Description Usage Arguments Value Author(s) Examples
Various methods for converting objects from one shape to another. These methods do the house keeping, keeping track of attributes and metadata.
as.field.station
uses regrid
to generate a field based
on bi-linear interpolation of station values and their coordinates. Unfinished...
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | as.4seasons(x,FUN='mean',...)
as.4seasons.default(x,FUN='mean',...)
as.4seasons.station(x,FUN='mean',...)
as.4seasons.day(x,FUN='mean',na.rm=TRUE,dateindex=TRUE,...)
as.4seasons.field(x,FUN='mean',...)
as.4seasons.spell(x,FUN=mean,...)
as.seasons(x,start='01-01',end='12-31',FUN='mean', ...)
as.annual(x,...)
as.annual.default(x, ...)
as.annual.numeric(x, ...)
as.annual.integer(x, ...)
as.annual.yearqtr(x, frac = 0, ...)
as.annual.spell(x, ...)
as.annual.station(x, ...)
as.anomaly(x,...)
as.anomaly.default(x,ref=NULL,monthly=NULL,na.rm=TRUE)
as.anomaly.station(x,ref=NULL,monthly=NULL,na.rm=TRUE)
as.anomaly.field(x,ref=NULL,monthly=NULL,na.rm=TRUE)
as.anomaly.zoo(x,ref=NULL,monthly=NULL,na.rm=TRUE)
as.appended(x,...)
as.appended.ds.comb(x,iapp=1)
as.appended.eof.comb(x,iapp=1)
as.appended.field.comb(x,iapp=1)
as.eof(x,...)
as.eof.zoo(x,...)
as.eof.eof(x,iapp=NULL)
as.eof.comb(x,iapp=NULL)
as.eof.field(x,iapp=NULL,...)
as.eof.appendix(x,iapp=1)
as.calibrationdata(x)
as.calibrationdata.ds(x)
as.calibrationdata.station(x)
as.climatology(x,...)
as.comb(x,...)
as.comb.eof(x,...)
as.ds(x)
as.field(x,...)
as.field.zoo(x,lon,lat,param,unit,
longname=NA,quality=NA,src=NA,url=NA,
reference=NA,info=NA,calendar='gregorian',
greenwich=TRUE, method= NA,type=NA,aspect=NA)
as.field.default(x,index,lon,lat,param,unit,
longname=NA,quality=NA,src=NA,url=NA,
reference=NA,info=NA,calendar='gregorian',
greenwich=TRUE, method= NA,type=NA,aspect=NA)
as.field.eof(x,...)
as.field.comb(x,iapp=NULL,...)
as.field.station(x,...)
as.fitted.values(x)
as.fitted.values.ds(x)
as.fitted.values.station(x)
as.monthly(x,fun='mean')
as.observed.station(x)
as.original.data(x)
as.original.data.ds(x)
as.original.data.station(x)
as.pattern(x)
as.pattern.ds(x)
as.pattern.eof(x)
as.pattern.cca(x)
as.pattern.mvr(x)
as.pattern.field(x)
as.pattern.trend(x)
as.pattern.corfield(x)
as.pca(x)
as.pca.ds(x)
as.pca.station(x)
as.residual(x)
as.residual.ds(x)
as.residual.station(x)
as.station(x,...)
as.station.zoo(x,loc=NA,param=NA,unit=NA,lon=NA,lat=NA,alt=NA,
cntr=NA,longname=NA,stid=NA,quality=NA,src=NA,url=NA,
reference=NA,info=NA, method= NA)
as.station.data.frame(x,location=NA,param=NA,unit=NA,lon=NA,lat=NA,alt=NA,
cntr=NA,longname=NA,stid=NA,quality=NA,src=NA,url=NA,
reference=NA,info=NA, method= NA)
as.station.zoo(x,location=NA,param=NA,unit=NA,lon=NA,lat=NA,alt=NA,
cntr=NA,longname=NA,stid=NA,quality=NA,src=NA,url=NA,
reference=NA,info=NA, method= NA,type=NA,aspect=NA)
as.station.list(x)
as.station.ds(x)
as.station.pca(x)
as.station.field(x)
as.station.spell(x)
as.station.eof(x,pattern=1:10)
as.pca.ds(x)
as.pca.station(x)
|
x |
Data object |
location |
define location attribute |
param |
define variable attribute |
unit |
define unit attribute |
lon |
define longitude attribute |
lat |
define latitude attribute |
alt |
define altitude attribute |
cntr |
define country attribute |
longname |
define long-name attribute |
stid |
define station ID attribute |
quality |
define quality attribute |
src |
define source attribute |
url |
define URL attribute |
reference |
define reference attribute |
info |
define info attribute |
method |
define method attribute |
FUN |
function |
na.rm |
TRUE: ignore NA's |
dateindex |
|
monthly |
|
aspect |
|
iapp |
For values greater than 1, select the corresponding
appended field in 'comb' objects (e.g. 1 gives
|
pattern |
Which EOF pattern (mode) to extract as a series for PC |
A field object
R.E. Benestad and A. Mezghanil
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | # Example: how to generate a new station object.
data <- round(matrix(rnorm(20*12),20,12),2); colnames(data) <- month.abb
x <- data.frame(year=1981:2000,data)
X <- as.station.data.frame(x,loc="",param="noise",unit="none")
# Example: how to generate a new field object.
year <- sort(rep(1991:2000,12))
month <- rep(1:12,length(1991:2000))
n <-length(year)
lon <- seq(-30,40,by=5); nx <- length(lon)
lat <- seq(40,70,by=5); ny <- length(lat)
# Time dimension should come first, space second.
y <- matrix(rnorm(nx*ny*n),n,nx*ny)
index <- as.Date(paste(year,month,1,sep="-"))
Y <- as.field(y,index,lon,lat,param="noise",unit="none")
map(Y)
plot(EOF(Y))
data(Oslo)
plot(as.anomaly(Oslo))
data(ferder)
plot(annual(ferder,FUN=min))
plot(annual(ferder,FUN=IQR,na.rm=TRUE))
plot(as.4seasons(ferder))
data(bjornholt)
plot(annual(bjornholt,FUN="exceedance",fun="counts"))
plot(annual(bjornholt,FUN="exceedance",fun="freq"))
plot(annual(bjornholt,FUN="exceedance"))
# Test the as.4seasons function:
data(ferder)
#Daily data:
yd <- ferder
# Monthly data:
ym <- aggregate(ferder,as.yearmon)
ym <- zoo(coredata(ym),as.Date(index(ym)))
ym <- attrcp(ferder,ym)
plot(ym)
#Monthly reanalyses:
t2m <- t2m.ERAINT(lon=c(-30,40),lat=c(50,70))
T2m <- as.4seasons(t2m)
#Extract the grid point with location corresponding to that of the station:
x <- regrid(t2m,is=ferder)
x4s <- as.4seasons(x)
X4s <- regrid(T2m,is=ferder)
y4s1 <- as.4seasons(yd)
y4s2 <- as.4seasons(ym)
plot.zoo(y4s1,lwd=2,xlim=as.Date(c("1980-01-01","2000-01-01")),ylim=c(-10,20))
lines(y4s2,col="red",lty=2)
lines(x4s,col="darkblue",lwd=2)
lines(X4s,col="lightblue",lty=2)
# Select a random season
data(bjornholt)
data(ferder)
plot(as.seasons(ferder,FUN='CDD'))
plot(as.seasons(ferder,start='05-17',end='11-11',FUN='HDD'))
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