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<p class=MsoNormal style='text-autospace:none'><font size=2
face="Times New Roman"><span style='font-size:11.0pt'>I am looking to find a
solution to a problem and believe that Numpy may help. I'd appreciate some
advice and/or direction and I'll pursue from there.<o:p></o:p></span></font></p>
<p class=MsoNormal style='text-autospace:none'><font size=2
face="Times New Roman"><span style='font-size:11.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span style='font-size:
11.0pt'>The problem is that I am looking for a most efficient solution where I
have to select 25 solutions where the highest pair-covariance value is the
lowest of all possible 25 solution combinations. There are possible 95
solutions to choose from and I have a 95 x 95 matrix of pair-covariance values.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span style='font-size:
11.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span style='font-size:
11.0pt'>Thanks in advance.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span style='font-size:
11.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face="Times New Roman"><span style='font-size:
11.0pt'>Chris<o:p></o:p></span></font></p>
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