seas (version 0.2-1)

image.seas.sum: Show a seasonal sum data object

Description

Graphically display a seasonal sum object, as well as the method of solution of the median/quantile normal

Usage

## 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, \ldots)

Arguments

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

Details

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.

See Also

seas.sum, seas.norm

Examples

data(mscdata)

dat.ss <- seas.sum(mscdata, id=1108447, width="mon")
image(dat.ss)

image(dat.ss,contour=FALSE)

image(dat.ss,norm="active")