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$\mathrm{with}\left(\mathrm{Statistics}\right)\:$

A simple 1D case. Excise will remove the sparsest half of the data, leaving the densest half, which it returns as a 1D Array. In this case, this will the center four points.
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$\mathrm{data1}\u2254\mathrm{Array}\left(\left[\left[1\,2\right]\,\left[3\,4\right]\,\left[5\,6\right]\,\left[7\,8\right]\right]\right)\:$

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$\mathrm{ret1}\u2254\mathrm{Excise}\left(0.5\,\mathrm{data1}\right)$

${\mathrm{ret1}}{\u2254}\left[\begin{array}{cccc}{4.}& {5.}& {3.}& {6.}\end{array}\right]$
 (1) 
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$\mathrm{type}\left(\mathrm{ret1}\,\mathrm{Array}\right)$

If a negative fraction is used as the first argument, then the returned data will be the sparsest points, in this case the outer four points.
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$\mathrm{Excise}\left(0.5\,\mathrm{data1}\right)$

$\left[\begin{array}{cccc}{8.}& {1.}& {7.}& {2.}\end{array}\right]$
 (3) 
If the return_same option is used, then Excise will return the remaining data as the same type as was entered.
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$\mathrm{data2}\u2254\left[2\,4\,6\,8\,10\,12\,14\,16\,18\,20\,22\,24\right]$

${\mathrm{data2}}{\u2254}\left[{2}{\,}{4}{\,}{6}{\,}{8}{\,}{10}{\,}{12}{\,}{14}{\,}{16}{\,}{18}{\,}{20}{\,}{22}{\,}{24}\right]$
 (4) 
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$\mathrm{ret2}\u2254\mathrm{Excise}\left(\frac{2}{3}\,\mathrm{data2}\,\mathrm{return\_same}\right)$

${\mathrm{ret2}}{\u2254}\left[{14.}{\,}{12.}{\,}{10.}{\,}{16.}\right]$
 (5) 
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$\mathrm{type}\left(\mathrm{ret2}\,\mathrm{list}\right)$

Excise can be used to trim points from data and then pass the remainders to a plotting function. If the to_plot option is used, then the original range of the data will be preserved so it can be compared with the original data. This is accomplished by returning a line of the form view= [range(s)] to be used as an option by the plotting function.
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$\mathrm{with}\left(\mathrm{Statistics}\right)\:$

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$A\u2254\mathrm{Sample}\left(\mathrm{RandomVariable}\left(\mathrm{Normal}\left(0\,1\right)\right)\,500\right)\:$

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$B\u2254\mathrm{Sample}\left(\mathrm{RandomVariable}\left(\mathrm{Normal}\left(0\,1\right)\right)\,500\right)\:$

Plot original data
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$\mathrm{ScatterPlot}\left(A\,B\right)$

Plot of the densest half of the data
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$\mathrm{ScatterPlot}\left(\mathrm{Excise}\left(0.5\,A\,B\,\mathrm{to\_plot}\right)\right)$
