pacman::p_load(dplyr,purrr,tidyr,ggplot2, here, patchwork, conflicted)
conflict_prefer_all("dplyr", quiet = TRUE)

col.names = c("Phase","Block","BlockTrial","Pattern","Category","Pattern.Token","distortion","Response","Corr","rt",
              "x1","y1","x2","y2","x3","y3","x4","y4","x5","y5","x6","y6","x7","y7","x8","y8","x9","y9", "file", "condit", "sbjCode")

d <- read.table(here::here("data/dot_4conds_random/dot_cond4_sub99.txt")) |>
  mutate(file="dot_cond4_sub99",condit="4",sbjCode="tgtest") |> purrr::set_names(col.names) |> group_by(sbjCode, condit) |>
  mutate(trial = row_number()) |> 
  relocate("sbjCode", "condit", "trial") 


dCat <- d |> 
  mutate(
    phase = case_when(
      Phase == "1" ~ "Training",
      Phase == "2" ~ "Test"
    ), 
    Stage = case_when(
      trial %in% 1:90 ~ "Start",
      trial %in% 91:180 ~ "Middle",
      trial %in% 181:270 ~ "End",
      trial %in% 271:354 ~ "Test"
    ),
    pattern = case_when(
      Pattern == "1" ~ "old",
      Pattern == "2" ~ "prototype",
      Pattern == "3" ~ "new_low",
      Pattern == "4" ~ "new_med",
      Pattern == "5" ~ "new_high"
    ),
    distortion = recode(distortion,
                        `0` = "prototype",
                        `1` = "low",
                        `2` = "med",
                        `3` = "high"),
    Pattern_Token = case_when(
      pattern == "old" & Pattern.Token %in% 1:90 ~ "old",
      pattern == "prototype" & Pattern.Token == 0 ~ "prototype",
      pattern == "new_low" & Pattern.Token %in% 1:3 ~ "new_low",
      pattern == "new_med" & Pattern.Token %in% 1:6 ~ "new_med",
      pattern == "new_high" & Pattern.Token %in% 1:9 ~ "new_high"
    ),
    condit = recode(condit,
                    "cond1" = "low",
                    "cond2" = "medium",
                    "cond3" = "high",
                    "cond4" = "mixed")
  ) |> 
  relocate(Stage, .after=trial) |> relocate(Pattern_Token, pattern, .after=Pattern.Token)

dCat$Pattern_Token = factor(dCat$Pattern_Token,levels=c("old","prototype","new_low","new_med","new_high")) 
dCat <- dCat |> mutate(exp="mc24",
                       id=paste0(sbjCode,".",condit))  |>
  relocate(id,sbjCode,exp,condit,Phase,phase,Stage,trial,
           Block,BlockTrial,Pattern_Token,Pattern.Token,Pattern,pattern,distortion,
           Category,Response,Corr,rt)
  

teg_test_patterns <- dCat |> 
  ungroup() |>
  rename(Pattern.Type="Pattern_Token") |>
  mutate(Pattern.Type=forcats::fct_relevel(Pattern.Type,"prototype","old","new_low","new_med","new_high")) |>
  mutate(item_label = paste(sbjCode,condit,Category,trial,sep="_")) |>
  select(id,sbjCode,item_label,condit,exp,file,Phase,trial,Block,Pattern.Type,Category,Response,Corr,x1:y9) |>
  arrange(sbjCode,trial,condit,Category)



write.csv(teg_test_patterns |> slice_head(n=9),here("Stimulii","teg_test_patterns.csv"), row.names = FALSE)



ids <- unique(teg_test_patterns$id)
pat_themes <- list(theme_minimal(),xlim(-25, 25),ylim(-25, 25),
                        labs(x = "X Coordinate", y = "Y Coordinate"),
                   coord_fixed(),guides(alpha = FALSE))

Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use "none" instead as
of ggplot2 3.3.4.

 pat_long <- teg_test_patterns |> 
    filter(Block==1,Phase==1) |>
   select(id, condit, Category,Phase, item_label,trial,Block,Pattern.Type, x1:y9) |>
   group_by(id, trial,item_label,condit, Category,Phase, Pattern.Type) |> 
   gather(key = "coordinate", value = "value", -id,-Phase,-Block, -condit,-trial,-item_label, -Category,-Pattern.Type) %>%
   separate(coordinate, into = c("axis", "number"), sep = 1) %>%
   spread(key = axis, value = value) %>%
   mutate(number = as.integer(number))
 
 pat_long |> 
   ggplot(aes(x = x, y = y,col=Pattern.Type)) +
   geom_point() + # Add dots
   ggh4x::facet_wrap2(~trial+item_label) + # Create a grid of plots, with subjects by rows and categories by columns
   pat_themes + labs(title="Prototypes from Category 1 - with distortions")

Attempt flip to match MATLAB - this works

pat_long |> 
   mutate(y=-y) |>
   ggplot(aes(x = x, y = y,col=Pattern.Type)) +
   geom_point() + # Add dots
   ggh4x::facet_wrap2(~trial+item_label) + # Create a grid of plots, with subjects by rows and categories by columns
   pat_themes + labs(title="Prototypes from Category 1 - with distortions")

cat-learn24