66 lines
1.9 KiB
Markdown
66 lines
1.9 KiB
Markdown
# DifferentialEquations
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A library, written in Rust, for integrating ordinary differential equations. For now, this is
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relatively simple, but it does have key features that are needed for orbit propagation, ray tracing,
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and field line tracing:
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## Features
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- A relatively efficient Dormand Prince 5th(4th) order integration algorithm, which is effective for
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non-stiff problems
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- A PI-controller for adaptive time stepping
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- The ability to define "callback events" and stop or change the integator or underlying ODE if
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certain conditions are met (zero crossings)
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- A fourth order interpolator for the Domand Prince algorithm
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- Parameters in the derivative and callback functions
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### Future Improvements
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- More algorithms
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- Rosenbrock
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- Verner
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- Tsit(5)
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- Runge Kutta Cash Karp
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- Composite Algorithms
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- Automatic Stiffness Detection
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- Fixed Time Steps
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- Boolean callback eventing
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- Improved solution handling like `DifferentialEquations.jl`
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## To Use
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For now, here is a simple example of using the propagator to solve a simple system:
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```rust
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use nalgebra::Vector3;
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use differential_equations::prelude::*;
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// Define the system (parameters, derivative, and initial state)
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type Params = (f64, bool);
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let params = (34.0, true);
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fn derivative(t: f64, y: Vector3<f64>, p: &Params) -> Vector3<f64> {
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if p.1 { -y } else { y * t }
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}
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let y0 = Vector3::new(1.0, 1.0, 1.0);
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// Set up the problem (ODE, Integrator, Controller, and Callbacks)
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let ode = ODE::new(&derivative, 0.0, 10.0, y0, params);
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let dp45 = DormandPrince45::new(1e-12_f64, 1e-5_f64);
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let controller = PIController::default();
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let value_too_high = Callback {
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event: &|_: f64, y: Vector3<f64>, _: &Params| { 10.0 - y[0] },
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effect: &stop,
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};
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// Solve the problem
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let mut problem = Problem::new(ode, dp45, controller).with_callback(value_too_high);
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let solution = problem.solve();
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// Can interpolate solutions to whatever you want
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let interpolated_answer = solution.interpolate(8.2);
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```
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