strat.plot.simple {rioja} | R Documentation |
Plots a simple stratigraphic diagram using lattice
. The function is most useful for visualising the effect of interpolating and / or smoothing a dataset.
strat.plot.simple(y1, x1, y2=NULL, x2=NULL, col=c("blue", "red"), sort.vars=c("original","wa", "alphabetical"), ylim=range(x1), y.rev=FALSE, type=c("b", "l"), subset=c(1:ncol(y1)), ...)
y1, y2, x1, x2 |
data frames to be plotted and corresponding x-values. If y2 and x2 are specified columns of y2 will be plotted overlain on those of y1. |
col, type |
colours and line types for the plots. |
sort.vars |
how to order variables in the plot). |
ylim |
limits for the y-axis. |
y.rev |
logical to reverse y-axis (which is actually the x-variable). |
subset |
a vector of column indices or a logical vector giving a subset of columns. |
... |
additional arguments to xyplot . |
strat.plot.simple
plots all or a subset of variables in a data frame (y) against a single secondary variable (x). The function is appropriate for plotting stratigraphic data, with the x-variable is plotted on the y-axis and variables in y arrayed across the page. The function is primarily intended to visualise the effect of smoothing by plotting the original data with the interpolated or smoothed version superimposed.
The number of rows and columns in the plot may be controlled using the layout
argument passed to link{xyplot}
. For example layout=c(10,1)
will produce a plot with 1 row and 10 columns.
By default, the x-axis has the same scale for all variables. To allow independent x-scales for each variable include the additional argument: scales=list(x="free"))
.
The function uses lattice to produce the plots so if you call it from a loop or using source
you will need to wrap it in a print
or plot
statement.
Function strat.plot.simple
returns an object of class link{trellis}
.
Steve Juggins
strat.plot
for better looking stratigraphics diagrams and interp.dataset
for interpolation and / or smoothing.
data(RLGH) spec <- RLGH$spec depth <- RLGH$depth$Depth # interpolate new dataset to every 0.5 cm # using default method (linear) x.new <- seq(0, 20, by=0.5) sp.interp <- interp.dataset(y=spec, x=depth, xout=x.new) ## Not run: # examine the results and compare to original data strat.plot.simple(spec, depth, sp.interp, x.new) ## End(Not run)