#############################################################################################
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## Test Candidates: FPOP1 ##
## The number of candidate changepoints stored over time by FPOP ##
## The data without changepoints ##
## See Tests\Test Candidates ##
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#For this test, you need to set the length of the time series "size", the vector of dimension "dim", the number of iterations"nb_Iter" and "fileresult"
devtools::install_github("lpishchagina/FPOPapprox2D")
library(FPOPapprox2D)
library(base)
library(rstream)
nb_Iter = 100
size <-1000
dim <- 15
s = "10^3"
mu <- matrix(0, nrow = dim, ncol = 1)
fileresult = paste("dim",dim,"FPOP1",s,"MultiTest Candidates.txt")
sigma <- 1
penalty <- 2*dim*sigma*log(size)
matrix_candidates <- matrix(0, nrow = size, ncol = nb_Iter)
t = 13
for ( k in 1:nb_Iter){
set.seed(t+k)
Data <- data_genDp(dim, size, chp = NULL, mu, sigma)
res_FPOP1<- FPOPDp(Data, penalty, type = 1)
###############################
# matrix "lbl_excl" #
###############################
#"lbl_excl" is the matrix with n rows.
#Each row contains a sequence of pairs of integer numbers for the moment t (t = 1:n).
#Each pair contains two values: candidate of changepoint and quantity of exclusion for this candidate.
## The values of matrix "lbl_excl" is contained in the papier "Test The data without changepoints".
lbl_excl <- readLines(con = 'test.txt', n = -1)
lbl_excl <- strsplit(lbl_excl,split = ' ')
lbl_excl <- sapply(lbl_excl, FUN = function(x) {as.integer(unlist(x))})
###############################
# number of canditates #
###############################
nb_canditates = NULL
for (i in 1:length(lbl_excl)){ nb_canditates[i] = length(lbl_excl[[i]])}
matrix_candidates[,k] = nb_canditates
}
###############################
# mean number of canditates #
###############################
means_candidates = apply(matrix_candidates, 1, mean)
max_value <- max(means_candidates)
mean_value <- mean(means_candidates)
write.table(means_candidates, fileresult, row.names = FALSE,col.names = FALSE)
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