plot.seas.norm {seas} | R Documentation |
Plots a “normal” of a seasonal variable, including a precipitation normal (which shows rain and snow fractions, where available). Significant missing data values are also indicated.
## S3 method for class 'seas.norm': plot(x, start=1, rep=0, ylim, varwidth=FALSE, normwidth=FALSE, leg, add.alt=FALSE, main, ylab, ...)
x |
a seas.norm object created by either
seas.norm or precip.norm |
start |
starting bin |
rep |
repeat bins |
ylim |
range of y-axis; either as a single value,
c(0,max) , or as two values c(min,max) |
varwidth |
logical ; varies the width of each bar directly
proportional to the frequency of active days (defined by a
threshold); the value is normalized according to the next argument |
normwidth |
normalizes the width of the bars to a fixed
numeric value (in days), or the maximum value if given
TRUE ; the default FALSE value normalizes each bar to
the number of potentially active days |
leg |
if TRUE shows a legend summary of the statistics in
the upper left hand corner; it can also be a c(x,y) pair or
“locator ” to manually place the legend on the
active graphics device |
add.alt |
logical ; adds imperial units on the right-hand
y-axis |
main |
title for plot; if it is missing, then it will automatically be generated |
ylab |
y-axis label; if it is missing, then it will automatically be generated |
... |
ignored |
The varwidth
variable is useful for separating different
precipitation patterns throughout the season. It changes the width of
the bar proportional to the frequency of precipitation events within
the bin. Ideally, the bars will be tall and narrow with intense storms
that occur infrequently, such as convective storms. Conversely the
bars will be broader with less-intense rainfall events occurring more
frequently.
M.W. Toews
seas.norm
, precip.norm
,
seas.sum
data(mscdata) dat <- mksub(mscdata, id=1108447) d.ss <- seas.sum(dat) plot(seas.norm(d.ss)) plot(precip.norm(d.ss,fun=median)) plot(precip.norm(d.ss,fun=mean)) plot(precip.norm(d.ss,fun=mean,norm="active")) plot(precip.norm(d.ss,fun=median,norm="active")) plot(precip.norm(d.ss),start=15,rep=12) mar <- par("mar") plot(precip.norm(d.ss),add.alt=TRUE) par(mar=mar) d2.ss <- seas.sum(dat,start.day=as.Date("2000-08-01")) plot(precip.norm(d2.ss, fun="mean"))