## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.width = 6.5,
                      fig.height = 4.2, dpi = 120)

## ----setup--------------------------------------------------------------------
library(trialSizing)

## ----data, message = FALSE----------------------------------------------------
grid_mat <- function(t)
  unname(as.matrix(uniformity_trial[uniformity_trial$trial == t,
                                    grep("^col", names(uniformity_trial))]))
E1 <- grid_mat("T1")
E2 <- grid_mat("T2")
dim(E1)

## ----fit----------------------------------------------------------------------
fit <- calc_paranaiba(E1)
fit

## ----summary------------------------------------------------------------------
summary(fit)

## ----access-------------------------------------------------------------------
fit$summary[, c("mean", "variance", "CV", "rho", "Xo", "CVxo")]

## ----directions---------------------------------------------------------------
do.call(rbind, lapply(c("row", "col", "mean"), function(d) {
  f <- calc_paranaiba(E1, rho_direction = d)
  data.frame(direction = d, rho = f$summary$rho,
             Xo = f$summary$Xo, CVxo = f$summary$CVxo)
}))

## ----list---------------------------------------------------------------------
res <- calc_paranaiba(list(`Trial 1` = E1, `Trial 2` = E2))
res

## ----long---------------------------------------------------------------------
long <- expand.grid(col = 1:12, row = 1:8)
long$mf <- as.vector(t(E1))

calc_paranaiba(long, value = "mf", row_id = "row", col_id = "col")$summary$Xo

## ----long-trial---------------------------------------------------------------
long2 <- rbind(
  transform(long, trial = "Trial 1"),
  transform(expand.grid(col = 1:12, row = 1:8), mf = as.vector(t(E2)),
            trial = "Trial 2")
)

calc_paranaiba(long2, value = "mf", row_id = "row", col_id = "col",
               trial = "trial")$summary[, c("trial", "rho", "Xo", "CVxo")]

## ----plot---------------------------------------------------------------------
plot(res, title = "Paranaiba: optimal plot size")

## ----plot-cv------------------------------------------------------------------
plot(res, y_var = "CVxo", title = "CV at the optimal plot size")

## ----save, eval = FALSE-------------------------------------------------------
# plot(res, title = "Paranaiba",
#      save = TRUE, file = "paranaiba.tiff", format = "tiff", dpi = 300)