popcount bisect stats (orig)

gistfile1.txt

00 : mean=0.000000,variance=0.000000,std-dev=0.000000, count=67108863 on [0.000000,0.000000]
01 : mean=6.511208,variance=3.084904,std-dev=1.756390, count=67108863 on [2.000000,31.000000]
02 : mean=6.254943,variance=3.523351,std-dev=1.877059, count=67108863 on [2.000000,30.000000]
03 : mean=6.142395,variance=3.876341,std-dev=1.968843, count=67108863 on [2.000000,31.000000]
04 : mean=6.083418,variance=4.125431,std-dev=2.031116, count=67108863 on [2.000000,31.000000]
05 : mean=6.046452,variance=4.320036,std-dev=2.078470, count=67108863 on [2.000000,31.000000]
06 : mean=6.018018,variance=4.485348,std-dev=2.117864, count=67108863 on [2.000000,31.000000]
07 : mean=5.996642,variance=4.607561,std-dev=2.146523, count=67108863 on [2.000000,33.000000]
08 : mean=5.986188,variance=4.664854,std-dev=2.159827, count=67108863 on [2.000000,32.000000]
09 : mean=5.987023,variance=4.672484,std-dev=2.161593, count=67108863 on [2.000000,33.000000]
10 : mean=5.991162,variance=4.674994,std-dev=2.162174, count=67108863 on [2.000000,31.000000]
11 : mean=5.989318,variance=4.719829,std-dev=2.172517, count=67108863 on [1.000000,33.000000]
12 : mean=5.976038,variance=4.824372,std-dev=2.196445, count=67108863 on [1.000000,32.000000]
13 : mean=5.953389,variance=4.979196,std-dev=2.231411, count=67108863 on [1.000000,30.000000]
14 : mean=5.928748,variance=5.134817,std-dev=2.266014, count=67108863 on [1.000000,32.000000]
15 : mean=5.910224,variance=5.246801,std-dev=2.290590, count=67108863 on [1.000000,34.000000]
16 : mean=5.903411,variance=5.281729,std-dev=2.298201, count=67108863 on [1.000000,31.000000]
17 : mean=5.910299,variance=5.237496,std-dev=2.288558, count=67108863 on [1.000000,34.000000]
18 : mean=5.927216,variance=5.127605,std-dev=2.264422, count=67108863 on [1.000000,32.000000]
19 : mean=5.949126,variance=4.989222,std-dev=2.233657, count=67108863 on [1.000000,36.000000]
20 : mean=5.968949,variance=4.856948,std-dev=2.203848, count=67108863 on [1.000000,34.000000]
21 : mean=5.983764,variance=4.753242,std-dev=2.180193, count=67108863 on [1.000000,34.000000]
22 : mean=5.991708,variance=4.701682,std-dev=2.168336, count=67108863 on [1.000000,32.000000]
23 : mean=5.992362,variance=4.699069,std-dev=2.167734, count=67108863 on [1.000000,31.000000]
24 : mean=5.985921,variance=4.748561,std-dev=2.179119, count=67108863 on [1.000000,31.000000]
25 : mean=5.974245,variance=4.849230,std-dev=2.202097, count=67108863 on [1.000000,32.000000]
26 : mean=5.955646,variance=4.996840,std-dev=2.235361, count=67108863 on [1.000000,38.000000]
27 : mean=5.932357,variance=5.191312,std-dev=2.278445, count=67108863 on [1.000000,33.000000]
28 : mean=5.903723,variance=5.415349,std-dev=2.327090, count=67108863 on [1.000000,36.000000]
29 : mean=5.875142,variance=5.644647,std-dev=2.375847, count=67108863 on [1.000000,31.000000]
30 : mean=5.848721,variance=5.839872,std-dev=2.416583, count=67108863 on [1.000000,37.000000]
31 : mean=5.830816,variance=5.975040,std-dev=2.444390, count=67108863 on [1.000000,35.000000]
32 : mean=5.823826,variance=6.023565,std-dev=2.454295, count=67108863 on [1.000000,34.000000]
33 : mean=5.830826,variance=5.976772,std-dev=2.444744, count=67108863 on [1.000000,35.000000]
34 : mean=5.849143,variance=5.840755,std-dev=2.416765, count=67108863 on [1.000000,29.000000]
35 : mean=5.874879,variance=5.642770,std-dev=2.375452, count=67108863 on [1.000000,34.000000]
36 : mean=5.903783,variance=5.415743,std-dev=2.327175, count=67108863 on [1.000000,38.000000]
37 : mean=5.931813,variance=5.191497,std-dev=2.278486, count=67108863 on [1.000000,31.000000]
38 : mean=5.955869,variance=4.999717,std-dev=2.236005, count=67108863 on [1.000000,34.000000]
39 : mean=5.974198,variance=4.848607,std-dev=2.201955, count=67108863 on [1.000000,33.000000]
40 : mean=5.986207,variance=4.748833,std-dev=2.179182, count=67108863 on [1.000000,31.000000]
41 : mean=5.992135,variance=4.697425,std-dev=2.167354, count=67108863 on [1.000000,33.000000]
42 : mean=5.991835,variance=4.701428,std-dev=2.168278, count=67108863 on [1.000000,33.000000]
43 : mean=5.983777,variance=4.753874,std-dev=2.180338, count=67108863 on [1.000000,31.000000]
44 : mean=5.968466,variance=4.855547,std-dev=2.203531, count=67108863 on [1.000000,33.000000]
45 : mean=5.948883,variance=4.987862,std-dev=2.233352, count=67108863 on [1.000000,30.000000]
46 : mean=5.926964,variance=5.126137,std-dev=2.264097, count=67108863 on [1.000000,32.000000]
47 : mean=5.909913,variance=5.236039,std-dev=2.288239, count=67108863 on [1.000000,31.000000]
48 : mean=5.903080,variance=5.281483,std-dev=2.298148, count=67108863 on [1.000000,32.000000]
49 : mean=5.910509,variance=5.245671,std-dev=2.290343, count=67108863 on [1.000000,30.000000]
50 : mean=5.928343,variance=5.134827,std-dev=2.266016, count=67108863 on [1.000000,30.000000]
51 : mean=5.953441,variance=4.977320,std-dev=2.230991, count=67108863 on [1.000000,33.000000]
52 : mean=5.976085,variance=4.825344,std-dev=2.196667, count=67108863 on [1.000000,30.000000]
53 : mean=5.989048,variance=4.717402,std-dev=2.171958, count=67108863 on [1.000000,31.000000]
54 : mean=5.991181,variance=4.675705,std-dev=2.162338, count=67108863 on [1.000000,33.000000]
55 : mean=5.986851,variance=4.672795,std-dev=2.161665, count=67108863 on [1.000000,30.000000]
56 : mean=5.986188,variance=4.664919,std-dev=2.159842, count=67108863 on [2.000000,32.000000]
57 : mean=5.996461,variance=4.604532,std-dev=2.145817, count=67108863 on [2.000000,34.000000]
58 : mean=6.017784,variance=4.483653,std-dev=2.117464, count=67108863 on [2.000000,31.000000]
59 : mean=6.046547,variance=4.319893,std-dev=2.078435, count=67108863 on [2.000000,33.000000]
60 : mean=6.083887,variance=4.126396,std-dev=2.031353, count=67108863 on [2.000000,33.000000]
61 : mean=6.142503,variance=3.876520,std-dev=1.968888, count=67108863 on [2.000000,32.000000]
62 : mean=6.254979,variance=3.523733,std-dev=1.877161, count=67108863 on [2.000000,32.000000]
63 : mean=6.511379,variance=3.084617,std-dev=1.756308, count=67108863 on [2.000000,33.000000]
64 : mean=7.344018,variance=3.474551,std-dev=1.864015, count=67108863 on [2.000000,34.000000]