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if we run the data from the csv CSV_CODIF CSV_CODIF.csv
that has a hierarchy in the first column in the file hrc_C1 (must be changed to hrc format): hrc_C1.csv
we get that negative objective value:
with rounded values far from the original values:
Meanwhile if we do the same with CSV_CODIF_2 that has the same columns and hierarchy but different values:
When trying to use the round suppress, it sometimes rounds with a very big negative objective value. To show this, using the r code "test_code"
`
###fill
test<-read.table(file="CSV_CODIF.csv" , sep="\t", header=TRUE)
###fill
names <-colnames(test)
tot_code<-c("C1_1","C2_1","C3_1","C4_1")
dirname <-"tauargus_files"
filename <-"ex1"
dir_temp<-paste("/",dirname,"/",filename,".csv",sep="")
###fill
file_hrc=c("U:/anonimizacion/r tau argus/comprobacion/tabla_a_codificar/hrc_C1.hrc")
###fill
list_hrc<-setNames(file_hrc,"C1")
library(rtauargus)
###fill
loc_tauargus<-"C:/Users/ext-arodcur/Desktop/TauArgus4.2.4b2/TauArgus4.2.4b2/TauArgus.exe"
###fill
options(rtauargus.tauargus_exe = loc_tauargus)
ex1<- tab_rtauargus(
test,
dir_name = dirname,
files_name = filename,
explanatory_vars = names[-length(names)],
safety_rules = "FREQ(5,20)",
value= "OBS_VALUE",
freq = "OBS_VALUE",
totcode = tot_code,
suppress= "RND(1,5,0,1000,0)",
hrc=list_hrc,
verbose = TRUE,
)
###fill
test<-read.table(file="CSV_CODIF_2.csv" , sep="\t", header=TRUE)
###fill
names <-colnames(test)
tot_code<-c("C1_1","C2_1","C3_1","C4_1")
dirname <-"tauargus_files"
filename <-"ex1"
dir_temp<-paste("/",dirname,"/",filename,".csv",sep="")
file_hrc=c("hrc_C1.hrc")
list_hrc<-setNames(file_hrc,"C1")
ex1<- tab_rtauargus(
test,
dir_name = dirname,
files_name = filename,
explanatory_vars = names[-length(names)],
safety_rules = "FREQ(5,20)",
value= "OBS_VALUE",
freq = "OBS_VALUE",
totcode = tot_code,
suppress= "RND(1,5,0,1000,0)",
hrc=list_hrc,
verbose = TRUE,
)`
if we run the data from the csv CSV_CODIF
CSV_CODIF.csv
that has a hierarchy in the first column in the file hrc_C1 (must be changed to hrc format):
hrc_C1.csv
we get that negative objective value:
with rounded values far from the original values:
Meanwhile if we do the same with CSV_CODIF_2 that has the same columns and hierarchy but different values:
CSV_CODIF_2.csv
it doesnt happend:
Also, if we use Tau-Argus with the first file it turns out correct:
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