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RNL_new trans model_with DEB_1.6.1_olve.R
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# RNL_new trans model_with DEB_1.6.1_olve
#16-6-16
# changed all instances of Min-T_b and Max-T_b to T_opt_lower and T_opt_upper to relfect changes in Netlogo (v6.1.1_two strategies)
#29-1-16
# created sim count (sc) and function to replace results with most recent results of sim run. use to have access to all previous sim runs. Used for getting mean results from multiple sims.
# added results, spdf, homerange, and NL plots to write results loop
#14-1-15
# added days to turtle homerange spdf to plot movement paths by day
# added wetmass (V_pres, wetfood, wetgonad, wetstorage) NL plotting function in DEB loop
# updated DEB loop to run on 2-min time steps
# updated initial debout variables in loop to user friendly values
# added gutfull and gutthresh pars within DEB loop to update feeding behav (decision-making part in NL)
#6-1-15
# defined gutfull and X_food pars prior to sim loop (also fixes error of not recognising gutfull in sim loop)
# added V_pres, wetgonad, wetstorage, and wetfood from debout to results output
#30-12-15 / RNL_new trans model_with DEB_1.6.1_olve
# added plot function to compare gutfill 75% and 100%
# updated reserve level in loop with 'X_food' and 'actfeed' vars
# updated mass var in NL plot output file name
#24-12-15 modularised with NicheMapR functions
# 15-6-15
# Added hr<-4*emis*sigma*((Tc+Trad)/2+273)^3 # radiation resistance (Line 270)
#22-5-15
# updated with new DEB model parameters ... still needs Mike to check discrepancies against his params
#11-5-15 (v.1.6)
# Added ctminthresh parameter to keep turtle alive when under VTMIN (12 hours)
# Added plot export function from NL.
#30-4-15
# Updated movement path plot functions to accomodate for new NL spatial plot output in NL model.
# Movement path plots accept dynamic month input-- sep, nov, dec, etc.
#25-4-15
# Fixed NLGetAgentSet error and homerange plot error (changed 'die' in Soft foraging model (NL))
# 30-3-15
# Added home range polygon plotting function
# Added plotting code for new monthly simulations
#23-3-15
# Added lower and upper activity ranges (NL_T_opt_l, NL_T_opt_u)
# Added procedure for plotting per simulation month
#2-12-14
# new analytical transient model (one lump trans)
# TO DO
# Confirm if new VTMAX of 51 C works for month of November
# Feedcount in NL doesn't match 'NLfoodcount', ........ under progress
# Need to change q to something other than 0?
# 27-11-14
# WORKING VERSION
# X_food variable changed to X_food<-NLReport("[energy-gain] of turtle 0]")
# DEB loop now runs on one NL hour
# 3-10-14
# Uses simulation part from RNL_new trans model_with DEB.R, but with the following:
# - NLCommand("set T_b precision", Tb, "2") # Updating Tb
# - acthr<-NLGetAgentSet("in-food?","turtles", as.data.frame=T) ; acthr<-as.numeric(acthr) # Reports true if turtle is in food. For cum. feeding bouts: acthr<- NLReport("feedcount") (# hours of activity. This would change with input from IBM)
# - X_food<-NLCommand("ask turtle 0 [set energy-gain Low-food-gain]") # sets energy intake from feeding. (changes with input from IBM)
# - Reports reserve-level
# 1-10-14
# Now opens NL version 5.1.0
# Removed f==1 from 'Regulates X_food dynamics' loop (Line 1116)
# 16-9-14
# Tb updated after DEB simulation
# acthr reports when turtle in food patch
# Feeding dynamics updates with movement (: 1098)
#12-9-14
# NL reserve level updated in NL setup procedure (:634)
# X_food updates with NL "[handle-food]"" procedure (:695)
# install.packages(NicheMapR)
# library(NicheMapR) # ultimately you'll install the package, but for now just source them directly
setwd("/Users/malishev/Documents/Melbourne Uni/Programs/Sleepy IBM")
source('DEB.R')
source('onelump_varenv.R')
setwd("/Users/malishev/Documents/Melbourne Uni/Programs/Sleepy IBM")
# read in microclimate data
tzone<-paste("Etc/GMT-",10,sep="")
metout<-read.csv('metout.csv')
soil<-read.csv('soil.csv')
shadmet<-read.csv('shadmet.csv')
shadsoil<-read.csv('shadsoil.csv')
micro_sun_all<-cbind(metout[,2:5],metout[,9],metout[,11],metout[,14:16])
colnames(micro_sun_all)<-c('dates','JULDAY','TIME','TALOC','VLOC','TS','ZEN','SOLR','TSKYC')
micro_shd_all<-cbind(metout[,2],shadmet[,2:4],shadmet[,8],shadmet[,10],shadmet[,13:15])
colnames(micro_shd_all)<-c('dates','JULDAY','TIME','TALOC','VLOC','TS','ZEN','SOLR','TSKYC')
# choose a day(s) to simulate
daystart<-paste('09/09/05',sep="") # yy/mm/dd
dayfin<-paste('10/12/31',sep="") # yy/mm/dd
micro_sun<-subset(micro_sun_all, format(as.POSIXlt(micro_sun_all$dates), "%y/%m/%d")>=daystart & format(as.POSIXlt(micro_sun_all$dates), "%y/%m/%d")<=dayfin)
micro_shd<-subset(micro_shd_all, format(as.POSIXlt(micro_shd_all$dates), "%y/%m/%d")>=daystart & format(as.POSIXlt(micro_shd_all$dates), "%y/%m/%d")<=dayfin)
days<-as.numeric(as.POSIXlt(dayfin)-as.POSIXlt(daystart))
# create time vectors
time<-seq(0,(days+1)*60*24,60) #60 minute intervals from microclimate output
time<-time[-1]
times2<-seq(0,(days+1)*60*24,2) #two minute intervals for prediction
time<-time*60 # minutes to seconds
times2<-times2*60 # minutes to seconds
# apply interpolation functions
velfun<- approxfun(time, micro_sun[,5], rule = 2)
Zenfun<- approxfun(time, micro_sun[,7], rule = 2)
Qsolfun_sun<- approxfun(time, micro_sun[,8], rule = 2)
Tradfun_sun<- approxfun(time, rowMeans(cbind(micro_sun[,6],micro_sun[,9])), rule = 2)
Tairfun_sun<- approxfun(time, micro_sun[,4], rule = 2)
Qsolfun_shd<- approxfun(time, micro_shd[,8]*.1, rule = 2)
Tradfun_shd<- approxfun(time, rowMeans(cbind(micro_shd[,6],micro_shd[,9])), rule = 2)
Tairfun_shd<- approxfun(time, micro_shd[,4], rule = 2)
VTMIN<- 26 # from Bundey field site (2-9-14)
VTMAX<- 35 # from max(results$Tb)
# ***************** end TRANSIENT MODEL SETUP ***************
# ***********************************************************
# initial setup complete, now run the model for a particular 2 min interval
# **************************************************************************************************************
# ***************************************** start NETLOGO SIMULATION ******************************************
# ****************************************** open NETLOGO *****************************************
# install.packages(c('RNetLogo','adehabitatHR','sp'))
library(RNetLogo); library(adehabitatHR); library(sp)
library(rJava) # run rJava?
nl.path<-"/Users/malishev/Documents/Melbourne Uni/Programs/NetLogo 5.3.1/"
#nl.path<-"/Users/malishev/Documents/Melbourne Uni/Programs/NetLogo 5.3.1/app" # for running in El Capitan
NLStart(nl.path)
model.path<-"/Users/malishev/Documents/Melbourne Uni/Programs/Sleepy IBM/Sleepy IBM_v.6.1.nlogo"
NLLoadModel(model.path)
# ****************************************** setup NETLOGO MODEL **********************************
# update initial conditions for DEB model ........ under progress
E_m<-32*7.997/0.886/0.065 #p_M*z/kap/v
E_pres_init<-E_m
V_pres_init<-(7.9967^3)*0.85
E_H_init<-1.865e+05
acthr = 1
Tb_init = 20
E_sm<-1116 # J cm^3 of gut #KearSimpRaubKooij FuncEcol 2013 (Cunningham's skink)
gutfull<-1
Es_pres_init = (E_sm*gutfull)*V_pres_init
X_food<-3000
debout<-DEB(E_pres=E_pres_init, V_pres=V_pres_init, E_H_pres=E_H_init, acthr = acthr, breeding = 1, Es_pres = Es_pres_init, E_sm = E_sm)
V_pres<-debout[2]
wetgonad<-debout[19]
wetstorage<-debout[20]
wetfood<-debout[21]
ctminthresh<-120000
month<-"sep"
Tairfun<-Tairfun_shd
Tc_init<-Tairfun(1)+0.1 # Initial core temperature
mass<-800 # Weight in grams
NL_shade<-1000 # Shade patches
NL_food<-100 # Food patches (*10)
NL_days<-30 # No. of days simulated
NL_T_b<-Tc_init # Initial T_b
NL_T_b_min<-VTMIN # Min foraging T_b
NL_T_b_max<-VTMAX # Max foraging T_b
NL_ctminthresh<-ctminthresh # No. of consecutive hours below CTmin that leads to death
NL_reserve<-E_m # Initial reserve density
NL_max_reserve<-E_m # Maximum reserve level
NL_maint<-0 # Maintenance cost
NL_move<-0 # Movement cost
NL_zen<-Zenfun(1*60*60) # Zenith angle
NL_gutthresh<-0.75
sc<-25 # sim count for automating writing of each sim results to file (set before NL loop)
for (i in 1:sc){ # start sc sim loop
NLCommand("set Shade-patches",NL_shade,"set Food-patches",NL_food,"set No.-of-days",NL_days,"set T_b precision",
NL_T_b, "2","set T_opt_lower precision", NL_T_b_min, "2","set T_opt_upper precision", NL_T_b_max, "2",
"setup", "set reserve-level", NL_reserve, "set Maximum-reserve", NL_max_reserve, "set Maintenance-cost", NL_maint,
"set Movement-cost", NL_move, "set zenith", NL_zen, "set ctminthresh", NL_ctminthresh,
"set gutthresh", NL_gutthresh, 'set gutfull', gutfull, 'set V_pres precision', V_pres, "5", 'set wetstorage precision', wetstorage, "5", 'set wetfood precision', wetfood, "5", 'set wetgonad precision', wetgonad, "5")
NL_ticks<-NL_days / (2 / 60 / 24) # No. of NL ticks (measurement of days)
NL_T_opt_l<-NLReport("[T_opt_lower] of turtle 0")
NL_T_opt_u<-NLReport("[T_opt_upper] of turtle 0")
# data frame setup for homerange polygon
turtles<-data.frame() # make an empty data frame
NLReport("[X] of turtle 0"); NLReport("[Y] of turtle 0")
who<-NLReport("[who] of turtle 0")
# **********************************************************
# ******************** start NETLOGO SIMULATION ***********
debcall<-0 # check for first call to DEB
stepcount<-0 # DEB model step count
for (i in 1:NL_ticks){
stepcount<-stepcount+1
NLDoCommand(1, "go")
######### Reporting presence of shade
#if (NLReport("any? turtles")){
shade<-NLGetAgentSet("in-shade?","turtles", as.data.frame=T); shade<-as.numeric(shade) # returns an agentset of whether turtle is currently on shade patch
#food<-NLGetAgentSet("in-food?","turtles", as.data.frame=T) ; food<-as.numeric(food)
#}
# choose sun or shade
tick<-i
times3<-c(times2[tick],times2[tick+1])
if(shade==0){
Qsolfun<-Qsolfun_sun
Tradfun<-Tradfun_sun
Tairfun<-Tairfun_sun
}else{
Qsolfun<-Qsolfun_shd
Tradfun<-Tradfun_shd
Tairfun<-Tairfun_shd
}
if(i==1){
Tc_init<-Tairfun(1)+0.1 #initial core temperature
#Zenf<-Zenf(1*60*60) # initial zenith angle at 1 a.m (?)
}
# ----------------------------------- 2-12-14 new one_lump_trans params
Qsol<-Qsolfun(mean(times3)); Qsol
vel<-velfun(mean(times3)) ;vel
Tair<-Tairfun(mean(times3));Tair
Trad<-Tradfun(mean(times3)); Trad
Zen<-Zenfun(mean(times3)); Zen
# calc Tb params at 2 mins interval
Tbs<-onelump_varenv(t=120,time=times3[2],Tc_init=Tc_init,thresh = 30, AMASS = mass, lometry = 3, Tairf=Tairfun,Tradf=Tradfun,velf=velfun,Qsolf=Qsolfun,Zenf=Zenfun)
Tb<-Tbs$Tc
rate<-Tbs$dTc
Tc_init<-Tb
NLCommand("set T_b precision", Tb, "2") # Updating Tb
NLCommand("set zenith", Zenfun(i*60*60)) # Updating zenith
# time spent below VTMIN
ctminhours<-NLReport("[ctmincount] of turtle 0") * 2/60 # ticks to hours
if (ctminhours == NL_ctminthresh) {NLCommand("ask turtle 0 [stop]")}
# ******************** start DEB SIMULATION ***************
if(stepcount==1) { # run DEB loop every time step (2 mins)
stepcount<-0
actfeed<-NLGetAgentSet("in-food?","turtles", as.data.frame=T); actfeed<-as.numeric(actfeed) # Reports true if turtle is in food.
n<-1 # time steps
step<-2/1440 # step size (2 mins). For hourly: 1/24
if(Tbs$Tc>=VTMIN & Tbs$Tc<=VTMAX & Zen!=90 & gutfull<=NL_gutthresh){
acthr=1
if(actfeed==1){ # if in food patch
X_food<-NLReport("[energy-gain] of turtle 0") # report joules intake
}
}else{
X_food = 0
acthr=0
}
if(debcall==0){
# initialise
debout<-matrix(data = 0, nrow = n, ncol = 26)
deb.names<-c("E_pres","V_pres","E_H_pres","q_pres","hs_pres","surviv_pres","Es_pres","cumrepro","cumbatch","p_B_past","O2FLUX","CO2FLUX","MLO2","GH2OMET","DEBQMET","DRYFOOD","FAECES","NWASTE","wetgonad","wetstorage","wetfood","wetmass","gutfreemass","gutfull","fecundity","clutches")
colnames(debout)<-deb.names
# initial conditions
debout<-DEB(E_pres=E_pres_init, V_pres=V_pres_init, E_H_pres=E_H_init, acthr = acthr, Tb = Tb_init, breeding = 1, Es_pres = Es_pres_init, E_sm = E_sm, step = step)
debcall<-1
}else{
debout<-DEB(X=X_food,acthr = acthr, Tb = Tbs$Tc, breeding = 1, step = step,E_sm = E_sm, E_pres=debout[1],V_pres=debout[2],E_H_pres=debout[3],q_pres=debout[4],hs_pres=debout[5],surviv_pres=debout[6],Es_pres=debout[7],cumrepro=debout[8],cumbatch=debout[9],p_B_past=debout[10])
}
mass<-debout[22]
gutfull<-debout[24]
NL_reserve<-debout[1]
V_pres<-debout[2]
wetgonad<-debout[19]
wetstorage<-debout[20]
wetfood<-debout[21]
#update NL wetmass properties
NLCommand("set V_pres precision", V_pres, "5")
NLDoCommand("plot xcor ycor")
NLCommand("set wetgonad precision", wetgonad, "5")
NLDoCommand("plot xcor ycor")
NLCommand("set wetstorage precision", wetstorage, "5")
NLDoCommand("plot xcor ycor")
NLCommand("set wetfood precision", wetfood, "5")
NLDoCommand("plot xcor ycor")
} # end DEB loop
NLCommand("set reserve-level", NL_reserve) # Updating reserve
NLCommand("set gutfull", debout[24])
# ******************** end DEB SIMULATION ******************
# generate results, with V_pres, wetgonad, wetstorage, and wetfood from debout
if(i==1){
results<-cbind(tick,Tb,rate,shade,V_pres,wetgonad,wetstorage,wetfood,NL_reserve)
}else{
results<-rbind(results,c(tick,Tb,rate,shade,V_pres,wetgonad,wetstorage,wetfood,NL_reserve))
}
results<-as.data.frame(results)
# generate data frames for homerange polygon
if (tick == NL_ticks - 1){
X<-NLReport("[X] of turtle 0"); head(X)
Y<-NLReport("[Y] of turtle 0"); head(Y)
turtles<-data.frame(X,Y)
who1<-rep(who,NL_ticks); who # who1<-rep(who,NL_ticks - 1); who
turtledays<-rep(1:NL_days,length.out=NL_ticks,each=720)
turtle<-data.frame(ID = who1,days=turtledays)
turtles<-cbind(turtles,turtle)
}
} # end NL loop ###########
# get hr data
spdf<-SpatialPointsDataFrame(turtles[1:2], turtles[3]) # creates a spatial points data frame (adehabitatHR package)
homerange<-mcp(spdf,percent=100)
# writing new results
if (exists("results")){ #if results exist
sc<-sc-1
nam <- paste("results", sc, sep = "") # generate new name with added sc count
rass<-assign(nam,results) #assign new name to results. call 'results1, results2 ... resultsN'
namh <- paste("turtles", sc, sep = "") #generate new name with added sc count
rassh<-assign(namh,turtles) #assign new name to results. call 'results1, results2 ... resultsN'
#nams <- paste("spdf", sc, sep = "")
#rasss<-assign(nams,spdf)
#namhr <- paste("homerange", sc, sep = "")
#rasshr<-assign(namhr,homerange)
# write each result for each sim to file dir getwd()
for (i in rass){
write.table(results,file=paste("C:/NicheMapR_Working/projects/sleepy_ibm_transient/",nam,".R",sep=""))
}
for (i in rassh){
write.table(turtles,file=paste("C:/NicheMapR_Working/projects/sleepy_ibm_transient/",namh,".R",sep=""))
}
#output NL plots
month<-"sep"
#temp plot
tfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_",sc,"_temp",sep="")
NLCommand(paste("export-plot \"Body temperature (T_b)\" \"C:/NicheMapR_Working/projects/sleepy_ibm_transient/",tfh,".csv\"",sep=""))
#activity budget
afh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_",sc,"_act","",sep="");afh
NLCommand(paste("export-plot \"Global time budget\" \"C:/NicheMapR_Working/projects/sleepy_ibm_transient/",afh,".csv\"",sep=""))
#text output
xfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_",sc,"_txt",sep="");xfh
NLCommand(paste("export-output \"C:/NicheMapR_Working/projects/sleepy_ibm_transient/",xfh,".csv\"",sep=""))
#gut level
gfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_",sc,"_gut","",sep="");gfh
NLCommand(paste("export-plot \"Gutfull\" \"C:/NicheMapR_Working/projects/sleepy_ibm_transient",gfh,".csv\"",sep=""))
#wet mass
mfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_",sc,"_wetmass","",sep="");mfh
NLCommand(paste("export-plot \"Total wetmass plot\" \"C:/NicheMapR_Working/projects/sleepy_ibm_transient",mfh,".csv\"",sep=""))
#for (i in rasss){
# write.table(spdf,file=paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Resubmission/Sims/Home ranges/",nams,".R",sep=""))
# }
#for (i in rasshr){
# write.table(homerange,file=paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Resubmission/Sims/Home ranges/",namhr,".R",sep=""))
# }
}
} # end sc sim loop ########
#*********************** end NETLOGO SIMULATION ****************************
#***************************************************************************
results<-as.data.frame(results);results7<-as.data.frame(results7)
par(mfrow=c(1,1))
# plotting debout results
plot(results$V_pres,type='h',ylim=c(0,max(results$V_pres)))
with(results,points(wetstorage,type='h',col='light blue'))
with(results,points(wetfood,type='h',col='red'))
with(results,points(wetgonad,type='h',col='green'))
with(results,points(NL_reserve,type='h',col='orange'))
plot(results$NL_reserve,type='h',col='orange')
plot(results7$V_pres,type='l',ylim=c(0,max(results7$V_pres)))
with(results7,points(wetstorage,type='l',col='light blue'))
with(results7,points(wetfood,type='l',col='red'))
with(results7,points(wetgonad,type='h',col='green'))
with(results7,points(NL_reserve,type='h',col='red'))
plot(results7$NL_reserve,type='l',col='orange')
# compare Tb for 75% and 100% gutfull
plot(results7$Tb,col='black',las=1,type='l',
xaxt='n',
xlab="Days",
ylab='Tb',
main = paste('Tb with 75% (red) and 100% (black) gutfull par from ',daystart,' for ',NL_days,' days',sep=''),
)
with(results7,points(Tb,col='red', type='l'))
axis(1,at=c(0,(length(results$Tb)/2),length(results$Tb)),labels=c(0,NL_days/2,NL_days))
# ---------------------- home range plots
spdf<-SpatialPointsDataFrame(turtles[1:2], turtles[3]) # creates a spatial points data frame (adehabitatHR package)
homerange<-mcp(spdf,percent=100)
# change this with each sim
hr7<-homerange
hrpath7<-spdf
# original code. NB: using min/maxpcors doesn't work for exporting plot to pdf or jpeg
minpxcor<-NLReport("min-pxcor");maxpxcor<-NLReport("max-pxcor")
minpycor<-NLReport("min-pycor");maxpycor<-NLReport("max-pycor")
# plot 75% and 100% gutfull HRs
colvec = adjustcolor(c("black"), alpha = 0.5)
plot(hr7,lty=1,bty="o",pch=21,col=colvec, xlim=c(minpxcor,maxpxcor),ylim=c(minpycor,maxpycor),axes=F)
plot(hrpath7,pch=3,col=turtles$days,add=T)
colvec = adjustcolor(c("red"), alpha = 0.5)
plot(hr7,lty=1,bty="o",col=colvec,add=T)
plot(hrpath7,pch=3,col=turtles$days,add=T)
# use if axes = F
realaxis<-c(minpxcor*2,minpxcor,0,maxpxcor,maxpxcor*2)
axis(1,at=c(minpxcor,minpxcor/2,0,maxpxcor/2,maxpxcor),labels=realaxis)
axis(2,at=c(minpycor,minpycor/2,0,maxpycor/2,maxpycor),labels=realaxis)
text(maxpxcor/2,minpycor/2,paste("100% area = \n",hr$area,sep=""))# hr
text(minpxcor/2,minpycor,paste("75% area = \n",hr7$area,sep=""))# hr7
par(new=T); plot(0, type="n",xlab="X",ylab="Y",
main=paste('Homerange for 75% gut threshold for ',NL_days,' days from ',daystart,sep=''),
main=paste('Red=75% gutfull , black=100% gutfull for ',NL_days,' days from ',daystart,sep=''),
axes=F)
box(which="plot")
# summary stats for homerange sizes
summary(turtles)
max(turtles$X) - min(turtles$X) # width of HR
max(turtles$Y) - min(turtles$Y) # height of HR
# diff in HR
diffhr<-hr-hr7; diffhr
plot(diffhr,lty=1,bty='o',col=colvec_h)
# ------------------------ export plots from NL --------------------------
month<-"sep"
#dir = /Applications/Programs/NetLogo 5.0.5/Soft foraging model/Simulations
#spatial plot
sfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_move","",sep="");sfh
#NLCommand("export-plot \"Spatial coordinates of transition between activity states\" \"Simulations/spatialplot.csv\"")
NLCommand(paste("export-plot \"Spatial coordinates of transition between activity states\" \"Simulations/",sfh,".csv\"",sep=""))
# home range
hfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_homerange","",sep="");hfh
# reserve plot
rfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_reserve","",sep="");rfh
#NLCommand("export-plot \"Reserve level and starvation reserve over time\" \"Simulations/reserveplot.csv\"")
NLCommand(paste("export-plot \"Reserve level and starvation reserve over time\" \"Simulations/",rfh,".csv\"",sep=""))
#temp plot
tfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_temp",sep="");tfh
#NLCommand("export-plot \"Body temperature (T_b)\" \"Simulations/tempplot.csv\"")
NLCommand(paste("export-plot \"Body temperature (T_b)\" \"Simulations/",tfh,".csv\"",sep=""))
# activity budget
afh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_act","",sep="");afh
#NLCommand("export-plot \"Global time budget\" \"Simulations/activitybudget.csv\"")
NLCommand(paste("export-plot \"Global time budget\" \"Simulations/",afh,".csv\"",sep=""))
# world view
NLCommand("export-view \"Simulations/worldview.png\"")
# text output
xfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_txt",sep="");xfh
NLCommand(paste("export-output \"Simulations/",xfh,".csv\"",sep=""))
# gut level
gfh<-paste(month,NL_days,round(mass,0),NL_shade,NL_food*10,"_gut","",sep="");gfh
#NLCommand("export-plot \"Global time budget\" \"Simulations/activitybudget.csv\"")
NLCommand(paste("export-plot \"Gutfull\" \"Simulations/",gfh,".csv\"",sep=""))
#-----------------------------------------------------------
#------------------------ plot NETLOGO RESULTS -------------
#-----------------------------------------------------------
###
### add export function that saves plot as e.g. "sep15"
###
#fh<-paste(daystart,NL_days,mass,NL_shade,NL_food,sep="")
ttl<-paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")
pdf(paste("/Applications/Programs/NetLogo 5.0.5/NL_transient_outputs/",fh,".pdf",sep=""),width=15,height=15,paper="a4r",title=ttl)
par(mfrow=c(1,1)) # new plot window with x rows and y columns, fills by rows
par(mar=c(5,6,5,5))
#------------------ regular results plot ------------------------
#NL_shade<-NLReport("Shade-patches"); NL_food<-NLReport("Food-patches")
results<-as.data.frame(results)
ticktime<-results$tick * 2 / 60 / 24 # convert to real days
# Plot with title
# with(results,plot(Tb~ticktime,type='l',las=1,xlab="Days",ylab = expression(paste("Body temperature (" * degree,"C)")),main=paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")))
with(results,plot(Tb~ticktime,type='l',las=1,xlab="Days",ylab = expression(paste("Body temperature (" * degree,"C)"))))
shade.results<-results[results$shade %in% 1,] ; head(shade.results)
sticktime<-shade.results$tick * 2 / 60 / 24 # convert to real days
shade.results_Tb<-results[results$shade %in% 1,'Tb'] ; head(shade.results_Tb)
#with(results,points(shade.results$Tb~shade.results$tick, type='p', col="blue"))
with(results,points(shade.results$Tb~sticktime, type='p', col="blue"))
#with(results,points(shade*20~tick,type='p',col="red"))
abline(h = c(NL_T_opt_l,NL_T_opt_u), col = "red", lty = 3)
text(0,28, "Activity range", col = "red", adj = c(.3, 1))
# dev.off() # use only with jpeg function above
hist(shade.results$Tb, main="Proportion of Tb when in shade", xlab="Tb (C) when in shade")
plot(shade.results$tick,shade.results$Tb, col="blue")
# ------------------ Tb plot per month ------------------------
if (exists("results")){
newones<-results
}
# change this to reflect new data period and save as dataframe
dec15<-newones
ticktime<-newones$tick * 2 / 60 / 24 # convert to real days
# define shade data frame
shade.newones<-newones[newones$shade %in% 1,]
shade.newones_Tb<-newones[newones$shade %in% 1,'Tb'] ; head(shade.newones_Tb)
sticktime<-shade.newones$tick * 2 / 60 / 24 # convert to real days
#sep15: lty=3
#nov1: lty=2
#dec15: lty=1
month<-"dec15"
par(pty="m")
fh<-paste(month,NL_days,mass,NL_shade,NL_food*10,"_2",sep="")
ttl<-paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")
pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Tb plot/",fh,".pdf",sep=""),width=15,height=15,paper="a4r",title=ttl)
#plot.new()
#par(new=T)
# make data points transparent
colvec = adjustcolor(c("red"), alpha = 0.5)
col=colvec[sep15$Tb]
# Plot with title
# with(results,plot(Tb~ticktime,type='l',las=1,xlab="Days",ylab = expression(paste("Body temperature (" * degree,"C)")),main=paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")))
with(newones,plot(Tb~ticktime,type='l',las=1,lwd=1,lty=1,col=colvec,xlim=c(0,NL_days),ylim=c(0,45),xlab="Days",ylab = expression(paste("Body temperature (" * degree,"C)"))))
#with(results,points(shade.results$Tb~shade.results$tick, type='p', col="blue"))
with(newones,points(shade.newones$Tb~sticktime, type='p', col=colvec))
#with(results,points(shade*20~tick,type='p',col="red"))
abline(h = c(NL_T_opt_l,NL_T_opt_u), col = "red", lty = 3)
text(0,28, "Activity range", col = "red", adj = c(.3, 1))
dev.off()
# ------------------ simultaneous simulation plots --------------------
par(mfrow=c(1,1),mar=c(5,6,5,5),pty="m")
month<-"all"
fh<-paste(month,NL_days,mass,NL_shade,NL_food*10,"",sep="");fh
ttl<-paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")
pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Tb plot/",fh,".pdf",sep=""),width=15,height=15,paper="a4r",title=ttl)
#plot.new()
# sep15
# make data points transparent
colvec = adjustcolor(c("black"), alpha = 0.3)
#col=colvec[sep15$Tb]
ticktime<-sep15$tick * (2 / 60 / 24) # convert to real days
sticktime<-shade.sep15$tick * 2 / 60 / 24 # convert to real days
with(sep15,plot(Tb~ticktime,type='l',las=1,lwd=2,lty=1,,col=colvec,xlim=c(0,max(ticktime)),ylim=c(0,45),xlab="",ylab="",axes=F))
shade.sep15<-sep15[sep15$shade %in% 1,] ; head(shade.sep15)
shade.sep15_Tb<-sep15[sep15$shade %in% 1,'Tb'] ; head(shade.sep15_Tb)
#with(results,points(shade.results$Tb~shade.results$tick, type='p', col="blue"))
with(sep15,points(shade.sep15$Tb~sticktime, type='p', col=colvec))
#nov1
colvec = adjustcolor(c("blue"), alpha = 0.3)
ticktime<-nov1$tick * (2 / 60 / 24) # convert to real days
sticktime<-shade.nov1$tick * 2 / 60 / 24 # convert to real days
par(new=T)
with(nov1,plot(Tb~ticktime,type='l',las=1,lwd=2,lty=1,col=colvec,xlim=c(0,max(ticktime)),ylim=c(0,45),xlab="",ylab="",axes=F))
shade.nov1<-nov1[nov1$shade %in% 1,] ; head(shade.nov1)
shade.nov1_Tb<-nov1[nov1$shade %in% 1,'Tb'] ; head(shade.nov1_Tb)
#with(results,points(shade.results$Tb~shade.results$tick, type='p', col="blue"))
with(nov1,points(shade.nov1$Tb~sticktime, type='p', col=colvec))
#dec15
colvec = adjustcolor(c("red"), alpha = 0.3)
ticktime<-dec15$tick * (2 / 60 / 24) # convert to real days
sticktime<-shade.dec15$tick * 2 / 60 / 24 # convert to real days
par(new=T)
with(dec15,plot(Tb~ticktime,type='l',las=1,lwd=2,lty=1,col=colvec,xlim=c(0,max(ticktime)),ylim=c(0,45),xlab="Days",ylab = expression(paste("Body temperature (" * degree,"C)"))))
shade.dec15<-dec15[dec15$shade %in% 1,] ; head(shade.dec15)
shade.dec15_Tb<-nov1[dec15$shade %in% 1,'Tb'] ; head(shade.dec15_Tb)
#with(results,points(shade.results$Tb~shade.results$tick, type='p', col="blue"))
with(dec15,points(shade.dec15$Tb~sticktime, type='p', col=colvec))
abline(h = c(NL_T_opt_l,NL_T_opt_u), col = "red", lty = 3)
text(0,30, "Activity range", col = "red", adj = c(.3, 1))
dev.off() # use only with jpeg function above
hist(shade.results$Tb, main="Proportion of Tb when in shade", xlab="Tb (C) when in shade")
plot(shade.results$tick,shade.results$Tb, col="blue")
# ----------- home range plot ------------------
# get homerange ------------------
#X<-NLReport("[X] of turtle 0"); head(X)
#Y<-NLReport("[Y] of turtle 0"); head(Y)
# turtles<-data.frame(X,Y)
# who1<-rep(who,NL_ticks); who #
#who1<-rep(who,NL_ticks); who
# turtle<-data.frame(ID = who1)
# turtles<-cbind(turtles,turtle)
#
#
# need to make new variable for new spdf (movement paths) ........ under progress
spdf<-SpatialPointsDataFrame(turtles[1:2], turtles[3]) # creates a spatial points data frame (adehabitatHR package)
homerange<-mcp(spdf,percent=100)
# draw-homerange ------------------
#calculate homerange points
temp <- slot(homerange,'polygons')[[which(slot(homerange,'data')$id == who)]]@Polygons[[1]]@coords
tempX<-temp[,1]
tempY<- temp[,2]
#tempXY<-cbind(tempX,tempY); tempXY<-as.list(tempXY)
tempXY<-NLCommand("set tempXY (map [list ?1 ?2]",tempX,tempY, ")" )
# Setting as.list makes no difference
#as.list(tempXY)
# The below command doesn't work yet, so the model calls the NL 'draw-homerange' procedure instead
#NLCommand("set tempX", tempX, "set tempY", tempY, "set tempXY", tempXY)
NLCommand("draw-homerange")
# hatch a turtle to draw the homerange boundary points
NLCommand("ask turtle 0 [hatch-homeranges 1", "hide-turtle","set color red]")
# draw the homerange
NLCommand("foreach tempXY [ask homeranges", "[move-to patch (item 0 ?) (item 1 ?)", "pd]]")
# close the homerange polygon
NLCommand("ask homeranges [let lastpoint first tempXY","move-to patch (item 0 lastpoint) (item 1 lastpoint)","]")
# to save-homerange ---------------
# change this with each sim
sep15_homerange<-homerange
month<-"all"
par(new=T)
par(pty="s")
#save the homerange polygon into a pdf
fh<-paste(month,NL_days,mass,NL_shade,NL_food*10,"_homerange","",sep="");fh
ttl<-paste("From ",daystart," + ",NL_days,"days ;","Weight =",mass,"g ; Shade =", NL_shade,"; Food =", NL_food,"; VTMIN", NL_T_b_min,"C")
#pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Home range polygon/",fh,".pdf",sep=""),width=15,height=15,paper="a4r",title=ttl)
pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Home range polygon/",fh,".pdf",sep=""))
jpeg(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Home range polygon/",fh,".jpeg",sep=""))
# plot polygon
colvec_h = adjustcolor(c("black"), alpha = 0.5)
plot(sep15_homerange,lty=1,bty="o",col=colvec_h,lwd=2,xlim=c(-25,25),ylim=c(-25,25),axes=F)
# plot animal tracks in polygon. NB: col = white. ........ under progress
plot(spdf,col=as.data.frame(spdf)[,1],pch=4,add=T)
# adding 2nd homerange polygon
colvec_h = adjustcolor(c("blue"), alpha = 0.2)
plot(nov1_homerange,lty=1,bty="o",col=colvec_h,lwd=2,xlim=c(-25,25),ylim=c(-25,25),axes=F,add=T)
# plot animal tracks in polygon. NB: col = white......... under progress
plot(spdf,col=as.data.frame(spdf)[,1],pch=4,add=T)
# adding 3rd homerange polygon
colvec_h = adjustcolor(c("red"), alpha = 0.2)
plot(dec15_homerange,lty=1,bty="o",col=colvec_h,lwd=2,xlim=c(-25,25),ylim=c(-25,25),axes=F,add=T)
# plot animal tracks in polygon. NB: col = white......... under progress
plot(spdf,col=as.data.frame(spdf)[,1],pch=4,add=T)
text(-16,5,labels="A",cex=1.5);text(0,5,labels="B",cex=1.5); text(14,5,labels="C",cex=1.5)
# use if axes = F
realaxis<-c("-50","-25","0","25","50")
axis(1,at=c(-25,-12.5,0,12.5,25),labels=realaxis)
axis(2,at=c(-25,-12.5,0,12.5,25),labels=realaxis)
par(new=T); plot(0, type="n",xlab="X",ylab="Y",axes=F)
box(which="plot")
dev.off()
#save a plot of the homerange area level into a pdf
pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Home range polygon/",month,"_homearea",".pdf",sep=""))
plot(mcp.area(spdf,unout='m2'),colpol="blue",main=paste("Homerange polygon for ",NL_days," days with ",NL_shade," shade and ",NL_food," food patches"))
dev.off()
# original code. NB: using min/maxpcors doesn't work for exporting plot to pdf or jpeg
minpxcor<-NLReport("min-pxcor");maxpxcor<-NLReport("max-pxcor")
minpycor<-NLReport("min-pycor");maxpycor<-NLReport("max-pycor")
plot(nov1_homerange,lty=3,lwd=2,xlab="X", ylab="Y", xlim=c(minpxcor,maxpxcor), ylim=c(minpycor,maxpycor), axes=T)
par(new=T); plot(0, type="n",xlab="X coordinates",ylab="Y coordinates",axes=F)
#-----------------------------------------------------------
#------------------------ plot activity budget ------------
#-----------------------------------------------------------
library(data.table)
setwd("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Activity budget/")
sep15_act<-read.csv("sep15/sep15.csv",header=T,sep=",",row.names=NULL,skip=20)
# sep15
names(sep15_act);head(sep15_act)
sfeed<-sep15_act[,1:2]
#setnames(sfeed,"x","X"); setnames(sfeed,"y","Y")
ssearchi<-sep15_act[,5:6]
# trans overlaps searching in 'diffr' plot (diff bw sep and dec activity)
#strans<-sep15_act[,9:10]
srest<-sep15_act[,13:14]
sep15_act<-as.data.frame(sep15_act)
activity_time<-sfeed$x*(2/60/24)
par(mfrow=c(1,1))
par(new=T)
activity<-sfeed
colvec_a = adjustcolor(c("black"), alpha = 1)
plot(activity_time,activity$y,
type="s",
lwd=1,
ylab="",
xlab="",
xlim=c(0,max(activity_time)),
ylim=c(0,5000),
col=colvec_a,
axes=F
)
# use if axes = F
actaxis_time<-c("0","1","2","3","4","5","6","7")
actaxis_freq<-c("0","1000","2000","3000","4000","5000")
axis(1,at=c(0:7),labels=actaxis_time)
axis(2,at=c(0,1000,2000,3000,4000,5000),labels=actaxis_freq)
par(new=T); plot(0, type="n",xlab="Days",ylab="Frequency of activity state",axes=F)
box(which="plot")
# nov1
nov1_act<-read.csv("nov1/nov1.csv",header=T,sep=",",row.names=NULL,skip=20)
nfeed<-nov1_act[,1:2]
nsearchi<-nov1_act[,5:6]
#ntrans<-nov1_act[,9:10]
nrest<-nov1_act[,13:14]
# dec15
dec15_act<-read.csv("dec15/dec15.csv",header=T,sep=",",row.names=NULL,skip=20)
dfeed<-dec15_act[,1:2]
dsearchi<-dec15_act[,5:6]
#dtrans<-dec15_act[,9:10]
drest<-dec15_act[,13:14]
# plot difference between time spent in activity states in early vs late season
par(mfrow=c(1,1),mar=c(5,6,5,5),pty="m")
month<-"diffr"
fh<-paste(month,NL_days,mass,NL_shade,NL_food*10,"_act","",sep="");fh
pdf(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Activity budget/",fh,".pdf",sep=""))
jpeg(paste("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Activity budget/",fh,".jpeg",sep=""))
# plotting order
#rest
#searchi
#feed
par(mfrow=c(1,1),mar=c(5,6,5,5),pty="m")
diffra<-"rest"
diffr<-eval(parse(text=paste("s",diffra,"-","d",diffra,sep="")))
par(new=T)
activity<-diffr
colvec_a = adjustcolor(c("dark green"), alpha = 1)
plot(activity_time,activity$y,
type="s",
lwd=1,
ylab="",
xlab="",
xlim=c(0,7),
ylim=c(-400,400),
col=colvec_a,
axes=F
)
# find y==0 value (pivotal point when animal switches activity) ........ under progress
diffr23<-subset(diffr,subset=srest$x * (2 / 60 / 24)==c(2:3))
diffrz<-subset(diffr23,subset=diffr23$y==0)
# use if axes = F
actaxis_time<-c("0","1","2","3","4","5","6","7")
actaxis_freq<-c("-400","-200","0","200","400")
axis(1,at=c(0:7),labels=actaxis_time,las=1)
axis(2,at=c(-400,-200,0,200,400),labels=actaxis_freq,las=1)
mtext("Days",1,line=3)
mtext("Difference in time spent within activity state",2,line=4)
abline(v=2.41111,col="red",lty=3)
box(which="plot")
dev.off()
#------------- reserve plot
par(mfrow=c(1,1))
#Netlogo outputs
setwd("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Reserve plot")
setwd("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/")
reserve<-read.table("sep157800100100_reserve.csv",header=T,sep=",",row.names=NULL,skip=17)
# change for each sim month
sep15reserve<-reserve
reserve<-reserve[,1:2]
reserve<-as.data.frame(reserve)
reserve$Time<-reserve$x * (2 / 60 / 24)
plot(reserve$Time,reserve$y, main="Reserve level (J)",xlim=c(0,max(reserve$Time)),xlab="Days",ylab="Reserve level (J)", col="red",las=1,type="l")
#-----------------------------------------------------------
#------------------------ plot movement paths --------------
#-----------------------------------------------------------
# get all food and shade patches
foodh <- NLGetAgentSet(c("pxcor","pycor"),
"patches with [pcolor = green]",
as.data.frame=TRUE,
# df.col.names=c("x","y")
)
foodl <- NLGetAgentSet(c("pxcor","pycor"),
"patches with [pcolor = yellow]",
as.data.frame=TRUE,
)
shadep1 <- NLGetAgentSet(c("pxcor","pycor"),
"patches with [pcolor = black]",
as.data.frame=TRUE,
)
shadep2 <- NLGetAgentSet(c("pxcor","pycor"),
"patches with [pcolor = black + 2]",
as.data.frame=TRUE,
)
# remove NA's
foodh<-na.omit(foodh)
foodl<-na.omit(foodl)
shadeall<-rbind(shadep1,shadep2)
foodall<-rbind(foodh,foodl)
#x.minmax <- NLReport("(list min-pxcor max-pxcor)")
#y.minmax <- NLReport("(list min-pycor max-pycor)")
# retrieve turtle location
#liz <- NLGetAgentSet(c("xcor","ycor"),
# "turtles","pd",
# as.data.frame=TRUE,
#)
#par(new=T)
# plot(liz, xlim=x.minmax, ylim=y.minmax,col="red", pch=19)
# ------------ formatting data
setwd("/Users/matthewmalishev/Documents/Manuscripts/Malishev and Kearney/Figures/Simulations/Movement trajectories/")
# -----sep15
spatialplot<-read.table("sep15/sep15.csv",header=T,sep=",",skip=19)
spatialplot<-as.data.frame(spatialplot); head(spatialplot)
names(spatialplot)
# format data
spen_move<-spatialplot[,1:2];head(spen_move)
sfeed_move<-spatialplot[,5:6];head(sfeed_move)
ssearch_move<-spatialplot[,9:10];head(ssearch_move)
srest_move<-spatialplot[,13:14]; head(srest_move)
#round off food and shade data points
sfeed_move<-round(sfeed_move,0)
srest_move<-round(srest_move,0)
# ------nov1
spatialplot<-read.table("nov1/nov1.csv",header=T,sep=",",skip=19)
spatialplot<-as.data.frame(spatialplot); head(spatialplot)
names(spatialplot)
# format data
npen_move<-spatialplot[,1:2];head(npen_move)
nfeed_move<-spatialplot[,5:6];head(nfeed_move)
nsearch_move<-spatialplot[,9:10];head(nsearch_move)
nrest_move<-spatialplot[,13:14]; head(nrest_move)
#round off food and shade data points
nfeed_move<-round(nfeed_move,0)
nrest_move<-round(nrest_move,0)
# -----dec15
spatialplot<-read.table("dec15/dec15.csv",header=T,sep=",",skip=19)
spatialplot<-as.data.frame(spatialplot); head(spatialplot)
names(spatialplot)
# format data
dpen_move<-spatialplot[,1:2];head(dpen_move)
dfeed_move<-spatialplot[,5:6];head(dfeed_move)
dsearch_move<-spatialplot[,9:10];head(dsearch_move)
drest_move<-spatialplot[,13:14]; head(drest_move)
#round off food and shade data points
dfeed_move<-round(dfeed_move,0)
drest_move<-round(drest_move,0)
# remove NA's
sfeed_move<-na.omit(sfeed_move)
#subset feeding data by food patch type (high or low)
green<-subset(spatialplot[,5:7],color.1==55,select=c(x.1,y.1))
green<-green[,1:2]
yellow<-subset(spatialplot[,5:7],color.1==45,select=c(x.1,y.1))
yellow<-yellow[,1:2]
green<-round(green,0) ;yellow<-round(yellow,0)
# ------------------ plotting all food and shade patches
# plot food patches
# colvec_m = adjustcolor(c("yellow"), alpha = 0.8)
plot(foodl, xlim=c(-25,25), ylim=c(-25,25),pch=22,cex=2,col="grey",bg="yellow",xlab="",ylab="",axes=F)
par(new=T)
plot(foodh, xlim=c(-25,25), ylim=c(-25,25),pch=22, cex=2,col="grey",bg="dark green",xlab="",ylab="",axes=F)
par(new=T) #if plotting food patches above
# plot all shade patches
par(new=T)
plot(shadeall, xlim=c(-25,25), ylim=c(-25,25),pch=22, cex=2,col="grey",bg="black",xlab="",ylab="",axes=F)
par(new=T)
# ------------------- plotting movement paths
# change input to reflect simulation month