plot.Spectra: Plots an object inheriting from the Spectra class

In inspectr: Storing, manipulating and analysis spectroscopy and associated data in R.

Description

Plots an object inheriting from the Spectra class

Usage

## S3 method for class 'Spectra'
 plot(x, gg=FALSE, gaps=TRUE, attr=NULL, ...)
## S4 method for signature 'Spectra'
 plot_summary(x, fun=mean, se=TRUE, ...)
## S4 method for signature 'Spectra'
 plot_stack(x)
## S4 method for signature 'Spectra'
 plot_offset(x, offset=1)

Arguments

x	an object of class "Spectra" or inheriting from this class
gg	if TRUE, uses the ggplot2 package to plot the data, if FALSE uses matplot from base graphics (much faster)
gaps	if TRUE, gaps in the spectra are not plotted
attr	attribute against which lines are coloured (only for gg = TRUE
fun	an aggregation function
se	if TRUE, plots the standard deviation around the summary spectra (computed by function as given by fun). If FALSE, does not plot dispersion information. If a function, uses this function instead of sd.
offset	Offset between spectra
...	options to be passed to matplot

Details

The philosophy of this plotting routine is to provide a "quick'n'dirty" way to plot your spectra collection. For advanced visualisations, the use of melt_spectra alongside with ggplot2 or lattice is encouraged.

Author(s)

Pierre Roudier [e-mail]

Examples

# Loading example data
data(australia)
spectra(australia) <- sr_no ~ ... ~ 350:2500

# Default plotting method
plot(australia)

# Default plot using ggplot2
plot(australia, gg = TRUE)

# Managing gaps in the spectra
s <- cut(australia, wl =c(-1*450:500, -1*1800:2050))
plot(s, gaps = TRUE)
plot(s, gaps = FALSE)

# passing various options to matplot
plot(australia, lty = 1:5, col = 'blue', xlab = 'foo', ylab = 'bar', ylim = c(0.4,0.6), main = 'my plot')

# Using colour ramps
plot(australia, lty = 1, col = rainbow(10), main = "It is possible to create really ugly visualisations")

## Not run: 
# Example using colours given by ColorBrewer (http://colorbrewer2.org/)
library(RColorBrewer)
plot(australia, lty = 1, col = brewer.pal(n = 8, name = "Set2"))

## End(Not run)

# Using an attribute to group spectra

australia$fact <- sample(LETTERS[1:3], size = nrow(australia), replace = TRUE) # Generate some kind of factor
s <- aggregate_spectra(australia, fun = mean, id = 'fact')
plot(s, gg = TRUE, attr = 'fact')

inspectr documentation built on May 2, 2019, 5:45 p.m.