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parallel_task_ftest.R
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parallel_task_ftest.R
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require(compiler)
require(parallel)
enableJIT(3)
Seq_Nfix <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100,tau=1e6,sg=0.85){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
for(m in tau){
for(o in sg){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l, tau=m, sg=o)
}
}
}
}
}
}
trails <- mclapply(trails,FUN = walk_Nfix,mc.cores=20,mc.preschedule = T)
#trails <- lapply(trails,FUN = walk_Nfix)
c=0
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
for(m in tau){
for(o in sg){
c=c+1
trails[[c]]<-list(N=i, n=j, mms=k, Nf=l, tau=m, sg=o,data=trails[[c]])
}
}
}
}
}
}
return(trails)
}
Seq_Nfix_csv <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100,tau=1e6,sg=0.85){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
for(m in tau){
for(o in sg){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l, tau=m, sg=o)
}
}
}
}
}
}
mclapply(trails,FUN = walk_Nfix_v,mc.cores=20,mc.preschedule = T)
}
Seq_Nfix_T <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l)
}
}
}
}
trails <- mclapply(trails,FUN = walk_Nfix_T,mc.cores=20,mc.preschedule = T)
#trails <- lapply(trails,FUN = walk_Nfix)
c=0
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
c=c+1
trails[[c]]<-list(N=i, n=j, mms=k, Nf=l, data=trails[[c]])
}
}
}
}
return(trails)
}
Seq_Nfix_T_csv <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l)
}
}
}
}
trails <- mclapply(trails,FUN = walk_Nfix_v_T,mc.cores=20,mc.preschedule = T)
#trails <- lapply(trails,FUN = walk_Nfix)
}
Seq_Nfix_O <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l)
}
}
}
}
trails <- mclapply(trails,FUN = walk_Nfix_O,mc.cores=20,mc.preschedule = T)
#trails <- lapply(trails,FUN = walk_Nfix)
c=0
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
c=c+1
trails[[c]]<-list(N=i, n=j, mms=k, Nf=l, data=trails[[c]])
}
}
}
}
return(trails)
}
Seq_Nfix_O_csv <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l)
}
}
}
}
mclapply(trails,FUN = walk_Nfix_v_O,mc.cores=20,mc.preschedule = T)
}
Seq_sphere <- function(n=c(2,10,20),d=2.0,r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100,f=0.9){
trails <-list()
for(i in n){
for(j in d){
for(k in r){
for(l in Nf){
for(m in f){
trails[[length(trails)+1]]<-list(n=i, d=j, mms=k, Nf=l, f=m)
}
}
}
}
}
trails <- mclapply(trails, FUN = walk_sphere, mc.cores=20, mc.preschedule = T)
c=0
for(i in n){
for(j in d){
for(k in r){
for(l in Nf){
for(m in f){
c=c+1
trails[[c]]<-list(n=i, d=j, mms=k, Nf=l, f=m,data=trails[[c]])
}
}
}
}
}
return(trails)
}
Seq_Nfix_f <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=100,tau=1e6,sg=0.85){
trails <-list()
name <- character(0)
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
for(m in tau){
for(o in sg){
trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nm=l, tau=m, sg=o)
}
}
}
}
}
}
trails <- mclapply(trails,FUN = walk_Nfix_f,mc.cores=8)
#trails <- lapply(trails,FUN = walk_Nfix)
c=0
for(i in N){
for(j in n){
for(k in r){
for(l in Nf){
for(m in tau){
for(o in sg){
c=c+1
trails[[c]]<-list(N=i, n=j, mms=k, Nm=l, tau=m, sg=o,data=trails[[c]])
}
}
}
}
}
}
return(trails)
}
#
# Seq_all <- function(N=c(10,100,1000),n=c(2,10,20),r=c(0.001, 0.025, 0.05, 0.075, 0.1, 0.2, 0.3, 0.4, 0.5),Nf=25000,tau=NA,sg=0.85){
#
# trails <-list()
# name <- character(0)
# for(i in N){
# for(j in n){
# for(k in r){
# for(l in Nf){
# for(m in tau){
# for(m in sg){
#
# trails[[length(trails)+1]]<-list(N=i, n=j, mms=k, Nf=l, tau=m, sg=n)
#
# }
# }
# }
# }
# }
# }
#
# trails <- mclapply(trails,FUN = walk_all,mc.cores=20,mc.preschedule = T)
#
# c=0
# for(i in N){
# for(j in n){
# for(k in r){
# for(l in Nf){
# for(m in tau){
# for(o in sg){
#
# c=c+1
# trails[[c]]<-list(N=i, n=j, mms=k, Nf=l, tau=m, sg=o,data=trails[[c]])
#
# }
# }
# }
# }
# }
# }
#
# return(trails)
# }