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If I understand you correctly, is the following what you want? correlations2 = Map[ Outer[Correlation, #, #, 1] &[Transpose[#]] &, partitionedData, {2}]; Now the Correlation receives two vector as its input, and you can replace it with SpearmanRankCorrelation or KendallRankCorrelation legally. To verify it, compare correlations2 with your ...

Here is a method to generate the ticks automatically based on the plot range. It uses FindDivisions to select "pleasing" values. eVticks = {1240/#, NumberForm[N@#, {2, 1}]} & /@ FindDivisions[1240/{##}, 8] &; ListPlot[{{500, 50}}, Frame -> True, PlotRange -> {{400, 800}, {-10, 110}}, FrameLabel -> {"Wavelength (nm)", "Intensity ...

As soon as I posted, I realized I could check whether there were any options for LinTicks that might be useful: Options@LinTicks // TableForm Scanning that list, I saw: TickLabelFunction -> Automatic On a hunch, I added TickLabelFunction -> TraditionalForm To the ticks definition from the question, and things worked:

You appear to have an inefficiency in your algorithm. You generate a symmetrical correlation matrix and only use one element (correlations[[All, All, 1, 2]]). You also partition everything before processing which takes a lot of memory: ByteCount[partitionedData] 505899832 I suggest reformulating your code to produce only the significant correlation ...

I would define my upper ticks so that it should be easy to change the number of decimal points if needed (thanks to Mr.Wizard for pointing out a mistake). upperTicks = Module[{labels, positions}, labels = Range[1240/400, 1240/800, -0.2]; positions = 1240/# & /@ labels; Transpose[{positions, labels}]]; upperTicksMinor = Module[{labels, positions, ...