library(petab)
try(setwd(dirname(rstudioapi::getSourceEditorContext()$path)))
# -------------------------------------------------------------------------#
# Create enzyme kinetics model and data ----
# -------------------------------------------------------------------------#
# .. Eqnlist and objects -----
modelname <- "petab"
el <- NULL
el <- addReaction(el, from = "A", to = "B", rate = "k_AB * A", description = "A to B")
el <- addReaction(el, from = "B", to = "C", rate = "k_BC * B", description = "B to C")
el <- eqnlist_addDefaultCompartment(el, "cytoplasm") # Need compartment information for SBML
parInfo <- data.table(tibble::tribble(
~parName, ~parValue, ~parUnit,
"k_AB" , 1 ,"per_second" ,
"k_BC" , 0.1,"per_second" ))
speciesInfo <- data.table(tibble::tribble(
~speciesName, ~compName, ~initialAmount,
"A" ,"cytoplasm" , 1, # Amount, not concentration
"B" ,"cytoplasm" , 1e-12,
"C" ,"cytoplasm" , 1e-12))
# compartmentInfo is left as the default getCompartmentInfo(el)
# unitInfo is left as the default getUnitInfo(): If you need other units, you need to add them
# .. Simulate Data -----
compiled <- odemodel(f = el,modelname = modelname)
x <- Xs(compiled, condition = "C1", optionsOde = list(atol = 1e-12,rtol = 1e-12))
pars <- c(setNames(parInfo$parValue, parInfo$parName),
setNames(speciesInfo$initialAmount, speciesInfo$speciesName))
pred <- x(seq(0,50, 1), pars)
pred <- data.table(as.data.frame(pred))
pred <- rbind(pred,pred,pred)
pred <- pred[time %in% seq(25,50,5)]
pred <- pred[name == "C"]
set.seed(1)
pred[,`:=`(sigma = 0.1)]
pred[,`:=`(value = exp(log(value) + rnorm(length(value), sd = sigma)))]
pred[,`:=`(name = paste0("obs", name))]
# -------------------------------------------------------------------------#
# Export Petab ----
# -------------------------------------------------------------------------#
# .. Create petab tables -----
pe_ex <- petab_experimentalCondition("C1", "C1")
pe_ob <- petab_observables(observableId = c("obsC"),
observableName = c("obsC"),
observableFormula = c("C"),
observableTransformation = "log",
noiseFormula = c("0.1"),
noiseDistribution = c("normal"))
pe_me <- petab_measurementData(observableId = pred$name,
simulationConditionId = "C1",
measurement = pred$value,
time = pred$time,
observableParameters = NA_character_,
noiseParameters = pred$sigma,
datasetId = "data1",
replicateId = rep(1:3, each = nrow(pred)/3),
preequilibrationConditionId = NA_character_,
datapointId = 1:nrow(pred))
# .. error model -----
pe_ob[,`:=`(noiseFormula = paste0("noiseParameter1_", observableId))]
pe_me[,`:=`(noiseParameters = paste0("sigma_", observableId))]
# .. -----
pe_me[observableId == "obsE",`:=`(observableParameters = "offset_E")]
pe_mo <- petab_model(el,events = NULL,parInfo = parInfo, speciesInfo = speciesInfo)
# .. Create petab -----
pe <- petab(model = pe_mo,
experimentalCondition = pe_ex,
measurementData = pe_me,
observables = pe_ob)
pe$parameters <- petab_create_parameter_df(pe)
pe$parameters$objectivePriorType <- NA_character_
filename <- "petab"
writePetab(pe, filename)
unlink(list.files(".", "\\.o$|\\.so$|\\.c$"))
# Exit ----
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