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I have two functions that I both use memoization for. My goal is to plot the ratio of these two functions. Since I already plot the functions by themselves, and I use memoization, it would seem to me that this shouldn't take much time. However, it still runs very slowly, suggesting to me that the memoization doesn't work as I had intended.

mem : f1[x_?NumericQ] := mem = (*slow function 1*)
mem : f2[x_?NumericQ] := mem = (*slow function 2*)
mem : f3[x_?NumericQ] := mem = f1[x]/f2[x]
Plot[f1[x], {x,0,1}]
Plot[f2[x], {x,0,1}]
Plot[f3[x], {x,0,1}]

All three plots are slow, but I would expect the third one to be fast since the relevant details have been calculated in the previous two plots. My guess is that Plot uses different x-values for the third plot than the ones that are stored in memory, possibly due to the fact that these x-values for f1 and f2 differ. Is there a way to speed up this procedure?

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    $\begingroup$ The adaptive sampling ("Plot initially evaluates f at a number of equally spaced sample points specified by PlotPoints. Then it uses an adaptive algorithm to choose additional sample points, subdividing a given interval at most MaxRecursion times.") varies between the graphs due to the different functions; consequently, the sample points are not generally the same and the memorization has limited effect. $\endgroup$
    – Bob Hanlon
    Sep 3, 2021 at 14:14

1 Answer 1

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Switch off adaptive sampling: setting MaxRecursion to zero,

Clear[f1, f2, f3]
mem : f1[x_?NumericQ] := mem = (Pause[1]; x^2)
mem : f2[x_?NumericQ] := mem = (Pause[1]; x^3)
mem : f3[x_?NumericQ] := mem = f1[x]/f2[x]

Plot[f1[x], {x, 0, 1}, PlotPoints -> 10, MaxRecursion -> 0] // AbsoluteTiming
Plot[f2[x], {x, 0, 1}, PlotPoints -> 10, MaxRecursion -> 0] // AbsoluteTiming
Plot[f3[x], {x, 0, 1}, PlotPoints -> 10, MaxRecursion -> 0] // AbsoluteTiming
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