src/summarize_map.R

#'  Diagnostics for messy joins
#'
#'  given a data frame with two ways to group rows,
#'  summarize and give examples of situations where the mapping is not 1-1
#'
#' @param x_cols tidyselect specification of a set of columns defining objects
#' @param y_cols tidyselect specification of a set of columns defining objects
#'
#' data <- data.frame(
#' 	x=c(1,2,NA,3,4,5,6,6,6,7,7),
#' 	y=c("a",NA,"c","d","d","d","e","f","g","h","h"))
#'
#' data |> summarize_map(
#'   x_cols = x),
#'   y_cols = y))
#' X<-[x]:
#'   |X|: 7                          # number of groups
#'   |is.na.X|: 1                    # number of groups with NA in atleaset 1 col
#'   range(|x|:X): 1, 3              # size range of groups
#' Y<-[y]:
#'   |Y|: 7
#'   |is.na.Y|: 1
#'   range(|y|:Y): 1, 3
#' [X U Y]:                          # grouping by the union of xcols and ycols
#'   |X U Y|: 8
#'   |is.na.XUY|: 2
#'   range(|z|:X U Y): 1, 2
#' [X @ Y]:
#'   |X ~ Y|: 5
#'   |X:X < Y|, |Y:Y < X|: 1, 1
#'   |X:X > Y|, |Y:Y < X|: 3, 3
#' $is.na.X
#'    x y
#' 1 NA c
#'
#' $is.na.Y
#'   x    y
#' 1 2 <NA>
#'
#' $dup.XUY
#'   x y
#' 1 7 h
#' 2 7 h
#'
#' $dup.X
#'   x y
#' 1 6 e
#' 2 6 f
#' 3 6 g
#'
#' $dup.Y
#'   y x
#' 1 d 3
#' 2 d 4
#' 3 d 5
#' @export
summarize_map <- function(
  data,
  x_cols,
  y_cols,
  n_examples = 4,
  verbose = FALSE) {

    # convert column selections named vectors of column indices into data
    x_cols <- tidyselect::eval_select(rlang::enquo(x_cols), data)
    y_cols <- tidyselect::eval_select(rlang::enquo(y_cols), data)
    xUy_cols <- union(x_cols, y_cols)
    names(xUy_cols) <- names(data[xUy_cols])
    
    if(verbose) {
        cat("The following is a report of the relationship between two different ways of identifying instances\n")
    }

    # example rows
    problems <- list()

    count_xUy <- data |>
        dplyr::count(dplyr::across(tidyselect::all_of(xUy_cols))) |>
        dplyr::ungroup()
    count_x <- count_xUy |>
        dplyr::count(dplyr::across(tidyselect::all_of(names(x_cols))), name = "size") |>
        dplyr::ungroup()
    count_y <- count_xUy |>
        dplyr::count(dplyr::across(tidyselect::all_of(names(y_cols))), name = "size") |>
        dplyr::ungroup()
    
    if (verbose) {
        cat("\nProperties of X identifiers:\n")
    }
    cat("X<-[", paste(names(x_cols), collapse = ", "), "]:\n", sep = "")
    cat("  |X|: ", count_x |> stats::na.omit(method = "r") |> nrow(), sep = "")
    
    na_count <- data |>
        dplyr::select(tidyselect::all_of(x_cols)) |>
        stats::complete.cases() |>
        magrittr::not() |>
        sum()
    cat(
        ifelse(
            na_count == 0,
            "",
            paste0(" (", na_count, " NA)")),
        "\n", sep = "")

    size_dist <- count_x |>
        stats::na.omit(method = "r") |>
        dplyr::count(size) |>
        dplyr::ungroup()
    if (nrow(size_dist) < 12) {
        cat("  count*size: ",
            paste(size_dist$n, size_dist$size, sep = "*", collapse = ", "),
            "\n", sep = "")
	} else {
            top <- 1:6
            bottom <- (nrow(size_dist) - 6+1):nrow(size_dist)
            cat("  count*size: ",
                paste(
                    size_dist$n[top],
                    size_dist$size[top], sep = "*", collapse = ", "),
                ", ... ",
                paste(
                    size_dist$n[bottom],
                    size_dist$size[bottom], sep = "*", collapse = ", "),
                "\n", sep="")
	}

    if (verbose) {
        cat("\nProperties of the Y identifiers:\n")
    }
    cat("Y<-[", paste(names(y_cols), collapse = ", "), "]:\n", sep = "")
    cat("  |Y|: ", count_y |> stats::na.omit(method = "r") |> nrow(), sep = "")
    na_count <- data |>
        dplyr:::select(tidyselect::all_of(y_cols)) |>
        stats::complete.cases() |>
        magrittr::not() |>
        sum()
    cat(ifelse(na_count == 0, "", paste0(" (", na_count, " NA)")), "\n", sep = "")
    
    size_dist <- count_y |>
        stats::na.omit(method = "r") |>
        dplyr::count(size) |>
        dplyr::ungroup()
    if (nrow(size_dist) < 12) {
        cat("  count*size: ",
            paste(size_dist$n, size_dist$size, sep = "*", collapse = ", "),
            "\n", sep = "")
    } else {
        top <- 1:6
        bottom <- (nrow(size_dist) - 6+1):nrow(size_dist)
        cat("  count*size: ",
            paste(
                size_dist$n[top],
                size_dist$size[top], sep = "*", collapse = ", "),
            ", ... ",
            paste(
                size_dist$n[bottom],
                size_dist$size[bottom], sep = "*", collapse = ", "),
            "\n", sep="")
    }
    
    if (verbose) {
        cat("\nProperties of the intersection of union of the X and Y identifiers:\n")
    }
    cat("[X U Y]:\n")
    cat("  |X U Y|: ", count_xUy |> stats::na.omit(method = "r") |> nrow(), sep = "")
    na_count <- data |>
        dplyr:::select(!!!xUy_cols) |>
        stats::complete.cases() |>
        magrittr::not() |>
        sum()
    cat(ifelse(na_count == 0, "", paste0(" (", na_count, " NA)")), "\n", sep = "")
    
    size_dist <- count_xUy |>
        stats::na.omit(method = "r") |>
        dplyr::rename(size = n) |>
        dplyr::count(size) |>
        dplyr::ungroup()
    if (nrow(size_dist) < 12) {
        cat("  count*size: ",
            paste(size_dist$n, size_dist$size, sep = "*", collapse = ", "),
            "\n", sep="")
    } else {
        top <- 1:6
        bottom <- (nrow(size_dist) - 6+1):nrow(size_dist)
        cat("  count*size: ",
            paste(
                size_dist$n[top],
                size_dist$size[top], sep = "*", collapse = ", "),
            ", ... ",
            paste(
                size_dist$n[bottom],
                size_dist$size[bottom], sep = "*", collapse = ", "),
            "\n", sep = "")
    }
    

    count_xUy <- count_xUy |> stats::na.omit(method = "r")
    
    if (verbose) {
        cat("Properties of the intersection of the X and Y identifiers:\n")
    }
    cat("[X @ Y]:\n")
    if (verbose) {
        cat("  Number of X and Y identifiers that are 1 to 1:\n")
    }
    cat("  |X ~ Y|: ",
        count_xUy |>
        dplyr::semi_join(
            count_x |> dplyr::filter(size == 1),
            by = names(x_cols)) |>
        dplyr::semi_join(
            count_y |> dplyr::filter(size == 1),
            by = names(y_cols)) |>
        nrow(),
        "\n", sep = "")
    
    if (verbose) {
        cat("  Number of X and Y identifiers where an X identifier maps to multiple Y identifiers:\n")
    }
    cat(
        "  |X:X < Y|, |Y:Y < X|: ",
        count_xUy |>
        dplyr::semi_join(
            count_x |> dplyr::filter(size > 1),
            by = names(x_cols)) |>
        nrow(),
        ", ",
        count_xUy |>
        dplyr::count(
            dplyr::across(tidyselect::all_of(names(x_cols))),
            name = "size") |>
        dplyr::filter(size > 1) |>
        nrow(),
        "\n", sep = "")
    
    if (verbose) {
        cat(
            "  Number of X and Y identifiers where a Y identifier maps to ",
            "multiple X identifiers:\n")
    }
    cat(
        "  |X:X > Y|, |Y:Y > X|: ",
        count_xUy |>
        dplyr::semi_join(
            count_y |>
            dplyr::filter(size > 1),
            by = names(y_cols)) |>
        nrow(),
        ", ",
        count_xUy |>
        dplyr::count(
            dplyr::across(tidyselect::all_of(names(y_cols))),
            name = "size") |>
        dplyr::filter(size > 1) |>
        nrow(),
        "\n", sep = "")
    
    #is.na.X
    ex_rows <- data |>
        dplyr:::select(tidyselect::all_of(x_cols)) |>
        stats::complete.cases() |>
        magrittr::not() |>
        which()
    if (length(ex_rows)) {
        if (!is.null(n_examples) && (n_examples < length(ex_rows))) {
            ex_rows <- ex_rows |> sample(n_examples, replace = FALSE)
        }
        problems$is.na.X <- data |>
            dplyr::slice(ex_rows) |>
            dplyr::arrange(dplyr::across(tidyselect::all_of(names(x_cols))))
    }
    
    #is.na.Y
    ex_rows <- data |>
        dplyr:::select(tidyselect::all_of(y_cols)) |>
        stats::complete.cases() |>
        magrittr::not() |>
        which()
    if (length(ex_rows)) {
        if (!is.null(n_examples) && (n_examples < length(ex_rows))) {
            ex_rows <- ex_rows |> sample(n_examples, replace = FALSE)
        }
        problems$is.na.Y <- data |>
            dplyr::slice(ex_rows) |>
            dplyr::arrange(dplyr::across(tidyselect::all_of(names(y_cols))))
    }
    
    #dup.X
    dup.X <- count_xUy |>
        dplyr::filter(n == 1) |>
        dplyr::count(
            dplyr::across(tidyselect::all_of(names(x_cols))),
            name = "size") |>
        dplyr::filter(size > 1) |>
        dplyr::ungroup() |>
        dplyr:::select(-size)
    if (nrow(dup.X) > 1) {
        if (!is.null(n_examples) && (n_examples < nrow(dup.X))) {
            dup.X <- dup.X |> dplyr::sample_n(n_examples, replace = FALSE)
        }
        problems$dup.X <- dup.X |>
            dplyr::left_join(data, by = names(x_cols)) |>
            dplyr::arrange(dplyr::across(tidyselect::all_of(names(x_cols))))
    }
    
    #dup.Y
    dup.Y <- count_xUy |>
        dplyr::filter(n == 1) |>
        dplyr::count(
            dplyr::across(tidyselect::all_of(names(y_cols))),
            name = "size") |>
        dplyr::filter(size > 1) |>
        dplyr::ungroup() |>
        dplyr:::select(-size)
    if (nrow(dup.Y) > 1) {
        if (!is.null(n_examples) && (n_examples < nrow(dup.Y))) {
            dup.Y <- dup.Y |> dplyr::sample_n(n_examples, replace = FALSE)
        }
        problems$dup.Y <- dup.Y |>
            dplyr::left_join(data, by = names(ycols)) |>
            dplyr::arrange(dplyr::across(tidyselect::all_of(names(y_cols))))
    }
    
    #dup.XUY
    dup.XUY <- count_xUy |>
        dplyr::filter(n > 1) |>
        dplyr:::select(-n)
    if (nrow(dup.XUY) > 1) {
        if (!is.null(n_examples) && (n_examples < nrow(dup.XUY))) {
            dup.XUY <- dup.XUY |> dplyr::sample_n(n_examples, replace = FALSE)
        }
        problems$dup.XUY <- dup.XUY |>
            dplyr::left_join(data, by = names(xUy_cols)) |>
            dplyr::arrange(dplyr::across(tidyselect::all_of(names(xUy_cols))))
    }
    if (verbose) {
        cat("Returned instances where:\n")
        cat("\tis.na.X: The X identifier is NA\n")
        cat("\tis.na.Y: The Y identifier is NA\n")
        cat("\tdup.X:   The X identifier is not unique\n")
        cat("\tdup.Y:   The Y identifier is not unique\n")
        cat("\tdup.XUY: The X and Y identifiers together are not unique\n")
    }
    problems
}