## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----results="hide", message=FALSE-------------------------------------------- library(landsepi) ## ----results="hide", message=FALSE-------------------------------------------- ## Initialisation of the simulation simul_params <- createSimulParams(outputDir = getwd()) ## Seed simul_params@Seed simul_params <- setSeed(simul_params, seed = 1) simul_params@Seed ## Time parameters Nyears = 6 nTSpY = 120 simul_params <- setTime(simul_params, Nyears = Nyears, nTSpY = nTSpY) ## Landscape landscape <- loadLandscape(id = 1) simul_params <- setLandscape(simul_params, land = landscape) ## ----------------------------------------------------------------------------- basic_patho_param <- loadPathogen(disease = "rust") ## ----------------------------------------------------------------------------- basic_patho_param$repro_sex_prob <- 1 ## at every time step all pathogen individuals reproduces sexually basic_patho_param$repro_sex_prob <- 0 ## at every time step all pathogen individuals reproduces clonally basic_patho_param$repro_sex_prob <- 0.5 ## at every time step half of the pathogen population ## reproduce clonally and half sexually basic_patho_param ## ----------------------------------------------------------------------------- repro_sex_probs <- c(rep(0.0, nTSpY), 1.0) ## ----------------------------------------------------------------------------- simul_params <- updateReproSexProb(simul_params, repro_sex_probs) simul_params@Pathogen ## ----------------------------------------------------------------------------- basic_patho_param$sex_propagule_release_mean = 1 basic_patho_param$sex_propagule_viability_limit = 5 simul_params <- setPathogen(simul_params, basic_patho_param) ## ----------------------------------------------------------------------------- basic_patho_param$clonal_propagule_gradual_release = TRUE ## clonal propagules are progressively ## released during the next cropping season basic_patho_param$clonal_propagule_gradual_release = FALSE ## clonal propagules are released at ## the first day of the next cropping season ## ----------------------------------------------------------------------------- disp_patho <- loadDispersalPathogen(id = 1) ## ----------------------------------------------------------------------------- disp_patho_clonal <- disp_patho[[1]] disp_patho_sex <- disp_patho[[2]] head(disp_patho_clonal) head(disp_patho_sex) ## ----------------------------------------------------------------------------- disp_patho_clonal <- disp_patho[[1]] disp_patho_sex <- disp_patho[[1]] head(disp_patho_clonal) head(disp_patho_sex) ## ----------------------------------------------------------------------------- simul_params <- setDispersalPathogen(simul_params, disp_patho_clonal, disp_patho_sex) ## ----------------------------------------------------------------------------- # Resistance genes gene1 <- loadGene(name = "gene 1", type = "majorGene") gene2 <- loadGene(name = "gene 2", type = "QTL") #gene2$recombination_sd <- 0.8 gene2$Nlevels_aggressiveness <- 3 genes <- data.frame(rbind(gene1, gene2), stringsAsFactors = FALSE) ## ----------------------------------------------------------------------------- # Cultivars cultivar1 <- loadCultivar(name = "Susceptible", type = "wheat") cultivar2 <- loadCultivar(name = "Resistant1", type = "wheat") cultivar3 <- loadCultivar(name = "Resistant2", type = "wheat") cultivars <- data.frame(rbind(cultivar1, cultivar2, cultivar3) , stringsAsFactors = FALSE) # Allocating genes to cultivars simul_params <- setGenes(simul_params, dfGenes = genes) simul_params <- setCultivars(simul_params, dfCultivars = cultivars) simul_params <- allocateCultivarGenes(simul_params , cultivarName = "Resistant1" , listGenesNames = c("gene 1")) simul_params <- allocateCultivarGenes(simul_params , cultivarName = "Resistant2" , listGenesNames = c("gene 2")) # Allocating cultivars to croptypes croptypes <- loadCroptypes(simul_params, names = c("Susceptible crop" , "Resistant crop 1" , "Resistant crop 2")) croptypes <- allocateCroptypeCultivars(croptypes , croptypeName = "Susceptible crop" , cultivarsInCroptype = "Susceptible") croptypes <- allocateCroptypeCultivars(croptypes , croptypeName = "Resistant crop 1" , cultivarsInCroptype = "Resistant1") croptypes <- allocateCroptypeCultivars(croptypes , croptypeName = "Resistant crop 2" , cultivarsInCroptype = "Resistant2") simul_params <- setCroptypes(simul_params, dfCroptypes = croptypes) # Allocating croptypes to fields of the landscape rotation_sequence <- croptypes$croptypeID ## No rotation -> 1 rotation_sequence element rotation_period <- 0 # number of years before rotation of the landscape prop <- c(1/3,1/3,1/3) # proportion (in surface) of each croptype aggreg <- 0 # level of spatial aggregation simul_params <- allocateLandscapeCroptypes(simul_params , rotation_period = rotation_period , rotation_sequence = rotation_sequence , prop = prop , aggreg = aggreg , graphic = FALSE) ## Inoculum simul_params <- setInoculum(simul_params, 5e-4) # Choosing output variables outputlist <- loadOutputs(epid_outputs = "all", evol_outputs = "all") simul_params <- setOutputs(simul_params, outputlist) ## ----eval=FALSE--------------------------------------------------------------- # checkSimulParams(simul_params) # runSimul(simul_params, graphic = TRUE, videoMP4 = FALSE) ## ----include=FALSE------------------------------------------------------------ system(paste("rm -rf ", simul_params@OutputDir))