In jtrampush/npsych.data: BrainWorkup Neuropsychological Report Writing Package

CEFI SR/OR

Setup

# Set JAVA environment
Sys.setenv(
  JAVA_HOME =
    "/Library/Java/JavaVirtualMachines/graalvm-community-openjdk-22.0.1+8.1/Contents/Home"
)
options(java.parameters = "-Xmx16000m")
# Set knitr options
knitr::opts_chunk$set(
  root.dir = normalizePath("./"),
  echo = TRUE,
  message = TRUE,
  warning = FALSE,
  error = TRUE
)
library(fs)
library(glue)
library(hablar)
library(here)
library(knitr)
library(magrittr)
library(miniUI)
library(pdftools)
library(rJava)
library(rmarkdown)
library(rmdformats)
library(shiny)
library(snakecase)
library(tabulapdf)
library(tidyverse)
library(xfun)
library(bwu)

patient <- params$patient
test <- params$test
test_name <- params$test_name
pages <- params$pages
file <- file.path(file.choose())
# file <- file.path(params$file)
# saveRDS(file, "cefi.rds")

if (params$test == "cefi_sr" || params$test == "cefi_or") {
  areas <- list(
    table1 = c(460, 34, 483, 578),
    table2 = c(533, 34, 671, 578)
  )
} else if (params$test == "cefi_sr_12-18") {
  areas <- list(
    table1 = c(467.033, 53.0, 480.038, 557.9),
    table2 = c(536.648, 52.02, 667.463, 557.685)
  )
} else if (params$test == "cefi_or_5-18") {
  areas <- list(
    table1 = c(468.563, 53.0, 481.568, 557.9),
    table2 = c(493.043, 50.49, 669.758, 559.98)
  )
}

# This works well so far
plucked_tables <- tabulapdf::extract_tables(
  file = file,
  pages = pages,
  area = areas,
  guess = NULL,
  method = "stream",
  output = "matrix"
)

local <- paste0("plucked_tables_", test, ".RData")

# Save the plucked_tables object to a file
save(plucked_tables, file = local)

# Load the plucked_tables object from a file
load(local)

library(dplyr)
library(purrr)

process_cefi_tables <- function(cefi_data) {
  table_list <- purrr::map(cefi_data, as_tibble) %>%
    set_names(paste0("table", 1:length(cefi_data))) # Rename tables

  list2env(table_list, .GlobalEnv) # Assign to global environment
}

# Usage:
process_cefi_tables(plucked_tables)

# Loop over the list and write each matrix to a CSV file
for (i in seq_along(plucked_tables)) {
  write.csv(plucked_tables[[i]], file = paste0(test, "_", i, ".csv"), row.names = FALSE)
}

Table 1

library(tibble)
library(dplyr)

# Convert to tibble
table1 <- as_tibble(table1)
# Ensure column names are correct
names(table1) <- c("score", "ci_95", "percentile", "category")

# Add 'scale' column with empty strings
table1 <- table1 |> mutate(scale = "Full Scale")
table1 <- table1[c("scale", "score", "ci_95", "percentile", "category")]

convert_columns <- function(df) {
  # Specify the columns to be converted to numeric
  numeric_cols <- c("score", "percentile")

  # Convert specified columns to numeric
  df[numeric_cols] <- lapply(df[numeric_cols], function(x) as.numeric(as.character(x)))

  # Convert remaining columns to character
  char_cols <- setdiff(names(df), numeric_cols)
  df[char_cols] <- lapply(df[char_cols], as.character)

  return(df)
}

# Usage (assuming you have a dataframe named 'df')
table1 <- convert_columns(df = table1)

Table 2

# Convert to tibble
table2 <- as_tibble(table2)

# Remove empty columns from table2
table2 <- table2 %>%
  select_if(~ any(. != ""))

# Display the modified table2
print(table2)

# Ensure column names are correct
names(table2) <- c("scale", "score", "ci_95", "percentile", "category", "diff_from_avg", "stat", "strength")

table2 <- table2 |>
  select(-c("diff_from_avg", "stat", "strength")) |>
  slice(-1, -5)

# Usage (assuming you have a dataframe named 'df')
table2 <- convert_columns(df = table2)

# Function to replace "-" with NA and filter out rows with no real data
filter_real_data <- function(table, key_columns) {
  table <- table %>%
    mutate(across(all_of(key_columns), ~ if_else(. == "-", NA_character_, as.character(.)))) %>%
    mutate(across(all_of(key_columns), as.numeric)) %>%
    filter(rowSums(is.na(select(., all_of(key_columns)))) < length(key_columns))

  return(table)
}

# Assuming key_columns are those columns which must have data
key_columns <- c("score", "percentile")

# Extract and filter table1
# table1_all_rows <- table1
# table1 <- filter_real_data(table1_all_rows, key_columns)

table2_all_rows <- table2
table2 <- filter_real_data(table2_all_rows, key_columns)

# Print the filtered table
print(table1)
print(table2)

# table2 <- convert_columns(df = table2)

table2[1, "scale"] <- "Attention"
table2[2, "scale"] <- "Emotion Regulation"
table2[3, "scale"] <- "Flexibility"
table2[4, "scale"] <- "Inhibitory Control"
table2[5, "scale"] <- "Initiation"
table2[6, "scale"] <- "Organization"
table2[7, "scale"] <- "Planning"
table2[8, "scale"] <- "Self-Monitoring"
table2[9, "scale"] <- "Working Memory"

keep <- c("scale", "score", "ci_95", "percentile")

# Selecting the columns in keep for both tables
table1 <- table1[, keep, drop = FALSE]
table2 <- table2[, keep, drop = FALSE]

# Binding rows
table <- rbind(table1, table2)

Mutate

table <- bwu::gpluck_make_columns(
  data = table,
  test = params$test,
  test_name = params$test_name,
  raw_score = NA,
  range = NA,
  domain = "ADHD",
  subdomain = "Executive Function",
  narrow = NA,
  pass = NA,
  verbal = NA,
  timed = NA,
  test_type = "rating_scale",
  score_type = "standard_score",
  description = NA,
  result = NA
)

table <-
  dplyr::relocate(table,
    c(test, test_name),
    .before = scale
  ) |>
  dplyr::relocate(c(raw_score), .before = score)

Test score ranges

table <- bwu::gpluck_make_score_ranges(table, test_type = "rating_scale")

Narrow subdomains

table <-
  dplyr::mutate(table,
    narrow = dplyr::case_when(
      scale == "Full Scale" ~ "Overall Executive Function",
      scale == "Attention" ~ "Attention",
      scale == "Emotion Regulation" ~ "Emotion Regulation",
      scale == "Flexibility" ~ "Flexibility",
      scale == "Inhibitory Control" ~ "Inhibitory Control",
      scale == "Initiation" ~ "Initiation",
      scale == "Organization" ~ "Organization",
      scale == "Planning" ~ "Planning",
      scale == "Self-Monitoring" ~ "Self-Monitoring",
      scale == "Working Memory" ~ "Working Memory",
      TRUE ~ as.character(narrow)
    )
  )


# if (params$test == "cefi_sr" ||
#     params$test == "cefi_sr_12-18") {
#   table <-
#     dplyr::mutate(table,
#       narrow = dplyr::case_when(
#         scale == "CEFI-SR Full Scale" ~ "Overall Executive Function",
#         scale == "CEFI-SR Attention" ~ "Attention",
#         scale == "CEFI-SR Emotion Regulation" ~ "Emotion Regulation",
#         scale == "CEFI-SR Flexibility" ~ "Flexibility",
#         scale == "CEFI-SR Inhibitory Control" ~ "Inhibitory Control",
#         scale == "CEFI-SR Initiation" ~ "Initiation",
#         scale == "CEFI-SR Organization" ~ "Organization",
#         scale == "CEFI-SR Planning" ~ "Planning",
#         scale == "CEFI-SR Self-Monitoring" ~ "Self-Monitoring",
#         scale == "CEFI-SR Working Memory" ~ "Working Memory",
#         TRUE ~ as.character(narrow)
#       )
#     )
# } else {
#   table <-
#     dplyr::mutate(table,
#       narrow = dplyr::case_when(
#         scale == "CEFI-OR Full Scale" ~ "Overall Executive Function",
#         scale == "CEFI-OR Attention" ~ "Attention",
#         scale == "CEFI-OR Emotion Regulation" ~ "Emotion Regulation",
#         scale == "CEFI-OR Flexibility" ~ "Flexibility",
#         scale == "CEFI-OR Inhibitory Control" ~ "Inhibitory Control",
#         scale == "CEFI-OR Initiation" ~ "Initiation",
#         scale == "CEFI-OR Organization" ~ "Organization",
#         scale == "CEFI-OR Planning" ~ "Planning",
#         scale == "CEFI-OR Self-Monitoring" ~ "Self-Monitoring",
#         scale == "CEFI-OR Working Memory" ~ "Working Memory",
#         TRUE ~ as.character(narrow)
#       )
#     )
# }

Scale descriptions

table <-
  dplyr::mutate(table,
    description = dplyr::case_when(
      scale == "Full Scale" ~
        "overall level of executive functioning",
      scale == "Attention" ~
        "i.e., avoid distractions, concentrate on tasks, and sustain attention",
      scale == "Emotion Regulation" ~
        "i.e., control and manage emotions, including staying calm when handling small problems and reacting with the right level of emotion",
      scale == "Flexibility" ~
        "i.e., adjust behavior to meet circumstances, including coming up with different ways to solve problems, changing behavior when needed, and being able to come up with new ways to reach a goal",
      scale == "Inhibitory Control" ~
        "i.e., control behavior or impulses, including thinking about consequences before acting, maintaining self-control, and thinking before speaking",
      scale == "Initiation" ~
        "i.e., begin tasks or projects on own, including starting tasks easily, being motivated, and taking the initiative when needed",
      scale == "Organization" ~
        "i.e., manage personal effects, work, or multiple tasks, including organizing tasks and thoughts well, managing time effectively, and working neatly",
      scale == "Planning" ~
        "i.e., develop and implement strategies to accomplish tasks, including planning ahead and making good decisions",
      scale == "Self-Monitoring" ~
        "i.e., evaluate own behavior in order to determine when a different approach is necessary, including noticing and fixing mistakes, knowing when help is required, and understanding when a task is completed",
      scale == "Working Memory" ~
        "i.e., keep information in mind that is important for knowing what to do and how to do it, including remembering important things, instructions, and steps",
      TRUE ~ as.character(description)
    )
  )



# if (params$test == "cefi_sr" ||
#     params$test == "cefi_sr_12-18") {
#   table <-
#     dplyr::mutate(table,
#       description = dplyr::case_when(
#         scale == "CEFI-SR Full Scale" ~
#           "overall level of executive functioning",
#         scale == "CEFI-SR Attention" ~
#           "i.e., avoid distractions, concentrate on tasks, and sustain attention",
#         scale == "CEFI-SR Emotion Regulation" ~
#           "i.e., control and manage emotions, including staying calm when handling small problems and reacting with the right level of emotion",
#         scale == "CEFI-SR Flexibility" ~
#           "i.e., adjust behavior to meet circumstances, including coming up with different ways to solve problems, changing behavior when needed, and being able to come up with new ways to reach a goal",
#         scale == "CEFI-SR Inhibitory Control" ~
#           "i.e., control behavior or impulses, including thinking about consequences before acting, maintaining self-control, and thinking before speaking",
#         scale == "CEFI-SR Initiation" ~
#           "i.e., begin tasks or projects on own, including starting tasks easily, being motivated, and taking the initiative when needed",
#         scale == "CEFI-SR Organization" ~
#           "i.e., manage personal effects, work, or multiple tasks, including organizing tasks and thoughts well, managing time effectively, and working neatly",
#         scale == "CEFI-SR Planning" ~
#           "i.e., develop and implement strategies to accomplish tasks, including planning ahead and making good decisions",
#         scale == "CEFI-SR Self-Monitoring" ~
#           "i.e., evaluate own behavior in order to determine when a different approach is necessary, including noticing and fixing mistakes, knowing when help is required, and understanding when a task is completed",
#         scale == "CEFI-SR Working Memory" ~
#           "i.e., keep information in mind that is important for knowing what to do and how to do it, including remembering important things, instructions, and steps",
#         TRUE ~ as.character(description)
#       )
#     )
# } else {
#   table <-
#     dplyr::mutate(table,
#       description = dplyr::case_when(
#         scale == "CEFI-OR Full Scale" ~
#           "overall level of executive functioning",
#         scale == "CEFI-OR Attention" ~
#           "i.e., avoid distractions, concentrate on tasks, and sustain attention",
#         scale == "CEFI-OR Emotion Regulation" ~
#           "i.e., control and manage emotions, including staying calm when handling small problems and reacting with the right level of emotion",
#         scale == "CEFI-OR Flexibility" ~
#           "i.e., adjust behavior to meet circumstances, including coming up with different ways to solve problems, changing behavior when needed, and being able to come up with new ways to reach a goal",
#         scale == "CEFI-OR Inhibitory Control" ~
#           "i.e., control behavior or impulses, including thinking about consequences before acting, maintaining self-control, and thinking before speaking",
#         scale == "CEFI-OR Initiation" ~
#           "i.e., begin tasks or projects on own, including starting tasks easily, being motivated, and taking the initiative when needed",
#         scale == "CEFI-OR Organization" ~
#           "i.e., manage personal effects, work, or multiple tasks, including organizing tasks and thoughts well, managing time effectively, and working neatly",
#         scale == "CEFI-OR Planning" ~
#           "i.e., develop and implement strategies to accomplish tasks, including planning ahead and making good decisions",
#         scale == "CEFI-OR Self-Monitoring" ~
#           "i.e., evaluate own behavior in order to determine when a different approach is necessary, including noticing and fixing mistakes, knowing when help is required, and understanding when a task is completed",
#         scale == "CEFI-OR Working Memory" ~
#           "i.e., keep information in mind that is important for knowing what to do and how to do it, including remembering important things, instructions, and steps",
#         TRUE ~ as.character(description)
#       )
#     )
# }

Glue results

if (params$test == "cefi_sr" || params$test == "cefi_sr_12-18") {
  table <-
    dplyr::mutate(table,
      result = dplyr::case_when(
        scale == "Full Scale" ~ glue::glue(
          "- {patient}'s self-reported {description} was {range}.\n"
        ),
        scale == "Attention" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Emotion Regulation" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Flexibility" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Inhibitory Control" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Initiation" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Organization" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Planning" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Self-Monitoring" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Working Memory" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        TRUE ~ as.character(result)
      )
    )
} else {
  table <-
    dplyr::mutate(table,
      result = dplyr::case_when(
        scale == "Full Scale" ~ glue::glue(
          "- {patient}'s observer-reported {description} was {range}.\n"
        ),
        scale == "Attention" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Emotion Regulation" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Flexibility" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Inhibitory Control" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Initiation" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Organization" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Planning" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Self-Monitoring" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Working Memory" ~ glue::glue(
          "- {patient}'s observer-reported {narrow} ({description}) was {range}.\n"
        ),
        TRUE ~ as.character(result)
      )
    )
}

Finalize and save

Write/save CEFI csv file

test <- params$test
vroom::vroom_write(
  table,
  here::here("data", "csv", paste0(test, ".csv")),
  delim = ",",
  col_names = TRUE,
  na = ""
)

Pluck Text

# save file as path
# file <- fs::as_fs_path(params$file)

# Function to extract text from PDF
get_text <- function(file) {
  tryCatch(
    {
      txt <- pdftools::pdf_text(file) |>
        stringr::str_split("\n") |>
        unlist()
      return(txt)
    },
    error = function(e) {
      message("Error reading PDF: ", e)
      return(NULL)
    }
  )
}

# CEFI Self-Report
if (params$test == "cefi_sr" || params$test == "cefi_sr_12-18") {
  ## extract text
  cefi_sr_txt <- get_text(file)
  if (!is.null(cefi_sr_txt)) {
    # Replace long spaces with a col break symbol
    cefi_sr_squished <- stringr::str_replace_all(cefi_sr_txt, "\\s{2,}", "- ") |>
      stringr::str_remove_all(",")

    # save as markdown
    readr::write_lines(
      cefi_sr_squished,
      here::here("cefi_sr_text.md"),
      sep = "\n"
    )
    # save as quarto
    readr::write_lines(
      cefi_sr_squished,
      here::here("cefi_sr_text.qmd"),
      sep = "\n"
    )
    # save as text
    readr::write_lines(
      cefi_sr_squished,
      here::here("cefi_sr_text.txt"),
      sep = "\n"
    )
  }

  # CEFI Observer-Report
} else if (params$test == "cefi_or" || params$test == "cefi_or_5-18") {
  ## extract text
  cefi_or_txt <- get_text(file)
  if (!is.null(cefi_or_txt)) {
    # Replace long spaces with a col break symbol
    cefi_or_squished <- stringr::str_replace_all(cefi_or_txt, "\\s{2,}", "- ") |>
      stringr::str_remove_all(",")

    # save as markdown
    readr::write_lines(
      cefi_or_squished,
      here::here("cefi_or_textMOM.md"),
      sep = "\n"
    )
    # save as quarto
    readr::write_lines(
      cefi_or_squished,
      here::here("cefi_or_textMOM.qmd"),
      sep = "\n"
    )
    # save as text
    readr::write_lines(
      cefi_or_squished,
      here::here("cefi_or_textMOM.txt"),
      sep = "\n"
    )
  }
}

jtrampush/npsych.data documentation built on Feb. 25, 2025, 12:30 a.m.