Skip to main content

differential equations - WhenEvent in NDSolve


How come this doesn't work as I intended?


s[{x0_, y0_}, a_, v_] := NDSolveValue[{

x'[t] == vx[t], WhenEvent[x[t] > 0, vx[t] -> -vx[t]],
y'[t] == vy[t] - t, WhenEvent[y[t] < 0, vy[t] -> -vy[t]],
x[0] == x0, vx[0] == v Cos@a,
y[0] == y0, vy[0] == v Sin@a},
{x[t], y[t]}, {t, 0, 10},
DiscreteVariables -> {vx, vy}]

Simulating falling and bouncing of a 2D mass point.


With[{r0 = {-5, 7}},
ParametricPlot[Evaluate@s[r0, -.9, 2],

{t, 0, 10},
PlotRange -> {{-10, 10}, {-10, 10}},
Epilog -> {Point@r0}]]

Fall


I can't understand why it doesn't bounce on the x-axis first, and what does happen there anyway? Event x[t]>0 works fine.




bouncing ball


Following help I started with lowering the order of equations (and so doubling the number of variables). Here I wrote the equations in a more familiar 2nd order; everything works as expected. I put the function below in a tiny loop which bisected the right initial velocity v0 that returns the ball in its starting position.


Could this be done within NDSolve? I looked Wolfram tutorial for Boundary Value Problems but haven't been able to figure it out.



sstop[{x0_, y0_}, a_, v0_] := NDSolveValue[{
x''[t] == 0, WhenEvent[x[t] > 0, x'[t] -> -x'[t]],
y''[t] == -1, WhenEvent[y[t] < 0, y'[t] -> -y'[t]],
WhenEvent[x[t] < x0, Sow[{t, y[t]}]; "StopIntegration"],
x[0] == x0, x'[0] == v0 Cos[a],
y[0] == y0, y'[0] == v0 Sin[a]},
{x[t], y[t]}, {t, 0, 20}] // Reap

Answer



Here you have a bouncing ball simulation using WithEvents[]:


s[{x0_, y0_}, a_, v_] := NDSolveValue[

{
y''[t] == -1,
x'[t] == vx[t],
y[0] == y0,
x[0] == x0,
y'[0] == v Sin@a,
vx[0] == v Cos@a,
vy[0] == v Sin@a,
WhenEvent[y[t] < 0, y'[t] -> - y'[t]],
WhenEvent[x[t] > 0, vx[t] -> -vx[t]]},

{x, y}, {t, 0, 8},
DiscreteVariables -> {vx, vy}] ;

With[{r0 = {-1, 1}},
ParametricPlot[Through[s[r0, 1, 1][u]], {u, 0, 5}, PlotRange -> All,
Epilog -> {Point@r0}]]

enter image description here


Comments

Popular posts from this blog

plotting - Filling between two spheres in SphericalPlot3D

Manipulate[ SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, Mesh -> None, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], {n, 0, 1}] I cant' seem to be able to make a filling between two spheres. I've already tried the obvious Filling -> {1 -> {2}} but Mathematica doesn't seem to like that option. Is there any easy way around this or ... Answer There is no built-in filling in SphericalPlot3D . One option is to use ParametricPlot3D to draw the surfaces between the two shells: Manipulate[ Show[SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], ParametricPlot3D[{ r {Sin[t] Cos[1.5 Pi], Sin[t] Sin[1.5 Pi], Cos[t]}, r {Sin[t] Cos[0 Pi], Sin[t] Sin[0 Pi], Cos[t]}}, {r, 1, 2 - n}, {t, 0, Pi}, PlotStyle -> Yellow, Mesh -> {2, 15}]], {n, 0, 1}]

plotting - Plot 4D data with color as 4th dimension

I have a list of 4D data (x position, y position, amplitude, wavelength). I want to plot x, y, and amplitude on a 3D plot and have the color of the points correspond to the wavelength. I have seen many examples using functions to define color but my wavelength cannot be expressed by an analytic function. Is there a simple way to do this? Answer Here a another possible way to visualize 4D data: data = Flatten[Table[{x, y, x^2 + y^2, Sin[x - y]}, {x, -Pi, Pi,Pi/10}, {y,-Pi,Pi, Pi/10}], 1]; You can use the function Point along with VertexColors . Now the points are places using the first three elements and the color is determined by the fourth. In this case I used Hue, but you can use whatever you prefer. Graphics3D[ Point[data[[All, 1 ;; 3]], VertexColors -> Hue /@ data[[All, 4]]], Axes -> True, BoxRatios -> {1, 1, 1/GoldenRatio}]

plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1.