|
104 | 104 | u0 = [ |
105 | 105 | rc_model.capacitor.v => 0.0, |
106 | 106 | ] |
107 | | -prob = ODAEProblem(rc_model, u0, (0, 10.0)) |
108 | | -sol = solve(prob, Tsit5()) |
| 107 | +prob = ODEProblem(rc_model, u0, (0, 10.0)) |
| 108 | +sol = solve(prob) |
109 | 109 | plot(sol) |
110 | 110 | ``` |
111 | 111 |
|
@@ -319,25 +319,10 @@ u0 = [rc_model.capacitor.v => 0.0 |
319 | 319 | rc_model.capacitor.p.i => 0.0] |
320 | 320 |
|
321 | 321 | prob = ODEProblem(rc_model, u0, (0, 10.0)) |
322 | | -sol = solve(prob, Rodas4()) |
323 | | -plot(sol) |
324 | | -``` |
325 | | - |
326 | | -MTK can numerically solve all the |
327 | | -unreduced algebraic equations using the `ODAEProblem` (note the |
328 | | -letter `A`): |
329 | | - |
330 | | -```@example acausal |
331 | | -u0 = [ |
332 | | - rc_model.capacitor.v => 0.0, |
333 | | -] |
334 | | -prob = ODAEProblem(rc_model, u0, (0, 10.0)) |
335 | | -sol = solve(prob, Rodas4()) |
| 322 | +sol = solve(prob) |
336 | 323 | plot(sol) |
337 | 324 | ``` |
338 | 325 |
|
339 | | -Notice that this solves the whole system by only solving for one variable! |
340 | | - |
341 | 326 | However, what if we wanted to plot the timeseries of a different variable? Do |
342 | 327 | not worry, that information was not thrown away! Instead, transformations |
343 | 328 | like `structural_simplify` simply change state variables into observables which are |
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