TestScripts/moveCov_longer_time.R
In Blevy2/READ-PDB-blevy2-MFS2: Mixed Fishery fleet dynamics simulation tool
#This script is for creating and testing temperature covariate matrices
library(MixFishSim)
#############################################################################################
#Init Sim
#############################################################################################
#OLD VERSION
sim <- init_sim(nrows = 100, ncols = 100, n_years = 20, n_tows_day = 4,
n_days_wk_fished = 5, n_fleets = 2, n_vessels = 20, n_species = 2,
move_freq = 1)
#NEW VERSION that has week breaks for entire simulation and allows no fishing
source("R/init_sim_Bens.R")
sim <- init_sim_Bens(nrows = 100, ncols = 100, n_years = 20, n_tows_day = 4,
n_days_wk_fished = 1, n_fleets = 1, n_vessels = 1, n_species = 2,
move_freq = 1)
#############################################################################################
###Habitat setup
#############################################################################################
source("R/BENS_create_hab.R")
source("R/BENS_plot_habitat.R")
#values settled on from anisotropy and habtest scripts
spp.ctrl = list(
"spp.1" = list('nu' = 1/0.05,
'var' = 1,
'scale' = 2,
'Aniso' = matrix(nc = 2, c(1, -2, 1, 2))),
"spp.2" = list('nu' = 1/0.015,
'var' = 1,
'scale' = 40,
'Aniso' = matrix(nc = 2, c(1.5, -3, 3, 4))),
plot.dist = TRUE,
plot.file = "testfolder"
)
hab <- BENS_create_hab(sim_init = sim,
spp.ctrl = spp.ctrl,
spawn_areas = list(
"spp1" = list(
'area1' = c(40,50,40,50), #of the form c(x1, x2, y1, y2) THESE ARE BOUNDARIES OF MATRIX VALUES
'area2' = c(80,90,60,70) #need to revisit closure areas
),
"spp2" = list(
'area1' = c(50,60,30,40),
'area2' = c(70,90,80,90)
),
spwn_mult = 10,
plot.dist = TRUE,
plot.file = "testfolder" ),
#created this new part defining strata
strata = list( #Form: upper left, upper right, lower left, lower right
"strata1" = c(1,sim$idx[["nrows"]]/2,1,sim$idx[["ncols"]]/2), #of the form c(x1, x2, y1, y2) THESE ARE BOUNDARIES OF STRATA VALUES
"strata2" = c(1,sim$idx[["nrows"]]/2,sim$idx[["ncols"]]/2+1,sim$idx[["ncols"]]),
"strata3" = c(sim$idx[["nrows"]]/2 + 1,sim$idx[["nrows"]], 1 ,sim$idx[["ncols"]]/2),
"strata4" = c(sim$idx[["nrows"]]/2 + 1,sim$idx[["nrows"]],sim$idx[["ncols"]]/2 +1 , sim$idx[["ncols"]])
)
)
#old version
plot_habitat(hab$hab)
## Plot the adjusted habitat fields
plot_habitat(hab$spwn_hab)
plot_spatiotemp_hab(hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
#to plot just the temp preferences over time
source("R/BENS_plot_spatiotemp_hab_justtemp.R")
BENS_plot_spatiotemp_hab_justtemp(plot_wk = c(1,10,20,30,40,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
dev.off()
#############################################################################################
###Init moveCov
#############################################################################################
#first try
source("R/init_moveCov_Bens.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#second try
source("R/init_moveCov_Bens2.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens2(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#third try
source("R/init_moveCov_Bens3.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens3(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#fourth try- try to get initial setup to not get so cold/hot on first
source("R/init_moveCov_Bens4.R")
steps <- 52 #must be multiple of 52
moveCov <- init_moveCov_Bens4(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
###############################################################################################
###############################################################################################
##mean of initial moveCov matrix is 10. seeing how many values are less tahn 10 or more than 10
mean(moveCov$cov.matrix[[1]])
test_moveCov <- matrix(0, nrow = 100, ncol = 100)
#check where the 10s are
test_moveCov <- ifelse(moveCov$cov.matrix[[1]]==10,NA,1) #puts NA on antidiagonal
#10s exist along the antidiagonal of the matrix
#put 1 for <10 and 99 for >10
test_moveCov <- ifelse(moveCov$cov.matrix[[1]]<10,1,99)
###FINAL TAKEAWAY: NUMBERS ABOVE ANTIDIAGONAL < 10, NUMBERS BELOW > 10, NUMBERS ON IT = 10
###############################################################################################
###############################################################################################
#the above creates a gradient that gets too cold on one side and too hot on the other.
#below adjusts it here
#this one add to the small and subtracts from the large, but eventually results in values flipping (less than 10 become greater than 10 and vice versa)
#moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10,moveCov$cov.matrix[[1]]+13,moveCov$cov.matrix[[1]]-3.25) #was +.75 and -2.5
#this one JUST adds to the small to increase min value as max seemed ok
#moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10,moveCov$cov.matrix[[1]]+5,moveCov$cov.matrix[[1]])
#do it in a way that avoids numbers jumping each other
inc <- 10 #set increase amount
moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10, #want to add inc to them, but not if it causes values to increase past 10
ifelse(moveCov$cov.matrix[[1]]+inc<10,moveCov$cov.matrix[[1]]+inc,moveCov$cov.matrix[[1]]+inc-.075*(row(moveCov$cov.matrix[[1]])+col(moveCov$cov.matrix[[1]]))),moveCov$cov.matrix[[1]]+1
)
#inc <- 8, +10 instead of +inc, and +1 at the end creates plot I sent to chris
#############################################################################################
###take single original covariate map and apply sine to create 1-year oscilating pattern
#############################################################################################
all_moveCov <- list() #create list to store all 52 sequences
for(j in seq(1)){ #now just pulling out first map and making it work
#assign(paste0('moveCov',j),list()) #create list using index j
idx <- 1
temp <- list()
for(i in seq(pi/2 + 22*2*pi/51 , 2*pi+pi/2 + 22*2*pi/51, 2*pi/51) ){ #old one from August: seq(pi/2,2*pi+pi/2,2*pi/51)
# print(j)
# print(idx)
temp[[idx]] <- 0.3*(sin(i)+2)*moveCov[[1]][[j]] #creates list of size 52 used to be 0.45* and +2
idx <- idx + 1
}
all_moveCov[[j]] <- temp #stores previous list as list
}
#plot results
pdf(file="testfolder/moveCov_plots.pdf")
for(j in seq(1)){ #seq(1) plots the first year to plot them all do seq(52)
#plot each weekly mean
wk_meantemp <- vector()
yr_meantemp <- vector()
wk_mintemp <- vector()
wk_maxtemp <- vector()
for(i in seq(52)){
wk_meantemp <- c(wk_meantemp,mean(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
wk_mintemp <- c(wk_mintemp,min(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
wk_maxtemp <- c(wk_maxtemp,max(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
#record yearly temp
if(i %% 51 == 0){
p <- i - 50
yr_meantemp <- c(yr_meantemp,mean(as.vector(wk_meantemp[p:i])))
}
}
plot(wk_meantemp)
plot(wk_mintemp)
plot(wk_maxtemp)
#plot(yr_meantemp)
min(yr_meantemp)
max(yr_meantemp)
max(yr_meantemp)-min(yr_meantemp)
}
dev.off() #close pdf
#############################################################################################
###manipulate single temp for re-use VERSION #1
#############################################################################################
#############################################################################################
###this version creates oscillating effect that widens as time goes on (due to scaling)
#############################################################################################
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
moveCov <- list()
steps <- 52*20 #total months
inc <- 1.02 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
}
#increase/stretch
if(i %% 52 == 0){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
}
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
moveCov[["cov.matrix"]][[i]] <- inc*moveCov[["cov.matrix"]][[i-52]]
}
}
#############################################################################################
###manipulate single temp for re-use VERSION #2
#############################################################################################
#############################################################################################
###this version creates oscilatting effect that remains consistent width, but its not smooth
#############################################################################################
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
moveCov <- list()
steps <- 52*20 #total months
inc <- 1.025 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
}
#increase/stretch
if(i %% 52 == 0){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
}
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
moveCov[["cov.matrix"]][[i]] <- .25+moveCov[["cov.matrix"]][[i-52]]
}
}
#############################################################################################
###manipulate single yearly temp gradient for re-use VERSION #3
#############################################################################################
#############################################################################################
###this version tries to lift up the first copy the correct amount and then copy away the rest
#############################################################################################
Good_moveCov <- all_moveCov[[1]] #to be used below
#package for flipping over
library(pracma)
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
#moveCov <- list()
steps <- 52*20 #total months
inc <- 1.02 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
# print(i)
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#to achieve correct temp relationship
#apply(matrix,1,rev) flips the matrix horizontally
#apply(matrix,2,rev) flips the matrix vertically
#vertical flip not working
#have also tried simply t(), but not a matrix
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
new_moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
new_moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
#increase/stretch
if(i %% 52 == 0){
new_moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
}
#after creating first stretched sequence, see how far first and last mean values are
if(i==52){
#rasie up by this amount
diff <- mean(as.vector(as.matrix(new_moveCov[["cov.matrix"]][[52]])))-mean(as.vector(as.matrix(new_moveCov[["cov.matrix"]][[1]])))
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
new_moveCov[["cov.matrix"]][[i]] <- diff+new_moveCov[["cov.matrix"]][[i-52]]
}
}
#pass to moveCov to be used elsewhere
moveCov[["cov.matrix"]] <- new_moveCov[["cov.matrix"]]
#detach pracma package incase it interferes with other packages
detach("package:pracma",unload = TRUE)
#
#
# #transpose matrix to create final form
#
# for(i in seq(52)){ #52 weeks = 52 moveCov
# for(j in seq(100)){ #100 rows and columns
# print(i)
# print(j)
# moveCov[["cov.matrix"]][[i]][,j] <- new_moveCov[["cov.matrix"]][[i]][j,]
#
# }
# }
#
#
# #transpose matrix one element at a time to create final form
#
# for(i in seq(52)){ #52 weeks = 52 moveCov
# # print(i)
# for(j in seq(100)){ #100 rows and columns
#
# # print(j)
# #pull out row
# row <- vector()
# row <- new_moveCov[["cov.matrix"]][[i]][j,]
#
# for(k in seq(100)){
#
# # print(k)
# moveCov[["cov.matrix"]][[i]][k,j] <-row[k]
# }
#
# }
# }
#to plot just the temp preferences over time
source("R/BENS_plot_spatiotemp_hab_justtemp.R")
BENS_plot_spatiotemp_hab_justtemp(plot_wk = seq(1,1040,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
dev.off()
#plot spatiotemperal distribution (combine temp and spatial preferences)
source("R/BENS_plot_spatiotemp_hab.R")
plot_spatiotemp_hab(plot_monthly = TRUE, plot_wk = seq(1,1040,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
#############################################################################################
##PLots
#############################################################################################
#plot mean in covariate values
#plot each weekly mean
wk_meantemp <- vector()
yr_meantemp <- vector()
wk_mintemp <- vector()
wk_maxtemp <- vector()
for(i in seq(steps)){
wk_meantemp <- c(wk_meantemp,mean(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
wk_mintemp <- c(wk_mintemp,min(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
wk_maxtemp <- c(wk_maxtemp,max(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
#record yearly temp
if(i %% 52 == 0){
p <- i - 51
yr_meantemp <- c(yr_meantemp,mean(as.vector(wk_meantemp[p:i])))
}
}
plot(wk_meantemp)
plot(wk_meantemp[1:60])
plot(wk_mintemp)
plot(wk_maxtemp)
plot(yr_meantemp)
min(yr_meantemp)
max(yr_meantemp)
max(yr_meantemp)-min(yr_meantemp)
##################################################################
# PLOTTING THE ABOVE BY QUADRANT
##################################################################
#first break into strata
Strata1 <- list() #matrix(0,nrow=50,ncol=100)
Strata2 <- list() #matrix(0,nrow=50,ncol=100)
Strata3 <- list() #matrix(0,nrow=50,ncol=100)
Strata4 <- list()
for(i in seq(52*20)){
#Strata1
Strata1[[i]]<-moveCov$cov.matrix[[i]][1:50,1:50]
#Strata2
Strata2[[i]]<-moveCov$cov.matrix[[i]][1:50,51:100]
#Strata3
Strata3[[i]]<-moveCov$cov.matrix[[i]][51:100,1:50]
#Strata4
Strata4[[i]]<-moveCov$cov.matrix[[i]][51:100,51:100]
}
#copied above for each strata
wk_meantemps1 <- vector()
yr_meantemps1 <- vector()
wk_mintemps1 <- vector()
wk_maxtemps1 <- vector()
wk_meantemps2 <- vector()
yr_meantemps2 <- vector()
wk_mintemps2 <- vector()
wk_maxtemps2 <- vector()
wk_meantemps3 <- vector()
yr_meantemps3 <- vector()
wk_mintemps3 <- vector()
wk_maxtemps3 <- vector()
wk_meantemps4 <- vector()
yr_meantemps4 <- vector()
wk_mintemps4 <- vector()
wk_maxtemps4 <- vector()
for(i in seq(steps)){
wk_meantemps1 <- c(wk_meantemps1,mean(as.vector(as.matrix(Strata1[[i]]))))
wk_mintemps1 <- c(wk_mintemps1,min(as.vector(as.matrix(Strata1[[i]]))))
wk_maxtemps1 <- c(wk_maxtemps1,max(as.vector(as.matrix(Strata1[[i]]))))
wk_meantemps2 <- c(wk_meantemps2,mean(as.vector(as.matrix(Strata2[[i]]))))
wk_mintemps2 <- c(wk_mintemps2,min(as.vector(as.matrix(Strata2[[i]]))))
wk_maxtemps2 <- c(wk_maxtemps2,max(as.vector(as.matrix(Strata2[[i]]))))
wk_meantemps3 <- c(wk_meantemps3,mean(as.vector(as.matrix(Strata3[[i]]))))
wk_mintemps3 <- c(wk_mintemps3,min(as.vector(as.matrix(Strata3[[i]]))))
wk_maxtemps3 <- c(wk_maxtemps3,max(as.vector(as.matrix(Strata3[[i]]))))
wk_meantemps4 <- c(wk_meantemps4,mean(as.vector(as.matrix(Strata4[[i]]))))
wk_mintemps4 <- c(wk_mintemps4,min(as.vector(as.matrix(Strata4[[i]]))))
wk_maxtemps4 <- c(wk_maxtemps4,max(as.vector(as.matrix(Strata4[[i]]))))
#record yearly temp
if(i %% 52 == 0){
p <- i - 51
yr_meantemps1 <- c(yr_meantemps1,mean(as.vector(wk_meantemps1[p:i])))
yr_meantemps2 <- c(yr_meantemps2,mean(as.vector(wk_meantemps2[p:i])))
yr_meantemps3 <- c(yr_meantemps3,mean(as.vector(wk_meantemps3[p:i])))
yr_meantemps4 <- c(yr_meantemps4,mean(as.vector(wk_meantemps4[p:i])))
}
}
par(mfrow = c(2,2),mar = c(4, 4, 4, 4))
plot(wk_meantemps1)
plot(wk_mintemps1)
plot(wk_maxtemps1)
plot(yr_meantemps1)
mtext("Strata 1- NW", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps2)
plot(wk_mintemps2)
plot(wk_maxtemps2)
plot(yr_meantemps2)
mtext("Strata 2- NE", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps3)
plot(wk_mintemps3)
plot(wk_maxtemps3)
plot(yr_meantemps3)
mtext("Strata 3- SW", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps4)
plot(wk_mintemps4)
plot(wk_maxtemps4)
plot(yr_meantemps4)
mtext("Strata 4- SE", side = 3, line = -1, outer = TRUE)
Blevy2/READ-PDB-blevy2-MFS2 documentation built on Nov. 29, 2023, 11:48 p.m.
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#This script is for creating and testing temperature covariate matrices
library(MixFishSim)
#############################################################################################
#Init Sim
#############################################################################################
#OLD VERSION
sim <- init_sim(nrows = 100, ncols = 100, n_years = 20, n_tows_day = 4,
n_days_wk_fished = 5, n_fleets = 2, n_vessels = 20, n_species = 2,
move_freq = 1)
#NEW VERSION that has week breaks for entire simulation and allows no fishing
source("R/init_sim_Bens.R")
sim <- init_sim_Bens(nrows = 100, ncols = 100, n_years = 20, n_tows_day = 4,
n_days_wk_fished = 1, n_fleets = 1, n_vessels = 1, n_species = 2,
move_freq = 1)
#############################################################################################
###Habitat setup
#############################################################################################
source("R/BENS_create_hab.R")
source("R/BENS_plot_habitat.R")
#values settled on from anisotropy and habtest scripts
spp.ctrl = list(
"spp.1" = list('nu' = 1/0.05,
'var' = 1,
'scale' = 2,
'Aniso' = matrix(nc = 2, c(1, -2, 1, 2))),
"spp.2" = list('nu' = 1/0.015,
'var' = 1,
'scale' = 40,
'Aniso' = matrix(nc = 2, c(1.5, -3, 3, 4))),
plot.dist = TRUE,
plot.file = "testfolder"
)
hab <- BENS_create_hab(sim_init = sim,
spp.ctrl = spp.ctrl,
spawn_areas = list(
"spp1" = list(
'area1' = c(40,50,40,50), #of the form c(x1, x2, y1, y2) THESE ARE BOUNDARIES OF MATRIX VALUES
'area2' = c(80,90,60,70) #need to revisit closure areas
),
"spp2" = list(
'area1' = c(50,60,30,40),
'area2' = c(70,90,80,90)
),
spwn_mult = 10,
plot.dist = TRUE,
plot.file = "testfolder" ),
#created this new part defining strata
strata = list( #Form: upper left, upper right, lower left, lower right
"strata1" = c(1,sim$idx[["nrows"]]/2,1,sim$idx[["ncols"]]/2), #of the form c(x1, x2, y1, y2) THESE ARE BOUNDARIES OF STRATA VALUES
"strata2" = c(1,sim$idx[["nrows"]]/2,sim$idx[["ncols"]]/2+1,sim$idx[["ncols"]]),
"strata3" = c(sim$idx[["nrows"]]/2 + 1,sim$idx[["nrows"]], 1 ,sim$idx[["ncols"]]/2),
"strata4" = c(sim$idx[["nrows"]]/2 + 1,sim$idx[["nrows"]],sim$idx[["ncols"]]/2 +1 , sim$idx[["ncols"]])
)
)
#old version
plot_habitat(hab$hab)
## Plot the adjusted habitat fields
plot_habitat(hab$spwn_hab)
plot_spatiotemp_hab(hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
#to plot just the temp preferences over time
source("R/BENS_plot_spatiotemp_hab_justtemp.R")
BENS_plot_spatiotemp_hab_justtemp(plot_wk = c(1,10,20,30,40,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
dev.off()
#############################################################################################
###Init moveCov
#############################################################################################
#first try
source("R/init_moveCov_Bens.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#second try
source("R/init_moveCov_Bens2.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens2(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#third try
source("R/init_moveCov_Bens3.R")
steps <- 52*20 #must be multiple of 52
moveCov <- init_moveCov_Bens3(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
#fourth try- try to get initial setup to not get so cold/hot on first
source("R/init_moveCov_Bens4.R")
steps <- 52 #must be multiple of 52
moveCov <- init_moveCov_Bens4(sim_init = sim, steps = steps,
spp_tol = list("spp1" = list("mu" = 12, "va" = 8),
"spp2" = list("mu" = 15, "va" = 7)
)
)
###############################################################################################
###############################################################################################
##mean of initial moveCov matrix is 10. seeing how many values are less tahn 10 or more than 10
mean(moveCov$cov.matrix[[1]])
test_moveCov <- matrix(0, nrow = 100, ncol = 100)
#check where the 10s are
test_moveCov <- ifelse(moveCov$cov.matrix[[1]]==10,NA,1) #puts NA on antidiagonal
#10s exist along the antidiagonal of the matrix
#put 1 for <10 and 99 for >10
test_moveCov <- ifelse(moveCov$cov.matrix[[1]]<10,1,99)
###FINAL TAKEAWAY: NUMBERS ABOVE ANTIDIAGONAL < 10, NUMBERS BELOW > 10, NUMBERS ON IT = 10
###############################################################################################
###############################################################################################
#the above creates a gradient that gets too cold on one side and too hot on the other.
#below adjusts it here
#this one add to the small and subtracts from the large, but eventually results in values flipping (less than 10 become greater than 10 and vice versa)
#moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10,moveCov$cov.matrix[[1]]+13,moveCov$cov.matrix[[1]]-3.25) #was +.75 and -2.5
#this one JUST adds to the small to increase min value as max seemed ok
#moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10,moveCov$cov.matrix[[1]]+5,moveCov$cov.matrix[[1]])
#do it in a way that avoids numbers jumping each other
inc <- 10 #set increase amount
moveCov$cov.matrix[[1]]<-ifelse(moveCov$cov.matrix[[1]]<10, #want to add inc to them, but not if it causes values to increase past 10
ifelse(moveCov$cov.matrix[[1]]+inc<10,moveCov$cov.matrix[[1]]+inc,moveCov$cov.matrix[[1]]+inc-.075*(row(moveCov$cov.matrix[[1]])+col(moveCov$cov.matrix[[1]]))),moveCov$cov.matrix[[1]]+1
)
#inc <- 8, +10 instead of +inc, and +1 at the end creates plot I sent to chris
#############################################################################################
###take single original covariate map and apply sine to create 1-year oscilating pattern
#############################################################################################
all_moveCov <- list() #create list to store all 52 sequences
for(j in seq(1)){ #now just pulling out first map and making it work
#assign(paste0('moveCov',j),list()) #create list using index j
idx <- 1
temp <- list()
for(i in seq(pi/2 + 22*2*pi/51 , 2*pi+pi/2 + 22*2*pi/51, 2*pi/51) ){ #old one from August: seq(pi/2,2*pi+pi/2,2*pi/51)
# print(j)
# print(idx)
temp[[idx]] <- 0.3*(sin(i)+2)*moveCov[[1]][[j]] #creates list of size 52 used to be 0.45* and +2
idx <- idx + 1
}
all_moveCov[[j]] <- temp #stores previous list as list
}
#plot results
pdf(file="testfolder/moveCov_plots.pdf")
for(j in seq(1)){ #seq(1) plots the first year to plot them all do seq(52)
#plot each weekly mean
wk_meantemp <- vector()
yr_meantemp <- vector()
wk_mintemp <- vector()
wk_maxtemp <- vector()
for(i in seq(52)){
wk_meantemp <- c(wk_meantemp,mean(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
wk_mintemp <- c(wk_mintemp,min(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
wk_maxtemp <- c(wk_maxtemp,max(as.vector(as.matrix(all_moveCov[[j]][[i]]))))
#record yearly temp
if(i %% 51 == 0){
p <- i - 50
yr_meantemp <- c(yr_meantemp,mean(as.vector(wk_meantemp[p:i])))
}
}
plot(wk_meantemp)
plot(wk_mintemp)
plot(wk_maxtemp)
#plot(yr_meantemp)
min(yr_meantemp)
max(yr_meantemp)
max(yr_meantemp)-min(yr_meantemp)
}
dev.off() #close pdf
#############################################################################################
###manipulate single temp for re-use VERSION #1
#############################################################################################
#############################################################################################
###this version creates oscillating effect that widens as time goes on (due to scaling)
#############################################################################################
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
moveCov <- list()
steps <- 52*20 #total months
inc <- 1.02 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
}
#increase/stretch
if(i %% 52 == 0){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
}
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
moveCov[["cov.matrix"]][[i]] <- inc*moveCov[["cov.matrix"]][[i-52]]
}
}
#############################################################################################
###manipulate single temp for re-use VERSION #2
#############################################################################################
#############################################################################################
###this version creates oscilatting effect that remains consistent width, but its not smooth
#############################################################################################
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
moveCov <- list()
steps <- 52*20 #total months
inc <- 1.025 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
}
#increase/stretch
if(i %% 52 == 0){
moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
}
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
moveCov[["cov.matrix"]][[i]] <- .25+moveCov[["cov.matrix"]][[i-52]]
}
}
#############################################################################################
###manipulate single yearly temp gradient for re-use VERSION #3
#############################################################################################
#############################################################################################
###this version tries to lift up the first copy the correct amount and then copy away the rest
#############################################################################################
Good_moveCov <- all_moveCov[[1]] #to be used below
#package for flipping over
library(pracma)
#take initial yearly run and extend it so that temp growth over time is 5 degrees
new_moveCov <- list()
#moveCov <- list()
steps <- 52*20 #total months
inc <- 1.02 #percent increase each year
for(i in seq(steps)){
#create first stretched sequence
if(i<=52){
# print(i)
#first half the year keep the same while they are decreasing
# second half of the year stretch the values by inc
#to achieve correct temp relationship
#apply(matrix,1,rev) flips the matrix horizontally
#apply(matrix,2,rev) flips the matrix vertically
#vertical flip not working
#have also tried simply t(), but not a matrix
#decrease
if((i %% 52 < 27) & (i %% 52 !=0)){
new_moveCov[["cov.matrix"]][[i]] <- Good_moveCov[[i %% 52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
#increase/stretch
if((i %% 52 >= 27) & (i %% 52 !=0)){
new_moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[i %% 52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
#increase/stretch
if(i %% 52 == 0){
new_moveCov[["cov.matrix"]][[i]] <- inc*Good_moveCov[[52]]
new_moveCov[["cov.matrix"]][[i]] <- pracma::fliplr(new_moveCov[["cov.matrix"]][[i]]) #flip left to right to obtain correct temp gradient (cold NE, hot SW, SW ~ SE)
}
}
#after creating first stretched sequence, see how far first and last mean values are
if(i==52){
#rasie up by this amount
diff <- mean(as.vector(as.matrix(new_moveCov[["cov.matrix"]][[52]])))-mean(as.vector(as.matrix(new_moveCov[["cov.matrix"]][[1]])))
}
#after creating first stretched sequence, use previous one as basis for next one
if(i>52){
new_moveCov[["cov.matrix"]][[i]] <- diff+new_moveCov[["cov.matrix"]][[i-52]]
}
}
#pass to moveCov to be used elsewhere
moveCov[["cov.matrix"]] <- new_moveCov[["cov.matrix"]]
#detach pracma package incase it interferes with other packages
detach("package:pracma",unload = TRUE)
#
#
# #transpose matrix to create final form
#
# for(i in seq(52)){ #52 weeks = 52 moveCov
# for(j in seq(100)){ #100 rows and columns
# print(i)
# print(j)
# moveCov[["cov.matrix"]][[i]][,j] <- new_moveCov[["cov.matrix"]][[i]][j,]
#
# }
# }
#
#
# #transpose matrix one element at a time to create final form
#
# for(i in seq(52)){ #52 weeks = 52 moveCov
# # print(i)
# for(j in seq(100)){ #100 rows and columns
#
# # print(j)
# #pull out row
# row <- vector()
# row <- new_moveCov[["cov.matrix"]][[i]][j,]
#
# for(k in seq(100)){
#
# # print(k)
# moveCov[["cov.matrix"]][[i]][k,j] <-row[k]
# }
#
# }
# }
#to plot just the temp preferences over time
source("R/BENS_plot_spatiotemp_hab_justtemp.R")
BENS_plot_spatiotemp_hab_justtemp(plot_wk = seq(1,1040,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
dev.off()
#plot spatiotemperal distribution (combine temp and spatial preferences)
source("R/BENS_plot_spatiotemp_hab.R")
plot_spatiotemp_hab(plot_monthly = TRUE, plot_wk = seq(1,1040,50),hab = hab, moveCov = moveCov, spwn_wk = list("spp1" = 16:18, "spp2" = 16:19), plot.file = "testfolder")
#############################################################################################
##PLots
#############################################################################################
#plot mean in covariate values
#plot each weekly mean
wk_meantemp <- vector()
yr_meantemp <- vector()
wk_mintemp <- vector()
wk_maxtemp <- vector()
for(i in seq(steps)){
wk_meantemp <- c(wk_meantemp,mean(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
wk_mintemp <- c(wk_mintemp,min(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
wk_maxtemp <- c(wk_maxtemp,max(as.vector(as.matrix(moveCov[["cov.matrix"]][[i]]))))
#record yearly temp
if(i %% 52 == 0){
p <- i - 51
yr_meantemp <- c(yr_meantemp,mean(as.vector(wk_meantemp[p:i])))
}
}
plot(wk_meantemp)
plot(wk_meantemp[1:60])
plot(wk_mintemp)
plot(wk_maxtemp)
plot(yr_meantemp)
min(yr_meantemp)
max(yr_meantemp)
max(yr_meantemp)-min(yr_meantemp)
##################################################################
# PLOTTING THE ABOVE BY QUADRANT
##################################################################
#first break into strata
Strata1 <- list() #matrix(0,nrow=50,ncol=100)
Strata2 <- list() #matrix(0,nrow=50,ncol=100)
Strata3 <- list() #matrix(0,nrow=50,ncol=100)
Strata4 <- list()
for(i in seq(52*20)){
#Strata1
Strata1[[i]]<-moveCov$cov.matrix[[i]][1:50,1:50]
#Strata2
Strata2[[i]]<-moveCov$cov.matrix[[i]][1:50,51:100]
#Strata3
Strata3[[i]]<-moveCov$cov.matrix[[i]][51:100,1:50]
#Strata4
Strata4[[i]]<-moveCov$cov.matrix[[i]][51:100,51:100]
}
#copied above for each strata
wk_meantemps1 <- vector()
yr_meantemps1 <- vector()
wk_mintemps1 <- vector()
wk_maxtemps1 <- vector()
wk_meantemps2 <- vector()
yr_meantemps2 <- vector()
wk_mintemps2 <- vector()
wk_maxtemps2 <- vector()
wk_meantemps3 <- vector()
yr_meantemps3 <- vector()
wk_mintemps3 <- vector()
wk_maxtemps3 <- vector()
wk_meantemps4 <- vector()
yr_meantemps4 <- vector()
wk_mintemps4 <- vector()
wk_maxtemps4 <- vector()
for(i in seq(steps)){
wk_meantemps1 <- c(wk_meantemps1,mean(as.vector(as.matrix(Strata1[[i]]))))
wk_mintemps1 <- c(wk_mintemps1,min(as.vector(as.matrix(Strata1[[i]]))))
wk_maxtemps1 <- c(wk_maxtemps1,max(as.vector(as.matrix(Strata1[[i]]))))
wk_meantemps2 <- c(wk_meantemps2,mean(as.vector(as.matrix(Strata2[[i]]))))
wk_mintemps2 <- c(wk_mintemps2,min(as.vector(as.matrix(Strata2[[i]]))))
wk_maxtemps2 <- c(wk_maxtemps2,max(as.vector(as.matrix(Strata2[[i]]))))
wk_meantemps3 <- c(wk_meantemps3,mean(as.vector(as.matrix(Strata3[[i]]))))
wk_mintemps3 <- c(wk_mintemps3,min(as.vector(as.matrix(Strata3[[i]]))))
wk_maxtemps3 <- c(wk_maxtemps3,max(as.vector(as.matrix(Strata3[[i]]))))
wk_meantemps4 <- c(wk_meantemps4,mean(as.vector(as.matrix(Strata4[[i]]))))
wk_mintemps4 <- c(wk_mintemps4,min(as.vector(as.matrix(Strata4[[i]]))))
wk_maxtemps4 <- c(wk_maxtemps4,max(as.vector(as.matrix(Strata4[[i]]))))
#record yearly temp
if(i %% 52 == 0){
p <- i - 51
yr_meantemps1 <- c(yr_meantemps1,mean(as.vector(wk_meantemps1[p:i])))
yr_meantemps2 <- c(yr_meantemps2,mean(as.vector(wk_meantemps2[p:i])))
yr_meantemps3 <- c(yr_meantemps3,mean(as.vector(wk_meantemps3[p:i])))
yr_meantemps4 <- c(yr_meantemps4,mean(as.vector(wk_meantemps4[p:i])))
}
}
par(mfrow = c(2,2),mar = c(4, 4, 4, 4))
plot(wk_meantemps1)
plot(wk_mintemps1)
plot(wk_maxtemps1)
plot(yr_meantemps1)
mtext("Strata 1- NW", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps2)
plot(wk_mintemps2)
plot(wk_maxtemps2)
plot(yr_meantemps2)
mtext("Strata 2- NE", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps3)
plot(wk_mintemps3)
plot(wk_maxtemps3)
plot(yr_meantemps3)
mtext("Strata 3- SW", side = 3, line = -1, outer = TRUE)
par(mfrow = c(2,2),mar = c(4,4,4,4))
plot(wk_meantemps4)
plot(wk_mintemps4)
plot(wk_maxtemps4)
plot(yr_meantemps4)
mtext("Strata 4- SE", side = 3, line = -1, outer = TRUE)
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