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3

I propose an example silhouette descriptor based on a polar histogram. In my example histogram consits of 36 bins. newBinCounts funtion newBinCounts[angles_, bins_] := Module[{hist, sectorIndex}, ( hist = BinCounts[angles, {bins}]; sectorIndex = Table[Flatten[ Union[Position[angles, #] & /@ ...


8

[Edited to correct the bin definition.] You could use SectorChart. The trick is to ensure that your bin widths sum to 360° and that the first bin charted starts at zero. Firstly, and borrowing shamelessly from @george2079's answer [and subsequent correction], define the bins: bins = Table[a , {a, -180, 180, 30}]; Next create the sector chart data: ...


8

data = RandomReal[ {0, 200}, {200, 2}]; center = {50, 50}; centereddata = (# - center) & /@ data; angles = N[ArcTan[#[[1]], #[[2]]]/Degree] & /@ centereddata; radiis = N@Sqrt[#[[1]]^2 + #[[2]]^2] & /@ centereddata; note you need to use Degree to put the angles back to radians here.. polardata = Transpose[Join[{angles Degree}, {radiis}]]; ...


6

Something like this is probably what you're after: dat = DeleteCases[({CityData[#, "Population"], CityData[#, "Coordinates"]} & /@ CityData[{All, "Mexico"}]), {___, _Missing, ___}]; func = PDF[SmoothKernelDistribution[ WeightedData[dat[[All, 2]], dat[[All, 1]]]], {x, y}]; ra = func[[2, 0, 1]]; Plot3D[Log10@func, {x, ra[[1, 1]], ra[[1, ...


5

With some random numbers rNumbers = RandomReal[{0, 1}, 100] you can get a cumulative histogram with a log-log scale using Histogram[rNumbers, "Log", {"Log", "CumulativeCount"}]


1

data = RandomVariate[NormalDistribution[2, .1], 100]; ListPlot[ Transpose[{Mean /@ Partition[#[[1]], 2, 1], Accumulate@#[[2]]}] &@HistogramList[ data ] , Filling -> Axis, PlotRange -> {0, Automatic}] BarChart[ Accumulate@#[[2]] &@ HistogramList[ data ] ] Edit : missed the loglog part earlier, properly we need to cook up ...



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