Package 'WeightedTreemaps' reference manual

Title:	Generate and Plot Voronoi or Sunburst Treemaps from Hierarchical Data
Description:	Treemaps are a visually appealing graphical representation of numerical data using a space-filling approach. A plane or 'map' is subdivided into smaller areas called cells. The cells in the map are scaled according to an underlying metric which allows to grasp the hierarchical organization and relative importance of many objects at once. This package contains two different implementations of treemaps, Voronoi treemaps and Sunburst treemaps. The Voronoi treemap function subdivides the plot area in polygonal cells according to the highest hierarchical level, then continues to subdivide those parental cells on the next lower hierarchical level, and so on. The Sunburst treemap is a computationally less demanding treemap that does not require iterative refinement, but simply generates circle sectors that are sized according to predefined weights. The Voronoi tesselation is based on functions from Paul Murrell (2012) <https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoiTreeMap.html>.
Authors:	Michael Jahn [aut, cre] , David Leslie [aut], Ahmadou Dicko [aut] , Paul Murrell [aut, cph]
Maintainer:	Michael Jahn <[email protected]>
License:	GPL-3
Version:	0.1.3
Built:	2024-11-05 06:46:46 UTC
Source:	CRAN

cropped_voronoi

Description

Tesselates a plane using a set of XY coordinates

Usage

cropped_voronoi(sites)
cropped_voronoi(sites)

Arguments

sites

(numeric matrix) The only input parameter for the function. A matrix with 3 columns: X and Y coordinates, as well as weights that are used for tesselation.

Details

The function is only intended for internal use. However, one can also use it directly for test purposes.

Value

A list of cell coordinates; one cell for each set of input coordinates.

Draws the treemap object that was obtained by running voronoiTreemap or sunburstTreemap. Many graphical parameters can be customized but some settings that determine the appearance of treemaps are already made during treemap generation. Such parameters are primarily cell size and initial shape of the treemap.

Usage

drawTreemap(
  treemap,
  levels = 1:length(treemap@call$levels),
  color_type = "categorical",
  color_level = NULL,
  color_palette = NULL,
  border_level = levels,
  border_size = 6,
  border_color = grey(0.9),
  label_level = max(levels),
  label_size = 1,
  label_color = grey(0.9),
  title = NULL,
  title_size = 1,
  title_color = grey(0.5),
  legend = FALSE,
  legend_position = "left",
  legend_size = 0.1,
  custom_range = NULL,
  width = 0.9,
  height = 0.9,
  layout = c(1, 1),
  position = c(1, 1),
  add = FALSE
)
drawTreemap(
  treemap,
  levels = 1:length(treemap@call$levels),
  color_type = "categorical",
  color_level = NULL,
  color_palette = NULL,
  border_level = levels,
  border_size = 6,
  border_color = grey(0.9),
  label_level = max(levels),
  label_size = 1,
  label_color = grey(0.9),
  title = NULL,
  title_size = 1,
  title_color = grey(0.5),
  legend = FALSE,
  legend_position = "left",
  legend_size = 0.1,
  custom_range = NULL,
  width = 0.9,
  height = 0.9,
  layout = c(1, 1),
  position = c(1, 1),
  add = FALSE
)

Arguments

`treemap`	(treemapResult) Either a `voronoiResult` or `sunburstResult` object that contains polygons and metadata as output from running `voronoiTreemap` or `sunburstTreemap`.
`levels`	(numeric) A numeric vector representing the hierarchical levels that are drawn. The default is to draw all levels.
`color_type`	(character) One of "categorical", "cell_size", "both", or "custom_color". For "categorical", each cell is colored based on the (parent) category it belongs. Colors may repeat if there are many cells. For "cell_size", cells are colored according to their relative area. For "both", cells are be colored the same way as for "categorical", but lightness is adjusted according to cell area. For "custom_color", a color index is used that was specified by `custom_color` during treemap generation. Use `NULL` to omit drawing colors.
`color_level`	(numeric) A numeric vector representing the hierarchical level that should be used for cell coloring. Must be one of `levels`. Default is to use the lowest level cells for Voronoi treemaps and all levels for sunburst treemaps.
`color_palette`	(character) A character vector of colors used to fill cells. The default is to use `rainbow_hcl` from
`border_level`	(numeric) A numeric vector representing the hierarchical level that should be used for drawing cell borders, or NULL to omit drawing borders, The default is that all borders are drawn.
`border_size`	(numeric) A single number indicating initial line width of the highest level cells. Is reduced each level, default is 6 pts. Alternatively a vector of `length(border_level)`, then each border is drawn with the specified width.
`border_color`	(character) A single character indicating color for cell borders, default is a light grey. Alternatively a vector of `length(border_level)`, then each border is drawn with the specified color.
`label_level`	(numeric) A numeric vector representing the hierarchical level that should be used for drawing cell labels, or NULL to omit drawing labels. The default is the deepest level (every cell has a label).
`label_size`	(numeric) A single number indicating relative size of each label in relation to its parent cell. Alternatively a numeric vector of `length(label_level)` that specifies relative size of labels for each level individually.
`label_color`	(character) A single character indicating color for cell labels. Alternatively a vector of `length(label_level)`, then each label is drawn with the specified color.
`title`	(character) An optional title, default to `NULL`.
`title_size`	(numeric) The size (or 'character expansion') of the title.
`title_color`	(character) Color for title.
`legend`	(logical) Set to TRUE if a color key should be drawn. Default is FALSE.
`legend_position`	(character) The position of the legend, one of "left" (default), "right", "top", or "bottom".
`legend_size`	(numeric) The relative size of the legend (0 to 1), default is 0.1.
`custom_range`	(numeric) A numeric vector of length 2 that can be used to rescale the values in `custom_color` to the range of choice. The default is `NULL` and it only has an effect if `custom_color` was specified when generating the treemap.
`width`	(numeric) The width (0 to 0.9) of the viewport that the treemap will occupy.
`height`	(numeric) The height (0 to 0.9) of the viewport that the treemap will occupy.
`layout`	(numeric) Vector of length 2 indicating the number of rows and columns that the plotting area is supposed to be subdivided in. Useful only together with `position`, which indicates the position of the specific treemap. Use `add = TRUE` to omit starting a new page every time you call `drawTreemap()`.
`position`	(numeric) Vector of length 2 indicating the position where the current treemap should be drawn. Useful only together with `layout`, which indicates the number of rows and columns the plotting area is subdivided into. Use `add = TRUE` to omit starting a new page every time you call `drawTreemap()`.
`add`	(logical) Defaults to `FALSE`, creating a new page when drawing a treemap. When multiple treemaps should be plotted on the same page, this should be set to TRUE, and position of treemaps specified by `layout` and `position` arguments.

Value

The function does not return a value (except NULL). It creates a grid viewport and draws the treemap.

Examples

# load package
library(WeightedTreemaps)

# generate dummy data
df <- data.frame(
  A = rep(c("abcd", "efgh"), each = 4),
  B = letters[1:8],
  size = c(37, 52, 58, 27, 49, 44, 34, 45)
)

# compute treemap
tm <- voronoiTreemap(
  data = df,
  levels = c("B"),
  cell_size = "size",
  shape = "circle",
  positioning = "regular",
  seed = 123
)

# plot treemap with each cell colored by name (default)
drawTreemap(tm, label_size = 1, color_type = "categorical")

# plot treemap with each cell colored by name, but larger cells
# lighter and smaller cells darker
drawTreemap(tm, label_size = 1, color_type = "both")

# plot treemap with different color palette and style
drawTreemap(tm, label_size = 1, label_color = grey(0.3),
            border_color = grey(0.3), color_palette = heat.colors(6)
)

# ---------------------------------------------

# load example data
data(mtcars)
mtcars$car_name = gsub(" ", "\n", row.names(mtcars))

# generate sunburst treemap
tm <- sunburstTreemap(
  data = mtcars,
  levels = c("gear", "cyl"),
  cell_size = "hp"
)

# draw treemap
drawTreemap(tm,
  title = "A sunburst treemap",
  legend = TRUE,
  border_size = 2,
  label_color = grey(0.6)
)

# load package
library(WeightedTreemaps)

# generate dummy data
df <- data.frame(
  A = rep(c("abcd", "efgh"), each = 4),
  B = letters[1:8],
  size = c(37, 52, 58, 27, 49, 44, 34, 45)
)

# compute treemap
tm <- voronoiTreemap(
  data = df,
  levels = c("B"),
  cell_size = "size",
  shape = "circle",
  positioning = "regular",
  seed = 123
)

# plot treemap with each cell colored by name (default)
drawTreemap(tm, label_size = 1, color_type = "categorical")

# plot treemap with each cell colored by name, but larger cells
# lighter and smaller cells darker
drawTreemap(tm, label_size = 1, color_type = "both")

# plot treemap with different color palette and style
drawTreemap(tm, label_size = 1, label_color = grey(0.3),
            border_color = grey(0.3), color_palette = heat.colors(6)
)

# ---------------------------------------------

# load example data
data(mtcars)
mtcars$car_name = gsub(" ", "\n", row.names(mtcars))

# generate sunburst treemap
tm <- sunburstTreemap(
  data = mtcars,
  levels = c("gear", "cyl"),
  cell_size = "hp"
)

# draw treemap
drawTreemap(tm,
  title = "A sunburst treemap",
  legend = TRUE,
  border_size = 2,
  label_color = grey(0.6)
)

get_polygons

Description

Extract the list of polygons from a voronoiResult object.

Usage

get_polygons(x, ...)
get_polygons(x, ...)

Arguments

`x`	(voronoiResult) A voronoi treemap results object
`...`	(none) Not used

Value

List of polygons, as class POLYGON from sf

Data from the publication of Jahn et al., CellReports, 2018

Description

The dataset contains protein abundances of the Synechocystis sp. PCC6803 proteome. Protein abundance was determined using shotgun mass spectrometry. The data set also contains pathway information according to the cyanobase hierarchical annotation:

Usage

data(Jahn_CellReports_2018)
data(Jahn_CellReports_2018)

Format

A data frame with 19790 rows and 12 variables

Details

protein - protein ID
condition - combination from light and CO2
light - light intensity in umol photons / m2 * s
co2_concentration - CO2 concentration in
mean_intensity - mean MS1 ion intensity
mean_mass_fraction_norm - normalized mean mass fraction of protein
sd_intensity - standard deviation from mean
Process - functional annotation 1st level
Pathway - functional annotation 2nd level
Protein - functional annotation 3rd level
Process.abbr - abbreviated Process
Pathway.abbr - abbreviated Pathway
Gene.names - trivial names of genes, if available

Source

https://pubmed.ncbi.nlm.nih.gov/30304686/

poly_area

Description

Mainly for internal use. Determines the area of a polygon based on its x and y coordinates. This function is a reimplementation of 'soiltexture::TT.polygon.area()' and only re-implemented to avoid extra dependencies.

Usage

poly_area(poly_x, poly_y)
poly_area(poly_x, poly_y)

Arguments

`poly_x`	(numeric) X coordinates of each vertices of the polygon
`poly_y`	(numeric) Y coordinates of each vertices of the polygon

Value

A numeric, the area of the polygon.

poly_centroid

Description

Mainly for internal use. Determines the centroids of a polygon based on its x and y coordinates. This function is a reimplementation of 'soiltexture::TT.polygon.centroids()' and only re-implemented to avoid extra dependencies.

Usage

poly_centroid(poly_x, poly_y)
poly_centroid(poly_x, poly_y)

Arguments

`poly_x`	(numeric) X coordinates of each vertices of the polygon
`poly_y`	(numeric) Y coordinates of each vertices of the polygon

Value

A numeric, the area of the polygon.

poly_transform_shape

Description

Mainly for internal use. The function transforms ('projects') arbitrary input coordinates that are used as parent polygon or shape of the treemap. By default it scales and centers polygon coordinates on a square of 0 to 2000 units.

Usage

poly_transform_shape(poly, xy_max = 2000)
poly_transform_shape(poly, xy_max = 2000)

Arguments

`poly`	(list) named list of 'x' and 'y' coordinates of the polygon
`xy_max`	(numeric) maximum desired expansion of the polygon (default: 2000)

Value

A list with slots 'x' and 'y' containing numeric coordinates

print.sunburstResult

Description

Print method for sunburstResult

Usage

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

Arguments

`x`	(sunburstResult) A sunburst treemap results object
`...`	(none) Not used

Value

Returns a data.frame

print.voronoiResult

Description

Print method for voronoiResult

Usage

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

Arguments

`x`	(voronoiResult) A voronoi treemap results object
`...`	(none) Not used

Value

Returns a data.frame

Coordinates to draw a rounded rectangle as parent cell for treemaps

Description

Set of coordinates for a rounded rectangle as parent cell for treemaps

Usage

data(rounded_rect)
data(rounded_rect)

Format

A data frame with 50 rows and 2 variables

Details

X - coordinate
Y - coordinate

summary.sunburstResult

Description

Summary method for sunburstResult

Usage

## S3 method for class 'sunburstResult'
summary(object, ...)
## S3 method for class 'sunburstResult'
summary(object, ...)

Arguments

`object`	(sunburstResult) A sunburst treemap results object
`...`	(none) Not used

Value

Returns a data.frame

summary.voronoiResult

Description

Summary method for voronoiResult.

Usage

## S3 method for class 'voronoiResult'
summary(object, ...)
## S3 method for class 'voronoiResult'
summary(object, ...)

Arguments

`object`	(voronoiResult) A voronoi treemap results object
`...`	(none) Not used

Value

Returns a data.frame

sunburstTreemap

Description

Create sunburst treemaps where variables are encoded by size of circular sectors.

Usage

sunburstTreemap(
  data,
  levels,
  fun = sum,
  sort = TRUE,
  filter = 0,
  cell_size = NULL,
  custom_color = NULL,
  diameter_inner = 0.3,
  diameter_outer = 0.8,
  verbose = FALSE
)
sunburstTreemap(
  data,
  levels,
  fun = sum,
  sort = TRUE,
  filter = 0,
  cell_size = NULL,
  custom_color = NULL,
  diameter_inner = 0.3,
  diameter_outer = 0.8,
  verbose = FALSE
)

Arguments

`data`	(data.frame) A data.frame with one column for each hierarchical level
`levels`	(character) Character vector indicating the column names to be used. The order of names must correspond to the hierarchical levels, going from broad to fine
`fun`	(function) Function to be used to aggregate cell sizes of parental cells
`sort`	(logical) Should the columns of the data.frame be sorted before?
`filter`	(logical) Filter the supplied data frame to remove very small sectors that may not be visible. The default is to not remove any sectors.
`cell_size`	(character) The name of the column used to control sector size. Can be one of `levels` or any other column with numerical data. NA or values equal or less than zero are not allowed. The values in this column are aggregated by the function specified by `fun`. If `sector_size = NULL`, sector size is simply computed by the number of members for the respective sector (corresponding to rows in the data.frame).
`custom_color`	(character) An optional column that can be specified to control cell color. Cell colors are determined when drawing the treemap using `drawTreemap`, but the default is to use one of `levels` or `cell size`. Any other data source that shall be used instead has to be included in the treemap generation and explicitly specified here. The default value is `NULL`.
`diameter_inner`	(numeric) The minimum inner diameter of the drawn map. Defaults to 0.3,
`diameter_outer`	(numeric) The maximum outer diameter of the drawn map. Defaults to 0.8
`verbose`	(logical) If verbose is TRUE (default is FALSE), basic information such as a success message is printed to the console.

Details

This function returns a treemap object instead of a plot. In order to actually draw the treemap, use drawTreemap.

Value

'sunburstTreemap' returns an object of the formal class 'sunburstResult'. It is essentially a list of objects related to the graphical representation of the treemap (polygons, labels, cell data) as well as data from the call of the function. It contains the following slots:

`cells`	'list' of polygons for drawing a treemap
`data`	'data.frame', the original data that was supplied to calling 'voronoiTreemap'
`call`	'list' of arguments used to call 'voronoiTreemap'

Examples

# load example data
data(mtcars)
mtcars$car_name = gsub(" ", "\n", row.names(mtcars))

# generate treemap;
# by default cell (sector) size is encoded by number of members per group
tm <- sunburstTreemap(
  data = mtcars,
  levels = c("gear", "cyl"),
  cell_size = "hp"
)

# draw treemap with default options
drawTreemap(tm,
  title = "A sunburst treemap",
  legend = TRUE,
  border_size = 2,
  layout = c(1, 3),
  position = c(1, 1)
)

# use custom color palette
drawTreemap(tm,
  title = "Use custom palette",
  legend = TRUE,
  color_palette = rep(c("#81E06E", "#E68CFF", "#76BBF7"), c(3, 4, 5)),
  border_size = 2,
  label_level = 2,
  label_size = 0.7,
  label_color = grey(0.5),
  layout = c(1, 3),
  position = c(1, 2),
  add = TRUE
)

# color cells (sectors) based on cell size
drawTreemap(tm,
  title = "Coloring encoded by cell size",
  color_type = "cell_size",
  legend = TRUE,
  color_palette = rev(heat.colors(10)),
  border_size = 3,
  border_color = grey(0.3),
  label_level = 1,
  label_size = 2,
  label_color = grey(0.5),
  layout = c(1, 3),
  position = c(1, 3),
  add = TRUE
)

# load example data
data(mtcars)
mtcars$car_name = gsub(" ", "\n", row.names(mtcars))

# generate treemap;
# by default cell (sector) size is encoded by number of members per group
tm <- sunburstTreemap(
  data = mtcars,
  levels = c("gear", "cyl"),
  cell_size = "hp"
)

# draw treemap with default options
drawTreemap(tm,
  title = "A sunburst treemap",
  legend = TRUE,
  border_size = 2,
  layout = c(1, 3),
  position = c(1, 1)
)

# use custom color palette
drawTreemap(tm,
  title = "Use custom palette",
  legend = TRUE,
  color_palette = rep(c("#81E06E", "#E68CFF", "#76BBF7"), c(3, 4, 5)),
  border_size = 2,
  label_level = 2,
  label_size = 0.7,
  label_color = grey(0.5),
  layout = c(1, 3),
  position = c(1, 2),
  add = TRUE
)

# color cells (sectors) based on cell size
drawTreemap(tm,
  title = "Coloring encoded by cell size",
  color_type = "cell_size",
  legend = TRUE,
  color_palette = rev(heat.colors(10)),
  border_size = 3,
  border_color = grey(0.3),
  label_level = 1,
  label_size = 2,
  label_color = grey(0.5),
  layout = c(1, 3),
  position = c(1, 3),
  add = TRUE
)

voronoiTreemap

Description

Create nested additively weighted Voronoi treemaps.

Usage

voronoiTreemap(
  data,
  levels,
  fun = sum,
  sort = TRUE,
  filter = 0,
  cell_size = NULL,
  custom_color = NULL,
  shape = "rectangle",
  maxIteration = 100,
  error_tol = 0.01,
  convergence = "intermediate",
  seed = NULL,
  positioning = "regular",
  verbose = FALSE,
  debug = FALSE
)
voronoiTreemap(
  data,
  levels,
  fun = sum,
  sort = TRUE,
  filter = 0,
  cell_size = NULL,
  custom_color = NULL,
  shape = "rectangle",
  maxIteration = 100,
  error_tol = 0.01,
  convergence = "intermediate",
  seed = NULL,
  positioning = "regular",
  verbose = FALSE,
  debug = FALSE
)

Arguments

`data`	(data.frame) A data.frame with one column for each hierarchical level
`levels`	(character) Character vector indicating the column names to be used. The order of names must correspond to the hierarchical levels, going from broad to fine
`fun`	(function) Function to be used to aggregate cell sizes of parental cells
`sort`	(logical) Should the columns of the data.frame be sorted before treemap generation?
`filter`	(numeric) Filter the supplied data frame to remove very small cells that may not be visible. The default is to remove cells with a relative target area below a threshold of zero (no negative values allowed). Computation time can increase when many small cells are present. For example, a threshold of 0.01 filters out all observations/cells below 1 % of the total area.
`cell_size`	(character) The name of the column used to control cell size. Can be one of `levels` or any other column with numerical data. NA or values equal or less than zero are not allowed as the cell area needs to be positive. The values in this column are aggregated by the function specified by `fun`. If `cell_size = NULL`, cell area is simply computed by the number of members for the respective cell (corresponding to rows in the data.frame).
`custom_color`	(character) An optional column that can be specified to control cell color. Cell colors are determined when drawing the treemap using `drawTreemap`, but the default is to use one of `levels` or `cell size`. Any other data source that shall be used instead has to be included in the treemap generation and explicitly specified here. The default value is `NULL`.
`shape`	(list or character) Set the initial shape of the treemap. Currently supported are the keywords "rectangle", "rounded_rect", "circle" or "hexagon". Alternatively the user can supply a named list with coordinates for a custom polygon. The slots of the list must be labeled 'x' and 'y'. The coordinates are not tested for validity, use on your own risk.
`maxIteration`	(numeric) Force algorithm to stop at this number of iterations for each parent cell. The algorithm usually converges to an acceptable solution fairly quickly, so it seems reasonable to restrict this number in order to save computation time. However, more iterations give higher accuracy.
`error_tol`	(numeric) The allowed maximum error tolerance of a cell. The algorithm will stop when all cells have lower error than this value. It is calculated as the absolute difference of a cell's area to its target area. The default is 0.01 (or 1 %) of the total parental area. Note: this is is different from a relative per-cell error, where 1 % would be more strict.
`convergence`	(character) One of "slow", "intermediate", or "fast". Intermediate (default) and fast try to adjust cell weights stronger such that the algorithm converges faster towards the final size of the cell. However this comes at the price of stability, with a larger number of polygons possibly being misformed, e.g. by having self-intersections. Set convergence to "slow" if you experience problems to calculate treemaps with very unequal cell sizes or very large treemaps.
`seed`	(integer) The default seed is NULL, which will lead to a new random sampling of cell coordinates for each tesselation. If you want a reproducible arrangement of cells, set seed to an arbitrary number.
`positioning`	(character) Algorithm for positioning of starting coordinates of child cells in the parental cell using `spsample()`; "random" for completely random positions, "regular" for cells aligned to a grid sorted from bottom to top by name, "clustered" with regular positions of cells but sorted by name from inside out. Two variants "regular_by_area" and "clustered_by_area" will work as their counterparts but will sort by cell target area instead of cell name. `positioning` can be a single character or a vector of `length(levels)` to allow different positioning algorithms for each level.
`verbose`	(logical) If verbose is TRUE (default is FALSE), messages with statistics for each iteration of a treemap as well as a success message are printed to the console.
`debug`	(logical) If debug is TRUE (default is FALSE), the solution for each iteration is drawn to the viewport to allow some visual inspection. The weights, target area, and difference are printed to the console. It is not recommended to set this option to TRUE unless you know what you are doing, as it makes treemap generation much slower.

Details

This is a recursive wrapper function, making use of the original implementation of the voronoi tesselation from Paul Murrell, University of Auckland. The original functions were obtained and slightly modified from https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoiTreeMap.html This function returns a treemap object instead of a plot. In order to actually draw the treemap, use drawTreemap.

Value

'voronoiTreemap' returns an object of the formal class 'voronoiResult'. It is essentially a list of objects related to the graphical representation of the treemap (polygons, labels, cell data) as well as data from the call of the function. It contains the following slots:

`cells`	'list' of polygons for drawing a treemap
`data`	'data.frame', the original data that was supplied to calling 'voronoiTreemap'
`call`	'list' of arguments used to call 'voronoiTreemap'

Examples

# load package
library(WeightedTreemaps)

# generate dummy data
df <- data.frame(
  A = rep(c("abcd", "efgh"), each = 4),
  B = letters[1:8],
  size = c(37, 52, 58, 27, 49, 44, 34, 45)
)

# compute treemap
tm <- voronoiTreemap(
  data = df,
  levels = c("B"),
  cell_size = "size",
  shape = "circle",
  positioning = "regular",
  seed = 123
)

# plot treemap with each cell colored by name (default)
drawTreemap(tm, label_size = 1, color_type = "categorical")

# plot treemap with each cell colored by name, but larger cells
# lighter and smaller cells darker
drawTreemap(tm, label_size = 1, color_type = "both")

# plot treemap with different color palette and style
drawTreemap(tm, label_size = 1, label_color = grey(0.3),
            border_color = grey(0.3), color_palette = heat.colors(6)
)

# load package
library(WeightedTreemaps)

# generate dummy data
df <- data.frame(
  A = rep(c("abcd", "efgh"), each = 4),
  B = letters[1:8],
  size = c(37, 52, 58, 27, 49, 44, 34, 45)
)

# compute treemap
tm <- voronoiTreemap(
  data = df,
  levels = c("B"),
  cell_size = "size",
  shape = "circle",
  positioning = "regular",
  seed = 123
)

# plot treemap with each cell colored by name (default)
drawTreemap(tm, label_size = 1, color_type = "categorical")

# plot treemap with each cell colored by name, but larger cells
# lighter and smaller cells darker
drawTreemap(tm, label_size = 1, color_type = "both")

# plot treemap with different color palette and style
drawTreemap(tm, label_size = 1, label_color = grey(0.3),
            border_color = grey(0.3), color_palette = heat.colors(6)
)

Package 'WeightedTreemaps'

Help Index

as.data.frame.sunburstResult

Description

Usage

Arguments

Value

See Also

as.data.frame.voronoiResult

Description

Usage

Arguments

Value

See Also

cropped_voronoi

Description

Usage

Arguments

Details

Value

drawTreemap

Description

Usage

Arguments

Value

See Also

Examples

get_polygons

Description

Usage

Arguments

Value

See Also

Data from the publication of Jahn et al., CellReports, 2018

Description

Usage

Format

Details

Source

poly_area

Description

Usage

Arguments

Value

See Also

poly_centroid

Description

Usage

Arguments

Value

See Also

poly_transform_shape

Description

Usage

Arguments

Value

print.sunburstResult

Description

Usage

Arguments

Value

See Also

print.voronoiResult

Description

Usage

Arguments

Value

See Also

Coordinates to draw a rounded rectangle as parent cell for treemaps

Description

Usage

Format

Details

summary.sunburstResult

Description

Usage

Arguments

Value

See Also

summary.voronoiResult