not a defined differential equation like X does. |
| Event driver |
|
Eventer interface implemented. |
| Stiff solver |
|
Working on Newton implementation of Euler-Backward. |
Examples
To run an example, navigate to it's directory (under examples) then type go run . in console.
There are three simple examples which have been cooked up and left in _examples directory. I've been having problems running Pixel on my machine so the simulation animations are still under work.
Imports
The import signature for a godesim simulation usually looks like this:
import (
"github.com/soypat/godesim"
"github.com/soypat/godesim/state" // uses gonum's `floats` subpackage
)
ODE solver example Code is in test file
// Declare your rate-of-change functions using state-space symbols
Dtheta := func(s state.State) float64 {
return s.X("theta-dot")
}
DDtheta := func(s state.State) float64 {
return 1
}
// Set the Simulation's differential equations and initial values and hit Begin!
sim := godesim.New() // Configurable with Simulation.SetConfig(godesim.Config{...})
sim.SetDiffFromMap(map[state.Symbol]state.Diff {
"theta": Dtheta,
"theta-dot": DDtheta,
})
sim.SetX0FromMap(map[state.Symbol]float64{
"theta": 0,
"theta-dot": 0,
})
sim.SetTimespan(0.0, 1.0, 10) // One second simulated
sim.Begin()
The above code solves the following system:
for the domain t=0 to t=1.0 in 10 steps where theta and theta-dot are the X variables. The resulting curve is quadratic as the solution for this equation (for theta and theta-dot equal to zero) is
How to obtain results
// one can then obtain simulation results as float slices
t := sim.Results("time")
theta := sim.Results("theta")
Contributing
Pull requests welcome!
This is my first library written for any programming language ever. I'll try to be fast on replying to pull-requests and issues.
