[Calibayesr-commits] r11 - pkg/demo

[noreply at r-forge.r-project.org]

Author: conor
Date: 2011-01-13 11:06:00 +0100 (Thu, 13 Jan 2011)
New Revision: 11

Modified:
   pkg/demo/YeastGrowthDemo.R
Log:
I've updated the wsdl address to http://calibayes2.ncl.ac.uk:81/CaliBayesService_v2.wsdl since the previously referenced wsdl seems to be on a machine that has either crashed or no longer exists (calibayes1).

Modified: pkg/demo/YeastGrowthDemo.R
===================================================================
--- pkg/demo/YeastGrowthDemo.R	2010-03-25 14:58:07 UTC (rev 10)
+++ pkg/demo/YeastGrowthDemo.R	2011-01-13 10:06:00 UTC (rev 11)
@@ -1,56 +1,56 @@
-#Demo for YeastGrowthDemo
-library(calibayesR)
-library(SBMLModels)
-data(LogisticModel)
-
-#Which simulators are available
-wsdl = "http://calibayes1.ncl.ac.uk:81/CaliBayesService_v2.wsdl"
-listSimulatorMethods(wsdl)
-
-#Create settings file
-settings = createCaliBayesSettings(wsdl, burn=10, thin=2, simulator="copasi-deterministic")
-
-#Just use the first experiment and a copy of points for illustration
-yeast_data = YeastGrowth[[1]][1:3,]
-
-#Plot of the experiment data for the simple decay model
-plot(yeast_data$time, yeast_data$value, xlab="Time", ylab="Population level")
-
-#yeast_data$value are observations with error, 
-#where the error has a Normal distribution with mean 0, and precision tau
-
-#The number of particles
-#n increases with the number of parameters
-n = 100
-
-#Create prior for the initial species level
-species=data.frame(S=rlnorm(n,3,sqrt(0.02)))
-
-#Create prior distribution for the measurement error structure
-distributions = c('Gaussian')
-errors = data.frame(S.tau=rlnorm(n,- 11, 1))
-
-#Create priors for the parameters
-parameters = data.frame(K=rlnorm(n,9,0.2), r=rlnorm(n,1,0.6))
-
-#Create a distribution object that contains our prior
-prior = createCaliBayesDistribution(parameters, species, distributions, errors, FALSE)
-plot(prior)
-
-#Create a Experiment object
-experiments = createCaliBayesExperiment(yeast_data, species)
-
-sid = calibrate(wsdl, LogisticModel, settings, experiments, prior, asText=TRUE)
-
-isCaliBayesReady(wsdl, sid)
-isCaliBayesFinished(wsdl, sid, 10, 10)
-
-#Retrieve the posterior from CaliBayes
-posterior = getPosterior(wsdl, sid)
-
-#Check the output
-plot(posterior)
-
-#Compare the posterior to the prior
-compareDistributions(prior, posterior)
-
+#Demo for YeastGrowthDemo
+library(calibayesR)
+library(SBMLModels)
+data(LogisticModel)
+
+#Which simulators are available
+wsdl = "http://calibayes2.ncl.ac.uk:81/CaliBayesService_v2.wsdl"
+listSimulatorMethods(wsdl)
+
+#Create settings file
+settings = createCaliBayesSettings(wsdl, burn=10, thin=2, simulator="copasi-deterministic")
+
+#Just use the first experiment and a copy of points for illustration
+yeast_data = YeastGrowth[[1]][1:3,]
+
+#Plot of the experiment data for the simple decay model
+plot(yeast_data$time, yeast_data$value, xlab="Time", ylab="Population level")
+
+#yeast_data$value are observations with error, 
+#where the error has a Normal distribution with mean 0, and precision tau
+
+#The number of particles
+#n increases with the number of parameters
+n = 100
+
+#Create prior for the initial species level
+species=data.frame(S=rlnorm(n,3,sqrt(0.02)))
+
+#Create prior distribution for the measurement error structure
+distributions = c('Gaussian')
+errors = data.frame(S.tau=rlnorm(n,- 11, 1))
+
+#Create priors for the parameters
+parameters = data.frame(K=rlnorm(n,9,0.2), r=rlnorm(n,1,0.6))
+
+#Create a distribution object that contains our prior
+prior = createCaliBayesDistribution(parameters, species, distributions, errors, FALSE)
+plot(prior)
+
+#Create a Experiment object
+experiments = createCaliBayesExperiment(yeast_data, species)
+
+sid = calibrate(wsdl, LogisticModel, settings, experiments, prior, asText=TRUE)
+
+isCaliBayesReady(wsdl, sid)
+isCaliBayesFinished(wsdl, sid, 10, 10)
+
+#Retrieve the posterior from CaliBayes
+posterior = getPosterior(wsdl, sid)
+
+#Check the output
+plot(posterior)
+
+#Compare the posterior to the prior
+compareDistributions(prior, posterior)
+