R/plot-hai-density.R

In healthyR.ai: The Machine Learning and AI Modeling Companion to 'healthyR'

#' Density Histogram Plot
#'
#' @family Distribution Plots
#'
#' @author Steven P. Sanderson II, MPH
#'
#' @details This will produce a density plot of the density information that is
#' produced from the function `hai_get_density_data_tbl`. It will look for an attribute
#' from the `.data` param to ensure the function was used.
#'
#' @description this will produce a `ggplot2` or `plotly` histogram plot of the
#' density information provided from the `hai_get_density_data_tbl` function.
#'
#' @param .data The data that is produced from using `hai_get_density_data_tbl`
#' @param .dist_name_col The column that has the distribution name, should be
#' distribution and that is set as the default.
#' @param .x_col The x value from the tidied density object.
#' @param .y_col The y value from the tidied density object.
#' @param .size The size parameter for ggplot.
#' @param .alpha The alpha parameter for ggplot.
#' @param .interactive This is a Boolean fo TRUE/FALSE and is defaulted to FALSE.
#' TRUE will produce a `plotly` plot.
#'
#' @examples
#' library(dplyr)
#'
#' df <- hai_scale_zero_one_vec(.x = mtcars$mpg) %>%
#'   hai_distribution_comparison_tbl()
#'
#' tidy_density_tbl <- hai_get_density_data_tbl(df)
#'
#' hai_density_plot(
#'   .data = tidy_density_tbl,
#'   .dist_name_col = distribution,
#'   .x_col = x,
#'   .y_col = y,
#'   .alpha = 0.5,
#'   .interactive = FALSE
#' )
#'
#' @return
#' A plot, either `ggplot`2 or `plotly`
#'
#' @export
#'

hai_density_plot <- function(.data, .dist_name_col, .x_col, .y_col,
                             .size = 1, .alpha = 0.382, .interactive = FALSE) {

  # Tidyeval ----
  dist_name_var <- rlang::enquo(.dist_name_col)
  x_col_var <- rlang::enquo(.x_col)
  y_col_var <- rlang::enquo(.y_col)
  size <- as.numeric(.size)
  alpha <- as.numeric(.alpha)

  dnv_name <- rlang::quo_name(dist_name_var)
  xcv_name <- rlang::quo_name(x_col_var)
  ycv_name <- rlang::quo_name(y_col_var)

  # Checks ----
  if (rlang::quo_is_missing(dist_name_var) |
    rlang::quo_is_missing(x_col_var) |
    rlang::quo_is_missing(y_col_var)
  ) {
    rlang::abort(
      "All parameters must be supplied:
       * .dist_name_col,
       * .x_col, and
       * .y_col"
    )
  }

  if (!is.numeric(alpha) | (alpha > 1) | (alpha < 0)) {
    rlang::abort("The .alpha parameter must be a number between 0 and 1")
  }

  if (!is.numeric(size) | (size <= 0)) {
    rlang::abort("The .size parameter must be a number greater than 0")
  }

  # Data setup ----
  data_tbl <- tibble::as_tibble(.data) %>%
    dplyr::ungroup() %>%
    dplyr::select(
      {{ dist_name_var }},
      {{ x_col_var }},
      {{ y_col_var }}
    )

  if (!attributes(.data)$tibble_type == "hai_density_data_tbl") {
    rlang::abort("Attibute of 'hai_density_data_tbl' is missing.
                 Did yo use the 'hai_get_density_data_tbl()' function?")
  }

  # Plots ---
  plt <- ggplot2::ggplot(
    data = data_tbl,
    mapping = ggplot2::aes_string(
      x = xcv_name,
      y = ycv_name,
      color = dnv_name,
      group = dnv_name
    )
  ) +
    ggplot2::geom_line(size = size, alpha = alpha) +
    ggplot2::theme_minimal() +
    ggplot2::labs(
      title = "Distribution Density Comparison",
      color = "Distribution",
      x = "",
      y = "Desnsity"
    ) +
    ggplot2::theme(legend.position = "bottom")

  if (.interactive) {
    plt <- plotly::ggplotly(plt)
  }

  # Return ----
  return(plt)
}