Learn R Programming

loa (version 0.3.1.1)

4.1.panel.pal: panelPal

Description

lattice plot management using the loa function panelPal

Usage

panelPal(ans, panel = NULL, preprocess = FALSE, 
         reset.xylims = FALSE, legend = NULL,
         by.group = NULL, by.zcase = NULL, ...)

panelPal.old(x, y, subscripts, at, col.regions, ..., panel = panel.xyplot, ignore = NULL, group.fun = NULL)

loaHandler(panel = NULL,...)

Value

Both panelPal and panelPal.old are intended to be used with

trellis plot outputs.

panelPal should be employed retrospectively. So, for example:

p1 <- xyplot(...)

panelPanel(p1, ...)

The previous version, currently retained as panelPal.old, was employed developed as a panel... function wrapper and intended to be employed within the plot call. So, for example:

xyplot(..., panel = function(...) panelPal(..., panel=panel))

Because it is run within the plot call, and therefore within each panel called, it does not provide features that require panel-to-plot, panel-to-key or panel-to-panel communication.

loaHandler returns either a logical (FALSE if not loa 'friendly';

TRUE if loa 'friendly') or a list of default arguments to be used when plotting.

Arguments

ans

For panelPal only, a stanard trellis object, such as that generated by lattice function xyplot.

panel

A panel function, e.g. panel.xyplot. If supplied in panelPal call, typically the one used to generate ans. If supplied in panelPal.old, the panel that is intended to used when generating a plot.

preprocess, reset.xylims, legend, by.group, by.zcase

For panelPal only, loa plot management arguments. proprocess: Logical, should the supplied panel function be preprocessed? reset.xylims: Logical, should the plot dimensions be reset if changed, e.g. by preprocessing? legend: the legend as with standard lattice plots, by.group: a vector of plot argument names to be linked to any group conditioning, by.zcase: a vector of plot argument names to be linked to any z case conditioning See Details below.

...

Additional arguments, typically passed on.

x,y,subscripts,at,col.regions

For panelPal.old only, panel arguments passed down to individual panels.

ignore

Any additional arguments that panelPal.old should ignore and pass on to panel unchecked/unmodified.

group.fun

Fine control of the standard lattice plot argument group. It can be a vector or list containing the same number of elements as there as groups. These can be functions (or the names of functions as characters) setting individual functions for group or sets of parameters to be evaluated using the panel function. For example, the current NULL default generates a list of col and pch settings that produce a conventional grouped scatter plot output when the group argument is applied to the panel default panel.xyplot. See Details below.

Author

Karl Ropkins

Details

panelPal provides a range of generic plot management features.

Firstly, it allows plot as well as panel defaults to be managed by the panel... function. This allows the panel developer to control plot-level components of the plot output, e.g. which key to use with the plot and what default settings to apply to it. See example 1 below.

Secondly, it uses a generalised extension of the subscripting methods described by Deepayan Sarkar in Chapter 5 of Lattice (see sections on scatterplots and extensions) to automatically handle plot argument subscripting, demonstrated in example 2 below.

Thirdly, it applies an extension of the method used by the hexbin lattice panel to pass hex cell counts (calculated in panels) to the plot key and standardise the assignment of associated parameters within all panels to provide more general panel-to-panel and panel-to-scale. The method is briefly discussed in Chapter 14 of Sarkar.

This method has also been extended by isolating processing and plot components of the panel... function operation allowing results of any calculations made in-panel to be retained rather than lost when plot is generated.

Fourly, group... and zcase... arguments can used to manage plot group and zcase based plot outputs.

Some panelPal are implemented if specially structured (or loa-friendly) panel... functions are supplied. These are illustrated in the final example below.

loaHandler is a workhorse that assesses information in 'loa' friendly panel... functions. As well as checking this, loaHandler also checks the supplied panel for any default plot settings. This allows users to manage the appearance of a plot from the panel or automatically associated color keys.

References

These function makes extensive use of code developed by others.

lattice:
Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R. Springer, New York. ISBN 978-0-387-75968-5

hexbin:
Dan Carr, ported by Nicholas Lewin-Koh and Martin Maechler (2013). hexbin: Hexagonal Binning Routines. R package version 1.26.2. http://CRAN.R-project.org/package=hexbin

panelPal.old and panelPal both apply an extension of the subscripting methods described by Deepayan Sarkar in Chapter 5 of Lattice (see sections on scatterplots and extensions) to automatically handle plot argument subscripting.

panelPal applies an extension of the method used by hex bin lattice panel to comunicate hex cell counts (calculated in panels) panel-to-panel and panel-to-scale. The method is briefly discussed in Chapter 14 of Sarkar.

See Also

Examples

Run this code

## the combination of panelPal and specially 
## structured panel... functions provides 
## several additional plot features:

require(lattice)

## example 1
## plot management from the panel... functions.

# loaHandler can used to see if a panel is loa-friendly

loaHandler(panel.xyplot)  #FALSE
loaHandler(panel.loaPlot) #panel defaults

# note that these include a list called 
# default.settings. These are settings that are  
# automatically added to the plot call.

# Here this assigns a specialist key to that 
# panel. However, the same mechanism can also 
# be used to turn off plot elements like the 
# standard lattice axes, when using in panel 
# alternatives

# first some silly data

a <- rnorm(1000)
b <- rnorm(1000)

# now compare:  

# default plot 
# note bubble plot style key

loaPlot(a~a*b) 

# bin plot
# with classic color key

loaPlot(a~a*b, panel = panel.binPlot) 

 
## example 2
## automatic subscripting with loa

# Other arguments are not automatically 
# aligned with the main plots. 

# For example, consider the data:

a <- 1:10
ref <- rep(1:2, each=5)

# and associated lattice xyplot output:

xyplot(a~a|ref, col=ref, pch=19)

# Here, the 'col' argument does not 
# automatically track plot conditioning. 

# With lattice plots you need to assign
# arguments you want to track in this 
# manner using subscripts, as discussed 
# in Lattice Chapter 5.

# Now compare a similar loaPlot:

loaPlot(~a*a|ref, col=ref, pch=19)

# Here, panelPal automatically handles 
# such subscripting. It extends this 
# assumption to all supplied arguments.  

# For example, try
if (FALSE) {
  loaPlot(~a*a|ref, col=ref, pch=ref)
  loaPlot(~a*a|ref, col=ref, pch=1:10)}

Run the code above in your browser using DataLab