None- )whether or not to ignore unders and oversa Histogram is a list of contiguous boundaries (a boundary being the lower edge of one bucket and the upper edge of another), and a count for each bucket Overs and Unders are counted in key=0 and key=length cutfill a Histogram using pre-specified cuts >>> fill [0,50,100] [1..100] Histogram {cuts = [0.0,50.0,100.0], values = fromList [(1,50.0),(2,50.0)]}make a histogram using n equally spaced cuts over the entire range of the data >>> regular 4 [0..100] Histogram {cuts = [0.0,25.0,50.0,75.0,100.0], values = fromList [(0,1.0),(1,25.0),(2,25.0),(3,25.0),(4,25.0)]} transform a Histogram to Rects >>> makeRects IgnoreOvers (regular 4 [0..100]) [Rect 0.0 25.0 0.0 0.25,Rect 25.0 50.0 0.0 0.25,Rect 50.0 75.0 0.0 0.25,Rect 75.0 100.0 0.0 0.25] Yapprox regular n-quantiles >>> regularQuantiles 4 [0..100] [0.0,24.75,50.0,75.25,100.0] #one-pass approximate quantiles fold take a specification of quantiles and make a Histogram >>> fromQuantiles [0,0.25,0.5,0.75,1] (regularQuantiles 4 [0..100]) Histogram {cuts = [0.0,24.75,50.0,75.25,100.0], values = fromList [(1,0.25),(2,0.25),(3,0.25),(4,0.25)]} normalize a histogram so that sum values = one >>> freq $ fill [0,50,100] [1..100] Histogram {cuts = [0.0,50.0,100.0], values = fromList [(1,0.5),(2,0.5)]}  Safe     /numhask-histogram-0.0.1.0-RrNgr2ec60F4IuZ8J134QNumHask.HistogramPaths_numhask_histogram DealOvers IgnoreOvers IncludeOvers Histogramcutsvaluesfillregular makeRectsregularQuantiles quantileFold fromQuantilesfreq$fShowHistogram $fEqHistogramversion getBinDir getLibDir getDynLibDir getDataDir getLibexecDir getSysconfDirgetDataFileName