use unnormalized histogram output

git-svn-id: https://bucket.mit.edu/svn/nilm/zoom@8125 ddd99763-3ecb-0310-9145-efcb8ce7c51f

pc/data/20091104/hist.dat

@@ -1,61 +1,61 @@
- -1.50000000e+01 5.19611963e-05
+ -1.50000000e+01 2.30000000e+01
  -1.45000000e+01 0.00000000e+00
  -1.40000000e+01 0.00000000e+00
- -1.35000000e+01 4.51836489e-06
- -1.30000000e+01 9.03672979e-06
- -1.25000000e+01 2.25918245e-06
- -1.20000000e+01 6.77754734e-06
- -1.15000000e+01 4.29244665e-05
- -1.10000000e+01 8.81081154e-05
- -1.05000000e+01 1.35550947e-04
- -1.00000000e+01 2.25918245e-04
- -9.50000000e+00 2.64324346e-04
- -9.00000000e+00 8.04268951e-04
- -8.50000000e+00 1.05955657e-03
- -8.00000000e+00 2.94823309e-03
- -7.50000000e+00 2.26821918e-03
- -7.00000000e+00 2.50091497e-03
- -6.50000000e+00 8.07431807e-03
- -6.00000000e+00 8.80403400e-03
- -5.50000000e+00 1.66546930e-02
- -5.00000000e+00 1.21363281e-02
- -4.50000000e+00 1.90968692e-02
- -4.00000000e+00 3.24034538e-02
- -3.50000000e+00 3.48185199e-02
- -3.00000000e+00 4.31232745e-02
- -2.50000000e+00 4.71762479e-02
- -2.00000000e+00 5.44801847e-02
- -1.50000000e+00 5.79005869e-02
- -1.00000000e+00 7.05768596e-02
- -5.00000000e-01 6.44386609e-02
- 0.00000000e+00 4.39704680e-02
- 5.00000000e-01 7.41554046e-02
- 1.00000000e+00 6.22449948e-02
- 1.50000000e+00 4.86153471e-02
- 2.00000000e+00 5.30343079e-02
- 2.50000000e+00 5.31156385e-02
- 3.00000000e+00 4.28928379e-02
- 3.50000000e+00 3.35940430e-02
- 4.00000000e+00 3.33026085e-02
- 4.50000000e+00 1.64807360e-02
- 5.00000000e+00 1.71720458e-02
- 5.50000000e+00 1.28073053e-02
- 6.00000000e+00 7.65185095e-03
- 6.50000000e+00 5.23678491e-03
- 7.00000000e+00 6.95828194e-03
- 7.50000000e+00 3.53562053e-03
- 8.00000000e+00 2.54835780e-03
- 8.50000000e+00 1.21995852e-03
- 9.00000000e+00 6.82273099e-04
- 9.50000000e+00 2.30436610e-04
- 1.00000000e+01 2.43991704e-04
- 1.05000000e+01 5.19611963e-05
- 1.10000000e+01 5.42203787e-05
- 1.15000000e+01 4.97020138e-05
- 1.20000000e+01 2.48510069e-05
- 1.25000000e+01 1.35550947e-05
- 1.30000000e+01 4.51836489e-06
+ -1.35000000e+01 2.00000000e+00
+ -1.30000000e+01 4.00000000e+00
+ -1.25000000e+01 1.00000000e+00
+ -1.20000000e+01 3.00000000e+00
+ -1.15000000e+01 1.90000000e+01
+ -1.10000000e+01 3.90000000e+01
+ -1.05000000e+01 6.00000000e+01
+ -1.00000000e+01 1.00000000e+02
+ -9.50000000e+00 1.17000000e+02
+ -9.00000000e+00 3.56000000e+02
+ -8.50000000e+00 4.69000000e+02
+ -8.00000000e+00 1.30500000e+03
+ -7.50000000e+00 1.00400000e+03
+ -7.00000000e+00 1.10700000e+03
+ -6.50000000e+00 3.57400000e+03
+ -6.00000000e+00 3.89700000e+03
+ -5.50000000e+00 7.37200000e+03
+ -5.00000000e+00 5.37200000e+03
+ -4.50000000e+00 8.45300000e+03
+ -4.00000000e+00 1.43430000e+04
+ -3.50000000e+00 1.54120000e+04
+ -3.00000000e+00 1.90880000e+04
+ -2.50000000e+00 2.08820000e+04
+ -2.00000000e+00 2.41150000e+04
+ -1.50000000e+00 2.56290000e+04
+ -1.00000000e+00 3.12400000e+04
+ -5.00000000e-01 2.85230000e+04
+ 0.00000000e+00 1.94630000e+04
+ 5.00000000e-01 3.28240000e+04
+ 1.00000000e+00 2.75520000e+04
+ 1.50000000e+00 2.15190000e+04
+ 2.00000000e+00 2.34750000e+04
+ 2.50000000e+00 2.35110000e+04
+ 3.00000000e+00 1.89860000e+04
+ 3.50000000e+00 1.48700000e+04
+ 4.00000000e+00 1.47410000e+04
+ 4.50000000e+00 7.29500000e+03
+ 5.00000000e+00 7.60100000e+03
+ 5.50000000e+00 5.66900000e+03
+ 6.00000000e+00 3.38700000e+03
+ 6.50000000e+00 2.31800000e+03
+ 7.00000000e+00 3.08000000e+03
+ 7.50000000e+00 1.56500000e+03
+ 8.00000000e+00 1.12800000e+03
+ 8.50000000e+00 5.40000000e+02
+ 9.00000000e+00 3.02000000e+02
+ 9.50000000e+00 1.02000000e+02
+ 1.00000000e+01 1.08000000e+02
+ 1.05000000e+01 2.30000000e+01
+ 1.10000000e+01 2.40000000e+01
+ 1.15000000e+01 2.20000000e+01
+ 1.20000000e+01 1.10000000e+01
+ 1.25000000e+01 6.00000000e+00
+ 1.30000000e+01 2.00000000e+00
  1.35000000e+01 0.00000000e+00
  1.40000000e+01 0.00000000e+00
  1.45000000e+01 0.00000000e+00
- 1.50000000e+01 1.12959122e-05
+ 1.50000000e+01 5.00000000e+00

pc/data/20091104/makehist.m

@@ -13,12 +13,17 @@ p = polyfit(meas, keith_amps, 1)
 meas_amps = meas * p(1) + p(2);  # calibration fit
 err_amps = keith_amps - meas_amps;
 
-[n, x] = hist(err_amps*1000, [-15:0.5:15], 1);
+[n, x] = hist(err_amps*1000, [-15:0.5:15]);
+
+for i = 0:30
+  cumulative(i+1)=sum(n((31-i):(31+i))/len);
+endfor
+figure(1);
+plot(x(31:61),cumulative);
 
-# Looks pretty good: 93% of points are within ±5mA (14 bits)
-# 99.9% of points are within ±10mA (13 bits)
 
 savedata = [ x' n' ];
 save("-ascii", "hist.dat", "savedata");
 
+figure(2);
 bar(x,n)