Package 'eulerr' reference manual

Package 'eulerr'

Title:	Area-Proportional Euler and Venn Diagrams with Ellipses
Description:	Generate area-proportional Euler diagrams using numerical optimization. An Euler diagram is a generalization of a Venn diagram, relaxing the criterion that all interactions need to be represented. Diagrams may be fit with ellipses and circles via a wide range of inputs and can be visualized in numerous ways.
Authors:	Johan Larsson [aut, cre] , A. Jonathan R. Godfrey [ctb], Peter Gustafsson [ctb], David H. Eberly [ctb] (geometric algorithms), Emanuel Huber [ctb] (root solver code), Florian Privé [ctb]
Maintainer:	Johan Larsson <[email protected]>
License:	GPL-3
Version:	7.0.2
Built:	2024-11-25 06:34:19 UTC
Source:	CRAN

Title:

Area-Proportional Euler and Venn Diagrams with Ellipses

Description:

Generate area-proportional Euler diagrams using numerical optimization. An Euler diagram is a generalization of a Venn diagram, relaxing the criterion that all interactions need to be represented. Diagrams may be fit with ellipses and circles via a wide range of inputs and can be visualized in numerous ways.

Authors:

Johan Larsson [aut, cre]

, A. Jonathan R. Godfrey [ctb], Peter Gustafsson [ctb], David H. Eberly [ctb] (geometric algorithms), Emanuel Huber [ctb] (root solver code), Florian Privé [ctb]

Maintainer:

Johan Larsson <[email protected]>

License:

GPL-3

Version:

7.0.2

Built:

2024-11-25 06:34:19 UTC

Source:

CRAN

Help Index

Error plot for `euler` objects

Description

This is a diagnostic tool for evaluating the fit from a call to euler() visually. A color key is provided by default, which represents the chosen error metric so that one can easily detect which areas in the diagram to be skeptical about.

Usage

error_plot(
  x,
  type = c("regionError", "residuals"),
  quantities = TRUE,
  pal = NULL,
  ...
)
error_plot(
  x,
  type = c("regionError", "residuals"),
  quantities = TRUE,
  pal = NULL,
  ...
)

Arguments

`x`	an object of class `euler`, typically the result of a call to `euler()`.
`type`	error metric. `'regionError'` is the difference in percentage points from the input
`quantities`	whether to draw the error metric on the plot
`pal`	color palette for the fills in the legend
`...`	arguments passed down to `plot.euler()`. Currently, providing `fills`, `legend`, or `strips` are not allowed and will return a warning.

Details

Notice that this function is purely provided for diagnostic reasons and does not come with the same kind of customization that plot.euler() provides: the color legend can only be customized in regards to its color palette and another key (instead of labels) is completely turned off.

Value

Returns an object of class eulergram, which will be plotted on the device in the same manner as objects from plot.euler(). See plot.eulergram() for details.

Examples

error_plot(euler(organisms), quantities = FALSE)
error_plot(euler(organisms), quantities = FALSE)

Area-proportional Euler diagrams

Description

Fit Euler diagrams (a generalization of Venn diagrams) using numerical optimization to find exact or approximate solutions to a specification of set relationships. The shape of the diagram may be a circle or an ellipse.

Usage

euler(combinations, ...)

## Default S3 method:
euler(
  combinations,
  input = c("disjoint", "union"),
  shape = c("circle", "ellipse"),
  loss = c("square", "abs", "region"),
  loss_aggregator = c("sum", "max"),
  control = list(),
  ...
)

## S3 method for class 'data.frame'
euler(
  combinations,
  weights = NULL,
  by = NULL,
  sep = "_",
  factor_names = TRUE,
  ...
)

## S3 method for class 'matrix'
euler(combinations, ...)

## S3 method for class 'table'
euler(combinations, ...)

## S3 method for class 'list'
euler(combinations, ...)
euler(combinations, ...)

## Default S3 method:
euler(
  combinations,
  input = c("disjoint", "union"),
  shape = c("circle", "ellipse"),
  loss = c("square", "abs", "region"),
  loss_aggregator = c("sum", "max"),
  control = list(),
  ...
)

## S3 method for class 'data.frame'
euler(
  combinations,
  weights = NULL,
  by = NULL,
  sep = "_",
  factor_names = TRUE,
  ...
)

## S3 method for class 'matrix'
euler(combinations, ...)

## S3 method for class 'table'
euler(combinations, ...)

## S3 method for class 'list'
euler(combinations, ...)

Arguments

`combinations`	set relationships as a named numeric vector, matrix, or data.frame (see methods (by class))
`...`	arguments passed down to other methods
`input`	type of input: disjoint identities (`'disjoint'`) or unions (`'union'`).
`shape`	geometric shape used in the diagram
`loss`	type of loss to minimize over. If `"square"` is used together with the value `"sum"` for `loss_aggregator`, then the resulting loss function is the sum of squared errors, which is the default.
`loss_aggregator`	how the final loss is computed. `"sum"` indicates that the sum of the losses computed by `loss` are summed up. `"max"` indicates
`control`	a list of control parameters. `extraopt`: should the more thorough optimizer (currently `GenSA::GenSA()`) kick in (provided `extraopt_threshold` is exceeded)? The default is `TRUE` for ellipses and three sets and `FALSE` otherwise. `extraopt_threshold`: threshold, in terms of `diagError`, for when the extra optimizer kicks in. This will almost always slow down the process considerably. A value of 0 means that the extra optimizer will kick in if there is any error. A value of 1 means that it will never kick in. The default is `0.001`. `extraopt_control`: a list of control parameters to pass to the extra optimizer, such as `max.call`. See `GenSA::GenSA()`.
`weights`	a numeric vector of weights of the same length as the number of rows in `combinations`.
`by`	a factor or character matrix to be used in `base::by()` to split the data.frame or matrix of set combinations
`sep`	a character to use to separate the dummy-coded factors if there are factor or character vectors in 'combinations'.
`factor_names`	whether to include factor names when constructing dummy codes

Details

If the input is a matrix or data frame and argument by is specified, the function returns a list of euler diagrams.

The function minimizes the residual sums of squares,

$\sum_{i=1}^n (A_i - \omega_i)^2,$

by default, where $\omega_i$ the size of the ith disjoint subset, and $A_i$ the corresponding area in the diagram, that is, the unique contribution to the total area from this overlap. The loss function can, however, be controlled via the loss argument.

euler() also returns stress (from venneuler), as well as diagError, and regionError from eulerAPE.

The stress statistic is computed as

$\frac{\sum_{i=1}^n (A_i - \beta\omega_i)^2}{\sum_{i=1}^n A_i^2},$

where

$\beta = \sum_{i=1}^n A_i\omega_i / \sum_{i=1}^n \omega_i^2.$

regionError is computed as

$\left| \frac{A_i}{\sum_{i=1}^n A_i} - \frac{\omega_i}{\sum_{i=1}^n \omega_i}\right|.$

diagError is simply the maximum of regionError.

Value

A list object of class 'euler' with the following parameters.

`ellipses`	a matrix of `h` and `k` (x and y-coordinates for the centers of the shapes), semiaxes `a` and `b`, and rotation angle `phi`
`original.values`	set relationships in the input
`fitted.values`	set relationships in the solution
`residuals`	residuals
`regionError`	the difference in percentage points between each disjoint subset in the input and the respective area in the output
`diagError`	the largest `regionError`
`stress`	normalized residual sums of squares

Methods (by class)

euler(default): a named numeric vector, with combinations separated by an ampersand, for instance A&B = 10. Missing combinations are treated as being 0.
euler(data.frame): a data.frame of logicals, binary integers, or factors.
euler(matrix): a matrix that can be converted to a data.frame of logicals (as in the description above) via base::as.data.frame.matrix().
euler(table): A table with max(dim(x)) < 3.
euler(list): a list of vectors, each vector giving the contents of that set (with no duplicates). Vectors in the list must be named.

References

Wilkinson L. Exact and Approximate Area-Proportional Circular Venn and Euler Diagrams. IEEE Transactions on Visualization and Computer Graphics (Internet). 2012 Feb (cited 2016 Apr 9);18(2):321-31. Available from: doi:10.1109/TVCG.2011.56

Micallef L, Rodgers P. eulerAPE: Drawing Area-Proportional 3-Venn Diagrams Using Ellipses. PLOS ONE (Internet). 2014 Jul (cited 2016 Dec 10);9(7):e101717. Available from: doi:10.1371/journal.pone.0101717

Examples

# Fit a diagram with circles
combo <- c(A = 2, B = 2, C = 2, "A&B" = 1, "A&C" = 1, "B&C" = 1)
fit1 <- euler(combo)

# Investigate the fit
fit1

# Refit using ellipses instead
fit2 <- euler(combo, shape = "ellipse")

# Investigate the fit again (which is now exact)
fit2

# Plot it
plot(fit2)

# A set with no perfect solution
euler(c(
  "a" = 3491, "b" = 3409, "c" = 3503,
  "a&b" = 120, "a&c" = 114, "b&c" = 132,
  "a&b&c" = 50
))


# Using grouping via the 'by' argument through the data.frame method
euler(fruits, by = list(sex, age))


# Using the matrix method
euler(organisms)

# Using weights
euler(organisms, weights = c(10, 20, 5, 4, 8, 9, 2))

# The table method
euler(pain, factor_names = FALSE)

# A euler diagram from a list of sample spaces (the list method)
euler(plants[c("erigenia", "solanum", "cynodon")])
# Fit a diagram with circles
combo <- c(A = 2, B = 2, C = 2, "A&B" = 1, "A&C" = 1, "B&C" = 1)
fit1 <- euler(combo)

# Investigate the fit
fit1

# Refit using ellipses instead
fit2 <- euler(combo, shape = "ellipse")

# Investigate the fit again (which is now exact)
fit2

# Plot it
plot(fit2)

# A set with no perfect solution
euler(c(
  "a" = 3491, "b" = 3409, "c" = 3503,
  "a&b" = 120, "a&c" = 114, "b&c" = 132,
  "a&b&c" = 50
))


# Using grouping via the 'by' argument through the data.frame method
euler(fruits, by = list(sex, age))


# Using the matrix method
euler(organisms)

# Using weights
euler(organisms, weights = c(10, 20, 5, 4, 8, 9, 2))

# The table method
euler(pain, factor_names = FALSE)

# A euler diagram from a list of sample spaces (the list method)
euler(plants[c("erigenia", "solanum", "cynodon")])

Get or set global graphical parameters for eulerr

Description

This function provides a means to set default parameters for functions in eulerr. Query eulerr_options() (without any argument) to see all the available options and read more about the plot-related ones in grid::gpar() and graphics::par().

Usage

eulerr_options(...)
eulerr_options(...)

Arguments

...

objects to update the global graphical parameters for eulerr with.

Details

Currently, the following items will be considered:

pointsize: size in pts to be used as basis for fontsizes and some margin sizes in the resulting plot

fills: a list of items fill and alpha
edges: a list of items col, alpha, lex, lwd, and lty
labels: a list of items rot, col, alpha, fontsize, cex, fontfamily, fontface, lineheight, and font
quantities: a list of items type, rot, col, alpha, fontsize, cex, fontfamily, lineheight, and font
strips: col, alpha, fontsize, cex, fontfamily, lineheight, and font
legend: arguments to grid::legendGrob() as well as col, alpha, fontsize, cex, fontfamily, lineheight, and font
main: arguments to grid::textGrob()
padding: a grid::unit() giving the padding between various elements in plots from plot.euler(), which you can change if you, for instance, want to increase spacing between labels, quantities, and percentages.

Value

This function gets or sets updates in the global environment that are used in plot.euler().

Examples

eulerr_options(edges = list(col = "blue"), fontsize = 10)
eulerr_options(n_threads = 2)
eulerr_options(edges = list(col = "blue"), fontsize = 10)
eulerr_options(n_threads = 2)

Fruits

Description

A synthethic data set of preferences for fruits and their overlaps, generated only to be a showcase for the examples for this package.

Usage

fruits
fruits

Format

A data.frame with 100 observations of 5 variables:

banana: whether the person likes bananas, a logical
apple: whether the person likes apples, a logical
orange: whether the person likes oranges, a logical
sex: the sex of the person, a factor with levels 'male' and 'female'
age: the age of the person, a factor with levels 'child' and 'adult'

Organisms

Description

Example data from the VennMaster package.

Usage

organisms
organisms

Format

A matrix with 7 observations, consisting of various organisms, and 5 variables: animal, mammal, plant, sea, and, spiny, indicating whether the organism belongs to the category or not.

Details

Note that this data is difficult to fit using an Euler diagram, even if we use ellipses, which is clear if one chooses to study the various overlaps in the resulting diagrams.

Source

https://github.com/sysbio-bioinf/VennMaster/blob/master/data_examples/deploy/example1.list

Pain distribution data

Description

Data from a study on pain distribution for patients with persistent neck pain in relation to a whiplash trauma.

Usage

pain
pain

Format

A flat table (cross-table) with with sex in columns and pain distribution in rows and integer counts making up the cells of the table.

Disclaimer

Note that the maintainer of this package is an author of the source for this data.

Source

Westergren H, Larsson J, Freeman M, Carlsson A, Jöud A, Malmström E-M. Sex-based differences in pain distribution in a cohort of patients with persistent post-traumatic neck pain. Disability and Rehabilitation. 2017 Jan 27

Plants

Description

Data on plants and the states in the US and Canada they occur in.

Usage

plants
plants

Format

A list with 33,721 plants, each containing a character vector listing the states in the US and Canada in which they occur. The names in the list specify the species or genus of the plant.

Source

USDA, NRCS. 2008. The PLANTS Database (http://plants.usda.gov/, 31 December 2008). National Plant Data Center, Baton Rouge, LA 70874-4490 USA.

Dua, D. and Karra Taniskidou, E. (2017). UCI Machine Learning Repository http://archive.ics.uci.edu/ml/. Irvine, CA: University of California, School of Information and Computer Science.

Plot Euler and Venn diagrams

Description

Plot diagrams fit with euler() and venn() using grid::Grid() graphics. This function sets up all the necessary plot parameters and computes the geometry of the diagram. plot.eulergram(), meanwhile, does the actual plotting of the diagram. Please see the Details section to learn about the individual settings for each argument.

Usage

## S3 method for class 'euler'
plot(
  x,
  fills = TRUE,
  edges = TRUE,
  legend = FALSE,
  labels = identical(legend, FALSE),
  quantities = FALSE,
  strips = NULL,
  main = NULL,
  n = 200L,
  adjust_labels = TRUE,
  ...
)

## S3 method for class 'venn'
plot(
  x,
  fills = TRUE,
  edges = TRUE,
  legend = FALSE,
  labels = identical(legend, FALSE),
  quantities = TRUE,
  strips = NULL,
  main = NULL,
  n = 200L,
  adjust_labels = TRUE,
  ...
)
## S3 method for class 'euler'
plot(
  x,
  fills = TRUE,
  edges = TRUE,
  legend = FALSE,
  labels = identical(legend, FALSE),
  quantities = FALSE,
  strips = NULL,
  main = NULL,
  n = 200L,
  adjust_labels = TRUE,
  ...
)

## S3 method for class 'venn'
plot(
  x,
  fills = TRUE,
  edges = TRUE,
  legend = FALSE,
  labels = identical(legend, FALSE),
  quantities = TRUE,
  strips = NULL,
  main = NULL,
  n = 200L,
  adjust_labels = TRUE,
  ...
)

Arguments

`x`	an object of class `'euler'`, generated from `euler()`
`fills`	a logical, vector, or list of graphical parameters for the fills in the diagram. Vectors are assumed to be colors for the fills. See `grid::grid.path()`.
`edges`	a logical, vector, or list of graphical parameters for the edges in the diagram. Vectors are assumed to be colors for the edges. See `grid::grid.polyline()`.
`legend`	a logical scalar or list. If a list, the item `side` can be used to set the location of the legend. See `grid::grid.legend()`.
`labels`	a logical, vector, or list. Vectors are assumed to be text for the labels. See `grid::grid.text()`.
`quantities`	a logical, vector, or list. Vectors are assumed to be text for the quantities' labels, which by default are the original values in the input to `euler()`. In addition to arguments that apply to `grid::grid.text()`, an argument `type` may also be used which should be a combination of `"counts"` and `"percent"`. The first item will be printed first and the second will be printed thereafter inside brackets. The default is `type = "counts"`.
`strips`	a list, ignored unless the `'by'` argument was used in `euler()`
`main`	a title for the plot in the form of a character, expression, list or something that can be sensibly converted to a label via `grDevices::as.graphicsAnnot()`. A list of length one can be provided, in which case its only element is used as the label. If a list of longer length is provided, an item named `'label'` must be provided (and will be used for the actual text).
`n`	number of vertices for the `edges` and `fills`
`adjust_labels`	a logical. If `TRUE`, adjustment will be made to avoid overlaps or out-of-limits plotting of labels, quantities, and percentages.
`...`	parameters to update `fills` and `edges` with and thereby a shortcut to set these parameters `grid::grid.text()`.

Details

The only difference between plot.euler() and plot.venn() is that quantities is set to TRUE by default in the latter and FALSE in the former.

Most of the arguments to this function accept either a logical, a vector, or a list where

logical values set the attribute on or off,
vectors are shortcuts to commonly used options (see the individual parameters), and
lists enable fine-grained control, including graphical parameters as described in grid::gpar() and control arguments that are specific to each argument.

The various grid::gpar() values that are available for each argument are:

	fills	edges	labels	quantities	strips	legend	main
col		x	x	x	x	x	x
fill	x
alpha	x	x	x	x	x	x	x
lty		x
lwd		x
lex		x
fontsize			x	x	x	x	x
cex			x	x	x	x	x
fontfamily			x	x	x	x	x
lineheight			x	x	x	x	x
font			x	x	x	x	x

Defaults for these values, as well as other parameters of the plots, can be set globally using eulerr_options().

If the diagram has been fit using the data.frame or matrix methods and using the by argument, the plot area will be split into panels for each combination of the one to two factors.

For users who are looking to plot their diagram using another package, all the necessary parameters can be collected if the result of this function is assigned to a variable (rather than printed to screen).

Value

Provides an object of class 'eulergram' , which is a description of the diagram to be drawn. plot.eulergram() does the actual drawing of the diagram.

Examples

fit <- euler(c("A" = 10, "B" = 5, "A&B" = 3))

# Customize colors, remove borders, bump alpha, color labels white
plot(fit,
     fills = list(fill = c("red", "steelblue4"), alpha = 0.5),
     labels = list(col = "white", font = 4))

# Add quantities to the plot
plot(fit, quantities = TRUE)

# Add a custom legend and retain quantities
plot(fit, quantities = TRUE, legend = list(labels = c("foo", "bar")))

# Plot without fills and distinguish sets with border types instead
plot(fit, fills = "transparent", lty = 1:2)

# Save plot parameters to plot using some other method
diagram_description <- plot(fit)

# Plots using 'by' argument
plot(euler(fruits[, 1:4], by = list(sex)), legend = TRUE)
fit <- euler(c("A" = 10, "B" = 5, "A&B" = 3))

# Customize colors, remove borders, bump alpha, color labels white
plot(fit,
     fills = list(fill = c("red", "steelblue4"), alpha = 0.5),
     labels = list(col = "white", font = 4))

# Add quantities to the plot
plot(fit, quantities = TRUE)

# Add a custom legend and retain quantities
plot(fit, quantities = TRUE, legend = list(labels = c("foo", "bar")))

# Plot without fills and distinguish sets with border types instead
plot(fit, fills = "transparent", lty = 1:2)

# Save plot parameters to plot using some other method
diagram_description <- plot(fit)

# Plots using 'by' argument
plot(euler(fruits[, 1:4], by = list(sex)), legend = TRUE)

Print (plot) Euler diagram

Description

This function is responsible for the actual drawing of 'eulergram' objects created through plot.euler(). print.eulergram() is an alias for plot.eulergram(), which has been provided so that plot.euler() gets called automatically.

Usage

## S3 method for class 'eulergram'
plot(x, newpage = TRUE, ...)

## S3 method for class 'eulergram'
print(x, ...)
## S3 method for class 'eulergram'
plot(x, newpage = TRUE, ...)

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

Arguments

`x`	an object of class `'eulergram'`, usually the output of `plot.euler()`
`newpage`	if `TRUE`, opens a new page via `grid.newpage()` to draw on
`...`	ignored

Value

A plot is drawn on the current device using grid::Grid() graphics.

Print a summary of an Euler diagram

Description

This function is responsible for printing fits from euler() and provides a summary of the fit. Prints a data frame of the original set relationships and the fitted values as well as diagError and stress statistics.

Usage

## S3 method for class 'euler'
print(x, round = 3, vsep = strrep("-", 0.75 * getOption("width")), ...)
## S3 method for class 'euler'
print(x, round = 3, vsep = strrep("-", 0.75 * getOption("width")), ...)

Arguments

`x`	`'euler'` object from `euler()`
`round`	number of decimal places to round to
`vsep`	character string to paste in between `euler` objects when `x` is a nested `euler` object
`...`	arguments passed to `base::print.data.frame()`

Value

Summary statistics of the fitted Euler diagram are printed to screen.

Examples

euler(organisms)
euler(organisms)

Print a summary of a Venn diagram

Description

This function is responsible for printing objects from from venn() and provides a simple description of the number of sets and the specifications for the ellipses of the Venn diagram.

Usage

## S3 method for class 'venn'
print(x, round = 3, vsep = strrep("-", 0.75 * getOption("width")), ...)
## S3 method for class 'venn'
print(x, round = 3, vsep = strrep("-", 0.75 * getOption("width")), ...)

Arguments

`x`	an object of class `'venn'`
`round`	number of digits to round the ellipse specification to
`vsep`	character string to paste in between `euler` objects when `x` is a nested `euler` object
`...`	arguments passed to `base::print.data.frame()`

Value

Summary statistics of the fitted Venn diagram are printed to screen.

Examples

venn(organisms)
venn(organisms)

Venn diagrams

Description

This function fits Venn diagrams using an interface that is almost identical to euler(). Strictly speaking, Venn diagrams are Euler diagrams where every intersection is visible, regardless of whether or not it is zero. In almost every incarnation of Venn diagrams, however, the areas in the diagram are also non-proportional to the input; this is also the case here.

Usage

venn(combinations, ...)

## Default S3 method:
venn(
  combinations,
  input = c("disjoint", "union"),
  names = letters[length(combinations)],
  ...
)

## S3 method for class 'table'
venn(combinations, ...)

## S3 method for class 'data.frame'
venn(
  combinations,
  weights = NULL,
  by = NULL,
  sep = "_",
  factor_names = TRUE,
  ...
)

## S3 method for class 'matrix'
venn(combinations, ...)

## S3 method for class 'list'
venn(combinations, ...)
venn(combinations, ...)

## Default S3 method:
venn(
  combinations,
  input = c("disjoint", "union"),
  names = letters[length(combinations)],
  ...
)

## S3 method for class 'table'
venn(combinations, ...)

## S3 method for class 'data.frame'
venn(
  combinations,
  weights = NULL,
  by = NULL,
  sep = "_",
  factor_names = TRUE,
  ...
)

## S3 method for class 'matrix'
venn(combinations, ...)

## S3 method for class 'list'
venn(combinations, ...)

Arguments

`combinations`	set relationships as a named numeric vector, matrix, or data.frame (see methods (by class))
`...`	arguments passed down to other methods
`input`	type of input: disjoint identities (`'disjoint'`) or unions (`'union'`).
`names`	a character vector for the names of each set of the same length as 'combinations'. Must not be `NULL` if `combinations` is a one-length numeric.
`weights`	a numeric vector of weights of the same length as the number of rows in `combinations`.
`by`	a factor or character matrix to be used in `base::by()` to split the data.frame or matrix of set combinations
`sep`	a character to use to separate the dummy-coded factors if there are factor or character vectors in 'combinations'.
`factor_names`	whether to include factor names when constructing dummy codes

Value

Returns an object of class ⁠'venn', 'euler'⁠ with items

`ellipses`	a matrix of `h` and `k` (x and y-coordinates for the centers of the shapes), semiaxes `a` and `b`, and rotation angle `phi`
`original.values`	set relationships in the input
`fitted.values`	set relationships in the solution

Methods (by class)

venn(default): a named numeric vector, with combinations separated by an ampersand, for instance A&B = 10. Missing combinations are treated as being 0.
venn(table): A table with max(dim(x)) < 3.
venn(data.frame): a data.frame of logicals, binary integers, or factors.
venn(matrix): a matrix that can be converted to a data.frame of logicals (as in the description above) via base::as.data.frame.matrix().
venn(list): a list of vectors, each vector giving the contents of that set (with no duplicates). Vectors in the list do not need to be named.

Examples

# The trivial version
f1 <- venn(5, names = letters[1:5])
plot(f1)

# Using data (a numeric vector)
f2 <- venn(c(A = 1, "B&C" = 3, "A&D" = 0.3))

# The table method
venn(pain, factor_names = FALSE)

# Using grouping via the 'by' argument through the data.frame method
venn(fruits, by = list(sex, age))


# Using the matrix method
venn(organisms)

# Using weights
venn(organisms, weights = c(10, 20, 5, 4, 8, 9, 2))

# A venn diagram from a list of sample spaces (the list method)
venn(plants[c("erigenia", "solanum", "cynodon")])
# The trivial version
f1 <- venn(5, names = letters[1:5])
plot(f1)

# Using data (a numeric vector)
f2 <- venn(c(A = 1, "B&C" = 3, "A&D" = 0.3))

# The table method
venn(pain, factor_names = FALSE)

# Using grouping via the 'by' argument through the data.frame method
venn(fruits, by = list(sex, age))


# Using the matrix method
venn(organisms)

# Using weights
venn(organisms, weights = c(10, 20, 5, 4, 8, 9, 2))

# A venn diagram from a list of sample spaces (the list method)
venn(plants[c("erigenia", "solanum", "cynodon")])

Package 'eulerr'

Help Index

Error plot for euler objects

Description

Usage

Arguments

Details

Value

See Also

Examples

Area-proportional Euler diagrams

Description

Usage

Arguments

Details

Value

Methods (by class)

References

See Also

Examples

Get or set global graphical parameters for eulerr

Description

Usage

Arguments

Details

Value

See Also

Examples

Fruits

Description

Usage

Format

Organisms

Description

Usage

Format

Details

Source

Pain distribution data

Description

Usage

Format

Disclaimer

Source

Plants

Description

Usage

Format

Source

Plot Euler and Venn diagrams

Description

Usage

Arguments

Details

Value

See Also

Examples

Print (plot) Euler diagram

Description

Usage

Arguments

Value

Print a summary of an Euler diagram

Description

Usage

Arguments

Value

See Also

Examples

Print a summary of a Venn diagram

Description

Usage

Arguments

Value

See Also

Examples

Venn diagrams

Description

Usage

Arguments

Error plot for `euler` objects