more graphs for evo1d

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-added_one.gnuplot.fit.log

@@ -1,7 +1,7 @@
 
 
 *******************************************************************************
-Wed Aug 30 22:31:49 2017
+Sun Oct  1 19:59:33 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5
@@ -47,7 +47,7 @@ b              -0.996  1.000
 
 
 *******************************************************************************
-Wed Aug 30 22:31:49 2017
+Sun Oct  1 19:59:33 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5
@@ -93,7 +93,7 @@ bb             -1.000  1.000
 
 
 *******************************************************************************
-Wed Aug 30 22:31:49 2017
+Sun Oct  1 19:59:33 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-added_one.gnuplot.script

@@ -2,13 +2,19 @@ set datafile separator ","
 f(x)=a*x+b
 fit f(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 via a,b
 set terminal png
+set xlabel 'regularity'
+set ylabel 'steps'
 set output "20170830-evolution1D_5x5_100Times-added_one_regularity-vs-steps.png"
-plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "regularity vs. steps", f(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
 g(x)=aa*x+bb
 fit g(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 via aa,bb
+set xlabel 'improvement potential'
+set ylabel 'steps'
 set output "20170830-evolution1D_5x5_100Times-added_one_improvement-vs-steps.png"
-plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "improvement potential vs. steps", g(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
 h(x)=aaa*x+bbb
 fit h(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 via aaa,bbb
+set xlabel 'improvement potential'
+set ylabel 'evolution error'
 set output "20170830-evolution1D_5x5_100Times-added_one_improvement-vs-evo-error.png"
-plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "improvement potential vs. evolution error", h(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-all.csv

@@ -0,0 +1,201 @@
+"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
+183.763,0.0179571,0.00111111,0.938632,228,192.44,0.032644
+229.099,0.0189281,0.00111111,0.923492,96,240.171,0.0562716
+238.479,0.0215758,0.00111111,0.920359,195,249.883,0.0272032
+188.152,0.0144312,0.00111111,0.937166,256,197.529,0.0244736
+191.586,0.0207835,0.00111111,0.936019,156,201.143,0.0235659
+202.916,0.0168021,0.00111111,0.932236,220,212.978,0.0318143
+178.439,0.0180162,0.00111111,0.94041,259,187.236,0.0269287
+229.734,0.0238245,0.00111111,0.92328,203,241.13,0.0281426
+211.994,0.0192363,0.00111111,0.929204,211,222.511,0.0152364
+245.717,0.0185166,0.00111111,0.917942,154,256.592,0.0379309
+225.543,0.0204032,0.00111111,0.92468,160,236.693,0.0243299
+211.533,0.0207268,0.00111111,0.929358,135,221.694,0.0377055
+213.806,0.022426,0.00111111,0.928599,188,224.469,0.0237864
+223.483,0.0172601,0.00111111,0.925368,203,234.382,0.0196412
+231.924,0.0177059,0.00111111,0.922549,209,243.433,0.0259235
+184.824,0.0162623,0.00111111,0.938278,242,194.032,0.0222468
+223.766,0.0179083,0.00111111,0.925273,207,234.567,0.0301655
+203.27,0.0161445,0.00111111,0.932118,220,213.401,0.0273719
+193.158,0.0166659,0.00111111,0.935494,221,201.428,0.0414548
+197.851,0.0185201,0.00111111,0.933927,195,207.224,0.0362339
+214.041,0.0178594,0.00111111,0.928521,139,224.585,0.0340444
+211.533,0.018782,0.00111111,0.929358,132,221.895,0.0369246
+185.356,0.0195083,0.00111111,0.9381,222,194.499,0.0184425
+198.81,0.0201802,0.00111111,0.933607,242,208.589,0.0259606
+205.265,0.0202697,0.00111111,0.931451,184,215.456,0.0190532
+222.952,0.019699,0.00111111,0.925545,178,234.028,0.0261726
+205.276,0.0193633,0.00111111,0.931448,191,214.716,0.02818
+230.047,0.0214453,0.00111111,0.923175,216,241.431,0.0234518
+196.924,0.0190251,0.00111111,0.934237,183,206.599,0.0212354
+195.184,0.0181113,0.00111111,0.934818,178,204.769,0.0299481
+194.787,0.018323,0.00111111,0.934951,212,204.23,0.0294953
+212.533,0.0182128,0.00111111,0.929024,231,222.938,0.0412254
+176.623,0.0158336,0.00111111,0.941017,209,185.355,0.0266792
+209.136,0.0204612,0.00111111,0.930159,91,218.429,0.0579325
+209.848,0.0201986,0.00111111,0.929921,163,219.886,0.0336554
+209.515,0.0191636,0.00111111,0.930032,185,219.696,0.0286176
+193.943,0.0178079,0.00111111,0.935233,199,203.581,0.0232988
+216.239,0.0212003,0.00111111,0.927787,151,226.759,0.0189421
+211.37,0.0162232,0.00111111,0.929413,173,221.819,0.0171682
+224.988,0.0196037,0.00111111,0.924865,112,236.226,0.0602406
+207.221,0.0185908,0.00111111,0.930798,157,217.553,0.0314001
+203.513,0.0172686,0.00111111,0.932037,188,213.564,0.0328506
+186.642,0.0195431,0.00111111,0.937671,178,195.759,0.0419734
+236.265,0.0204047,0.00111111,0.921099,106,247.931,0.0409088
+222.669,0.0231925,0.00111111,0.925639,162,233.713,0.0215862
+223.48,0.0208053,0.00111111,0.925369,190,234.013,0.0261078
+213.098,0.0182925,0.00111111,0.928835,227,223.628,0.0354102
+185.847,0.0198307,0.00111111,0.937936,217,194.983,0.0198853
+215.818,0.0211463,0.00111111,0.927927,212,226.437,0.0327274
+203.914,0.0228368,0.00111111,0.931903,219,214.086,0.0166239
+177.639,0.0183023,0.00111111,0.940677,243,186.419,0.0388416
+187.065,0.0182927,0.00111111,0.937529,217,196.416,0.0185577
+224.069,0.0206082,0.00111111,0.925172,240,235.058,0.0214527
+233.059,0.020766,0.00111111,0.922169,249,244.587,0.0304497
+243.252,0.0197131,0.00111111,0.918766,218,255.376,0.0210078
+216.096,0.018823,0.00111111,0.927834,240,226.808,0.0218857
+229.899,0.0235834,0.00111111,0.923225,185,241.372,0.0226563
+214.545,0.02158,0.00111111,0.928352,180,225.08,0.0281248
+201.315,0.0215738,0.00111111,0.932771,122,210.821,0.0306565
+196.866,0.0199231,0.00111111,0.934256,254,206.672,0.0171958
+191.811,0.0187791,0.00111111,0.935944,264,201.399,0.0284519
+234.589,0.0153778,0.00111111,0.921659,173,246.066,0.0288251
+241.822,0.0210075,0.00111111,0.919243,147,253.875,0.0448453
+247.389,0.020118,0.00111111,0.917384,180,259.741,0.0237541
+197.862,0.0191194,0.00111111,0.933924,258,207.655,0.0309044
+227.298,0.0193875,0.00111111,0.924094,189,238.654,0.0244366
+203.016,0.0194783,0.00111111,0.932203,345,213.147,0.0293344
+200.344,0.0181137,0.00111111,0.933095,211,210.34,0.0279667
+260.653,0.0211892,0.00111111,0.912955,159,273.684,0.0173598
+190.801,0.018724,0.00111111,0.936282,145,200.321,0.0244174
+219.31,0.0152034,0.00111111,0.926761,298,230.127,0.0304617
+201.013,0.0189705,0.00111111,0.932871,154,210.898,0.0368793
+214.751,0.0212631,0.00111111,0.928283,189,224.914,0.0281325
+199.042,0.0200792,0.00111111,0.93353,228,208.711,0.0294291
+222.258,0.0190311,0.00111111,0.925777,220,233.241,0.0218053
+193.965,0.0185556,0.00111111,0.935225,281,203.658,0.0236132
+216.305,0.0220209,0.00111111,0.927765,187,227.058,0.0289074
+209.518,0.0164836,0.00111111,0.930031,193,219.89,0.0252204
+202.805,0.0195855,0.00111111,0.932273,235,212.877,0.0518397
+205.584,0.0203958,0.00111111,0.931345,203,215.439,0.0362367
+181.975,0.0182167,0.00111111,0.939229,173,191.017,0.0257238
+161.995,0.0204489,0.00111111,0.945902,260,170.069,0.0166518
+194.688,0.0204944,0.00111111,0.934984,184,204.348,0.0314503
+185.811,0.0200401,0.00111111,0.937948,332,195.049,0.0270099
+197.624,0.020823,0.00111111,0.934003,281,207.186,0.0391989
+214.766,0.0218128,0.00111111,0.928278,157,225.229,0.0353567
+219.632,0.0173274,0.00111111,0.926653,160,230.466,0.036049
+202.581,0.0162571,0.00111111,0.932348,237,212.578,0.0297746
+181.621,0.0177214,0.00111111,0.939347,316,190.496,0.0259462
+250.268,0.0185787,0.00111111,0.916423,135,262.382,0.0245029
+205.717,0.0178907,0.00111111,0.931301,255,215.988,0.0274579
+197.391,0.0189724,0.00111111,0.934081,215,206.934,0.0376919
+238.981,0.0223217,0.00111111,0.920192,100,250.737,0.0435432
+196.091,0.01434,0.00111111,0.934515,190,205.827,0.0556249
+202.756,0.0184759,0.00111111,0.932289,271,212.891,0.0270203
+191.765,0.0184657,0.00111111,0.93596,193,201.034,0.0201355
+202.525,0.0186188,0.00111111,0.932366,239,212.53,0.0201397
+198.694,0.0176067,0.00111111,0.933646,278,208.545,0.0231376
+196.578,0.0184124,0.00111111,0.934353,226,206.327,0.0391784
+190.046,0.0198379,0.00111111,0.936534,133,199.413,0.0284771
+198.091,0.0185605,0.00111111,0.933847,245,207.886,0.0152523
+234.524,0.0192422,0.00111111,0.92168,203,245.873,0.0333896
+199.665,0.0169589,0.00111111,0.933322,236,209.253,0.0256795
+225.432,0.019794,0.00111111,0.924717,164,236.693,0.0303567
+226.331,0.0198218,0.00111111,0.924416,133,237.512,0.0326327
+207.081,0.0183173,0.00111111,0.930845,293,217.347,0.0173303
+197.215,0.0195282,0.00111111,0.93414,144,206.725,0.0274424
+207.985,0.018551,0.00111111,0.930543,167,218.216,0.0264904
+199.179,0.0192478,0.00111111,0.933484,230,208.831,0.0280096
+190.622,0.0185748,0.00111111,0.936342,146,199.805,0.040456
+186.169,0.0193022,0.00111111,0.937829,196,195.163,0.0339487
+184.072,0.0170487,0.00111111,0.938529,224,193.258,0.0325346
+173.247,0.0203667,0.00111111,0.942144,191,181.901,0.0186411
+174.505,0.0185505,0.00111111,0.941724,232,183.091,0.0391035
+204.996,0.019809,0.00111111,0.931541,126,215.233,0.0317816
+201.159,0.0177293,0.00111111,0.932823,231,210.992,0.033055
+215.57,0.0184879,0.00111111,0.92801,157,226.197,0.0248099
+220.4,0.0220813,0.00111111,0.926397,120,230.55,0.0266999
+192.669,0.0189865,0.00111111,0.935658,197,201.997,0.0273896
+217.249,0.0209109,0.00111111,0.927449,196,227.649,0.0314102
+183.442,0.0177993,0.00111111,0.938739,276,192.577,0.0290511
+211.058,0.0191396,0.00111111,0.929517,262,221.454,0.0258037
+225.405,0.0142923,0.00111111,0.924726,232,236.59,0.0554429
+214.129,0.0153926,0.00111111,0.928491,258,224.637,0.025707
+191.681,0.0159947,0.00111111,0.935988,221,201.263,0.0168213
+208.302,0.0168977,0.00111111,0.930437,267,218.685,0.0303307
+244.265,0.0186614,0.00111111,0.918427,240,256.401,0.014142
+217.424,0.0189707,0.00111111,0.927391,194,228.137,0.0234014
+193.974,0.0187277,0.00111111,0.935222,200,203.421,0.0313489
+217.843,0.0191009,0.00111111,0.927251,244,228.677,0.0186412
+228.126,0.0195362,0.00111111,0.923817,171,239.173,0.0237806
+194.236,0.0205534,0.00111111,0.935135,206,203.783,0.0222971
+231.826,0.017672,0.00111111,0.922582,126,243.217,0.0354461
+194.684,0.0180998,0.00111111,0.934985,149,204.188,0.0265668
+201.513,0.0176892,0.00111111,0.932705,232,211.535,0.0277219
+219.557,0.016394,0.00111111,0.926679,145,229.573,0.0466214
+215.208,0.0203045,0.00111111,0.928131,217,225.773,0.0198841
+224.784,0.0187965,0.00111111,0.924933,207,235.748,0.0249149
+198.752,0.0192186,0.00111111,0.933626,214,208.659,0.0198508
+210.374,0.0169978,0.00111111,0.929745,201,220.83,0.029392
+182.397,0.0156577,0.00111111,0.939088,271,191.357,0.0356415
+214.532,0.017907,0.00111111,0.928357,187,224.938,0.0315807
+206.254,0.0198955,0.00111111,0.931121,144,216.195,0.0261497
+208.845,0.019427,0.00111111,0.930256,302,218.868,0.0293849
+219.847,0.018273,0.00111111,0.926582,205,230.63,0.0222702
+178.072,0.0161684,0.00111111,0.940532,271,186.89,0.0224425
+208.094,0.0174596,0.00111111,0.930507,188,218.199,0.026439
+206.759,0.017792,0.00111111,0.930952,249,217.047,0.0196121
+213.588,0.0179354,0.00111111,0.928672,154,223.644,0.0261114
+203.691,0.0186109,0.00111111,0.931977,215,213.801,0.029634
+196.02,0.0164293,0.00111111,0.934539,286,205.631,0.0248201
+200.893,0.0206686,0.00111111,0.932911,218,210.824,0.0165101
+219.308,0.018868,0.00111111,0.926762,202,230.178,0.0193291
+246.019,0.0189353,0.00111111,0.917842,155,257.369,0.0271402
+231.847,0.0197966,0.00111111,0.922574,168,243.262,0.0289334
+218.91,0.0209849,0.00111111,0.926895,197,229.047,0.0299942
+211.126,0.0167501,0.00111111,0.929494,196,221.493,0.0286991
+169.535,0.0151348,0.00111111,0.943383,175,177.905,0.0337364
+230.113,0.0201869,0.00111111,0.923153,167,241.468,0.0344348
+231.924,0.0200713,0.00111111,0.922549,149,243.443,0.0257716
+223.016,0.0200786,0.00111111,0.925524,178,233.782,0.0402102
+195.674,0.014894,0.00111111,0.934654,268,205.347,0.0551882
+255.95,0.0195439,0.00111111,0.914525,148,268.384,0.0447607
+220.055,0.0198234,0.00111111,0.926512,236,230.853,0.0367555
+216.155,0.0189146,0.00111111,0.927815,129,226.312,0.0430726
+199.784,0.0187532,0.00111111,0.933282,199,209.55,0.0353292
+222.549,0.0203982,0.00111111,0.925679,178,233.426,0.0233115
+200.95,0.0183086,0.00111111,0.932893,256,210.991,0.016803
+209.249,0.016696,0.00111111,0.930121,269,219.415,0.02081
+249.03,0.0223912,0.00111111,0.916836,177,260.926,0.0294009
+219.09,0.019419,0.00111111,0.926835,218,229.786,0.0289335
+185.792,0.0169305,0.00111111,0.937954,291,194.888,0.0258978
+184.383,0.0208635,0.00111111,0.938425,256,193.57,0.0185135
+201.82,0.0183427,0.00111111,0.932602,236,211.086,0.0474114
+226.705,0.0196988,0.00111111,0.924292,255,237.989,0.0227452
+206.776,0.019382,0.00111111,0.930947,187,217.102,0.0280757
+185.74,0.0141851,0.00111111,0.937972,166,194.775,0.0321003
+232.792,0.0240912,0.00111111,0.922259,191,244.384,0.0176279
+201.838,0.0188448,0.00111111,0.932596,181,211.814,0.0297108
+202.159,0.0179769,0.00111111,0.932489,175,212.073,0.0239756
+178.922,0.018115,0.00111111,0.940249,259,187.619,0.0215103
+196.096,0.0172259,0.00111111,0.934514,220,205.625,0.030462
+200.913,0.0195059,0.00111111,0.932905,162,210.781,0.0383751
+182.439,0.020238,0.00111111,0.939074,172,191.55,0.0264845
+169.79,0.018196,0.00111111,0.943298,226,178.258,0.0148133
+185.191,0.0167884,0.00111111,0.938155,194,194.329,0.0261194
+202.268,0.0211018,0.00111111,0.932452,200,212.217,0.0301675
+191.444,0.0189881,0.00111111,0.936067,211,200.944,0.0234532
+216.792,0.0196005,0.00111111,0.927602,200,227.453,0.0212078
+252.534,0.0172473,0.00111111,0.915666,225,264.972,0.0178314
+193.043,0.0156078,0.00111111,0.935533,226,202.656,0.0411515
+192.167,0.0174455,0.00111111,0.935826,195,201.39,0.0254769
+225.725,0.0178959,0.00111111,0.924619,240,236.882,0.018903
+204.599,0.0213119,0.00111111,0.931674,171,214.712,0.0263085
+185.635,0.0163761,0.00111111,0.938007,190,194.569,0.0284307
+186.264,0.016572,0.00111111,0.937797,232,195.513,0.0210752
+249.948,0.0194051,0.00111111,0.91653,246,262.158,0.0215199
+240.864,0.0182591,0.00111111,0.919563,188,251.577,0.0306745
+184.618,0.0171253,0.00111111,0.938346,222,193.849,0.0300316
+213.473,0.0190352,0.00111111,0.92871,275,224.14,0.0207037

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-all.gnuplot.fit.log

@@ -0,0 +1,138 @@
+
+
+*******************************************************************************
+Sun Oct  1 20:05:21 2017
+
+
+FIT:    data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 2:5
+        format = x:z
+        #datapoints = 200
+        residuals are weighted equally (unit weight)
+
+function used for fitting: f(x)
+fitted parameters initialized with current variable values
+
+
+
+ Iteration 0
+ WSSR        : 8.65799e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.707234
+
+initial set of free parameter values
+
+a               = 1
+b               = 1
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 387750
+rel. change during last iteration : -1.80465e-10
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 44.2531
+variance of residuals (reduced chisquare) = WSSR/ndf   : 1958.33
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+a               = -7207.93         +/- 1699         (23.57%)
+b               = 339.971          +/- 32.22        (9.477%)
+
+
+correlation matrix of the fit parameters:
+
+               a      b      
+a               1.000 
+b              -0.995  1.000 
+
+
+*******************************************************************************
+Sun Oct  1 20:05:21 2017
+
+
+FIT:    data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:5
+        format = x:z
+        #datapoints = 200
+        residuals are weighted equally (unit weight)
+
+function used for fitting: g(x)
+fitted parameters initialized with current variable values
+
+
+
+ Iteration 0
+ WSSR        : 8.58412e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.965888
+
+initial set of free parameter values
+
+aa              = 1
+bb              = 1
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 374307
+rel. change during last iteration : -1.28123e-12
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 43.4792
+variance of residuals (reduced chisquare) = WSSR/ndf   : 1890.44
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+aa              = 2485.68          +/- 489.8        (19.71%)
+bb              = -2109            +/- 455.8        (21.61%)
+
+
+correlation matrix of the fit parameters:
+
+               aa     bb     
+aa              1.000 
+bb             -1.000  1.000 
+
+
+*******************************************************************************
+Sun Oct  1 20:05:21 2017
+
+
+FIT:    data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:6
+        format = x:z
+        #datapoints = 200
+        residuals are weighted equally (unit weight)
+
+function used for fitting: h(x)
+fitted parameters initialized with current variable values
+
+
+
+ Iteration 0
+ WSSR        : 9.43971e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.965888
+
+initial set of free parameter values
+
+aaa             = 1
+bbb             = 1
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 11.3578
+rel. change during last iteration : -7.81502e-08
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 0.239505
+variance of residuals (reduced chisquare) = WSSR/ndf   : 0.0573625
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+aaa             = -3135.44         +/- 2.698        (0.08605%)
+bbb             = 3135.83          +/- 2.511        (0.08006%)
+
+
+correlation matrix of the fit parameters:
+
+               aaa    bbb    
+aaa             1.000 
+bbb            -1.000  1.000 

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-all.gnuplot.log

@@ -0,0 +1,261 @@
+
+
+ Iteration 0
+ WSSR        : 8.65799e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.707234
+
+initial set of free parameter values
+
+a               = 1
+b               = 1
+/
+
+ Iteration 1
+ WSSR        : 422995            delta(WSSR)/WSSR   : -19.4683
+ delta(WSSR) : -8.235e+06        limit for stopping : 1e-05
+ lambda	  : 0.0707234
+
+resultant parameter values
+
+a               = -4.94625
+b               = 203.522
+/
+
+ Iteration 2
+ WSSR        : 415042            delta(WSSR)/WSSR   : -0.0191613
+ delta(WSSR) : -7952.76          limit for stopping : 1e-05
+ lambda	  : 0.00707234
+
+resultant parameter values
+
+a               = -864.859
+b               = 220.257
+/
+
+ Iteration 3
+ WSSR        : 387879            delta(WSSR)/WSSR   : -0.0700308
+ delta(WSSR) : -27163.5          limit for stopping : 1e-05
+ lambda	  : 0.000707234
+
+resultant parameter values
+
+a               = -6772.19
+b               = 331.747
+/
+
+ Iteration 4
+ WSSR        : 387750            delta(WSSR)/WSSR   : -0.000332164
+ delta(WSSR) : -128.797          limit for stopping : 1e-05
+ lambda	  : 7.07234e-05
+
+resultant parameter values
+
+a               = -7207.61
+b               = 339.965
+/
+
+ Iteration 5
+ WSSR        : 387750            delta(WSSR)/WSSR   : -1.80465e-10
+ delta(WSSR) : -6.99755e-05      limit for stopping : 1e-05
+ lambda	  : 7.07234e-06
+
+resultant parameter values
+
+a               = -7207.93
+b               = 339.971
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 387750
+rel. change during last iteration : -1.80465e-10
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 44.2531
+variance of residuals (reduced chisquare) = WSSR/ndf   : 1958.33
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+a               = -7207.93         +/- 1699         (23.57%)
+b               = 339.971          +/- 32.22        (9.477%)
+
+
+correlation matrix of the fit parameters:
+
+               a      b      
+a               1.000 
+b              -0.995  1.000 
+
+
+ Iteration 0
+ WSSR        : 8.58412e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.965888
+
+initial set of free parameter values
+
+aa              = 1
+bb              = 1
+/
+
+ Iteration 1
+ WSSR        : 418736            delta(WSSR)/WSSR   : -19.5001
+ delta(WSSR) : -8.16538e+06      limit for stopping : 1e-05
+ lambda	  : 0.0965888
+
+resultant parameter values
+
+aa              = 112.257
+bb              = 99.0225
+/
+
+ Iteration 2
+ WSSR        : 395337            delta(WSSR)/WSSR   : -0.0591881
+ delta(WSSR) : -23399.2          limit for stopping : 1e-05
+ lambda	  : 0.00965888
+
+resultant parameter values
+
+aa              = 852.014
+bb              = -588.836
+/
+
+ Iteration 3
+ WSSR        : 374316            delta(WSSR)/WSSR   : -0.0561565
+ delta(WSSR) : -21020.3          limit for stopping : 1e-05
+ lambda	  : 0.000965888
+
+resultant parameter values
+
+aa              = 2450.37
+bb              = -2076.15
+/
+
+ Iteration 4
+ WSSR        : 374307            delta(WSSR)/WSSR   : -2.6247e-05
+ delta(WSSR) : -9.82442          limit for stopping : 1e-05
+ lambda	  : 9.65888e-05
+
+resultant parameter values
+
+aa              = 2485.68
+bb              = -2109
+/
+
+ Iteration 5
+ WSSR        : 374307            delta(WSSR)/WSSR   : -1.28123e-12
+ delta(WSSR) : -4.79573e-07      limit for stopping : 1e-05
+ lambda	  : 9.65888e-06
+
+resultant parameter values
+
+aa              = 2485.68
+bb              = -2109
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 374307
+rel. change during last iteration : -1.28123e-12
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 43.4792
+variance of residuals (reduced chisquare) = WSSR/ndf   : 1890.44
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+aa              = 2485.68          +/- 489.8        (19.71%)
+bb              = -2109            +/- 455.8        (21.61%)
+
+
+correlation matrix of the fit parameters:
+
+               aa     bb     
+aa              1.000 
+bb             -1.000  1.000 
+
+
+ Iteration 0
+ WSSR        : 9.43971e+06       delta(WSSR)/WSSR   : 0
+ delta(WSSR) : 0                 limit for stopping : 1e-05
+ lambda	  : 0.965888
+
+initial set of free parameter values
+
+aaa             = 1
+bbb             = 1
+/
+
+ Iteration 1
+ WSSR        : 82262.8           delta(WSSR)/WSSR   : -113.751
+ delta(WSSR) : -9.35745e+06      limit for stopping : 1e-05
+ lambda	  : 0.0965888
+
+resultant parameter values
+
+aaa             = 93.9799
+bbb             = 130.237
+/
+
+ Iteration 2
+ WSSR        : 38961.1           delta(WSSR)/WSSR   : -1.11141
+ delta(WSSR) : -43301.7          limit for stopping : 1e-05
+ lambda	  : 0.00965888
+
+resultant parameter values
+
+aaa             = -912.157
+bbb             = 1067.01
+/
+
+ Iteration 3
+ WSSR        : 29.5535           delta(WSSR)/WSSR   : -1317.32
+ delta(WSSR) : -38931.6          limit for stopping : 1e-05
+ lambda	  : 0.000965888
+
+resultant parameter values
+
+aaa             = -3087.39
+bbb             = 3091.12
+/
+
+ Iteration 4
+ WSSR        : 11.3578           delta(WSSR)/WSSR   : -1.60205
+ delta(WSSR) : -18.1958          limit for stopping : 1e-05
+ lambda	  : 9.65888e-05
+
+resultant parameter values
+
+aaa             = -3135.43
+bbb             = 3135.82
+/
+
+ Iteration 5
+ WSSR        : 11.3578           delta(WSSR)/WSSR   : -7.81502e-08
+ delta(WSSR) : -8.87612e-07      limit for stopping : 1e-05
+ lambda	  : 9.65888e-06
+
+resultant parameter values
+
+aaa             = -3135.44
+bbb             = 3135.83
+
+After 5 iterations the fit converged.
+final sum of squares of residuals : 11.3578
+rel. change during last iteration : -7.81502e-08
+
+degrees of freedom    (FIT_NDF)                        : 198
+rms of residuals      (FIT_STDFIT) = sqrt(WSSR/ndf)    : 0.239505
+variance of residuals (reduced chisquare) = WSSR/ndf   : 0.0573625
+
+Final set of parameters            Asymptotic Standard Error
+=======================            ==========================
+
+aaa             = -3135.44         +/- 2.698        (0.08605%)
+bbb             = 3135.83          +/- 2.511        (0.08006%)
+
+
+correlation matrix of the fit parameters:
+
+               aaa    bbb    
+aaa             1.000 
+bbb            -1.000  1.000 

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times-all.gnuplot.script

@@ -0,0 +1,20 @@
+set datafile separator ","
+f(x)=a*x+b
+fit f(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 2:5 via a,b
+set terminal png
+set xlabel 'regularity'
+set ylabel 'steps'
+set output "20170830-evolution1D_5x5_100Times-all_regularity-vs-steps.png"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", f(x) title "lin. fit" lc rgb "black"
+g(x)=aa*x+bb
+fit g(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:5 via aa,bb
+set xlabel 'improvement potential'
+set ylabel 'steps'
+set output "20170830-evolution1D_5x5_100Times-all_improvement-vs-steps.png"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", g(x) title "lin. fit" lc rgb "black"
+h(x)=aaa*x+bbb
+fit h(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:6 via aaa,bbb
+set xlabel 'improvement potential'
+set ylabel 'evolution error'
+set output "20170830-evolution1D_5x5_100Times-all_improvement-vs-evo-error.png"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times-added_one.csv", h(x) title "lin. fit" lc rgb "black"

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times.gnuplot.fit.log

@@ -1,7 +1,7 @@
 
 
 *******************************************************************************
-Wed Aug 30 21:11:12 2017
+Sun Oct  1 19:58:40 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5
@@ -47,7 +47,7 @@ b              -0.995  1.000
 
 
 *******************************************************************************
-Wed Aug 30 21:11:12 2017
+Sun Oct  1 19:58:40 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5
@@ -93,7 +93,7 @@ bb             -1.000  1.000
 
 
 *******************************************************************************
-Wed Aug 30 21:11:12 2017
+Sun Oct  1 19:58:40 2017
 
 
 FIT:    data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6

dokumentation/evolution1d/20170830-evolution1D_5x5_100Times.gnuplot.script

@@ -2,13 +2,19 @@ set datafile separator ","
 f(x)=a*x+b
 fit f(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 via a,b
 set terminal png
+set xlabel 'regularity'
+set ylabel 'steps'
 set output "20170830-evolution1D_5x5_100Times_regularity-vs-steps.png"
-plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "regularity vs. steps", f(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
 g(x)=aa*x+bb
 fit g(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 via aa,bb
+set xlabel 'improvement potential'
+set ylabel 'steps'
 set output "20170830-evolution1D_5x5_100Times_improvement-vs-steps.png"
-plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "improvement potential vs. steps", g(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
 h(x)=aaa*x+bbb
 fit h(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 via aaa,bbb
+set xlabel 'improvement potential'
+set ylabel 'evolution error'
 set output "20170830-evolution1D_5x5_100Times_improvement-vs-evo-error.png"
-plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "improvement potential vs. evolution error", h(x) lc rgb "black"
+plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"

dokumentation/evolution1d/combine.sh

@@ -0,0 +1,33 @@
+#!/bin/bash
+
+if [[ $# -eq 0 ]]; 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) "$data" every ::1 using 2:5 via a,b
+set terminal png
+set xlabel 'regularity'
+set ylabel 'steps'
+set output "${png}_regularity-vs-steps.png"
+plot "$2" every ::1 using 2:5 title "$2", "$3" every ::1 using 2:5 title "$3", f(x) title "lin. fit" lc rgb "black"
+g(x)=aa*x+bb
+fit g(x) "$data" every ::1 using 4:5 via aa,bb
+set xlabel 'improvement potential'
+set ylabel 'steps'
+set output "${png}_improvement-vs-steps.png"
+plot "$2" every ::1 using 4:5 title "$2", "$3" every ::1 using 4:5 title "$3", g(x) title "lin. fit" lc rgb "black"
+h(x)=aaa*x+bbb
+fit h(x) "$data" every ::1 using 4:6 via aaa,bbb
+set xlabel 'improvement potential'
+set ylabel 'evolution error'
+set output "${png}_improvement-vs-evo-error.png"
+plot "$2" every ::1 using 4:6 title "$2", "$3" every ::1 using 4:6 title "$3", h(x) title "lin. fit" lc rgb "black"
+EOD
+) > "${png}.gnuplot.script" 
+    gnuplot "${png}.gnuplot.script" 2> "${png}.gnuplot.log"
+    mv fit.log "${png}.gnuplot.fit.log"
+fi

dokumentation/evolution1d/images.sh

@@ -10,16 +10,22 @@ set datafile separator ","
 f(x)=a*x+b
 fit f(x) "$data" every ::1 using 2:5 via a,b
 set terminal png
+set xlabel 'regularity'
+set ylabel 'steps'
 set output "${png}_regularity-vs-steps.png"
-plot "$data" every ::1 using 2:5 title "regularity vs. steps", f(x) lc rgb "black"
+plot "$data" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
 g(x)=aa*x+bb
 fit g(x) "$data" every ::1 using 4:5 via aa,bb
+set xlabel 'improvement potential'
+set ylabel 'steps'
 set output "${png}_improvement-vs-steps.png"
-plot "$data" every ::1 using 4:5 title "improvement potential vs. steps", g(x) lc rgb "black"
+plot "$data" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
 h(x)=aaa*x+bbb
 fit h(x) "$data" every ::1 using 4:6 via aaa,bbb
+set xlabel 'improvement potential'
+set ylabel 'evolution error'
 set output "${png}_improvement-vs-evo-error.png"
-plot "$data" every ::1 using 4:6 title "improvement potential vs. evolution error", h(x) lc rgb "black"
+plot "$data" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
 EOD
 ) > "${png}.gnuplot.script" 
     gnuplot "${png}.gnuplot.script" 2> "${png}.gnuplot.log"