Skip to main content

programming - A fast, robust DropWhile


For reasons that have never been entirely clear to me, Mathematica has had a built-in TakeWhile function since version 6.0, but has no equivalent DropWhile function. This means that I find myself periodically writing my own. Since this is a function that I use fairly frequently, I'd like to have a version that is both fast and robust. It's also the kind of function that you can write in a bunch of ways; I've tested variants that depend on While loops, on using Scan and Throw, and on using Position.


Of these, a version using Position is the fastest I've found:


DropWhile[list_, test_] := 
With[{pos =

Position[list, elt_ /; ! TrueQ@test[elt], {1}, 1, Heads -> False]},
pos /. {
{} -> {},
{{fail_}} :> Drop[list, fail - 1]
}];

The TrueQ slows things down a bit, but is there to match the observed behavior of TakeWhile, which takes elements only as long as the test function returns True. Are there good ways to make this function work faster?



Answer



Simple solution


Why not just



dropWhile[list_, test_] := Drop[list, LengthWhile[list, test]]

?


Fast JIT-based solution with automatic type identification / dispatch


Here I will show a solution that is potentially much faster on packed arrays. The code is directly modeled after this answer, so I refer to some additional details there.


JIT version with type memoization


Here is the first ingredient: the specialized JIT version


ClearAll[dropWhileJIT];
dropWhileJIT[pred_,listType_,target:"MVM"|"C":"MVM"]:=
dropWhileJIT[pred,Verbatim[listType],target]=

Block[{l},
With[{decl={Prepend[listType,l]}},
Compile@@
Hold[
decl,
Module[{pos=1},
While[pred[l[[pos]]],pos++];Drop[l,pos-1]
],
CompilationTarget->target
]

]
]

which can be tested as


dropWhileJIT[# < 99999 &, {_Integer, 1}, "C"][Range[100000]] // AbsoluteTiming

(* {5.481445, {99999, 100000}} *)

The second and subsequent times this will be blazingly fast:


dropWhileJIT[# < 99999 &, {_Integer, 1}, "C"][Range[100000]] // AbsoluteTiming


(* {0.000977, {99999, 100000}} *)

Here, we also should have a function to clear the cache:


ClearAll[clearDropWhileCache];
clearDropWhileCache[]:=
DownValues[dropWhileJIT]={Last[DownValues[dropWhileJIT]]};

which can be used to remove the memoized definitions.


Automatic type identification and dispatch



Here we will use the following functions:


Clear[getType,$useCompile];
getType[arg_List]/;$useCompile&&ArrayQ[arg,_,IntegerQ]:=
{_Integer,Length[Dimensions[arg]]};
getType[arg_List]/;$useCompile&&ArrayQ[arg,_,NumericQ]&&Re[arg]==arg:=
{_Real,Length[Dimensions[arg]]};
getType[_]:=
General;

and



Clear[dropWhileDispatch];
dropWhileDispatch[
t:{Verbatim[_Integer]|Verbatim[_Real]|Verbatim[_Complex],n_},pred_
]:=
dropWhileJIT[pred,t,$target];

dropWhileDispatch[_,pred_]:=
dropWhileGeneric[#1,pred]&;

Final functions



Here is our previous generic implementation (I changed the name):


ClearAll[dropWhileGeneric];
dropWhileGeneric[list_,test_]:=
Drop[list,LengthWhile[list,test]]

and here is a final function:


ClearAll[dropWhile];
Options[dropWhile]={CompileToC->False,Compiled->True};
dropWhile[lst_List,pred_,opts:OptionsPattern[]]:=
Block[

{
$target=If[TrueQ[OptionValue[CompileToC]],"C","MVM"],
$useCompile=TrueQ[OptionValue[Compiled]]
},
dropWhileDispatch[getType[lst],pred][lst]
];

Benchmarks


JIT-compilation to MVM is really fast:


clearDropWhileCache[];

dropWhile[Range[100000], # < 99999 &] // AbsoluteTiming

(* {0.007813, {99999, 100000}} *)

The second time is faster still, since we don't have to recompile:


dropWhile[Range[100000], # < 99999 &] // AbsoluteTiming

(* {0.006836, {99999, 100000}} *)

The compilation to C is quite slow:



dropWhile[Range[100000], # < 99999 &,CompileToC -> True] // AbsoluteTiming

(* {4.640625, {99999, 100000}} *)

But gives a considerable further speedup:


dropWhile[Range[100000], # < 99999 &,CompileToC -> True] // AbsoluteTiming

(* {0.001953, {99999, 100000}} *)

Here is what we get from the generic implementation:



dropWhile[Range[100000], # < 99999 &, Compiled -> False] // AbsoluteTiming

(* {0.157226, {99999, 100000}} *)

It is not as bad as it could have been, since LengthWhile by itself is optimized on packed arrays, but it does not compare with the JIT versions.


The complete code


ClearAll[dropWhileJIT];
dropWhileJIT[pred_,listType_,target:"MVM"|"C":"MVM"]:=
dropWhileJIT[pred,Verbatim[listType],target]=
Block[{l},

With[{decl={Prepend[listType,l]}},
Compile@@
Hold[
decl,
Module[{pos=1},
While[pred[l[[pos]]],pos++];Drop[l,pos-1]
],
CompilationTarget->target
]
]

]


Clear[getType,$useCompile];
getType[arg_List]/;$useCompile&&ArrayQ[arg,_,IntegerQ]:=
{_Integer,Length[Dimensions[arg]]};
getType[arg_List]/;$useCompile&&ArrayQ[arg,_,NumericQ]&&Re[arg]==arg:=
{_Real,Length[Dimensions[arg]]};
getType[_]:=
General;


Clear[dropWhileDispatch];
dropWhileDispatch[
t:{Verbatim[_Integer]|Verbatim[_Real]|Verbatim[_Complex],n_},pred_
]:=
dropWhileJIT[pred,t,$target];

dropWhileDispatch[_,pred_]:=
dropWhileGeneric[#1,pred]&;



ClearAll[dropWhileGeneric];
dropWhileGeneric[list_,test_]:=
Drop[list,LengthWhile[list,test]]


ClearAll[dropWhile];
Options[dropWhile]={CompileToC->False,Compiled->True};
dropWhile[lst_List,pred_,opts:OptionsPattern[]]:=
Block[

{
$target=If[TrueQ[OptionValue[CompileToC]],"C","MVM"],
$useCompile=TrueQ[OptionValue[Compiled]]
},
dropWhileDispatch[getType[lst],pred][lst]
];


ClearAll[clearDropWhileCache];
clearDropWhileCache[]:=

DownValues[dropWhileJIT]={Last[DownValues[dropWhileJIT]]};

Comments

Popular posts from this blog

functions - Get leading series expansion term?

Given a function f[x] , I would like to have a function leadingSeries that returns just the leading term in the series around x=0 . For example: leadingSeries[(1/x + 2)/(4 + 1/x^2 + x)] x and leadingSeries[(1/x + 2 + (1 - 1/x^3)/4)/(4 + x)] -(1/(16 x^3)) Is there such a function in Mathematica? Or maybe one can implement it efficiently? EDIT I finally went with the following implementation, based on Carl Woll 's answer: lds[ex_,x_]:=( (ex/.x->(x+O[x]^2))/.SeriesData[U_,Z_,L_List,Mi_,Ma_,De_]:>SeriesData[U,Z,{L[[1]]},Mi,Mi+1,De]//Quiet//Normal) The advantage is, that this one also properly works with functions whose leading term is a constant: lds[Exp[x],x] 1 Answer Update 1 Updated to eliminate SeriesData and to not return additional terms Perhaps you could use: leadingSeries[expr_, x_] := Normal[expr /. x->(x+O[x]^2) /. a_List :> Take[a, 1]] Then for your examples: leadingSeries[(1/x + 2)/(4 + 1/x^2 + x), x] leadingSeries[Exp[x], x] leadingSeries[(1/x + 2 + (1 - 1/x...

mathematical optimization - Minimizing using indices, error: Part::pkspec1: The expression cannot be used as a part specification

I want to use Minimize where the variables to minimize are indices pointing into an array. Here a MWE that hopefully shows what my problem is. vars = u@# & /@ Range[3]; cons = Flatten@ { Table[(u[j] != #) & /@ vars[[j + 1 ;; -1]], {j, 1, 3 - 1}], 1 vec1 = {1, 2, 3}; vec2 = {1, 2, 3}; Minimize[{Total@((vec1[[#]] - vec2[[u[#]]])^2 & /@ Range[1, 3]), cons}, vars, Integers] The error I get: Part::pkspec1: The expression u[1] cannot be used as a part specification. >> Answer Ok, it seems that one can get around Mathematica trying to evaluate vec2[[u[1]]] too early by using the function Indexed[vec2,u[1]] . The working MWE would then look like the following: vars = u@# & /@ Range[3]; cons = Flatten@{ Table[(u[j] != #) & /@ vars[[j + 1 ;; -1]], {j, 1, 3 - 1}], 1 vec1 = {1, 2, 3}; vec2 = {1, 2, 3}; NMinimize[ {Total@((vec1[[#]] - Indexed[vec2, u[#]])^2 & /@ R...

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}]