[Pomp-commits] r191 - in pkg: . data inst inst/doc inst/examples src tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Dec 31 18:13:18 CET 2009
Author: kingaa
Date: 2009-12-31 18:13:18 +0100 (Thu, 31 Dec 2009)
New Revision: 191
Modified:
pkg/DESCRIPTION
pkg/data/euler.sir.R
pkg/inst/ChangeLog
pkg/inst/doc/advanced_topics_in_pomp.Rnw
pkg/inst/doc/advanced_topics_in_pomp.pdf
pkg/inst/doc/intro_to_pomp.pdf
pkg/inst/examples/euler_sir.R
pkg/inst/examples/euler_sir.c
pkg/src/euler_sir.c
pkg/tests/sir.R
pkg/tests/sir.Rout.save
Log:
- make some simplifications to the advanced (SIR) example:
it was confusing to have the dprocess specified when it is never used.
better to leave this out until such time as we have a method that uses dprocess.
Modified: pkg/DESCRIPTION
===================================================================
--- pkg/DESCRIPTION 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/DESCRIPTION 2009-12-31 17:13:18 UTC (rev 191)
@@ -1,8 +1,8 @@
Package: pomp
Type: Package
Title: Statistical inference for partially observed Markov processes
-Version: 0.26-4
-Date: 2009-12-30
+Version: 0.26-5
+Date: 2009-12-31
Author: Aaron A. King, Edward L. Ionides, Carles Breto, Steve Ellner, Bruce Kendall
Maintainer: Aaron A. King <kingaa at umich.edu>
Description: Inference methods for partially-observed Markov processes
Modified: pkg/data/euler.sir.R
===================================================================
--- pkg/data/euler.sir.R 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/data/euler.sir.R 2009-12-31 17:13:18 UTC (rev 191)
@@ -13,25 +13,20 @@
dimnames=list(NULL,paste("seas",1:3,sep=''))
),
delta.t=1/52/20,
- statenames=c("S","I","R","cases","W","B","dW"),
+ statenames=c("S","I","R","cases","W"),
paramnames=c("gamma","mu","iota","beta1","beta.sd","pop","rho"),
covarnames=c("seas1"),
zeronames=c("cases"),
comp.names=c("S","I","R"),
step.fun="sir_euler_simulator",
rprocess=euler.simulate,
- dens.fun="sir_euler_density",
- dprocess=onestep.density,
skeleton.vectorfield="sir_ODE",
rmeasure="binom_rmeasure",
dmeasure="binom_dmeasure",
PACKAGE="pomp",
initializer=function(params, t0, comp.names, ...){
p <- exp(params)
- snames <- c(
- "S","I","R","cases","W","B",
- "SI","SD","IR","ID","RD","dW"
- )
+ snames <- c("S","I","R","cases","W")
fracs <- p[paste(comp.names,"0",sep=".")]
x0 <- numeric(length(snames))
names(x0) <- snames
Modified: pkg/inst/ChangeLog
===================================================================
--- pkg/inst/ChangeLog 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/inst/ChangeLog 2009-12-31 17:13:18 UTC (rev 191)
@@ -1,5 +1,8 @@
2009-12-30 kingaa
+ * [r190] DESCRIPTION, inst/ChangeLog,
+ inst/doc/advanced_topics_in_pomp.pdf, inst/doc/intro_to_pomp.pdf:
+ - version 0.26-4
* [r189] inst/ChangeLog, inst/doc/advanced_topics_in_pomp.pdf,
inst/doc/intro_to_pomp.Rnw, inst/doc/intro_to_pomp.pdf,
man/euler.Rd, man/mif.Rd, man/pomp-package.Rd, man/pomp.Rd: -
Modified: pkg/inst/doc/advanced_topics_in_pomp.Rnw
===================================================================
--- pkg/inst/doc/advanced_topics_in_pomp.Rnw 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/inst/doc/advanced_topics_in_pomp.Rnw 2009-12-31 17:13:18 UTC (rev 191)
@@ -243,30 +243,25 @@
t0=0,
tcovar=seq(0,25,by=1/52),
covar=matrix(
- periodic.bspline.basis(seq(0,25,by=1/52),nbasis=3,period=1,degree=3),
+ periodic.bspline.basis(seq(0,50,by=1/52),nbasis=3,period=1,degree=3),
ncol=3,
dimnames=list(NULL,paste("seas",1:3,sep=''))
),
delta.t=1/52/20,
- statenames=c("S","I","R","cases","W","B","dW"),
+ statenames=c("S","I","R","cases","W"),
paramnames=c("gamma","mu","iota","beta1","beta.sd","pop","rho"),
covarnames=c("seas1"),
zeronames=c("cases"),
comp.names=c("S","I","R"),
- rprocess=euler.simulate,
step.fun="sir_euler_simulator",
- dprocess=onestep.density,
- dens.fun="sir_euler_density",
+ rprocess=euler.simulate,
skeleton.vectorfield="sir_ODE",
rmeasure="binom_rmeasure",
dmeasure="binom_dmeasure",
PACKAGE="pomp",
initializer=function(params, t0, comp.names, ...){
p <- exp(params)
- snames <- c(
- "S","I","R","cases","W","B",
- "SI","SD","IR","ID","RD","dW"
- )
+ snames <- c("S","I","R","cases","W")
fracs <- p[paste(comp.names,"0",sep=".")]
x0 <- numeric(length(snames))
names(x0) <- snames
Modified: pkg/inst/doc/advanced_topics_in_pomp.pdf
===================================================================
(Binary files differ)
Modified: pkg/inst/doc/intro_to_pomp.pdf
===================================================================
(Binary files differ)
Modified: pkg/inst/examples/euler_sir.R
===================================================================
--- pkg/inst/examples/euler_sir.R 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/inst/examples/euler_sir.R 2009-12-31 17:13:18 UTC (rev 191)
@@ -44,39 +44,11 @@
I=I+trans[2]-trans[4]-trans[5],
R=R+trans[4]-trans[6],
cases=cases+trans[4],
- W=if (beta.sd>0) W+(dW-delta.t)/beta.sd else W,
- B=trans[1],
- SI=trans[2],
- SD=trans[3],
- IR=trans[4],
- ID=trans[5],
- RD=trans[6],
- dW=dW
+ W=if (beta.sd>0) W+(dW-delta.t)/beta.sd else W
)
}
)
},
- dens.fun=function(t1,t2,params,x1,x2,covars,...) {
- params <- exp(params)
- with(
- as.list(params),
- {
- dt <- t2-t1
- beta <- exp(sum(log(c(beta1,beta2,beta3))*covars))
- beta.var <- beta.sd^2
- dW <- x2['dW']
- foi <- (iota+beta*x1["I"]*dW/dt)/pop
- probs <- c(
- dpois(x=x2["B"],lambda=mu*pop*dt,log=T),
- deulermultinom(x=x2[c("SI","SD")],size=x1["S"],rate=c(foi,mu),dt=dt,log=T),
- deulermultinom(x=x2[c("IR","ID")],size=x1["I"],rate=c(gamma,mu),dt=dt,log=T),
- deulermultinom(x=x2["RD"],size=x1["R"],rate=c(mu),dt=dt,log=T),
- dgamma(x=dW,shape=dt/beta.var,scale=beta.var,log=T)
- )
- sum(probs)
- }
- )
- },
skeleton.vectorfield=function(x,t,params,covars,...) {
params <- exp(params)
with(
@@ -103,7 +75,6 @@
)
},
rprocess=euler.simulate,
- dprocess=onestep.density,
measurement.model=measles~binom(size=cases,prob=exp(rho)),
initializer=function(params,t0,...){
p <- exp(params)
@@ -113,9 +84,9 @@
fracs <- c(S.0,I.0,R.0)
x0 <- c(
round(pop*fracs/sum(fracs)), # make sure the three compartments sum to 'pop' initially
- rep(0,9) # zeros for 'cases', 'W', and the transition numbers
+ rep(0,2) # zeros for 'cases' and 'W'
)
- names(x0) <- c("S","I","R","cases","W","B","SI","SD","IR","ID","RD","dW")
+ names(x0) <- c("S","I","R","cases","W")
x0
}
)
@@ -150,14 +121,12 @@
tcovar=tbasis,
covar=basis,
delta.t=1/52/20,
- statenames=c("S","I","R","cases","W","B","dW"),
+ statenames=c("S","I","R","cases","W"),
paramnames=c("gamma","mu","iota","beta1","beta.sd","pop","rho"),
covarnames=c("seas1"),
zeronames=c("cases"),
step.fun="sir_euler_simulator",
rprocess=euler.simulate,
- dens.fun="sir_euler_density",
- dprocess=onestep.density,
skeleton.vectorfield="sir_ODE",
rmeasure="binom_rmeasure",
dmeasure="binom_dmeasure",
@@ -170,9 +139,9 @@
fracs <- c(S.0,I.0,R.0)
x0 <- c(
round(pop*fracs/sum(fracs)), # make sure the three compartments sum to 'pop' initially
- rep(0,9) # zeros for 'cases', 'W', and the transition numbers
+ rep(0,2) # zeros for 'cases' and 'W'
)
- names(x0) <- c("S","I","R","cases","W","B","SI","SD","IR","ID","RD","dW")
+ names(x0) <- c("S","I","R","cases","W")
x0
}
)
Modified: pkg/inst/examples/euler_sir.c
===================================================================
--- pkg/inst/examples/euler_sir.c 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/inst/examples/euler_sir.c 2009-12-31 17:13:18 UTC (rev 191)
@@ -36,8 +36,6 @@
#define RCVD (x[stateindex[2]]) // number of recovereds
#define CASE (x[stateindex[3]]) // number of cases (accumulated per reporting period)
#define W (x[stateindex[4]]) // integrated white noise
-#define BIRTHS (x[stateindex[5]]) // births
-#define dW (x[stateindex[6]]) // white noise process
#define SEASBASIS (covar[covindex[0]]) // first column of seasonality basis in lookup table
@@ -68,10 +66,11 @@
{
int nrate = 6;
double rate[nrate]; // transition rates
- double *trans; // transition numbers
+ double trans[nrate]; // transition numbers
double gamma, mu, iota, beta_sd, beta_var, popsize;
double beta;
-
+ double dW;
+
// untransform the parameters
gamma = exp(LOGGAMMA);
mu = exp(LOGMU);
@@ -112,7 +111,6 @@
rate[5] = mu; // death from recovered class
// compute the transition numbers
- trans = &BIRTHS;
trans[0] = rpois(rate[0]*dt); // births are Poisson
reulermultinom(2,SUSC,&rate[1],dt,&trans[1]);
reulermultinom(2,INFD,&rate[3],dt,&trans[3]);
@@ -186,89 +184,9 @@
#undef RCVD
#undef CASE
#undef W
-#undef BIRTHS
-#undef dW
-#define SUSC (x1[stateindex[0]]) // number of susceptibles
-#define INFD (x1[stateindex[1]]) // number of infectives
-#define RCVD (x1[stateindex[2]]) // number of recovereds
-#define CASE (x1[stateindex[3]]) // number of cases (accumulated per reporting period)
-#define W (x1[stateindex[4]]) // integrated white noise
-#define BIRTHS (x2[stateindex[5]]) // births
-#define dW (x2[stateindex[6]]) // white noise process
-
-// SIR model with Euler multinomial step
-// forced transmission (basis functions passed as covariates)
-// constant population size as a parameter
-// environmental stochasticity on transmission
-void sir_euler_density (double *f, double *x1, double *x2, double t1, double t2, const double *p,
- const int *stateindex, const int *parindex, const int *covindex,
- int covdim, const double *covar)
-{
- int nrate = 6;
- double rate[nrate]; // transition rates
- double *trans; // transition numbers
- double gamma, mu, iota, beta_sd, popsize;
- double beta;
- double dt = t2-t1;
-
- // untransform the parameters
- gamma = exp(LOGGAMMA);
- mu = exp(LOGMU);
- iota = exp(LOGIOTA);
- beta_sd = exp(LOGBETA_SD);
- popsize = exp(LOGPOPSIZE);
-
- beta = exp(dot_product(covdim,&SEASBASIS,&LOGBETA));
-
- // test to make sure the parameters and state variable values are sane
- if (!(R_FINITE(beta)) ||
- !(R_FINITE(gamma)) ||
- !(R_FINITE(mu)) ||
- !(R_FINITE(beta_sd)) ||
- !(R_FINITE(iota)) ||
- !(R_FINITE(popsize)) ||
- !(R_FINITE(SUSC)) ||
- !(R_FINITE(INFD)) ||
- !(R_FINITE(RCVD)) ||
- !(R_FINITE(CASE)) ||
- !(R_FINITE(W))) {
- *f = R_NaN;
- return;
- }
-
- // compute the transition rates
- trans = &BIRTHS;
- if (beta_sd > 0.0) { // environmental noise is ON
- double beta_var = beta_sd*beta_sd;
- *f = dgamma(dW,dt/beta_var,beta_var,1);
- } else { // environmental noise is OFF
- *f = 0; // THIS ASSUMES THAT dw = dt !!!
- }
- rate[0] = mu*popsize; // birth into susceptible class
- rate[1] = (iota+beta*INFD*dW/dt)/popsize; // force of infection
- rate[2] = mu; // death from susceptible class
- rate[3] = gamma; // recovery
- rate[4] = mu; // death from infectious class
- rate[5] = mu; // death from recovered class
-
- // compute the transition numbers
- *f += dpois(trans[0],rate[0]*dt,1); // births are Poisson
- *f += deulermultinom(2,SUSC,&rate[1],dt,&trans[1],1);
- *f += deulermultinom(2,INFD,&rate[3],dt,&trans[3],1);
- *f += deulermultinom(1,RCVD,&rate[5],dt,&trans[5],1);
-}
-
#undef SEASBASIS
-#undef SUSC
-#undef INFD
-#undef RCVD
-#undef CASE
-#undef W
-#undef BIRTHS
-#undef dW
-
#undef LOGGAMMA
#undef LOGMU
#undef LOGIOTA
Modified: pkg/src/euler_sir.c
===================================================================
--- pkg/src/euler_sir.c 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/src/euler_sir.c 2009-12-31 17:13:18 UTC (rev 191)
@@ -36,8 +36,6 @@
#define RCVD (x[stateindex[2]]) // number of recovereds
#define CASE (x[stateindex[3]]) // number of cases (accumulated per reporting period)
#define W (x[stateindex[4]]) // integrated white noise
-#define BIRTHS (x[stateindex[5]]) // births
-#define dW (x[stateindex[6]]) // white noise process
#define SEASBASIS (covar[covindex[0]]) // first column of seasonality basis in lookup table
@@ -68,10 +66,11 @@
{
int nrate = 6;
double rate[nrate]; // transition rates
- double *trans; // transition numbers
+ double trans[nrate]; // transition numbers
double gamma, mu, iota, beta_sd, beta_var, popsize;
double beta;
-
+ double dW;
+
// untransform the parameters
gamma = exp(LOGGAMMA);
mu = exp(LOGMU);
@@ -112,7 +111,6 @@
rate[5] = mu; // death from recovered class
// compute the transition numbers
- trans = &BIRTHS;
trans[0] = rpois(rate[0]*dt); // births are Poisson
reulermultinom(2,SUSC,&rate[1],dt,&trans[1]);
reulermultinom(2,INFD,&rate[3],dt,&trans[3]);
@@ -186,89 +184,9 @@
#undef RCVD
#undef CASE
#undef W
-#undef BIRTHS
-#undef dW
-#define SUSC (x1[stateindex[0]]) // number of susceptibles
-#define INFD (x1[stateindex[1]]) // number of infectives
-#define RCVD (x1[stateindex[2]]) // number of recovereds
-#define CASE (x1[stateindex[3]]) // number of cases (accumulated per reporting period)
-#define W (x1[stateindex[4]]) // integrated white noise
-#define BIRTHS (x2[stateindex[5]]) // births
-#define dW (x2[stateindex[6]]) // white noise process
-
-// SIR model with Euler multinomial step
-// forced transmission (basis functions passed as covariates)
-// constant population size as a parameter
-// environmental stochasticity on transmission
-void sir_euler_density (double *f, double *x1, double *x2, double t1, double t2, const double *p,
- const int *stateindex, const int *parindex, const int *covindex,
- int covdim, const double *covar)
-{
- int nrate = 6;
- double rate[nrate]; // transition rates
- double *trans; // transition numbers
- double gamma, mu, iota, beta_sd, popsize;
- double beta;
- double dt = t2-t1;
-
- // untransform the parameters
- gamma = exp(LOGGAMMA);
- mu = exp(LOGMU);
- iota = exp(LOGIOTA);
- beta_sd = exp(LOGBETA_SD);
- popsize = exp(LOGPOPSIZE);
-
- beta = exp(dot_product(covdim,&SEASBASIS,&LOGBETA));
-
- // test to make sure the parameters and state variable values are sane
- if (!(R_FINITE(beta)) ||
- !(R_FINITE(gamma)) ||
- !(R_FINITE(mu)) ||
- !(R_FINITE(beta_sd)) ||
- !(R_FINITE(iota)) ||
- !(R_FINITE(popsize)) ||
- !(R_FINITE(SUSC)) ||
- !(R_FINITE(INFD)) ||
- !(R_FINITE(RCVD)) ||
- !(R_FINITE(CASE)) ||
- !(R_FINITE(W))) {
- *f = R_NaN;
- return;
- }
-
- // compute the transition rates
- trans = &BIRTHS;
- if (beta_sd > 0.0) { // environmental noise is ON
- double beta_var = beta_sd*beta_sd;
- *f = dgamma(dW,dt/beta_var,beta_var,1);
- } else { // environmental noise is OFF
- *f = 0; // THIS ASSUMES THAT dw = dt !!!
- }
- rate[0] = mu*popsize; // birth into susceptible class
- rate[1] = (iota+beta*INFD*dW/dt)/popsize; // force of infection
- rate[2] = mu; // death from susceptible class
- rate[3] = gamma; // recovery
- rate[4] = mu; // death from infectious class
- rate[5] = mu; // death from recovered class
-
- // compute the transition numbers
- *f += dpois(trans[0],rate[0]*dt,1); // births are Poisson
- *f += deulermultinom(2,SUSC,&rate[1],dt,&trans[1],1);
- *f += deulermultinom(2,INFD,&rate[3],dt,&trans[3],1);
- *f += deulermultinom(1,RCVD,&rate[5],dt,&trans[5],1);
-}
-
#undef SEASBASIS
-#undef SUSC
-#undef INFD
-#undef RCVD
-#undef CASE
-#undef W
-#undef BIRTHS
-#undef dW
-
#undef LOGGAMMA
#undef LOGMU
#undef LOGIOTA
Modified: pkg/tests/sir.R
===================================================================
--- pkg/tests/sir.R 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/tests/sir.R 2009-12-31 17:13:18 UTC (rev 191)
@@ -186,41 +186,27 @@
)
print(h1[c("S","I","R"),,],digits=4)
-data(euler.sir)
+## now repeat using the compiled native codes built into the package
-show(euler.sir)
+po <- euler.sir
set.seed(3049953)
## simulate from the model
tic <- Sys.time()
-x <- simulate(euler.sir,nsim=100)
+x <- simulate(po,nsim=100)
toc <- Sys.time()
print(toc-tic)
plot(x[[1]],variables=c("S","I","R","cases","W"))
t3 <- seq(0,20,by=1/52)
tic <- Sys.time()
-X4 <- trajectory(euler.sir,times=t3,hmax=1/52)
+X4 <- trajectory(po,times=t3,hmax=1/52)
toc <- Sys.time()
print(toc-tic)
plot(t3,X4['I',1,],type='l')
-f2 <- dprocess(
- euler.sir,
- x=X1$states[,,31:40],
- times=t1[31:40],
- params=matrix(
- log(params),
- nrow=length(params),
- ncol=10,
- dimnames=list(names(params),NULL)
- ),
- log=TRUE
- )
-print(apply(f2,1,sum),digits=4)
-
g2 <- dmeasure(
- euler.sir,
+ po,
y=rbind(measles=X1$obs[,7,]),
x=X1$states,
times=t1,
@@ -235,22 +221,20 @@
print(apply(g2,1,sum),digits=4)
h2 <- skeleton(
- euler.sir,
+ po,
x=X2$states[,1,55:70,drop=FALSE],
t=t2[55:70],
params=as.matrix(log(params))
)
print(h2[c("S","I","R"),,],digits=4)
-print(max(abs(f2-f1),na.rm=T),digits=4)
print(max(abs(g2-g1),na.rm=T),digits=4)
print(max(abs(h2-h1),na.rm=T),digits=4)
-data(euler.sir)
-states(euler.sir)[,1:2]
-time(euler.sir) <- seq(0,1,by=1/52)
-states(euler.sir)[,1:3]
-states(simulate(euler.sir))[,1:3]
+states(po)[,1:2]
+time(po) <- seq(0,1,by=1/52)
+states(po)[,1:3]
+states(simulate(po))[,1:3]
dev.off()
Modified: pkg/tests/sir.Rout.save
===================================================================
--- pkg/tests/sir.Rout.save 2009-12-30 15:57:59 UTC (rev 190)
+++ pkg/tests/sir.Rout.save 2009-12-31 17:13:18 UTC (rev 191)
@@ -1,5 +1,5 @@
-R version 2.9.1 (2009-06-26)
+R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
@@ -423,7 +423,7 @@
}
y
}
-<environment: 0x1203c28>
+<environment: 0x185b800>
measurement model density, dmeasure =
function (y, x, t, params, log, covars, ...)
{
@@ -436,7 +436,7 @@
f
else exp(f)
}
-<environment: 0x1203c28>
+<environment: 0x185b800>
initializer =
function (params, t0, ...)
{
@@ -507,7 +507,7 @@
> x <- simulate(po,params=log(params),nsim=3)
> toc <- Sys.time()
> print(toc-tic)
-Time difference of 1.975832 secs
+Time difference of 2.009385 secs
>
> pdf(file='sir.pdf')
>
@@ -524,7 +524,7 @@
> X3 <- trajectory(po,params=log(params),times=t3,hmax=1/52)
> toc <- Sys.time()
> print(toc-tic)
-Time difference of 4.516915 secs
+Time difference of 4.488558 secs
> plot(t3,X3['I',1,],type='l')
>
> f1 <- dprocess(
@@ -574,557 +574,29 @@
I 6165 8975 11503 15834.2 21418 27852 34849
R -30746 -26601 -22900 -16156.5 -6714 5662 22453
>
-> data(euler.sir)
+> ## now repeat using the compiled native codes built into the package
>
-> show(euler.sir)
- time measles S I R cases W B SI SD IR ID RD
-1 0.01923077 616 45318 2038 2052647 1045 -0.23343314 52 49 0 58 0 40
-2 0.03846154 626 45113 2020 2052886 996 -0.02382536 52 57 1 52 0 35
-3 0.05769231 559 44915 2065 2053068 970 0.14783667 38 58 1 64 0 47
-4 0.07692308 612 44614 2152 2053280 1010 0.05182453 54 61 0 47 0 33
-5 0.09615385 673 44274 2184 2053652 1091 -0.02306256 31 52 1 56 0 25
-6 0.11538462 649 43794 2336 2053982 1106 0.21577036 43 62 0 56 0 48
-7 0.13461538 667 43340 2441 2054340 1159 0.17847926 35 65 1 68 0 45
-8 0.15384615 744 42779 2620 2054753 1229 0.10016846 44 74 1 65 0 42
-9 0.17307692 823 41977 2830 2055329 1359 -0.03593619 35 76 0 73 0 47
-10 0.19230769 852 41143 3010 2055983 1446 -0.04214926 41 88 0 59 0 32
-11 0.21153846 894 40227 3188 2056683 1525 0.11057318 41 77 0 72 0 34
-12 0.23076923 1011 39309 3273 2057514 1651 0.03682855 51 84 1 110 0 48
-13 0.25000000 983 38353 3384 2058391 1659 0.11847457 52 64 4 84 0 34
-14 0.26923077 1036 37422 3447 2059232 1674 0.18459661 44 88 1 81 0 54
-15 0.28846154 998 36553 3422 2060082 1682 -0.06696936 44 102 1 86 1 42
-16 0.30769231 1011 35750 3356 2060990 1702 0.15311053 38 82 0 84 0 45
-17 0.32692308 983 35094 3215 2061847 1621 0.09218384 42 83 1 88 0 33
-18 0.34615385 934 34506 3029 2062569 1569 0.29357440 48 77 0 76 0 46
-19 0.36538462 833 34060 2825 2063272 1430 0.15543085 41 73 1 73 0 37
-20 0.38461538 774 33758 2609 2063780 1328 0.28027118 34 68 2 61 0 41
-21 0.40384615 752 33545 2362 2064250 1249 0.31715722 33 40 1 67 0 33
-22 0.42307692 670 33457 2114 2064583 1131 0.43797614 38 42 1 56 0 47
-23 0.44230769 595 33565 1875 2064745 978 0.27351520 48 32 1 44 0 40
-24 0.46153846 528 33695 1658 2064816 874 0.33919388 44 28 0 36 0 37
-25 0.48076923 473 33878 1427 2064830 792 0.33973801 35 30 0 29 0 24
-26 0.50000000 429 34186 1245 2064667 667 0.41309774 27 24 1 30 0 51
-27 0.51923077 322 34643 1036 2064400 545 0.32707592 52 15 0 29 0 39
-28 0.53846154 277 35180 873 2064053 451 0.19646192 49 10 2 21 0 37
-29 0.55769231 224 35706 735 2063666 393 0.18991544 31 18 0 24 0 40
-30 0.57692308 194 36299 612 2063213 339 0.12573803 34 8 1 12 0 32
-31 0.59615385 168 36893 526 2062654 278 0.13981543 30 2 0 10 0 45
-32 0.61538462 159 37480 438 2062102 247 0.17438300 32 6 1 9 0 37
-33 0.63461538 102 38095 375 2061498 172 0.23967634 39 6 0 10 0 47
-34 0.65384615 136 38799 284 2060858 194 0.13755786 51 2 3 7 0 44
-35 0.67307692 74 39525 218 2060206 123 0.08037701 37 1 0 8 0 41
-36 0.69230769 53 40238 197 2059447 87 0.22075061 28 3 0 5 0 30
-37 0.71153846 62 41001 151 2058782 96 0.11658598 52 2 1 5 0 41
-38 0.73076923 41 41726 115 2058026 73 0.03575223 40 2 2 3 0 41
-39 0.75000000 39 42523 84 2057281 58 0.13233301 45 2 0 4 0 41
-40 0.76923077 12 43278 90 2056507 26 -0.06742852 50 4 0 0 0 38
-41 0.78846154 25 44091 82 2055718 37 -0.20462744 36 2 0 2 0 32
-42 0.80769231 31 44835 65 2054971 41 -0.22748932 28 1 1 3 0 42
-43 0.82692308 17 45640 65 2054157 23 -0.44995890 38 1 0 0 0 52
-44 0.84615385 18 46357 59 2053406 30 -0.40279498 33 1 1 1 0 30
-45 0.86538462 15 47127 44 2052651 28 -0.47959030 39 1 1 0 0 26
-46 0.88461538 13 47926 35 2051866 20 -0.68189209 38 1 0 1 0 38
-47 0.90384615 11 48715 34 2051065 14 -0.63900133 40 1 0 0 0 36
-48 0.92307692 9 49525 36 2050278 16 -0.63994901 30 1 1 0 0 40
-49 0.94230769 13 50312 40 2049464 18 -0.63032479 33 1 1 0 0 29
-50 0.96153846 11 51049 42 2048682 18 -0.47608654 38 0 0 2 0 51
-51 0.98076923 10 51808 51 2047907 17 -0.39053790 41 2 1 0 0 31
-52 1.00000000 17 52616 50 2047135 28 -0.24811016 46 4 1 0 0 38
-53 1.01923077 14 53359 54 2046395 25 -0.14548526 35 0 2 1 0 31
-54 1.03846154 19 54107 56 2045607 32 -0.33061880 39 5 2 2 0 43
-55 1.05769231 15 54892 68 2044873 26 -0.40793381 36 1 0 0 0 40
-56 1.07692308 26 55639 66 2044097 40 -0.43656551 32 4 1 3 0 28
-57 1.09615385 26 56329 83 2043362 38 -0.32970344 29 5 3 3 0 37
-58 1.11538462 24 57004 98 2042570 48 -0.27780751 30 0 0 3 0 40
-59 1.13461538 34 57682 110 2041869 67 -0.49094954 42 4 3 5 0 35
-60 1.15384615 45 58350 127 2041190 69 -0.68013808 40 8 1 3 0 27
-61 1.17307692 45 59013 179 2040516 74 -0.78779956 44 8 1 3 0 39
-62 1.19230769 56 59654 212 2039851 114 -0.78396548 36 8 1 9 0 40
-63 1.21153846 86 60190 280 2039247 132 -0.68717315 44 8 1 11 0 47
-64 1.23076923 75 60654 415 2038599 138 -0.58816451 41 11 3 11 0 45
-65 1.25000000 157 61018 605 2038067 252 -0.52871848 39 30 3 19 0 33
-66 1.26923077 180 61263 832 2037579 323 -0.59846996 42 31 1 19 0 42
-67 1.28846154 287 61313 1130 2037243 487 -0.56289492 40 48 0 33 0 39
-68 1.30769231 409 61030 1512 2037102 668 -0.47529347 41 67 2 38 0 45
-69 1.32692308 513 60449 1992 2037243 883 -0.55577105 45 85 0 61 0 32
-70 1.34615385 663 59620 2536 2037529 1111 -0.40009198 43 97 1 66 0 41
-71 1.36538462 845 58297 3230 2038176 1411 -0.51354479 36 116 2 69 0 48
-72 1.38461538 1041 56553 4003 2039123 1733 -0.47004141 36 128 0 109 0 39
-73 1.40384615 1286 54484 4693 2040521 2170 -0.32503552 41 139 1 119 0 38
-74 1.42307692 1489 52278 5178 2042219 2487 -0.28972645 36 145 1 135 1 45
-75 1.44230769 1538 50197 5449 2043989 2578 -0.42048560 58 136 2 111 0 44
-76 1.46153846 1610 48134 5554 2045921 2753 -0.34909517 43 143 0 132 0 48
-77 1.48076923 1657 46152 5520 2047877 2742 -0.26218412 43 141 1 156 0 37
-78 1.50000000 1551 44573 5219 2049718 2654 -0.17463656 38 121 0 121 0 48
-79 1.51923077 1533 43303 4767 2051430 2541 0.13498494 38 87 2 127 0 50
-80 1.53846154 1304 42355 4346 2052796 2147 -0.01211920 28 78 0 115 0 42
-81 1.55769231 1145 41697 3783 2054086 2010 0.03293035 42 66 1 91 0 35
-82 1.57692308 1016 41323 3247 2054925 1686 -0.25498958 43 40 3 73 0 32
-83 1.59615385 908 41099 2736 2055644 1509 -0.34409660 37 48 1 76 0 30
-84 1.61538462 760 41126 2214 2056131 1264 -0.52666076 41 35 0 65 0 37
-85 1.63461538 599 41234 1848 2056368 1021 -0.30731247 32 33 1 43 0 43
-86 1.65384615 449 41544 1555 2056356 780 -0.32200354 51 22 0 35 0 43
-87 1.67307692 388 41874 1317 2056252 693 -0.37403780 42 18 2 37 0 39
-88 1.69230769 387 42277 1119 2056078 635 -0.22976211 51 17 0 28 0 40
-89 1.71153846 292 42763 962 2055756 491 -0.21560701 37 14 0 21 0 44
-90 1.73076923 263 43316 794 2055383 430 -0.14208254 47 11 0 19 0 43
-91 1.75000000 224 43875 687 2054998 364 -0.20035037 49 14 1 26 0 37
-92 1.76923077 180 44466 602 2054515 299 -0.18466700 47 12 1 12 0 32
-93 1.78846154 160 45028 505 2054032 282 -0.22000195 43 13 0 9 0 42
-94 1.80769231 138 45640 452 2053505 234 -0.12075892 48 8 1 12 0 43
-95 1.82692308 118 46295 397 2052875 190 -0.23403658 36 4 0 9 0 45
-96 1.84615385 106 46928 351 2052295 190 -0.28140298 42 7 1 10 0 35
-97 1.86538462 104 47621 310 2051670 172 -0.36579931 41 8 1 8 0 45
-98 1.88461538 88 48233 277 2051068 149 -0.40558561 55 3 0 10 0 40
-99 1.90384615 83 48864 263 2050382 129 -0.41035027 37 6 0 6 0 37
-100 1.92307692 92 49476 241 2049738 139 -0.48169108 48 2 2 8 0 38
-101 1.94230769 72 50202 239 2049095 121 -0.53959622 49 5 2 7 0 42
-102 1.96153846 78 50900 234 2048446 132 -0.60648214 29 8 0 8 0 38
-103 1.98076923 59 51525 248 2047732 115 -0.66705505 48 7 4 6 0 41
-104 2.00000000 75 52210 242 2047067 127 -0.60053175 43 8 1 5 0 38
-105 2.01923077 70 52826 265 2046435 120 -0.50431053 32 8 3 8 0 36
-106 2.03846154 101 53472 285 2045796 149 -0.25586265 43 7 0 15 0 41
-107 2.05769231 82 54114 313 2045164 138 -0.37868239 36 10 0 3 0 40
-108 2.07692308 88 54694 365 2044506 161 -0.53519436 48 12 0 7 0 36
-109 2.09615385 126 55220 433 2043890 189 -0.49626709 47 13 2 9 0 52
-110 2.11538462 162 55711 516 2043365 237 -0.41789549 36 21 2 14 0 34
-111 2.13461538 159 56137 641 2042834 262 -0.46829412 44 20 1 17 0 31
-112 2.15384615 210 56463 773 2042443 341 -0.74613620 40 31 3 25 0 47
-113 2.17307692 250 56554 1034 2042097 416 -0.53641459 48 41 2 21 0 31
-114 2.19230769 339 56565 1246 2041915 560 -0.86950817 46 32 3 31 0 34
-115 2.21153846 436 56307 1563 2041881 731 -0.79115329 41 50 1 40 0 48
-116 2.23076923 512 55862 1914 2041982 880 -0.75925161 36 87 1 45 0 51
-117 2.25000000 648 55046 2417 2042323 1110 -0.71871132 51 94 0 72 0 33
-118 2.26923077 840 53946 2947 2042866 1346 -0.73518670 40 95 1 69 0 40
-119 2.28846154 984 52425 3592 2043723 1659 -0.68792582 46 120 2 97 0 41
-120 2.30769231 1132 50522 4398 2044855 1928 -0.57911984 46 151 0 99 0 47
-121 2.32692308 1404 48192 5179 2046388 2349 -0.54770487 47 171 0 115 0 43
-122 2.34615385 1623 45826 5696 2048282 2682 -0.38512822 46 161 1 142 0 40
-123 2.36538462 1762 43300 6106 2050356 2912 -0.41541495 44 148 0 157 0 48
-124 2.38461538 1787 40794 6395 2052555 2985 -0.11872976 42 169 0 135 0 41
-125 2.40384615 1906 38708 6136 2054859 3105 -0.38217946 33 165 1 122 0 42
-126 2.42307692 1801 36763 5929 2057024 2938 -0.37554258 34 137 0 140 0 28
-127 2.44230769 1676 35323 5347 2059032 2787 -0.56057212 44 87 0 122 0 37
-128 2.46153846 1506 34302 4688 2060756 2511 -0.69205985 42 93 0 122 0 51
-129 2.48076923 1282 33605 4035 2062122 2144 -1.00878235 43 68 1 87 0 34
-130 2.50000000 1129 33106 3484 2063114 1808 -0.89239531 39 51 0 83 0 36
-131 2.51923077 919 32907 2838 2063910 1585 -0.79888960 42 43 0 76 0 44
-132 2.53846154 775 32884 2421 2064393 1273 -0.47039221 52 44 0 53 0 34
-133 2.55769231 673 33059 1950 2064727 1126 -0.42992121 31 37 0 60 0 43
-134 2.57692308 534 33343 1577 2064769 889 -0.14340333 46 20 0 42 0 37
-135 2.59615385 414 33837 1232 2064669 712 -0.37955547 42 14 0 41 0 44
-136 2.61538462 303 34335 1000 2064440 535 -0.51596820 41 12 1 20 0 35
-137 2.63461538 259 34877 805 2064072 434 -0.45075394 48 10 0 22 0 31
-138 2.65384615 207 35476 674 2063650 328 -0.37712635 43 18 1 19 0 29
-139 2.67307692 172 36087 577 2063209 282 -0.27194398 43 8 0 14 0 29
-140 2.69230769 158 36775 474 2062694 250 -0.23055234 40 8 0 11 0 35
-141 2.71153846 131 37407 376 2062131 218 -0.13284405 48 1 1 10 0 33
-142 2.73076923 108 38109 291 2061485 168 -0.13016837 44 4 1 10 0 53
-143 2.75000000 74 38848 231 2060820 130 -0.03313058 42 3 1 5 0 39
-144 2.76923077 61 39576 200 2060156 108 0.05626756 41 4 0 5 0 46
-145 2.78846154 61 40291 159 2059474 97 -0.04637448 43 5 3 3 0 28
-146 2.80769231 38 41047 122 2058744 69 -0.07579954 41 3 0 3 0 50
-147 2.82692308 41 41773 94 2058024 61 -0.12698925 30 1 2 1 0 30
-148 2.84615385 28 42519 73 2057308 50 0.01120443 42 1 1 1 0 36
-149 2.86538462 21 43245 77 2056547 33 -0.11584266 39 3 2 2 0 35
-150 2.88461538 17 44001 66 2055736 34 0.05695438 50 2 3 2 0 42
-151 2.90384615 18 44800 59 2055009 31 -0.21614297 47 0 0 0 0 35
-152 2.92307692 12 45586 50 2054244 25 -0.21752992 47 1 0 1 0 28
-153 2.94230769 22 46344 48 2053454 29 -0.36255244 45 2 0 0 0 40
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/pomp -r 191
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