# plot_icons: Plot an icon array of a population. In riskyr: Rendering Risk Literacy more Transparent

## Description

`plot_icons` plots a population of which individual's condition has been classified correctly or incorrectly as icons from a sufficient and valid set of 3 essential probabilities (`prev`, and `sens` or its complement `mirt`, and `spec` or its complement `fart`) or existing frequency information `freq` and a population size of `N` individuals.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ```plot_icons(prev = num\$prev, sens = num\$sens, mirt = NA, spec = num\$spec, fart = NA, N = freq\$N, type = "array", ident.order = c("hi", "mi", "fa", "cr"), icon.colors = pal[c("hi", "mi", "fa", "cr")], icon.types = 22, icon.border.col = grey(0.1, 0.5), icon.border.lwd = 1.5, transparency = 0.5, icon.size = NULL, block.d = NULL, border.d = 0.1, block.size.row = 10, block.size.col = 10, nblocks.row = NULL, nblocks.col = NULL, fill.array = "left", fill.blocks = "rowwise", show.accu = TRUE, w.acc = 0.5, title.lbl = txt\$scen.lbl, type.lbls = txt[c("hi.lbl", "mi.lbl", "fa.lbl", "cr.lbl")], cex.lbl = 0.85) ```

## Arguments

 `prev` The condition's prevalence `prev` (i.e., the probability of condition being `TRUE`). `sens` The decision's sensitivity `sens` (i.e., the conditional probability of a positive decision provided that the condition is `TRUE`). `sens` is optional when its complement `mirt` is provided. `mirt` The decision's miss rate `mirt` (i.e., the conditional probability of a negative decision provided that the condition is `TRUE`). `mirt` is optional when its complement `sens` is provided. `spec` The decision's specificity value `spec` (i.e., the conditional probability of a negative decision provided that the condition is `FALSE`). `spec` is optional when its complement `fart` is provided. `fart` The decision's false alarm rate `fart` (i.e., the conditional probability of a positive decision provided that the condition is `FALSE`). `fart` is optional when its complement `spec` is provided. `N` The number of individuals in the population. A suitable value of `N` is computed, if not provided. If N is 100,000 or greater it is reduced to 10,000 for the array types if the frequencies allow it. `type` The icons can be arranged in different ways resulting in different types of displays: `type = "array"`: Icons are plotted in a classical icon array (default). Icons can be arranged in blocks using `block.d`. The order of filling the array can be customized using `fill.array` and `fill.blocks`. `type = "shuffledarray"`: Icons are plotted in an icon array, but positions are shuffled (randomized). Icons can be arranged in blocks using `block.d`. The order of filling the array can be customized using `fill.array` and `fill.blocks`. `type = "mosaic"`: Icons are ordered like in a mosaic plot. The area size displays the relative proportions of their frequencies. `type = "fillequal"`: Icons are positioned into equally sized blocks. Thus, their density reflects the relative proportions of their frequencies. `type = "fillleft"`: Icons are randomly filled from the left. `type = "filltop"`: Icons are randomly filled from the top. `type = "scatter"`: Icons are randomly scattered into the plot. `ident.order` The order in which icon identities (i.e, hi, mi, fa, and cr) are plotted. Default: `ident.order = c("hi", "mi", "fa", "cr")` `icon.colors` Specifies the icon colors as a vector. `icon.types` Specifies the appearance of the icons as a vector. Accepts values from 1 to 25 (see `?points`). `icon.border.col` Specifies the border color of icons (if applicable). `icon.border.lwd` Specifies the border width of icons (if applicable). `transparency` Specifies the transparency for overlapping icons (not `type` "array" and "shuffledarray"). `icon.size` Manually specifies the size of the icons via `cex` (calculated dynamically by default.) `block.d` The distance between blocks (does not apply to "filleft", "filltop", and "scatter") `border.d` The distance of icons to the border. Additional options allow to control the arrangement of the arrays (`type` "array" and "shuffledarray"): `block.size.row` specifies how many icons should be in each block row. `block.size.col` specifies how many icons should be in each block column. `nblocks.row` specifies how many blocks there are in each row. Is calculated by default. `nblocks.col` specifies how many blocks are there in each column. Is calculated by default. `fill.array` specifies how the blocks are filled into the array (Options "left" (default) and "top"). `fill.blocks` specifies how icons within blocks are filled (Options: `fill.blocks = "rowwise"` (default) and `fill.blocks = "colwise"`) `show.accu` Option for showing current accuracy metrics `accu` in the plot. Default: `show.accu = TRUE`. `w.acc` Weigthing parameter `w` used to compute weighted accuracy `w.acc` in `comp_accu`. Default: `w.acc = .50`. Various other options allow the customization of text labels and colors: `title.lbl` Text label to set plot title. `type.lbls` Text labels for icon types to be displayed in legend. `cex.lbl` Scaling factor for the size of text labels (e.g., on axes, legend, margin text). Default: `cex.lbl = .85`.

## Details

If probabilities are provided, a new list of natural frequencies `freq` is computed by `comp_freq`. By contrast, if no probabilities are provided, the values currently contained in `freq` are used. By default, `comp_freq` rounds frequencies to nearest integers to avoid decimal values in `freq`.

Other visualization functions: `plot.riskyr`, `plot_curve`, `plot_fnet`, `plot_mosaic`, `plot_plane`, `plot_tree`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33``` ```# ways to work: plot_icons() # => plots icon array for default population (with default type = "array") plot_icons(type = "shuffledarray") # => icon array with shuffled IDs plot_icons(type = "mosaic", N = 1000) # => areas as in mosaic plot plot_icons(type = "fillequal", N = 1000) # => areas of equal size (density reflects probability) plot_icons(type = "fillleft", N = 1000) # => icons filled from left to right (in columns) plot_icons(type = "filltop", N = 1000) # => icons filled from top to bottom (in rows) plot_icons(icon.types = c(21,23,24,23), block.size.row = 5, block.size.col = 5, #nblocks.row = 2, nblocks.col = 2, block.d = 0.5, border.d = 0.9) plot_icons(type = "scatter", N = 1000) # => icons randomly scattered. # some variants: plot_icons(N = 800, type = "array", icon.types = c(21,22,23,24), block.d = 0.5, border.d = 0.5) plot_icons(N = 1250, sens = 0.9, spec = 0.9, prev = 0.9, icon.types = c(21,23,24,23), block.size.row = 10, block.size.col = 5, nblocks.row = 5, nblocks.col = 5, block.d = 0.8, border.d = 0.2, fill.array = "top") plot_icons(N = 800, type = "shuffledarray", icon.types = c(21,23,24,22), block.d = 0.5, border.d = 0.5) plot_icons(N = 800, type = "shuffledarray", icon.types = c(21,23,24,22), icon.border.col = grey(.33, .99), icon.border.lwd = 3) plot_icons(N = 800, type = "fillequal", icon.types = c(21,22,22,21), icon.border.lwd = .5, cex = 3) ```