added evolution3d

This commit is contained in:
Nicole Dresselhaus 2017-09-27 22:06:25 +02:00
parent 57ed8ce291
commit 1bbe1682c8
Signed by: Drezil
GPG Key ID: 057D94F356F41E25
18 changed files with 4712 additions and 0 deletions

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regularity,variability,improvement,"Evolution error",steps
6.57581e-05,0.00592209,0.622392,113.016.,2368
5.16451e-05,0.00592209,0.610293,118.796.,2433
6.45083e-05,0.00592209,0.592139,127.157.,1655
7.14801e-05,0.00592209,0.624039,121.613.,1933
5.62707e-05,0.00592209,0.611091,119.539.,2618
5.55953e-05,0.00592209,0.625812,119.512.,2505
5.96026e-05,0.00592209,0.622873,118.285.,1582
6.63676e-05,0.00592209,0.602386,126.579.,2214
5.93125e-05,0.00592209,0.608913,122.512.,2262
6.05066e-05,0.00592209,0.621467,118.473.,2465
6.42976e-05,0.00592209,0.602593,121.998.,2127
5.32868e-05,0.00592209,0.616501,115.313.,2746
5.47856e-05,0.00592209,0.615173,118.034.,2148
6.47209e-05,0.00592209,0.603935,120.003.,2304
7.07812e-05,0.00592209,0.620422,123.494.,1941
6.49313e-05,0.00592209,0.616232,122.989.,2214
6.64295e-05,0.00592209,0.605206,123.757.,1675
5.88806e-05,0.00592209,0.628055,110.67.,2230
7.56461e-05,0.00592209,0.625361,121.232.,2187
4.932e-05,0.00592209,0.612261,120.979.,2280
5.45998e-05,0.00592209,0.61935,115.394.,2380
6.10654e-05,0.00592209,0.614029,116.928.,2327
6.09488e-05,0.00592209,0.611892,125.294.,1609
5.85691e-05,0.00592209,0.632686,111.635.,2831
6.87292e-05,0.00592209,0.61519,114.681.,2565
6.53377e-05,0.00592209,0.627408,111.935.,2596
6.98345e-05,0.00592209,0.616158,111.392.,2417
7.90547e-05,0.00592209,0.620575,115.346.,2031
6.50231e-05,0.00592209,0.625725,119.055.,1842
6.76541e-05,0.00592209,0.625399,117.452.,1452
5.72222e-05,0.00592209,0.614171,123.379.,2186
7.42483e-05,0.00592209,0.624683,115.053.,2236
6.9354e-05,0.00592209,0.619596,123.994.,1688
5.75478e-05,0.00592209,0.605051,118.576.,1930
6.01309e-05,0.00592209,0.617511,116.894.,2184
6.69251e-05,0.00592209,0.608408,120.129.,2007
4.66926e-05,0.00592209,0.60606,126.708.,1552
4.90102e-05,0.00592209,0.618673,114.595.,2783
5.51505e-05,0.00592209,0.619245,120.056.,2463
6.1007e-05,0.00592209,0.605215,122.057.,1493
5.04717e-05,0.00592209,0.623503,116.846.,2620
6.3578e-05,0.00592209,0.625261,124.35.,2193
5.8875e-05,0.00592209,0.624526,118.43.,2502
7.95299e-05,0.00592209,0.611719,116.574.,1849
6.42733e-05,0.00592209,0.608178,128.474.,2078
6.41674e-05,0.00592209,0.624042,111.111.,2037
4.88661e-05,0.00592209,0.615408,120.004.,2627
7.27714e-05,0.00592209,0.626926,119.866.,2128
4.84641e-05,0.00592209,0.608054,119.676.,2408
6.66562e-05,0.00592209,0.603902,128.957.,1668
5.99872e-05,0.00592209,0.63676,108.467.,3448
7.73127e-05,0.00592209,0.62232,123.353.,1551
6.67597e-05,0.00592209,0.621411,123.301.,2180
5.2819e-05,0.00592209,0.617515,114.838.,4096
5.29257e-05,0.00592209,0.622611,118.611.,1973
5.35212e-05,0.00592209,0.62533,109.616.,3424
7.1947e-05,0.00592209,0.632331,113.565.,2905
5.04311e-05,0.00592209,0.611559,120.01.,2147
6.57161e-05,0.00592209,0.617789,125.441.,1820
5.18695e-05,0.00592209,0.610402,122.541.,2430
6.47262e-05,0.00592209,0.609141,123.169.,1989
5.87925e-05,0.00592209,0.61627,117.344.,2143
4.36904e-05,0.00592209,0.631954,112.674.,3526
6.45195e-05,0.00592209,0.614402,118.787.,1765
5.8354e-05,0.00592209,0.615515,112.061.,2368
7.14669e-05,0.00592209,0.628382,110.262.,1923
7.24908e-05,0.00592209,0.610848,116.504.,1830
5.98617e-05,0.00592209,0.622949,109.607.,3609
5.90411e-05,0.00592209,0.629175,122.198.,1859
5.25569e-05,0.00592209,0.621253,124.527.,1876
5.86979e-05,0.00592209,0.612603,120.886.,2916
4.73113e-05,0.00592209,0.610586,119.176.,2072
5.8777e-05,0.00592209,0.62863,121.081.,2338
5.6608e-05,0.00592209,0.617215,121.038.,3021
5.74614e-05,0.00592209,0.626088,112.392.,2182
6.86466e-05,0.00592209,0.631893,121.148.,2246
4.77969e-05,0.00592209,0.635218,117.053.,2939
5.50553e-05,0.00592209,0.610707,123.651.,1417
6.89628e-05,0.00592209,0.638474,128.446.,1840
6.85622e-05,0.00592209,0.620769,115.527.,2116
5.28017e-05,0.00592209,0.614948,121.456.,2178
7.06916e-05,0.00592209,0.61804,127.418.,2354
6.81788e-05,0.00592209,0.616056,113.541.,2768
7.89711e-05,0.00592209,0.615108,116.805.,2293
5.84297e-05,0.00592209,0.612733,123.244.,2206
5.53374e-05,0.00592209,0.605062,123.095.,1902
5.51739e-05,0.00592209,0.631543,115.9.,3145
6.9413e-05,0.00592209,0.59103,124.024.,1475
5.08739e-05,0.00592209,0.621454,114.685.,3356
5.95256e-05,0.00592209,0.626188,113.428.,2336
5.63659e-05,0.00592209,0.618554,117.456.,2105
6.32019e-05,0.00592209,0.616926,122.15.,1799
6.05333e-05,0.00592209,0.613481,124.576.,1873
5.35997e-05,0.00592209,0.621122,113.63.,2834
5.94187e-05,0.00592209,0.606925,126.608.,1970
6.52182e-05,0.00592209,0.610882,129.916.,1246
6.78626e-05,0.00592209,0.608581,119.673.,2155
5.12495e-05,0.00592209,0.6262,116.233.,3037
6.7083e-05,0.00592209,0.608299,125.086.,1595
6.74099e-05,0.00592209,0.620429,112.897.,2800
1 regularity variability improvement Evolution error steps
2 6.57581e-05 0.00592209 0.622392 113.016. 2368
3 5.16451e-05 0.00592209 0.610293 118.796. 2433
4 6.45083e-05 0.00592209 0.592139 127.157. 1655
5 7.14801e-05 0.00592209 0.624039 121.613. 1933
6 5.62707e-05 0.00592209 0.611091 119.539. 2618
7 5.55953e-05 0.00592209 0.625812 119.512. 2505
8 5.96026e-05 0.00592209 0.622873 118.285. 1582
9 6.63676e-05 0.00592209 0.602386 126.579. 2214
10 5.93125e-05 0.00592209 0.608913 122.512. 2262
11 6.05066e-05 0.00592209 0.621467 118.473. 2465
12 6.42976e-05 0.00592209 0.602593 121.998. 2127
13 5.32868e-05 0.00592209 0.616501 115.313. 2746
14 5.47856e-05 0.00592209 0.615173 118.034. 2148
15 6.47209e-05 0.00592209 0.603935 120.003. 2304
16 7.07812e-05 0.00592209 0.620422 123.494. 1941
17 6.49313e-05 0.00592209 0.616232 122.989. 2214
18 6.64295e-05 0.00592209 0.605206 123.757. 1675
19 5.88806e-05 0.00592209 0.628055 110.67. 2230
20 7.56461e-05 0.00592209 0.625361 121.232. 2187
21 4.932e-05 0.00592209 0.612261 120.979. 2280
22 5.45998e-05 0.00592209 0.61935 115.394. 2380
23 6.10654e-05 0.00592209 0.614029 116.928. 2327
24 6.09488e-05 0.00592209 0.611892 125.294. 1609
25 5.85691e-05 0.00592209 0.632686 111.635. 2831
26 6.87292e-05 0.00592209 0.61519 114.681. 2565
27 6.53377e-05 0.00592209 0.627408 111.935. 2596
28 6.98345e-05 0.00592209 0.616158 111.392. 2417
29 7.90547e-05 0.00592209 0.620575 115.346. 2031
30 6.50231e-05 0.00592209 0.625725 119.055. 1842
31 6.76541e-05 0.00592209 0.625399 117.452. 1452
32 5.72222e-05 0.00592209 0.614171 123.379. 2186
33 7.42483e-05 0.00592209 0.624683 115.053. 2236
34 6.9354e-05 0.00592209 0.619596 123.994. 1688
35 5.75478e-05 0.00592209 0.605051 118.576. 1930
36 6.01309e-05 0.00592209 0.617511 116.894. 2184
37 6.69251e-05 0.00592209 0.608408 120.129. 2007
38 4.66926e-05 0.00592209 0.60606 126.708. 1552
39 4.90102e-05 0.00592209 0.618673 114.595. 2783
40 5.51505e-05 0.00592209 0.619245 120.056. 2463
41 6.1007e-05 0.00592209 0.605215 122.057. 1493
42 5.04717e-05 0.00592209 0.623503 116.846. 2620
43 6.3578e-05 0.00592209 0.625261 124.35. 2193
44 5.8875e-05 0.00592209 0.624526 118.43. 2502
45 7.95299e-05 0.00592209 0.611719 116.574. 1849
46 6.42733e-05 0.00592209 0.608178 128.474. 2078
47 6.41674e-05 0.00592209 0.624042 111.111. 2037
48 4.88661e-05 0.00592209 0.615408 120.004. 2627
49 7.27714e-05 0.00592209 0.626926 119.866. 2128
50 4.84641e-05 0.00592209 0.608054 119.676. 2408
51 6.66562e-05 0.00592209 0.603902 128.957. 1668
52 5.99872e-05 0.00592209 0.63676 108.467. 3448
53 7.73127e-05 0.00592209 0.62232 123.353. 1551
54 6.67597e-05 0.00592209 0.621411 123.301. 2180
55 5.2819e-05 0.00592209 0.617515 114.838. 4096
56 5.29257e-05 0.00592209 0.622611 118.611. 1973
57 5.35212e-05 0.00592209 0.62533 109.616. 3424
58 7.1947e-05 0.00592209 0.632331 113.565. 2905
59 5.04311e-05 0.00592209 0.611559 120.01. 2147
60 6.57161e-05 0.00592209 0.617789 125.441. 1820
61 5.18695e-05 0.00592209 0.610402 122.541. 2430
62 6.47262e-05 0.00592209 0.609141 123.169. 1989
63 5.87925e-05 0.00592209 0.61627 117.344. 2143
64 4.36904e-05 0.00592209 0.631954 112.674. 3526
65 6.45195e-05 0.00592209 0.614402 118.787. 1765
66 5.8354e-05 0.00592209 0.615515 112.061. 2368
67 7.14669e-05 0.00592209 0.628382 110.262. 1923
68 7.24908e-05 0.00592209 0.610848 116.504. 1830
69 5.98617e-05 0.00592209 0.622949 109.607. 3609
70 5.90411e-05 0.00592209 0.629175 122.198. 1859
71 5.25569e-05 0.00592209 0.621253 124.527. 1876
72 5.86979e-05 0.00592209 0.612603 120.886. 2916
73 4.73113e-05 0.00592209 0.610586 119.176. 2072
74 5.8777e-05 0.00592209 0.62863 121.081. 2338
75 5.6608e-05 0.00592209 0.617215 121.038. 3021
76 5.74614e-05 0.00592209 0.626088 112.392. 2182
77 6.86466e-05 0.00592209 0.631893 121.148. 2246
78 4.77969e-05 0.00592209 0.635218 117.053. 2939
79 5.50553e-05 0.00592209 0.610707 123.651. 1417
80 6.89628e-05 0.00592209 0.638474 128.446. 1840
81 6.85622e-05 0.00592209 0.620769 115.527. 2116
82 5.28017e-05 0.00592209 0.614948 121.456. 2178
83 7.06916e-05 0.00592209 0.61804 127.418. 2354
84 6.81788e-05 0.00592209 0.616056 113.541. 2768
85 7.89711e-05 0.00592209 0.615108 116.805. 2293
86 5.84297e-05 0.00592209 0.612733 123.244. 2206
87 5.53374e-05 0.00592209 0.605062 123.095. 1902
88 5.51739e-05 0.00592209 0.631543 115.9. 3145
89 6.9413e-05 0.00592209 0.59103 124.024. 1475
90 5.08739e-05 0.00592209 0.621454 114.685. 3356
91 5.95256e-05 0.00592209 0.626188 113.428. 2336
92 5.63659e-05 0.00592209 0.618554 117.456. 2105
93 6.32019e-05 0.00592209 0.616926 122.15. 1799
94 6.05333e-05 0.00592209 0.613481 124.576. 1873
95 5.35997e-05 0.00592209 0.621122 113.63. 2834
96 5.94187e-05 0.00592209 0.606925 126.608. 1970
97 6.52182e-05 0.00592209 0.610882 129.916. 1246
98 6.78626e-05 0.00592209 0.608581 119.673. 2155
99 5.12495e-05 0.00592209 0.6262 116.233. 3037
100 6.7083e-05 0.00592209 0.608299 125.086. 1595
101 6.74099e-05 0.00592209 0.620429 112.897. 2800

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*******************************************************************************
Wed Sep 27 11:56:04 2017
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: f(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 5.3712e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.707107
initial set of free parameter values
a = 1
b = 1
After 7 iterations the fit converged.
final sum of squares of residuals : 2.31113e+07
rel. change during last iteration : -1.94885e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 485.622
variance of residuals (reduced chisquare) = WSSR/ndf : 235829
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = -2.48881e+07 +/- 6.082e+06 (24.44%)
b = 3784.57 +/- 375.9 (9.931%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.992 1.000
*******************************************************************************
Wed Sep 27 11:56:04 2017
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: g(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 5.3684e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.831115
initial set of free parameter values
aa = 1
bb = 1
After 4 iterations the fit converged.
final sum of squares of residuals : 2.25731e+07
rel. change during last iteration : -7.03747e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 479.935
variance of residuals (reduced chisquare) = WSSR/ndf : 230338
Final set of parameters Asymptotic Standard Error
======================= ==========================
aa = 23500.6 +/- 5325 (22.66%)
bb = -12254.4 +/- 3289 (26.84%)
correlation matrix of the fit parameters:
aa bb
aa 1.000
bb -1.000 1.000
*******************************************************************************
Wed Sep 27 11:56:04 2017
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: h(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 1.38452e+06 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.831115
initial set of free parameter values
aaa = 1
bbb = 1
After 5 iterations the fit converged.
final sum of squares of residuals : 1849.66
rel. change during last iteration : -2.46715e-13
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 4.34443
variance of residuals (reduced chisquare) = WSSR/ndf : 18.8741
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaa = -271.314 +/- 48.2 (17.77%)
bbb = 286.74 +/- 29.77 (10.38%)
correlation matrix of the fit parameters:
aaa bbb
aaa 1.000
bbb -1.000 1.000

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Iteration 0
WSSR : 5.3712e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.707107
initial set of free parameter values
a = 1
b = 1
/
Iteration 1
WSSR : 2.70726e+07 delta(WSSR)/WSSR : -18.84
delta(WSSR) : -5.10047e+08 limit for stopping : 1e-05
lambda : 0.0707107
resultant parameter values
a = 0.820391
b = 2248.21
/
Iteration 2
WSSR : 2.70599e+07 delta(WSSR)/WSSR : -0.000466926
delta(WSSR) : -12635 limit for stopping : 1e-05
lambda : 0.00707107
resultant parameter values
a = -30.91
b = 2259.45
/
Iteration 3
WSSR : 2.70589e+07 delta(WSSR)/WSSR : -3.7204e-05
delta(WSSR) : -1006.7 limit for stopping : 1e-05
lambda : 0.000707107
resultant parameter values
a = -3203.66
b = 2259.65
/
Iteration 4
WSSR : 2.69602e+07 delta(WSSR)/WSSR : -0.00366358
delta(WSSR) : -98770.7 limit for stopping : 1e-05
lambda : 7.07107e-05
resultant parameter values
a = -316485
b = 2278.84
/
Iteration 5
WSSR : 2.38549e+07 delta(WSSR)/WSSR : -0.130172
delta(WSSR) : -3.10523e+06 limit for stopping : 1e-05
lambda : 7.07107e-06
resultant parameter values
a = -1.40873e+07
b = 3122.7
/
Iteration 6
WSSR : 2.31113e+07 delta(WSSR)/WSSR : -0.0321763
delta(WSSR) : -743637 limit for stopping : 1e-05
lambda : 7.07107e-07
resultant parameter values
a = -2.48041e+07
b = 3779.42
/
Iteration 7
WSSR : 2.31113e+07 delta(WSSR)/WSSR : -1.94885e-06
delta(WSSR) : -45.0403 limit for stopping : 1e-05
lambda : 7.07107e-08
resultant parameter values
a = -2.48881e+07
b = 3784.57
After 7 iterations the fit converged.
final sum of squares of residuals : 2.31113e+07
rel. change during last iteration : -1.94885e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 485.622
variance of residuals (reduced chisquare) = WSSR/ndf : 235829
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = -2.48881e+07 +/- 6.082e+06 (24.44%)
b = 3784.57 +/- 375.9 (9.931%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.992 1.000
Iteration 0
WSSR : 5.3684e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.831115
initial set of free parameter values
aa = 1
bb = 1
/
Iteration 1
WSSR : 2.66259e+07 delta(WSSR)/WSSR : -19.1623
delta(WSSR) : -5.10214e+08 limit for stopping : 1e-05
lambda : 0.0831115
resultant parameter values
aa = 1195.65
bb = 1510.59
/
Iteration 2
WSSR : 2.37518e+07 delta(WSSR)/WSSR : -0.121004
delta(WSSR) : -2.87407e+06 limit for stopping : 1e-05
lambda : 0.00831115
resultant parameter values
aa = 11455.6
bb = -4815.03
/
Iteration 3
WSSR : 2.25733e+07 delta(WSSR)/WSSR : -0.0522096
delta(WSSR) : -1.17854e+06 limit for stopping : 1e-05
lambda : 0.000831115
resultant parameter values
aa = 23360.8
bb = -12168
/
Iteration 4
WSSR : 2.25731e+07 delta(WSSR)/WSSR : -7.03747e-06
delta(WSSR) : -158.858 limit for stopping : 1e-05
lambda : 8.31115e-05
resultant parameter values
aa = 23500.6
bb = -12254.4
After 4 iterations the fit converged.
final sum of squares of residuals : 2.25731e+07
rel. change during last iteration : -7.03747e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 479.935
variance of residuals (reduced chisquare) = WSSR/ndf : 230338
Final set of parameters Asymptotic Standard Error
======================= ==========================
aa = 23500.6 +/- 5325 (22.66%)
bb = -12254.4 +/- 3289 (26.84%)
correlation matrix of the fit parameters:
aa bb
aa 1.000
bb -1.000 1.000
Iteration 0
WSSR : 1.38452e+06 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.831115
initial set of free parameter values
aaa = 1
bbb = 1
/
Iteration 1
WSSR : 2726.89 delta(WSSR)/WSSR : -506.728
delta(WSSR) : -1.38179e+06 limit for stopping : 1e-05
lambda : 0.0831115
resultant parameter values
aaa = 50.5512
bbb = 87.3622
/
Iteration 2
WSSR : 2095.61 delta(WSSR)/WSSR : -0.301239
delta(WSSR) : -631.281 limit for stopping : 1e-05
lambda : 0.00831115
resultant parameter values
aaa = -97.3216
bbb = 179.278
/
Iteration 3
WSSR : 1849.69 delta(WSSR)/WSSR : -0.13295
delta(WSSR) : -245.917 limit for stopping : 1e-05
lambda : 0.000831115
resultant parameter values
aaa = -269.294
bbb = 285.493
/
Iteration 4
WSSR : 1849.66 delta(WSSR)/WSSR : -1.79209e-05
delta(WSSR) : -0.0331476 limit for stopping : 1e-05
lambda : 8.31115e-05
resultant parameter values
aaa = -271.313
bbb = 286.74
/
Iteration 5
WSSR : 1849.66 delta(WSSR)/WSSR : -2.46715e-13
delta(WSSR) : -4.56339e-10 limit for stopping : 1e-05
lambda : 8.31115e-06
resultant parameter values
aaa = -271.314
bbb = 286.74
After 5 iterations the fit converged.
final sum of squares of residuals : 1849.66
rel. change during last iteration : -2.46715e-13
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 4.34443
variance of residuals (reduced chisquare) = WSSR/ndf : 18.8741
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaa = -271.314 +/- 48.2 (17.77%)
bbb = 286.74 +/- 29.77 (10.38%)
correlation matrix of the fit parameters:
aaa bbb
aaa 1.000
bbb -1.000 1.000

View File

@ -0,0 +1,14 @@
set datafile separator ","
f(x)=a*x+b
fit f(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 via a,b
set terminal png
set output "20170926_3dFit_4x4x4_100times_regularity-vs-steps.png"
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "regularity vs. steps", f(x) lc rgb "black"
g(x)=aa*x+bb
fit g(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 via aa,bb
set output "20170926_3dFit_4x4x4_100times_improvement-vs-steps.png"
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "improvement potential vs. steps", g(x) lc rgb "black"
h(x)=aaa*x+bbb
fit h(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 via aaa,bbb
set output "20170926_3dFit_4x4x4_100times_improvement-vs-evo-error.png"
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "improvement potential vs. evolution error", h(x) lc rgb "black"

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regularity,variability,improvement,"Evolution error",steps
7.0689e-05,0.0115666,0.73748,73.9627.,781
8.30021e-05,0.0115666,0.733986,79.3303.,965
0.000115663,0.0115666,0.754351,72.8373.,1029
0.000115101,0.0115666,0.761361,60.0032.,1435
0.000130222,0.0115666,0.760933,80.1321.,1189
0.000134453,0.0115666,0.765,66.1526.,1209
0.000108858,0.0115666,0.741158,74.6032.,940
0.000100633,0.0115666,0.742555,71.3161.,874
9.22496e-05,0.0115666,0.750011,71.9377.,1407
7.41514e-05,0.0115666,0.742094,70.127.,1525
0.000149467,0.0115666,0.75484,61.7195.,1705
0.000168885,0.0115666,0.73862,86.6101.,593
0.000122462,0.0115666,0.731222,77.235.,770
0.000117266,0.0115666,0.757041,70.3058.,1136
0.000119127,0.0115666,0.747804,73.3268.,890
0.000124455,0.0115666,0.748928,72.8603.,743
9.47125e-05,0.0115666,0.738797,70.5867.,1935
7.9171e-05,0.0115666,0.741438,79.8851.,1007
9.00926e-05,0.0115666,0.729562,89.169.,854
9.71306e-05,0.0115666,0.73793,86.3505.,849
0.000113959,0.0115666,0.738424,77.8282.,842
0.000108279,0.0115666,0.755674,70.418.,1942
6.42834e-05,0.0115666,0.740169,82.3889.,861
8.8094e-05,0.0115666,0.737385,80.3257.,902
8.57496e-05,0.0115666,0.731752,85.6612.,649
7.97196e-05,0.0115666,0.764609,76.2377.,671
0.000107926,0.0115666,0.747697,76.8062.,905
5.63544e-05,0.0115666,0.740041,75.0253.,1091
0.000127036,0.0115666,0.746509,73.6296.,1218
8.93177e-05,0.0115666,0.750775,71.8145.,1018
7.13592e-05,0.0115666,0.746741,82.1172.,1052
0.000121511,0.0115666,0.747184,68.4228.,1322
0.000154913,0.0115666,0.736936,74.5628.,937
0.000120138,0.0115666,0.75356,82.4297.,698
5.97068e-05,0.0115666,0.744391,74.6568.,952
0.000104185,0.0115666,0.7341,76.5874.,1223
0.000123751,0.0115666,0.735266,82.2821.,715
0.000108341,0.0115666,0.744947,71.321.,1058
9.75329e-05,0.0115666,0.746476,80.1887.,1033
6.51759e-05,0.0115666,0.754359,60.0022.,3631
9.35949e-05,0.0115666,0.733867,73.5674.,1300
8.56673e-05,0.0115666,0.744773,68.7547.,1081
7.41782e-05,0.0115666,0.754371,97.4154.,907
0.000111943,0.0115666,0.749778,81.1639.,1013
8.48407e-05,0.0115666,0.726201,82.2747.,473
6.14894e-05,0.0115666,0.746102,70.415.,938
6.76652e-05,0.0115666,0.736705,72.564.,881
9.73343e-05,0.0115666,0.754973,70.1961.,1019
9.54201e-05,0.0115666,0.718442,83.8507.,762
7.51464e-05,0.0115666,0.736317,82.3622.,646
0.000105639,0.0115666,0.741073,74.3285.,1122
0.000131041,0.0115666,0.735624,84.2108.,860
0.000136142,0.0115666,0.754096,69.7744.,1124
8.76576e-05,0.0115666,0.734191,82.1376.,889
8.54651e-05,0.0115666,0.731117,74.2818.,715
0.000121696,0.0115666,0.736555,78.989.,1029
0.000124672,0.0115666,0.748948,82.2812.,939
0.000135654,0.0115666,0.738358,74.0614.,1106
7.8306e-05,0.0115666,0.73738,83.257.,390
0.000117894,0.0115666,0.756543,72.454.,1223
0.000107745,0.0115666,0.729775,71.9554.,1000
0.000177142,0.0115666,0.733159,93.8159.,756
0.000120879,0.0115666,0.752328,64.5602.,979
0.000160079,0.0115666,0.737225,81.597.,836
0.000108096,0.0115666,0.737118,74.8947.,802
0.000104671,0.0115666,0.746382,71.937.,1625
8.82439e-05,0.0115666,0.739388,82.8423.,728
0.000128997,0.0115666,0.754149,66.0827.,1490
0.0001338,0.0115666,0.751957,79.8222.,859
0.000112858,0.0115666,0.745379,80.2208.,729
0.000114923,0.0115666,0.749297,76.7288.,856
7.53845e-05,0.0115666,0.748722,75.2866.,842
7.55779e-05,0.0115666,0.77028,75.6383.,970
8.87548e-05,0.0115666,0.743615,79.3073.,806
8.4754e-05,0.0115666,0.760469,69.5742.,1140
0.000129571,0.0115666,0.745269,76.4946.,975
0.000110111,0.0115666,0.737088,92.7633.,599
6.87804e-05,0.0115666,0.744389,83.3937.,775
0.000101892,0.0115666,0.743134,83.8943.,728
0.000105793,0.0115666,0.742164,73.5603.,1486
0.000108123,0.0115666,0.751606,76.8801.,1162
0.000109415,0.0115666,0.75257,70.703.,1264
0.000118515,0.0115666,0.746588,69.1493.,1822
0.000143603,0.0115666,0.762834,79.6539.,647
8.09027e-05,0.0115666,0.74586,83.4016.,810
8.85206e-05,0.0115666,0.719237,88.5801.,1201
9.85622e-05,0.0115666,0.73017,85.8292.,843
0.000116044,0.0115666,0.741297,72.5448.,1369
0.000104403,0.0115666,0.737101,82.2857.,788
0.000106433,0.0115666,0.741242,83.8247.,1129
6.46802e-05,0.0115666,0.746106,78.3849.,497
8.77417e-05,0.0115666,0.744569,84.6062.,810
0.000103672,0.0115666,0.739614,75.7662.,1202
7.23422e-05,0.0115666,0.742384,78.4256.,687
7.63333e-05,0.0115666,0.740292,68.3999.,1707
0.000167486,0.0115666,0.735526,72.1529.,1386
8.76744e-05,0.0115666,0.736893,78.0544.,775
7.8021e-05,0.0115666,0.740389,89.1144.,578
7.86278e-05,0.0115666,0.722219,86.8059.,708
0.000152359,0.0115666,0.740523,75.2054.,976
1 regularity variability improvement Evolution error steps
2 7.0689e-05 0.0115666 0.73748 73.9627. 781
3 8.30021e-05 0.0115666 0.733986 79.3303. 965
4 0.000115663 0.0115666 0.754351 72.8373. 1029
5 0.000115101 0.0115666 0.761361 60.0032. 1435
6 0.000130222 0.0115666 0.760933 80.1321. 1189
7 0.000134453 0.0115666 0.765 66.1526. 1209
8 0.000108858 0.0115666 0.741158 74.6032. 940
9 0.000100633 0.0115666 0.742555 71.3161. 874
10 9.22496e-05 0.0115666 0.750011 71.9377. 1407
11 7.41514e-05 0.0115666 0.742094 70.127. 1525
12 0.000149467 0.0115666 0.75484 61.7195. 1705
13 0.000168885 0.0115666 0.73862 86.6101. 593
14 0.000122462 0.0115666 0.731222 77.235. 770
15 0.000117266 0.0115666 0.757041 70.3058. 1136
16 0.000119127 0.0115666 0.747804 73.3268. 890
17 0.000124455 0.0115666 0.748928 72.8603. 743
18 9.47125e-05 0.0115666 0.738797 70.5867. 1935
19 7.9171e-05 0.0115666 0.741438 79.8851. 1007
20 9.00926e-05 0.0115666 0.729562 89.169. 854
21 9.71306e-05 0.0115666 0.73793 86.3505. 849
22 0.000113959 0.0115666 0.738424 77.8282. 842
23 0.000108279 0.0115666 0.755674 70.418. 1942
24 6.42834e-05 0.0115666 0.740169 82.3889. 861
25 8.8094e-05 0.0115666 0.737385 80.3257. 902
26 8.57496e-05 0.0115666 0.731752 85.6612. 649
27 7.97196e-05 0.0115666 0.764609 76.2377. 671
28 0.000107926 0.0115666 0.747697 76.8062. 905
29 5.63544e-05 0.0115666 0.740041 75.0253. 1091
30 0.000127036 0.0115666 0.746509 73.6296. 1218
31 8.93177e-05 0.0115666 0.750775 71.8145. 1018
32 7.13592e-05 0.0115666 0.746741 82.1172. 1052
33 0.000121511 0.0115666 0.747184 68.4228. 1322
34 0.000154913 0.0115666 0.736936 74.5628. 937
35 0.000120138 0.0115666 0.75356 82.4297. 698
36 5.97068e-05 0.0115666 0.744391 74.6568. 952
37 0.000104185 0.0115666 0.7341 76.5874. 1223
38 0.000123751 0.0115666 0.735266 82.2821. 715
39 0.000108341 0.0115666 0.744947 71.321. 1058
40 9.75329e-05 0.0115666 0.746476 80.1887. 1033
41 6.51759e-05 0.0115666 0.754359 60.0022. 3631
42 9.35949e-05 0.0115666 0.733867 73.5674. 1300
43 8.56673e-05 0.0115666 0.744773 68.7547. 1081
44 7.41782e-05 0.0115666 0.754371 97.4154. 907
45 0.000111943 0.0115666 0.749778 81.1639. 1013
46 8.48407e-05 0.0115666 0.726201 82.2747. 473
47 6.14894e-05 0.0115666 0.746102 70.415. 938
48 6.76652e-05 0.0115666 0.736705 72.564. 881
49 9.73343e-05 0.0115666 0.754973 70.1961. 1019
50 9.54201e-05 0.0115666 0.718442 83.8507. 762
51 7.51464e-05 0.0115666 0.736317 82.3622. 646
52 0.000105639 0.0115666 0.741073 74.3285. 1122
53 0.000131041 0.0115666 0.735624 84.2108. 860
54 0.000136142 0.0115666 0.754096 69.7744. 1124
55 8.76576e-05 0.0115666 0.734191 82.1376. 889
56 8.54651e-05 0.0115666 0.731117 74.2818. 715
57 0.000121696 0.0115666 0.736555 78.989. 1029
58 0.000124672 0.0115666 0.748948 82.2812. 939
59 0.000135654 0.0115666 0.738358 74.0614. 1106
60 7.8306e-05 0.0115666 0.73738 83.257. 390
61 0.000117894 0.0115666 0.756543 72.454. 1223
62 0.000107745 0.0115666 0.729775 71.9554. 1000
63 0.000177142 0.0115666 0.733159 93.8159. 756
64 0.000120879 0.0115666 0.752328 64.5602. 979
65 0.000160079 0.0115666 0.737225 81.597. 836
66 0.000108096 0.0115666 0.737118 74.8947. 802
67 0.000104671 0.0115666 0.746382 71.937. 1625
68 8.82439e-05 0.0115666 0.739388 82.8423. 728
69 0.000128997 0.0115666 0.754149 66.0827. 1490
70 0.0001338 0.0115666 0.751957 79.8222. 859
71 0.000112858 0.0115666 0.745379 80.2208. 729
72 0.000114923 0.0115666 0.749297 76.7288. 856
73 7.53845e-05 0.0115666 0.748722 75.2866. 842
74 7.55779e-05 0.0115666 0.77028 75.6383. 970
75 8.87548e-05 0.0115666 0.743615 79.3073. 806
76 8.4754e-05 0.0115666 0.760469 69.5742. 1140
77 0.000129571 0.0115666 0.745269 76.4946. 975
78 0.000110111 0.0115666 0.737088 92.7633. 599
79 6.87804e-05 0.0115666 0.744389 83.3937. 775
80 0.000101892 0.0115666 0.743134 83.8943. 728
81 0.000105793 0.0115666 0.742164 73.5603. 1486
82 0.000108123 0.0115666 0.751606 76.8801. 1162
83 0.000109415 0.0115666 0.75257 70.703. 1264
84 0.000118515 0.0115666 0.746588 69.1493. 1822
85 0.000143603 0.0115666 0.762834 79.6539. 647
86 8.09027e-05 0.0115666 0.74586 83.4016. 810
87 8.85206e-05 0.0115666 0.719237 88.5801. 1201
88 9.85622e-05 0.0115666 0.73017 85.8292. 843
89 0.000116044 0.0115666 0.741297 72.5448. 1369
90 0.000104403 0.0115666 0.737101 82.2857. 788
91 0.000106433 0.0115666 0.741242 83.8247. 1129
92 6.46802e-05 0.0115666 0.746106 78.3849. 497
93 8.77417e-05 0.0115666 0.744569 84.6062. 810
94 0.000103672 0.0115666 0.739614 75.7662. 1202
95 7.23422e-05 0.0115666 0.742384 78.4256. 687
96 7.63333e-05 0.0115666 0.740292 68.3999. 1707
97 0.000167486 0.0115666 0.735526 72.1529. 1386
98 8.76744e-05 0.0115666 0.736893 78.0544. 775
99 7.8021e-05 0.0115666 0.740389 89.1144. 578
100 7.86278e-05 0.0115666 0.722219 86.8059. 708
101 0.000152359 0.0115666 0.740523 75.2054. 976

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@ -0,0 +1,138 @@
*******************************************************************************
Wed Sep 27 22:04:33 2017
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: f(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 1.20736e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.707107
initial set of free parameter values
a = 1
b = 1
After 3 iterations the fit converged.
final sum of squares of residuals : 1.62567e+07
rel. change during last iteration : -1.45857e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 407.29
variance of residuals (reduced chisquare) = WSSR/ndf : 165885
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 492.81 +/- 1.574e+06 (3.194e+05%)
b = 1023.1 +/- 167.9 (16.41%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.970 1.000
*******************************************************************************
Wed Sep 27 22:04:33 2017
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: g(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 1.20584e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.881185
initial set of free parameter values
aa = 1
bb = 1
After 4 iterations the fit converged.
final sum of squares of residuals : 1.50391e+07
rel. change during last iteration : -3.68299e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 391.74
variance of residuals (reduced chisquare) = WSSR/ndf : 153460
Final set of parameters Asymptotic Standard Error
======================= ==========================
aa = 11373.7 +/- 4038 (35.5%)
bb = -7433.86 +/- 3003 (40.39%)
correlation matrix of the fit parameters:
aa bb
aa 1.000
bb -1.000 1.000
*******************************************************************************
Wed Sep 27 22:04:33 2017
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4
format = x:z
#datapoints = 100
residuals are weighted equally (unit weight)
function used for fitting: h(x)
fitted parameters initialized with current variable values
Iteration 0
WSSR : 571790 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.881185
initial set of free parameter values
aaa = 1
bbb = 1
After 5 iterations the fit converged.
final sum of squares of residuals : 3867.86
rel. change during last iteration : -2.64534e-13
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.28235
variance of residuals (reduced chisquare) = WSSR/ndf : 39.468
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaa = -328.478 +/- 64.75 (19.71%)
bbb = 321.279 +/- 48.15 (14.99%)
correlation matrix of the fit parameters:
aaa bbb
aaa 1.000
bbb -1.000 1.000

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@ -0,0 +1,228 @@
Iteration 0
WSSR : 1.20736e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.707107
initial set of free parameter values
a = 1
b = 1
/
Iteration 1
WSSR : 1.62593e+07 delta(WSSR)/WSSR : -6.42563
delta(WSSR) : -1.04476e+08 limit for stopping : 1e-05
lambda : 0.0707107
resultant parameter values
a = 1.15399
b = 1018.06
/
Iteration 2
WSSR : 1.62568e+07 delta(WSSR)/WSSR : -0.00015909
delta(WSSR) : -2586.29 limit for stopping : 1e-05
lambda : 0.00707107
resultant parameter values
a = 6.02889
b = 1023.15
/
Iteration 3
WSSR : 1.62567e+07 delta(WSSR)/WSSR : -1.45857e-06
delta(WSSR) : -23.7115 limit for stopping : 1e-05
lambda : 0.000707107
resultant parameter values
a = 492.81
b = 1023.1
After 3 iterations the fit converged.
final sum of squares of residuals : 1.62567e+07
rel. change during last iteration : -1.45857e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 407.29
variance of residuals (reduced chisquare) = WSSR/ndf : 165885
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 492.81 +/- 1.574e+06 (3.194e+05%)
b = 1023.1 +/- 167.9 (16.41%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.970 1.000
Iteration 0
WSSR : 1.20584e+08 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.881185
initial set of free parameter values
aa = 1
bb = 1
/
Iteration 1
WSSR : 1.61394e+07 delta(WSSR)/WSSR : -6.47137
delta(WSSR) : -1.04444e+08 limit for stopping : 1e-05
lambda : 0.0881185
resultant parameter values
aa = 572.195
bb = 593.092
/
Iteration 2
WSSR : 1.53853e+07 delta(WSSR)/WSSR : -0.0490152
delta(WSSR) : -754114 limit for stopping : 1e-05
lambda : 0.00881185
resultant parameter values
aa = 5308.94
bb = -2924.08
/
Iteration 3
WSSR : 1.50391e+07 delta(WSSR)/WSSR : -0.0230181
delta(WSSR) : -346172 limit for stopping : 1e-05
lambda : 0.000881185
resultant parameter values
aa = 11297
bb = -7376.83
/
Iteration 4
WSSR : 1.50391e+07 delta(WSSR)/WSSR : -3.68299e-06
delta(WSSR) : -55.3888 limit for stopping : 1e-05
lambda : 8.81185e-05
resultant parameter values
aa = 11373.7
bb = -7433.86
After 4 iterations the fit converged.
final sum of squares of residuals : 1.50391e+07
rel. change during last iteration : -3.68299e-06
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 391.74
variance of residuals (reduced chisquare) = WSSR/ndf : 153460
Final set of parameters Asymptotic Standard Error
======================= ==========================
aa = 11373.7 +/- 4038 (35.5%)
bb = -7433.86 +/- 3003 (40.39%)
correlation matrix of the fit parameters:
aa bb
aa 1.000
bb -1.000 1.000
Iteration 0
WSSR : 571790 delta(WSSR)/WSSR : 0
delta(WSSR) : 0 limit for stopping : 1e-05
lambda : 0.881185
initial set of free parameter values
aaa = 1
bbb = 1
/
Iteration 1
WSSR : 5120.14 delta(WSSR)/WSSR : -110.675
delta(WSSR) : -566670 limit for stopping : 1e-05
lambda : 0.0881185
resultant parameter values
aaa = 34.035
bbb = 51.3384
/
Iteration 2
WSSR : 4258.4 delta(WSSR)/WSSR : -0.202363
delta(WSSR) : -861.742 limit for stopping : 1e-05
lambda : 0.00881185
resultant parameter values
aaa = -124.79
bbb = 169.816
/
Iteration 3
WSSR : 3867.92 delta(WSSR)/WSSR : -0.100953
delta(WSSR) : -390.477 limit for stopping : 1e-05
lambda : 0.000881185
resultant parameter values
aaa = -325.902
bbb = 319.363
/
Iteration 4
WSSR : 3867.86 delta(WSSR)/WSSR : -1.61531e-05
delta(WSSR) : -0.0624778 limit for stopping : 1e-05
lambda : 8.81185e-05
resultant parameter values
aaa = -328.478
bbb = 321.279
/
Iteration 5
WSSR : 3867.86 delta(WSSR)/WSSR : -2.64534e-13
delta(WSSR) : -1.02318e-09 limit for stopping : 1e-05
lambda : 8.81185e-06
resultant parameter values
aaa = -328.478
bbb = 321.279
After 5 iterations the fit converged.
final sum of squares of residuals : 3867.86
rel. change during last iteration : -2.64534e-13
degrees of freedom (FIT_NDF) : 98
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.28235
variance of residuals (reduced chisquare) = WSSR/ndf : 39.468
Final set of parameters Asymptotic Standard Error
======================= ==========================
aaa = -328.478 +/- 64.75 (19.71%)
bbb = 321.279 +/- 48.15 (14.99%)
correlation matrix of the fit parameters:
aaa bbb
aaa 1.000
bbb -1.000 1.000

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set datafile separator ","
f(x)=a*x+b
fit f(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 via a,b
set terminal png
set output "20170926_3dFit_5x5x5_100times_regularity-vs-steps.png"
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 title "regularity vs. steps", f(x) lc rgb "black"
g(x)=aa*x+bb
fit g(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 via aa,bb
set output "20170926_3dFit_5x5x5_100times_improvement-vs-steps.png"
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 title "improvement potential vs. steps", g(x) lc rgb "black"
h(x)=aaa*x+bbb
fit h(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 via aaa,bbb
set output "20170926_3dFit_5x5x5_100times_improvement-vs-evo-error.png"
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 title "improvement potential vs. evolution error", h(x) lc rgb "black"

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#!/bin/bash
if [[ $# -ne 1 ]]; then
echo "usage: $0 <DATA.csv>"
else
data="$1";
png="`echo $1 | sed -s "s/\.csv$//"`" # strip ending
(cat <<EOD
set datafile separator ","
f(x)=a*x+b
fit f(x) "$data" every ::1 using 1:5 via a,b
set terminal png
set output "${png}_regularity-vs-steps.png"
plot "$data" every ::1 using 1:5 title "regularity vs. steps", f(x) lc rgb "black"
g(x)=aa*x+bb
fit g(x) "$data" every ::1 using 3:5 via aa,bb
set output "${png}_improvement-vs-steps.png"
plot "$data" every ::1 using 3:5 title "improvement potential vs. steps", g(x) lc rgb "black"
h(x)=aaa*x+bbb
fit h(x) "$data" every ::1 using 3:4 via aaa,bbb
set output "${png}_improvement-vs-evo-error.png"
plot "$data" every ::1 using 3:4 title "improvement potential vs. evolution error", h(x) lc rgb "black"
EOD
) > "${png}.gnuplot.script"
gnuplot "${png}.gnuplot.script" 2> "${png}.gnuplot.log"
mv fit.log "${png}.gnuplot.fit.log"
fi

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#!/bin/bash
echo "regularity,variability,improvement,\"Evolution error\",steps"
cat "$1" | grep "EVOL" \
| sed -s "s/info: EVOL: //" \
| grep -v "info:" \
| grep -v "Evolvability" \
| grep -v "Converged after" \
| sed -s "s/regularity: //" \
| sed -s "s/variability: //" \
| sed -s "s/improvement: //" \
| sed -s "s/Best value: //" \
| sed -s "s/TOTAL STEPS: //" \
| while read -r ONE; do
read -r TWO
read -r THREE
read -r FOUR
read -r FIVE
echo "$ONE,$TWO,$THREE,$FOUR,$FIVE"
done