_load-data.qmd

```{r}
library(dplyr)
library(tidyr)
library(stringr)
```

```{r}
# set user and dataset
# dataset <- redivis::user("datapages")$dataset("item_response_warehouse")

# get metadata table
# metadata_table <- dataset$table("metadata")
# metadata <- metadata_table$to_tibble()

project <- redivis::user("mikabr")$project("irw")

# get metadata table
metadata_table <- project$table("metadata_output")
metadata <- metadata_table$to_tibble()
metadata <- metadata |>
  mutate(partition = if_else(n_categories == 2, "dichotomous", "polytomous"))

# cont_vars <- metadata |> select(where(is.numeric)) |> colnames()
# cont_vars_list <- set_names(cont_vars, cont_vars |> str_replace_all("_", " ") |> str_to_sentence()) |> as.list()
# ojs_define(cont_vars = cont_vars_list)

# get item summary table
item_table <- project$table("item_summary_output")
item_summary <- item_table$to_tibble()

# get subject summary table
subject_table <- project$table("subject_summary_output")
subject_summary <- subject_table$to_tibble()

# combine item and subject summaries, put into data structure for selector
summaries <- full_join(
  item_summary |> nest(items = -dataset_name),
  subject_summary |> nest(subjects = -dataset_name),
  by = "dataset_name"
) |>
  mutate(data = map2(items, subjects, \(i, s) list(items = i, subjects = s)),
         summaries = map2(dataset_name, data, \(n, d) set_names(list(d), n))) |>
  arrange(dataset_name) |>
  pull(summaries) |>
  flatten()

# pass data to ojs
ojs_define(metadata = metadata)
ojs_define(summaries = summaries)
```