venneuler {venneuler} | R Documentation |
venneuler
calculates a Venn diagram from a disjoint set specification.
venneuler(combinations, weights, ...)
combinations |
This can be one of: a character vector (specifies class combinations as
class names separated by the ampersand \& character –
e.g. c("A","B","A&B") ), a named numeric vector (names specify
class combinations and values specify weights – e.g. c(A=1, B=2,
`A&B`=0.5) ), a character matrix of two columns (specifies mapping of
elements to sets – elements in first column and set names in second
column, weights argument is ignored) or a logical or numeric
matrix whose columns represent sets and co-occurrence is defined by
non-zero (rep. TRUE ) values in rows (weight for a row being 1 for
logical matrices or the row sum for numeric matrices). For convenience
data frames can be passed instead of matrices and they will be coerced
using as.matrix() .
|
weights |
If combinations is a character vector then this argument
specifies the associated weights. It is ignored in all other cases.
|
... |
Additional arguments (currently unused). |
An object of the class VennDiagram
with following components:
centers |
centers of the circles (columns are x and y coordinates) |
diameters |
diameters of the circles |
colors |
colors of the circles as values between 0 and 1 |
labels |
labels of the circles |
residuals |
residuals (percentage difference between input intersection area and fitted intersection area) |
stress |
stress value for solution |
stress01 |
.01 critical value for stress based on random data |
stress05 |
.05 critical value for stress based on random data |
Lee Wilkinson <leland.wilkinson@gmail.com>, R package: Simon Urbanek <simon.urbanek@r-project.org>
vd <- venneuler(c(A=0.3, B=0.3, C=1.1, "A&B"=0.1, "A&C"=0.2, "B&C"=0.1 ,"A&B&C"=0.1)) plot(vd) # same as c(A=1, `A&B`=1, `B&C`=1, C=1) m <- data.frame(elements=c("1","2","2","2","3"), sets=c("A","A","B","C","C")) v <- venneuler(m) plot(v) m <- as.matrix(data.frame(A=c(1.5, 0.2, 0.4, 0, 0), B=c(0 , 0.2, 0 , 1, 0), C=c(0 , 0 , 0.3, 0, 1))) # without weights v <- venneuler(m > 0) plot(v) # with weights v <- venneuler(m) plot(v)