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funky_heatmap.R
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funky_heatmap.R
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#' Generate a funky heatmaps for benchmarks
#'
#' Allows generating heatmap-like visualisations for benchmark data
#' frames. Funky heatmaps can be fine-tuned by providing annotations of the
#' columns and rows, which allows assigning multiple palettes or geometries
#' or grouping rows and columns together in categories.
#'
#' @param data A data frame with items by row and features in the columns.
#' Must contain one column named `"id"`.
#'
#' @param column_info A data frame describing which columns in `data` to
#' plot. This data frame should contain the following columns:
#'
#' * `id` (`character`): The corresponding column name in `data`.
#'
#' * `name` (`character`): A label for the column. If `NA` or `""`,
#' no label will be plotted. If this column is missing, `id` will
#' be used to generate the `name` column.
#'
#' * `geom` (`character`): The geom of the column. Must be one of:
#' `"funkyrect"`, `"circle"`, `"rect"`, `"bar"`, `"pie"`, `"text"` or `"image"`.
#' For `"text"`, the corresponding column in `data` must be a `character`.
#' For `"pie"`, the column must be a list of named numeric vectors.
#' For all other geoms, the column must be a `numeric`.
#'
#' * `group` (`character`): The grouping id of each column, must match with
#' `column_groups$group`. If this column is missing or all values are `NA`,
#' columns are assumed not to be grouped.
#'
#' * `palette` (`character`): Which palette to colour the geom by.
#' Each value should have a matching value in `palettes$palette`.
#'
#' * `width`: Custom width for this column (default: 1).
#'
#' * `overlay`: Whether to overlay this column over the previous column.
#' If so, the width of that column will be inherited.
#'
#' * `legend`: Whether or not to add a legend for this column.
#'
#' * `hjust`: Horizontal alignment of the bar, must be between \[0,1\]
#' (only for `geom = "bar"`).
#'
#' * `vjust`: Vertical alignment of the label, must be between \[0,1\]
#' (only for `geom = "text"`).
#'
#' * `size`: Size of the label, must be a numeric value
#' (only for `geom = "text"`).
#'
#' * `label`: Which column to use as a label (only for `geom = "text"`).
#'
#' * `directory`: Which directory to use to find the images (only for `geom = "image"`).
#'
#' * `extension`: The extension of the images (only for `geom = "image"`).
#'
#' * `options` (`list` or `json`): Any of the options above. Any values in this
#' column will be spread across the other columns. This is useful for
#' not having to provide a data frame with 1000s of columns.
#' This column can be a json string.
#'
#' @param row_info A data frame describing the rows of `data`.
#' This data should contain two columns:
#'
#' * `id` (`character`): Corresponds to the column `data$id`.
#'
#' * `group` (`character`): The group of the row.
#' If all are `NA`, the rows will not be split up into groups.
#'
#' @param column_groups A data frame describing of how to group the columns
#' in `column_info`. Can consist of the following columns:
#'
#' * `group` (`character`): The corresponding group in `column_info$group`.
#' * `palette` (`character`, optional): The palette used to colour the
#' column group backgrounds.
#' * `level1` (`character`): The label at the highest level.
#' * `level2` (`character`, optional): The label at the middle level.
#' * `level3` (`character`, optional): The label at the lowest level
#' (not recommended).
#'
#' @param row_groups A data frame describing of how to group the rows
#' in `row_info`. Can consist of the following columns:
#'
#' * `group` (`character`): The corresponding group in `row_info$group`.
#' * `level1` (`character`): The label at the highest level.
#' * `level2` (`character`, optional): The label at the middle level.
#' * `level3` (`character`, optional): The label at the lowest level
#' (not recommended).
#'
#' @param palettes A named list of palettes. Each entry in `column_info$palette`
#' should have an entry in this object. If an entry is missing, the type
#' of the column will be inferred (categorical or numerical) and one of the
#' default palettes will be applied. Alternatively, the name of one of the
#' standard palette names can be used:
#'
#' * `numerical`: `"Greys"`, `"Blues"`, `"Reds"`, `"YlOrBr"`, `"Greens"`
#' * `categorical`: `"Set3"`, `"Set1"`, `"Set2"`, `"Dark2"`
#'
#' @param position_args Sets parameters that affect positioning within a
#' plot, such as row and column dimensions, annotation details, and the
#' expansion directions of the plot. See `position_arguments()` for more information.
#'
#' @param scale_column Whether or not to apply min-max scaling to each
#' numerical column.
#'
#' @param add_abc Whether or not to add subfigure labels to the different
#' columns groups.
#'
#' @param removed_entries Which methods to not show in the rows. Missing methods
#' are replaced by a "Not shown" label.
#'
#' @param col_annot_offset DEPRECATED: use `position_args = position_arguments(col_annot_offset = ...)` instead.
#' @param col_annot_angle DEPRECATED: use `position_args = position_arguments(col_annot_angle = ...)` instead.
#' @param expand DEPRECATED: use `position_args = position_arguments(expand_* = ...)` instead.
#'
#' @importFrom ggforce geom_arc_bar geom_circle geom_arc
#' @importFrom cowplot theme_nothing
#'
#' @returns A ggplot. `.$width` and `.$height` are suggested dimensions for
#' storing the plot with [ggsave()].
#'
#' @export
#'
#' @examples
#' library(tibble, warn.conflicts = FALSE)
#'
#' data("mtcars")
#'
#' data <- rownames_to_column(mtcars, "id")
#'
#' funky_heatmap(data)
funky_heatmap <- function(
data,
column_info = NULL,
row_info = NULL,
column_groups = NULL,
row_groups = NULL,
palettes = NULL,
position_args = position_arguments(),
scale_column = TRUE,
add_abc = TRUE,
removed_entries = NULL,
col_annot_offset,
col_annot_angle,
expand) {
# validate input objects
data <- verify_data(data)
column_info <- verify_column_info(column_info, data)
row_info <- verify_row_info(row_info, data)
column_groups <- verify_column_groups(column_groups, column_info)
row_groups <- verify_row_groups(row_groups, row_info)
palettes <- verify_palettes(palettes, column_info, data)
# check deprecated arguments
if (!missing(col_annot_offset)) {
warning("Argument `col_annot_offset` is deprecated. Use `position_arguments(col_annot_offset = ...)` instead.")
position_args$col_annot_offset <- col_annot_offset
}
if (!missing(col_annot_angle)) {
warning("Argument `col_annot_angle` is deprecated. Use `position_arguments(col_annot_angle = ...)` instead.")
position_args$col_annot_angle <- col_annot_angle
}
if (!missing(expand)) {
warning("Argument `expand` is deprecated. Use `position_arguments(expand_* = ...)` instead.")
for (name in names(expand)) {
position_args[[paste0("expand_", name)]] <- expand[[name]]
}
}
# todo: add column groups to verify_palettes
geom_positions <- calculate_geom_positions(
data,
column_info,
row_info,
column_groups,
row_groups,
palettes,
position_args,
scale_column,
add_abc,
removed_entries
)
compose_ggplot(
geom_positions,
position_args
)
}