weitere 1D evo
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501
dokumentation/evolution1d/20171005-all.csv
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dokumentation/evolution1d/20171005-all.csv
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"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
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183.763,0.0179571,0.00111111,0.938632,228,192.44,0.032644
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229.099,0.0189281,0.00111111,0.923492,96,240.171,0.0562716
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238.479,0.0215758,0.00111111,0.920359,195,249.883,0.0272032
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188.152,0.0144312,0.00111111,0.937166,256,197.529,0.0244736
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191.586,0.0207835,0.00111111,0.936019,156,201.143,0.0235659
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202.916,0.0168021,0.00111111,0.932236,220,212.978,0.0318143
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178.439,0.0180162,0.00111111,0.94041,259,187.236,0.0269287
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229.734,0.0238245,0.00111111,0.92328,203,241.13,0.0281426
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211.994,0.0192363,0.00111111,0.929204,211,222.511,0.0152364
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245.717,0.0185166,0.00111111,0.917942,154,256.592,0.0379309
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225.543,0.0204032,0.00111111,0.92468,160,236.693,0.0243299
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211.533,0.0207268,0.00111111,0.929358,135,221.694,0.0377055
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213.806,0.022426,0.00111111,0.928599,188,224.469,0.0237864
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223.483,0.0172601,0.00111111,0.925368,203,234.382,0.0196412
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231.924,0.0177059,0.00111111,0.922549,209,243.433,0.0259235
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184.824,0.0162623,0.00111111,0.938278,242,194.032,0.0222468
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223.766,0.0179083,0.00111111,0.925273,207,234.567,0.0301655
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203.27,0.0161445,0.00111111,0.932118,220,213.401,0.0273719
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193.158,0.0166659,0.00111111,0.935494,221,201.428,0.0414548
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197.851,0.0185201,0.00111111,0.933927,195,207.224,0.0362339
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214.041,0.0178594,0.00111111,0.928521,139,224.585,0.0340444
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211.533,0.018782,0.00111111,0.929358,132,221.895,0.0369246
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185.356,0.0195083,0.00111111,0.9381,222,194.499,0.0184425
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198.81,0.0201802,0.00111111,0.933607,242,208.589,0.0259606
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205.265,0.0202697,0.00111111,0.931451,184,215.456,0.0190532
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222.952,0.019699,0.00111111,0.925545,178,234.028,0.0261726
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205.276,0.0193633,0.00111111,0.931448,191,214.716,0.02818
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230.047,0.0214453,0.00111111,0.923175,216,241.431,0.0234518
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196.924,0.0190251,0.00111111,0.934237,183,206.599,0.0212354
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195.184,0.0181113,0.00111111,0.934818,178,204.769,0.0299481
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194.787,0.018323,0.00111111,0.934951,212,204.23,0.0294953
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212.533,0.0182128,0.00111111,0.929024,231,222.938,0.0412254
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176.623,0.0158336,0.00111111,0.941017,209,185.355,0.0266792
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209.136,0.0204612,0.00111111,0.930159,91,218.429,0.0579325
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209.848,0.0201986,0.00111111,0.929921,163,219.886,0.0336554
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209.515,0.0191636,0.00111111,0.930032,185,219.696,0.0286176
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193.943,0.0178079,0.00111111,0.935233,199,203.581,0.0232988
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216.239,0.0212003,0.00111111,0.927787,151,226.759,0.0189421
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211.37,0.0162232,0.00111111,0.929413,173,221.819,0.0171682
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224.988,0.0196037,0.00111111,0.924865,112,236.226,0.0602406
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207.221,0.0185908,0.00111111,0.930798,157,217.553,0.0314001
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203.513,0.0172686,0.00111111,0.932037,188,213.564,0.0328506
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186.642,0.0195431,0.00111111,0.937671,178,195.759,0.0419734
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236.265,0.0204047,0.00111111,0.921099,106,247.931,0.0409088
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222.669,0.0231925,0.00111111,0.925639,162,233.713,0.0215862
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223.48,0.0208053,0.00111111,0.925369,190,234.013,0.0261078
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213.098,0.0182925,0.00111111,0.928835,227,223.628,0.0354102
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185.847,0.0198307,0.00111111,0.937936,217,194.983,0.0198853
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215.818,0.0211463,0.00111111,0.927927,212,226.437,0.0327274
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203.914,0.0228368,0.00111111,0.931903,219,214.086,0.0166239
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177.639,0.0183023,0.00111111,0.940677,243,186.419,0.0388416
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187.065,0.0182927,0.00111111,0.937529,217,196.416,0.0185577
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224.069,0.0206082,0.00111111,0.925172,240,235.058,0.0214527
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233.059,0.020766,0.00111111,0.922169,249,244.587,0.0304497
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243.252,0.0197131,0.00111111,0.918766,218,255.376,0.0210078
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216.096,0.018823,0.00111111,0.927834,240,226.808,0.0218857
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229.899,0.0235834,0.00111111,0.923225,185,241.372,0.0226563
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214.545,0.02158,0.00111111,0.928352,180,225.08,0.0281248
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201.315,0.0215738,0.00111111,0.932771,122,210.821,0.0306565
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196.866,0.0199231,0.00111111,0.934256,254,206.672,0.0171958
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191.811,0.0187791,0.00111111,0.935944,264,201.399,0.0284519
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234.589,0.0153778,0.00111111,0.921659,173,246.066,0.0288251
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241.822,0.0210075,0.00111111,0.919243,147,253.875,0.0448453
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247.389,0.020118,0.00111111,0.917384,180,259.741,0.0237541
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197.862,0.0191194,0.00111111,0.933924,258,207.655,0.0309044
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227.298,0.0193875,0.00111111,0.924094,189,238.654,0.0244366
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203.016,0.0194783,0.00111111,0.932203,345,213.147,0.0293344
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200.344,0.0181137,0.00111111,0.933095,211,210.34,0.0279667
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260.653,0.0211892,0.00111111,0.912955,159,273.684,0.0173598
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190.801,0.018724,0.00111111,0.936282,145,200.321,0.0244174
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219.31,0.0152034,0.00111111,0.926761,298,230.127,0.0304617
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201.013,0.0189705,0.00111111,0.932871,154,210.898,0.0368793
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214.751,0.0212631,0.00111111,0.928283,189,224.914,0.0281325
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199.042,0.0200792,0.00111111,0.93353,228,208.711,0.0294291
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222.258,0.0190311,0.00111111,0.925777,220,233.241,0.0218053
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193.965,0.0185556,0.00111111,0.935225,281,203.658,0.0236132
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216.305,0.0220209,0.00111111,0.927765,187,227.058,0.0289074
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209.518,0.0164836,0.00111111,0.930031,193,219.89,0.0252204
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202.805,0.0195855,0.00111111,0.932273,235,212.877,0.0518397
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205.584,0.0203958,0.00111111,0.931345,203,215.439,0.0362367
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181.975,0.0182167,0.00111111,0.939229,173,191.017,0.0257238
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161.995,0.0204489,0.00111111,0.945902,260,170.069,0.0166518
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194.688,0.0204944,0.00111111,0.934984,184,204.348,0.0314503
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185.811,0.0200401,0.00111111,0.937948,332,195.049,0.0270099
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197.624,0.020823,0.00111111,0.934003,281,207.186,0.0391989
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214.766,0.0218128,0.00111111,0.928278,157,225.229,0.0353567
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219.632,0.0173274,0.00111111,0.926653,160,230.466,0.036049
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202.581,0.0162571,0.00111111,0.932348,237,212.578,0.0297746
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181.621,0.0177214,0.00111111,0.939347,316,190.496,0.0259462
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250.268,0.0185787,0.00111111,0.916423,135,262.382,0.0245029
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205.717,0.0178907,0.00111111,0.931301,255,215.988,0.0274579
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197.391,0.0189724,0.00111111,0.934081,215,206.934,0.0376919
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238.981,0.0223217,0.00111111,0.920192,100,250.737,0.0435432
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196.091,0.01434,0.00111111,0.934515,190,205.827,0.0556249
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202.756,0.0184759,0.00111111,0.932289,271,212.891,0.0270203
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191.765,0.0184657,0.00111111,0.93596,193,201.034,0.0201355
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202.525,0.0186188,0.00111111,0.932366,239,212.53,0.0201397
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198.694,0.0176067,0.00111111,0.933646,278,208.545,0.0231376
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196.578,0.0184124,0.00111111,0.934353,226,206.327,0.0391784
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190.046,0.0198379,0.00111111,0.936534,133,199.413,0.0284771
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198.091,0.0185605,0.00111111,0.933847,245,207.886,0.0152523
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234.524,0.0192422,0.00111111,0.92168,203,245.873,0.0333896
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199.665,0.0169589,0.00111111,0.933322,236,209.253,0.0256795
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225.432,0.019794,0.00111111,0.924717,164,236.693,0.0303567
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226.331,0.0198218,0.00111111,0.924416,133,237.512,0.0326327
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207.081,0.0183173,0.00111111,0.930845,293,217.347,0.0173303
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197.215,0.0195282,0.00111111,0.93414,144,206.725,0.0274424
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207.985,0.018551,0.00111111,0.930543,167,218.216,0.0264904
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183.442,0.0177993,0.00111111,0.938739,276,192.577,0.0290511
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211.058,0.0191396,0.00111111,0.929517,262,221.454,0.0258037
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225.405,0.0142923,0.00111111,0.924726,232,236.59,0.0554429
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214.129,0.0153926,0.00111111,0.928491,258,224.637,0.025707
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191.681,0.0159947,0.00111111,0.935988,221,201.263,0.0168213
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208.302,0.0168977,0.00111111,0.930437,267,218.685,0.0303307
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244.265,0.0186614,0.00111111,0.918427,240,256.401,0.014142
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232.792,0.0240912,0.00111111,0.922259,191,244.384,0.0176279
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|
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216.792,0.0196005,0.00111111,0.927602,200,227.453,0.0212078
|
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252.534,0.0172473,0.00111111,0.915666,225,264.972,0.0178314
|
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193.043,0.0156078,0.00111111,0.935533,226,202.656,0.0411515
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|
||||
199.436,0.0181063,0.00124444,0.933398,365,209.245,0.0217639
|
||||
225.485,0.0172431,0.00124444,0.924699,196,235.881,0.032626
|
||||
230.548,0.0145494,0.00124444,0.923008,224,241.881,0.0357782
|
||||
220.164,0.014643,0.00124444,0.926476,221,231.035,0.021201
|
||||
210.607,0.0149307,0.00124444,0.929668,197,220.946,0.027384
|
||||
202.034,0.0154935,0.00124444,0.932531,219,212.015,0.0227197
|
||||
223.702,0.0156465,0.00124444,0.925294,220,234.886,0.0202163
|
||||
223.274,0.0153501,0.00124444,0.925437,237,234.38,0.0210493
|
||||
239.317,0.0139175,0.00124444,0.92008,167,250.999,0.0352055
|
||||
219.42,0.0157887,0.00124444,0.926724,194,229.239,0.0410685
|
||||
211.502,0.0159828,0.00124444,0.929368,183,222.041,0.021811
|
||||
198.88,0.0172708,0.00124444,0.933584,139,208.038,0.0256466
|
||||
207.561,0.0138982,0.00124444,0.930685,199,217.716,0.016863
|
||||
210.296,0.0164974,0.00124444,0.929771,195,220.769,0.0256633
|
||||
120.527,0.0305651,0.00217778,0.95975,182,126.241,0.0274436
|
||||
105.717,0.0304078,0.00217778,0.964696,282,110.962,0.0158715
|
||||
119.901,0.0296548,0.00217778,0.959959,224,125.853,0.0221449
|
||||
133.689,0.0301734,0.00217778,0.955354,233,140.195,0.0223482
|
||||
120.918,0.0297028,0.00217778,0.959619,175,126.647,0.0197707
|
||||
147.295,0.0283644,0.00217778,0.950811,243,154.539,0.0261081
|
||||
102.228,0.0319967,0.00217778,0.965861,251,107.206,0.0145694
|
||||
122.622,0.0252732,0.00217778,0.95905,232,128.558,0.0183895
|
||||
130.819,0.0325323,0.00217778,0.956313,169,136.77,0.0248296
|
||||
139.062,0.029404,0.00217778,0.95356,239,145.941,0.0198192
|
||||
163.931,0.0284774,0.00217778,0.945255,197,171.996,0.0243894
|
||||
113.252,0.0321719,0.00217778,0.962179,241,118.437,0.0246194
|
||||
137.3,0.0283919,0.00217778,0.954149,176,143.556,0.0201642
|
||||
115.119,0.0300041,0.00217778,0.961556,295,120.873,0.0178014
|
||||
100.904,0.0288716,0.00217778,0.966303,208,105.887,0.0200813
|
||||
147.487,0.024799,0.00217778,0.950747,189,154.67,0.0243077
|
||||
147.404,0.0277859,0.00217778,0.950774,143,154.182,0.0287594
|
||||
110.849,0.0278082,0.00217778,0.962982,247,116.314,0.0130491
|
||||
108.144,0.0317319,0.00217778,0.963885,221,113.496,0.0213925
|
||||
152.471,0.0309984,0.00217778,0.949082,193,159.92,0.0216455
|
||||
151.301,0.0316553,0.00217778,0.949473,183,158.727,0.026995
|
||||
103.761,0.0245259,0.00217778,0.965349,208,108.387,0.0261726
|
||||
141.47,0.0299984,0.00217778,0.952756,215,148.334,0.0212445
|
||||
107.693,0.0288702,0.00217778,0.964036,237,112.767,0.0184018
|
||||
132.834,0.0291123,0.00217778,0.95564,243,139.428,0.0137168
|
||||
118.598,0.0294951,0.00217778,0.960394,224,124.479,0.0151507
|
||||
101.31,0.0290843,0.00217778,0.966168,277,106.309,0.0130174
|
||||
133.211,0.0291807,0.00217778,0.955514,223,139.721,0.0234585
|
||||
127.816,0.031699,0.00217778,0.957316,228,133.951,0.0207455
|
||||
128.875,0.0282553,0.00217778,0.956962,205,135.062,0.0212527
|
||||
128.065,0.0277151,0.00217778,0.957233,232,133.884,0.0207377
|
||||
114.407,0.0308509,0.00217778,0.961794,248,120.051,0.0177078
|
||||
96.6405,0.0323881,0.00217778,0.967727,257,101.318,0.0205648
|
||||
128.856,0.0302615,0.00217778,0.956968,196,135.279,0.0185934
|
||||
104.861,0.0307769,0.00217778,0.964981,300,110.051,0.0107628
|
||||
130.225,0.0302749,0.00217778,0.956511,206,136.437,0.0178083
|
||||
128.374,0.025948,0.00217778,0.957129,198,134.697,0.0240022
|
||||
108.68,0.0299555,0.00217778,0.963706,261,113.78,0.0165322
|
||||
116.83,0.0285706,0.00217778,0.960984,214,122.484,0.0175649
|
||||
109.654,0.0290142,0.00217778,0.963381,201,114.487,0.0242023
|
||||
121.709,0.0293128,0.00217778,0.959355,181,127.55,0.0230015
|
||||
119.756,0.0299435,0.00217778,0.960007,266,125.629,0.0222042
|
||||
154.595,0.0296071,0.00217778,0.948373,161,162.041,0.031111
|
||||
148.94,0.0288307,0.00217778,0.950261,189,156.364,0.0201626
|
||||
108.541,0.0309115,0.00217778,0.963753,215,113.788,0.0194676
|
||||
131.712,0.0305304,0.00217778,0.956015,170,138.26,0.0233339
|
||||
104.985,0.0269759,0.00217778,0.96494,223,109.996,0.0200455
|
||||
156.935,0.0277759,0.00217778,0.947591,197,164.442,0.0274963
|
||||
101.562,0.0270836,0.00217778,0.966083,228,105.711,0.0285827
|
||||
149.172,0.0293507,0.00217778,0.950184,266,156.553,0.0137586
|
||||
110.786,0.0301022,0.00217778,0.963003,225,116.304,0.0160115
|
||||
108.126,0.0296889,0.00217778,0.963891,272,113.339,0.0139973
|
||||
113.396,0.0280885,0.00217778,0.962131,184,118.637,0.0206842
|
||||
157.303,0.0286129,0.00217778,0.947469,205,164.957,0.0204323
|
||||
92.5603,0.0310149,0.00217778,0.969089,288,97.1774,0.0118406
|
||||
131.31,0.0312147,0.00217778,0.956149,201,137.814,0.0216513
|
||||
151.662,0.0264346,0.00217778,0.949352,241,158.652,0.0206991
|
||||
122.986,0.0296999,0.00217778,0.958929,239,128.639,0.0250375
|
||||
138.21,0.0276365,0.00217778,0.953845,210,144.853,0.0221076
|
||||
130.258,0.0288724,0.00217778,0.9565,203,136.728,0.0240955
|
||||
95.4606,0.0305017,0.00217778,0.968121,264,100.103,0.0134085
|
||||
123.79,0.0302927,0.00217778,0.95866,290,129.972,0.0120363
|
||||
128.023,0.0269328,0.00217778,0.957247,263,134.171,0.0176036
|
||||
97.4169,0.0294049,0.00217778,0.967467,283,102.086,0.0154436
|
||||
131.497,0.032637,0.00217778,0.956086,194,137.823,0.0230214
|
||||
114.486,0.0296235,0.00217778,0.961767,209,120.165,0.0182154
|
||||
115.802,0.030273,0.00217778,0.961328,249,121.511,0.0168117
|
||||
104.888,0.0298335,0.00217778,0.964972,266,110.067,0.0157024
|
||||
107.529,0.0299312,0.00217778,0.96409,214,112.614,0.0242658
|
||||
100.39,0.0284705,0.00217778,0.966475,228,105.271,0.0152932
|
||||
134.206,0.0300452,0.00217778,0.955182,190,140.821,0.0262343
|
||||
118.423,0.0285713,0.00217778,0.960452,230,124.285,0.0195539
|
||||
150.763,0.0269517,0.00217778,0.949652,188,158.103,0.0213998
|
||||
134.048,0.0302692,0.00217778,0.955234,169,140.515,0.0308499
|
||||
96.9072,0.029681,0.00217778,0.967638,245,101.64,0.0165011
|
||||
123.811,0.0258042,0.00217778,0.958653,254,129.887,0.0140323
|
||||
159.564,0.0304946,0.00217778,0.946713,205,167.194,0.0194008
|
||||
105.757,0.0290973,0.00217778,0.964682,238,110.881,0.0179311
|
||||
139.738,0.0289451,0.00217778,0.953334,194,146.669,0.0262391
|
||||
112.768,0.0276706,0.00217778,0.962341,195,118.035,0.0156339
|
||||
143.501,0.0254884,0.00217778,0.952078,256,150.583,0.0127485
|
||||
136.72,0.0262001,0.00217778,0.954342,244,143.211,0.0193324
|
||||
109.952,0.0287195,0.00217778,0.963281,223,114.785,0.0241593
|
||||
139.559,0.029377,0.00217778,0.953394,187,146.421,0.0183773
|
||||
124.8,0.028991,0.00217778,0.958323,220,130.875,0.0179003
|
||||
102.291,0.0285261,0.00217778,0.96584,278,107.373,0.0140422
|
||||
144.967,0.0281308,0.00217778,0.951588,234,152.164,0.0189975
|
||||
123.808,0.031638,0.00217778,0.958654,185,129.282,0.0314699
|
||||
93.612,0.0275759,0.00217778,0.968738,271,98.1416,0.0124221
|
||||
123.829,0.0279283,0.00217778,0.958647,199,129.997,0.0222236
|
||||
111.654,0.0290171,0.00217778,0.962713,183,117,0.0200822
|
||||
105.848,0.0278707,0.00217778,0.964652,235,111.092,0.0159004
|
||||
108.727,0.0240196,0.00217778,0.96369,330,114.087,0.0151336
|
||||
102.465,0.0285859,0.00217778,0.965782,267,107.558,0.0137917
|
||||
137.886,0.0315396,0.00217778,0.953953,162,144.45,0.0198371
|
||||
112.847,0.0258472,0.00217778,0.962315,233,118.484,0.0194957
|
||||
104.672,0.0280787,0.00217778,0.965045,270,109.701,0.017613
|
||||
121.264,0.0247246,0.00217778,0.959504,181,126.593,0.0240936
|
||||
161.034,0.0240912,0.00217778,0.946223,165,168.971,0.0262645
|
||||
137.026,0.0283714,0.00217778,0.95424,262,143.838,0.02069
|
||||
|
144
dokumentation/evolution1d/20171005-all.gnuplot.fit.log
Normal file
144
dokumentation/evolution1d/20171005-all.gnuplot.fit.log
Normal file
@ -0,0 +1,144 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 500
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 2.2819584538e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
4 9.2387072945e+05 -3.77e-04 7.07e-05 5.253352e+02 1.999370e+02
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 923871
|
||||
rel. change during last iteration : -3.77204e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 43.0716
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1855.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = 525.335 +/- 371.3 (70.69%)
|
||||
b = 199.937 +/- 7.551 (3.777%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.967 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 500
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 2.2629211027e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
4 8.9631538551e+05 -2.78e-05 9.66e-05 4.610660e+02 -2.189272e+02
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 896315
|
||||
rel. change during last iteration : -2.77934e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 42.4244
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1799.83
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 461.066 +/- 110.6 (23.99%)
|
||||
bb = -218.927 +/- 103 (47.04%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 500
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 2.4597834778e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
5 4.4603658393e+01 -1.73e-08 9.66e-06 -3.139922e+03 3.139954e+03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 44.6037
|
||||
rel. change during last iteration : -1.72842e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.299275
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0895656
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3139.92 +/- 0.7803 (0.02485%)
|
||||
bbb = 3139.95 +/- 0.7265 (0.02314%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 3:6
|
||||
format = x:z
|
||||
#datapoints = 500
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
i(x)=aaaa*x+bbbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
0 2.4797348325e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 6.2575820484e+05 -6.78e-01 7.07e-06 -1.004063e+05 3.554273e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 625758
|
||||
rel. change during last iteration : -6.77885e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 35.4477
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1256.54
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaaa = -100406 +/- 3920 (3.904%)
|
||||
bbbb = 355.427 +/- 5.629 (1.584%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.960 1.000
|
||||
102
dokumentation/evolution1d/20171005-all.gnuplot.log
Normal file
102
dokumentation/evolution1d/20171005-all.gnuplot.log
Normal file
@ -0,0 +1,102 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 2.2819584538e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 9.2734539506e+05 -2.36e+06 7.07e-02 1.872894e+01 2.096890e+02
|
||||
2 9.2412450892e+05 -3.49e+02 7.07e-03 3.879916e+02 2.026375e+02
|
||||
3 9.2387073294e+05 -2.75e+01 7.07e-04 5.248262e+02 1.999470e+02
|
||||
4 9.2387072945e+05 -3.77e-04 7.07e-05 5.253352e+02 1.999370e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 923871
|
||||
rel. change during last iteration : -3.77204e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 43.0716
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1855.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = 525.335 +/- 371.3 (70.69%)
|
||||
b = 199.937 +/- 7.551 (3.777%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.967 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 2.2629211027e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
1 9.1220178149e+05 -2.38e+06 9.66e-02 1.325557e+02 8.671371e+01
|
||||
2 8.9649334140e+05 -1.75e+03 9.66e-03 4.262842e+02 -1.865447e+02
|
||||
3 8.9631538576e+05 -1.99e+01 9.66e-04 4.610248e+02 -2.188888e+02
|
||||
4 8.9631538551e+05 -2.78e-05 9.66e-05 4.610660e+02 -2.189272e+02
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 896315
|
||||
rel. change during last iteration : -2.77934e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 42.4244
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1799.83
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 461.066 +/- 110.6 (23.99%)
|
||||
bb = -218.927 +/- 103 (47.04%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 2.4597834778e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3196790874e+06 -1.76e+06 9.66e-02 -1.448795e+02 3.513002e+02
|
||||
2 1.4846794008e+04 -8.79e+06 9.66e-03 -2.822704e+03 2.844618e+03
|
||||
3 4.4624379637e+01 -3.32e+07 9.66e-04 -3.139547e+03 3.139604e+03
|
||||
4 4.4603658393e+01 -4.65e+01 9.66e-05 -3.139922e+03 3.139954e+03
|
||||
5 4.4603658393e+01 -1.73e-08 9.66e-06 -3.139922e+03 3.139954e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 44.6037
|
||||
rel. change during last iteration : -1.72842e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.299275
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0895656
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3139.92 +/- 0.7803 (0.02485%)
|
||||
bbb = 3139.95 +/- 0.7265 (0.02314%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
0 2.4797348325e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.4499765510e+06 -1.61e+06 7.07e-02 -1.512219e+01 2.168949e+02
|
||||
2 1.4236400853e+06 -1.85e+03 7.07e-03 -1.630660e+03 2.193366e+02
|
||||
3 7.4062425817e+05 -9.22e+04 7.07e-04 -6.292829e+04 3.037910e+02
|
||||
4 6.2576244676e+05 -1.84e+04 7.07e-05 -1.001785e+05 3.551135e+02
|
||||
5 6.2575820484e+05 -6.78e-01 7.07e-06 -1.004063e+05 3.554273e+02
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 625758
|
||||
rel. change during last iteration : -6.77885e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 35.4477
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1256.54
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaaa = -100406 +/- 3920 (3.904%)
|
||||
bbbb = 355.427 +/- 5.629 (1.584%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.960 1.000
|
||||
26
dokumentation/evolution1d/20171005-all.gnuplot.script
Normal file
26
dokumentation/evolution1d/20171005-all.gnuplot.script
Normal file
@ -0,0 +1,26 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-all.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-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", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_7x7_100Times.csv", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005-all.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-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", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_7x7_100Times.csv", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005-all.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-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", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_7x7_100Times.csv", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171005-all.csv" every ::1 using 3:6 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-all_variability-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 3:6 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 3:6 title "20170830-evolution1D_5x5_100Times-added_one.csv", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_7x7_100Times.csv", i(x) title "lin. fit" lc rgb "black"
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 7.6 KiB |
BIN
dokumentation/evolution1d/20171005-all_improvement-vs-steps.png
Normal file
BIN
dokumentation/evolution1d/20171005-all_improvement-vs-steps.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 12 KiB |
BIN
dokumentation/evolution1d/20171005-all_regularity-vs-steps.png
Normal file
BIN
dokumentation/evolution1d/20171005-all_regularity-vs-steps.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 11 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 6.6 KiB |
101
dokumentation/evolution1d/20171005-evolution1D_4x7_100Times.csv
Normal file
101
dokumentation/evolution1d/20171005-evolution1D_4x7_100Times.csv
Normal file
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
267.876,0.0160237,0.00124444,0.910542,173,280.917,0.041317
|
||||
301.035,0.0149818,0.00124444,0.899469,192,315.729,0.0371435
|
||||
252.283,0.016224,0.00124444,0.91575,186,264.639,0.0251523
|
||||
262.811,0.0143632,0.00124444,0.912234,228,275.922,0.0292345
|
||||
307.779,0.0168661,0.00124444,0.897217,247,323.159,0.0446967
|
||||
287.196,0.0162634,0.00124444,0.90409,153,300.933,0.0402748
|
||||
252.185,0.0186589,0.00124444,0.915782,204,264.541,0.0537674
|
||||
252.368,0.0185828,0.00124444,0.915721,163,264.875,0.0516944
|
||||
273.504,0.0153228,0.00124444,0.908663,206,286.999,0.0589335
|
||||
299.8,0.015452,0.00124444,0.899881,252,314.771,0.0322635
|
||||
242.916,0.0165246,0.00124444,0.918878,207,254.996,0.0375956
|
||||
258.239,0.0130383,0.00124444,0.913761,240,270.99,0.0271465
|
||||
320.936,0.0142181,0.00124444,0.892823,127,336.401,0.0474298
|
||||
238.158,0.0182024,0.00124444,0.920467,195,249.761,0.0431037
|
||||
296.336,0.0164207,0.00124444,0.901038,171,310.473,0.0315425
|
||||
269.239,0.0126131,0.00124444,0.910087,187,282.476,0.0734215
|
||||
288.295,0.0160129,0.00124444,0.903723,153,301.45,0.0409347
|
||||
290.458,0.0165057,0.00124444,0.903001,215,304.67,0.0372574
|
||||
286.663,0.0166434,0.00124444,0.904268,226,300.451,0.0414395
|
||||
300.22,0.0182222,0.00124444,0.899741,174,315.122,0.0280977
|
||||
288.785,0.0149497,0.00124444,0.90356,251,302.947,0.0310956
|
||||
250.657,0.0167552,0.00124444,0.916293,192,262.796,0.0357012
|
||||
259.912,0.012238,0.00124444,0.913202,293,272.873,0.0517974
|
||||
277.775,0.0144144,0.00124444,0.907237,229,291.472,0.0314516
|
||||
267.052,0.0167378,0.00124444,0.910818,204,280.073,0.040238
|
||||
262.339,0.0144557,0.00124444,0.912391,189,274.973,0.0494119
|
||||
264.729,0.0144438,0.00124444,0.911593,182,277.642,0.0599785
|
||||
253.582,0.0174023,0.00124444,0.915316,230,266.096,0.0268471
|
||||
286.594,0.0157891,0.00124444,0.904292,194,300.458,0.0522694
|
||||
269.748,0.0129119,0.00124444,0.909917,181,281.797,0.0678929
|
||||
276.445,0.0153961,0.00124444,0.907681,172,287.84,0.0616759
|
||||
257.365,0.0192891,0.00124444,0.914053,137,270.181,0.0442534
|
||||
290.578,0.0130388,0.00124444,0.902961,230,304.713,0.0312996
|
||||
286.822,0.0141783,0.00124444,0.904215,228,301.015,0.0325938
|
||||
239.331,0.0156718,0.00124444,0.920075,296,250.936,0.0318135
|
||||
312.447,0.0182524,0.00124444,0.895658,252,327.876,0.0256484
|
||||
254.695,0.0185449,0.00124444,0.914944,202,267.093,0.0335235
|
||||
254.524,0.0141017,0.00124444,0.915001,249,266.032,0.0379196
|
||||
280.578,0.0169944,0.00124444,0.906301,214,293.5,0.0607412
|
||||
262.034,0.0159614,0.00124444,0.912493,196,274.145,0.0441671
|
||||
288.236,0.0136483,0.00124444,0.903743,211,302.284,0.0553983
|
||||
282.566,0.0162714,0.00124444,0.905637,259,296.447,0.0386496
|
||||
277.384,0.0144486,0.00124444,0.907367,234,290.496,0.0723565
|
||||
310.869,0.0161428,0.00124444,0.896185,255,326.409,0.0480313
|
||||
240.505,0.0152832,0.00124444,0.919683,216,252.376,0.0350769
|
||||
271.764,0.0168533,0.00124444,0.909244,161,285.256,0.0431168
|
||||
248.918,0.0160118,0.00124444,0.916874,204,261.023,0.05097
|
||||
260.936,0.0166911,0.00124444,0.91286,319,273.732,0.0188483
|
||||
273.958,0.0145448,0.00124444,0.908511,251,287.211,0.0305499
|
||||
235.056,0.0163734,0.00124444,0.921503,258,246.715,0.0317013
|
||||
303.02,0.0151119,0.00124444,0.898806,199,317.892,0.0592121
|
||||
253.213,0.0182013,0.00124444,0.915439,236,265.825,0.0371061
|
||||
247.874,0.0157508,0.00124444,0.917222,245,259.862,0.0417326
|
||||
260.379,0.0137206,0.00124444,0.913046,235,273.217,0.0402591
|
||||
257.113,0.0160861,0.00124444,0.914137,256,269.759,0.0330447
|
||||
299.543,0.0150175,0.00124444,0.899967,220,314.394,0.045574
|
||||
302.404,0.0167334,0.00124444,0.899012,187,314.765,0.0707083
|
||||
271.225,0.0181028,0.00124444,0.909424,257,284.627,0.0206609
|
||||
250.03,0.0160492,0.00124444,0.916502,232,262.319,0.0595344
|
||||
256.332,0.0128525,0.00124444,0.914397,220,269.132,0.0465511
|
||||
248.162,0.018139,0.00124444,0.917126,202,259.973,0.0298866
|
||||
282.813,0.0169151,0.00124444,0.905554,159,296.171,0.0453673
|
||||
252.465,0.0164028,0.00124444,0.915689,228,264.153,0.0481631
|
||||
294.434,0.0150393,0.00124444,0.901673,195,307.381,0.0516829
|
||||
237.397,0.0176428,0.00124444,0.920721,217,248.894,0.021071
|
||||
297.923,0.0140163,0.00124444,0.900508,238,312.436,0.0434852
|
||||
260.603,0.012484,0.00124444,0.912971,309,273.599,0.0320857
|
||||
273.926,0.0168922,0.00124444,0.908522,249,286.954,0.0443297
|
||||
298.718,0.0174071,0.00124444,0.900243,209,313.315,0.0236055
|
||||
276.871,0.0167161,0.00124444,0.907539,268,290.546,0.0248795
|
||||
302.089,0.0162225,0.00124444,0.899117,262,317.095,0.015801
|
||||
276.551,0.0114517,0.00124444,0.907645,178,289.397,0.045748
|
||||
280.724,0.0182241,0.00124444,0.906252,184,293.925,0.0576927
|
||||
261.057,0.0172636,0.00124444,0.912819,152,273.573,0.0649999
|
||||
236.373,0.0156888,0.00124444,0.921063,257,248.052,0.0402787
|
||||
270.794,0.0143144,0.00124444,0.909568,234,282.84,0.0429796
|
||||
272.7,0.0156175,0.00124444,0.908931,170,286.257,0.0583084
|
||||
270.983,0.012891,0.00124444,0.909505,247,284.314,0.0303283
|
||||
306.135,0.0148554,0.00124444,0.897766,175,321.302,0.0456628
|
||||
248.478,0.016144,0.00124444,0.91702,227,260.894,0.0294851
|
||||
265.44,0.0103717,0.00124444,0.911356,274,278.436,0.0266817
|
||||
262.233,0.0150257,0.00124444,0.912427,235,274.697,0.0387567
|
||||
256.662,0.0181041,0.00124444,0.914287,202,269.428,0.0345583
|
||||
274.338,0.0138554,0.00124444,0.908385,181,287.274,0.0490538
|
||||
268.815,0.0144361,0.00124444,0.910229,222,281.924,0.0243106
|
||||
251.425,0.0171867,0.00124444,0.916036,241,263.843,0.0501147
|
||||
284.735,0.0165221,0.00124444,0.904912,200,298.757,0.0397164
|
||||
262.717,0.0162912,0.00124444,0.912265,229,275.521,0.0401815
|
||||
256.866,0.0145304,0.00124444,0.914219,249,269.146,0.0306201
|
||||
260.708,0.0144833,0.00124444,0.912936,210,273.475,0.0343934
|
||||
261.745,0.0147709,0.00124444,0.91259,222,273.666,0.033181
|
||||
284.729,0.0160625,0.00124444,0.904914,197,298.125,0.0467389
|
||||
291.835,0.0146895,0.00124444,0.902541,175,305.642,0.0475431
|
||||
283.297,0.0163328,0.00124444,0.905392,349,297.086,0.0203907
|
||||
303.006,0.0165804,0.00124444,0.898811,158,317.845,0.0610993
|
||||
261.705,0.0175394,0.00124444,0.912603,323,274.586,0.0235008
|
||||
316.6,0.0135961,0.00124444,0.894271,229,332.413,0.03878
|
||||
287.234,0.0143036,0.00124444,0.904078,203,301.147,0.0376103
|
||||
337.364,0.0140911,0.00124444,0.887337,150,354.08,0.0600292
|
||||
253.797,0.0164939,0.00124444,0.915244,247,266.461,0.0321915
|
||||
|
@ -0,0 +1,108 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.8453053176e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6409518325e+05 -9.52e-05 7.07e-06 -3.129336e+03 2.663203e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 164095
|
||||
rel. change during last iteration : -9.51616e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.9199
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1674.44
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -3129.34 +/- 2384 (76.19%)
|
||||
b = 266.32 +/- 37.57 (14.11%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.8067339365e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
5 1.5824530732e+05 -3.08e-07 9.56e-06 1.317597e+03 -9.801188e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 158245
|
||||
rel. change during last iteration : -3.0782e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.1839
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1614.75
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 1317.6 +/- 566.5 (43%)
|
||||
bb = -980.119 +/- 514.9 (52.53%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 8.1385601354e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
5 2.1970491829e+01 -1.63e-02 9.56e-06 -3.136035e+03 3.136342e+03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 21.9705
|
||||
rel. change during last iteration : -1.62953e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.473486
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.224189
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3136.04 +/- 6.675 (0.2129%)
|
||||
bbb = 3136.34 +/- 6.067 (0.1934%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,78 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.8453053176e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6709987683e+05 -2.80e+06 7.07e-02 2.525913e+00 2.161942e+02
|
||||
2 1.6667175206e+05 -2.57e+02 7.07e-03 -1.715968e+02 2.199973e+02
|
||||
3 1.6414949666e+05 -1.54e+03 7.07e-04 -2.699906e+03 2.595947e+02
|
||||
4 1.6409518341e+05 -3.31e+01 7.07e-05 -3.128608e+03 2.663089e+02
|
||||
5 1.6409518325e+05 -9.52e-05 7.07e-06 -3.129336e+03 2.663203e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 164095
|
||||
rel. change during last iteration : -9.51616e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.9199
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1674.44
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -3129.34 +/- 2384 (76.19%)
|
||||
b = 266.32 +/- 37.57 (14.11%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.8067339365e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6567425140e+05 -2.80e+06 9.56e-02 1.113320e+02 1.150902e+02
|
||||
2 1.6256126289e+05 -1.91e+03 9.56e-03 3.913863e+02 -1.383578e+02
|
||||
3 1.5824974701e+05 -2.72e+03 9.56e-04 1.287890e+03 -9.531211e+02
|
||||
4 1.5824530732e+05 -2.81e+00 9.56e-05 1.317587e+03 -9.801098e+02
|
||||
5 1.5824530732e+05 -3.08e-07 9.56e-06 1.317597e+03 -9.801188e+02
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 158245
|
||||
rel. change during last iteration : -3.0782e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.1839
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1614.75
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 1317.6 +/- 566.5 (43%)
|
||||
bb = -980.119 +/- 514.9 (52.53%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 8.1385601354e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
1 5.3975388072e+04 -1.50e+07 9.56e-02 1.319509e+02 1.649079e+02
|
||||
2 3.1741255515e+04 -7.00e+04 9.56e-03 -6.251153e+02 8.543613e+02
|
||||
3 5.4599157975e+01 -5.80e+07 9.56e-04 -3.055503e+03 3.063152e+03
|
||||
4 2.1970495409e+01 -1.49e+05 9.56e-05 -3.136008e+03 3.136318e+03
|
||||
5 2.1970491829e+01 -1.63e-02 9.56e-06 -3.136035e+03 3.136342e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 21.9705
|
||||
rel. change during last iteration : -1.62953e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.473486
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.224189
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3136.04 +/- 6.675 (0.2129%)
|
||||
bbb = 3136.34 +/- 6.067 (0.1934%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_4x7_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_4x7_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) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_4x7_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_4x7_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) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-evolution1D_4x7_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
2131
dokumentation/evolution1d/20171005-evolution1D_4x7_100Times.log
Normal file
2131
dokumentation/evolution1d/20171005-evolution1D_4x7_100Times.log
Normal file
File diff suppressed because it is too large
Load Diff
Binary file not shown.
|
After Width: | Height: | Size: 5.8 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.5 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.2 KiB |
101
dokumentation/evolution1d/20171005-evolution1D_7x4_100Times.csv
Normal file
101
dokumentation/evolution1d/20171005-evolution1D_7x4_100Times.csv
Normal file
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
201.297,0.0153997,0.00124444,0.932777,211,211.096,0.0324233
|
||||
222.924,0.0138755,0.00124444,0.925554,215,233.828,0.0321173
|
||||
195.586,0.0165785,0.00124444,0.934684,233,205.276,0.0262902
|
||||
249.343,0.0170463,0.00124444,0.916732,140,261.016,0.0297848
|
||||
196.161,0.0169011,0.00124444,0.934492,167,205.753,0.0340118
|
||||
232.94,0.0151993,0.00124444,0.922209,203,244.494,0.0327092
|
||||
225.704,0.0187794,0.00124444,0.924626,200,236.857,0.0285021
|
||||
232.061,0.0176159,0.00124444,0.922503,141,243.624,0.0341091
|
||||
216.478,0.0193808,0.00124444,0.927707,205,227.071,0.0319641
|
||||
218.526,0.0168255,0.00124444,0.927023,132,228.254,0.0371698
|
||||
209.13,0.016102,0.00124444,0.930161,195,219.293,0.0254967
|
||||
224.21,0.0097335,0.00124444,0.925125,260,235.159,0.0286628
|
||||
229.764,0.0131346,0.00124444,0.92327,222,240.691,0.0421742
|
||||
221.783,0.0154066,0.00124444,0.925935,234,232.853,0.0190093
|
||||
232.166,0.0181673,0.00124444,0.922468,153,243.665,0.0176615
|
||||
231.214,0.016363,0.00124444,0.922786,194,242.766,0.0286637
|
||||
232.146,0.0160201,0.00124444,0.922474,151,243.618,0.0318045
|
||||
226.741,0.0160234,0.00124444,0.92428,185,238.051,0.029258
|
||||
214.091,0.0162548,0.00124444,0.928504,191,224.685,0.0293766
|
||||
197.18,0.0183974,0.00124444,0.934152,200,206.919,0.0280479
|
||||
254.147,0.0141509,0.00124444,0.915127,180,266.62,0.0401662
|
||||
218.998,0.0166688,0.00124444,0.926865,172,229.771,0.0316734
|
||||
229.888,0.015569,0.00124444,0.923229,172,241.243,0.0383093
|
||||
218.144,0.0175268,0.00124444,0.92715,166,228.75,0.0277466
|
||||
235.229,0.0139292,0.00124444,0.921445,122,246.415,0.0328971
|
||||
234.47,0.0170242,0.00124444,0.921698,214,245.936,0.0311265
|
||||
223.637,0.0147445,0.00124444,0.925316,275,234.603,0.0173437
|
||||
220.006,0.01659,0.00124444,0.926529,223,230.971,0.0221785
|
||||
234.897,0.0153778,0.00124444,0.921556,219,246.319,0.0330376
|
||||
224.176,0.017539,0.00124444,0.925136,182,235.173,0.0316049
|
||||
238.295,0.0167376,0.00124444,0.920421,310,250.199,0.0212912
|
||||
230.074,0.0145246,0.00124444,0.923166,180,240.854,0.0325642
|
||||
222.461,0.0172363,0.00124444,0.925709,226,233.456,0.0200254
|
||||
206.544,0.0113106,0.00124444,0.931024,218,216.659,0.0203372
|
||||
228.658,0.0143528,0.00124444,0.923639,227,240.033,0.0230481
|
||||
232.581,0.0168069,0.00124444,0.922329,208,244.108,0.0315845
|
||||
207.444,0.014401,0.00124444,0.930724,156,216.874,0.0423996
|
||||
230.579,0.0161407,0.00124444,0.922998,222,242.058,0.0155056
|
||||
211.161,0.0154943,0.00124444,0.929483,200,221.484,0.0288013
|
||||
212.025,0.0162238,0.00124444,0.929194,131,222.485,0.0315666
|
||||
228.383,0.0165074,0.00124444,0.923731,306,239.78,0.0203423
|
||||
221.656,0.0168344,0.00124444,0.925978,247,232.709,0.0234514
|
||||
220.116,0.0175812,0.00124444,0.926492,191,230.785,0.0250425
|
||||
219.146,0.0195251,0.00124444,0.926816,168,229.968,0.0433433
|
||||
224.008,0.0160092,0.00124444,0.925192,221,235.149,0.0209819
|
||||
222.645,0.0136684,0.00124444,0.925647,221,233.462,0.028072
|
||||
229.597,0.0142117,0.00124444,0.923326,194,241.027,0.0407908
|
||||
218.437,0.015863,0.00124444,0.927053,246,229.139,0.0264266
|
||||
200.414,0.0159252,0.00124444,0.933072,218,210.309,0.0307566
|
||||
212.507,0.0156027,0.00124444,0.929033,204,222.927,0.0213849
|
||||
225.552,0.014999,0.00124444,0.924676,255,236.762,0.0204812
|
||||
233.174,0.0171498,0.00124444,0.922131,202,244.312,0.0424202
|
||||
214.771,0.0198871,0.00124444,0.928277,257,225.283,0.0205486
|
||||
217.951,0.0156941,0.00124444,0.927215,172,228.831,0.0309327
|
||||
223.826,0.0132289,0.00124444,0.925253,178,234.735,0.0339935
|
||||
211.781,0.0154319,0.00124444,0.929275,249,222.154,0.0359608
|
||||
205.208,0.0165743,0.00124444,0.931471,241,215.144,0.0313585
|
||||
236.053,0.0147814,0.00124444,0.92117,182,247.533,0.0489446
|
||||
231.21,0.0149828,0.00124444,0.922787,202,242.563,0.0415887
|
||||
220.924,0.0177705,0.00124444,0.926222,156,231.706,0.0301208
|
||||
234.408,0.0159816,0.00124444,0.921719,145,245.743,0.0317348
|
||||
222.408,0.0143535,0.00124444,0.925727,242,233.422,0.0246441
|
||||
210.758,0.0174935,0.00124444,0.929617,255,221.213,0.0207961
|
||||
212.849,0.0159688,0.00124444,0.928919,220,223.48,0.0267984
|
||||
223.157,0.0195002,0.00124444,0.925477,188,234.243,0.0198455
|
||||
235.148,0.01368,0.00124444,0.921472,267,246.759,0.0250402
|
||||
214.6,0.0139443,0.00124444,0.928334,204,225.232,0.0280205
|
||||
222.275,0.0167278,0.00124444,0.925771,162,233.179,0.0281601
|
||||
245.067,0.014789,0.00124444,0.918159,173,256.94,0.03829
|
||||
226.652,0.0148565,0.00124444,0.924309,164,237.977,0.0260072
|
||||
227.432,0.0164053,0.00124444,0.924049,186,238.547,0.0399367
|
||||
243.016,0.0161022,0.00124444,0.918844,144,254.967,0.0548178
|
||||
212.727,0.0144341,0.00124444,0.92896,186,223.3,0.0462393
|
||||
232.305,0.0180672,0.00124444,0.922421,147,243.823,0.0243951
|
||||
228.648,0.0124633,0.00124444,0.923643,234,240.056,0.0235827
|
||||
210.07,0.0209562,0.00124444,0.929847,134,220.234,0.03316
|
||||
231.44,0.0145091,0.00124444,0.92271,199,242.633,0.0341166
|
||||
233.47,0.0162595,0.00124444,0.922032,151,244.981,0.0352567
|
||||
233.24,0.0173451,0.00124444,0.922109,196,244.803,0.0189091
|
||||
230.457,0.0150522,0.00124444,0.923039,218,241.898,0.0377671
|
||||
212.095,0.0146085,0.00124444,0.929171,196,222.32,0.0308945
|
||||
220.969,0.0171665,0.00124444,0.926207,243,232.013,0.0183292
|
||||
218.034,0.0154712,0.00124444,0.927187,232,228.661,0.0208262
|
||||
229.902,0.01589,0.00124444,0.923224,226,241.097,0.032418
|
||||
215.14,0.015205,0.00124444,0.928154,226,225.772,0.0165023
|
||||
232.714,0.0171707,0.00124444,0.922285,163,243.746,0.0267255
|
||||
199.436,0.0181063,0.00124444,0.933398,365,209.245,0.0217639
|
||||
225.485,0.0172431,0.00124444,0.924699,196,235.881,0.032626
|
||||
230.548,0.0145494,0.00124444,0.923008,224,241.881,0.0357782
|
||||
220.164,0.014643,0.00124444,0.926476,221,231.035,0.021201
|
||||
210.607,0.0149307,0.00124444,0.929668,197,220.946,0.027384
|
||||
202.034,0.0154935,0.00124444,0.932531,219,212.015,0.0227197
|
||||
223.702,0.0156465,0.00124444,0.925294,220,234.886,0.0202163
|
||||
223.274,0.0153501,0.00124444,0.925437,237,234.38,0.0210493
|
||||
239.317,0.0139175,0.00124444,0.92008,167,250.999,0.0352055
|
||||
219.42,0.0157887,0.00124444,0.926724,194,229.239,0.0410685
|
||||
211.502,0.0159828,0.00124444,0.929368,183,222.041,0.021811
|
||||
198.88,0.0172708,0.00124444,0.933584,139,208.038,0.0256466
|
||||
207.561,0.0138982,0.00124444,0.930685,199,217.716,0.016863
|
||||
210.296,0.0164974,0.00124444,0.929771,195,220.769,0.0256633
|
||||
|
@ -0,0 +1,108 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.2059624024e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6157855782e+05 -1.28e-04 7.07e-06 -3.703035e+03 2.609538e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 161579
|
||||
rel. change during last iteration : -1.2809e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.6049
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1648.76
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -3703.04 +/- 2343 (63.28%)
|
||||
b = 260.954 +/- 37.51 (14.38%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.1694597860e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6088124752e+05 -2.98e-05 9.64e-06 1.779074e+03 -1.445031e+03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 160881
|
||||
rel. change during last iteration : -2.98408e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.5172
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1641.65
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 1779.07 +/- 1039 (58.39%)
|
||||
bb = -1445.03 +/- 961.8 (66.56%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 5.3588910602e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
6 5.4694656646e+00 -5.96e-09 9.64e-07 -3.141932e+03 3.141867e+03
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.46947
|
||||
rel. change during last iteration : -5.95966e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.236243
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0558109
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3141.93 +/- 6.057 (0.1928%)
|
||||
bbb = 3141.87 +/- 5.608 (0.1785%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,79 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.2059624024e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6580035617e+05 -2.44e+06 7.07e-02 1.958416e+00 2.009886e+02
|
||||
2 1.6524678185e+05 -3.35e+02 7.07e-03 -2.078184e+02 2.053272e+02
|
||||
3 1.6165337078e+05 -2.22e+03 7.07e-04 -3.203881e+03 2.530098e+02
|
||||
4 1.6157855802e+05 -4.63e+01 7.07e-05 -3.702205e+03 2.609406e+02
|
||||
5 1.6157855782e+05 -1.28e-04 7.07e-06 -3.703035e+03 2.609538e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 161579
|
||||
rel. change during last iteration : -1.2809e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.6049
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1648.76
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -3703.04 +/- 2343 (63.28%)
|
||||
b = 260.954 +/- 37.51 (14.38%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.1694597860e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6525762522e+05 -2.42e+06 9.64e-02 1.017401e+02 1.068470e+02
|
||||
2 1.6449315575e+05 -4.65e+02 9.64e-03 2.381672e+02 -1.846147e+01
|
||||
3 1.6091869157e+05 -2.22e+03 9.64e-04 1.622183e+03 -1.299781e+03
|
||||
4 1.6088124757e+05 -2.33e+01 9.64e-05 1.778896e+03 -1.444867e+03
|
||||
5 1.6088124752e+05 -2.98e-05 9.64e-06 1.779074e+03 -1.445031e+03
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 160881
|
||||
rel. change during last iteration : -2.98408e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.5172
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1641.65
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 1779.07 +/- 1039 (58.39%)
|
||||
bb = -1445.03 +/- 961.8 (66.56%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 5.3588910602e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6257651642e+04 -3.29e+07 9.64e-02 1.127845e+02 1.275042e+02
|
||||
2 1.3617851160e+04 -1.94e+04 9.64e-03 -1.505284e+02 3.724288e+02
|
||||
3 1.4658675724e+02 -9.19e+06 9.64e-04 -2.837355e+03 2.859890e+03
|
||||
4 5.4696465957e+00 -2.58e+06 9.64e-05 -3.141588e+03 3.141548e+03
|
||||
5 5.4694656646e+00 -3.31e+00 9.64e-06 -3.141932e+03 3.141867e+03
|
||||
6 5.4694656646e+00 -5.96e-09 9.64e-07 -3.141932e+03 3.141867e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.46947
|
||||
rel. change during last iteration : -5.95966e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.236243
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0558109
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3141.93 +/- 6.057 (0.1928%)
|
||||
bbb = 3141.87 +/- 5.608 (0.1785%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_7x4_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x4_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) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_7x4_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x4_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) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-evolution1D_7x4_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
2131
dokumentation/evolution1d/20171005-evolution1D_7x4_100Times.log
Normal file
2131
dokumentation/evolution1d/20171005-evolution1D_7x4_100Times.log
Normal file
File diff suppressed because it is too large
Load Diff
Binary file not shown.
|
After Width: | Height: | Size: 6.0 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.5 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.1 KiB |
101
dokumentation/evolution1d/20171005-evolution1D_7x7_100Times.csv
Normal file
101
dokumentation/evolution1d/20171005-evolution1D_7x7_100Times.csv
Normal file
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
120.527,0.0305651,0.00217778,0.95975,182,126.241,0.0274436
|
||||
105.717,0.0304078,0.00217778,0.964696,282,110.962,0.0158715
|
||||
119.901,0.0296548,0.00217778,0.959959,224,125.853,0.0221449
|
||||
133.689,0.0301734,0.00217778,0.955354,233,140.195,0.0223482
|
||||
120.918,0.0297028,0.00217778,0.959619,175,126.647,0.0197707
|
||||
147.295,0.0283644,0.00217778,0.950811,243,154.539,0.0261081
|
||||
102.228,0.0319967,0.00217778,0.965861,251,107.206,0.0145694
|
||||
122.622,0.0252732,0.00217778,0.95905,232,128.558,0.0183895
|
||||
130.819,0.0325323,0.00217778,0.956313,169,136.77,0.0248296
|
||||
139.062,0.029404,0.00217778,0.95356,239,145.941,0.0198192
|
||||
163.931,0.0284774,0.00217778,0.945255,197,171.996,0.0243894
|
||||
113.252,0.0321719,0.00217778,0.962179,241,118.437,0.0246194
|
||||
137.3,0.0283919,0.00217778,0.954149,176,143.556,0.0201642
|
||||
115.119,0.0300041,0.00217778,0.961556,295,120.873,0.0178014
|
||||
100.904,0.0288716,0.00217778,0.966303,208,105.887,0.0200813
|
||||
147.487,0.024799,0.00217778,0.950747,189,154.67,0.0243077
|
||||
147.404,0.0277859,0.00217778,0.950774,143,154.182,0.0287594
|
||||
110.849,0.0278082,0.00217778,0.962982,247,116.314,0.0130491
|
||||
108.144,0.0317319,0.00217778,0.963885,221,113.496,0.0213925
|
||||
152.471,0.0309984,0.00217778,0.949082,193,159.92,0.0216455
|
||||
151.301,0.0316553,0.00217778,0.949473,183,158.727,0.026995
|
||||
103.761,0.0245259,0.00217778,0.965349,208,108.387,0.0261726
|
||||
141.47,0.0299984,0.00217778,0.952756,215,148.334,0.0212445
|
||||
107.693,0.0288702,0.00217778,0.964036,237,112.767,0.0184018
|
||||
132.834,0.0291123,0.00217778,0.95564,243,139.428,0.0137168
|
||||
118.598,0.0294951,0.00217778,0.960394,224,124.479,0.0151507
|
||||
101.31,0.0290843,0.00217778,0.966168,277,106.309,0.0130174
|
||||
133.211,0.0291807,0.00217778,0.955514,223,139.721,0.0234585
|
||||
127.816,0.031699,0.00217778,0.957316,228,133.951,0.0207455
|
||||
128.875,0.0282553,0.00217778,0.956962,205,135.062,0.0212527
|
||||
128.065,0.0277151,0.00217778,0.957233,232,133.884,0.0207377
|
||||
114.407,0.0308509,0.00217778,0.961794,248,120.051,0.0177078
|
||||
96.6405,0.0323881,0.00217778,0.967727,257,101.318,0.0205648
|
||||
128.856,0.0302615,0.00217778,0.956968,196,135.279,0.0185934
|
||||
104.861,0.0307769,0.00217778,0.964981,300,110.051,0.0107628
|
||||
130.225,0.0302749,0.00217778,0.956511,206,136.437,0.0178083
|
||||
128.374,0.025948,0.00217778,0.957129,198,134.697,0.0240022
|
||||
108.68,0.0299555,0.00217778,0.963706,261,113.78,0.0165322
|
||||
116.83,0.0285706,0.00217778,0.960984,214,122.484,0.0175649
|
||||
109.654,0.0290142,0.00217778,0.963381,201,114.487,0.0242023
|
||||
121.709,0.0293128,0.00217778,0.959355,181,127.55,0.0230015
|
||||
119.756,0.0299435,0.00217778,0.960007,266,125.629,0.0222042
|
||||
154.595,0.0296071,0.00217778,0.948373,161,162.041,0.031111
|
||||
148.94,0.0288307,0.00217778,0.950261,189,156.364,0.0201626
|
||||
108.541,0.0309115,0.00217778,0.963753,215,113.788,0.0194676
|
||||
131.712,0.0305304,0.00217778,0.956015,170,138.26,0.0233339
|
||||
104.985,0.0269759,0.00217778,0.96494,223,109.996,0.0200455
|
||||
156.935,0.0277759,0.00217778,0.947591,197,164.442,0.0274963
|
||||
101.562,0.0270836,0.00217778,0.966083,228,105.711,0.0285827
|
||||
149.172,0.0293507,0.00217778,0.950184,266,156.553,0.0137586
|
||||
110.786,0.0301022,0.00217778,0.963003,225,116.304,0.0160115
|
||||
108.126,0.0296889,0.00217778,0.963891,272,113.339,0.0139973
|
||||
113.396,0.0280885,0.00217778,0.962131,184,118.637,0.0206842
|
||||
157.303,0.0286129,0.00217778,0.947469,205,164.957,0.0204323
|
||||
92.5603,0.0310149,0.00217778,0.969089,288,97.1774,0.0118406
|
||||
131.31,0.0312147,0.00217778,0.956149,201,137.814,0.0216513
|
||||
151.662,0.0264346,0.00217778,0.949352,241,158.652,0.0206991
|
||||
122.986,0.0296999,0.00217778,0.958929,239,128.639,0.0250375
|
||||
138.21,0.0276365,0.00217778,0.953845,210,144.853,0.0221076
|
||||
130.258,0.0288724,0.00217778,0.9565,203,136.728,0.0240955
|
||||
95.4606,0.0305017,0.00217778,0.968121,264,100.103,0.0134085
|
||||
123.79,0.0302927,0.00217778,0.95866,290,129.972,0.0120363
|
||||
128.023,0.0269328,0.00217778,0.957247,263,134.171,0.0176036
|
||||
97.4169,0.0294049,0.00217778,0.967467,283,102.086,0.0154436
|
||||
131.497,0.032637,0.00217778,0.956086,194,137.823,0.0230214
|
||||
114.486,0.0296235,0.00217778,0.961767,209,120.165,0.0182154
|
||||
115.802,0.030273,0.00217778,0.961328,249,121.511,0.0168117
|
||||
104.888,0.0298335,0.00217778,0.964972,266,110.067,0.0157024
|
||||
107.529,0.0299312,0.00217778,0.96409,214,112.614,0.0242658
|
||||
100.39,0.0284705,0.00217778,0.966475,228,105.271,0.0152932
|
||||
134.206,0.0300452,0.00217778,0.955182,190,140.821,0.0262343
|
||||
118.423,0.0285713,0.00217778,0.960452,230,124.285,0.0195539
|
||||
150.763,0.0269517,0.00217778,0.949652,188,158.103,0.0213998
|
||||
134.048,0.0302692,0.00217778,0.955234,169,140.515,0.0308499
|
||||
96.9072,0.029681,0.00217778,0.967638,245,101.64,0.0165011
|
||||
123.811,0.0258042,0.00217778,0.958653,254,129.887,0.0140323
|
||||
159.564,0.0304946,0.00217778,0.946713,205,167.194,0.0194008
|
||||
105.757,0.0290973,0.00217778,0.964682,238,110.881,0.0179311
|
||||
139.738,0.0289451,0.00217778,0.953334,194,146.669,0.0262391
|
||||
112.768,0.0276706,0.00217778,0.962341,195,118.035,0.0156339
|
||||
143.501,0.0254884,0.00217778,0.952078,256,150.583,0.0127485
|
||||
136.72,0.0262001,0.00217778,0.954342,244,143.211,0.0193324
|
||||
109.952,0.0287195,0.00217778,0.963281,223,114.785,0.0241593
|
||||
139.559,0.029377,0.00217778,0.953394,187,146.421,0.0183773
|
||||
124.8,0.028991,0.00217778,0.958323,220,130.875,0.0179003
|
||||
102.291,0.0285261,0.00217778,0.96584,278,107.373,0.0140422
|
||||
144.967,0.0281308,0.00217778,0.951588,234,152.164,0.0189975
|
||||
123.808,0.031638,0.00217778,0.958654,185,129.282,0.0314699
|
||||
93.612,0.0275759,0.00217778,0.968738,271,98.1416,0.0124221
|
||||
123.829,0.0279283,0.00217778,0.958647,199,129.997,0.0222236
|
||||
111.654,0.0290171,0.00217778,0.962713,183,117,0.0200822
|
||||
105.848,0.0278707,0.00217778,0.964652,235,111.092,0.0159004
|
||||
108.727,0.0240196,0.00217778,0.96369,330,114.087,0.0151336
|
||||
102.465,0.0285859,0.00217778,0.965782,267,107.558,0.0137917
|
||||
137.886,0.0315396,0.00217778,0.953953,162,144.45,0.0198371
|
||||
112.847,0.0258472,0.00217778,0.962315,233,118.484,0.0194957
|
||||
104.672,0.0280787,0.00217778,0.965045,270,109.701,0.017613
|
||||
121.264,0.0247246,0.00217778,0.959504,181,126.593,0.0240936
|
||||
161.034,0.0240912,0.00217778,0.946223,165,168.971,0.0262645
|
||||
137.026,0.0283714,0.00217778,0.95424,262,143.838,0.02069
|
||||
|
@ -0,0 +1,108 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 5.1103239746e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.3279798348e+05 -2.35e-06 7.07e-06 -5.771314e+02 2.408587e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 132798
|
||||
rel. change during last iteration : -2.35102e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 36.8114
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1355.08
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -577.131 +/- 1945 (337%)
|
||||
b = 240.859 +/- 56.49 (23.46%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.998 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 5.0689010815e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
5 9.8040471485e+04 -1.51e-05 9.80e-06 3.134345e+03 -2.780953e+03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 98040.5
|
||||
rel. change during last iteration : -1.51467e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 31.6293
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1000.41
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 3134.35 +/- 530.8 (16.94%)
|
||||
bb = -2780.95 +/- 509 (18.3%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 1.6606716013e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
5 3.7498507724e+00 -4.46e-01 9.80e-06 -3.142464e+03 3.142323e+03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3.74985
|
||||
rel. change during last iteration : -4.45921e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.195611
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0382638
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3142.46 +/- 3.283 (0.1045%)
|
||||
bbb = 3142.32 +/- 3.148 (0.1002%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,78 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 5.1103239746e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3304344126e+05 -3.74e+06 7.07e-02 7.011364e+00 2.228167e+02
|
||||
2 1.3290446272e+05 -1.05e+02 7.07e-03 -3.195295e+01 2.250561e+02
|
||||
3 1.3279958538e+05 -7.90e+01 7.07e-04 -5.102627e+02 2.389204e+02
|
||||
4 1.3279798349e+05 -1.21e+00 7.07e-05 -5.770380e+02 2.408559e+02
|
||||
5 1.3279798348e+05 -2.35e-06 7.07e-06 -5.771314e+02 2.408587e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 132798
|
||||
rel. change during last iteration : -2.35102e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 36.8114
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1355.08
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
a = -577.131 +/- 1945 (337%)
|
||||
b = 240.859 +/- 56.49 (23.46%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
a 1.000
|
||||
b -0.998 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 5.0689010815e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3046686978e+05 -3.79e+06 9.80e-02 1.172773e+02 1.106372e+02
|
||||
2 1.2074716009e+05 -8.05e+03 9.80e-03 6.053195e+02 -3.561808e+02
|
||||
3 9.8095704395e+04 -2.31e+04 9.80e-04 3.009614e+03 -2.661363e+03
|
||||
4 9.8040471500e+04 -5.63e+01 9.80e-05 3.134281e+03 -2.780891e+03
|
||||
5 9.8040471485e+04 -1.51e-05 9.80e-06 3.134345e+03 -2.780953e+03
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 98040.5
|
||||
rel. change during last iteration : -1.51467e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 31.6293
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1000.41
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aa = 3134.35 +/- 530.8 (16.94%)
|
||||
bb = -2780.95 +/- 509 (18.3%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 1.6606716013e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
1 3.6419319985e+04 -4.46e+06 9.80e-02 5.817813e+01 7.298767e+01
|
||||
2 2.5572102437e+04 -4.24e+04 9.80e-03 -4.588023e+02 5.692906e+02
|
||||
3 6.5943618679e+01 -3.87e+07 9.80e-04 -3.010106e+03 3.015422e+03
|
||||
4 3.7498674938e+00 -1.66e+06 9.80e-05 -3.142395e+03 3.142258e+03
|
||||
5 3.7498507724e+00 -4.46e-01 9.80e-06 -3.142464e+03 3.142323e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3.74985
|
||||
rel. change during last iteration : -4.45921e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.195611
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0382638
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaa = -3142.46 +/- 3.283 (0.1045%)
|
||||
bbb = 3142.32 +/- 3.148 (0.1002%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_7x7_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x7_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) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set output "20171005-evolution1D_7x7_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x7_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) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-evolution1D_7x7_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
2172
dokumentation/evolution1d/20171005-evolution1D_7x7_100Times.log
Normal file
2172
dokumentation/evolution1d/20171005-evolution1D_7x7_100Times.log
Normal file
File diff suppressed because it is too large
Load Diff
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|
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|
After Width: | Height: | Size: 5.8 KiB |
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|
After Width: | Height: | Size: 5.5 KiB |
@ -13,19 +13,49 @@ 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"
|
||||
plot \
|
||||
"$2" every ::1 using 2:5 title "$2", \
|
||||
"$3" every ::1 using 2:5 title "$3", \
|
||||
"$4" every ::1 using 2:5 title "$4", \
|
||||
"$5" every ::1 using 2:5 title "$5", \
|
||||
"$6" every ::1 using 2:5 title "$6", \
|
||||
f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "$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"
|
||||
plot \
|
||||
"$2" every ::1 using 4:5 title "$2", \
|
||||
"$3" every ::1 using 4:5 title "$3", \
|
||||
"$4" every ::1 using 4:5 title "$4", \
|
||||
"$5" every ::1 using 4:5 title "$5", \
|
||||
"$6" every ::1 using 4:5 title "$6", \
|
||||
g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "$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"
|
||||
plot \
|
||||
"$2" every ::1 using 4:6 title "$2", \
|
||||
"$3" every ::1 using 4:6 title "$3", \
|
||||
"$4" every ::1 using 4:6 title "$4", \
|
||||
"$5" every ::1 using 4:6 title "$5", \
|
||||
"$6" every ::1 using 4:6 title "$6", \
|
||||
h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "$data" every ::1 using 3:6 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set output "${png}_variability-vs-evo-error.png"
|
||||
plot \
|
||||
"$2" every ::1 using 3:6 title "$2", \
|
||||
"$3" every ::1 using 3:6 title "$3", \
|
||||
"$4" every ::1 using 3:6 title "$4", \
|
||||
"$5" every ::1 using 3:6 title "$5", \
|
||||
"$6" every ::1 using 3:6 title "$6", \
|
||||
i(x) title "lin. fit" lc rgb "black"
|
||||
EOD
|
||||
) > "${png}.gnuplot.script"
|
||||
gnuplot "${png}.gnuplot.script" 2> "${png}.gnuplot.log"
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 12 KiB |
Loading…
Reference in New Issue
Block a user