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R/init_pal.R
In riskyr: Rendering Risk Literacy more Transparent
Defines functions
init_pal
Documented in
init_pal
## init_pal.R | riskyr
## 2021 12 10
## Define custom color palettes (pal):
## -----------------------------------------------
## pal contains defaults for user inputs.
## (A) Define colors: ----------
## (1) Select and name some colors: ---------
## (1) from unikn:
# seeblau <- rgb(0, 169, 224, max = 255) # seeblau.4 (non-transparent)
# pal_uni_kn = data.frame( ## in one df:
# "seeblau1" = rgb(204, 238, 249, maxColorValue = 255), # 1. seeblau1 (non-transparent)
# "seeblau2" = rgb(166, 225, 244, maxColorValue = 255), # 2. seeblau2 (non-transparent)
# "seeblau3" = rgb( 89, 199, 235, maxColorValue = 255), # 3. seeblau3 (non-transparent)
# "seeblau4" = rgb( 0, 169, 224, maxColorValue = 255), # 4. seeblau4 (= seeblau base color)
# "black" = rgb( 0, 0, 0, maxColorValue = 255), # 5. black
# "seegrau4" = rgb(102, 102, 102, maxColorValue = 255), # 6. grey40 (non-transparent)
# "seegrau3" = rgb(153, 153, 153, maxColorValue = 255), # 7. grey60 (non-transparent)
# "seegrau2" = rgb(204, 204, 204, maxColorValue = 255), # 8. grey80 (non-transparent)
# "seegrau1" = rgb(229, 229, 229, maxColorValue = 255), # 9. grey90 (non-transparent)
# "white" = rgb(255, 255, 255, maxColorValue = 255), # 10. white
# stringsAsFactors = FALSE)
# individual palettes (from unikn):
pal_seeblau <- data.frame( # element:
"seeblau1" = rgb(204, 238, 249, maxColorValue = 255), # 1. seeblau1 (non-transparent): 20%
"seeblau2" = rgb(166, 225, 244, maxColorValue = 255), # 2. seeblau2 (non-transparent): 35%
"seeblau3" = rgb( 89, 199, 235, maxColorValue = 255), # 3. seeblau3 (non-transparent): 65%: preferred color: "seeblau"
"seeblau4" = rgb( 0, 169, 224, maxColorValue = 255), # 4. seeblau4 (non-transparent): 100%
"seeblau5" = rgb( 0, 142, 206, maxColorValue = 255), # 5. seeblau5 (non-transparent): neu
stringsAsFactors = FALSE)
pal_seegruen <- data.frame( # element:
"seegruen1" = rgb(113, 209, 204, maxColorValue = 255), # 1. seegruen1 (non-transparent)
"seegruen2" = rgb( 84, 191, 183, maxColorValue = 255), # 2. seegruen2 (non-transparent)
"seegruen3" = rgb( 10, 163, 152, maxColorValue = 255), # 3. seegruen3 (non-transparent)
"seegruen4" = rgb( 10, 144, 134, maxColorValue = 255), # 4. seegruen4 (non-transparent): preferred color: "seegruen"
"seegruen5" = rgb( 6, 126, 121, maxColorValue = 255), # 5. seegruen5 (non-transparent)
stringsAsFactors = FALSE)
pal_grau <- data.frame( # element:
"grau1" = rgb(225, 226, 229, maxColorValue = 255), # 1. grau1 (non-transparent)
"grau2" = rgb(184, 188, 193, maxColorValue = 255), # 2. grau2 (non-transparent)
"grau3" = rgb(154, 160, 167, maxColorValue = 255), # 3. grau3 (non-transparent): preferred color: "grau"
"grau4" = rgb(115, 120, 126, maxColorValue = 255), # 4. grau4 (non-transparent)
"grau5" = rgb( 77, 80, 84, maxColorValue = 255), # 5. grau5 (non-transparent)
stringsAsFactors = FALSE)
pal_peach <- data.frame( # Element:
"peach1" = rgb(254, 226, 221, maxColorValue = 255), # 1.
"peach2" = rgb(254, 207, 199, maxColorValue = 255), # 2.
"peach3" = rgb(255, 184, 172, maxColorValue = 255), # 3.
"peach4" = rgb(254, 160, 144, maxColorValue = 255), # 4. preferred color: "peach"
"peach5" = rgb(255, 142, 123, maxColorValue = 255), # 5.
stringsAsFactors = FALSE)
pal_petrol <- data.frame( # element:
"petrol1" = rgb(156, 198, 207, maxColorValue = 255), # 1. petrol1 (non-transparent)
"petrol2" = rgb(106, 170, 183, maxColorValue = 255), # 2. petrol2 (non-transparent)
"petrol3" = rgb( 57, 141, 159, maxColorValue = 255), # 3. petrol3 (non-transparent)
"petrol4" = rgb( 7, 113, 135, maxColorValue = 255), # 4. petrol4 (non-transparent): preferred color: "petrol"
"petrol5" = rgb( 3, 95, 114, maxColorValue = 255), # 5. petrol5 (non-transparent)
stringsAsFactors = FALSE)
pal_karpfenblau <- data.frame( # element:
"karpfenblau1" = rgb(180, 188, 214, maxColorValue = 255), # 1. karpfenblau1 (non-transparent)
"karpfenblau2" = rgb(130, 144, 187, maxColorValue = 255), # 2. karpfenblau2 (non-transparent)
"karpfenblau3" = rgb( 88, 107, 164, maxColorValue = 255), # 3. karpfenblau3 (non-transparent)
"karpfenblau4" = rgb( 62, 84, 150, maxColorValue = 255), # 4. karpfenblau4 (non-transparent): preferred color: "karpfenblau"
"karpfenblau5" = rgb( 50, 67, 118, maxColorValue = 255), # 5. karpfenblau5 (non-transparent)
stringsAsFactors = FALSE)
pal_petrol <- data.frame( # element:
"petrol1" = rgb(156, 198, 207, maxColorValue = 255), # 1. petrol1 (non-transparent)
"petrol2" = rgb(106, 170, 183, maxColorValue = 255), # 2. petrol2 (non-transparent)
"petrol3" = rgb( 57, 141, 159, maxColorValue = 255), # 3. petrol3 (non-transparent)
"petrol4" = rgb( 7, 113, 135, maxColorValue = 255), # 4. petrol4 (non-transparent): preferred color: "petrol"
"petrol5" = rgb( 3, 95, 114, maxColorValue = 255), # 5. petrol5 (non-transparent)
stringsAsFactors = FALSE)
pal_pinky <- data.frame( # Element:
"pinky1" = rgb(243, 191, 203, maxColorValue = 255), # 1. pinky1 (non-transparent)
"pinky2" = rgb(236, 160, 178, maxColorValue = 255), # 2. pinky2 (non-transparent)
"pinky3" = rgb(230, 128, 152, maxColorValue = 255), # 3. pinky3 (non-transparent)
"pinky4" = rgb(224, 96, 126, maxColorValue = 255), # 4. pinky4 (non-transparent): preferred color: "pinky"
"pinky5" = rgb(202, 74, 104, maxColorValue = 255), # 5. pinky5 (non-transparent)
stringsAsFactors = FALSE)
pal_bordeaux <- data.frame( # Element:
"bordeaux1" = rgb(210, 166, 180, maxColorValue = 255), # 1. bordeaux1 (non-transparent)
"bordeaux2" = rgb(188, 122, 143, maxColorValue = 255), # 2. bordeaux2 (non-transparent)
"bordeaux3" = rgb(165, 77, 105, maxColorValue = 255), # 3. bordeaux3 (non-transparent)
"bordeaux4" = rgb(142, 32, 67, maxColorValue = 255), # 4. bordeaux4 (non-transparent): preferred color: "bordeaux"
"bordeaux5" = rgb(119, 20, 52, maxColorValue = 255), # 5. bordeaux5 (non-transparent)
stringsAsFactors = FALSE)
## (2) from https://bootswatch.com/sandstone/:
col_sand_light <- rgb(248, 245, 240, max = 255)
col_sand_mid <- rgb(142, 140, 132, max = 255)
col_sand_dark <- rgb(62, 63, 58, max = 255)
col_grey_1 <- rgb(181, 179, 174, max = 255)
col_grey_2 <- rgb(123, 121, 113, max = 255)
col_grey_3 <- "grey25"
col_grey_4 <- "grey10"
col_green_1 <- rgb(184, 217, 137, max = 255)
col_green_2 <- rgb(128, 177, 57, max = 255)
col_red_1 <- rgb(230, 142, 140, max = 255)
col_red_2 <- rgb(210, 52, 48, max = 255)
col_blue_1 <- rgb(115, 200, 234, max = 255)
col_blue_2 <- rgb(121, 149, 177, max = 255)
col_blue_3 <- rgb(29, 149, 198, max = 255)
col_blue_4 <- rgb(40, 74, 108, max = 255)
col_orange_1 <- rgb(247, 169, 127, max = 255)
col_orange_2 <- rgb(242, 100, 24, max = 255)
## (3) basic colors + transparency:
my_red <- "tomato3"
my_blue <- "steelblue3"
my_green <- "olivedrab4"
my_yellow <- "lightgoldenrod1"
my_orange <- "sienna1"
green_1 <- make_transparent(my_green, alpha = .50)
green_2 <- make_transparent(my_green, alpha = 1.0)
red_1 <- make_transparent(my_red, alpha = .50)
red_2 <- make_transparent(my_red, alpha = 1.0)
blue_1 <- make_transparent(my_blue, alpha = .50)
blue_2 <- make_transparent(my_blue, alpha = 1.0)
yellow_1 <- make_transparent(my_yellow, alpha = .50)
yellow_2 <- make_transparent(my_yellow, alpha = 1.0)
orange_1 <- make_transparent(my_orange, alpha = .50)
orange_2 <- make_transparent(my_orange, alpha = 1.0)
my_white <- "white"
my_grey <- "grey75"
my_black <- "black"
my_whitish <- "antiquewhite" # "whitesmoke"
my_bluish <- "aliceblue"
## (2) Assign colors to recurring elements/roles ----------
## (to set default colors for plots and app display):
## (a) Define base color (for population N):
N_col <- grey(.90, .99) # "white", col_grey_1
## (b) by condition: Define 2 colors for condition cases:
cond_true_col <- my_yellow # "lightgoldenrod1" "gold1", col_orange_1, "yellow2"
cond_false_col <- "lightskyblue2" #, my_blue, "deepskyblue1", "lightskyblue2", col_blue_1
## Combine in a named vector:
cond_colors <- setNames(c(cond_true_col, cond_false_col),
c("cond_true", "cond_false"))
## (c) by decision: Define 3 colors for decision cases:
dec_pos_col <- "rosybrown3" # "khaki", my_whitish
dec_neg_col <- "lightsteelblue3" # "lightsteelblue2", "wheat", "lightsteelblue1", my_bluish, "chartreuse4"
## Combine in a named vector:
dec_colors <- setNames(c(dec_pos_col, dec_neg_col),
c("dec_pos", "dec_neg"))
## (d) Accuracy colors:
dec_cor_col <- "palegreen3" # "forestgreen" # correct/accurate decisions
dec_err_col <- "firebrick3" # erroneous/inaccurate decisions
acc_colors <- setNames(c(dec_cor_col, dec_err_col),
c("dec_cor", "dec_err"))
## (e) by condition x decision: Define 4 colors for SDT cases:
hi_col <- my_green # "olivedrab4", "palegreen4", col_green_2, "chartreuse4"
mi_col <- my_red # "tomato3", "orangered3", "firebrick3", col_red_2
fa_col <- "lightsalmon2" # lightcoral", "tomato1", "orangered1", "firebrick1", col_red_1
cr_col <- "olivedrab3" # "springgreen2", "palegreen3", col_green_1
## Combine in a named vector:
sdt.colors <- setNames(c(hi_col, mi_col, fa_col, cr_col),
c("hi", "mi", "fa", "cr")
)
## (f) Define 2 colors for main PVs:
PPV_col <- my_orange # "sienna1" # col_orange_2 # "orange3" "firebrick" "red3"
NPV_col <- my_blue # "steelblue3", col_blue_3, "green4" "gray50" "brown4"
## (g) Other colors:
## Text and borders:
txt_col <- grey(.01, .99) # near "black" text labels, NA removes text?
brd_col <- grey(.20, .99) # greyish borders, NA removes borders
## Plot background:
bg_col <- "white" # background color, NA creates transparent background [set ONLY here]
## Probability lines (within Mosaic/area plots):
# prev.li <- "gold" # "aliceblue"
# sens.li <- "cornsilk" # "darkseagreen1" "olivedrab1"
# spec.li <- "whitesmoke" # "lemonchiffon" "antiquewhite"
# col_p <- c(prev.li, sens.li, spec.li) # 3 bright colors (visible on SDT rectangles)
## (3) Define corresponding default palette: ----------
# vector of colors:
pal_def <- c(N_col,
cond_colors, dec_colors, acc_colors,
sdt.colors,
PPV_col, NPV_col,
txt_col, brd_col,
bg_col)
# names of colors:
pal_def <- setNames(object = pal_def,
nm = c("N",
names(cond_colors), names(dec_colors), names(acc_colors),
names(sdt.colors),
"ppv", "npv",
"txt", "brd", "bg")
)
n_colors <- length(pal_def) # number of colors for which defaults are currently defined
# n_colors
## (B) Initialization function for all color elements (titles and labels): ----------
## init_pal: Documentation ------
#' Initialize basic color information.
#'
#' \code{init_pal} initializes basic color information
#' (i.e., all colors corresponding to functional roles in
#' the current scenario and used throughout the \bold{riskyr} package).
#'
#' All color information of the current scenario
#' is stored as named colors in a list \code{pal}.
#' \code{init_pal} allows changing colors by assigning
#' new colors to existing names.
#'
#' @param N_col Color representing the \emph{population} of \code{\link{N}} cases or individuals.
#'
#' @param cond_true_col Color representing cases of \code{\link{cond_true}}, for which the current condition is \code{TRUE}.
#' @param cond_false_col Color representing cases of in \code{\link{cond_false}}, for which the current condition is \code{FALSE}.
#'
#' @param dec_pos_col Color representing cases of \code{\link{dec_pos}}, for which the current decision is \code{positive}.
#' @param dec_neg_col Color representing cases in \code{\link{dec_neg}}, for which the current decision is \code{negative}.
#'
#' @param dec_cor_col Color representing cases of correct decisions \code{\link{dec_cor}}, for which the current decision is \code{accurate}.
#' @param dec_err_col Color representing cases in erroneous decisions \code{\link{dec_err}}, for which the current decision is \code{inaccurate}.
#'
#' @param hi_col Color representing \emph{hits} or true positives in \code{\link{hi}}
#' (i.e., correct cases for which the current condition is TRUE and the decision is positive).
#' @param mi_col Color representing \emph{misses} or false negatives in \code{\link{mi}}
#' (i.e., incorrect cases for which the current condition is TRUE but the decision is negative).
#' @param fa_col Color representing \emph{false alarms} or false positives in \code{\link{fa}}
#' (i.e., incorrect cases for which the current condition is FALSE but the decision is positive).
#' @param cr_col Color representing \emph{correct rejections} or true negatives in \code{\link{cr}}
#' (i.e., correct cases for which the current condition is FALSE and the decision is negative).
#'
#' @param PPV_col Color representing \emph{positive predictive values} \code{\link{PPV}} (i.e., the conditional probability that
#' the condition is TRUE, provided that the decision is positive).
#' @param NPV_col Color representing \emph{negative predictive values} \code{\link{NPV}} (i.e., the conditional probability that
#' the condition is FALSE, provided that the decision is negative).
#'
#' @param txt_col Color used for text labels.
#' @param bg_col Background color of plot (used to set \code{par(bg = bg_col)}).
#' @param brd_col Color used for borders (e.g., around bars or boxes).
#'
#' @examples
#' init_pal() # => define and return a vector of current (default) colors
#' length(init_pal()) # => 15 named colors
#' pal <- init_pal(N_col = "steelblue4") # => change a color (stored in pal)
#' pal <- init_pal(brd_col = NA) # => remove a color
#'
#' @family functions initializing scenario information
#'
#' @seealso
#' \code{\link{num}} contains basic numeric parameters;
#' \code{\link{init_num}} initializes basic numeric parameters;
#' \code{\link{txt}} contains current text information;
#' \code{\link{init_txt}} initializes text information;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{freq}} contains current frequency information;
#' \code{\link{comp_freq}} computes current frequency information;
#' \code{\link{prob}} contains current probability information;
#' \code{\link{comp_prob}} computes current probability information.
#'
#' @importFrom grDevices adjustcolor
#' @importFrom grDevices col2rgb
#' @importFrom grDevices grey
#' @importFrom grDevices rgb
#'
#' @importFrom stats setNames
#'
#' @export
## init_pal: Definition ------
init_pal <- function(N_col = pal_def["N"], # population N
## by condition:
cond_true_col = pal_def["cond_true"], # condition true
cond_false_col = pal_def["cond_false"], # condition false
## by decision:
dec_pos_col = pal_def["dec_pos"], # decision positive
dec_neg_col = pal_def["dec_neg"], # decision negative
## by accuracy:
dec_cor_col = pal_def["dec_cor"], # decision correct / accurate
dec_err_col = pal_def["dec_err"], # decision erroneous / inaccurate
## Combinations:
hi_col = pal_def["hi"], # hits / true positives
mi_col = pal_def["mi"], # misses / false negatives
fa_col = pal_def["fa"], # false alarms / false positives
cr_col = pal_def["cr"], # correct rejections / true negatives
## Derived conditional probabilities:
PPV_col = pal_def["ppv"], # positive predictive values
NPV_col = pal_def["npv"], # negative predictive values
## Text labels and borders:
txt_col = pal_def["txt"], # text labels
bg_col = pal_def["bg"], # background
brd_col = pal_def["brd"] # borders
) {
## 1. Initialize pal as a VECTOR:
pal <- rep(NA, n_colors)
## 2. Pass arguments to VECTOR:
pal <- c(N_col, # population N
## by condition:
cond_true_col, # condition true
cond_false_col, # condition false
## by decision:
dec_pos_col, # decision positive
dec_neg_col, # decision negative
## by accuracy:
dec_cor_col, # decision correct / accurate
dec_err_col, # decision erroneous / inaccurate
## Combinations:
hi_col, # hits / true positives
mi_col, # misses / false negatives
fa_col, # false alarms / false positives
cr_col, # correct rejections / true negatives
## Derived conditional probabilities:
PPV_col, # positive predictive values
NPV_col, # negative predictive values
## Text labels and borders:
txt_col, # text labels
brd_col, # borders
## Background:
bg_col
)
## 3. Name vector elements:
pal <- setNames(object = pal,
nm = c("N",
names(cond_colors), names(dec_colors), names(acc_colors),
names(sdt.colors),
"ppv", "npv", "txt", "brd", "bg")
)
## 4. Return vector:
return(pal)
}
## Check:
# init_pal() # => define and return a vector of current (default) colors
# length(init_pal()) # => 16 named colors
# pal <- init_pal(N_col = "steelblue4") # => change a color (stored in pal)
# pal <- init_pal(brd_col = NA) # => remove a color
## (C) Initialize vector pal with current color information: ----------
## pal: Documentation ------
#' List current values of scenario color palette.
#'
#' \code{pal} is initialized to a vector of named elements (colors)
#' to define the scenario color scheme that is
#' used throughout the \bold{riskyr} package.
#'
#' All color information corresponding to the current scenario
#' is stored as named colors in a vector \code{pal}.
#' To change a color, assign a new color to an existing element name.
#'
#' \code{pal} currently contains colors with the following names:
#'
#' \enumerate{
#'
#' \item \code{N} Color representing the \emph{population} of \code{\link{N}} cases or individuals.
#'
#' \item \code{cond_true} Color representing cases of \code{\link{cond_true}}, for which the current condition is \code{TRUE}.
#'
#' \item \code{cond_false} Color representing cases of in \code{\link{cond_false}}, for which the current condition is \code{FALSE}.
#'
#' \item \code{dec_pos} Color representing cases of \code{\link{dec_pos}}, for which the current decision is \code{positive}.
#'
#' \item \code{dec_neg} Color representing cases in \code{\link{dec_neg}}, for which the current decision is \code{negative}.
#'
#' \item \code{dec_cor} Color representing cases of correct decisions \code{\link{dec_cor}}, for which the current decision is \code{accurate}.
#'
#' \item \code{dec_err} Color representing cases of erroneous decisions \code{\link{dec_err}}, for which the current decision is \code{inaccurate}.
#'
#' \item \code{hi} Color representing \emph{hits} or true positives in \code{\link{hi}}
#' (i.e., correct cases for which the current condition is TRUE and the decision is positive).
#'
#' \item \code{mi} Color representing \emph{misses} or false negatives in \code{\link{mi}}
#' (i.e., incorrect cases for which the current condition is TRUE but the decision is negative).
#'
#' \item \code{fa} Color representing \emph{false alarms} or false positives in \code{\link{fa}}
#' (i.e., incorrect cases for which the current condition is FALSE but the decision is positive).
#'
#' \item \code{cr} Color representing \emph{correct rejections} or true negatives in \code{\link{cr}}
#' (i.e., correct cases for which the current condition is FALSE and the decision is negative).
#'
#' \item \code{ppv} Color representing \emph{positive predictive values} \code{\link{PPV}} (i.e., the conditional probability that
#' the condition is TRUE, provided that the decision is positive).
#'
#' \item \code{npv} Color representing \emph{negative predictive values} \code{\link{NPV}} (i.e., the conditional probability that
#' the condition is FALSE, provided that the decision is negative).
#'
#' \item \code{txt} Color used for text labels.
#'
#' \item \code{brd} Color used for borders.
#'
#' \item \code{bg} Color used for plot background (used to set \code{par(bg = bg_col)}).
#'
#' }
#'
#' Note that color names for frequencies correspond to frequency names,
#' but are different for probabilities (which are written in lowercase
#' and only \code{\link{PPV}} and \code{\link{NPV}} have assigned colors).
#'
#' @examples
#' pal # shows all color names and current values
#' pal["hi"] # shows the current color for hits (true positives, TP)
#' pal["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{num}} contains basic numeric parameters;
#' \code{\link{init_num}} initializes basic numeric parameters;
#' \code{\link{txt}} contains current text information;
#' \code{\link{init_txt}} initializes text information;
#' \code{\link{freq}} contains current frequency information;
#' \code{\link{comp_freq}} computes current frequency information;
#' \code{\link{prob}} contains current probability information;
#' \code{\link{comp_prob}} computes current probability information.
#'
#' @export
## pal: Definition ------
pal <- init_pal() ## apply
## Check:
# pal
# length(pal) # => 15 colors
# pal[2] == pal["true"]
## pal_org: A copy of original color palette: --------
#' Original color palette.
#'
#' \code{pal_org} is a copy of \code{\link{pal}}
#' (to retrieve original set of colors in case
#' \code{\link{pal}} is changed).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_org} to re-set default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_org # shows all color names and current values
#' pal_org["hi"] # shows the current color for hits (true positives, TP)
#' pal_org["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_org <- pal # copy pal
## pal_bw: A black-and-white (b/w/grey) color palette: --------
#' Alternative color palette for black-and-white (greyscale) graphs.
#'
#' \code{pal_bw} is initialized to a vector of named elements (colors)
#' to define an alternative (black-and-white, b/w) scenario color scheme.
#'
#' Note that \code{pal_bw} uses various shades of grey for frequency boxes
#' so that their bounds remain visible on a white background
#' when \code{f_lwd = 0} (as per default for most graphs).
#'
#' See \code{\link{pal_bwp}} for a stricter version that enforces
#' black text and lines on white boxes (e.g., for printing purposes).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_bw} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_bw # shows all color names and current values
#' pal_bw["hi"] # shows the current color for hits (true positives, TP)
#' pal_bw["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_bw <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.90, .99), # darker white
cond_false_col = grey(.80, .99), # darker white
dec_pos_col = grey(.85, .99), # darker white
dec_neg_col = grey(.70, .99), # darker white
dec_cor_col = grey(.75, .99), # darker white
dec_err_col = grey(.60, .99), # darker white
hi_col = grey(.80, .99), # brighter 1
mi_col = grey(.60, .99), # darker 1
fa_col = grey(.50, .99), # darker 2
cr_col = grey(.70, .99), # brighter 2
PPV_col = grey(.60, .99), # medium grey
NPV_col = grey(.45, .99), # darker grey
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_bw
# pal_bw["hi"]
## pal_bwp: A strict black-and-white (b/w) color palette for printing purposes: --------
#' Alternative color palette for black-and-white graphs (for printing purposes).
#'
#' \code{pal_bwp} is initialized to a vector of named elements (colors)
#' to define a strict (black-and-white, b/w) scenario color scheme
#' that is suited for printing graphs in black-and-white.
#'
#' \code{pal_bwp} is a stricter version of the greyscale
#' palette \code{\link{pal_bw}} that enforces
#' black text and lines on white boxes. Thus, the bounds of frequency boxes
#' are invisible on white backgrounds unless the default of
#' \code{f_lwd = 0} is changed (e.g., to \code{f_lwd = 1}).
#'
#' Some background colors (of frequencies) are also used as
#' foreground colors (of probabilities, e.g.,
#' in \code{\link{plot_curve}} and \code{\link{plot_plane}}).
#' For this reason, the plotting functions detect and
#' adjust colors and/or line settings when \code{pal_bwp}
#' is used.
#'
#' See \code{\link{pal_bw}} for a more permissible black-and-white
#' palette that uses various shades of grey for frequency boxes
#' so that their bounds remain visible on a white background
#' when \code{f_lwd = 0} (as per default for most graphs).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_bwp} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_bwp # shows all color names and current values
#' pal_bwp["hi"] # shows the current color for hits (true positives, TP)
#' pal_bwp["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_bwp <- init_pal(N_col = my_white, # grey(.95, .99), # nearly white
cond_true_col = my_white, # grey(.90, .99), # darker white
cond_false_col = my_white, # grey(.80, .99), # darker white
dec_pos_col = my_white, # grey(.85, .99), # darker white
dec_neg_col = my_white, # grey(.70, .99), # darker white
dec_cor_col = my_white, # grey(.75, .99), # darker white
dec_err_col = my_white, # grey(.60, .99), # darker white
hi_col = my_white, # grey(.80, .99), # brighter 1
mi_col = my_white, # grey(.60, .99), # darker 1
fa_col = my_white, # grey(.50, .99), # darker 2
cr_col = my_white, # grey(.70, .99), # brighter 2
PPV_col = my_black, # grey(.60, .99), # medium grey
NPV_col = my_black, # grey(.45, .99), # darker grey
txt_col = my_black, # grey(0, .99), # black
brd_col = my_black # grey(.10, .99) # almost black
)
## Check:
# pal_bwp
# pal_bwp["hi"]
## pal_rgb: A reduced RGB color palette: --------
#' Alternative color palette for graphs (with RGB colors).
#'
#' \code{pal_rgb} is initialized to a vector of named elements (colors)
#' to define an alternative (reduced) scenario color scheme
#' (using red, green, and blue colors).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_rgb} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_rgb # shows all color names and current values
#' pal_rgb["hi"] # shows the current color for hits (true positives, TP)
#' pal_rgb["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_rgb <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.90, .99), # darker white
cond_false_col = grey(.75, .99), # lighter white
dec_pos_col = grey(.85, .99), # lighter grey
dec_neg_col = grey(.70, .99), # darker grey
dec_cor_col = grey(.75, .99), # lighter grey
dec_err_col = grey(.60, .99), # darker grey
# hi_col = pal["hi"], # from pal
# mi_col = pal["mi"], # from pal
# fa_col = pal["fa"], # from pal
# cr_col = pal["cr"], # from pal
# PPV_col = grey(.60, .99), # medium grey
# NPV_col = grey(.45, .99), # darker grey
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_rgb
# pal_rgb["N"] # => "#D9D9D9FC"
## Use reduced RGB color scheme (as default):
# pal <- pal_rgb
## Note: Check http://colorbrewer2.org for alternatives:
## http://colorbrewer2.org/?type=qualitative&scheme=Paired&n=4
## pal_mod: A modern (green/blue/orange) color palette: --------
#' Modern color palette (in green/blue/orange).
#'
#' \code{pal_mod} is initialized to a vector of named colors
#' to define a modern scenario color scheme (in green/blue/orange).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_mod} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_mod # shows all color names and current values
#' pal_mod["hi"] # shows the current color for hits (true positives, TP)
#' pal_mod["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_mod <- init_pal(N_col = grey(.90, .99), # "wheat3", nearly white
cond_true_col = my_yellow, # col_sand_mid, # grey(.80, .99), # "wheat3", #
cond_false_col = grey(.75, .99), # col_sand_mid, # "wheat4"
dec_pos_col = col_orange_1, # my_orange, # col_red_1, # grey(.85, .99), # col_grey_1,
dec_neg_col = grey(.65, .99), # col_grey_2,
dec_cor_col = my_green,
dec_err_col = my_blue,
hi_col = col_green_1,
mi_col = col_blue_1,
fa_col = col_blue_3,
cr_col = col_green_2,
PPV_col = col_orange_2,
NPV_col = col_blue_3,
txt_col = grey(0, .99), # black
brd_col = col_sand_dark
)
## Check:
# pal_mod
# pal_mod["hi"] # => "#B8D989"
## Use pal_mod color scheme (as default):
# pal <- pal_mod
## pal_mbw: A reduced modern (green/blue/bw) color palette: --------
#' Modern and reduced color palette (in green/blue/bw).
#'
#' \code{pal_mod} is initialized to a vector of named colors
#' to define a reduced modern scenario color scheme (in green/blue/bw).
#'
#' See \code{\link{pal_org}} for original color information;
#' \code{\link{pal_mod}} for a richer modern color palette; and
#' \code{\link{pal_bw}} for a more reduced black-and-white color palette.
#'
#' Assign \code{pal <- pal_mbw} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_mbw # shows all color names and current values
#' pal_mbw["hi"] # shows the current color for hits (true positives, TP)
#' pal_mbw["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{pal_org}} for original color palette;
#' \code{\link{pal_mod}} for a richer modern color palette;
#' \code{\link{pal_bw}} for a more reduced black-and-white color palette.
#'
#' @export
pal_mbw <- init_pal(N_col = grey(.90, .99), # "wheat3", nearly white
cond_true_col = grey(.80, .99), # my_yellow, # col_sand_mid, # # "wheat3", #
cond_false_col = grey(.75, .99), # col_sand_mid, # "wheat4"
dec_pos_col = grey(.85, .99), # col_orange_1, # my_orange, # col_red_1, # col_grey_1,
dec_neg_col = grey(.65, .99), # col_grey_2,
dec_cor_col = my_green,
dec_err_col = my_blue,
hi_col = col_green_1,
mi_col = col_blue_1,
fa_col = col_blue_3,
cr_col = col_green_2,
PPV_col = col_orange_2,
NPV_col = col_blue_3,
txt_col = grey(0, .99), # black
brd_col = col_sand_dark
)
## Check:
# pal_mbw
# pal_mbw["cond_true"] # => "#CCCCCCFC"
## Use pal_mbw color scheme (as default):
# pal <- pal_mbw
## pal_kn: A uni.kn palette: --------
#' Alternative color palette for kn.
#'
#' \code{pal_kn} is initialized to a vector of named elements (colors)
#' to define an alternative (kn) scenario color scheme.
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_kn} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_kn # shows all color names and current values
#' pal_kn["hi"] # shows the current color for hits (true positives, TP)
#' pal_kn["hi"] <- "grey" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal_unikn}} contains more \bold{unikn} colors;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_kn <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.70, .99), # darker white
cond_false_col = grey(.85, .99), # darker white
dec_pos_col = grey(.60, .99), # darker white
dec_neg_col = grey(.75, .99), # darker white
dec_cor_col = grey(.50, .99), # grey
dec_err_col = grey(.65, .99), # darker white
hi_col = pal_seeblau[[4]],
mi_col = pal_seeblau[[2]],
fa_col = pal_seeblau[[1]],
cr_col = pal_seeblau[[3]],
PPV_col = col_orange_2,
NPV_col = pal_seeblau[[5]],
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_kn
# pal_kn["hi"]
## Use uni.kn color scheme (as default):
# pal <- pal_kn
## pal_unikn: A unikn palette: --------
#' Alternative color palette for unikn.
#'
#' \code{pal_unikn} is initialized to a vector of named elements (colors)
#' to define an alternative (unikn) scenario color scheme.
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_unikn} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_unikn # shows all color names and current values
#' pal_unikn["hi"] # shows the current color for hits (true positives, TP)
#' pal_unikn["hi"] <- "grey" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal_kn}} contains fewer \bold{unikn} colors;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_unikn <- init_pal(N_col = grey(.95, 1), # nearly white
cond_true_col = pal_seeblau[[3]],
cond_false_col = pal_seeblau[[1]],
dec_pos_col = pal_pinky[[2]],
dec_neg_col = pal_karpfenblau[[2]],
dec_cor_col = pal_seegruen[[2]],
dec_err_col = pal_bordeaux[[2]],
hi_col = pal_petrol[[2]],
mi_col = pal_bordeaux[[1]],
fa_col = pal_bordeaux[[2]],
cr_col = pal_petrol[[1]],
PPV_col = pal_pinky[[4]],
NPV_col = pal_karpfenblau[[4]],
txt_col = grey(0, 1), # black
brd_col = grey(.10, 1) # almost black
)
## Check:
# pal_unikn
# pal_unikn["hi"]
## Use pal_unikn color scheme (as default):
# pal <- pal_unikn
## pal_vir: A viridis color palette: ----------
## Using viridisLite (version 0.3.0):
## URL: https://github.com/sjmgarnier/viridisLite
## Maintainer: Simon Garnier <garnier@njit.edu>
# viridisLite::viridis(4)
vir_04 <- c("#440154FF", "#31688EFF", "#35B779FF", "#FDE725FF")
# viridisLite::viridis(8)
vir_08 <- c("#440154FF", "#46337EFF", "#365C8DFF", "#277F8EFF",
"#1FA187FF", "#4AC16DFF", "#9FDA3AFF", "#FDE725FF")
# viridisLite::viridis(12)
vir_12 <- c("#440154FF", "#482173FF", "#433E85FF", "#38598CFF",
"#2D708EFF", "#25858EFF", "#1E9B8AFF", "#2BB07FFF",
"#51C56AFF", "#85D54AFF", "#C2DF23FF", "#FDE725FF")
#' Alternative color palette using viridis colors.
#'
#' \code{pal_vir} is initialized to a vector of named elements (colors)
#' to define a scenario color scheme modeled on the \code{viridis} color scale.
#'
#' These colors are select by the Matplotlib \code{viridis} color map
#' created by Stéfan van der Walt and Nathaniel Smith.
#' See the \code{viridisLite} package (maintained by Simon Garnier)
#' for further information.
#'
#' Assign \code{pal <- pal_vir} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_vir # shows all color names and current values
#' pal_vir["hi"] # shows the current color for hits (true positives, TP)
#' pal_vir["hi"] <- "green3" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_vir <- init_pal(N_col = grey(.70, .99), # mid-grey
cond_true_col = grey(.85, .99), # brighter by 15
cond_false_col = grey(.55, .99), # darker
dec_pos_col = grey(.80, .99), # brighter by 10
dec_neg_col = grey(.60, .99), # darker
dec_cor_col = grey(.90, .99), # brighter by 20
dec_err_col = grey(.50, .99), # darker
hi_col = vir_12[10], # hi: bright green
mi_col = vir_12[12], # mi: yellow
fa_col = vir_12[5], # fa: bluish
cr_col = vir_12[8], # cr: darker green
PPV_col = vir_12[9], # between hi and cr
NPV_col = vir_12[3], # beyond fa
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_vir
# pal_vir["hi"]
## Use viridis color scheme (as default):
# pal <- pal_vir
## Set default color palette: -------
## Use pal_mbw by default (riskyr 0.2.0):
# pal <- pal_mbw
## Use pal_mod by default (riskyr 0.2.0.9000+):
pal <- pal_mod
## Test:
# pal <- pal_bwp
# pal <- pal_unikn
## Define a crisk color palette: --------
# Define a mixed color palette:
pal_mix <- c("deepskyblue", "deeppink",
col_green_1, col_green_2, col_orange_1, col_orange_2,
col_blue_1, col_blue_2, col_blue_3, col_blue_4,
col_red_1, col_red_2,
col_sand_light, col_sand_mid, col_sand_dark,
my_whitish, my_bluish, my_yellow, my_orange)
names(pal_mix) <- c("deepskyblue", "deeppink", "lightgreen", "green", "lightorange", "orange",
"blue1", "blue2", "blue3", "blue4",
"red1", "red2",
"sand1", "sand2", "sand3",
"my_whitish", "my_bluish", "my_yellow", "my_orange")
# unikn::seecol(pal_mix)
# Select pal_crisk colors:
pal_crisk_select <- c(pal_mix["deepskyblue"], pal_mix["red2"],
"black", "grey50", pal_mix["deeppink"],
pal_mix["sand2"], pal_mix["my_yellow"],
pal_mix["blue4"], pal_mix["my_orange"], pal_mix["green"])
names(pal_crisk_select) <- c("cum", "rinc",
"txt", "aux", "high",
"pas", "rem",
"delta", "poly", "popu")
pal_crisk_select["poly"] <- pal_crisk_select["cum"] # make "poly"" same color as "cum"
# unikn::seecol(pal_crisk_select)
# pal_crisk: Documentation and definition:
#' Color palette for cumulative risk curve.
#'
#' \code{pal_crisk} defines a default color palette
#' for the \code{\link{plot_crisk}} function
#' (as a named vector).
#'
#' Color names and referents in plots
#' generated by \code{\link{plot_crisk}}:
#'
#' \enumerate{
#' \item \code{"cum"}: Cumulative risk curve
#' \item \code{"rinc"}: Relative risk increments
#'
#' \item \code{"txt"}: Text labels
#' \item \code{"aux"}: Auxiliary labels and lines
#' \item \code{"high"}: Highlighting elements
#'
#' \item \code{"pas"}: Past/passed risk
#' \item \code{"rem"}: Remaining risk
#'
#' \item \code{"delta"}: Delta-X- and -Y increments
#' \item \code{"poly"}: Polygon of increments
#' \item \code{"popu"}: Population partitions
#' }
#'
#' @examples
#' pal_crisk # show color palette (and names)
#'
#' @family color palettes
#'
#' @seealso
#' \code{\link{plot_crisk}} plots cumulative risk curves;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_crisk <- pal_crisk_select
# +++ here now +++
# unikn::seecol(pal_crisk)
# knitr::kable(pal_crisk, caption = "The `pal_crisk` color palette.")
## (*) Done: ----------
## - Addressed limitation: [2019 01 23]
## Lack of an explicit background color (e.g., "white" or NA by default).
## Solution implemented:
# 1. bg_col <- "white" # in all color palettes
# 2. par(bg = col_pal[["bg"]]) # in all plot functions
## (+) ToDo: ----------
## - Lack of most probability colors:
## Only PPV and NPV are assigned dedicated colors.
## Plotting ppod and acc in plot_curve and plot_plane recruits frequency colors.
## This can lead to conflicts (e.g., with pal_bwp when par("bg") == "white").
## - Lack of ability to invert boxes (e.g., text bright, fill color dark).
## ToDos:
## - Add more 2x2-dimensional (+/-, T/F) color palettes.
## - Add dark (inverted) color palette (bright text on dark boxes).
## eof. ------------------------------------------
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Defines functions init_pal
Documented in init_pal
## init_pal.R | riskyr
## 2021 12 10
## Define custom color palettes (pal):
## -----------------------------------------------
## pal contains defaults for user inputs.
## (A) Define colors: ----------
## (1) Select and name some colors: ---------
## (1) from unikn:
# seeblau <- rgb(0, 169, 224, max = 255) # seeblau.4 (non-transparent)
# pal_uni_kn = data.frame( ## in one df:
# "seeblau1" = rgb(204, 238, 249, maxColorValue = 255), # 1. seeblau1 (non-transparent)
# "seeblau2" = rgb(166, 225, 244, maxColorValue = 255), # 2. seeblau2 (non-transparent)
# "seeblau3" = rgb( 89, 199, 235, maxColorValue = 255), # 3. seeblau3 (non-transparent)
# "seeblau4" = rgb( 0, 169, 224, maxColorValue = 255), # 4. seeblau4 (= seeblau base color)
# "black" = rgb( 0, 0, 0, maxColorValue = 255), # 5. black
# "seegrau4" = rgb(102, 102, 102, maxColorValue = 255), # 6. grey40 (non-transparent)
# "seegrau3" = rgb(153, 153, 153, maxColorValue = 255), # 7. grey60 (non-transparent)
# "seegrau2" = rgb(204, 204, 204, maxColorValue = 255), # 8. grey80 (non-transparent)
# "seegrau1" = rgb(229, 229, 229, maxColorValue = 255), # 9. grey90 (non-transparent)
# "white" = rgb(255, 255, 255, maxColorValue = 255), # 10. white
# stringsAsFactors = FALSE)
# individual palettes (from unikn):
pal_seeblau <- data.frame( # element:
"seeblau1" = rgb(204, 238, 249, maxColorValue = 255), # 1. seeblau1 (non-transparent): 20%
"seeblau2" = rgb(166, 225, 244, maxColorValue = 255), # 2. seeblau2 (non-transparent): 35%
"seeblau3" = rgb( 89, 199, 235, maxColorValue = 255), # 3. seeblau3 (non-transparent): 65%: preferred color: "seeblau"
"seeblau4" = rgb( 0, 169, 224, maxColorValue = 255), # 4. seeblau4 (non-transparent): 100%
"seeblau5" = rgb( 0, 142, 206, maxColorValue = 255), # 5. seeblau5 (non-transparent): neu
stringsAsFactors = FALSE)
pal_seegruen <- data.frame( # element:
"seegruen1" = rgb(113, 209, 204, maxColorValue = 255), # 1. seegruen1 (non-transparent)
"seegruen2" = rgb( 84, 191, 183, maxColorValue = 255), # 2. seegruen2 (non-transparent)
"seegruen3" = rgb( 10, 163, 152, maxColorValue = 255), # 3. seegruen3 (non-transparent)
"seegruen4" = rgb( 10, 144, 134, maxColorValue = 255), # 4. seegruen4 (non-transparent): preferred color: "seegruen"
"seegruen5" = rgb( 6, 126, 121, maxColorValue = 255), # 5. seegruen5 (non-transparent)
stringsAsFactors = FALSE)
pal_grau <- data.frame( # element:
"grau1" = rgb(225, 226, 229, maxColorValue = 255), # 1. grau1 (non-transparent)
"grau2" = rgb(184, 188, 193, maxColorValue = 255), # 2. grau2 (non-transparent)
"grau3" = rgb(154, 160, 167, maxColorValue = 255), # 3. grau3 (non-transparent): preferred color: "grau"
"grau4" = rgb(115, 120, 126, maxColorValue = 255), # 4. grau4 (non-transparent)
"grau5" = rgb( 77, 80, 84, maxColorValue = 255), # 5. grau5 (non-transparent)
stringsAsFactors = FALSE)
pal_peach <- data.frame( # Element:
"peach1" = rgb(254, 226, 221, maxColorValue = 255), # 1.
"peach2" = rgb(254, 207, 199, maxColorValue = 255), # 2.
"peach3" = rgb(255, 184, 172, maxColorValue = 255), # 3.
"peach4" = rgb(254, 160, 144, maxColorValue = 255), # 4. preferred color: "peach"
"peach5" = rgb(255, 142, 123, maxColorValue = 255), # 5.
stringsAsFactors = FALSE)
pal_petrol <- data.frame( # element:
"petrol1" = rgb(156, 198, 207, maxColorValue = 255), # 1. petrol1 (non-transparent)
"petrol2" = rgb(106, 170, 183, maxColorValue = 255), # 2. petrol2 (non-transparent)
"petrol3" = rgb( 57, 141, 159, maxColorValue = 255), # 3. petrol3 (non-transparent)
"petrol4" = rgb( 7, 113, 135, maxColorValue = 255), # 4. petrol4 (non-transparent): preferred color: "petrol"
"petrol5" = rgb( 3, 95, 114, maxColorValue = 255), # 5. petrol5 (non-transparent)
stringsAsFactors = FALSE)
pal_karpfenblau <- data.frame( # element:
"karpfenblau1" = rgb(180, 188, 214, maxColorValue = 255), # 1. karpfenblau1 (non-transparent)
"karpfenblau2" = rgb(130, 144, 187, maxColorValue = 255), # 2. karpfenblau2 (non-transparent)
"karpfenblau3" = rgb( 88, 107, 164, maxColorValue = 255), # 3. karpfenblau3 (non-transparent)
"karpfenblau4" = rgb( 62, 84, 150, maxColorValue = 255), # 4. karpfenblau4 (non-transparent): preferred color: "karpfenblau"
"karpfenblau5" = rgb( 50, 67, 118, maxColorValue = 255), # 5. karpfenblau5 (non-transparent)
stringsAsFactors = FALSE)
pal_petrol <- data.frame( # element:
"petrol1" = rgb(156, 198, 207, maxColorValue = 255), # 1. petrol1 (non-transparent)
"petrol2" = rgb(106, 170, 183, maxColorValue = 255), # 2. petrol2 (non-transparent)
"petrol3" = rgb( 57, 141, 159, maxColorValue = 255), # 3. petrol3 (non-transparent)
"petrol4" = rgb( 7, 113, 135, maxColorValue = 255), # 4. petrol4 (non-transparent): preferred color: "petrol"
"petrol5" = rgb( 3, 95, 114, maxColorValue = 255), # 5. petrol5 (non-transparent)
stringsAsFactors = FALSE)
pal_pinky <- data.frame( # Element:
"pinky1" = rgb(243, 191, 203, maxColorValue = 255), # 1. pinky1 (non-transparent)
"pinky2" = rgb(236, 160, 178, maxColorValue = 255), # 2. pinky2 (non-transparent)
"pinky3" = rgb(230, 128, 152, maxColorValue = 255), # 3. pinky3 (non-transparent)
"pinky4" = rgb(224, 96, 126, maxColorValue = 255), # 4. pinky4 (non-transparent): preferred color: "pinky"
"pinky5" = rgb(202, 74, 104, maxColorValue = 255), # 5. pinky5 (non-transparent)
stringsAsFactors = FALSE)
pal_bordeaux <- data.frame( # Element:
"bordeaux1" = rgb(210, 166, 180, maxColorValue = 255), # 1. bordeaux1 (non-transparent)
"bordeaux2" = rgb(188, 122, 143, maxColorValue = 255), # 2. bordeaux2 (non-transparent)
"bordeaux3" = rgb(165, 77, 105, maxColorValue = 255), # 3. bordeaux3 (non-transparent)
"bordeaux4" = rgb(142, 32, 67, maxColorValue = 255), # 4. bordeaux4 (non-transparent): preferred color: "bordeaux"
"bordeaux5" = rgb(119, 20, 52, maxColorValue = 255), # 5. bordeaux5 (non-transparent)
stringsAsFactors = FALSE)
## (2) from https://bootswatch.com/sandstone/:
col_sand_light <- rgb(248, 245, 240, max = 255)
col_sand_mid <- rgb(142, 140, 132, max = 255)
col_sand_dark <- rgb(62, 63, 58, max = 255)
col_grey_1 <- rgb(181, 179, 174, max = 255)
col_grey_2 <- rgb(123, 121, 113, max = 255)
col_grey_3 <- "grey25"
col_grey_4 <- "grey10"
col_green_1 <- rgb(184, 217, 137, max = 255)
col_green_2 <- rgb(128, 177, 57, max = 255)
col_red_1 <- rgb(230, 142, 140, max = 255)
col_red_2 <- rgb(210, 52, 48, max = 255)
col_blue_1 <- rgb(115, 200, 234, max = 255)
col_blue_2 <- rgb(121, 149, 177, max = 255)
col_blue_3 <- rgb(29, 149, 198, max = 255)
col_blue_4 <- rgb(40, 74, 108, max = 255)
col_orange_1 <- rgb(247, 169, 127, max = 255)
col_orange_2 <- rgb(242, 100, 24, max = 255)
## (3) basic colors + transparency:
my_red <- "tomato3"
my_blue <- "steelblue3"
my_green <- "olivedrab4"
my_yellow <- "lightgoldenrod1"
my_orange <- "sienna1"
green_1 <- make_transparent(my_green, alpha = .50)
green_2 <- make_transparent(my_green, alpha = 1.0)
red_1 <- make_transparent(my_red, alpha = .50)
red_2 <- make_transparent(my_red, alpha = 1.0)
blue_1 <- make_transparent(my_blue, alpha = .50)
blue_2 <- make_transparent(my_blue, alpha = 1.0)
yellow_1 <- make_transparent(my_yellow, alpha = .50)
yellow_2 <- make_transparent(my_yellow, alpha = 1.0)
orange_1 <- make_transparent(my_orange, alpha = .50)
orange_2 <- make_transparent(my_orange, alpha = 1.0)
my_white <- "white"
my_grey <- "grey75"
my_black <- "black"
my_whitish <- "antiquewhite" # "whitesmoke"
my_bluish <- "aliceblue"
## (2) Assign colors to recurring elements/roles ----------
## (to set default colors for plots and app display):
## (a) Define base color (for population N):
N_col <- grey(.90, .99) # "white", col_grey_1
## (b) by condition: Define 2 colors for condition cases:
cond_true_col <- my_yellow # "lightgoldenrod1" "gold1", col_orange_1, "yellow2"
cond_false_col <- "lightskyblue2" #, my_blue, "deepskyblue1", "lightskyblue2", col_blue_1
## Combine in a named vector:
cond_colors <- setNames(c(cond_true_col, cond_false_col),
c("cond_true", "cond_false"))
## (c) by decision: Define 3 colors for decision cases:
dec_pos_col <- "rosybrown3" # "khaki", my_whitish
dec_neg_col <- "lightsteelblue3" # "lightsteelblue2", "wheat", "lightsteelblue1", my_bluish, "chartreuse4"
## Combine in a named vector:
dec_colors <- setNames(c(dec_pos_col, dec_neg_col),
c("dec_pos", "dec_neg"))
## (d) Accuracy colors:
dec_cor_col <- "palegreen3" # "forestgreen" # correct/accurate decisions
dec_err_col <- "firebrick3" # erroneous/inaccurate decisions
acc_colors <- setNames(c(dec_cor_col, dec_err_col),
c("dec_cor", "dec_err"))
## (e) by condition x decision: Define 4 colors for SDT cases:
hi_col <- my_green # "olivedrab4", "palegreen4", col_green_2, "chartreuse4"
mi_col <- my_red # "tomato3", "orangered3", "firebrick3", col_red_2
fa_col <- "lightsalmon2" # lightcoral", "tomato1", "orangered1", "firebrick1", col_red_1
cr_col <- "olivedrab3" # "springgreen2", "palegreen3", col_green_1
## Combine in a named vector:
sdt.colors <- setNames(c(hi_col, mi_col, fa_col, cr_col),
c("hi", "mi", "fa", "cr")
)
## (f) Define 2 colors for main PVs:
PPV_col <- my_orange # "sienna1" # col_orange_2 # "orange3" "firebrick" "red3"
NPV_col <- my_blue # "steelblue3", col_blue_3, "green4" "gray50" "brown4"
## (g) Other colors:
## Text and borders:
txt_col <- grey(.01, .99) # near "black" text labels, NA removes text?
brd_col <- grey(.20, .99) # greyish borders, NA removes borders
## Plot background:
bg_col <- "white" # background color, NA creates transparent background [set ONLY here]
## Probability lines (within Mosaic/area plots):
# prev.li <- "gold" # "aliceblue"
# sens.li <- "cornsilk" # "darkseagreen1" "olivedrab1"
# spec.li <- "whitesmoke" # "lemonchiffon" "antiquewhite"
# col_p <- c(prev.li, sens.li, spec.li) # 3 bright colors (visible on SDT rectangles)
## (3) Define corresponding default palette: ----------
# vector of colors:
pal_def <- c(N_col,
cond_colors, dec_colors, acc_colors,
sdt.colors,
PPV_col, NPV_col,
txt_col, brd_col,
bg_col)
# names of colors:
pal_def <- setNames(object = pal_def,
nm = c("N",
names(cond_colors), names(dec_colors), names(acc_colors),
names(sdt.colors),
"ppv", "npv",
"txt", "brd", "bg")
)
n_colors <- length(pal_def) # number of colors for which defaults are currently defined
# n_colors
## (B) Initialization function for all color elements (titles and labels): ----------
## init_pal: Documentation ------
#' Initialize basic color information.
#'
#' \code{init_pal} initializes basic color information
#' (i.e., all colors corresponding to functional roles in
#' the current scenario and used throughout the \bold{riskyr} package).
#'
#' All color information of the current scenario
#' is stored as named colors in a list \code{pal}.
#' \code{init_pal} allows changing colors by assigning
#' new colors to existing names.
#'
#' @param N_col Color representing the \emph{population} of \code{\link{N}} cases or individuals.
#'
#' @param cond_true_col Color representing cases of \code{\link{cond_true}}, for which the current condition is \code{TRUE}.
#' @param cond_false_col Color representing cases of in \code{\link{cond_false}}, for which the current condition is \code{FALSE}.
#'
#' @param dec_pos_col Color representing cases of \code{\link{dec_pos}}, for which the current decision is \code{positive}.
#' @param dec_neg_col Color representing cases in \code{\link{dec_neg}}, for which the current decision is \code{negative}.
#'
#' @param dec_cor_col Color representing cases of correct decisions \code{\link{dec_cor}}, for which the current decision is \code{accurate}.
#' @param dec_err_col Color representing cases in erroneous decisions \code{\link{dec_err}}, for which the current decision is \code{inaccurate}.
#'
#' @param hi_col Color representing \emph{hits} or true positives in \code{\link{hi}}
#' (i.e., correct cases for which the current condition is TRUE and the decision is positive).
#' @param mi_col Color representing \emph{misses} or false negatives in \code{\link{mi}}
#' (i.e., incorrect cases for which the current condition is TRUE but the decision is negative).
#' @param fa_col Color representing \emph{false alarms} or false positives in \code{\link{fa}}
#' (i.e., incorrect cases for which the current condition is FALSE but the decision is positive).
#' @param cr_col Color representing \emph{correct rejections} or true negatives in \code{\link{cr}}
#' (i.e., correct cases for which the current condition is FALSE and the decision is negative).
#'
#' @param PPV_col Color representing \emph{positive predictive values} \code{\link{PPV}} (i.e., the conditional probability that
#' the condition is TRUE, provided that the decision is positive).
#' @param NPV_col Color representing \emph{negative predictive values} \code{\link{NPV}} (i.e., the conditional probability that
#' the condition is FALSE, provided that the decision is negative).
#'
#' @param txt_col Color used for text labels.
#' @param bg_col Background color of plot (used to set \code{par(bg = bg_col)}).
#' @param brd_col Color used for borders (e.g., around bars or boxes).
#'
#' @examples
#' init_pal() # => define and return a vector of current (default) colors
#' length(init_pal()) # => 15 named colors
#' pal <- init_pal(N_col = "steelblue4") # => change a color (stored in pal)
#' pal <- init_pal(brd_col = NA) # => remove a color
#'
#' @family functions initializing scenario information
#'
#' @seealso
#' \code{\link{num}} contains basic numeric parameters;
#' \code{\link{init_num}} initializes basic numeric parameters;
#' \code{\link{txt}} contains current text information;
#' \code{\link{init_txt}} initializes text information;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{freq}} contains current frequency information;
#' \code{\link{comp_freq}} computes current frequency information;
#' \code{\link{prob}} contains current probability information;
#' \code{\link{comp_prob}} computes current probability information.
#'
#' @importFrom grDevices adjustcolor
#' @importFrom grDevices col2rgb
#' @importFrom grDevices grey
#' @importFrom grDevices rgb
#'
#' @importFrom stats setNames
#'
#' @export
## init_pal: Definition ------
init_pal <- function(N_col = pal_def["N"], # population N
## by condition:
cond_true_col = pal_def["cond_true"], # condition true
cond_false_col = pal_def["cond_false"], # condition false
## by decision:
dec_pos_col = pal_def["dec_pos"], # decision positive
dec_neg_col = pal_def["dec_neg"], # decision negative
## by accuracy:
dec_cor_col = pal_def["dec_cor"], # decision correct / accurate
dec_err_col = pal_def["dec_err"], # decision erroneous / inaccurate
## Combinations:
hi_col = pal_def["hi"], # hits / true positives
mi_col = pal_def["mi"], # misses / false negatives
fa_col = pal_def["fa"], # false alarms / false positives
cr_col = pal_def["cr"], # correct rejections / true negatives
## Derived conditional probabilities:
PPV_col = pal_def["ppv"], # positive predictive values
NPV_col = pal_def["npv"], # negative predictive values
## Text labels and borders:
txt_col = pal_def["txt"], # text labels
bg_col = pal_def["bg"], # background
brd_col = pal_def["brd"] # borders
) {
## 1. Initialize pal as a VECTOR:
pal <- rep(NA, n_colors)
## 2. Pass arguments to VECTOR:
pal <- c(N_col, # population N
## by condition:
cond_true_col, # condition true
cond_false_col, # condition false
## by decision:
dec_pos_col, # decision positive
dec_neg_col, # decision negative
## by accuracy:
dec_cor_col, # decision correct / accurate
dec_err_col, # decision erroneous / inaccurate
## Combinations:
hi_col, # hits / true positives
mi_col, # misses / false negatives
fa_col, # false alarms / false positives
cr_col, # correct rejections / true negatives
## Derived conditional probabilities:
PPV_col, # positive predictive values
NPV_col, # negative predictive values
## Text labels and borders:
txt_col, # text labels
brd_col, # borders
## Background:
bg_col
)
## 3. Name vector elements:
pal <- setNames(object = pal,
nm = c("N",
names(cond_colors), names(dec_colors), names(acc_colors),
names(sdt.colors),
"ppv", "npv", "txt", "brd", "bg")
)
## 4. Return vector:
return(pal)
}
## Check:
# init_pal() # => define and return a vector of current (default) colors
# length(init_pal()) # => 16 named colors
# pal <- init_pal(N_col = "steelblue4") # => change a color (stored in pal)
# pal <- init_pal(brd_col = NA) # => remove a color
## (C) Initialize vector pal with current color information: ----------
## pal: Documentation ------
#' List current values of scenario color palette.
#'
#' \code{pal} is initialized to a vector of named elements (colors)
#' to define the scenario color scheme that is
#' used throughout the \bold{riskyr} package.
#'
#' All color information corresponding to the current scenario
#' is stored as named colors in a vector \code{pal}.
#' To change a color, assign a new color to an existing element name.
#'
#' \code{pal} currently contains colors with the following names:
#'
#' \enumerate{
#'
#' \item \code{N} Color representing the \emph{population} of \code{\link{N}} cases or individuals.
#'
#' \item \code{cond_true} Color representing cases of \code{\link{cond_true}}, for which the current condition is \code{TRUE}.
#'
#' \item \code{cond_false} Color representing cases of in \code{\link{cond_false}}, for which the current condition is \code{FALSE}.
#'
#' \item \code{dec_pos} Color representing cases of \code{\link{dec_pos}}, for which the current decision is \code{positive}.
#'
#' \item \code{dec_neg} Color representing cases in \code{\link{dec_neg}}, for which the current decision is \code{negative}.
#'
#' \item \code{dec_cor} Color representing cases of correct decisions \code{\link{dec_cor}}, for which the current decision is \code{accurate}.
#'
#' \item \code{dec_err} Color representing cases of erroneous decisions \code{\link{dec_err}}, for which the current decision is \code{inaccurate}.
#'
#' \item \code{hi} Color representing \emph{hits} or true positives in \code{\link{hi}}
#' (i.e., correct cases for which the current condition is TRUE and the decision is positive).
#'
#' \item \code{mi} Color representing \emph{misses} or false negatives in \code{\link{mi}}
#' (i.e., incorrect cases for which the current condition is TRUE but the decision is negative).
#'
#' \item \code{fa} Color representing \emph{false alarms} or false positives in \code{\link{fa}}
#' (i.e., incorrect cases for which the current condition is FALSE but the decision is positive).
#'
#' \item \code{cr} Color representing \emph{correct rejections} or true negatives in \code{\link{cr}}
#' (i.e., correct cases for which the current condition is FALSE and the decision is negative).
#'
#' \item \code{ppv} Color representing \emph{positive predictive values} \code{\link{PPV}} (i.e., the conditional probability that
#' the condition is TRUE, provided that the decision is positive).
#'
#' \item \code{npv} Color representing \emph{negative predictive values} \code{\link{NPV}} (i.e., the conditional probability that
#' the condition is FALSE, provided that the decision is negative).
#'
#' \item \code{txt} Color used for text labels.
#'
#' \item \code{brd} Color used for borders.
#'
#' \item \code{bg} Color used for plot background (used to set \code{par(bg = bg_col)}).
#'
#' }
#'
#' Note that color names for frequencies correspond to frequency names,
#' but are different for probabilities (which are written in lowercase
#' and only \code{\link{PPV}} and \code{\link{NPV}} have assigned colors).
#'
#' @examples
#' pal # shows all color names and current values
#' pal["hi"] # shows the current color for hits (true positives, TP)
#' pal["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{num}} contains basic numeric parameters;
#' \code{\link{init_num}} initializes basic numeric parameters;
#' \code{\link{txt}} contains current text information;
#' \code{\link{init_txt}} initializes text information;
#' \code{\link{freq}} contains current frequency information;
#' \code{\link{comp_freq}} computes current frequency information;
#' \code{\link{prob}} contains current probability information;
#' \code{\link{comp_prob}} computes current probability information.
#'
#' @export
## pal: Definition ------
pal <- init_pal() ## apply
## Check:
# pal
# length(pal) # => 15 colors
# pal[2] == pal["true"]
## pal_org: A copy of original color palette: --------
#' Original color palette.
#'
#' \code{pal_org} is a copy of \code{\link{pal}}
#' (to retrieve original set of colors in case
#' \code{\link{pal}} is changed).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_org} to re-set default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_org # shows all color names and current values
#' pal_org["hi"] # shows the current color for hits (true positives, TP)
#' pal_org["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_org <- pal # copy pal
## pal_bw: A black-and-white (b/w/grey) color palette: --------
#' Alternative color palette for black-and-white (greyscale) graphs.
#'
#' \code{pal_bw} is initialized to a vector of named elements (colors)
#' to define an alternative (black-and-white, b/w) scenario color scheme.
#'
#' Note that \code{pal_bw} uses various shades of grey for frequency boxes
#' so that their bounds remain visible on a white background
#' when \code{f_lwd = 0} (as per default for most graphs).
#'
#' See \code{\link{pal_bwp}} for a stricter version that enforces
#' black text and lines on white boxes (e.g., for printing purposes).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_bw} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_bw # shows all color names and current values
#' pal_bw["hi"] # shows the current color for hits (true positives, TP)
#' pal_bw["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_bw <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.90, .99), # darker white
cond_false_col = grey(.80, .99), # darker white
dec_pos_col = grey(.85, .99), # darker white
dec_neg_col = grey(.70, .99), # darker white
dec_cor_col = grey(.75, .99), # darker white
dec_err_col = grey(.60, .99), # darker white
hi_col = grey(.80, .99), # brighter 1
mi_col = grey(.60, .99), # darker 1
fa_col = grey(.50, .99), # darker 2
cr_col = grey(.70, .99), # brighter 2
PPV_col = grey(.60, .99), # medium grey
NPV_col = grey(.45, .99), # darker grey
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_bw
# pal_bw["hi"]
## pal_bwp: A strict black-and-white (b/w) color palette for printing purposes: --------
#' Alternative color palette for black-and-white graphs (for printing purposes).
#'
#' \code{pal_bwp} is initialized to a vector of named elements (colors)
#' to define a strict (black-and-white, b/w) scenario color scheme
#' that is suited for printing graphs in black-and-white.
#'
#' \code{pal_bwp} is a stricter version of the greyscale
#' palette \code{\link{pal_bw}} that enforces
#' black text and lines on white boxes. Thus, the bounds of frequency boxes
#' are invisible on white backgrounds unless the default of
#' \code{f_lwd = 0} is changed (e.g., to \code{f_lwd = 1}).
#'
#' Some background colors (of frequencies) are also used as
#' foreground colors (of probabilities, e.g.,
#' in \code{\link{plot_curve}} and \code{\link{plot_plane}}).
#' For this reason, the plotting functions detect and
#' adjust colors and/or line settings when \code{pal_bwp}
#' is used.
#'
#' See \code{\link{pal_bw}} for a more permissible black-and-white
#' palette that uses various shades of grey for frequency boxes
#' so that their bounds remain visible on a white background
#' when \code{f_lwd = 0} (as per default for most graphs).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_bwp} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_bwp # shows all color names and current values
#' pal_bwp["hi"] # shows the current color for hits (true positives, TP)
#' pal_bwp["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_bwp <- init_pal(N_col = my_white, # grey(.95, .99), # nearly white
cond_true_col = my_white, # grey(.90, .99), # darker white
cond_false_col = my_white, # grey(.80, .99), # darker white
dec_pos_col = my_white, # grey(.85, .99), # darker white
dec_neg_col = my_white, # grey(.70, .99), # darker white
dec_cor_col = my_white, # grey(.75, .99), # darker white
dec_err_col = my_white, # grey(.60, .99), # darker white
hi_col = my_white, # grey(.80, .99), # brighter 1
mi_col = my_white, # grey(.60, .99), # darker 1
fa_col = my_white, # grey(.50, .99), # darker 2
cr_col = my_white, # grey(.70, .99), # brighter 2
PPV_col = my_black, # grey(.60, .99), # medium grey
NPV_col = my_black, # grey(.45, .99), # darker grey
txt_col = my_black, # grey(0, .99), # black
brd_col = my_black # grey(.10, .99) # almost black
)
## Check:
# pal_bwp
# pal_bwp["hi"]
## pal_rgb: A reduced RGB color palette: --------
#' Alternative color palette for graphs (with RGB colors).
#'
#' \code{pal_rgb} is initialized to a vector of named elements (colors)
#' to define an alternative (reduced) scenario color scheme
#' (using red, green, and blue colors).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_rgb} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_rgb # shows all color names and current values
#' pal_rgb["hi"] # shows the current color for hits (true positives, TP)
#' pal_rgb["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_rgb <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.90, .99), # darker white
cond_false_col = grey(.75, .99), # lighter white
dec_pos_col = grey(.85, .99), # lighter grey
dec_neg_col = grey(.70, .99), # darker grey
dec_cor_col = grey(.75, .99), # lighter grey
dec_err_col = grey(.60, .99), # darker grey
# hi_col = pal["hi"], # from pal
# mi_col = pal["mi"], # from pal
# fa_col = pal["fa"], # from pal
# cr_col = pal["cr"], # from pal
# PPV_col = grey(.60, .99), # medium grey
# NPV_col = grey(.45, .99), # darker grey
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_rgb
# pal_rgb["N"] # => "#D9D9D9FC"
## Use reduced RGB color scheme (as default):
# pal <- pal_rgb
## Note: Check http://colorbrewer2.org for alternatives:
## http://colorbrewer2.org/?type=qualitative&scheme=Paired&n=4
## pal_mod: A modern (green/blue/orange) color palette: --------
#' Modern color palette (in green/blue/orange).
#'
#' \code{pal_mod} is initialized to a vector of named colors
#' to define a modern scenario color scheme (in green/blue/orange).
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_mod} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_mod # shows all color names and current values
#' pal_mod["hi"] # shows the current color for hits (true positives, TP)
#' pal_mod["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_mod <- init_pal(N_col = grey(.90, .99), # "wheat3", nearly white
cond_true_col = my_yellow, # col_sand_mid, # grey(.80, .99), # "wheat3", #
cond_false_col = grey(.75, .99), # col_sand_mid, # "wheat4"
dec_pos_col = col_orange_1, # my_orange, # col_red_1, # grey(.85, .99), # col_grey_1,
dec_neg_col = grey(.65, .99), # col_grey_2,
dec_cor_col = my_green,
dec_err_col = my_blue,
hi_col = col_green_1,
mi_col = col_blue_1,
fa_col = col_blue_3,
cr_col = col_green_2,
PPV_col = col_orange_2,
NPV_col = col_blue_3,
txt_col = grey(0, .99), # black
brd_col = col_sand_dark
)
## Check:
# pal_mod
# pal_mod["hi"] # => "#B8D989"
## Use pal_mod color scheme (as default):
# pal <- pal_mod
## pal_mbw: A reduced modern (green/blue/bw) color palette: --------
#' Modern and reduced color palette (in green/blue/bw).
#'
#' \code{pal_mod} is initialized to a vector of named colors
#' to define a reduced modern scenario color scheme (in green/blue/bw).
#'
#' See \code{\link{pal_org}} for original color information;
#' \code{\link{pal_mod}} for a richer modern color palette; and
#' \code{\link{pal_bw}} for a more reduced black-and-white color palette.
#'
#' Assign \code{pal <- pal_mbw} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_mbw # shows all color names and current values
#' pal_mbw["hi"] # shows the current color for hits (true positives, TP)
#' pal_mbw["hi"] <- "gold" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information;
#' \code{\link{pal_org}} for original color palette;
#' \code{\link{pal_mod}} for a richer modern color palette;
#' \code{\link{pal_bw}} for a more reduced black-and-white color palette.
#'
#' @export
pal_mbw <- init_pal(N_col = grey(.90, .99), # "wheat3", nearly white
cond_true_col = grey(.80, .99), # my_yellow, # col_sand_mid, # # "wheat3", #
cond_false_col = grey(.75, .99), # col_sand_mid, # "wheat4"
dec_pos_col = grey(.85, .99), # col_orange_1, # my_orange, # col_red_1, # col_grey_1,
dec_neg_col = grey(.65, .99), # col_grey_2,
dec_cor_col = my_green,
dec_err_col = my_blue,
hi_col = col_green_1,
mi_col = col_blue_1,
fa_col = col_blue_3,
cr_col = col_green_2,
PPV_col = col_orange_2,
NPV_col = col_blue_3,
txt_col = grey(0, .99), # black
brd_col = col_sand_dark
)
## Check:
# pal_mbw
# pal_mbw["cond_true"] # => "#CCCCCCFC"
## Use pal_mbw color scheme (as default):
# pal <- pal_mbw
## pal_kn: A uni.kn palette: --------
#' Alternative color palette for kn.
#'
#' \code{pal_kn} is initialized to a vector of named elements (colors)
#' to define an alternative (kn) scenario color scheme.
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_kn} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_kn # shows all color names and current values
#' pal_kn["hi"] # shows the current color for hits (true positives, TP)
#' pal_kn["hi"] <- "grey" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal_unikn}} contains more \bold{unikn} colors;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_kn <- init_pal(N_col = grey(.95, .99), # nearly white
cond_true_col = grey(.70, .99), # darker white
cond_false_col = grey(.85, .99), # darker white
dec_pos_col = grey(.60, .99), # darker white
dec_neg_col = grey(.75, .99), # darker white
dec_cor_col = grey(.50, .99), # grey
dec_err_col = grey(.65, .99), # darker white
hi_col = pal_seeblau[[4]],
mi_col = pal_seeblau[[2]],
fa_col = pal_seeblau[[1]],
cr_col = pal_seeblau[[3]],
PPV_col = col_orange_2,
NPV_col = pal_seeblau[[5]],
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_kn
# pal_kn["hi"]
## Use uni.kn color scheme (as default):
# pal <- pal_kn
## pal_unikn: A unikn palette: --------
#' Alternative color palette for unikn.
#'
#' \code{pal_unikn} is initialized to a vector of named elements (colors)
#' to define an alternative (unikn) scenario color scheme.
#'
#' See \code{\link{pal}} for default color information.
#'
#' Assign \code{pal <- pal_unikn} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_unikn # shows all color names and current values
#' pal_unikn["hi"] # shows the current color for hits (true positives, TP)
#' pal_unikn["hi"] <- "grey" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal_kn}} contains fewer \bold{unikn} colors;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_unikn <- init_pal(N_col = grey(.95, 1), # nearly white
cond_true_col = pal_seeblau[[3]],
cond_false_col = pal_seeblau[[1]],
dec_pos_col = pal_pinky[[2]],
dec_neg_col = pal_karpfenblau[[2]],
dec_cor_col = pal_seegruen[[2]],
dec_err_col = pal_bordeaux[[2]],
hi_col = pal_petrol[[2]],
mi_col = pal_bordeaux[[1]],
fa_col = pal_bordeaux[[2]],
cr_col = pal_petrol[[1]],
PPV_col = pal_pinky[[4]],
NPV_col = pal_karpfenblau[[4]],
txt_col = grey(0, 1), # black
brd_col = grey(.10, 1) # almost black
)
## Check:
# pal_unikn
# pal_unikn["hi"]
## Use pal_unikn color scheme (as default):
# pal <- pal_unikn
## pal_vir: A viridis color palette: ----------
## Using viridisLite (version 0.3.0):
## URL: https://github.com/sjmgarnier/viridisLite
## Maintainer: Simon Garnier <garnier@njit.edu>
# viridisLite::viridis(4)
vir_04 <- c("#440154FF", "#31688EFF", "#35B779FF", "#FDE725FF")
# viridisLite::viridis(8)
vir_08 <- c("#440154FF", "#46337EFF", "#365C8DFF", "#277F8EFF",
"#1FA187FF", "#4AC16DFF", "#9FDA3AFF", "#FDE725FF")
# viridisLite::viridis(12)
vir_12 <- c("#440154FF", "#482173FF", "#433E85FF", "#38598CFF",
"#2D708EFF", "#25858EFF", "#1E9B8AFF", "#2BB07FFF",
"#51C56AFF", "#85D54AFF", "#C2DF23FF", "#FDE725FF")
#' Alternative color palette using viridis colors.
#'
#' \code{pal_vir} is initialized to a vector of named elements (colors)
#' to define a scenario color scheme modeled on the \code{viridis} color scale.
#'
#' These colors are select by the Matplotlib \code{viridis} color map
#' created by Stéfan van der Walt and Nathaniel Smith.
#' See the \code{viridisLite} package (maintained by Simon Garnier)
#' for further information.
#'
#' Assign \code{pal <- pal_vir} to use as default color scheme
#' throughout the \bold{riskyr} package.
#'
#' @examples
#' pal_vir # shows all color names and current values
#' pal_vir["hi"] # shows the current color for hits (true positives, TP)
#' pal_vir["hi"] <- "green3" # defines a new color for hits (true positives, TP)
#'
#' @family color palettes
#' @family lists containing current scenario information
#'
#' @seealso
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_vir <- init_pal(N_col = grey(.70, .99), # mid-grey
cond_true_col = grey(.85, .99), # brighter by 15
cond_false_col = grey(.55, .99), # darker
dec_pos_col = grey(.80, .99), # brighter by 10
dec_neg_col = grey(.60, .99), # darker
dec_cor_col = grey(.90, .99), # brighter by 20
dec_err_col = grey(.50, .99), # darker
hi_col = vir_12[10], # hi: bright green
mi_col = vir_12[12], # mi: yellow
fa_col = vir_12[5], # fa: bluish
cr_col = vir_12[8], # cr: darker green
PPV_col = vir_12[9], # between hi and cr
NPV_col = vir_12[3], # beyond fa
txt_col = grey(0, .99), # black
brd_col = grey(.10, .99) # almost black
)
## Check:
# pal_vir
# pal_vir["hi"]
## Use viridis color scheme (as default):
# pal <- pal_vir
## Set default color palette: -------
## Use pal_mbw by default (riskyr 0.2.0):
# pal <- pal_mbw
## Use pal_mod by default (riskyr 0.2.0.9000+):
pal <- pal_mod
## Test:
# pal <- pal_bwp
# pal <- pal_unikn
## Define a crisk color palette: --------
# Define a mixed color palette:
pal_mix <- c("deepskyblue", "deeppink",
col_green_1, col_green_2, col_orange_1, col_orange_2,
col_blue_1, col_blue_2, col_blue_3, col_blue_4,
col_red_1, col_red_2,
col_sand_light, col_sand_mid, col_sand_dark,
my_whitish, my_bluish, my_yellow, my_orange)
names(pal_mix) <- c("deepskyblue", "deeppink", "lightgreen", "green", "lightorange", "orange",
"blue1", "blue2", "blue3", "blue4",
"red1", "red2",
"sand1", "sand2", "sand3",
"my_whitish", "my_bluish", "my_yellow", "my_orange")
# unikn::seecol(pal_mix)
# Select pal_crisk colors:
pal_crisk_select <- c(pal_mix["deepskyblue"], pal_mix["red2"],
"black", "grey50", pal_mix["deeppink"],
pal_mix["sand2"], pal_mix["my_yellow"],
pal_mix["blue4"], pal_mix["my_orange"], pal_mix["green"])
names(pal_crisk_select) <- c("cum", "rinc",
"txt", "aux", "high",
"pas", "rem",
"delta", "poly", "popu")
pal_crisk_select["poly"] <- pal_crisk_select["cum"] # make "poly"" same color as "cum"
# unikn::seecol(pal_crisk_select)
# pal_crisk: Documentation and definition:
#' Color palette for cumulative risk curve.
#'
#' \code{pal_crisk} defines a default color palette
#' for the \code{\link{plot_crisk}} function
#' (as a named vector).
#'
#' Color names and referents in plots
#' generated by \code{\link{plot_crisk}}:
#'
#' \enumerate{
#' \item \code{"cum"}: Cumulative risk curve
#' \item \code{"rinc"}: Relative risk increments
#'
#' \item \code{"txt"}: Text labels
#' \item \code{"aux"}: Auxiliary labels and lines
#' \item \code{"high"}: Highlighting elements
#'
#' \item \code{"pas"}: Past/passed risk
#' \item \code{"rem"}: Remaining risk
#'
#' \item \code{"delta"}: Delta-X- and -Y increments
#' \item \code{"poly"}: Polygon of increments
#' \item \code{"popu"}: Population partitions
#' }
#'
#' @examples
#' pal_crisk # show color palette (and names)
#'
#' @family color palettes
#'
#' @seealso
#' \code{\link{plot_crisk}} plots cumulative risk curves;
#' \code{\link{pal}} contains current color information;
#' \code{\link{init_pal}} initializes color information.
#'
#' @export
pal_crisk <- pal_crisk_select
# +++ here now +++
# unikn::seecol(pal_crisk)
# knitr::kable(pal_crisk, caption = "The `pal_crisk` color palette.")
## (*) Done: ----------
## - Addressed limitation: [2019 01 23]
## Lack of an explicit background color (e.g., "white" or NA by default).
## Solution implemented:
# 1. bg_col <- "white" # in all color palettes
# 2. par(bg = col_pal[["bg"]]) # in all plot functions
## (+) ToDo: ----------
## - Lack of most probability colors:
## Only PPV and NPV are assigned dedicated colors.
## Plotting ppod and acc in plot_curve and plot_plane recruits frequency colors.
## This can lead to conflicts (e.g., with pal_bwp when par("bg") == "white").
## - Lack of ability to invert boxes (e.g., text bright, fill color dark).
## ToDos:
## - Add more 2x2-dimensional (+/-, T/F) color palettes.
## - Add dark (inverted) color palette (bright text on dark boxes).
## eof. ------------------------------------------
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