ggplot {visa}

Create a new ggplot plot with a geom_line() layer from spectra data

Description

ggplot() initializes a ggplot object. It can be used to declare the input spectra object for a graphic and to optionally specify the set of plot aesthetics intended to be common throughout all subsequent layers unless specifically overridden.

Usage

## S3 method for class 'spectra'
ggplot(
  data,
  mapping = NULL,
  ...,
  wl = NULL,
  w.unit = "nm",
  environment = parent.frame()
)

## S3 method for class 'cm'
ggplot(
  data,
  mapping = NULL,
  ...,
  show.stat = TRUE,
  environment = parent.frame()
)

Arguments

data

Default spectra database to use for plot. If not a spectra database, the methods used will be those defined in package ggplot2. See ggplot. If not specified, must be supplied in each layer added to the plot.

mapping

Default list of aesthetic mappings to use for plot. If not specified, in the case of spectra objects, a default mapping will be used.

...

Other arguments passed on to methods. Not currently used.

wl

numeric The wavelength vector.

w.unit

character The wavelength unit of the spectra.

environment

If an variable defined in the aesthetic mapping is not found in the data, ggplot will look for it in this environment. It defaults to using the environment in which ggplot() is called.

show.stat

A logic value. whether show the best R^2 and bands.

Details

ggplot() is typically used to construct a plot incrementally, using the + operator to add layers to the existing ggplot object. This is advantageous in that the code is explicit about which layers are added and the order in which they are added. For complex graphics with multiple layers, initialization with ggplot is recommended.

Value

cm_plot

Returns a ggplot object of correlation-matrix.

Note

Current implementation does not merge default mapping with user supplied mapping. If user supplies a mapping, it is used as is. To add to the default mapping, aes() can be used by itself to compose the ggplot.

See Also

?ggpmisc::ggplot()

Examples

library(visa)
library(ggplot2)
ggplot.spectra(NSpec.DF)

library(visa)
data(NSpec.DF)
x <- NSpec.DF$N # nitrogen
S <- NSpec.DF$spectra[, seq(1, ncol(NSpec.DF$spectra), 5)] # resampled to 10 nm steps
cm <- cm.sr(S, x, cm.plot = FALSE)
ggplot.cm(cm)