image.seas.sum {seas} | 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, start, end, var, norm = "days", maxz, nlevels = 128, maxa, col = .65, dark = 0, gamma = 0.8, sqrt = FALSE, show.na = TRUE, show.median = TRUE, contour = TRUE, ...)
x |
a seas.sum object |
start |
start year; if omitted minimum year will be used |
end |
end year; if omitted will use same as start , and if
start is omitted, will use maximum year |
var |
the desired variable to show, otherwise will use the prime
variable, defined in x |
norm |
variable to normalize by, usually "days" , to
produce unit/day |
maxz |
maximum value to be displayed |
nlevels |
number of colour levels |
maxa |
maximum for annual axis, on right-hand graphs (if
show.median=TRUE ) |
col |
colour or hue, between [0,1] |
dark |
darkness of colour |
gamma |
gamma correction for colour |
sqrt |
logical ; square root of the values to be taken
(legend is transposed back to original unit) |
show.na |
logical ; put red a ‘x’ where data are NA |
show.median |
logical ; show how the median calculation is
achieved graphically (computationally it is done using a secant
method); see seas.norm for more information on this
method |
contour |
logical ; show contours in lower left-hand plot |
... |
other arguments passed to .seastitle and
.seascols for title style, colours, and other
customizations to the appearance |
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 ammount. This
numerical solution is found using seas.norm
.
M.W. Toews
data(mscdata) dat.ss <- seas.sum(mscdata, id=1108447, width="mon") image(dat.ss) image(dat.ss,contour=FALSE) image(dat.ss,norm="active")