#install.packages("~/Dropbox/code/sodi/", type="source", repos=NULL)
library(sodi)
library(multicore)
library(doMC)
registerDoMC(cores=2)
parms <- list(
K=10000, #Carrying capacity
bbox = c(0,sqrt(10000),0,sqrt(10000)), #Area dimensions
n0 = 10000, #Initial population
infect0=1, #Number of infected individuals at start
stages0=rep(1,10000), #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
lamda_ex = seq(0, 0, length.out=101), #Sequence of external force of infection. Must be same length as times to report.
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(4, 4), #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
)
START=Sys.time()
sodi <-run_sodi(parms, name="test", reps=10, progress=TRUE, parallel=TRUE)
saveRDS(sodi, "multitest")
STOP=Sys.time()
STOP-START
#
# max(sodi$Infections)
#
# library(manipulate)
# manipulate(sodi_spatialplot(sodi, TIME), TIME = slider(0, tail(parms$times, 1), step=1))
# manipulate(sodi_infectionsplot(sodi, TIME), TIME=slider(0,tail(parms$times,1),1, step=1))
# manipulate(sodi_infectionsdensplot(sodi, TIME), TIME=slider(0,tail(parms$times,1),1, step=1))
#
# sodi_SItimepolot(sodi)
#
# #Rprof("out.prof", line.profiling=TRUE)
# C_SI = CSI(sodi, progress="time", n.quantiles=6)
# #Rprof(NULL)
#
# manipulate(CSI_plot(C_SI, TIME), TIME=slider(0,tail(parms$times,1),0, step=1))
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