Nothing
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
#### Testing the function to evalaute FCM parameters
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
test_that("The evaluate parameters function must return the same values as calculated by the simple functions",{
## situation
data(LyonIris)
AnalysisFields <-c("Lden","NO2","PM25","VegHautPrt","Pct0_14","Pct_65","Pct_Img",
"TxChom1564","Pct_brevet","NivVieMed")
dataset <- sf::st_drop_geometry(LyonIris[AnalysisFields])
ks <- c(2,3)
ms <- c(1.5,2)
myseed <- 123
idxs <- c("Silhouette.index", "Partition.entropy", "Partition.coeff", "XieBeni.index", "Explained.inertia")
list_res <- list()
for (k in ks){
for (m in ms){
res <- CMeans(dataset, k, m, seed = myseed, standardize = FALSE, verbose =F, tol = 0.001)
vals <- calcqualityIndexes(dataset,res$Belongings,m = m,indices = idxs)
list_res[[length(list_res)+1]] <- unlist(vals)
}
}
df1 <- data.frame(do.call(rbind, list_res))
df1$k <- c(2,2,3,3)
df1$m <- c(1.5,2,1.5,2)
df1$oid <- paste(df1$k,df1$m, sep = "_")
df1 <- df1[order(df1$oid),]
values <- select_parameters("FCM", dataset, k = c(2,3), m = c(1.5,2),
spconsist=FALSE, seed = 123, standardize = F, tol = 0.001, indices = idxs)
values$oid <- paste(values$k, values$m, sep = "_")
values <- values[order(values$oid),]
obtained <- sum(round(values[,1:5],3) - round(df1[,1:5],3))
expect_equal(obtained, 0)
})
test_that("The evaluate parameters function (multicore) must return the same values as calculated by the simple functions",{
## situation
data(LyonIris)
AnalysisFields <-c("Lden","NO2","PM25","VegHautPrt","Pct0_14","Pct_65","Pct_Img",
"TxChom1564","Pct_brevet","NivVieMed")
dataset <- sf::st_drop_geometry(LyonIris[AnalysisFields])
ks <- c(2,3)
ms <- c(1.5,2)
myseed <- 123
idxs <- c("Silhouette.index", "Partition.entropy", "Partition.coeff", "XieBeni.index", "Explained.inertia")
list_res <- list()
for (k in ks){
for (m in ms){
res <- CMeans(dataset, k, m, seed = myseed, standardize = FALSE, verbose =F, tol = 0.000001)
vals <- calcqualityIndexes(dataset,res$Belongings,m = m,indices = idxs)
list_res[[length(list_res)+1]] <- unlist(vals)
}
}
df1 <- data.frame(do.call(rbind, list_res))
df1$k <- c(2,2,3,3)
df1$m <- c(1.5,2,1.5,2)
df1$oid <- paste(df1$k,df1$m, sep = "_")
df1 <- df1[order(df1$oid),]
future::plan(future::multisession(workers=1))
values <- select_parameters.mc("FCM", dataset, k = c(2,3), m = c(1.5,2),
spconsist=FALSE, seed = 123, standardize = F, tol = 0.000001,
indices = idxs)
values$oid <- paste(values$k, values$m, sep = "_")
values <- values[order(values$oid),]
obtained <- sum(round(values[,1:5],3) - round(df1[,1:5],3))
expect_equal(obtained, 0)
})
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.