# ListDensityPlot in Polar coordinates with a higher efficiency

I have data like this

f[r,theta]


and cells number are about 600*600 (uniform mesh)

The original data has the property of uniform mesh for r and theta. However, when I transfer them into Cartesian coordinates, this property disappeared and it became a 360,000-point data. Using ListDensityPlot was very slow.

Because I have to plot a lot of data of this kind, I wonder if there is any other methods to plot them in polar coordinates with higher efficient.

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• Take a look at MaxPlotPoints – Dr. belisarius Nov 4 '15 at 14:25

How about you make a ListDensityPlot as usual in the original polar coordinates and then transform the vertices to Cartesian coordinates.

data = Flatten[
Table[{r, θ, Sin[3 r] Cos[3 θ]}, {r, 0, 2 π, 2 π/100}, {θ, 0, 2 π, 2 π/100}], 1];
plot = ListDensityPlot[data] transformGraphicsComplex[f_, g_] :=
GraphicsComplex[f /@ First[g], Sequence @@ Rest[g]]
Graphics[transformGraphicsComplex[# /. {r_, θ_} :> {r Cos[θ], r Sin[θ]} &, First@plot]] If the following is reasonable or not depends on your points' geometry. Anyway:

(*generate the points (slow)*)
n = 600;
f[r_, t_] := r^2 Sin[6 t]
s = CoordinateTransform[ "Cylindrical" -> "Cartesian", {{r1, t1, f[r1, t1]}}];
tab = Table[ Flatten[s /. {r1 -> r, t1 -> t}, 1], {r, n}, {t, 0, 2 Pi, 2 Pi/n}];

(*plot them(fast) *)
ListPlot3D[Flatten[RandomSample[tab, 10], 1]] • I don't get defining s in terms of r1, t1 and then using Rule to replace r1 with r and t1 with t. Wouldn't s = CoordinateTransform[ "Cylindrical" -> "Cartesian", {{r, t, f[r, t]}}] work directly? – Jack LaVigne Nov 4 '15 at 15:35
• @JackLaVigne Yes, but this way is more clear to me. – Dr. belisarius Nov 4 '15 at 15:45

using Rahul's data

f = Interpolation[{#[[1 ;; 2]], #[]} & /@ data];
DensityPlot[
f[Norm[{x, y}], Pi + ArcTan[-x, y] ] , {x, -2 Pi, 2 Pi}, {y, -2 Pi,
2 Pi},
RegionFunction -> (Norm[{##}] < 2 Pi &), PlotPoints -> 100] 