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I have two huge tables with 7241 and 1469620 rows (700KB, 141MB)

listData = 
  Import["https://www.dropbox.com/s/s2p7sozkjt67tii/listdata.csv?dl=1", "CSV"];

whitepositions = 
  Import["https://www.dropbox.com/s/03qkfszuvq0qbut/whitepositions.csv?dl=1", "CSV"];

I have a Do loop and it takes a long time for running.

dl = DelaunayMesh[listData];
cells = MeshCells[dl, 2];
cellcoord = Map[MeshCoordinates[dl][[#]] &, cells, {2}];

Do[{mf[i] = RegionMember[cellcoord[[i]]];
tf[i] = mf[i][whitepositions];
tf[i] = Length[Cases[tf[i], True]]}, {i, 1, Length[cellcoord]}]

listData is a data stream of many seed points to generate a Delaunay mesh.

whitepositions is the white pixel coordinates from a binary image.

Is there any way to boost the efficiency?

Thank you!

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  • $\begingroup$ It would be easier for us to help if you described what it is that you're trying to achieve with the code. It seems like you're trying to count how many white pixels are in each cell, is that right? $\endgroup$ – yohbs May 19 '17 at 13:25
  • $\begingroup$ Yes, I want to count how many white pixels in every single Delaunay triangle. $\endgroup$ – Shuoqi Li May 20 '17 at 5:04
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    $\begingroup$ Quick and dirty method: Find the triangle with the closest center using Nearest and test only that one. If the test point is inside, you can skip testing all the other triangles. If it's not inside (hopefully rare), test all of them. $\endgroup$ – Niki Estner May 20 '17 at 9:26
  • $\begingroup$ As it is now, it takes two seconds per iteration, for 14455 steps that is more than 8 hours. @nikie can you provide an efficient implementation for your idea? $\endgroup$ – rhermans May 22 '17 at 10:19
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    $\begingroup$ @rhermans: To be honest, I won't bother for a question that has almost no value for anyone but the OP. This isn't a free coding service ;-) $\endgroup$ – Niki Estner May 22 '17 at 17:39

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