Package 'Gmisc'

Description

This is a collection of functions that I've found useful in my research. The package is inspired by Frank Harrell's Hmisc package. The main focus is on tables, plots, and knitr-integration.

Awesome tables

The getDescriptionStatsBy is a straightforward function that aims at helping you to generate a descriptive table stratified by different variables. In other words, the function returns everything you need for generating a Table 1 ready for publication. This function is accompanied by the describeMean, describeMedian, describeProp, and describeFactors functions.

The mergeDesc allows you to merge a set of outputs getDescriptionStatsBy into a htmlTable with the rgroup arguments automatically generated, see vignette("descriptives", package = "Gmisc") for a detailed workflow description.

Some fancy plots

The transition plot function, transitionPlot, is for descriptive purposes. It tries to illustrate the size of change between one state and the next, i.e. a transition. This is basically a graph of based upon table(var1, var2).

The Singular value decomposition is a common method for reducing the number of variables. Unfortunately this compression can reduce the interpretability of the model. The getSvdMostInfluential function tries to remedy that by identifying the most influential elements from the V-matrix.

Other stuff

The insertRowAndKeepAttr simply adds a row while remembering all the attributes previously set by using the copyAllNewAttributes. The mergeLists tries to merge lists that do not have identical elements.

Author(s)

Maintainer: Max Gordon [email protected] (ORCID)

Authors:

• Max Gordon [email protected] (ORCID)

See Also

Useful links:

• https://gforge.se

• Report bugs at https://github.com/gforge/Gmisc/issues

Description

Aligns a set of boxGrob/boxPropGrob according to the first positional argument.

Align a list of boxes vertically or horizontally. Designed for piping ('|>').

Usage

alignVertical(
  reference,
  ...,
  position = c("center", "top", "bottom"),
  subelement = NULL
)

alignHorizontal(
  reference,
  ...,
  position = c("center", "left", "right"),
  sub_position = c("none", "left", "right"),
  subelement = NULL
)

align(x, ...)

## Default S3 method:
align(x, ...)

## S3 method for class 'list'
align(x, ...)

## S3 method for class 'Gmisc_list_of_boxes'
align(x, ..., axis = c("y", "x", "vertical", "horizontal"))

Arguments

Value

list with the boxes that are to be aligned

The aligned list of boxes (class 'Gmisc_list_of_boxes').

See Also

Other flowchart components: append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

library(grid)
grid.newpage()

# Create a reference box
box <- boxGrob("A cool reference box",
  x = .5, y = .8,
  box_gp = gpar(fill = "#ADB5C7")
)

# Create a group of boxes to align
boxes <- list(
  another_box = boxGrob("A horizontal box", x = .1, y = .5),
  yet_another_box = boxGrob("Another horizontal box", x = .8, y = .3)
)

# Align the group and then individual boxes within that group
# (do not pipe the list into the function, as the first argument is `reference`)
aligned_boxes <- alignHorizontal(boxes, reference = box, position = "right") |>
  alignVertical(reference = .5, position = "center")

# Example: align a nested element inside a complex list using a deep path
complex_list <- list(
  arms = list(
    early = list(boxGrob("Early", x = .2, y = .4)),
    late = list(boxGrob("Late", x = .8, y = .2))
  ),
  detail = list(
    list(boxGrob("D_early", x = .1, y = .6)),
    list(boxGrob("D_late", x = .9, y = .1))
  )
)

# Align the first detail element to the early arm by deep path
complex_list <- complex_list |>
  alignHorizontal(
    reference = c("arms", "early"),
    position = "center",
    subelement = c("detail", 1)
  )

# Print the reference and the aligned boxes
box
aligned_boxes
complex_list

Description

Append an element to a list of boxes, preserving attributes/class. Masks 'base::append' to support S3 dispatch.

Usage

append(x, values, after = length(x))

## Default S3 method:
append(x, values, after = length(x))

## S3 method for class 'Gmisc_list_of_boxes'
append(x, values, after = length(x))

Arguments

Value

Updated list of boxes.

See Also

Other flowchart components: align(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Description

This is an experimental addition to the original bezierArrowSmpl with the addition of a gradient in the center of the arrow that fades.

Usage

bezierArrowGradient(
  x = c(0.2, 0.7, 0.3, 0.9),
  y = c(0.2, 0.2, 0.9, 0.9),
  width = 0.05,
  clr = "#000000",
  default.units = "npc",
  align_2_axis = TRUE,
  grdt_type = c("triangle", "rectangle"),
  grdt_prop = 0.8,
  grdt_decrease_prop = 0.5,
  grdt_clr_prop = 0.7,
  grdt_line_width,
  grdt_clr = "#2F4F2F",
  vp = NULL,
  gp = gpar(),
  rm_intersect = 3L,
  ...
)

Arguments

Value

A grob of gList-type

Note

The triangle section of the arrow is not currently included in the gradient.

Examples

library(grid)
grid::grid.newpage()
arrowGrob <- bezierArrowGradient(
  x = c(.1, .3, .6, .9),
  y = c(0.2, 0.2, 0.9, 0.9)
)
grid.draw(arrowGrob)

Description

This is an alternative to the grid packages bezierGrob with the advantage that it allows you to draw an arrow with a specific unit width. Note, it has only a end-arrow at this point.

Usage

bezierArrowSmpl(
  x = c(0.2, 0.7, 0.3, 0.9),
  y = c(0.2, 0.2, 0.9, 0.9),
  width = 0.05,
  clr = "#000000",
  default.units = "npc",
  arrow = list(),
  rez = 200,
  align_2_axis = TRUE,
  name = NULL,
  rm_intersect = 3L,
  gp = gpar(),
  vp = NULL
)

Arguments

Value

grid::grob A grob of the class polygonGrob with attributes that correspond to the bezier points.

Examples

library(grid)
grid::grid.newpage()
arrowGrob <- bezierArrowSmpl(
  x = c(.1, .3, .6, .9),
  y = c(0.2, 0.2, 0.9, 0.9)
)
grid.draw(arrowGrob)

Description

Creates a grob box with text inside it.

Usage

boxGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  txt_padding = getOption("boxGrobTxtPadding", default = unit(6 *
    ifelse(is.null(txt_gp$cex), 1, txt_gp$cex), "mm")),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  box_fn = roundrectGrob,
  name = NULL,
  badge_label = NULL,
  badge_position = "top",
  badge_gp = gpar(fill = "steelblue", col = NA),
  badge_txt_gp = gpar(col = "white", cex = 0.7)
)

## S3 method for class 'box'
print(x, ...)

## S3 method for class 'box'
plot(x, ...)

## S3 method for class 'box'
widthDetails(x)

## S3 method for class 'box'
heightDetails(x)

Arguments

Value

A grob

The plot/print

To output the grob objects to the plot either call plot on the object or print it. Note that R automatically prints any object that is outputted to the console. The function calls in turn the grid.draw function on the object.

S3 from the grid package

Width and height functions address the coords attribute for the corresponding information. The widthDetails and heightDetails that provide information on an object.

See Also

The package provides several convenience shape helpers that can be passed to 'boxGrob(..., box_fn = ...)': boxDiamondGrob, boxEllipseGrob, boxRackGrob, boxServerGrob, boxDatabaseGrob, boxDocumentGrob, boxDocumentsGrob, and boxTapeGrob. For examples see the vignette: vignette("Grid-based_flowcharts", package = "Gmisc").

Other flowchart components: align(), append(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

# Note: grid functions are explicitly namespaced in examples to avoid
# relying on attaching the grid package in R CMD check.
grid::grid.newpage()
boxGrob("My box")

Description

Creates a grob box with a centered header and left-justified body text. Useful for flowchart elements that combine a title with bullet points or multi-line descriptions.

Usage

boxHeaderGrob(
  header,
  body,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  bjust = "center",
  header_gp = getOption("boxHeaderGrobTxt", default = gpar(color = "black", cex = 1)),
  body_gp = getOption("boxBodyGrobTxt", default = gpar(color = "black", cex = 0.9)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  box_fn = roundrectGrob,
  name = NULL
)

Arguments

Value

A grob with class "box" compatible with all Gmisc flowchart helpers (coords, distance, connectGrob, spreadVertical, alignHorizontal, etc.)

See Also

Other flowchart components: align(), append(), boxGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

library(grid)
grid.newpage()

# Simple example with header and bullets
box1 <- boxHeaderGrob(
  header = "Early rehabilitation",
  body = paste("0-1 weeks", "• Instruction", "• Pendulum + assisted ROM", sep = "\n"),
  header_gp = gpar(fontsize = 11, fontface = "bold"),
  body_gp = gpar(fontsize = 9),
  box_gp = gpar(fill = "#E8F5E9", col = "#2E7D32")
)
grid.draw(box1)

# Works with all helpers
box2 <- boxHeaderGrob(
  header = "Delayed rehabilitation",
  body = "0-3 weeks\n• Sling immobilisation",
  y = 0.3,
  box_gp = gpar(fill = "#FFF8E1", col = "#EF6C00")
)

# Distance calculation works
d <- distance(box1, box2, type = "v")

# Connect boxes
grid.draw(box2)
connectGrob(box1, box2, type = "vertical")

Description

Creates a grob box with text inside it and a color split in the horizontal axes that allow indicating different proportions. The box can also have a title that spanse the two color areas and that has its own background.

Usage

boxPropGrob(
  label,
  label_left,
  label_right,
  prop,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxPropGrobTxt", default = gpar(color = "black")),
  txt_left_gp = getOption("boxPropGrobLeftTxt", default = gpar(col = "black")),
  txt_right_gp = getOption("boxPropGrobRightTxt", default = gpar(col = "black")),
  box_left_gp = getOption("boxPropGrobLeft", default = gpar(fill = "#E6E8EF")),
  box_right_gp = getOption("boxPropGrobRight", default = gpar(fill = "#FFFDF6")),
  box_highlight_gp = getOption("boxPropGrobHighlight", default = gpar(fill = "#ffffff55",
    col = NA)),
  name = NULL
)

Arguments

Value

A box grob

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

library(grid)
grid::grid.newpage()
boxPropGrob("Main label", "Left text", "Right text", prop = .3)

Description

These helper functions provide alternative box drawing functions that can be passed to 'boxGrob(..., box_fn = ...)' or used via convenience wrappers ('boxDiamondGrob', 'boxEllipseGrob', 'boxRackGrob'). They are intentionally lightweight and implemented using base 'grid' primitives.

Two diamond variants are provided: a rounded diamond (default) implemented with 'xsplineGrob' for slightly softened corners, and a sharp diamond implemented with 'polygonGrob' for strict straight edges.

Approximates an ellipse using a polygon with many points; it respects the box viewport so it scales correctly.

A rectangular box with a slightly darker top band to mimic a server / disk rack look. Implemented by composing a rounded rectangle and an overlaying top strip. The strip is drawn without border to avoid double outlines.

Draws a cylinder-like database symbol (ellipse top, rectangular body, base ellipse).

A document icon with a wavy bottom edge, useful to indicate printed output.

Draws a stack of document shapes by repeating the same shape with offsets.

Left/right curved edges to mimic tape-like icons.

A server-styled box with front-panel vent lines so it is visually distinct from a rack (top strip) representation.

Usage

diamond_rounded_box_fn(x = 0.5, y = 0.5, gp = gpar())

diamond_sharp_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxDiamondGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  rounded = TRUE,
  name = NULL
)

ellipse_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxEllipseGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

rack_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxRackGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

database_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxDatabaseGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

document_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxDocumentGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

documents_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxDocumentsGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

tape_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxTapeGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

server_box_fn(x = 0.5, y = 0.5, gp = gpar())

boxServerGrob(
  label,
  y = unit(0.5, "npc"),
  x = unit(0.5, "npc"),
  width,
  height,
  just = "center",
  bjust = "center",
  txt_gp = getOption("boxGrobTxt", default = gpar(color = "black", cex = 1)),
  box_gp = getOption("boxGrob", default = gpar(fill = "white")),
  name = NULL
)

Arguments

Details

Shape functions are called with 'x' and 'y' in [0,1] inside the box viewport and with 'box_gp' for styling; convenience wrappers match the 'boxGrob' signature.

Value

A 'grid' grob that draws the requested shape inside the box viewport.

See Also

boxGrob for usage and the 'box_fn' argument

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

# These functions are designed to be passed to `boxGrob(..., box_fn = ...)`.
grid::grid.newpage()
d <- boxGrob("Decision", box_fn = diamond_rounded_box_fn)
e <- boxGrob("Start", box_fn = ellipse_box_fn)
r <- boxGrob("Server", box_fn = rack_box_fn)
spreadHorizontal(list(d, e, r))

Description

The function calculates new points according to the offset that lie to the left/right of the provided line.

Usage

calculateLinesAndArrow(
  x,
  y,
  offset,
  end_x = -1,
  end_y = -1,
  arrow_offset = -1,
  rm_intersect = 3L
)

Arguments

Value

list(list(x = ..., y = ...)) Returns a list with the right/left lines that in turn lists with x and y elements

Description

Creates connectors between boxes.

A convenient way to connect boxes in a 'Gmisc_list_of_boxes' or simple 'list' context, designed for piping ('|>').

Usage

connectGrob(
  start,
  end,
  type = c("vertical", "horizontal", "L", "-", "Z", "N", "fan_in_top", "fan_in_center",
    "side"),
  subelmnt = c("right", "left"),
  lty_gp = getOption("connectGrob", default = gpar(fill = "black")),
  arrow_obj = getOption("connectGrobArrow", default = arrow(ends = "last", type =
    "closed")),
  arrow_size = NULL,
  split_pad = unit(2, "mm"),
  margin = unit(2, "mm"),
  smooth = FALSE,
  corner_radius = unit(3, "mm"),
  side = c("auto", "left", "right"),
  label = NULL,
  label_gp = grid::gpar(cex = 0.9),
  label_bg_gp = grid::gpar(fill = "white", col = NA),
  label_pad = unit(1.5, "mm"),
  label_pos = c("mid", "near_start", "near_end"),
  label_offset = unit(2, "mm")
)

## S3 method for class 'connect_boxes'
print(x, ...)

## S3 method for class 'connect_boxes'
plot(x, ...)

## S3 method for class 'connect_boxes_list'
grid.draw(x, recording = TRUE)

## S3 method for class 'connect_boxes_list'
print(x, ...)

## S3 method for class 'connect_boxes_list'
plot(x, ...)

connect(x, ...)

## Default S3 method:
connect(x, ...)

## S3 method for class 'Gmisc_list_of_boxes'
connect(x, from = NULL, to = NULL, ...)

Arguments

Details

The function supports:

• One-to-one: a single start box connected to a single end box.

• One-to-many: a single start box connected to multiple end boxes.

• Many-to-one: multiple start boxes connected to a single end box.

Many-to-many connections are not supported.

If either start or end is a list, a list of connector grobs is returned (one per connection). Otherwise a single connector grob is returned.

Each connector stores its computed geometry in attr(x, "line") (or for each element when a list is returned). This can be reused to construct custom connectors using the calculated coordinates.

Connector types

type controls the connector shape:

• "vertical": straight vertical connector

• "horizontal": straight horizontal connector

• "L": vertical then horizontal (direction chosen automatically)

• "-": straight horizontal connector at the end box y-position

• "Z": horizontal connector with two 90-degree turns

• "N": vertical connector with one horizontal segment When connecting to or from multiple boxes, all connectors share the same bend height.

• "fan_in_top": many-to-one connector merging onto the top edge of the end box Attachment points are evenly distributed along the edge (with optional margin), and all connectors share a common bend height.

• "fan_in_center": many-to-one connector that aggregates stems onto a horizontal bus (shared at the computed bend height) and then a single centered trunk with an arrow that points to the center of the end box. Useful when you want a single arrow to represent the merged flow (e.g. a middle trunk bus).

For type = "N" and type = "fan_in_top" with multi-box connections, a shared bend position is computed so that the horizontal segment aligns visually across all connectors.

Labels

For one-to-one connectors you can add a text label (for example "yes" / "no"). The label is placed near the midpoint of the connector. The label is drawn with a white background for readability. Use label_pad to control padding around the text and label_offset to move the label away from the connector.

Split boxes

When connecting to or from a boxPropGrob, subelmnt controls whether the left or right sub-box x-coordinate is used as the anchor point.

Value

• One-to-one: a grid::grob() with class "connect_boxes".

• One-to-many or many-to-one: a list of grobs with class "connect_boxes_list".

The original list 'x' (upgraded to 'Gmisc_list_of_boxes') with a new connection appended to its '"connections"' attribute. When printed, these connections are drawn.

See Also

['connectGrob']

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, coords(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

library(grid)
grid.newpage()

# Initiate the boxes that we want to connect
boxes <- list(
  start = boxGrob("Top", x = .5, y = .8),
  end = boxGrob("Bottom", x = .5, y = .2),
  side = boxPropGrob("Side", "Left", "Right", prop = .3, x = .2, y = .8),
  exclude = boxGrob("Exclude:\n - Too sick\n - Prev. surgery", x = .8, y = .5, just = "left")
)

# Connect the boxes and print/plot them
connectGrob(boxes$start, boxes$end, "vertical")
connectGrob(boxes$start, boxes$side, "horizontal")
connectGrob(boxes$start, boxes$exclude, "L")

# We can also connect to/from lists
side_boxes <- list(
  left = boxGrob("Left", x = attr(boxes$side, "coords")$left_x, y = .5),
  right = boxGrob("Right", x = attr(boxes$side, "coords")$right_x, y = .5)
)

connectGrob(boxes$side, side_boxes$left, "v", "l")
connectGrob(boxes$side, side_boxes$right, "v", "r")

# Fan-in center example: multiple starts into one center bus and single trunk
list(
  boxes$start,
  boxGrob("S2", x = .3, y = .7),
  boxGrob("S3", x = .7, y = .7)
) |>
  connectGrob(boxes$end, type = "fan_in_center")

# Print the boxes
boxes
side_boxes

Description

The variable is supposed to be directly compatible with table(..., useNA = show_missing). It throws an error if not compatible. It is mostly useful for custom describe functions.

Usage

convertShowMissing(show_missing)

Arguments

Details

Deprecated: This function will be deprecated as all functions now use the useNA style in order to comply with standard R naming.

Value

string

Description

Retrieves the boxes "coords" attribute.

Usage

coords(box)

Arguments

Value

A list with the coordinates

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), distance(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

box <- boxGrob("A test box")
coords(box)

Description

Skips the attributes that the to object already has to avoid overwriting dim and other important attributes

Usage

copyAllNewAttributes(from, to, attr2skip = c(), attr2force = c())

Arguments

Value

object The to argument object

Examples

a <- "test"
attr(a, 'wow') <- 1000
b <- a
b <- copyAllNewAttributes(a, b)
print(attr(b, 'wow'))

Description

This function calculates the amount of missing per row for describeMean, describeMedian and custom description functions. It will return invisibly when no missing values are present.

Usage

descGetMissing(
  x,
  html = TRUE,
  number_first = TRUE,
  percentage_sign = TRUE,
  language = "en",
  useNA.digits = 1,
  ...
)

Arguments

Value

vector A vector with the missing estimate

Description

A function that returns a description of proportions in a factor that contains the number of times a level occurs and the percentage

Usage

describeFactors(
  x,
  html = TRUE,
  digits = 1,
  digits.nonzero = NA,
  number_first = TRUE,
  useNA = c("ifany", "no", "always"),
  useNA.digits = digits,
  horizontal_proportions,
  percentage_sign = TRUE,
  language = "en",
  ...
)

Arguments

Value

A string formatted for printing either latex by HTML

See Also

getDescriptionStatsBy

Other descriptive functions: describeMean(), describeMedian(), describeProp(), getDescriptionStatsBy(), getPvalWilcox()

Examples

set.seed(1)
describeFactors(sample(50, x = c("A", "B", "C"), replace = TRUE))

n <- 500
my_var <- factor(sample(size = n, x = c("A", "B", "C", NA), replace = TRUE))
my_exp <- rbinom(n = n, size = 1, prob = 0.2)
total <- table(my_var, useNA = "ifany")
by(my_var,
  INDICES = my_exp,
  FUN = describeFactors,
  useNA = "ifany",
  horizontal_proportions = total
)

Description

A function that returns a description of a continuous variable using the mean together with the standard deviation. The standard deviation is used as it is "industry standard" to use mean with standard deviation and not because it's the only option.

Usage

describeMean(
  x,
  html = TRUE,
  digits = 1,
  digits.nonzero = NA,
  number_first = TRUE,
  useNA = c("ifany", "no", "always"),
  useNA.digits = digits,
  percentage_sign = TRUE,
  plusmin_str,
  language = "en",
  ...
)

Arguments

Value

string Returns a string formatted for either LaTeX or HTML

See Also

getDescriptionStatsBy

Other descriptive functions: describeFactors(), describeMedian(), describeProp(), getDescriptionStatsBy(), getPvalWilcox()

Examples

describeMean(1:10)
describeMean(c(1:10, NA), useNA = "always")
describeMean(c(1:10, NA), useNA = "no")

Description

A function that returns a description median that contains the interquartile range or the full range

Usage

describeMedian(
  x,
  iqr = TRUE,
  html = TRUE,
  digits = 1,
  digits.nonzero = NA,
  number_first = TRUE,
  useNA = c("ifany", "no", "always"),
  useNA.digits = digits,
  percentage_sign = TRUE,
  language = "en",
  ...
)

Arguments

Value

string A string formatted for either LaTeX or HTML

See Also

getDescriptionStatsBy

Other descriptive functions: describeFactors(), describeMean(), describeProp(), getDescriptionStatsBy(), getPvalWilcox()

Examples

describeMedian(1:10)
describeMedian(c(1:10, NA), useNA = "ifany")

Description

A function that returns a description proportion that contains the number and the percentage

Usage

describeProp(
  x,
  html = TRUE,
  digits = 1,
  digits.nonzero = NA,
  number_first = TRUE,
  useNA = c("ifany", "no", "always"),
  useNA.digits = digits,
  default_ref = NULL,
  percentage_sign = TRUE,
  language = "en",
  ...
)

Arguments

Value

string A string formatted for either LaTeX or HTML

See Also

Other descriptive functions: describeFactors(), describeMean(), describeMedian(), getDescriptionStatsBy(), getPvalWilcox()

Examples

describeProp(factor(sample(50, x = c("A", "B", NA), replace = TRUE)))

Description

Retrieves the distance between two boxes as absolute "mm" units. The function also accepts coords objects as well as a unit or a numeric input.

Usage

distance(
  box1,
  box2,
  type = c("vertical", "horizontal", "euclidean"),
  half = FALSE,
  center = FALSE
)

## S3 method for class 'Gmisc_unit'
print(x, ...)

Arguments

Value

A unit in "mm" with an absolute value. The attribute positive indicates the direction of the value, i.e. if it is TRUE the distance was calculated from the first to the second, otherwise it is FALSE. For euclidean distance the positive attribute is NA. There is also the from and to attributes that has the coordinates that were used for the calculations, for euclidean distance this is NA.

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), equalizeWidths(), flowchart(), insert(), move(), moveBox(), spread()

Examples

box1 <- boxGrob("A test box", y = .8)
box2 <- boxGrob("Another test box", y = .2)
distance(box1, box2, "v")

Formatter wrapper for html_document, facilitates easier porting to docx

Description

This function adds the option of having adaptations needed for seemless integration with MS Word for importing html-documents in the .docx-format. The advantage of html documents is the ability to create advanced formatting frequently needed in medical publications and that is available in the htmlTable function. You can view the series for more details regarding how to achieve fast-track-publishing (ftp) together with knitr.

Usage

docx_document(
  ...,
  self_contained = FALSE,
  mathjax = NULL,
  theme = NULL,
  highlight = NULL,
  css = "rmarkdown/docx.css",
  h1_style = "margin: 24pt 0pt 0pt 0pt;",
  other_h_style = "margin: 10pt 0pt 0pt 0pt;",
  remove_scripts = TRUE,
  force_captions = FALSE,
  css_max_width
)

Arguments

Details

If you want to get equations into Word the currently best way is to use the word_document format.

Value

R Markdown output format to pass to render

Author(s)

Max Gordon

Examples

# Possible yaml configuration at the top of the Rmd doc
## Not run: 
---
title: "Test"
author: "Max Gordon"
output:
  Gmisc::docx_document
---

## End(Not run)

Description

Sets selected boxes to a shared width. This is useful when aligning flowchart levels so corresponding boxes have consistent visual width and center points.

Usage

equalizeWidths(x, subelement = NULL, width = NULL)

Arguments

Value

The updated object with equalized widths.

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), flowchart(), insert(), move(), moveBox(), spread()

Examples

fc <- flowchart(
  groups = list("Group 1", "Group 2"),
  groups2 = list("Analysed", "Analysed")
)

fc |>
  equalizeWidths(subelement = list(c("groups", 1),
                                   c("groups2", 1),
                                   c("groups", 2),
                                   c("groups2", 2)))

# Global fixed width via explicit argument
fc |> equalizeWidths(subelement = "groups", width = grid::unit(30, "mm"))

Description

The do.call can be somewhat slow, especially when working with large objects. This function is based upon the suggestions from Hadley Wickham on the R mailing list. Also thanks to Tommy at StackOverflow for suggesting how to handle double and triple colon operators, ::, further enhancing the function.

Usage

fastDoCall(what, args, quote = FALSE, envir = parent.frame())

Arguments

Note

While the function attempts to do most of what do.call can it has limitations. It can currently not parse the example code from the original function: do.call(paste, list(as.name("A"), as.name("B")), quote = TRUE) and the functionality of quote has not been thoroughly tested.

Examples

fastDoCall("complex", list(imaginary = 1:3))

## if we already have a list (e.g. a data frame)
## we need c() to add further arguments
tmp <- expand.grid(letters[1:2], 1:3, c("+", "-"))
fastDoCall("paste", c(tmp, sep = ""))

## examples of where objects will be found.
A <- 2
f <- function(x) print(x^2)
env <- new.env()
assign("A", 10, envir = env)
assign("f", f, envir = env)
f <- function(x) print(x)
f(A)                                      # 2
fastDoCall("f", list(A))                     # 2
fastDoCall("f", list(A), envir = env)        # 4
fastDoCall(f, list(A), envir = env)          # 2
fastDoCall("f", list(quote(A)), envir = env) # 100
fastDoCall(f, list(quote(A)), envir = env)   # 10
fastDoCall("f", list(as.name("A")), envir = env) # 100

eval(call("f", A))                      # 2
eval(call("f", quote(A)))               # 2
eval(call("f", A), envir = env)         # 4
eval(call("f", quote(A)), envir = env)  # 100

Description

The function relies on options("fig_caption_no") in order to keep track of the last number. If you want to force the caption function to skip captions while still using it in the knitr fig.cap option then simply set options(fig_caption_no = FALSE)

Usage

figCapNo(
  str,
  roman = getOption("fig_caption_no_roman", default = FALSE),
  sprintf_str = getOption("fig_caption_no_sprintf", default = "Fig. %s: %s")
)

Arguments

See Also

Other figure caption functions: figCapNoLast(), figCapNoNext()

Examples

## Not run: 
```{r, fig.cap = pigCapNo("My nice plot")}
plot(1:10 + rnorm(10), 1:10)
```

## End(Not run)
org_opts <- options(fig_caption_no = 2,
                    fig_caption_no_sprintf = "Figure %s: %s")
figCapNo("A plot with caption number = 3")

org_opts <- options(fig_caption_no = TRUE)
figCapNo("A plot with caption number = 1")

# Use default setting
options(fig_caption_no_sprintf = NULL)
figCapNo("A plot with caption number = 2")

# Return the original settings
options(org_opts)

Description

The function relies on options("fig_caption_no") in order to keep track of the last number.

Usage

figCapNoLast(roman = getOption("fig_caption_no_roman", FALSE))

Arguments

See Also

Other figure caption functions: figCapNo(), figCapNoNext()

Examples

org_opts <- options(fig_caption_no = 1)
figCapNoLast()
options(org_opts)

Description

The function relies on options("fig_caption_no") in order to keep track of the last number.

Usage

figCapNoNext(roman = getOption("fig_caption_no_roman", default = FALSE))

Arguments

See Also

Other figure caption functions: figCapNo(), figCapNoLast()

Examples

org_opts <- options(fig_caption_no = 1)
figCapNoNext()
options(org_opts)

Description

This function initializes a flowchart object, which is essentially a list of boxes with the class 'Gmisc_list_of_boxes'. It serves as the starting point for the S3 pipeline, allowing for fluent chaining of ['align'], ['spread'], ['move'], and ['connect'] operations.

Usage

flowchart(..., default_box_fn = boxGrob)

Arguments

Value

A 'list' of class 'Gmisc_list_of_boxes'.

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), insert(), move(), moveBox(), spread()

Examples

library(grid)
grid.newpage()

# Create a flowchart with auto-conversion of text
fc <- flowchart(
  start = "Start",
  process = "Process",
  end = "End"
)

# Use the pipeline
fc |>
  align(axis = "y") |>
  connect("start", "process", type = "vertical") |>
  connect("process", "end", type = "vertical") |>
  print()

Description

Gets the bezier points adjusted for an arrow

Usage

getBezierAdj4Arrw(x, y, arrow_length, length_out = 100)

Arguments

Value

list

Description

A function that returns a description statistic that can be used for creating a publication "table 1" when you want it by groups. The function identifies if the variable is a continuous, binary or a factored variable. The format is inspired by NEJM, Lancet & BMJ.

Usage

getDescriptionStatsBy(
  x,
  ...,
  by,
  digits = 1,
  digits.nonzero = NA,
  html = TRUE,
  numbers_first = TRUE,
  statistics = FALSE,
  statistics.sig_lim = 10^-4,
  statistics.two_dec_lim = 10^-2,
  statistics.suppress_warnings = TRUE,
  useNA = c("ifany", "no", "always"),
  useNA.digits = digits,
  continuous_fn = describeMean,
  prop_fn = describeProp,
  factor_fn = describeFactors,
  show_all_values = FALSE,
  hrzl_prop = FALSE,
  add_total_col,
  total_col_show_perc = TRUE,
  use_units = FALSE,
  units_column_name = "Units",
  default_ref = NULL,
  NEJMstyle = FALSE,
  percentage_sign = TRUE,
  header_count = NULL,
  missing_value = "-",
  names_of_missing = NULL
)

## S3 method for class 'Gmisc_getDescriptionStatsBy'
htmlTable(x, ...)

## S3 method for class 'Gmisc_getDescriptionStatsBy'
print(x, ...)

## S3 method for class 'Gmisc_getDescriptionStatsBy'
knit_print(x, ...)

## S3 method for class 'Gmisc_getDescriptionStatsBy'
length(x)

Arguments

Value

Returns matrix if a single value was provided, otherwise a list of matrices with the class "Gmisc_getDescriptionStatsBy".

Customizing statistics

You can specify what function that you want for statistic by providing a function that takes two arguments x and by and returns a p-value. There are a few functions already prepared for this see getPvalAnova, getPvalChiSq getPvalFisher getPvalKruskal getPvalWilcox. The default functions used are getPvalFisher and getPvalWilcox (unless the by argument has more than three unique levels where it defaults to getPvalAnova).

If you want the function to select functions depending on the type of input you can provide a list with the names 'continuous', 'proportion', 'factor' and the function will choose accordingly. If you fail to define a certain category it will default to the above.

You can also use a custom function that returns a string with the attribute 'colname' set that will be appended to the results instead of the p-value column.

See Also

Other descriptive functions: describeFactors(), describeMean(), describeMedian(), describeProp(), getPvalWilcox()

Examples

library(magrittr)
library(dplyr)
library(htmlTable)

data(mtcars)
mtcars %<>%
  mutate(am = factor(am, levels = 0:1, labels = c("Automatic", "Manual")),
         vs = factor(vs, levels = 0:1, labels = c("V-shaped", "straight")),
         drat_prop = drat > median(drat),
         drat_prop = factor(drat_prop,
                            levels = c(FALSE, TRUE),
                            labels = c("High ratio", "Low ratio")),
         carb_prop = carb > 2,
         carb_prop = factor(carb_prop,
                            levels = c(FALSE, TRUE),
                            labels = c("&le; 2", "&gt; 2")),
         across(c(gear, carb, cyl), factor))

# A simple bare-bone example
mtcars %>%
  getDescriptionStatsBy(`Miles per gallon` = mpg,
                        Weight = wt,
                        `Carborators &le; 2` = carb_prop,
                        by = am) %>%
  htmlTable(caption  = "Basic continuous stats from the mtcars dataset")
invisible(readline(prompt = "Press [enter] to continue"))

# For labeling & units we use set_column_labels/set_column_unit that use
# the Hmisc package annotation functions
mtcars %<>%
  set_column_labels(am = "Transmission",
                    mpg = "Gas",
                    wt = "Weight",
                    gear = "Gears",
                    disp = "Displacement",
                    vs = "Engine type",
                    drat_prop = "Rear axel ratio",
                    carb_prop = "Carburetors") %>%
  set_column_units(mpg = "Miles/(US) gallon",
                   wt = "10<sup>3</sup> lbs",
                   disp = "cu.in.")

mtcars %>%
  getDescriptionStatsBy(mpg,
                        wt,
                        `Gear&dagger;` = gear,
                        drat_prop,
                        carb_prop,
                        vs,
                        by = am,
                        header_count = TRUE,
                        use_units = TRUE,
                        show_all_values = TRUE)  %>%
  addHtmlTableStyle(pos.caption = "bottom") %>%
  htmlTable(caption  = "Stats from the mtcars dataset",
            tfoot = "&dagger; Number of forward gears")
invisible(readline(prompt = "Press [enter] to continue"))

# Using the default parameter we can
mtcars %>%
  getDescriptionStatsBy(mpg,
                        wt,
                        `Gear&dagger;` = gear,
                        drat_prop,
                        carb_prop,
                        vs,
                        by = am,
                        header_count = TRUE,
                        use_units = TRUE,
                        default_ref = c(drat_prop = "Low ratio",
                                        carb_prop = "&gt; 2"))  %>%
  addHtmlTableStyle(pos.caption = "bottom") %>%
  htmlTable(caption  = "Stats from the mtcars dataset",
            tfoot = "&dagger; Number of forward gears")
invisible(readline(prompt = "Press [enter] to continue"))

# We can also use lists
tll <- list()
tll[["Gear (3 to 5)"]] <- getDescriptionStatsBy(mtcars$gear, mtcars$am)
tll <- c(tll,
         list(getDescriptionStatsBy(mtcars$disp, mtcars$am)))

mergeDesc(tll,
          htmlTable_args = list(caption  = "Factored variables")) %>%
  htmlTable::addHtmlTableStyle(css.rgroup = "")
invisible(readline(prompt = "Press [enter] to continue"))

tl_no_units <- list()
tl_no_units[["Gas (mile/gallons)"]] <-
  getDescriptionStatsBy(mtcars$mpg, mtcars$am,
                        header_count = TRUE)
tl_no_units[["Weight (10<sup>3</sup> kg)"]] <-
  getDescriptionStatsBy(mtcars$wt, mtcars$am,
                        header_count = TRUE)
mergeDesc(tl_no_units,
          tll) %>%
  htmlTable::addHtmlTableStyle(css.rgroup = "")
invisible(readline(prompt = "Press [enter] to continue"))

# Other settings
mtcars$mpg[sample(1:NROW(mtcars), size = 5)] <- NA
getDescriptionStatsBy(mtcars$mpg,
                      mtcars$am,
                      statistics = TRUE)
invisible(readline(prompt = "Press [enter] to continue"))

# Do the horizontal version
getDescriptionStatsBy(mtcars$gear,
                      mtcars$am,
                      statistics = TRUE,
                      hrzl_prop = TRUE)
invisible(readline(prompt = "Press [enter] to continue"))

mtcars$wt_with_missing <- mtcars$wt
mtcars$wt_with_missing[sample(1:NROW(mtcars), size = 8)] <- NA
getDescriptionStatsBy(mtcars$wt_with_missing, mtcars$am, statistics = TRUE,
                      hrzl_prop = TRUE, total_col_show_perc = FALSE)
invisible(readline(prompt = "Press [enter] to continue"))

## Not run: 
  ## There is also a LaTeX wrapper
  tll <- list(
    getDescriptionStatsBy(mtcars$gear, mtcars$am),
    getDescriptionStatsBy(mtcars$col, mtcars$am))

  latex(mergeDesc(tll),
        caption  = "Factored variables",
        file = "")

## End(Not run)

P-value extractors for getDescriptionStatsBy

Description

These functions are the base functions for getting the description p-values. You can provide your own functions but all functions should take two arguments and return a p-value (numeric, non-formatted)

Usage

getPvalWilcox(x, by)

getPvalAnova(x, by)

getPvalFisher(x, by)

getPvalChiSq(x, by)

getPvalKruskal(x, by)

Arguments

Value

numeric Returns the p-value from that particular test

getPvalWilcox

Performs a two-sample two-sided Wilcoxon test (also known as the Mann-Whitney test), see wilcox.test.

getPvalAnova

Performs a standard Analysis of Variance model through anova(lm(x ~ by))

getPvalFisher

Performs Fisher's exact test through the fisher.test.

getPvalChiSq

Performs a standard Chi-Squares analysis through chisq.test

getPvalKruskal

Performs a Kruskal-Wallis rank sum test through kruskal.test

See Also

Other descriptive functions: describeFactors(), describeMean(), describeMedian(), describeProp(), getDescriptionStatsBy()

Examples

set.seed(123)
getPvalFisher(
  sample(letters[1:3], size = 100, replace = TRUE),
  sample(LETTERS[1:3], size = 100, replace = TRUE)
)
getPvalWilcox(
  rnorm(100),
  sample(LETTERS[1:2], size = 100, replace = TRUE)
)

Description

This function is inspired by Jeff Leeks Data Analysis course where he suggests that one way to use the svd is to look at the most influential rows for first columns in the V matrix.

Usage

getSvdMostInfluential(
  mtrx,
  quantile,
  similarity_threshold,
  plot_selection = TRUE,
  plot_threshold = 0.05,
  varnames = NULL
)

Arguments

Details

This function expands on that idea and adds the option of choosing more than just the most contributing variable for each row. For instance two variables may have a major impact on a certain component where the second variable has 95 important in that particular component it makes sense to include it in the selection.

It is of course useful when you have many continuous variables and you want to determine a subgroup to look at, i.e. finding the needle in the haystack.

Value

Returns a list with vector with the column numbers that were picked in the "most_influential" variable and the svd caluclation in the "svd"

Examples

org_par <- par(ask = TRUE)
set.seed(1345)
# Simulate data with a pattern
dataMatrix <- matrix(rnorm(15 * 160), ncol = 15)
colnames(dataMatrix) <- c(
    paste("Pos.3:", 1:3, sep = " #"),
    paste("Neg.Decr:", 4:6, sep = " #"),
    paste("No pattern:", 7:8, sep = " #"),
    paste("Pos.Incr:", 9:11, sep = " #"),
    paste("No pattern:", 12:15, sep = " #"))

for (i in 1:nrow(dataMatrix)) {
  # flip a coin
  coinFlip1 <- rbinom(1, size = 1, prob = 0.5)
  coinFlip2 <- rbinom(1, size = 1, prob = 0.5)
  coinFlip3 <- rbinom(1, size = 1, prob = 0.5)

  # if coin is heads add a common pattern to that row
  if (coinFlip1) {
    cols <- grep("Pos.3", colnames(dataMatrix))
    dataMatrix[i, cols] <- dataMatrix[i, cols] + 3
  }

  if (coinFlip2) {
    cols <- grep("Neg.Decr", colnames(dataMatrix))
    dataMatrix[i, cols] <- dataMatrix[i, cols] - seq(from = 5, to = 15, length.out = length(cols))
  }

  if (coinFlip3) {
    cols <- grep("Pos.Incr", colnames(dataMatrix))
    dataMatrix[i, cols] <- dataMatrix[i, cols] + seq(from = 3, to = 15, length.out = length(cols))
  }
}

# Illustrate data
heatmap(dataMatrix, Colv = NA, Rowv = NA, margins = c(7, 2), labRow = "")

svd_out <- svd(scale(dataMatrix))

library(lattice)
b_clr <- c("steelblue", "darkred")
key <- simpleKey(
  rectangles = TRUE, space = "top", points = FALSE,
  text = c("Positive", "Negative")
)
key$rectangles$col <- b_clr

b1 <- barchart(as.table(svd_out$v[, 1]),
               main = "First column",
               horizontal = FALSE, col = ifelse(svd_out$v[, 1] > 0,
                                                b_clr[1], b_clr[2]
               ),
               ylab = "Impact value",
               scales = list(x = list(rot = 55, labels = colnames(dataMatrix), cex = 1.1)),
               key = key
)

b2 <- barchart(as.table(svd_out$v[, 2]),
               main = "Second column",
               horizontal = FALSE, col = ifelse(svd_out$v[, 2] > 0,
                                                b_clr[1], b_clr[2]
               ),
               ylab = "Impact value",
               scales = list(x = list(rot = 55, labels = colnames(dataMatrix), cex = 1.1)),
               key = key
)

b3 <- barchart(as.table(svd_out$v[, 3]),
               main = "Third column",
               horizontal = FALSE, col = ifelse(svd_out$v[, 3] > 0,
                                                b_clr[1], b_clr[2]
               ),
               ylab = "Impact value",
               scales = list(x = list(rot = 55, labels = colnames(dataMatrix), cex = 1.1)),
               key = key
)

b4 <- barchart(as.table(svd_out$v[, 4]),
               main = "Fourth column",
               horizontal = FALSE, col = ifelse(svd_out$v[, 4] > 0,
                                                b_clr[1], b_clr[2]
               ),
               ylab = "Impact value",
               scales = list(x = list(rot = 55, labels = colnames(dataMatrix), cex = 1.1)),
               key = key
)

# Note that the fourth has the no pattern columns as the
# chosen pattern, probably partly because of the previous
# patterns already had been identified
print(b1, position = c(0, 0.5, .5, 1), more = TRUE)
print(b2, position = c(0.5, 0.5, 1, 1), more = TRUE)
print(b3, position = c(0, 0, .5, .5), more = TRUE)
print(b4, position = c(0.5, 0, 1, .5))

# Let's look at how well the SVD identifies
# the most influential columns
getSvdMostInfluential(dataMatrix,
                      quantile = .8,
                      similarity_threshold = .9,
                      plot_threshold = .05,
                      plot_selection = TRUE)
par(org_par)

Description

This is a general form of bezier line that can be used for cubic, quadratic, and more advanced Bézier lines.

Usage

gnrlBezierPoints(ctrl_points, length_out = 100L)

Arguments

Examples

library(grid)
grid.newpage()
l <- gnrlBezierPoints(data.frame(x = c(.1, -.1, .7, 1, 1, 0.1),
                                 y = c(.9, 0, 1, .8, .4, .1)),
                      length_out = 100)
grid.lines(l[,1], l[,2], gp=gpar(col="#550000", lwd = 4))

out_sizes <- 4:20
clrs <- colorRampPalette(c("orange", "darkblue"))(length(out_sizes))
for (i in out_sizes){
   l <- gnrlBezierPoints(data.frame(x = c(.1, -.1, .7, 1, 1, 0.1),
                                    y = c(.9, 0, 1, .8, .4, .1)),
                         length_out = i)
   grid.lines(l[,1], l[,2],
   gp=gpar(col=clrs[which(i == out_sizes)]))
}

Description

This is a handy function for checking if item exist in a nested structure

Usage

has(sourceList, path)

Arguments

Value

Returns a boolean.

See Also

Other lodash similar functions: retrieve()

Examples

has(list(a = list(b = 1)), "a.b")

Description

Inserts a box into a list of boxes and positions it relative to the surrounding boxes.

Usage

insert(x, element, ..., after = NULL, before = NULL)

## Default S3 method:
insert(x, element, ..., after = NULL, before = NULL)

## S3 method for class 'Gmisc_list_of_boxes'
insert(x, element, ..., after = NULL, before = NULL)

Arguments

Value

The updated list of boxes with the new element inserted.

See Also

Other flowchart components: align(), append(), boxGrob(), boxHeaderGrob(), boxPropGrob(), boxShapes, connectGrob(), coords(), distance(), equalizeWidths(), flowchart(), move(), moveBox(), spread()

Description

Inserts a row and keeps the attributes copyAllNewAttributes

Usage

insertRowAndKeepAttr(m, r, v = NA, rName = "")

Arguments

Value

matrix Returns a matrix with one more row than the provided matrix m

Author(s)

Max Gordon, Arne Henningsen

Examples

test <- matrix(1:4, ncol = 2)
attr(test, "wow") <- 1000
test <- insertRowAndKeepAttr(test, 2)
print(attr(test, "wow"))

Description

Place text labels at the midpoint of connector grobs returned by ‘connectGrob()' (useful for multi-target connectors where 'label=' isn’t available). By default the function draws the labels; set 'draw = FALSE' to only return the 'textGrob' objects for programmatic use.

Usage

labelConnector(
  con,
  labels,
  x_offset = unit(0, "mm"),
  y_offset = unit(0, "mm"),
  gp = gpar(cex = 0.9),
  bg_gp = gpar(fill = "white", col = NA),
  pad = unit(2, "mm")
)

Arguments

Value

A 'Gmisc_connector_label' S3 object (invisible). Use 'print()' to draw the labels.

Examples

# Attach labels to a previously-created connector and draw them
a <- boxDiamondGrob("D")
b <- boxEllipseGrob("L")
c <- boxServerGrob("S")
boxes <- list(decision = a, outcomes = list(b, c)) |>
  spreadHorizontal(
    from = grid::unit(.1, "npc"),
    to = grid::unit(.9, "npc"),
    subelement = "outcomes"
  ) |>
  spreadVertical()

connectGrob(boxes$decision, boxes$outcomes, type = "N") |>
  labelConnector(c("Local", "Server"))

Description

By putting all the output from the getDescriptionStatsBy into a list, naming each element that we want in an rgroup we can automatically merge everything and create an object ready for the htmlTable.

Usage

mergeDesc(..., htmlTable_args = list())

Arguments

Value

matrix Returns a matrix object of class descList

The rgroup value

The value for the rgroup is by default the name of the list element. If you have passed a list without a name for that particular element or if you have passed a matrix it will look for a label set by the Hmisc::label function. For those elements that have only one row no rgroup is set, and the naming sequence is the same as above but with an additional rownames if the previous two turn out empty. All this behavior is exemplified in the example.

The rgroup value can be overridden by simply specifying a custom rgroup when calling the htmlTable function.

The colnames of the matrix

The function chooses the colnames from the first element in the tlist.

Examples

library(magrittr)
library(dplyr)
library(htmlTable)

data(mtcars)
mtcars %<>%
  mutate(am = factor(am, levels = 0:1, labels = c("Automatic", "Manual")),
         vs = factor(vs, levels = 0:1, labels = c("V-shaped", "straight")),
         drat_prop = drat > median(drat),
         drat_prop = factor(drat_prop,
                            levels = c(FALSE, TRUE),
                            labels = c("High ratio", "Low ratio")),
         carb_prop = carb > 2,
         carb_prop = factor(carb_prop,
                            levels = c(FALSE, TRUE),
                            labels = c("&le; 2", "&gt; 2")),
         across(c(gear, carb, cyl), factor))

# A simple bare-bone example
mtcars %>%
  getDescriptionStatsBy(`Miles per gallon` = mpg,
                        Weight = wt,
                        `Carborators &le; 2` = carb_prop,
                        by = am) %>%
  htmlTable(caption  = "Basic continuous stats from the mtcars dataset")
invisible(readline(prompt = "Press [enter] to continue"))

# For labeling & units we use set_column_labels/set_column_unit that use
# the Hmisc package annotation functions
mtcars %<>%
  set_column_labels(am = "Transmission",
                    mpg = "Gas",
                    wt = "Weight",
                    gear = "Gears",
                    disp = "Displacement",
                    vs = "Engine type",
                    drat_prop = "Rear axel ratio",
                    carb_prop = "Carburetors") %>%
  set_column_units(mpg = "Miles/(US) gallon",
                   wt = "10<sup>3</sup> lbs",
                   disp = "cu.in.")

mtcars %>%
  getDescriptionStatsBy(mpg,
                        wt,
                        `Gear&dagger;` = gear,
                        drat_prop,
                        carb_prop,
                        vs,
                        by = am,
                        header_count = TRUE,
                        use_units = TRUE,
                        show_all_values = TRUE)  %>%
  addHtmlTableStyle(pos.caption = "bottom") %>%
  htmlTable(caption  = "Stats from the mtcars dataset",
            tfoot = "&dagger; Number of forward gears")
invisible(readline(prompt = "Press [enter] to continue"))

# Using the default parameter we can
mtcars %>%
  getDescriptionStatsBy(mpg,
                        wt,
                        `Gear&dagger;` = gear,
                        drat_prop,
                        carb_prop,
                        vs,
                        by = am,
                        header_count = TRUE,
                        use_units = TRUE,
                        default_ref = c(drat_prop = "Low ratio",
                                        carb_prop = "&gt; 2"))  %>%
  addHtmlTableStyle(pos.caption = "bottom") %>%
  htmlTable(caption  = "Stats from the mtcars dataset",
            tfoot = "&dagger; Number of forward gears")
invisible(readline(prompt = "Press [enter] to continue"))

# We can also use lists
tll <- list()
tll[["Gear (3 to 5)"]] <- getDescriptionStatsBy(mtcars$gear, mtcars$am)
tll <- c(tll,
         list(getDescriptionStatsBy(mtcars$disp, mtcars$am)))

mergeDesc(tll,
          htmlTable_args = list(caption  = "Factored variables")) %>%
  htmlTable::addHtmlTableStyle(css.rgroup = "")
invisible(readline(prompt = "Press [enter] to continue"))

tl_no_units <- list()
tl_no_units[["Gas (mile/gallons)"]] <-
  getDescriptionStatsBy(mtcars$mpg, mtcars$am,
                        header_count = TRUE)
tl_no_units[["Weight (10<sup>3</sup> kg)"]] <-
  getDescriptionStatsBy(mtcars$wt, mtcars$am,
                        header_count = TRUE)
mergeDesc(tl_no_units,
          tll) %>%
  htmlTable::addHtmlTableStyle(css.rgroup = "")
invisible(readline(prompt = "Press [enter] to continue"))

# Other settings
mtcars$mpg[sample(1:NROW(mtcars), size = 5)] <- NA
getDescriptionStatsBy(mtcars$mpg,
                      mtcars$am,
                      statistics = TRUE)
invisible(readline(prompt = "Press [enter] to continue"))

# Do the horizontal version
getDescriptionStatsBy(mtcars$gear,
                      mtcars$am,
                      statistics = TRUE,
                      hrzl_prop = TRUE)
invisible(readline(prompt = "Press [enter] to continue"))

mtcars$wt_with_missing <- mtcars$wt
mtcars$wt_with_missing[sample(1:NROW(mtcars), size = 8)] <- NA
getDescriptionStatsBy(mtcars$wt_with_missing, mtcars$am, statistics = TRUE,
                      hrzl_prop = TRUE, total_col_show_perc = FALSE)
invisible(readline(prompt = "Press [enter] to continue"))

## Not run: 
  ## There is also a LaTeX wrapper
  tll <- list(
    getDescriptionStatsBy(mtcars$gear, mtcars$am),
    getDescriptionStatsBy(mtcars$col, mtcars$am))

  latex(mergeDesc(tll),
        caption  = "Factored variables",
        file = "")

## End(Not run)

Description

The merge allows for a recursive component where the lists are compared on the subelement. If one does not contain that element it will get NA in for those parameters.

Usage

mergeLists(
  ...,
  lapplyOutput = NULL,
  sortNames = getOption("Gmisc.mergeList.sort", default = TRUE)
)

Arguments

Value

Returns a list with all the given lists.

Examples

v1 <- list("a" = c(1, 2), b = "test 1", sublist = list(one = 20:21, two = 21:22))
v2 <- list("a" = c(3, 4), b = "test 2", sublist = list(one = 10:11, two = 11:12, three = 1:2))
mergeLists(v1, v2)