library(sodi)
parms0 <- list(
K=100, #Carrying capacity
bbox = c(0,sqrt(100),0,sqrt(100)), #Area dimensions
n0 = 100, #Initial population
infect0=1, #Number of infected individuals at start
stages0=rep(1,100), #Distribution of size classes
dispersalfn = 3, #disease dispersal: 1-exp, 2-fattail, 3-normal,0 for no spatial component
seedshadow = 0, #dispersal kernel for reproduction, if 0, random location
sp_names = c("Tanoak"), #vector of species names
sp_stages = c(2), #vector of the number of size classes for each species
m = c(1, 1), #dispersal parameter
seedm = c(1,1), #dispersal parameter for reproduction
times = seq(0,100,1), #Times to report. If a single number, the max time, and all events will be recorded
f = c(0.01, 0.01), #Fecundity parameter
g = c(0.1, 0), #Growth rates
d = c(0.005, 0.005), #Death rates
r = c(0.5, 0.5), #Resprout probability at death from disease
alpha = c(0.005, 0.005), #Increase in death rate per infection
lamda = c(0.3, 0.3), #Per-stage contact rate.
beta = c(1, 1), #Probability of acquiring disease when contacted
mu = c(0.05, 0.05), #Per-infection recovery rate
xi = c(1, 1), #Fecundity reduction minus one per infection
omega = c(1, 1), #Competitive coefficient
max_inf = c(1, 1), #Maximum number of infections per plant. Set to 1 for S/I model.
beta_meth = 0 #Maximum infection method. Zero for none, 1 for step function, 2 for decreasing probability
)
test0 <- run_sodi(parms0)
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