Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ---- results="hide", message=FALSE-------------------------------------------
library(landsepi)
## ---- results="hide", message="FALSE"-----------------------------------------
simul_params <- createSimulParams(outputDir = getwd())
## -----------------------------------------------------------------------------
simul_params@Seed
simul_params <- setSeed(simul_params, seed = 1)
simul_params@Seed
## -----------------------------------------------------------------------------
simul_params <- setTime(simul_params, Nyears = 6, nTSpY = 120)
simul_params@TimeParam
## -----------------------------------------------------------------------------
basic_patho_param <- loadPathogen(disease = "rust")
basic_patho_param
basic_patho_param <- loadPathogen(disease = "mildew")
basic_patho_param
basic_patho_param <- loadPathogen(disease = "sigatoka")
basic_patho_param
## -----------------------------------------------------------------------------
basic_patho_param <- loadPathogen("rust")
basic_patho_param$infection_rate <- 0.5
basic_patho_param
## -----------------------------------------------------------------------------
basic_patho_param <- list(infection_rate = 0.4
, latent_period_mean = 10
, latent_period_var = 9
, propagule_prod_rate = 3.125
, infectious_period_mean = 24
, infectious_period_var = 105
, survival_prob = 1e-4
, repro_sex_prob = 0
, sigmoid_kappa = 5.333
, sigmoid_sigma = 3
, sigmoid_plateau = 1
, sex_propagule_viability_limit = 1
, sex_propagule_release_mean = 1
, clonal_propagule_gradual_release = 0)
## -----------------------------------------------------------------------------
simul_params <- setPathogen(simul_params, patho_params = basic_patho_param)
simul_params@Pathogen
## -----------------------------------------------------------------------------
simul_params <- setInoculum(simul_params, val = 5e-4)
simul_params@PI0
## -----------------------------------------------------------------------------
landscape <- loadLandscape(id = 1)
length(landscape)
plot(landscape, main = "Landscape structure")
## -----------------------------------------------------------------------------
disp_patho_clonal <- loadDispersalPathogen(id = 1)[[1]]
head(disp_patho_clonal)
length(landscape)^2 == length(disp_patho_clonal)
## -----------------------------------------------------------------------------
simul_params <- setLandscape(simul_params, land = landscape)
simul_params <- setDispersalPathogen(simul_params, disp_patho_clonal)
## -----------------------------------------------------------------------------
cultivar1 <- loadCultivar(name = "Susceptible", type = "growingHost")
cultivar2 <- loadCultivar(name = "Resistant1", type = "growingHost")
cultivar3 <- loadCultivar(name = "Resistant2", type = "growingHost")
cultivar4 <- loadCultivar(name = "Resistant3", type = "nongrowingHost")
cultivar5 <- loadCultivar(name = "Forest", type = "nonCrop")
cultivars <- data.frame(rbind(cultivar1, cultivar2, cultivar3, cultivar4, cultivar5)
, stringsAsFactors = FALSE)
cultivars
## -----------------------------------------------------------------------------
cultivars[cultivars$cultivarName == "Susceptible", "growth_rate"] <- 0.2
cultivars
## -----------------------------------------------------------------------------
cultivars_new <- data.frame(cultivarName = c("Susceptible", "Resistant"),
initial_density = c(0.1, 0.2),
max_density = c(2.0, 3.0),
growth_rate = c(0.1, 0.2),
reproduction_rate = c(0.0, 0.0),
yield_H = c(2.5, 2.0),
yield_L = c(0.0, 0.0),
yield_I = c(0.0, 0.0),
yield_R = c(0.0, 0.0),
planting_cost = c(225, 300),
market_value = c(200, 150),
stringsAsFactors = FALSE)
cultivars_new
## -----------------------------------------------------------------------------
gene1 <- loadGene(name = "MG 1", type = "majorGene")
gene2 <- loadGene(name = "Lr34", type = "APR")
gene3 <- loadGene(name = "gene 3", type = "QTL")
gene4 <- loadGene(name = "nonhost resistance", type = "immunity")
genes <- data.frame(rbind(gene1, gene2, gene3, gene4), stringsAsFactors = FALSE)
genes
## -----------------------------------------------------------------------------
genes[genes$geneName == "MG 1", "mutation_prob"] <- 1e-3
genes
## -----------------------------------------------------------------------------
genes_new <- data.frame(geneName = c("MG1", "MG2"),
efficiency = c(1.0 , 0.8 ),
age_of_activ_mean = c(0.0 , 0.0 ),
age_of_activ_var = c(0.0 , 0.0 ),
mutation_prob = c(1E-7 , 1E-4),
Nlevels_aggressiveness = c(2 , 2 ),
adaptation_cost = c(0.50 , 0.75 ),
tradeoff_strength = c(1.0 , 1.0 ),
target_trait = c("IR" , "LAT"),
recombination_sd = c(1.0,1.0),
stringsAsFactors = FALSE)
genes_new
## -----------------------------------------------------------------------------
simul_params <- setGenes(simul_params, dfGenes = genes)
simul_params <- setCultivars(simul_params, dfCultivars = cultivars)
simul_params@Genes
simul_params@Cultivars
## -----------------------------------------------------------------------------
simul_params <- allocateCultivarGenes(simul_params
, cultivarName = "Resistant1"
, listGenesNames = c("MG 1"))
simul_params <- allocateCultivarGenes(simul_params
, cultivarName = "Resistant2"
, listGenesNames = c("Lr34", "gene 3"))
simul_params <- allocateCultivarGenes(simul_params
, cultivarName = "Resistant3"
, listGenesNames = c("nonhost resistance"))
simul_params@Cultivars
## -----------------------------------------------------------------------------
croptypes <- loadCroptypes(simul_params, names = c("Susceptible crop"
, "Pure resistant crop"
, "Mixture"
, "Other"))
croptypes
## -----------------------------------------------------------------------------
croptypes <- allocateCroptypeCultivars(croptypes
, croptypeName = "Susceptible crop"
, cultivarsInCroptype = "Susceptible")
croptypes <- allocateCroptypeCultivars(croptypes
, croptypeName = "Pure resistant crop"
, cultivarsInCroptype = "Resistant1")
croptypes <- allocateCroptypeCultivars(croptypes
, croptypeName = "Mixture"
, cultivarsInCroptype = c("Resistant2","Resistant3")
, prop = c(0.4, 0.6))
croptypes <- allocateCroptypeCultivars(croptypes
, croptypeName = "Other"
, cultivarsInCroptype = "Forest")
croptypes
## -----------------------------------------------------------------------------
simul_params <- setCroptypes(simul_params, dfCroptypes = croptypes)
simul_params@Croptypes
## -----------------------------------------------------------------------------
croptypes <- data.frame(croptypeID = c(0, 1, 2, 3) ## must start at 0 and match with values from landscape "croptypeID" layer
, croptypeName = c("Susceptible crop"
, "Pure resistant crop"
, "Mixture"
, "Other")
, Susceptible = c(1,0,0 ,0)
, Resistant1 = c(0,1,0 ,0)
, Resistant2 = c(0,0,0.5,0)
, Resistant3 = c(0,0,0.5,0)
, Forest = c(0,0,0 ,1)
, stringsAsFactors = FALSE)
simul_params <- setCroptypes(simul_params, croptypes)
## -----------------------------------------------------------------------------
# croptypeIDs cultivated in each element of the rotation sequence:
rotation_sequence <- list(c(0,1,3), c(0,2,3))
rotation_period <- 2 # number of years before rotation of the landscape
prop <- list(rep(1/3, 3), rep(1/3, 3)) # proportion (in surface) of each croptype
aggreg <-1 # level of spatial aggregation
simul_params <- allocateLandscapeCroptypes(simul_params
, rotation_period = rotation_period
, rotation_sequence = rotation_sequence
, prop = prop
, aggreg = aggreg
, graphic = TRUE)
# plot(simul_params@Landscape)
## -----------------------------------------------------------------------------
treatment <- list(treatment_degradation_rate = 0.1,
treatment_efficiency = 0.8,
treatment_timesteps = seq(1,120,14) ,
treatment_cultivars = c(0),
treatment_cost = 0,
treatment_application_threshold = c(0.0))
simul_params <- setTreatment(simul_params, treatment)
## -----------------------------------------------------------------------------
outputlist <- loadOutputs(epid_outputs = "all", evol_outputs = "all")
outputlist
## -----------------------------------------------------------------------------
audpc100S <- compute_audpc100S("rust", "growingHost", area=1E6)
audpc100S <- compute_audpc100S("mildew", "grapevine", area=1E6)
audpc100S <- compute_audpc100S("sigatoka", "banana", area=1E6, nTSpY=182)
## -----------------------------------------------------------------------------
simul_params <- setOutputs(simul_params, outputlist)
## ---- eval=FALSE--------------------------------------------------------------
# checkSimulParams(simul_params)
# simul_params <- saveDeploymentStrategy(simul_params)
## ---- eval=FALSE--------------------------------------------------------------
# runSimul(simul_params, graphic = TRUE, videoMP4 = FALSE)
## ---- include=FALSE-----------------------------------------------------------
system(paste("rm -rf ", simul_params@OutputDir))
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