image.seas.sum | R Documentation |
Graphically display a seasonal sum object, as well as the method of solution of the median/quantile “normal”
## S3 method for class 'seas.sum' image(x, var, norm = "days", start = 1, rep = 0, zlim, alim, palette = colorRampPalette(c("white", "blue"))(64), year.filter, power, contour = TRUE, show.median, main, ...)
x |
a |
var |
the desired variable to show, otherwise will use the prime
variable, defined in |
norm |
variable to normalize by, usually |
start |
starting bin number; e.g., for monthly sums, if
|
rep |
repetition of the bins (columns) |
zlim |
range of normalized values displayed; this can be either a
single number for the maximum (minimum set to zero), or a
|
alim |
if |
palette |
colours for |
year.filter |
specifies the annual seasons to display |
power |
this transforms the normalized values for the colours to
a power ( |
contour |
|
show.median |
|
main |
main title for plot, otherwise it will automatically be
generated; |
... |
ignored |
This is a graphical representation of a seas.sum
object,
and is far more informative than a traditional precipitation
“normal” (i.e., precip.norm
or
precip.norm
)
If norm = "days"
and show.median = TRUE
(default), the
seasonal sums appear in right-hand frames. Horizontal and vertical
lines indicate a ‘normal’ from the image, whereby the sum of
the quantile is equal to the median of the annual amount. This
numerical solution is found using seas.norm
.
Mike Toews
seas.sum
, seas.norm
See SeasOpts
to modify other aspects of the plot
data(mscdata) dat <- mksub(mscdata, id=1108447) dat.ss <- seas.sum(dat, width="mon") image(dat.ss) image(dat.ss, contour=FALSE) image(dat.ss, norm="active", start=6, rep=5) # different start day (not Jan 1st) dat2.ss <- seas.sum(dat, start.day=as.Date("2001-08-01")) image(dat2.ss) image(dat2.ss, power=2) image(dat2.ss, palette=rainbow(64), main=NA) # no title image(dat2.ss, palette=colorRampPalette(c("white", "darkgreen"))(16)) image(dat2.ss, "snow") image(dat2.ss, "snow", power=0.5) # growing degree days for 10 degC dat$gdd10 <- dat$t_mean - 10 dat$gdd10[dat$gdd10 < 0] <- 0 attr(dat$gdd10,"long.name") <- "growing degree days" dat3.ss <- seas.sum(dat, var="gdd10") image(dat3.ss, "gdd10", palette=colorRampPalette(c("white", "red"))(64))
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