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

Brown EF/A

Setup

library(dplyr)
library(fs)
library(hablar)
library(here)
library(knitr)
library(magrittr)
library(miniUI)
library(readr)
library(rJava)
library(rmarkdown)
library(shiny)
library(tabulapdf)
library(tibble)
library(tidyr)
library(bwu)
library(rmdformats)
# Set JAVA environment
Sys.setenv(
  JAVA_HOME =
    "/Library/Java/JavaVirtualMachines/temurin-11.jdk/Contents/Home"
)
options(java.parameters = "-Xmx16000m")
# Set knitr options
knitr::opts_chunk$set(
  root.dir = normalizePath("./"),
  echo = FALSE,
  message = FALSE,
  warning = FALSE,
  error = TRUE
)

Patient

# patient <- "Biggie"
patient <- params$patient

Test

test <- params$test
test_name <- params$test_name

Load PDF file and save as file.path

# pdf_file <- file.path(file.choose())
# pdf_file <- "/Users/joey/neuropsychology/Biggie/pdf/Brown-EF-A-Scales---Individual-Report_51189762_1693167228924.pdf"
pdf_file <- params$file

Pages

pages <- params$pages

Write/Read PDF file.path

writeLines(pdf_file, here::here(patient, "pre_csv", paste0(test, ".pdf")))

file <- readLines(here::here(patient, "pre_csv", paste0(test, ".pdf")))

Locate areas or Extract areas

# areas <- tabulapdf::locate_areas(file = pdf_file, pages = c(2))
# df <- tabulapdf::extract_areas(file = pdf_file, pages = c(2))

areas <- list(
  brown_efa_parent = c(500, 51, 589, 562)
)

# areas <- bwu::gpluck_locate_areas(
#   file = pdf_file,
#   pages = pages
# )

# saveRDS(areas, here::here(patient, "pre_csv", paste0(test, "_areas.rds")))

# areas <- readRDS(here::here(patient, "pre_csv", paste0(test, "_areas.rds")))

Extract tables

plucked_tables <- bwu::gpluck_extract_tables(
  file = pdf_file,
  pages = pages,
  area = areas,
  guess = NULL,
  method = "stream",
  output = "matrix"
)

Tidy Tables

Convert to tibble and format

df <- data.frame(plucked_tables[[1]])

# Rename columns
colnames1 <- c(
  "scale",
  "description",
  "raw_score",
  "score",
  "percentile",
  "ci_95")
colnames(df) <- colnames1

# Convert columns to double
to_double <- c("score", "percentile")
df[to_double] <- lapply(df[to_double], as.numeric)

Scale names

# Modify 'scale' value based on params$test
if (params$test == "brown_efa_parent") {
  df[1, "scale"] <- "Brown EF/A PR Activation"
  df[2, "scale"] <- "Brown EF/A PR Focus"
  df[3, "scale"] <- "Brown EF/A PR Effort"
  df[4, "scale"] <- "Brown EF/A PR Emotion"
  df[5, "scale"] <- "Brown EF/A PR Memory"
  df[6, "scale"] <- "Brown EF/A PR Action"
  df[7, "scale"] <- "Brown EF/A PR Total Composite"
} else {
  df[1, "scale"] <- "Brown EF/A SR Attention"
  df[2, "scale"] <- "Brown EF/A SR Emotion Regulation"
  df[3, "scale"] <- "Brown EF/A SR Flexibility"
  df[4, "scale"] <- "Brown EF/A SR Inhibitory Control"
  df[5, "scale"] <- "Brown EF/A SR Initiation"
  df[6, "scale"] <- "Brown EF/A SR Organization"
  df[7, "scale"] <- "Brown EF/A SR Planning"
  df[8, "scale"] <- "Brown EF/A SR Self-Monitoring"
  df[9, "scale"] <- "Brown EF/A SR Working Memory"
}
# TODO: teacher report

Format Tables

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

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

Test score ranges

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

Narrow subdomains

if (params$test == "brown_efa_parent") {
  df <-
    dplyr::mutate(df,
      narrow = dplyr::case_when(
        scale == "Brown EF/A PR Activation" ~ "Activation",
        scale == "Brown EF/A PR Focus" ~ "Focus",
        scale == "Brown EF/A PR Effort" ~ "Effort",
        scale == "Brown EF/A PR Emotion" ~ "Emotion",
        scale == "Brown EF/A PR Memory" ~ "Memory",
        scale == "Brown EF/A PR Action" ~ "Action",
        scale == "Brown EF/A PR Total Composite" ~ "Overall Executive Function",
        TRUE ~ as.character(narrow)
      )
    )
} else {
  df <-
    dplyr::mutate(df,
      narrow = dplyr::case_when(
        scale == "Brown EF/A SR Activation" ~ "Activation",
        scale == "Brown EF/A SR Focus" ~ "Focus",
        scale == "Brown EF/A SR Effort" ~ "Effort",
        scale == "Brown EF/A SR Emotion" ~ "Emotion",
        scale == "Brown EF/A SR Memory" ~ "Memory",
        scale == "Brown EF/A SR Action" ~ "Action",
        scale == "Brown EF/A SR Total Composite" ~ "Overall Executive Function",
        TRUE ~ as.character(narrow)
      )
    )
}

Scale descriptions

df <-
  df |>
  mutate(
    description = case_when(
      scale == "Brown EF/A PR Activation" ~ "Organizing, prioritizing, and activating to work (parent rated)",
      scale == "Brown EF/A PR Focus" ~ "Focusing, sustaining, and shifting attention to tasks (parent rated)",
      scale == "Brown EF/A PR Effort" ~ "Regulating alertness, sustaining effort, and adjusting processing speed (parent rated)",
      scale == "Brown EF/A PR Emotion" ~ "Managing frustration and modulating emotions (parent rated)",
      scale == "Brown EF/A PR Memory" ~ "Utilizing working memory and accessing recall (parent rated)",
      scale == "Brown EF/A PR Action" ~ "Monitoring and self-regulating action (parent rated)",
      scale == "Brown EF/A PR Total Composite" ~ "General executive functioning in daily life (parent rated)",
      TRUE ~ as.character(description)
    )
  )

Glue results

if (params$test == "brown_efa_parent") {
  df <-
    dplyr::mutate(df,
      result = dplyr::case_when(
        scale == "Brown EF/A PR Activation" ~ glue::glue(
          "- {patient}'s self-reported {description} was {range}.\n"
        ),
        scale == "Brown EF/A PR Focus" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A PR Effort" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A PR Emotion" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A PR Memory" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A PR Action" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A PR Total Composite" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        TRUE ~ as.character(result)
      )
    )
} else {
  df <-
    dplyr::mutate(df,
      result = dplyr::case_when(
        scale == "Brown EF/A SR Activation" ~ glue::glue(
          "- {patient}'s self-reported {description} was {range}.\n"
        ),
        scale == "Brown EF/A SR Focus" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A SR Effort" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A SR Emotion" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A SR Memory" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A SR Action" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        scale == "Brown EF/A SR Total Composite" ~ glue::glue(
          "- {patient}'s self-reported {narrow} ({description}) was {range}.\n"
        ),
        TRUE ~ as.character(result)
      )
    )
}

Finalize and save

Write/save csv files

test <- params$test
readr::write_csv(
  df,
  here::here(patient, "csv", paste0(test, ".csv")), 
  col_names = TRUE, 
  na = ""
  )

Pluck Text

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

# Brown EFA Parent
if (params$test == "brown_efa_parent") {

  ## extract text
  get_text <- function(file) {
    txt <- pdftools::pdf_text(file) |>
      stringr::str_split("\n") |>
      unlist()
  }
  brown_efa_parent_txt <- pdftools::pdf_text(file) |>
    stringr::str_split("\n") |>
    unlist()
  brown_efa_parent_txt

  # Replace long spaces with a col break symbol
  brown_efa_parent_squished <-
    stringr::str_replace_all(brown_efa_parent_txt, "\\s{2,}", "- ") |>
    stringr::str_remove_all(",")
  brown_efa_parent_squished

  # save as markdown
  readr::write_lines(
    brown_efa_parent_squished, 
    here::here(patient, "brown_efa_parent_text.md"), 
    sep = "\n")
  # save as quarto
  readr::write_lines(
    brown_efa_parent_squished, 
    here::here(patient, "brown_efa_parent_text.qmd"), 
    sep = "\n")
  # save as text
  readr::write_lines(brown_efa_parent_squished, 
    here::here(patient, "brown_efa_parent_text.txt"), 
    sep = "\n"
    )

# Brown EFA Self Report
} else if (params$test == "brown_efa_self") {

  ## extract text
  get_text <- function(file) {
    txt <- pdftools::pdf_text(file) |>
      stringr::str_split("\n") |>
      unlist()
  }
  brown_efa_self_txt <- pdftools::pdf_text(file) |>
    stringr::str_split("\n") |>
    unlist()
  brown_efa_self_txt

  # Replace long spaces with a col break symbol
  brown_efa_self_squished <-
    stringr::str_replace_all(brown_efa_self_txt, "\\s{2,}", "- ") |>
    stringr::str_remove_all(",")
  brown_efa_self_squished

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

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