5
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I need to obtain a matrix and DensityPlot it, then perform a SingularValueList on a 200*200 matrix. But my code is slow, more than 50 seconds. I need the running time to be less than 10 seconds, since I have a lot of similar data to run. I would like to know how to speed up this code. Any help or suggestion will be highly appreciated!

The code is shown below:

    a = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1,  1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1,  1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1};

    n1[λ_] :=   Sqrt[(2.0993 + 0.922683/(1 - 0.0467695/(λ*10^-3)^2) - 0.0138408 (λ*10^-3)^2)];
    n2[λ_] := √(2.12725 + 1.18431/(1 - 5.14852*10^-2/(λ*10^-3)^2) + 0.6603/(1 - 100.00507/(λ*10^-3)^2) - 9.68956*10^-3*(λ*10^-3)^2);
    λp[λs_, λi_] := 1/(1/λs + 1/λi);
    Δkk[λs_, λi_] := 2 π*(n1[λp[λs, λi]]/λp[λs, λi] - n1[λs]/λs - n2[λi]/λi);
    ϕ[x_, Δk_] :=Abs[Sum[a[[j+1]] 1/Δk (-I E^(I*x*j Δk) (-1+E^(I*x*Δk))), {j, 0, 1299}]];
    ϕ2[λs_, λi_] := ϕ[23111, Δkk[λs, λi]];
    α[λs_, λi_] := Exp[-(1/2) ((1/λi + 1/λs - 1/775)/(1.6/(1550)^2))^2];
    f[λs_, λi_] := ϕ2[λs, λi]*α[λs, λi];
    TimeUsed[]


    DensityPlot[ f[λs, λi], {λs, 1545, 1555}, {λi, 1545, 1555}, PlotPoints -> 100, PlotRange -> All,  ColorFunction -> "Rainbow", ImageSize -> {150, 150}]
    TimeUsed[]


    data = Table[f[1545 + i*0.05, 1545 + j*0.05], {i, Table[i, {i, 200}]}, {j, Table[i, {i, 200}]}];
    ListDensityPlot[data, InterpolationOrder -> 0, Mesh -> True, PlotRange -> All, ColorFunction -> "Rainbow", ImageSize -> {150, 150}]
    Total[N[SingularValueList[data]]]
    TimeUsed[]

The result is shown below :

enter image description here

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13
  • $\begingroup$ In the code for the function phi you have calls to DeltaK without arguments, but DeltaK is defined to take two arguments. What does that mean? $\endgroup$
    – MarcoB
    Jan 28, 2022 at 13:17
  • $\begingroup$ @MarcoB. Thanks for the comment. The current code is executable and the result is correct. If I define phi with three arguments ([Phi][x_, [Lambda]s_, [Lambda]i_]), there is an error “ Sum cannot be followed by a[[j+1]]1/[CapitalDelta]k[[Lambda]s,[Lambda]i]...” $\endgroup$
    – user14634
    Jan 28, 2022 at 13:52
  • 1
    $\begingroup$ The time is mainly spent in creating these plots. SingularValueList[data] only takes 0.156 sec. on my machine. $\endgroup$ Jan 28, 2022 at 14:19
  • $\begingroup$ In addition to creating the plots, generating the table data also takes 35 seconds on my machine. In comparison, the SVD on data takes 3 MILLIseconds. You need to profile your code and see which call is most expensive. For instance, you have Simplify and Sum calls deep in there: since your results should be numerical at that point, Simplify is probably doing nothing, and Sum may be re-cast as a more vectorial operation that could be quicker. If you include an explanation of what your code is supposed to do, then perhaps somebody could provide another approach. $\endgroup$
    – MarcoB
    Jan 28, 2022 at 14:51
  • $\begingroup$ Regarding the DeltaK: I see now that you used the exact same symbol as a parameter for the phi function, and as a function name itself. That is very poor practice and guaranteed to cause confusion, as it just did to me. Consider renaming one of those for future readability. $\endgroup$
    – MarcoB
    Jan 28, 2022 at 14:52

1 Answer 1

7
+50
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We can reduce computation time with using Dot instead of Sum and Compile as follows

a = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1,  1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1,  1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1, 1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, -1, -1, -1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1};

n1 = Sqrt[(2.0993 + 0.922683/(1 - 0.0467695/(\[Lambda]*10^-3)^2) - 
     0.0138408 (\[Lambda]*10^-3)^2)];
n2 = \[Sqrt](2.12725 + 
     1.18431/(1 - 5.14852*10^-2/(\[Lambda]*10^-3)^2) + 
     0.6603/(1 - 100.00507/(\[Lambda]*10^-3)^2) - 
     9.68956*10^-3*(\[Lambda]*10^-3)^2);
\[Lambda]p = 1/(1/\[Lambda]s + 1/\[Lambda]i);
\[CapitalDelta]kk = 
 2 \[Pi]*((n1 /. \[Lambda] -> \[Lambda]p)/\[Lambda]p - (n1 /. \
\[Lambda] -> \[Lambda]s)/\[Lambda]s - (n2 /. \[Lambda] -> \
\[Lambda]i)/\[Lambda]i); vec = 
 Table[E^(I*x*(j - 1) \[CapitalDelta]k), {j, 1300}];
\[Phi] = Abs[(a . 
       vec)/\[CapitalDelta]k (-I  (-1 + E^(I*x*\[CapitalDelta]k)))];
\[Phi]2 = (\[Phi] /. {x -> 
      23111, \[CapitalDelta]k -> \[CapitalDelta]kk});
\[Alpha] = 
  Exp[-(1/2) ((1/\[Lambda]i + 1/\[Lambda]s - 1/775)/(1.6/(1550)^2))^2];
f = \[Phi]2*\[Alpha]; fc = 
 Compile[{{x, _Real}, {y, _Real}}, 
  Evaluate[f /. {\[Lambda]s -> x, \[Lambda]i -> y}], 
  CompilationTarget -> "C", Parallelization -> True, 
  RuntimeOptions -> "Speed"]; fn[x_?NumericQ, y_?NumericQ] := fc[x, y];
TimeUsed[]

(*Out[]= 5.907*)

 DensityPlot[fc[x, y], {x, 1545, 1555}, {y, 1545, 1555}, 
 PlotPoints -> 100, PlotRange -> All, ColorFunction -> "Rainbow", 
 ImageSize -> {150, 150}]
TimeUsed[] 

Figure 1

coord = 
  Table[{1545 + i*0.05, 1545 + j*0.05}, {i, 200}, {j, 200}];
data = ConstantArray[0, {200, 200}];
Do[data[[i, j]] = 
   Evaluate[
    fn[x, y] /. {x -> coord[[i, j]][[1]], 
      y -> coord[[i, j]][[2]]}];, {i, 200}, {j, 
  200}]; ListDensityPlot[data, Mesh -> True, PlotRange -> All, 
 ColorFunction -> "Rainbow", ImageSize -> {150, 150}]
Total[N[SingularValueList[data]]]
TimeUsed[]

Out[]= 3.48182*10^8

Out[]= 10.907

Figure 2

Note, that DensityPlot takes 1.2 s, while data, ListDensityPlot and SVD - 3.6 s only. Largest time about 5.9 s (on my laptop) takes Compile. In the last cell of code we can also use Table to gain 0.5 s,

data = Table[
  Evaluate[fn[1545 + .05 i, 1545 + .05 j]], {i, 200}, {j, 
   200}]; ListDensityPlot[data, Mesh -> True, PlotRange -> All, 
 ColorFunction -> "Rainbow", ImageSize -> {150, 150}]
Total[N[SingularValueList[data]]]
TimeUsed[]

But computation time is shortest with ParallelTable

data = ParallelTable[
  Evaluate[fn[1545 + .05 i, 1545 + .05 j]], {i, 200}, {j, 
   200}]; ListDensityPlot[data, Mesh -> True, PlotRange -> All, 
 ColorFunction -> "Rainbow", ImageSize -> {150, 150}]
Total[N[SingularValueList[data]]]
TimeUsed[]
(*8.281*)

Last number we can compare to computational time of original code that is about 47.89 on my laptop. We can also test how computational time increasing with length a.

$\endgroup$
3
  • $\begingroup$ This is the answer I need. Thank you so much! $\endgroup$
    – user14634
    Feb 2, 2022 at 14:13
  • $\begingroup$ I have also tested and confirmed that the computational time is increasing linearly with the length a. If I change the length from a to 3a, the complie time is three times longer and the Table time is also three time longer. $\endgroup$
    – user14634
    Feb 2, 2022 at 14:20
  • $\begingroup$ @user14634 You are welcome! Did you test this code with Length[a]=13000? $\endgroup$ Feb 2, 2022 at 14:20

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