[Pomp-commits] r474 - pkg/tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed May 11 23:48:20 CEST 2011
Author: kingaa
Date: 2011-05-11 23:48:20 +0200 (Wed, 11 May 2011)
New Revision: 474
Modified:
pkg/tests/sir-icfit.R
pkg/tests/sir-icfit.Rout.save
Log:
- add a test for the new 'pfilter'-based initial-condition-estimation method
Modified: pkg/tests/sir-icfit.R
===================================================================
--- pkg/tests/sir-icfit.R 2011-05-11 21:39:37 UTC (rev 473)
+++ pkg/tests/sir-icfit.R 2011-05-11 21:48:20 UTC (rev 474)
@@ -5,10 +5,10 @@
pdf(file="sir-icfit.pdf")
data(euler.sir)
-po <- window(euler.sir,end=0.25)
+po <- window(euler.sir,end=0.2)
guess <- coef(po)
ics <- c("S.0","I.0","R.0")
-guess[ics[-3]] <- guess[ics[-3]]+c(0.5,-0.3)
+guess[ics[-3]] <- guess[ics[-3]]+c(0.2,-0.2)
plist <- list(
probe.marginal("reports",ref=obs(po),order=3,diff=1,transform=sqrt),
@@ -55,14 +55,8 @@
plot(range(time(po)),range(c(states(po,"cases"),x)),bty='l',xlab="time",ylab="cases",type='n')
points(time(po),states(po,"cases"))
matlines(time(po),x,lty=1,col=c("red","blue","green"))
-legend("topright",lty=1,bty='n',col=c("red","blue","green"),legend=colnames(x))
+legend("topright",lty=c(NA,1,1,1),pch=c(1,NA,NA,NA),bty='n',col=c("black","red","blue","green"),legend=c("actual",colnames(x)))
-data(euler.sir)
-po <- window(euler.sir,end=0.25)
-guess <- coef(po)
-ics <- c("S.0","I.0","R.0")
-guess[ics[-3]] <- guess[ics[-3]]+c(0.1,-0.2)
-
summary(tm.true <- traj.match(po,eval.only=TRUE))
summary(tm.guess <- traj.match(po,start=guess,eval.only=TRUE))
@@ -106,5 +100,54 @@
matlines(time(po),x,lty=1,col=c("red","blue","green"))
legend("topright",lty=c(NA,1,1,1),pch=c(1,NA,NA,NA),bty='n',col=c("black","red","blue","green"),legend=c("actual",colnames(x)))
+### now try an initial condition fitting approach based on particle filtering
+est <- ics[-1]
+np <- 10000 # number of particles to use
+pp <- array(coef(po),dim=c(length(coef(po)),np),dimnames=list(names(coef(po)),NULL))
+## generate an array of guesses
+guesses <- sobol.design(lower=guess[est]-0.5,upper=guess[est]+0.5,nseq=np)
+nd <- length(time(po))
+
+## fit the initial conditions using repeated filtering on the initial window of the data
+
+for (j in seq_len(3)) {
+ for (k in est) {
+ pp[k,] <- guesses[[k]]
+ }
+ for (k in seq_len(5)) {
+ pf <- pfilter(po,params=pp,save.params=TRUE)
+ pp <- pf at saved.params[,,nd]
+ }
+ guesses <- sobol.design(
+ lower=apply(pp[est,],1,min),
+ upper=apply(pp[est,],1,max),
+ nseq=np
+ )
+}
+
+pf.fit <- po
+coef(pf.fit,ics) <- log(apply(apply(exp(pp[ics,]),2,function(x)x/sum(x)),1,mean))
+pf.true <- pfilter(po,Np=2000)
+pf.guess <- pfilter(po,params=guess,Np=2000,max.fail=100)
+pf.fit <- pfilter(pf.fit,Np=2000)
+
+comp.table <- cbind(true=exp(coef(po,ics)),guess=exp(guess[ics]),fit=exp(coef(pf.fit,ics)))
+comp.table <- apply(comp.table,2,function(x)x/sum(x))
+comp.table <- rbind(
+ comp.table,
+ loglik=sapply(list(pf.true,pf.guess,pf.fit),logLik)
+ )
+comp.table
+
+x <- sapply(
+ list(true=pf.true,guess=pf.guess,fit=pf.fit),
+ function (x) trajectory(x,times=time(x),t0=timezero(x))["cases",1,]
+ )
+
+plot(range(time(po)),range(c(states(po,"cases"),x)),bty='l',xlab="time",ylab="cases",type='n')
+points(time(po),states(po,"cases"))
+matlines(time(po),x,lty=1,col=c("red","blue","green"))
+legend("topright",lty=c(NA,1,1,1),pch=c(1,NA,NA,NA),bty='n',col=c("black","red","blue","green"),legend=c("actual",colnames(x)))
+
dev.off()
Modified: pkg/tests/sir-icfit.Rout.save
===================================================================
--- pkg/tests/sir-icfit.Rout.save 2011-05-11 21:39:37 UTC (rev 473)
+++ pkg/tests/sir-icfit.Rout.save 2011-05-11 21:48:20 UTC (rev 474)
@@ -1,7 +1,8 @@
-R version 2.11.1 (2010-05-31)
-Copyright (C) 2010 The R Foundation for Statistical Computing
+R version 2.12.2 (2011-02-25)
+Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
+Platform: x86_64-unknown-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
@@ -25,10 +26,10 @@
> pdf(file="sir-icfit.pdf")
>
> data(euler.sir)
-> po <- window(euler.sir,end=0.25)
+> po <- window(euler.sir,end=0.2)
> guess <- coef(po)
> ics <- c("S.0","I.0","R.0")
-> guess[ics[-3]] <- guess[ics[-3]]+c(0.5,-0.3)
+> guess[ics[-3]] <- guess[ics[-3]]+c(0.2,-0.2)
>
> plist <- list(
+ probe.marginal("reports",ref=obs(po),order=3,diff=1,transform=sqrt),
@@ -50,18 +51,18 @@
$quantiles
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0.93 0.97 0.08 0.89 0.87
+ 0.99 0.99 0.01 0.74 0.53
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
- 0.81 0.78 0.23 0.36 0.35
+ 0.35 0.66 0.82 0.84 0.75
$pvals
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0.15841584 0.07920792 0.17821782 0.23762376 0.27722772
+ 0.03960396 0.03960396 0.03960396 0.53465347 0.95049505
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
- 0.39603960 0.45544554 0.47524752 0.73267327 0.71287129
+ 0.71287129 0.69306931 0.37623762 0.33663366 0.51485149
$synth.loglik
-[1] -4.012907
+[1] -4.649459
>
> summary(pm.guess <- probe(po,params=guess,probes=plist,nsim=100,seed=1066L))
@@ -71,25 +72,25 @@
beta1 beta2 beta3 beta.sd pop rho
7.09007684 7.49554194 6.39692966 -6.90775528 14.55744790 -0.51082562
S.0 I.0 R.0
--3.33198030 -7.20775528 -0.02292750
+-3.63198030 -7.10775528 -0.02292750
$nsim
[1] 100
$quantiles
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0 1 0 0 0
+ 0.97 0.98 0.03 0.00 0.00
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
- 0 0 0 1 0
+ 0.00 0.00 1.00 1.00 0.00
$pvals
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0.01980198 0.01980198 0.01980198 0.01980198 0.01980198
+ 0.07920792 0.05940594 0.07920792 0.01980198 0.01980198
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
0.01980198 0.01980198 0.01980198 0.01980198 0.01980198
$synth.loglik
-[1] -1247.474
+[1] -60.45215
>
> pm.fit <- probe.match(
@@ -105,73 +106,70 @@
+ seed=1066L
+ )
Nelder-Mead direct search function minimizer
-function value for initial parameters = 1247.473783
- Scaled convergence tolerance is 0.0124747
-Stepsize computed as 7.207755
-BUILD 3 1882.104083 1247.473783
-HI-REDUCTION 5 1273.599371 321.643854
-HI-REDUCTION 7 1247.473783 50.803164
-LO-REDUCTION 9 321.643854 30.294611
-HI-REDUCTION 11 83.364824 30.294611
-HI-REDUCTION 13 51.401288 30.294611
-HI-REDUCTION 15 50.803164 30.294611
-EXTENSION 17 45.048892 12.640485
-REFLECTION 19 30.294611 5.652463
-HI-REDUCTION 21 14.282091 5.652463
-HI-REDUCTION 23 12.640485 5.652463
-REFLECTION 25 8.321974 4.949657
-HI-REDUCTION 27 6.048930 4.949657
-LO-REDUCTION 29 5.652463 4.949657
-SHRINK 33 5.636242 4.949657
-LO-REDUCTION 35 5.525022 4.306266
-HI-REDUCTION 37 4.949657 3.956195
-SHRINK 41 6.425156 3.956195
-LO-REDUCTION 43 4.572072 3.956195
-LO-REDUCTION 45 4.137456 3.956195
-SHRINK 49 6.284694 3.956195
-LO-REDUCTION 51 4.866083 3.956195
-SHRINK 55 5.731239 3.956195
-LO-REDUCTION 57 4.807376 3.956195
-SHRINK 61 5.951373 3.956195
-LO-REDUCTION 63 5.871587 3.956195
-REFLECTION 65 5.226899 3.953204
-LO-REDUCTION 67 4.191270 3.953204
-SHRINK 71 5.553088 3.805070
-HI-REDUCTION 73 5.039328 3.805070
-LO-REDUCTION 75 4.677420 3.805070
-SHRINK 79 5.039328 3.805070
-SHRINK 83 5.553088 3.805070
-LO-REDUCTION 85 5.039328 3.805070
-SHRINK 89 5.553088 3.805070
+function value for initial parameters = 60.452154
+ Scaled convergence tolerance is 0.000604522
+Stepsize computed as 7.107755
+BUILD 3 4709.193920 60.452154
+HI-REDUCTION 5 1004.985881 60.452154
+HI-REDUCTION 7 439.543128 13.273516
+HI-REDUCTION 9 71.975176 13.273516
+HI-REDUCTION 11 60.452154 13.273516
+HI-REDUCTION 13 37.230822 13.273516
+LO-REDUCTION 15 30.402750 13.273516
+HI-REDUCTION 17 18.370468 13.187778
+REFLECTION 19 13.273516 11.040611
+HI-REDUCTION 21 13.187778 11.040611
+REFLECTION 23 11.076575 6.585215
+LO-REDUCTION 25 11.040611 4.959061
+HI-REDUCTION 27 6.585215 4.959061
+SHRINK 31 7.112652 4.959061
+LO-REDUCTION 33 6.359199 4.959061
+HI-REDUCTION 35 5.805375 4.959061
+SHRINK 39 5.894753 4.959061
+HI-REDUCTION 41 5.713127 4.959061
+HI-REDUCTION 43 5.246747 4.959061
+HI-REDUCTION 45 5.079659 4.015286
+SHRINK 49 9.296049 4.015286
+LO-REDUCTION 51 4.548796 4.015286
+SHRINK 55 7.605210 4.015286
+LO-REDUCTION 57 6.530295 4.015286
+HI-REDUCTION 59 5.965444 4.015286
+SHRINK 63 7.455235 4.015286
+LO-REDUCTION 65 5.627768 4.015286
+LO-REDUCTION 67 5.597704 4.015286
+SHRINK 71 6.184663 4.015286
+HI-REDUCTION 73 5.769219 4.015286
+SHRINK 77 7.455235 4.015286
+SHRINK 81 7.455235 4.015286
Exiting from Nelder Mead minimizer
- 91 function evaluations used
+ 83 function evaluations used
>
> summary(pm.fit)
$coef
gamma mu iota nbasis degree period beta1
3.2580965 -3.9120230 -4.6051702 3.0000000 3.0000000 1.0000000 7.0900768
beta2 beta3 beta.sd pop rho S.0 I.0
- 7.4955419 6.3969297 -6.9077553 14.5574479 -0.5108256 -3.3319803 -6.4597344
+ 7.4955419 6.3969297 -6.9077553 14.5574479 -0.5108256 -3.6319803 -6.7574763
R.0
- 0.4722391
+ 0.1485516
$nsim
[1] 100
$quantiles
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0.93 0.98 0.03 0.63 0.57
+ 0.97 0.97 0.03 0.18 0.11
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
- 0.55 0.53 0.10 0.45 0.57
+ 0.06 0.27 0.94 0.97 0.42
$pvals
marg.1 marg.2 marg.3 acf.0.reports acf.1.reports
- 0.15841584 0.05940594 0.07920792 0.75247525 0.87128713
+ 0.07920792 0.07920792 0.07920792 0.37623762 0.23762376
acf.2.reports acf.3.reports acf.4.reports acf.5.reports median
- 0.91089109 0.95049505 0.21782178 0.91089109 0.87128713
+ 0.13861386 0.55445545 0.13861386 0.07920792 0.85148515
$synth.loglik
-[1] -3.805070
+[1] -4.015286
$est
[1] "I.0" "R.0"
@@ -180,10 +178,10 @@
[1] 1
$value
-[1] 3.805070
+[1] 4.015286
$eval
-[1] 91 NA
+[1] 83 NA
$convergence
[1] 0
@@ -201,10 +199,10 @@
+ )
> comp.table
true guess fit
-S.0 0.02166667 3.523616e-02 0.0217703602
-I.0 0.00100000 7.307367e-04 0.0009538922
-R.0 0.97733333 9.640331e-01 0.9772757476
-synth.loglik -4.01290746 -1.247474e+03 -3.8050695934
+S.0 0.02166667 0.026342137 0.0222800165
+I.0 0.00100000 0.000814969 0.0009784302
+R.0 0.97733333 0.972842894 0.9767415533
+synth.loglik -4.64945875 -60.452154095 -4.0152862656
>
> x <- sapply(
+ list(true=pm.true,guess=pm.guess,fit=pm.fit),
@@ -214,14 +212,8 @@
> plot(range(time(po)),range(c(states(po,"cases"),x)),bty='l',xlab="time",ylab="cases",type='n')
> points(time(po),states(po,"cases"))
> matlines(time(po),x,lty=1,col=c("red","blue","green"))
-> legend("topright",lty=1,bty='n',col=c("red","blue","green"),legend=colnames(x))
+> legend("topright",lty=c(NA,1,1,1),pch=c(1,NA,NA,NA),bty='n',col=c("black","red","blue","green"),legend=c("actual",colnames(x)))
>
-> data(euler.sir)
-> po <- window(euler.sir,end=0.25)
-> guess <- coef(po)
-> ics <- c("S.0","I.0","R.0")
-> guess[ics[-3]] <- guess[ics[-3]]+c(0.1,-0.2)
->
> summary(tm.true <- traj.match(po,eval.only=TRUE))
$params
gamma mu iota nbasis degree period
@@ -232,7 +224,7 @@
-3.83198030 -6.90775528 -0.02292750
$loglik
-[1] -82.95589
+[1] -55.88139
$eval
[1] 1 0
@@ -251,10 +243,10 @@
beta1 beta2 beta3 beta.sd pop rho
7.09007684 7.49554194 6.39692966 -6.90775528 14.55744790 -0.51082562
S.0 I.0 R.0
--3.73198030 -7.10775528 -0.02292750
+-3.63198030 -7.10775528 -0.02292750
$loglik
-[1] -557.4875
+[1] -1673.693
$eval
[1] 1 0
@@ -275,308 +267,308 @@
+ trace=2,
+ parscale=c(0.1,0.1)
+ )
-initial evaluation: 557.4875
-iter 1 val= 202.5355 , accept= TRUE
-iter 2 val= 202.5355 , accept= FALSE
-iter 3 val= 202.5355 , accept= FALSE
-iter 4 val= 202.5355 , accept= FALSE
-iter 5 val= 202.5355 , accept= FALSE
-iter 6 val= 202.5355 , accept= FALSE
-iter 7 val= 202.5355 , accept= FALSE
-iter 8 val= 202.5355 , accept= FALSE
-iter 9 val= 202.5355 , accept= FALSE
-iter 10 val= 202.5355 , accept= FALSE
-iter 11 val= 202.5355 , accept= FALSE
-iter 12 val= 202.5355 , accept= FALSE
-iter 13 val= 202.5355 , accept= FALSE
-iter 14 val= 202.5355 , accept= FALSE
-iter 15 val= 202.5355 , accept= FALSE
-iter 16 val= 202.5355 , accept= FALSE
-iter 17 val= 202.5355 , accept= FALSE
-iter 18 val= 202.5355 , accept= FALSE
-iter 19 val= 202.5355 , accept= FALSE
-iter 20 val= 162.2567 , accept= TRUE
-iter 21 val= 162.2567 , accept= FALSE
-iter 22 val= 162.2567 , accept= FALSE
-iter 23 val= 162.2567 , accept= FALSE
-iter 24 val= 162.2567 , accept= FALSE
-iter 25 val= 162.2567 , accept= FALSE
-iter 26 val= 162.2567 , accept= FALSE
-iter 27 val= 141.8041 , accept= TRUE
-iter 28 val= 141.8041 , accept= FALSE
-iter 29 val= 130.7353 , accept= TRUE
-iter 30 val= 130.7353 , accept= FALSE
-iter 31 val= 130.7353 , accept= FALSE
-iter 32 val= 130.7353 , accept= FALSE
-iter 33 val= 130.7353 , accept= FALSE
-iter 34 val= 130.7353 , accept= FALSE
-iter 35 val= 130.7353 , accept= FALSE
-iter 36 val= 130.7353 , accept= FALSE
-iter 37 val= 130.7353 , accept= FALSE
-iter 38 val= 130.7353 , accept= FALSE
-iter 39 val= 130.7353 , accept= FALSE
-iter 40 val= 130.7353 , accept= FALSE
-iter 41 val= 130.7353 , accept= FALSE
-iter 42 val= 130.7353 , accept= FALSE
-iter 43 val= 130.7353 , accept= FALSE
-iter 44 val= 130.7353 , accept= FALSE
-iter 45 val= 130.7353 , accept= FALSE
-iter 46 val= 130.7353 , accept= FALSE
-iter 47 val= 123.9158 , accept= TRUE
-iter 48 val= 123.1513 , accept= TRUE
-iter 49 val= 123.1513 , accept= FALSE
-iter 50 val= 123.1513 , accept= FALSE
-iter 51 val= 123.1513 , accept= FALSE
-iter 52 val= 123.1513 , accept= FALSE
-iter 53 val= 123.1513 , accept= FALSE
-iter 54 val= 123.1513 , accept= FALSE
-iter 55 val= 123.1513 , accept= FALSE
-iter 56 val= 123.1513 , accept= FALSE
-iter 57 val= 123.1513 , accept= FALSE
-iter 58 val= 113.3106 , accept= TRUE
-iter 59 val= 113.3106 , accept= FALSE
-iter 60 val= 113.3106 , accept= FALSE
-iter 61 val= 113.3106 , accept= FALSE
-iter 62 val= 109.4542 , accept= TRUE
-iter 63 val= 109.4542 , accept= FALSE
-iter 64 val= 107.3697 , accept= TRUE
-iter 65 val= 107.3697 , accept= FALSE
-iter 66 val= 107.3697 , accept= FALSE
-iter 67 val= 107.3697 , accept= FALSE
-iter 68 val= 105.1804 , accept= TRUE
-iter 69 val= 105.1804 , accept= FALSE
-iter 70 val= 105.1804 , accept= FALSE
-iter 71 val= 105.1804 , accept= FALSE
-iter 72 val= 105.1804 , accept= FALSE
-iter 73 val= 105.1804 , accept= FALSE
-iter 74 val= 105.1804 , accept= FALSE
-iter 75 val= 105.1804 , accept= FALSE
-iter 76 val= 105.1804 , accept= FALSE
-iter 77 val= 105.1804 , accept= FALSE
-iter 78 val= 105.1804 , accept= FALSE
-iter 79 val= 102.0452 , accept= TRUE
-iter 80 val= 102.0452 , accept= FALSE
-iter 81 val= 102.0452 , accept= FALSE
-iter 82 val= 102.0452 , accept= FALSE
-iter 83 val= 102.0452 , accept= FALSE
-iter 84 val= 102.0452 , accept= FALSE
-iter 85 val= 96.87843 , accept= TRUE
-iter 86 val= 96.87843 , accept= FALSE
-iter 87 val= 96.87843 , accept= FALSE
-iter 88 val= 96.56392 , accept= TRUE
-iter 89 val= 96.56392 , accept= FALSE
-iter 90 val= 96.56392 , accept= FALSE
-iter 91 val= 96.56392 , accept= FALSE
-iter 92 val= 96.56392 , accept= FALSE
-iter 93 val= 96.56392 , accept= FALSE
-iter 94 val= 96.56392 , accept= FALSE
-iter 95 val= 96.56392 , accept= FALSE
-iter 96 val= 93.35854 , accept= TRUE
-iter 97 val= 93.35854 , accept= FALSE
-iter 98 val= 93.35854 , accept= FALSE
-iter 99 val= 93.35854 , accept= FALSE
-iter 100 val= 93.35854 , accept= FALSE
-iter 101 val= 93.35854 , accept= FALSE
-iter 102 val= 93.35854 , accept= FALSE
-iter 103 val= 89.3218 , accept= TRUE
-iter 104 val= 88.1193 , accept= TRUE
-iter 105 val= 88.1193 , accept= FALSE
-iter 106 val= 88.1193 , accept= FALSE
-iter 107 val= 88.1193 , accept= FALSE
-iter 108 val= 88.1193 , accept= FALSE
-iter 109 val= 88.1193 , accept= FALSE
-iter 110 val= 88.1193 , accept= FALSE
-iter 111 val= 88.1193 , accept= FALSE
-iter 112 val= 88.1193 , accept= FALSE
-iter 113 val= 88.1193 , accept= FALSE
-iter 114 val= 88.1193 , accept= FALSE
-iter 115 val= 88.1193 , accept= FALSE
-iter 116 val= 88.1193 , accept= FALSE
-iter 117 val= 88.1193 , accept= FALSE
-iter 118 val= 88.1193 , accept= FALSE
-iter 119 val= 88.1193 , accept= FALSE
-iter 120 val= 88.1193 , accept= FALSE
-iter 121 val= 88.1193 , accept= FALSE
-iter 122 val= 88.1193 , accept= FALSE
-iter 123 val= 88.1193 , accept= FALSE
-iter 124 val= 88.1193 , accept= FALSE
-iter 125 val= 88.1193 , accept= FALSE
-iter 126 val= 88.1193 , accept= FALSE
-iter 127 val= 88.1193 , accept= FALSE
-iter 128 val= 88.1193 , accept= FALSE
-iter 129 val= 86.8662 , accept= TRUE
-iter 130 val= 86.8662 , accept= FALSE
-iter 131 val= 86.8662 , accept= FALSE
-iter 132 val= 86.8662 , accept= FALSE
-iter 133 val= 86.8662 , accept= FALSE
-iter 134 val= 86.8662 , accept= FALSE
-iter 135 val= 86.8662 , accept= FALSE
-iter 136 val= 86.8662 , accept= FALSE
-iter 137 val= 86.8662 , accept= FALSE
-iter 138 val= 86.8662 , accept= FALSE
-iter 139 val= 86.8662 , accept= FALSE
-iter 140 val= 86.8662 , accept= FALSE
-iter 141 val= 81.4736 , accept= TRUE
-iter 142 val= 81.4736 , accept= FALSE
-iter 143 val= 81.4736 , accept= FALSE
-iter 144 val= 81.4736 , accept= FALSE
-iter 145 val= 81.4736 , accept= FALSE
-iter 146 val= 81.4736 , accept= FALSE
-iter 147 val= 81.4736 , accept= FALSE
-iter 148 val= 81.4736 , accept= FALSE
-iter 149 val= 81.4736 , accept= FALSE
-iter 150 val= 81.4736 , accept= FALSE
-iter 151 val= 81.4736 , accept= FALSE
-iter 152 val= 81.4736 , accept= FALSE
-iter 153 val= 81.4736 , accept= FALSE
-iter 154 val= 81.4736 , accept= FALSE
-iter 155 val= 81.4736 , accept= FALSE
-iter 156 val= 80.6933 , accept= TRUE
-iter 157 val= 80.6933 , accept= FALSE
-iter 158 val= 75.75244 , accept= TRUE
-iter 159 val= 75.75244 , accept= FALSE
-iter 160 val= 75.75244 , accept= FALSE
-iter 161 val= 71.66279 , accept= TRUE
-iter 162 val= 71.66279 , accept= FALSE
-iter 163 val= 71.66279 , accept= FALSE
-iter 164 val= 71.66279 , accept= FALSE
-iter 165 val= 71.66279 , accept= FALSE
-iter 166 val= 71.66279 , accept= FALSE
-iter 167 val= 72.1831 , accept= TRUE
-iter 168 val= 72.1831 , accept= FALSE
-iter 169 val= 72.1831 , accept= FALSE
-iter 170 val= 72.1831 , accept= FALSE
-iter 171 val= 72.1831 , accept= FALSE
-iter 172 val= 72.1831 , accept= FALSE
-iter 173 val= 72.1831 , accept= FALSE
-iter 174 val= 72.1831 , accept= FALSE
-iter 175 val= 72.1831 , accept= FALSE
-iter 176 val= 72.1831 , accept= FALSE
-iter 177 val= 72.1831 , accept= FALSE
-iter 178 val= 72.1831 , accept= FALSE
-iter 179 val= 68.91 , accept= TRUE
-iter 180 val= 68.91 , accept= FALSE
-iter 181 val= 68.91 , accept= FALSE
-iter 182 val= 68.91 , accept= FALSE
-iter 183 val= 68.91 , accept= FALSE
-iter 184 val= 68.91 , accept= FALSE
-iter 185 val= 68.91 , accept= FALSE
-iter 186 val= 68.91 , accept= FALSE
-iter 187 val= 68.91 , accept= FALSE
-iter 188 val= 68.91 , accept= FALSE
-iter 189 val= 68.91 , accept= FALSE
-iter 190 val= 68.91 , accept= FALSE
-iter 191 val= 68.91 , accept= FALSE
-iter 192 val= 68.91 , accept= FALSE
-iter 193 val= 68.91 , accept= FALSE
-iter 194 val= 68.91 , accept= FALSE
-iter 195 val= 68.91 , accept= FALSE
-iter 196 val= 68.91 , accept= FALSE
-iter 197 val= 68.91 , accept= FALSE
-iter 198 val= 68.91 , accept= FALSE
-iter 199 val= 68.91 , accept= FALSE
-iter 200 val= 68.91 , accept= FALSE
-iter 201 val= 68.91 , accept= FALSE
-iter 202 val= 69.15251 , accept= TRUE
-iter 203 val= 69.15251 , accept= FALSE
-iter 204 val= 69.15251 , accept= FALSE
-iter 205 val= 69.15251 , accept= FALSE
-iter 206 val= 69.15251 , accept= FALSE
-iter 207 val= 69.15251 , accept= FALSE
-iter 208 val= 69.15251 , accept= FALSE
-iter 209 val= 69.15251 , accept= FALSE
-iter 210 val= 69.15251 , accept= FALSE
-iter 211 val= 69.15251 , accept= FALSE
-iter 212 val= 69.15251 , accept= FALSE
-iter 213 val= 69.15251 , accept= FALSE
-iter 214 val= 69.15251 , accept= FALSE
-iter 215 val= 69.15251 , accept= FALSE
-iter 216 val= 69.15251 , accept= FALSE
-iter 217 val= 69.15251 , accept= FALSE
-iter 218 val= 69.15251 , accept= FALSE
-iter 219 val= 69.15251 , accept= FALSE
-iter 220 val= 69.15251 , accept= FALSE
-iter 221 val= 69.15251 , accept= FALSE
-iter 222 val= 69.15251 , accept= FALSE
-iter 223 val= 69.15251 , accept= FALSE
-iter 224 val= 69.15251 , accept= FALSE
-iter 225 val= 69.15251 , accept= FALSE
-iter 226 val= 69.21927 , accept= TRUE
-iter 227 val= 69.21927 , accept= FALSE
-iter 228 val= 69.21927 , accept= FALSE
-iter 229 val= 69.21927 , accept= FALSE
-iter 230 val= 69.21927 , accept= FALSE
-iter 231 val= 68.9241 , accept= TRUE
-iter 232 val= 68.9241 , accept= FALSE
-iter 233 val= 68.7367 , accept= TRUE
-iter 234 val= 68.7367 , accept= FALSE
-iter 235 val= 68.7367 , accept= FALSE
-iter 236 val= 68.7367 , accept= FALSE
-iter 237 val= 68.7367 , accept= FALSE
-iter 238 val= 68.7367 , accept= FALSE
-iter 239 val= 68.7367 , accept= FALSE
-iter 240 val= 68.7367 , accept= FALSE
-iter 241 val= 68.7367 , accept= FALSE
-iter 242 val= 68.7367 , accept= FALSE
-iter 243 val= 68.7367 , accept= FALSE
-iter 244 val= 68.7367 , accept= FALSE
-iter 245 val= 68.7367 , accept= FALSE
-iter 246 val= 68.7367 , accept= FALSE
-iter 247 val= 68.7367 , accept= FALSE
-iter 248 val= 68.7367 , accept= FALSE
-iter 249 val= 68.7367 , accept= FALSE
-iter 250 val= 68.7367 , accept= FALSE
-iter 251 val= 68.7367 , accept= FALSE
-iter 252 val= 68.7367 , accept= FALSE
-iter 253 val= 68.7367 , accept= FALSE
-iter 254 val= 68.7367 , accept= FALSE
-iter 255 val= 68.7367 , accept= FALSE
-iter 256 val= 68.7367 , accept= FALSE
-iter 257 val= 68.7367 , accept= FALSE
-iter 258 val= 68.7367 , accept= FALSE
-iter 259 val= 68.7367 , accept= FALSE
-iter 260 val= 68.7367 , accept= FALSE
-iter 261 val= 68.7367 , accept= FALSE
-iter 262 val= 68.7367 , accept= FALSE
-iter 263 val= 68.7367 , accept= FALSE
-iter 264 val= 68.7367 , accept= FALSE
-iter 265 val= 68.7367 , accept= FALSE
-iter 266 val= 68.7367 , accept= FALSE
-iter 267 val= 68.7367 , accept= FALSE
-iter 268 val= 68.7367 , accept= FALSE
-iter 269 val= 68.7367 , accept= FALSE
-iter 270 val= 68.7367 , accept= FALSE
-iter 271 val= 68.7367 , accept= FALSE
-iter 272 val= 68.7367 , accept= FALSE
-iter 273 val= 68.7367 , accept= FALSE
-iter 274 val= 68.91344 , accept= TRUE
-iter 275 val= 68.91344 , accept= FALSE
-iter 276 val= 68.91344 , accept= FALSE
-iter 277 val= 68.91344 , accept= FALSE
-iter 278 val= 68.91344 , accept= FALSE
-iter 279 val= 68.60169 , accept= TRUE
-iter 280 val= 68.60169 , accept= FALSE
-iter 281 val= 68.60169 , accept= FALSE
-iter 282 val= 68.60169 , accept= FALSE
-iter 283 val= 68.60169 , accept= FALSE
-iter 284 val= 68.60169 , accept= FALSE
-iter 285 val= 68.60169 , accept= FALSE
-iter 286 val= 68.60169 , accept= FALSE
-iter 287 val= 68.60169 , accept= FALSE
-iter 288 val= 68.60169 , accept= FALSE
-iter 289 val= 68.60169 , accept= FALSE
-iter 290 val= 68.60169 , accept= FALSE
-iter 291 val= 68.60169 , accept= FALSE
-iter 292 val= 68.60169 , accept= FALSE
-iter 293 val= 68.60169 , accept= FALSE
-iter 294 val= 68.60169 , accept= FALSE
-iter 295 val= 68.60169 , accept= FALSE
-iter 296 val= 68.60169 , accept= FALSE
-iter 297 val= 68.60169 , accept= FALSE
-iter 298 val= 68.60169 , accept= FALSE
-iter 299 val= 68.60169 , accept= FALSE
-iter 300 val= 68.60169 , accept= FALSE
-best val= 68.60169
+initial evaluation: 1673.693
+iter 1 val= 749.8673 , accept= TRUE
+iter 2 val= 749.8673 , accept= FALSE
+iter 3 val= 273.1971 , accept= TRUE
+iter 4 val= 273.1971 , accept= FALSE
+iter 5 val= 273.1971 , accept= FALSE
+iter 6 val= 273.1971 , accept= FALSE
+iter 7 val= 273.1971 , accept= FALSE
+iter 8 val= 273.1971 , accept= FALSE
+iter 9 val= 273.1971 , accept= FALSE
+iter 10 val= 273.1971 , accept= FALSE
+iter 11 val= 259.4957 , accept= TRUE
+iter 12 val= 259.4957 , accept= FALSE
+iter 13 val= 259.4957 , accept= FALSE
+iter 14 val= 259.4957 , accept= FALSE
+iter 15 val= 259.4957 , accept= FALSE
+iter 16 val= 259.4957 , accept= FALSE
+iter 17 val= 259.4957 , accept= FALSE
+iter 18 val= 259.4957 , accept= FALSE
+iter 19 val= 259.4957 , accept= FALSE
+iter 20 val= 251.5526 , accept= TRUE
+iter 21 val= 190.8693 , accept= TRUE
+iter 22 val= 185.4847 , accept= TRUE
+iter 23 val= 185.4847 , accept= FALSE
+iter 24 val= 185.4847 , accept= FALSE
+iter 25 val= 185.4847 , accept= FALSE
+iter 26 val= 185.4847 , accept= FALSE
+iter 27 val= 185.4847 , accept= FALSE
+iter 28 val= 185.4847 , accept= FALSE
+iter 29 val= 172.6744 , accept= TRUE
+iter 30 val= 172.6744 , accept= FALSE
+iter 31 val= 172.6744 , accept= FALSE
+iter 32 val= 172.6744 , accept= FALSE
+iter 33 val= 168.9433 , accept= TRUE
+iter 34 val= 168.9433 , accept= FALSE
+iter 35 val= 168.9433 , accept= FALSE
+iter 36 val= 168.9433 , accept= FALSE
+iter 37 val= 168.9433 , accept= FALSE
+iter 38 val= 168.9433 , accept= FALSE
+iter 39 val= 168.9433 , accept= FALSE
+iter 40 val= 168.9433 , accept= FALSE
+iter 41 val= 168.9433 , accept= FALSE
+iter 42 val= 168.9433 , accept= FALSE
+iter 43 val= 168.9433 , accept= FALSE
+iter 44 val= 168.9433 , accept= FALSE
+iter 45 val= 168.9433 , accept= FALSE
+iter 46 val= 168.9433 , accept= FALSE
+iter 47 val= 164.3881 , accept= TRUE
+iter 48 val= 161.7329 , accept= TRUE
+iter 49 val= 161.7329 , accept= FALSE
+iter 50 val= 161.7329 , accept= FALSE
+iter 51 val= 161.7329 , accept= FALSE
+iter 52 val= 161.7329 , accept= FALSE
+iter 53 val= 161.7329 , accept= FALSE
+iter 54 val= 161.7329 , accept= FALSE
+iter 55 val= 125.4230 , accept= TRUE
+iter 56 val= 125.4230 , accept= FALSE
+iter 57 val= 101.6445 , accept= TRUE
+iter 58 val= 101.6445 , accept= FALSE
+iter 59 val= 101.6445 , accept= FALSE
+iter 60 val= 101.6445 , accept= FALSE
+iter 61 val= 101.6445 , accept= FALSE
+iter 62 val= 98.189 , accept= TRUE
+iter 63 val= 98.189 , accept= FALSE
+iter 64 val= 96.83191 , accept= TRUE
+iter 65 val= 96.83191 , accept= FALSE
+iter 66 val= 96.83191 , accept= FALSE
+iter 67 val= 96.83191 , accept= FALSE
+iter 68 val= 95.41486 , accept= TRUE
+iter 69 val= 95.41486 , accept= FALSE
+iter 70 val= 92.515 , accept= TRUE
+iter 71 val= 92.515 , accept= FALSE
+iter 72 val= 92.515 , accept= FALSE
+iter 73 val= 92.515 , accept= FALSE
+iter 74 val= 77.25532 , accept= TRUE
+iter 75 val= 77.25532 , accept= FALSE
+iter 76 val= 77.25532 , accept= FALSE
+iter 77 val= 77.25532 , accept= FALSE
+iter 78 val= 77.25532 , accept= FALSE
+iter 79 val= 77.25532 , accept= FALSE
+iter 80 val= 77.25532 , accept= FALSE
+iter 81 val= 77.25532 , accept= FALSE
+iter 82 val= 77.25532 , accept= FALSE
+iter 83 val= 77.25532 , accept= FALSE
+iter 84 val= 77.25532 , accept= FALSE
+iter 85 val= 74.6038 , accept= TRUE
+iter 86 val= 74.6038 , accept= FALSE
+iter 87 val= 74.6038 , accept= FALSE
+iter 88 val= 73.26808 , accept= TRUE
+iter 89 val= 73.26808 , accept= FALSE
+iter 90 val= 73.26808 , accept= FALSE
+iter 91 val= 73.26808 , accept= FALSE
+iter 92 val= 73.26808 , accept= FALSE
+iter 93 val= 73.26808 , accept= FALSE
+iter 94 val= 73.26808 , accept= FALSE
+iter 95 val= 73.26808 , accept= FALSE
+iter 96 val= 71.45299 , accept= TRUE
+iter 97 val= 71.45299 , accept= FALSE
+iter 98 val= 71.45299 , accept= FALSE
+iter 99 val= 71.45299 , accept= FALSE
+iter 100 val= 71.45299 , accept= FALSE
+iter 101 val= 71.45299 , accept= FALSE
+iter 102 val= 71.45299 , accept= FALSE
+iter 103 val= 70.81809 , accept= TRUE
+iter 104 val= 69.41237 , accept= TRUE
+iter 105 val= 69.41237 , accept= FALSE
+iter 106 val= 69.41237 , accept= FALSE
+iter 107 val= 69.41237 , accept= FALSE
+iter 108 val= 69.41237 , accept= FALSE
+iter 109 val= 69.41237 , accept= FALSE
+iter 110 val= 69.41237 , accept= FALSE
+iter 111 val= 69.41237 , accept= FALSE
+iter 112 val= 69.41237 , accept= FALSE
+iter 113 val= 69.41237 , accept= FALSE
+iter 114 val= 69.41237 , accept= FALSE
+iter 115 val= 69.41237 , accept= FALSE
+iter 116 val= 69.41237 , accept= FALSE
+iter 117 val= 69.41237 , accept= FALSE
+iter 118 val= 69.41237 , accept= FALSE
+iter 119 val= 69.41237 , accept= FALSE
+iter 120 val= 69.41237 , accept= FALSE
+iter 121 val= 69.41237 , accept= FALSE
+iter 122 val= 69.41237 , accept= FALSE
+iter 123 val= 69.41237 , accept= FALSE
+iter 124 val= 69.41237 , accept= FALSE
+iter 125 val= 69.41237 , accept= FALSE
+iter 126 val= 69.41237 , accept= FALSE
+iter 127 val= 69.41237 , accept= FALSE
+iter 128 val= 69.41237 , accept= FALSE
+iter 129 val= 67.93792 , accept= TRUE
+iter 130 val= 67.93792 , accept= FALSE
+iter 131 val= 67.93792 , accept= FALSE
+iter 132 val= 67.93792 , accept= FALSE
+iter 133 val= 67.93792 , accept= FALSE
+iter 134 val= 67.93792 , accept= FALSE
+iter 135 val= 67.93792 , accept= FALSE
+iter 136 val= 67.93792 , accept= FALSE
+iter 137 val= 67.93792 , accept= FALSE
+iter 138 val= 67.93792 , accept= FALSE
+iter 139 val= 67.93792 , accept= FALSE
+iter 140 val= 67.93792 , accept= FALSE
+iter 141 val= 64.80474 , accept= TRUE
+iter 142 val= 64.80474 , accept= FALSE
+iter 143 val= 64.80474 , accept= FALSE
+iter 144 val= 64.80474 , accept= FALSE
+iter 145 val= 64.80474 , accept= FALSE
+iter 146 val= 64.80474 , accept= FALSE
+iter 147 val= 64.80474 , accept= FALSE
+iter 148 val= 64.80474 , accept= FALSE
+iter 149 val= 64.80474 , accept= FALSE
+iter 150 val= 64.80474 , accept= FALSE
+iter 151 val= 64.80474 , accept= FALSE
+iter 152 val= 64.80474 , accept= FALSE
+iter 153 val= 64.80474 , accept= FALSE
+iter 154 val= 64.80474 , accept= FALSE
+iter 155 val= 64.80474 , accept= FALSE
+iter 156 val= 64.23574 , accept= TRUE
+iter 157 val= 64.23574 , accept= FALSE
+iter 158 val= 61.12553 , accept= TRUE
+iter 159 val= 61.12553 , accept= FALSE
+iter 160 val= 61.12553 , accept= FALSE
+iter 161 val= 57.42108 , accept= TRUE
+iter 162 val= 57.42108 , accept= FALSE
+iter 163 val= 57.42108 , accept= FALSE
+iter 164 val= 57.42108 , accept= FALSE
+iter 165 val= 57.42108 , accept= FALSE
+iter 166 val= 57.42108 , accept= FALSE
+iter 167 val= 55.53341 , accept= TRUE
+iter 168 val= 55.53341 , accept= FALSE
+iter 169 val= 55.53341 , accept= FALSE
+iter 170 val= 55.53341 , accept= FALSE
+iter 171 val= 55.53341 , accept= FALSE
+iter 172 val= 55.53341 , accept= FALSE
+iter 173 val= 55.53341 , accept= FALSE
+iter 174 val= 55.53341 , accept= FALSE
+iter 175 val= 55.53341 , accept= FALSE
+iter 176 val= 55.53341 , accept= FALSE
+iter 177 val= 55.53341 , accept= FALSE
+iter 178 val= 55.53341 , accept= FALSE
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/pomp -r 474
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