savepoint
26
dokumentation/evolution1d/R_mean_med_sigma.sh
Executable file
@ -0,0 +1,26 @@
|
||||
#!/bin/bash
|
||||
|
||||
# regularity,variability,improvement,"Evolution error",steps
|
||||
# 6.57581e-05,0.00592209,0.622392,113.016,2368
|
||||
|
||||
if [[ -f "$2" ]]; then
|
||||
|
||||
R -q --slave --vanilla <<EOF
|
||||
print("================ Analyzing $2")
|
||||
#library(Hmisc)
|
||||
DF=as.matrix(read.csv("$2",header=TRUE))
|
||||
print("Mean:")
|
||||
mean(DF[,$1])
|
||||
print("Median:")
|
||||
median(DF[,$1])
|
||||
print("Sigma:")
|
||||
sd(DF[,$1])
|
||||
print("Range:")
|
||||
range(DF[,$1])
|
||||
EOF
|
||||
|
||||
else
|
||||
|
||||
echo "Usage: $0 <column> <Filename.csv>"
|
||||
fi
|
||||
|
@ -1,4 +1,4 @@
|
||||
"5x5","7x4","4x7","7x7","10x10"
|
||||
"5x5","4x7","7x4","7x7","10x10"
|
||||
218.554,280.917,211.096,126.241,15.0742
|
||||
215.888,315.729,233.828,110.962,19.0281
|
||||
274.375,264.639,205.276,125.853,11.8948
|
||||
|
|
Before Width: | Height: | Size: 5.1 KiB After Width: | Height: | Size: 5.1 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:40 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.992 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:40 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:40 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4
|
||||
@ -136,3 +136,49 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.39893e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707119
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 2447.69
|
||||
rel. change during last iteration : -3.53005e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 4.99764
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 24.9765
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.69981 +/- 9.656e+16 (5.681e+18%)
|
||||
bbbb = 119.169 +/- 5.718e+14 (4.798e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
|
@ -270,3 +270,69 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.39893e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707119
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 2482.26 delta(WSSR)/WSSR : -562.573
|
||||
delta(WSSR) : -1.39645e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707119
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.69632
|
||||
bbbb = 118.581
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 2447.69 delta(WSSR)/WSSR : -0.0141217
|
||||
delta(WSSR) : -34.5656 limit for stopping : 1e-05
|
||||
lambda : 0.00707119
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.69981
|
||||
bbbb = 119.169
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 2447.69 delta(WSSR)/WSSR : -3.53005e-11
|
||||
delta(WSSR) : -8.64047e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707119
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.69981
|
||||
bbbb = 119.169
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 2447.69
|
||||
rel. change during last iteration : -3.53005e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 4.99764
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 24.9765
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.69981 +/- 9.656e+16 (5.681e+18%)
|
||||
bbbb = 119.169 +/- 5.718e+14 (4.798e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.00592209:0.00592209], adjusting to [0.00586287:0.00598131]
|
||||
|
@ -2,19 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20170926_3dFit_4x4x4_100times_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20170926_3dFit_4x4x4_100times_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20170926_3dFit_4x4x4_100times_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20170926_3dFit_4x4x4_100times_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.4 KiB |
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.2 KiB |
Before Width: | Height: | Size: 5.6 KiB After Width: | Height: | Size: 5.9 KiB |
After Width: | Height: | Size: 5.0 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:42 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.970 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:42 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:12:42 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4
|
||||
@ -136,3 +136,49 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 582860 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707154
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4883.49
|
||||
rel. change during last iteration : -7.32216e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.05915
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 49.8315
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.87923 +/- 6.796e+16 (3.616e+18%)
|
||||
bbbb = 77.0146 +/- 7.861e+14 (1.021e+15%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
|
@ -226,3 +226,69 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 582860 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707154
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 4897.8 delta(WSSR)/WSSR : -118.005
|
||||
delta(WSSR) : -577962 limit for stopping : 1e-05
|
||||
lambda : 0.0707154
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.87486
|
||||
bbbb = 76.6364
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 4883.49 delta(WSSR)/WSSR : -0.00292946
|
||||
delta(WSSR) : -14.306 limit for stopping : 1e-05
|
||||
lambda : 0.00707154
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.87923
|
||||
bbbb = 77.0146
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 4883.49 delta(WSSR)/WSSR : -7.32216e-12
|
||||
delta(WSSR) : -3.57577e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707154
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.87923
|
||||
bbbb = 77.0146
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4883.49
|
||||
rel. change during last iteration : -7.32216e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.05915
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 49.8315
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.87923 +/- 6.796e+16 (3.616e+18%)
|
||||
bbbb = 77.0146 +/- 7.861e+14 (1.021e+15%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.0115666:0.0115666], adjusting to [0.0114509:0.0116823]
|
||||
|
@ -2,19 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20170926_3dFit_5x5x5_100times_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20170926_3dFit_5x5x5_100times_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20170926_3dFit_5x5x5_100times_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20170926_3dFit_5x5x5_100times_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.3 KiB |
Before Width: | Height: | Size: 5.3 KiB After Width: | Height: | Size: 5.6 KiB |
Before Width: | Height: | Size: 5.0 KiB After Width: | Height: | Size: 5.4 KiB |
After Width: | Height: | Size: 4.9 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:52 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.986 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:52 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:52 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4
|
||||
@ -136,3 +136,49 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.04253e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707126
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4497.91
|
||||
rel. change during last iteration : -1.42792e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.77474
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 45.8971
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.75417 +/- 1.135e+17 (6.469e+18%)
|
||||
bbbb = 102.878 +/- 8.4e+14 (8.165e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
|
@ -270,3 +270,69 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.04253e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707126
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 4523.61 delta(WSSR)/WSSR : -229.464
|
||||
delta(WSSR) : -1.03801e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.75041
|
||||
bbbb = 102.371
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 4497.91 delta(WSSR)/WSSR : -0.00571226
|
||||
delta(WSSR) : -25.6932 limit for stopping : 1e-05
|
||||
lambda : 0.00707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.75417
|
||||
bbbb = 102.878
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 4497.91 delta(WSSR)/WSSR : -1.42792e-11
|
||||
delta(WSSR) : -6.42267e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.75417
|
||||
bbbb = 102.878
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4497.91
|
||||
rel. change during last iteration : -1.42792e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.77474
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 45.8971
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.75417 +/- 1.135e+17 (6.469e+18%)
|
||||
bbbb = 102.878 +/- 8.4e+14 (8.165e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.00740261:0.00740261], adjusting to [0.00732858:0.00747664]
|
||||
|
@ -2,19 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171005_3dFit_4x4x5_100times_regularity-vs-steps.png"
|
||||
plot "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171005_3dFit_4x4x5_100times_improvement-vs-steps.png"
|
||||
plot "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171005_3dFit_4x4x5_100times_improvement-vs-evo-error.png"
|
||||
plot "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171005_3dFit_4x4x5_100times_variability-vs-evo-error.png"
|
||||
plot "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.4 KiB |
Before Width: | Height: | Size: 5.6 KiB After Width: | Height: | Size: 5.9 KiB |
Before Width: | Height: | Size: 5.3 KiB After Width: | Height: | Size: 5.7 KiB |
After Width: | Height: | Size: 5.1 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:58 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.972 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:58 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 11:48:58 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4
|
||||
@ -136,3 +136,49 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 716707 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707145
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 5014.73
|
||||
rel. change during last iteration : -8.78131e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.15337
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 51.1707
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.87421 +/- 6.575e+16 (3.508e+18%)
|
||||
bbbb = 85.3528 +/- 6.814e+14 (7.983e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
|
@ -259,3 +259,69 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 716707 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707145
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 5032.35 delta(WSSR)/WSSR : -141.42
|
||||
delta(WSSR) : -711675 limit for stopping : 1e-05
|
||||
lambda : 0.0707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.86986
|
||||
bbbb = 84.9331
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 5014.73 delta(WSSR)/WSSR : -0.00351279
|
||||
delta(WSSR) : -17.6157 limit for stopping : 1e-05
|
||||
lambda : 0.00707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.87421
|
||||
bbbb = 85.3528
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 5014.73 delta(WSSR)/WSSR : -8.78131e-12
|
||||
delta(WSSR) : -4.40359e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.87421
|
||||
bbbb = 85.3528
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 5014.73
|
||||
rel. change during last iteration : -8.78131e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.15337
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 51.1707
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.87421 +/- 6.575e+16 (3.508e+18%)
|
||||
bbbb = 85.3528 +/- 6.814e+14 (7.983e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.0103637:0.0103637], adjusting to [0.0102601:0.0104673]
|
||||
|
@ -2,19 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171005_3dFit_7x4x4_100times_regularity-vs-steps.png"
|
||||
plot "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171005_3dFit_7x4x4_100times_improvement-vs-steps.png"
|
||||
plot "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171005_3dFit_7x4x4_100times_improvement-vs-evo-error.png"
|
||||
plot "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171005_3dFit_7x4x4_100times_variability-vs-evo-error.png"
|
||||
plot "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.3 KiB |
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.8 KiB |
Before Width: | Height: | Size: 5.4 KiB After Width: | Height: | Size: 5.8 KiB |
After Width: | Height: | Size: 4.9 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 12:11:35 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171007_3dFit_all.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.945 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 12:11:35 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171007_3dFit_all.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -0.997 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 12:11:35 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171007_3dFit_all.csv" every ::1 using 3:4
|
||||
@ -139,7 +139,7 @@ bbb -0.997 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sat Oct 7 12:11:35 2017
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171007_3dFit_all.csv" every ::1 using 2:4
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171007_3dFit_all.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171007_3dFit_all_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "20170926_3dFit_4x4x4_100times.csv", "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 title "20170926_3dFit_5x5x5_100times.csv", "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5 title "20171005_3dFit_4x4x5_100times.csv", "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5 title "20171005_3dFit_7x4x4_100times.csv", f(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171007_3dFit_all.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171007_3dFit_all.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171007_3dFit_all_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "20170926_3dFit_4x4x4_100times.csv", "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 title "20170926_3dFit_5x5x5_100times.csv", "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5 title "20171005_3dFit_4x4x5_100times.csv", "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5 title "20171005_3dFit_7x4x4_100times.csv", g(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171007_3dFit_all.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171007_3dFit_all.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171007_3dFit_all_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "20170926_3dFit_4x4x4_100times.csv", "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 title "20170926_3dFit_5x5x5_100times.csv", "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4 title "20171005_3dFit_4x4x5_100times.csv", "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4 title "20171005_3dFit_7x4x4_100times.csv", h(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171007_3dFit_all.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171007_3dFit_all.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171007_3dFit_all_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "20170926_3dFit_4x4x4_100times.csv", "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4 title "20170926_3dFit_5x5x5_100times.csv", "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4 title "20171005_3dFit_4x4x5_100times.csv", "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4 title "20171005_3dFit_7x4x4_100times.csv", i(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171007_3dFit_all.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 11 KiB After Width: | Height: | Size: 9.2 KiB |
Before Width: | Height: | Size: 10 KiB After Width: | Height: | Size: 8.4 KiB |
Before Width: | Height: | Size: 10 KiB After Width: | Height: | Size: 8.3 KiB |
Before Width: | Height: | Size: 7.1 KiB After Width: | Height: | Size: 6.1 KiB |
@ -0,0 +1,184 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_4x4x7_100times.csv" every ::1 using 1:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.17059e+08 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707107
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 7 iterations the fit converged.
|
||||
final sum of squares of residuals : 1.87465e+07
|
||||
rel. change during last iteration : -3.45833e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 437.368
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 191291
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -1.04278e+07 +/- 2.15e+06 (20.62%)
|
||||
b = 2804.5 +/- 174.4 (6.22%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.968 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.16784e+08 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.860178
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 2.30326e+07
|
||||
rel. change during last iteration : -2.46431e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 484.795
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 235026
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 7203.94 +/- 7544 (104.7%)
|
||||
bb = -3004.38 +/- 5226 (173.9%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 770224 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.860178
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3831.77
|
||||
rel. change during last iteration : -2.81552e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.25298
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 39.0997
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -284.393 +/- 97.31 (34.22%)
|
||||
bbb = 286.203 +/- 67.4 (23.55%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_4x4x7_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 782212 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707145
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4165.76
|
||||
rel. change during last iteration : -1.15562e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51979
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.5077
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.91405 +/- 1.245e+17 (6.505e+18%)
|
||||
bbbb = 89.1974 +/- 1.29e+15 (1.447e+15%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
@ -0,0 +1,338 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.17059e+08 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707107
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 2.32566e+07 delta(WSSR)/WSSR : -16.9329
|
||||
delta(WSSR) : -3.93802e+08 limit for stopping : 1e-05
|
||||
lambda : 0.0707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.291954
|
||||
b = 1975.6
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 2.32468e+07 delta(WSSR)/WSSR : -0.000422514
|
||||
delta(WSSR) : -9822.08 limit for stopping : 1e-05
|
||||
lambda : 0.00707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -86.0202
|
||||
b = 1985.48
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 2.32393e+07 delta(WSSR)/WSSR : -0.000320176
|
||||
delta(WSSR) : -7440.69 limit for stopping : 1e-05
|
||||
lambda : 0.000707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -8710.18
|
||||
b = 1986.15
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 2.25787e+07 delta(WSSR)/WSSR : -0.0292598
|
||||
delta(WSSR) : -660649 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -805199
|
||||
b = 2048.71
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 1.87911e+07 delta(WSSR)/WSSR : -0.201566
|
||||
delta(WSSR) : -3.78764e+06 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -9.39061e+06
|
||||
b = 2723.04
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 1.87465e+07 delta(WSSR)/WSSR : -0.00237512
|
||||
delta(WSSR) : -44525.2 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.04266e+07
|
||||
b = 2804.4
|
||||
/
|
||||
|
||||
Iteration 7
|
||||
WSSR : 1.87465e+07 delta(WSSR)/WSSR : -3.45833e-09
|
||||
delta(WSSR) : -0.0648317 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-08
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.04278e+07
|
||||
b = 2804.5
|
||||
|
||||
After 7 iterations the fit converged.
|
||||
final sum of squares of residuals : 1.87465e+07
|
||||
rel. change during last iteration : -3.45833e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 437.368
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 191291
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -1.04278e+07 +/- 2.15e+06 (20.62%)
|
||||
b = 2804.5 +/- 174.4 (6.22%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.968 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.16784e+08 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.860178
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 2.32036e+07 delta(WSSR)/WSSR : -16.962
|
||||
delta(WSSR) : -3.9358e+08 limit for stopping : 1e-05
|
||||
lambda : 0.0860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 948.6
|
||||
bb = 1318.67
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 2.31176e+07 delta(WSSR)/WSSR : -0.00372074
|
||||
delta(WSSR) : -86014.6 limit for stopping : 1e-05
|
||||
lambda : 0.00860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 2665.07
|
||||
bb = 139.584
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 2.30326e+07 delta(WSSR)/WSSR : -0.00369116
|
||||
delta(WSSR) : -85017 limit for stopping : 1e-05
|
||||
lambda : 0.000860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 7086.74
|
||||
bb = -2923.19
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 2.30326e+07 delta(WSSR)/WSSR : -2.46431e-06
|
||||
delta(WSSR) : -56.7593 limit for stopping : 1e-05
|
||||
lambda : 8.60178e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 7203.94
|
||||
bb = -3004.38
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 2.30326e+07
|
||||
rel. change during last iteration : -2.46431e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 484.795
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 235026
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 7203.94 +/- 7544 (104.7%)
|
||||
bb = -3004.38 +/- 5226 (173.9%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 770224 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.860178
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 4287.26 delta(WSSR)/WSSR : -178.654
|
||||
delta(WSSR) : -765937 limit for stopping : 1e-05
|
||||
lambda : 0.0860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 40.5365
|
||||
bbb = 60.6977
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 4061.95 delta(WSSR)/WSSR : -0.0554706
|
||||
delta(WSSR) : -225.318 limit for stopping : 1e-05
|
||||
lambda : 0.00860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -48.3014
|
||||
bbb = 122.669
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 3831.93 delta(WSSR)/WSSR : -0.0600269
|
||||
delta(WSSR) : -230.019 limit for stopping : 1e-05
|
||||
lambda : 0.000860178
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -278.294
|
||||
bbb = 281.979
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 3831.77 delta(WSSR)/WSSR : -4.00769e-05
|
||||
delta(WSSR) : -0.153566 limit for stopping : 1e-05
|
||||
lambda : 8.60178e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -284.391
|
||||
bbb = 286.202
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 3831.77 delta(WSSR)/WSSR : -2.81552e-12
|
||||
delta(WSSR) : -1.07884e-08 limit for stopping : 1e-05
|
||||
lambda : 8.60178e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -284.393
|
||||
bbb = 286.203
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3831.77
|
||||
rel. change during last iteration : -2.81552e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.25298
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 39.0997
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -284.393 +/- 97.31 (34.22%)
|
||||
bbb = 286.203 +/- 67.4 (23.55%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 782212 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707145
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 4185.02 delta(WSSR)/WSSR : -185.908
|
||||
delta(WSSR) : -778027 limit for stopping : 1e-05
|
||||
lambda : 0.0707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.9095
|
||||
bbbb = 88.7586
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 4165.76 delta(WSSR)/WSSR : -0.00462295
|
||||
delta(WSSR) : -19.2581 limit for stopping : 1e-05
|
||||
lambda : 0.00707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.91405
|
||||
bbbb = 89.1974
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 4165.76 delta(WSSR)/WSSR : -1.15562e-11
|
||||
delta(WSSR) : -4.81405e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707145
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.91405
|
||||
bbbb = 89.1974
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 4165.76
|
||||
rel. change during last iteration : -1.15562e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51979
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.5077
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.91405 +/- 1.245e+17 (6.505e+18%)
|
||||
bbbb = 89.1974 +/- 1.29e+15 (1.447e+15%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.0103637:0.0103637], adjusting to [0.0102601:0.0104673]
|
@ -0,0 +1,26 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171013_3dFit_4x4x7_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171013_3dFit_4x4x7_100times_regularity-vs-steps.png"
|
||||
plot "20171013_3dFit_4x4x7_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171013_3dFit_4x4x7_100times_improvement-vs-steps.png"
|
||||
plot "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171013_3dFit_4x4x7_100times_improvement-vs-evo-error.png"
|
||||
plot "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171013_3dFit_4x4x7_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171013_3dFit_4x4x7_100times_variability-vs-evo-error.png"
|
||||
plot "20171013_3dFit_4x4x7_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
After Width: | Height: | Size: 6.1 KiB |
After Width: | Height: | Size: 5.7 KiB |
After Width: | Height: | Size: 6.2 KiB |
After Width: | Height: | Size: 4.8 KiB |
@ -0,0 +1,184 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_5x4x4_100times.csv" every ::1 using 1:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.41899e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707107
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 7 iterations the fit converged.
|
||||
final sum of squares of residuals : 8.72636e+06
|
||||
rel. change during last iteration : -9.16821e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 298.403
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 89044.5
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -1.15579e+06 +/- 1.468e+06 (127%)
|
||||
b = 1020.47 +/- 194.2 (19.03%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.988 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:07 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.40737e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.850561
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 7.83163e+06
|
||||
rel. change during last iteration : -4.61976e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 282.692
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 79914.6
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 10438.1 +/- 3028 (29%)
|
||||
bb = -6107.9 +/- 2024 (33.14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 997151 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.850561
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 4984.54
|
||||
rel. change during last iteration : -5.99309e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.1318
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 50.8626
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -241.373 +/- 76.38 (31.64%)
|
||||
bbb = 262.595 +/- 51.06 (19.44%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171013_3dFit_5x4x4_100times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.01036e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707126
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 5492.5
|
||||
rel. change during last iteration : -1.13205e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.48638
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 56.0459
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.74202 +/- 9.406e+16 (5.4e+18%)
|
||||
bbbb = 101.237 +/- 6.963e+14 (6.878e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
@ -0,0 +1,327 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.41899e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707107
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 8.78343e+06 delta(WSSR)/WSSR : -8.58509
|
||||
delta(WSSR) : -7.54065e+07 limit for stopping : 1e-05
|
||||
lambda : 0.0707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 1.01743
|
||||
b = 865.06
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 8.78156e+06 delta(WSSR)/WSSR : -0.000212651
|
||||
delta(WSSR) : -1867.41 limit for stopping : 1e-05
|
||||
lambda : 0.00707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -8.53399
|
||||
b = 869.381
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 8.78147e+06 delta(WSSR)/WSSR : -1.03771e-05
|
||||
delta(WSSR) : -91.1264 limit for stopping : 1e-05
|
||||
lambda : 0.000707107
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -962.938
|
||||
b = 869.506
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 8.77338e+06 delta(WSSR)/WSSR : -0.000922382
|
||||
delta(WSSR) : -8092.41 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -89117.8
|
||||
b = 881.03
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 8.72691e+06 delta(WSSR)/WSSR : -0.00532471
|
||||
delta(WSSR) : -46468.3 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.04065e+06
|
||||
b = 1005.42
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 8.72636e+06 delta(WSSR)/WSSR : -6.27725e-05
|
||||
delta(WSSR) : -547.775 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.15565e+06
|
||||
b = 1020.45
|
||||
/
|
||||
|
||||
Iteration 7
|
||||
WSSR : 8.72636e+06 delta(WSSR)/WSSR : -9.16821e-11
|
||||
delta(WSSR) : -0.000800051 limit for stopping : 1e-05
|
||||
lambda : 7.07107e-08
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.15579e+06
|
||||
b = 1020.47
|
||||
|
||||
After 7 iterations the fit converged.
|
||||
final sum of squares of residuals : 8.72636e+06
|
||||
rel. change during last iteration : -9.16821e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 298.403
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 89044.5
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -1.15579e+06 +/- 1.468e+06 (127%)
|
||||
b = 1020.47 +/- 194.2 (19.03%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.988 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.40737e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.850561
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 8.69722e+06 delta(WSSR)/WSSR : -8.66674
|
||||
delta(WSSR) : -7.53765e+07 limit for stopping : 1e-05
|
||||
lambda : 0.0850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 483.004
|
||||
bb = 542.6
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 8.08871e+06 delta(WSSR)/WSSR : -0.0752288
|
||||
delta(WSSR) : -608504 limit for stopping : 1e-05
|
||||
lambda : 0.00850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 5007.98
|
||||
bb = -2477.97
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 7.83167e+06 delta(WSSR)/WSSR : -0.0328215
|
||||
delta(WSSR) : -257047 limit for stopping : 1e-05
|
||||
lambda : 0.000850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 10373.7
|
||||
bb = -6064.85
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 7.83163e+06 delta(WSSR)/WSSR : -4.61976e-06
|
||||
delta(WSSR) : -36.1803 limit for stopping : 1e-05
|
||||
lambda : 8.50561e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 10438.1
|
||||
bb = -6107.9
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 7.83163e+06
|
||||
rel. change during last iteration : -4.61976e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 282.692
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 79914.6
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 10438.1 +/- 3028 (29%)
|
||||
bb = -6107.9 +/- 2024 (33.14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 997151 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.850561
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 5722.22 delta(WSSR)/WSSR : -173.259
|
||||
delta(WSSR) : -991429 limit for stopping : 1e-05
|
||||
lambda : 0.0850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 44.3933
|
||||
bbb = 71.0688
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 5196.8 delta(WSSR)/WSSR : -0.101105
|
||||
delta(WSSR) : -525.422 limit for stopping : 1e-05
|
||||
lambda : 0.00850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -85.3429
|
||||
bbb = 158.291
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 4984.57 delta(WSSR)/WSSR : -0.0425783
|
||||
delta(WSSR) : -212.235 limit for stopping : 1e-05
|
||||
lambda : 0.000850561
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -239.522
|
||||
bbb = 261.358
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 4984.54 delta(WSSR)/WSSR : -5.99309e-06
|
||||
delta(WSSR) : -0.0298728 limit for stopping : 1e-05
|
||||
lambda : 8.50561e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -241.373
|
||||
bbb = 262.595
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 4984.54
|
||||
rel. change during last iteration : -5.99309e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.1318
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 50.8626
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -241.373 +/- 76.38 (31.64%)
|
||||
bbb = 262.595 +/- 51.06 (19.44%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.01036e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707126
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 5517.37 delta(WSSR)/WSSR : -182.123
|
||||
delta(WSSR) : -1.00484e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.73833
|
||||
bbbb = 100.739
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 5492.5 delta(WSSR)/WSSR : -0.00452841
|
||||
delta(WSSR) : -24.8723 limit for stopping : 1e-05
|
||||
lambda : 0.00707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.74202
|
||||
bbbb = 101.237
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 5492.5 delta(WSSR)/WSSR : -1.13205e-11
|
||||
delta(WSSR) : -6.21776e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707126
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 1.74202
|
||||
bbbb = 101.237
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 5492.5
|
||||
rel. change during last iteration : -1.13205e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.48638
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 56.0459
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 1.74202 +/- 9.406e+16 (5.4e+18%)
|
||||
bbbb = 101.237 +/- 6.963e+14 (6.878e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.00740261:0.00740261], adjusting to [0.00732858:0.00747664]
|
@ -0,0 +1,26 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171013_3dFit_5x4x4_100times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171013_3dFit_5x4x4_100times_regularity-vs-steps.png"
|
||||
plot "20171013_3dFit_5x4x4_100times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171013_3dFit_5x4x4_100times_improvement-vs-steps.png"
|
||||
plot "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171013_3dFit_5x4x4_100times_improvement-vs-evo-error.png"
|
||||
plot "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171013_3dFit_5x4x4_100times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171013_3dFit_5x4x4_100times_variability-vs-evo-error.png"
|
||||
plot "20171013_3dFit_5x4x4_100times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
After Width: | Height: | Size: 6.4 KiB |
After Width: | Height: | Size: 6.0 KiB |
After Width: | Height: | Size: 5.7 KiB |
After Width: | Height: | Size: 5.2 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Mon Oct 23 12:06:26 2017
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171021-evolution3D_6x6_100Times.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Mon Oct 23 12:06:26 2017
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Mon Oct 23 12:06:26 2017
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:4
|
||||
@ -136,3 +136,49 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171021-evolution3D_6x6_100Times.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 110
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 423824 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707248
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 3576.05
|
||||
rel. change during last iteration : -4.97138e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 5.75426
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 33.1115
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 2.2349 +/- 2.531e+16 (1.133e+18%)
|
||||
bbbb = 62.785 +/- 5.059e+14 (8.058e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
|
@ -226,3 +226,69 @@ correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 423824 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707248
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 3584.65 delta(WSSR)/WSSR : -117.233
|
||||
delta(WSSR) : -420239 limit for stopping : 1e-05
|
||||
lambda : 0.0707248
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 2.22931
|
||||
bbbb = 62.5054
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 3576.05 delta(WSSR)/WSSR : -0.00240612
|
||||
delta(WSSR) : -8.6044 limit for stopping : 1e-05
|
||||
lambda : 0.00707248
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 2.2349
|
||||
bbbb = 62.785
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 3576.05 delta(WSSR)/WSSR : -4.97138e-12
|
||||
delta(WSSR) : -1.77779e-08 limit for stopping : 1e-05
|
||||
lambda : 0.000707248
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 2.2349
|
||||
bbbb = 62.785
|
||||
|
||||
After 3 iterations the fit converged.
|
||||
final sum of squares of residuals : 3576.05
|
||||
rel. change during last iteration : -4.97138e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 5.75426
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 33.1115
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = 2.2349 +/- 2.531e+16 (1.133e+18%)
|
||||
bbbb = 62.785 +/- 5.059e+14 (8.058e+14%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -1.000 1.000
|
||||
Warning: empty x range [0.019987:0.019987], adjusting to [0.0197871:0.0201869]
|
||||
|
@ -2,19 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171021-evolution3D_6x6_100Times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171021-evolution3D_6x6_100Times_regularity-vs-steps.png"
|
||||
plot "20171021-evolution3D_6x6_100Times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171021-evolution3D_6x6_100Times_improvement-vs-steps.png"
|
||||
plot "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171021-evolution3D_6x6_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171021-evolution3D_6x6_100Times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171021-evolution3D_6x6_100Times_variability-vs-evo-error.png"
|
||||
plot "20171021-evolution3D_6x6_100Times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 5.3 KiB After Width: | Height: | Size: 5.7 KiB |
Before Width: | Height: | Size: 5.4 KiB After Width: | Height: | Size: 5.7 KiB |
Before Width: | Height: | Size: 5.1 KiB After Width: | Height: | Size: 5.4 KiB |
After Width: | Height: | Size: 5.0 KiB |
@ -1,184 +1,10 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 16:01:21 2017
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 1:5
|
||||
format = x:z
|
||||
#datapoints = 6
|
||||
residuals are weighted equally (unit weight)
|
||||
BREAK: No data to fit
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.03463 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.800174
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.760112
|
||||
rel. change during last iteration : -7.81424e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.435922
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190028
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -0.500504 +/- 0.4333 (86.58%)
|
||||
b = 0.50226 +/- 0.2295 (45.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.632 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 16:01:21 2017
|
||||
|
||||
|
||||
FIT: data read from "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:5
|
||||
format = x:z
|
||||
#datapoints = 6
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.042 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.80039
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.760537
|
||||
rel. change during last iteration : -7.73688e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436044
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190134
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = -0.499395 +/- 0.4329 (86.68%)
|
||||
bb = 0.502057 +/- 0.2296 (45.72%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -0.631 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 16:01:21 2017
|
||||
|
||||
|
||||
FIT: data read from "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:4
|
||||
format = x:z
|
||||
#datapoints = 6
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.04152 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.80039
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.763537
|
||||
rel. change during last iteration : -7.73556e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436903
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190884
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -0.501106 +/- 0.4337 (86.55%)
|
||||
bbb = 0.503355 +/- 0.23 (45.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -0.631 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 16:01:21 2017
|
||||
|
||||
|
||||
FIT: data read from "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 6
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.04263 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.800411
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.763697
|
||||
rel. change during last iteration : -7.7194e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436949
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190924
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = -0.50098 +/- 0.4338 (86.59%)
|
||||
bbbb = 0.50338 +/- 0.2301 (45.71%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.632 1.000
|
||||
|
@ -1,304 +1,3 @@
|
||||
No data to fit
|
||||
"20171025-evolution3D_10x10x10_noFit.gnuplot.script", line 3:
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.03463 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.800174
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 1.04136 delta(WSSR)/WSSR : -7.67579
|
||||
delta(WSSR) : -7.99327 limit for stopping : 1e-05
|
||||
lambda : 0.0800174
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.00294917
|
||||
b = 0.398082
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 0.760123 delta(WSSR)/WSSR : -0.36999
|
||||
delta(WSSR) : -0.281238 limit for stopping : 1e-05
|
||||
lambda : 0.00800174
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.497122
|
||||
b = 0.501019
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 0.760112 delta(WSSR)/WSSR : -1.53218e-05
|
||||
delta(WSSR) : -1.16463e-05 limit for stopping : 1e-05
|
||||
lambda : 0.000800174
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.500504
|
||||
b = 0.50226
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 0.760112 delta(WSSR)/WSSR : -7.81424e-14
|
||||
delta(WSSR) : -5.93969e-14 limit for stopping : 1e-05
|
||||
lambda : 8.00174e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.500504
|
||||
b = 0.50226
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.760112
|
||||
rel. change during last iteration : -7.81424e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.435922
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190028
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -0.500504 +/- 0.4333 (86.58%)
|
||||
b = 0.50226 +/- 0.2295 (45.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.632 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.042 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.80039
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 1.04131 delta(WSSR)/WSSR : -7.68331
|
||||
delta(WSSR) : -8.0007 limit for stopping : 1e-05
|
||||
lambda : 0.080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.00287365
|
||||
bb = 0.398135
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 0.760548 delta(WSSR)/WSSR : -0.369155
|
||||
delta(WSSR) : -0.28076 limit for stopping : 1e-05
|
||||
lambda : 0.0080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = -0.496029
|
||||
bb = 0.50082
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 0.760537 delta(WSSR)/WSSR : -1.52182e-05
|
||||
delta(WSSR) : -1.1574e-05 limit for stopping : 1e-05
|
||||
lambda : 0.00080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = -0.499395
|
||||
bb = 0.502057
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 0.760537 delta(WSSR)/WSSR : -7.73688e-14
|
||||
delta(WSSR) : -5.88418e-14 limit for stopping : 1e-05
|
||||
lambda : 8.0039e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = -0.499395
|
||||
bb = 0.502057
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.760537
|
||||
rel. change during last iteration : -7.73688e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436044
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190134
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = -0.499395 +/- 0.4329 (86.68%)
|
||||
bb = 0.502057 +/- 0.2296 (45.72%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -0.631 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.04152 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.80039
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 1.04503 delta(WSSR)/WSSR : -7.65191
|
||||
delta(WSSR) : -7.99648 limit for stopping : 1e-05
|
||||
lambda : 0.080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 0.00194603
|
||||
bbb = 0.399071
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 0.763548 delta(WSSR)/WSSR : -0.36865
|
||||
delta(WSSR) : -0.281482 limit for stopping : 1e-05
|
||||
lambda : 0.0080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.497734
|
||||
bbb = 0.502116
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 0.763537 delta(WSSR)/WSSR : -1.52098e-05
|
||||
delta(WSSR) : -1.16133e-05 limit for stopping : 1e-05
|
||||
lambda : 0.00080039
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.501106
|
||||
bbb = 0.503355
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 0.763537 delta(WSSR)/WSSR : -7.73556e-14
|
||||
delta(WSSR) : -5.90639e-14 limit for stopping : 1e-05
|
||||
lambda : 8.0039e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.501106
|
||||
bbb = 0.503355
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.763537
|
||||
rel. change during last iteration : -7.73556e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436903
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190884
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -0.501106 +/- 0.4337 (86.55%)
|
||||
bbb = 0.503355 +/- 0.23 (45.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -0.631 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.04263 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.800411
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 1.04513 delta(WSSR)/WSSR : -7.65212
|
||||
delta(WSSR) : -7.99749 limit for stopping : 1e-05
|
||||
lambda : 0.0800411
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 0.00204362
|
||||
bbbb = 0.399044
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 0.763709 delta(WSSR)/WSSR : -0.368499
|
||||
delta(WSSR) : -0.281426 limit for stopping : 1e-05
|
||||
lambda : 0.00800411
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.497607
|
||||
bbbb = 0.50214
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 0.763697 delta(WSSR)/WSSR : -1.52103e-05
|
||||
delta(WSSR) : -1.16161e-05 limit for stopping : 1e-05
|
||||
lambda : 0.000800411
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.50098
|
||||
bbbb = 0.50338
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 0.763697 delta(WSSR)/WSSR : -7.7194e-14
|
||||
delta(WSSR) : -5.89528e-14 limit for stopping : 1e-05
|
||||
lambda : 8.00411e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.50098
|
||||
bbbb = 0.50338
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 0.763697
|
||||
rel. change during last iteration : -7.7194e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 4
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.436949
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.190924
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = -0.50098 +/- 0.4338 (86.59%)
|
||||
bbbb = 0.50338 +/- 0.2301 (45.71%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.632 1.000
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_regularity-vs-steps.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_improvement-vs-steps.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_improvement-vs-evo-error.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_variability-vs-evo-error.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
||||
|
@ -0,0 +1,10 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 1:5
|
||||
format = x:z
|
||||
BREAK: No data to fit
|
||||
|
@ -0,0 +1,3 @@
|
||||
No data to fit
|
||||
"20171025-evolution3D_10x10x10_noFit_100Times.gnuplot.script", line 3:
|
||||
|
@ -0,0 +1,26 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_100Times_regularity-vs-steps.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_100Times_improvement-vs-steps.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "20171025-evolution3D_10x10x10_noFit_100Times_variability-vs-evo-error.png"
|
||||
plot "20171025-evolution3D_10x10x10_noFit_100Times.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:24 2017
|
||||
Fri Oct 27 14:11:51 2017
|
||||
|
||||
|
||||
FIT: data read from "4x4xX.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.938 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:24 2017
|
||||
Fri Oct 27 14:11:51 2017
|
||||
|
||||
|
||||
FIT: data read from "4x4xX.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -0.999 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:24 2017
|
||||
Fri Oct 27 14:11:51 2017
|
||||
|
||||
|
||||
FIT: data read from "4x4xX.csv" every ::1 using 3:4
|
||||
@ -139,7 +139,7 @@ bbb -0.999 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:24 2017
|
||||
Fri Oct 27 14:11:51 2017
|
||||
|
||||
|
||||
FIT: data read from "4x4xX.csv" every ::1 using 2:4
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "4x4xX.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "4x4xX_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "4x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 1:5 title "4x4x7" pt 2, f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "4x4xX.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "4x4xX_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "4x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:5 title "4x4x7" pt 2, g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "4x4xX.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "4x4xX_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "4x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:4 title "4x4x7" pt 2, h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "4x4xX.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "4x4xX_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "4x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 2:4 title "4x4x7" pt 2, i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 9.0 KiB After Width: | Height: | Size: 9.4 KiB |
Before Width: | Height: | Size: 8.5 KiB After Width: | Height: | Size: 8.8 KiB |
Before Width: | Height: | Size: 8.8 KiB After Width: | Height: | Size: 9.1 KiB |
Before Width: | Height: | Size: 6.0 KiB After Width: | Height: | Size: 6.4 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:30 2017
|
||||
Fri Oct 27 14:12:05 2017
|
||||
|
||||
|
||||
FIT: data read from "Xx4x4.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.934 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:30 2017
|
||||
Fri Oct 27 14:12:05 2017
|
||||
|
||||
|
||||
FIT: data read from "Xx4x4.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -0.999 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:30 2017
|
||||
Fri Oct 27 14:12:05 2017
|
||||
|
||||
|
||||
FIT: data read from "Xx4x4.csv" every ::1 using 3:4
|
||||
@ -139,7 +139,7 @@ bbb -0.999 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:30 2017
|
||||
Fri Oct 27 14:12:05 2017
|
||||
|
||||
|
||||
FIT: data read from "Xx4x4.csv" every ::1 using 2:4
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "Xx4x4.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "Xx4x4_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 1:5 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5 title "7x4x4" pt 2, f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "Xx4x4.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "Xx4x4_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:5 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5 title "7x4x4" pt 2, g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "Xx4x4.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "Xx4x4_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:4 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4 title "7x4x4" pt 2, h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "Xx4x4.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "Xx4x4_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 2:4 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4 title "7x4x4" pt 2, i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 9.0 KiB After Width: | Height: | Size: 9.4 KiB |
Before Width: | Height: | Size: 8.5 KiB After Width: | Height: | Size: 8.8 KiB |
Before Width: | Height: | Size: 8.8 KiB After Width: | Height: | Size: 9.2 KiB |
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.4 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:34 2017
|
||||
Fri Oct 27 14:12:17 2017
|
||||
|
||||
|
||||
FIT: data read from "YxYxY.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.937 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:34 2017
|
||||
Fri Oct 27 14:12:17 2017
|
||||
|
||||
|
||||
FIT: data read from "YxYxY.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:34 2017
|
||||
Fri Oct 27 14:12:17 2017
|
||||
|
||||
|
||||
FIT: data read from "YxYxY.csv" every ::1 using 3:4
|
||||
@ -139,7 +139,7 @@ bbb -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:14:34 2017
|
||||
Fri Oct 27 14:12:17 2017
|
||||
|
||||
|
||||
FIT: data read from "YxYxY.csv" every ::1 using 2:4
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "YxYxY.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "YxYxY_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "4x4x4" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 1:5 title "6x6x6" pt 2, f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "YxYxY.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "YxYxY_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "4x4x4" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:5 title "6x6x6" pt 2, g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "YxYxY.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "YxYxY_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "4x4x4" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:4 title "6x6x6" pt 2, h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "YxYxY.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "YxYxY_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "4x4x4" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 2:4 title "6x6x6" pt 2, i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 8.0 KiB After Width: | Height: | Size: 8.5 KiB |
Before Width: | Height: | Size: 7.6 KiB After Width: | Height: | Size: 7.9 KiB |
Before Width: | Height: | Size: 8.2 KiB After Width: | Height: | Size: 8.5 KiB |
Before Width: | Height: | Size: 5.9 KiB After Width: | Height: | Size: 6.4 KiB |
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:09:05 2017
|
||||
Fri Oct 27 14:12:27 2017
|
||||
|
||||
|
||||
FIT: data read from "all.csv" every ::1 using 1:5
|
||||
@ -47,7 +47,7 @@ b -0.932 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:09:05 2017
|
||||
Fri Oct 27 14:12:27 2017
|
||||
|
||||
|
||||
FIT: data read from "all.csv" every ::1 using 3:5
|
||||
@ -93,7 +93,7 @@ bb -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:09:05 2017
|
||||
Fri Oct 27 14:12:27 2017
|
||||
|
||||
|
||||
FIT: data read from "all.csv" every ::1 using 3:4
|
||||
@ -139,7 +139,7 @@ bbb -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Wed Oct 25 19:09:05 2017
|
||||
Fri Oct 27 14:12:27 2017
|
||||
|
||||
|
||||
FIT: data read from "all.csv" every ::1 using 2:4
|
||||
|
@ -2,25 +2,25 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "all.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "all_regularity-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 1:5 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 1:5 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 1:5 title "7x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 1:5 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 1:5 title "4x4x7" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 1:5 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 1:5 title "6x6x6" pt 2, f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "all.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "all_improvement-vs-steps.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:5 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:5 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:5 title "7x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:5 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:5 title "4x4x7" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:5 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:5 title "6x6x6" pt 2, g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "all.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "all_improvement-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 3:4 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 3:4 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 3:4 title "7x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 3:4 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 3:4 title "4x4x7" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 3:4 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 3:4 title "6x6x6" pt 2, h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "all.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "all_variability-vs-evo-error.png"
|
||||
plot "20170926_3dFit_4x4x4_100times.csv" every ::1 using 2:4 title "4x4x4" pt 2, "20171013_3dFit_5x4x4_100times.csv" every ::1 using 2:4 title "5x4x4" pt 2, "20171005_3dFit_7x4x4_100times.csv" every ::1 using 2:4 title "7x4x4" pt 2, "20171005_3dFit_4x4x5_100times.csv" every ::1 using 2:4 title "4x4x5" pt 2, "20171013_3dFit_4x4x7_100times.csv" every ::1 using 2:4 title "4x4x7" pt 2, "20170926_3dFit_5x5x5_100times.csv" every ::1 using 2:4 title "5x5x5" pt 2, "20171021-evolution3D_6x6_100Times.csv" every ::1 using 2:4 title "6x6x6" pt 2, i(x) title "lin. fit" lc rgb "black"
|
||||
|
Before Width: | Height: | Size: 12 KiB After Width: | Height: | Size: 12 KiB |
Before Width: | Height: | Size: 12 KiB After Width: | Height: | Size: 12 KiB |
Before Width: | Height: | Size: 14 KiB After Width: | Height: | Size: 14 KiB |
Before Width: | Height: | Size: 7.1 KiB After Width: | Height: | Size: 7.7 KiB |
@ -10,8 +10,8 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "$data" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_regularity-vs-steps.png"
|
||||
plot \
|
||||
"$2" every ::1 using 1:5 title "$3" pt 2, \
|
||||
@ -20,8 +20,8 @@ plot \
|
||||
f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "$data" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_improvement-vs-steps.png"
|
||||
plot \
|
||||
"$2" every ::1 using 3:5 title "$3" pt 2, \
|
||||
@ -30,8 +30,8 @@ plot \
|
||||
g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "$data" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "${png}_improvement-vs-evo-error.png"
|
||||
plot \
|
||||
"$2" every ::1 using 3:4 title "$3" pt 2, \
|
||||
@ -40,8 +40,8 @@ plot \
|
||||
h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "$data" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "${png}_variability-vs-evo-error.png"
|
||||
plot \
|
||||
"$2" every ::1 using 2:4 title "$3" pt 2, \
|
||||
|
@ -10,8 +10,8 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "$data" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_regularity-vs-steps.png"
|
||||
plot \
|
||||
"$2" every ::1 using 1:5 title "$3" pt 2, \
|
||||
@ -24,8 +24,8 @@ plot \
|
||||
f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "$data" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_improvement-vs-steps.png"
|
||||
plot \
|
||||
"$2" every ::1 using 3:5 title "$3" pt 2, \
|
||||
@ -38,8 +38,8 @@ plot \
|
||||
g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "$data" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "${png}_improvement-vs-evo-error.png"
|
||||
plot \
|
||||
"$2" every ::1 using 3:4 title "$3" pt 2, \
|
||||
@ -52,8 +52,8 @@ plot \
|
||||
h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "$data" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'Error given by fitness-function'
|
||||
set output "${png}_variability-vs-evo-error.png"
|
||||
plot \
|
||||
"$2" every ::1 using 2:4 title "$3" pt 2, \
|
||||
|
184
dokumentation/evolution3d/errors.gnuplot.fit.log
Normal file
@ -0,0 +1,184 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "errors.csv" every ::1 using 1:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 129069 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 84.3477
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4993.5
|
||||
rel. change during last iteration : -5.46363e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.13821
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 50.9541
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -0.0931363 +/- 0.1443 (154.9%)
|
||||
b = 96.4721 +/- 17.21 (17.84%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.999 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "errors.csv" every ::1 using 3:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 38697.6 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 71.7898
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5010.73
|
||||
rel. change during last iteration : -1.443e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.15052
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 51.1299
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 0.0270058 +/- 0.09648 (357.3%)
|
||||
bb = 82.6379 +/- 9.795 (11.85%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -0.997 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "errors.csv" every ::1 using 3:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 27023.7 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 71.7898
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4159.2
|
||||
rel. change during last iteration : -2.19108e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51466
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.4408
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -0.0345469 +/- 0.0879 (254.4%)
|
||||
bbb = 92.7152 +/- 8.924 (9.625%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -0.997 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Fri Oct 27 14:09:08 2017
|
||||
|
||||
|
||||
FIT: data read from "errors.csv" every ::1 using 2:4
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 30294.4 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 72.9129
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4165.22
|
||||
rel. change during last iteration : -6.01785e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51938
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.5023
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = -0.0109066 +/- 0.09721 (891.3%)
|
||||
bbbb = 90.3395 +/- 10.02 (11.09%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.998 1.000
|
392
dokumentation/evolution3d/errors.gnuplot.log
Normal file
@ -0,0 +1,392 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 129069 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 84.3477
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 6564.6 delta(WSSR)/WSSR : -18.6613
|
||||
delta(WSSR) : -122504 limit for stopping : 1e-05
|
||||
lambda : 8.43477
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.708029
|
||||
b = 0.999863
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 6554.01 delta(WSSR)/WSSR : -0.00161544
|
||||
delta(WSSR) : -10.5876 limit for stopping : 1e-05
|
||||
lambda : 0.843477
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.70464
|
||||
b = 1.23013
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 6005.48 delta(WSSR)/WSSR : -0.0913382
|
||||
delta(WSSR) : -548.53 limit for stopping : 1e-05
|
||||
lambda : 0.0843477
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.549306
|
||||
b = 19.7746
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 4995.1 delta(WSSR)/WSSR : -0.202276
|
||||
delta(WSSR) : -1010.39 limit for stopping : 1e-05
|
||||
lambda : 0.00843477
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.067621
|
||||
b = 93.426
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 4993.5 delta(WSSR)/WSSR : -0.000319669
|
||||
delta(WSSR) : -1.59627 limit for stopping : 1e-05
|
||||
lambda : 0.000843477
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.0931258
|
||||
b = 96.4708
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 4993.5 delta(WSSR)/WSSR : -5.46363e-11
|
||||
delta(WSSR) : -2.72827e-07 limit for stopping : 1e-05
|
||||
lambda : 8.43477e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -0.0931363
|
||||
b = 96.4721
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4993.5
|
||||
rel. change during last iteration : -5.46363e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.13821
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 50.9541
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -0.0931363 +/- 0.1443 (154.9%)
|
||||
b = 96.4721 +/- 17.21 (17.84%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.999 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 38697.6 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 71.7898
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 8562.61 delta(WSSR)/WSSR : -3.51936
|
||||
delta(WSSR) : -30134.9 limit for stopping : 1e-05
|
||||
lambda : 7.17898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.829791
|
||||
bb = 1.00677
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 8489.56 delta(WSSR)/WSSR : -0.00860526
|
||||
delta(WSSR) : -73.0548 limit for stopping : 1e-05
|
||||
lambda : 0.717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.820734
|
||||
bb = 1.84213
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 5851.66 delta(WSSR)/WSSR : -0.450794
|
||||
delta(WSSR) : -2637.9 limit for stopping : 1e-05
|
||||
lambda : 0.0717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.41725
|
||||
bb = 42.9138
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 5010.8 delta(WSSR)/WSSR : -0.167809
|
||||
delta(WSSR) : -840.86 limit for stopping : 1e-05
|
||||
lambda : 0.00717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.030744
|
||||
bb = 82.2573
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 5010.73 delta(WSSR)/WSSR : -1.54001e-05
|
||||
delta(WSSR) : -0.0771658 limit for stopping : 1e-05
|
||||
lambda : 0.000717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.0270062
|
||||
bb = 82.6378
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 5010.73 delta(WSSR)/WSSR : -1.443e-13
|
||||
delta(WSSR) : -7.23048e-10 limit for stopping : 1e-05
|
||||
lambda : 7.17898e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 0.0270058
|
||||
bb = 82.6379
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5010.73
|
||||
rel. change during last iteration : -1.443e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 7.15052
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 51.1299
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 0.0270058 +/- 0.09648 (357.3%)
|
||||
bb = 82.6379 +/- 9.795 (11.85%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -0.997 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 27023.7 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 71.7898
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 8641.55 delta(WSSR)/WSSR : -2.12719
|
||||
delta(WSSR) : -18382.2 limit for stopping : 1e-05
|
||||
lambda : 7.17898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 0.867036
|
||||
bbb = 1.00818
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 8549.83 delta(WSSR)/WSSR : -0.0107272
|
||||
delta(WSSR) : -91.716 limit for stopping : 1e-05
|
||||
lambda : 0.717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 0.857153
|
||||
bbb = 1.94665
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 5220.55 delta(WSSR)/WSSR : -0.637727
|
||||
delta(WSSR) : -3329.29 limit for stopping : 1e-05
|
||||
lambda : 0.0717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 0.403866
|
||||
bbb = 48.0879
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 4159.3 delta(WSSR)/WSSR : -0.255151
|
||||
delta(WSSR) : -1061.25 limit for stopping : 1e-05
|
||||
lambda : 0.00717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.0303472
|
||||
bbb = 92.2877
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 4159.2 delta(WSSR)/WSSR : -2.34157e-05
|
||||
delta(WSSR) : -0.0973908 limit for stopping : 1e-05
|
||||
lambda : 0.000717898
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.0345465
|
||||
bbb = 92.7151
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 4159.2 delta(WSSR)/WSSR : -2.19108e-13
|
||||
delta(WSSR) : -9.11314e-10 limit for stopping : 1e-05
|
||||
lambda : 7.17898e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -0.0345469
|
||||
bbb = 92.7152
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4159.2
|
||||
rel. change during last iteration : -2.19108e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51466
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.4408
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -0.0345469 +/- 0.0879 (254.4%)
|
||||
bbb = 92.7152 +/- 8.924 (9.625%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -0.997 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 30294.4 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 72.9129
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaaa = 1
|
||||
bbbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 7542.11 delta(WSSR)/WSSR : -3.0167
|
||||
delta(WSSR) : -22752.3 limit for stopping : 1e-05
|
||||
lambda : 7.29129
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 0.854383
|
||||
bbbb = 1.0057
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 7488.45 delta(WSSR)/WSSR : -0.00716584
|
||||
delta(WSSR) : -53.661 limit for stopping : 1e-05
|
||||
lambda : 0.729129
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 0.84683
|
||||
bbbb = 1.71093
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 5195.8 delta(WSSR)/WSSR : -0.44125
|
||||
delta(WSSR) : -2292.65 limit for stopping : 1e-05
|
||||
lambda : 0.0729129
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = 0.466748
|
||||
bbbb = 40.9842
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 4165.38 delta(WSSR)/WSSR : -0.247377
|
||||
delta(WSSR) : -1030.42 limit for stopping : 1e-05
|
||||
lambda : 0.00729129
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.00497837
|
||||
bbbb = 89.7269
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 4165.22 delta(WSSR)/WSSR : -3.81126e-05
|
||||
delta(WSSR) : -0.158748 limit for stopping : 1e-05
|
||||
lambda : 0.000729129
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.0109059
|
||||
bbbb = 90.3394
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 4165.22 delta(WSSR)/WSSR : -6.01785e-13
|
||||
delta(WSSR) : -2.50657e-09 limit for stopping : 1e-05
|
||||
lambda : 7.29129e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaaa = -0.0109066
|
||||
bbbb = 90.3395
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 4165.22
|
||||
rel. change during last iteration : -6.01785e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 6.51938
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 42.5023
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaaa = -0.0109066 +/- 0.09721 (891.3%)
|
||||
bbbb = 90.3395 +/- 10.02 (11.09%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.998 1.000
|
26
dokumentation/evolution3d/errors.gnuplot.script
Normal file
@ -0,0 +1,26 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "errors.csv" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "errors_regularity-vs-steps.png"
|
||||
plot "errors.csv" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "errors.csv" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "errors_improvement-vs-steps.png"
|
||||
plot "errors.csv" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "errors.csv" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "errors_improvement-vs-evo-error.png"
|
||||
plot "errors.csv" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "errors.csv" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "errors_variability-vs-evo-error.png"
|
||||
plot "errors.csv" every ::1 using 2:4 title "data", i(x) title "lin. fit" lc rgb "black"
|
BIN
dokumentation/evolution3d/errors_improvement-vs-evo-error.png
Normal file
After Width: | Height: | Size: 5.9 KiB |
BIN
dokumentation/evolution3d/errors_improvement-vs-steps.png
Normal file
After Width: | Height: | Size: 5.6 KiB |
BIN
dokumentation/evolution3d/errors_regularity-vs-steps.png
Normal file
After Width: | Height: | Size: 5.3 KiB |
BIN
dokumentation/evolution3d/errors_variability-vs-evo-error.png
Normal file
After Width: | Height: | Size: 5.7 KiB |
@ -10,26 +10,26 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "$data" every ::1 using 1:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_regularity-vs-steps.png"
|
||||
plot "$data" every ::1 using 1:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "$data" every ::1 using 3:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Number of iterations'
|
||||
set output "${png}_improvement-vs-steps.png"
|
||||
plot "$data" every ::1 using 3:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "$data" every ::1 using 3:4 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "${png}_improvement-vs-evo-error.png"
|
||||
plot "$data" every ::1 using 3:4 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "$data" every ::1 using 2:4 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Variability'
|
||||
set ylabel 'error given by fitness-function'
|
||||
set output "${png}_variability-vs-evo-error.png"
|
||||
plot \
|
||||
"$data" every ::1 using 2:4 title "data", \
|
||||
|
Before Width: | Height: | Size: 34 KiB After Width: | Height: | Size: 35 KiB |
Before Width: | Height: | Size: 38 KiB After Width: | Height: | Size: 39 KiB |