| Title: | Tag Clouds |
|---|---|
| Description: | Generating Tag and Word Clouds. |
| Authors: | January Weiner |
| Maintainer: | January Weiner <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.6 |
| Built: | 2025-02-02 03:24:42 UTC |
| Source: | https://github.com/january3/tagcloud |
A minimalistic editor for object of the tagcloud class.
editor.tagcloud(boxes)editor.tagcloud(boxes)
boxes |
An object of the tagcloud class, returned by the
|
tagcloud provides a minimalistic editor for tag clouds produced by
tagcloud function. After editor.tagcloud is called, the
tag cloud is plotted. First click selects the tag to be moved. The second
click sends the tag such that its left lower corner is at the position
indicated by the mouse. Right-clicking terminates the program.
An object of the tagcloud class with the modified positions
of the tags.
January Weiner <[email protected]>
## Not run: data( gambia ) terms <- gambia$Term tagcloud( terms ) boxes <- editor.tagcloud( boxes ) ## End(Not run)## Not run: data( gambia ) terms <- gambia$Term tagcloud( terms ) boxes <- editor.tagcloud( boxes ) ## End(Not run)
A data.frame object containing the results of a GO enrichment analysis from the GOstats package.
A data frame with 318 observations on the following 9 variables.
GOBPID Pvalue OddsRatio ExpCount Count Size Term
Gene Ontology (GO) biological process (BP) identifier
P value from enrichment test
Measure of enrichment
expected number of genes in the enriched partition which map to this GO term
number of genes in the enriched partition which map to this GO term
number of genes within this GO Term
Gene Ontology term description
The data results from a microarray analysis of the whole blood transcriptome of tuberculosis (TB) patients compared to healthy individuals. Genes were sorted by their p-value and analysed using the GOstats package.
Significantly enriched GO terms are included in this data frame.
Maertzdorf J., Ota M., Repsilber D., Mollenkopf H.J., Weiner J., et al. (2011) Functional Correlations of Pathogenesis-Driven Gene Expression Signatures in Tuberculosis. PLoS ONE 6(10): e26938. doi:10.1371/journal.pone.0026938
data(gambia) tagcloud( gambia$Term, -log( gambia$Pvalue ) )data(gambia) tagcloud( gambia$Term, -log( gambia$Pvalue ) )
Functions to create and display plots called tag clouds, word clouds or weighted lists, in which a usually large number of words is displayed in size correlated with a numerical value (for example, frequency in a text or enrichment of a GO term). This makes it easier to visualize the prominence of certain tags or words. Also, it looks nice.
## S3 method for class 'tagcloud' plot(x, family = NULL, add = FALSE, with.box = FALSE, col = NULL, sel = NULL, ...) ## S3 method for class 'tagcloud' summary(object, ...) tagcloud(tags, weights = 1, algorithm = "oval", scale = "auto", scale.multiplier = 1, order = "size", sel = NULL, wmin = NULL, wmax = NULL, floor = 1, ceiling = 3, family = NULL, col = NULL, fvert = 0, plot = TRUE, add = FALSE)## S3 method for class 'tagcloud' plot(x, family = NULL, add = FALSE, with.box = FALSE, col = NULL, sel = NULL, ...) ## S3 method for class 'tagcloud' summary(object, ...) tagcloud(tags, weights = 1, algorithm = "oval", scale = "auto", scale.multiplier = 1, order = "size", sel = NULL, wmin = NULL, wmax = NULL, floor = 1, ceiling = 3, family = NULL, col = NULL, fvert = 0, plot = TRUE, add = FALSE)
x, object
|
An object of the type produced by tagcloud. |
family |
Font family to use, a vector containing font families to use
for each tag. For the |
add |
If TRUE, the tags will be added to the current plot instead of creating a new plot. |
with.box |
If TRUE, a rectangle will be plotted around each tag. |
col |
Color or a vector containing colors to use for drawing the tags. |
sel |
An integer or boolean vector indicating which terms from the
provided list will be used to plot. The vectors |
tags |
A character vector containing words or tags to be shown on the plot. |
weights |
A numeric vector giving the relative proportions of text size corresponding to the given tag. |
algorithm |
Name of the algorithm to use. Can be "oval", "fill", "random", "snake", "list" or "clist". See Details. |
scale |
If "auto", text expansion will be calculated automatically to fit the available space. Otherwise, a numeric value used to modify the calculated text sizes; tune scale to achieve a better fit. |
scale.multiplier |
Multiplier for the final calculated text expansion parameter. Increase if there is too much empty space around the tag cloud; decrease if the tags go over the plot boundaries. |
order |
Determines in which order the tags will be drawn. Can be "size", "keep", "random", "height" or "width". See Details. |
wmin |
All items in the |
wmax |
All items in the |
floor |
Minimal text size. See Details. |
ceiling |
Maximal text size. See Details. |
fvert |
Fraction of tags which will be rotated by 90 degrees counterclockwise. |
plot |
If FALSE, no plot will be produced. |
... |
Further arguments to be passed to downstream methods. |
The package tagcloud creates and plots tag clouds (word clouds). The
algorithms in the package have been designed specifically with long tags
(such as GO Term descriptions) in mind.
The available arguments are as follows:
size – tags are ordered by size, that is, their effective width multiplied by their effective height. Default.
keep – keep the order from the list of words provided
random – randomize the tag list
width – order by effective screen width
height – order by effective screen height
By default, prior to plotting terms are ordered by size.
There are four algorithms for placing tags on the plot implemented in tagcloud.
oval – creates an oval cloud.
fill – an attempt will be made to fill the available space
random – randomly distribute tags over the available space. This algorithm is slow and not very effective
snake – tags are placed clockwise around the first tag to plot
list – create a list, one tag directly beneath another, justified left
clist – create a list, one tag directly beneath another, centered
Algorithms oval, fill and random attempt to fill the
available space by adjusting the scaling factor for the font sizes.
Placing tags such that the empty space
between the tags is minimized poses a non-trivial problem, because the
effective bounding box of a displayed text is not linearly dependent on the
cex parameter.
In tagcloud, first a cex parameter is calculated for each tag
separately, based on the parameters floor, ceiling and the
vector of weights. Note that all weights smaller than wmin are
replaced by wmin and all weights larger than wmax are replaced
by wmax. Then, effective heights and widths of the tags to be
displayed are calculated using the strwidth and
strheight functions.
Unless the argument scale is different from "auto", a scaling
parameter for cex is automatically calculated based on the current
area of the tags and the available plotting area. This usually results in a
reasonable plot, but is neither guaranteed to occupy all of the available
space without margins, nor that no tag will cross the view port.
tagcloud returns an object of the tagcloud-class, which really
is a data frame with the following columns:
tags – the tags, words or phrases shown on the plot
weights – a numeric vector that is used to calculate the size
of the plotted tags
family – name of the font family to be used in plotting
vertical – whether the tag should be rotated by 90
degrees counter-clockwise
x,y – coordinates of the left
lower corner of the tags bounding box
w,h – width and height of the bounding box
cex – text expansion factor, see par
s – surface of the tag (width x height)
The object of the tagcloud class can be manipulated using
editor.tagcloud and displayed using plot,
print and summary functions.
Care should be taken when using extra fonts loaded by the extrafont package; not all fonts can be easily copied to a PDF file.
Some ideas in this package are based on the 'wordcloud' package by Ian Fellows.
January Weiner <[email protected]>
editor.tagcloud – interactive editing of tagcloud
objects.
strmultline – splitting multi-word sentences into lines for a
better cloud display.
smoothPalette – mapping values onto a color gradient.
# a rather boring tag cloud data( gambia ) terms <- gambia$Term tagcloud( terms ) # tag cloud with weights relative to P value # colors relative to odds ratio, from light # grey to black weights <- -log( gambia$Pvalue ) colors <- smoothPalette( gambia$OddsRatio, max=4 ) tagcloud( terms, weights, col= colors, algorithm= "oval" ) # tag cloud filling the whole plot tagcloud( terms, weights, col= colors, algorithm= "fill" ) # just a list of only the first ten terms tagcloud( terms, weights, sel= 1:10, col= colors, algorithm= "list", order= "width" ) # oval, with line breaks in terms terms <- strmultline( gambia$Term ) tagcloud( terms, weights, col= colors, algorithm= "oval" ) ## Not run: # shows available font families, scaled according to # the total disk space occupied by the fonts require( extrafont ) ft <- fonttable() fi <- file.info( fonttable()$fontfile ) families <- unique( ft$FamilyName ) sizes <- sapply( families,function( x ) sum( fi[ ft$FamilyName == x, "size" ] ) ) tagcloud( families, sizes, family= families ) ## End(Not run)# a rather boring tag cloud data( gambia ) terms <- gambia$Term tagcloud( terms ) # tag cloud with weights relative to P value # colors relative to odds ratio, from light # grey to black weights <- -log( gambia$Pvalue ) colors <- smoothPalette( gambia$OddsRatio, max=4 ) tagcloud( terms, weights, col= colors, algorithm= "oval" ) # tag cloud filling the whole plot tagcloud( terms, weights, col= colors, algorithm= "fill" ) # just a list of only the first ten terms tagcloud( terms, weights, sel= 1:10, col= colors, algorithm= "list", order= "width" ) # oval, with line breaks in terms terms <- strmultline( gambia$Term ) tagcloud( terms, weights, col= colors, algorithm= "oval" ) ## Not run: # shows available font families, scaled according to # the total disk space occupied by the fonts require( extrafont ) ft <- fonttable() fi <- file.info( fonttable()$fontfile ) families <- unique( ft$FamilyName ) sizes <- sapply( families,function( x ) sum( fi[ ft$FamilyName == x, "size" ] ) ) tagcloud( families, sizes, family= families ) ## End(Not run)
Replace a vector of numbers by a vector of colors from a palette, such that values correspond to the colors on a smooth gradient.
smoothPalette(x, pal = NULL, max = NULL, min = NULL, n = 9, palfunc = NULL, na.color = "white")smoothPalette(x, pal = NULL, max = NULL, min = NULL, n = 9, palfunc = NULL, na.color = "white")
x |
A numeric vector |
pal |
Character vector containing the color gradient onto which the
numeric vector |
max |
Values of |
min |
Values of |
n |
Number of steps |
palfunc |
Palette function returned by colorRampPalette |
na.color |
NA values will be replaced by that color |
This function is used to map a continues numerical vector on an ordinal character vector, in especially a vector of colors. Color palette can be specified using an RColorBrewer palette name.
A character vector of the same length as the numeric vector
x, containing the matching colors.
January Weiner <[email protected]>
smoothPalette( 1:3 ) # will print: # "#CCCCCC" "#666666" "#000000" smoothPalette( 1:3, pal= "Blues" ) # will produce: # "#F7FBFF" "#6BAED6" "#08306B" x <- runif( 100 ) plot( 1:100, x, col= smoothPalette( x, pal= "BrBG" ), pch= 19 )smoothPalette( 1:3 ) # will print: # "#CCCCCC" "#666666" "#000000" smoothPalette( 1:3, pal= "Blues" ) # will produce: # "#F7FBFF" "#6BAED6" "#08306B" x <- runif( 100 ) plot( 1:100, x, col= smoothPalette( x, pal= "BrBG" ), pch= 19 )
Replace a space character by a newline in a multi-word sentence to get a better height / width ratio
strmultline(strings, ratio = 0.2)strmultline(strings, ratio = 0.2)
strings |
a character vector containing the multi-word sentences to be split |
ratio |
the desired ratio height / width |
Very long tags, for example GO Term descriptions, make a bad tag cloud.
strmultline tries to chop up such a long sentence into multiple
(currently two) lines, to get a better height / width ratio.
A character vector containing the modified sentences.
January Weiner <[email protected]>