plot_icons: Plot an icon array of a population.
In riskyr: Rendering Risk Literacy more Transparent
plot_icons R Documentation
Plot an icon array of a population.
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
plot_icons(
prev = num$prev,
sens = num$sens,
mirt = NA,
spec = num$spec,
fart = NA,
N = freq$N,
sample = FALSE,
arr_type = "array",
by = "all",
ident_order = c("hi", "mi", "fa", "cr"),
icon_types = 22,
icon_size = NULL,
icon_brd_lwd = 1.5,
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",
lbl_txt = txt,
main = txt$scen_lbl,
sub = "type",
title_lbl = NULL,
cex_lbl = 0.9,
col_pal = pal,
transparency = 0.5,
mar_notes = FALSE,
...
)
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.
sample
Boolean value that determines whether frequency values
are sampled from N, given the probability values of
prev, sens, and spec.
Default: sample = FALSE.
arr_type
The icons can be arranged in different ways
resulting in different types of displays:
-
arr_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.
-
arr_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.
-
arr_type = "mosaic": Icons are ordered like in a mosaic plot.
The area size displays the relative proportions of their frequencies.
-
arr_type = "fillequal": Icons are positioned into equally sized blocks.
Thus, their density reflects the relative proportions of their frequencies.
-
arr_type = "fillleft": Icons are randomly filled from the left.
-
arr_type = "filltop": Icons are randomly filled from the top.
-
arr_type = "scatter": Icons are randomly scattered into the plot.
by
A character code specifying a perspective to split the population into subsets,
with 4 options:
-
"all": by condition (cd) and by decision (dc):
hi, mi, fa, cr cases (default);
-
"cd": by condition (cd) only:
cond_true vs. cond_false cases;
-
"dc": by decision (dc) only:
dec_pos vs. dec_neg cases;
-
"ac": by accuracy (ac) only:
dec_cor vs. dec_err cases.
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_types
specifies the appearance of the icons as a vector.
Default: icon_types = 11 (i.e., squares with border).
Accepts values from 1 to 25 (see ?points).
icon_size
specifies the size of the icons via cex
Default: icon_size = NULL for automatic calculation.
icon_brd_lwd
specifies the border width of icons (if applicable).
Default: icon_brd_lwd = 1.5. Set to NA for no border.
block_d
The distance between blocks.
Default: block_d = NULL for automatic calculation;
(does not apply to "filleft", "filltop", and "scatter")
border_d
The distance of icons to the border.
Default: border_d = 0.1.
Additional options for controlling the arrangement of arrays
(for arr_type = "array" and "shuffledarray"):
block_size_row
specifies how many icons should be in each block row.
Default: block_size_row = 10.
block_size_col
specifies how many icons should be in each block column.
Default: block_size_col = 10.
nblocks_row
Number of blocks per row.
Default: nblocks_row = NULL for automatic calculation.
nblocks_col
Number of blocks per column.
Default: nblocks_col = NULL for automatic calculation.
fill_array
specifies how the blocks are filled into the array.
Options: fill_array = "left" (default) vs. "top".
fill_blocks
specifies how icons within blocks are filled.
Options: fill_blocks = "rowwise" (default) and "colwise".
Generic text and color options:
lbl_txt
Default label set for text elements.
Default: lbl_txt = txt.
main
Text label for main plot title.
Default: main = txt$scen_lbl.
sub
Text label for plot subtitle (on 2nd line).
Default: sub = "type" shows information on current plot type.
title_lbl
Deprecated text label for current plot title.
Replaced by main.
cex_lbl
Scaling factor for text labels.
Default: cex_lbl = .90.
col_pal
Color palette.
Default: col_pal = pal.
transparency
Specifies the transparency for overlapping icons
(not for arr_type = "array" and "shuffledarray").
mar_notes
Boolean option for showing margin notes.
Default: mar_notes = FALSE.
...
Other (graphical) parameters.
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.
Value
Nothing (NULL).
See Also
Other visualization functions:
plot.riskyr(),
plot_area(),
plot_bar(),
plot_crisk(),
plot_curve(),
plot_fnet(),
plot_mosaic(),
plot_plane(),
plot_prism(),
plot_tab(),
plot_tree()
Examples
# Basics:
plot_icons(N = 1000) # icon array with default settings (arr_type = "array")
plot_icons(arr_type = "shuffledarray", N = 1000) # icon array with shuffled IDs
# Sampling:
plot_icons(N = 1000, prev = 1/2, sens = 2/3, spec = 6/7, sample = TRUE)
# array types:
plot_icons(arr_type = "mosaic", N = 1000) # areas as in mosaic plot
plot_icons(arr_type = "fillequal", N = 1000) # areas of equal size (probability as density)
plot_icons(arr_type = "fillleft", N = 1000) # icons filled from left to right (in columns)
plot_icons(arr_type = "filltop", N = 1000) # icons filled from top to bottom (in rows)
plot_icons(arr_type = "scatter", N = 1000) # icons randomly scattered
# by:
plot_icons(N = 1000, by = "all") # hi, mi, fa, cr (TP, FN, FP, TN) cases
plot_icons(N = 1000, by = "cd", main = "Cases by condition") # (hi + mi) vs. (fa + cr)
plot_icons(N = 1000, by = "dc", main = "Cases by decision") # (hi + fa) vs. (mi + cr)
plot_icons(N = 1000, by = "ac", main = "Cases by accuracy") # (hi + cr) vs. (fa + mi)
# Custom icon types and colors:
plot_icons(N = 800, arr_type = "array", icon_types = c(21, 22, 23, 24),
block_d = 0.5, border_d = 0.5, col_pal = pal_vir)
plot_icons(N = 800, arr_type = "shuffledarray", icon_types = c(21, 23, 24, 22),
block_d = 0.5, border_d = 0.5)
plot_icons(N = 800, arr_type = "fillequal", icon_types = c(21, 22, 22, 21),
icon_brd_lwd = .5, cex = 1, cex_lbl = 1.1)
# Text and color options:
plot_icons(N = 1000, prev = .5, sens = .5, spec = .5, arr_type = "shuffledarray",
main = "My title", sub = NA, lbl_txt = txt_TF, col_pal = pal_vir, mar_notes = TRUE)
plot_icons(N = 1000, prev = .5, sens = .5, spec = .5, arr_type = "shuffledarray",
main = "Green vs. red", col_pal = pal_rgb, transparency = .5)
riskyr documentation built on Aug. 15, 2022, 9:09 a.m.
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| plot_icons | R Documentation |
Plot an icon array of a population.
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
plot_icons(
prev = num$prev,
sens = num$sens,
mirt = NA,
spec = num$spec,
fart = NA,
N = freq$N,
sample = FALSE,
arr_type = "array",
by = "all",
ident_order = c("hi", "mi", "fa", "cr"),
icon_types = 22,
icon_size = NULL,
icon_brd_lwd = 1.5,
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",
lbl_txt = txt,
main = txt$scen_lbl,
sub = "type",
title_lbl = NULL,
cex_lbl = 0.9,
col_pal = pal,
transparency = 0.5,
mar_notes = FALSE,
...
)
Arguments
prev |
The condition's prevalence |
sens |
The decision's sensitivity |
mirt |
The decision's miss rate |
spec |
The decision's specificity value |
fart |
The decision's false alarm rate |
N |
The number of individuals in the population.
A suitable value of |
sample |
Boolean value that determines whether frequency values
are sampled from |
arr_type |
The icons can be arranged in different ways resulting in different types of displays:
|
by |
A character code specifying a perspective to split the population into subsets, with 4 options:
|
ident_order |
The order in which icon identities
(i.e., hi, mi, fa, and cr) are plotted.
Default: |
icon_types |
specifies the appearance of the icons as a vector.
Default: |
icon_size |
specifies the size of the icons via |
icon_brd_lwd |
specifies the border width of icons (if applicable).
Default: |
block_d |
The distance between blocks.
Default: |
border_d |
The distance of icons to the border.
Default: Additional options for controlling the arrangement of arrays
(for |
block_size_row |
specifies how many icons should be in each block row.
Default: |
block_size_col |
specifies how many icons should be in each block column.
Default: |
nblocks_row |
Number of blocks per row.
Default: |
nblocks_col |
Number of blocks per column.
Default: |
fill_array |
specifies how the blocks are filled into the array.
Options: |
fill_blocks |
specifies how icons within blocks are filled.
Options: Generic text and color options: |
lbl_txt |
Default label set for text elements.
Default: |
main |
Text label for main plot title.
Default: |
sub |
Text label for plot subtitle (on 2nd line).
Default: |
title_lbl |
Deprecated text label for current plot title.
Replaced by |
cex_lbl |
Scaling factor for text labels.
Default: |
col_pal |
Color palette.
Default: |
transparency |
Specifies the transparency for overlapping icons
(not for |
mar_notes |
Boolean option for showing margin notes.
Default: |
... |
Other (graphical) parameters. |
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.
Value
Nothing (NULL).
See Also
Other visualization functions:
plot.riskyr(),
plot_area(),
plot_bar(),
plot_crisk(),
plot_curve(),
plot_fnet(),
plot_mosaic(),
plot_plane(),
plot_prism(),
plot_tab(),
plot_tree()
Examples
# Basics:
plot_icons(N = 1000) # icon array with default settings (arr_type = "array")
plot_icons(arr_type = "shuffledarray", N = 1000) # icon array with shuffled IDs
# Sampling:
plot_icons(N = 1000, prev = 1/2, sens = 2/3, spec = 6/7, sample = TRUE)
# array types:
plot_icons(arr_type = "mosaic", N = 1000) # areas as in mosaic plot
plot_icons(arr_type = "fillequal", N = 1000) # areas of equal size (probability as density)
plot_icons(arr_type = "fillleft", N = 1000) # icons filled from left to right (in columns)
plot_icons(arr_type = "filltop", N = 1000) # icons filled from top to bottom (in rows)
plot_icons(arr_type = "scatter", N = 1000) # icons randomly scattered
# by:
plot_icons(N = 1000, by = "all") # hi, mi, fa, cr (TP, FN, FP, TN) cases
plot_icons(N = 1000, by = "cd", main = "Cases by condition") # (hi + mi) vs. (fa + cr)
plot_icons(N = 1000, by = "dc", main = "Cases by decision") # (hi + fa) vs. (mi + cr)
plot_icons(N = 1000, by = "ac", main = "Cases by accuracy") # (hi + cr) vs. (fa + mi)
# Custom icon types and colors:
plot_icons(N = 800, arr_type = "array", icon_types = c(21, 22, 23, 24),
block_d = 0.5, border_d = 0.5, col_pal = pal_vir)
plot_icons(N = 800, arr_type = "shuffledarray", icon_types = c(21, 23, 24, 22),
block_d = 0.5, border_d = 0.5)
plot_icons(N = 800, arr_type = "fillequal", icon_types = c(21, 22, 22, 21),
icon_brd_lwd = .5, cex = 1, cex_lbl = 1.1)
# Text and color options:
plot_icons(N = 1000, prev = .5, sens = .5, spec = .5, arr_type = "shuffledarray",
main = "My title", sub = NA, lbl_txt = txt_TF, col_pal = pal_vir, mar_notes = TRUE)
plot_icons(N = 1000, prev = .5, sens = .5, spec = .5, arr_type = "shuffledarray",
main = "Green vs. red", col_pal = pal_rgb, transparency = .5)
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