# test_Calibration.R
# ::rtemis::
# EDG rtemis.org

# Key
# {Algorithm}[method]<Class> Further conditions

# Setup ----
# library(rtemis)
# library(testthat)
library(data.table)

# Data ----
## Regression Data ----
n <- 400
x <- rnormmat(n, 5, seed = 2025)
g <- factor(sample(c("A", "B"), n, replace = TRUE))
y <- x[, 3] + x[, 5] + ifelse(g == "A", 2, -1) + rnorm(n)
datr <- data.table(x, g, y)
resr <- resample(datr)
datr_train <- datr[resr$Fold_1, ]
datr_test <- datr[-resr$Fold_1, ]

## Classification Data ----
### Binary ----
datc2 <- data.frame(
  gn = factor(sample(c("alpha", "beta", "gamma"), 100, replace = TRUE)),
  iris[51:150, ]
)
datc2$Species <- factor(datc2$Species)
resc2 <- resample(datc2)
datc2_train <- datc2[resc2$Fold_1, ]
datc2_test <- datc2[-resc2$Fold_1, ]

### 3-class ----
datc3 <- iris
resc3 <- resample(datc3)
datc3_train <- datc3[resc3$Fold_1, ]
datc3_test <- datc3[-resc3$Fold_1, ]