IS(verification)
IS()所属R语言包：verification
Alternative Intensity Scale Function
替代烈度表功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Beta version of intensity scale function created by
所创造的强度等级功能的Beta版
用法----------Usage----------
IS(frcs, obs, thres)
参数----------Arguments----------
参数：frcs
Forecast matrix. Must be of $2^n$ dimensions.
预测矩阵。必须是$ 2 ^ n $的尺寸。
参数：obs
Observation matrix. Must be of $2^n$ dimensions.
观察矩阵。必须是$ 2 ^ n $的尺寸。
参数：thres
A vector of thresholds to be considered. By default, the percentiles 0, 90 are used.
要考虑的矢量阈值。默认情况下，使用的百分0，90。
值----------Value----------
SSul = SSul, MSEul = MSEul, l.frcs = dim(frcs)[1], thres = thres, Bias = Bu, BR = BRu
SSul = SSul，MSEul = MSEul，l.frcs = DIM（FRCS）[1]，THRES = THRES，BIAS =卜，BR = BRU
参数：SSul
Skill score as matrix. The rownames are the thresholds, the colnames are $n$ where $2^n$ is the spatial scale of the skill score decomposition.
矩阵的技巧得分。行名的阈值，列名是$ N $ $ 2 ^ n $是空间尺度的技巧得分分解。
参数：MSEul
A matrix with the mean squared error of the forecast
A矩阵的平均平方误差的预测
参数：l.frcs
Number of rows in forecast. Used in plotting routine.
行的预测数。在绘图程序。
参数：thres
Thresholds used in model
阈值模型
参数：Bias
Bias
偏见
参数：BR
BR
BR
注意----------Note----------
THIS IS A DRAFT FORM OF THIS FUNCTION. IT MAY CHANGE AND REPLACE int.scale.verify
这是一个草案FORM此功能。它可能会改变，更换int.scale.verify
（作者）----------Author(s)----------
Barbara Casati <barbara.casati@ec.gc.ca>
参考文献----------References----------
the verification of spatial precipitation forecasts, Meteorol. Appl, vol 11, 141-154 pp.
参见----------See Also----------
int.scale.verify and plot.int.scale
int.scale.verify和plot.int.scale
实例----------Examples----------
#####################################################[＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃ ＃＃]
# files.dat: read, create and write[files.dat：阅读，创建和写]
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IS.NIMROD.case <- IS(forecast.dat, analysis.dat,c(0, 2^seq(-5,6)))
NIMROD.SSul <- IS.NIMROD.case$SSul
colnames(NIMROD.SSul) <- paste(c("0","1/32", "1/16", "1/8", "1/4", "1/2", "1",
"2","4", "8", "16", "32", "64"),"mm/h")
rownames(NIMROD.SSul) <- paste(5*2^seq(0,8),"km")
# write.table(NIMROD.SSul,file="NIMROD.SSul.dat")[write.table（NIMROD.SSul，文件=“NIMROD.SSul.dat”的）]
NIMROD.MSEul <- IS.NIMROD.case$MSEul
colnames(NIMROD.MSEul) <- paste(c("0","1/32", "1/16", "1/8", "1/4", "1/2", "1",
"2","4", "8", "16", "32", "64"),"mm/h")
rownames(NIMROD.MSEul) <- paste(5*2^seq(0,8),"km")
###################################################[＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃]
# colorbars for the images[colorbars为图像]
###################################################[＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃＃]
Nimrod.colorbar <- function(){
colors = c(0,8,8,8,8,5,5,4,4,4,2,2,2)
xlimbar = c(7,8)
ylimbar = c(46.5,59.5)
barlabels = c("0","1/32", "1/16", "1/8", "1/4", "1/2", "1", "2", "4", "8", "16",
"32", "64","128")
ycoord = seq(ylimbar[1],ylimbar[2],length=length(colors)+1)
for(i in seq(1,length(colors))){
polygon(x=c(xlimbar[1],xlimbar[1],xlimbar[2],xlimbar[2],xlimbar[1]),
y=c(ycoord[i],ycoord[i+1],ycoord[i+1],ycoord[i],ycoord[i]),
col = colors[i])}
axis(4,at=ycoord,labels=barlabels,las=TRUE)
mtext("mm/h",line=1,at=c(7.5,61),cex=1.5)
}
colorbar <- function(xlimbar,ylimbar,colors,barlabels){
ycoord = seq(ylimbar[1],ylimbar[2],length=(length(colors)+1))
for(i in seq(1,length(colors))){
polygon(x=c(xlimbar[1],xlimbar[1],xlimbar[2],xlimbar[2],xlimbar[1]),
y=c(ycoord[i],ycoord[i+1],ycoord[i+1],ycoord[i],ycoord[i]),
col = colors[i])}
axis(4,at=ycoord,labels=barlabels,las=TRUE)
}
# images[图像]
#[]
par(oma=c(3,3,3,3), mfrow = c(1,1) )
image(seq(-12,8,length=256), seq(46.5,59.5,length=256), analysis.dat,
xlim = c(-12,8), ylim = c(46.5,59.5), zlim = c(0,128),
xlab = "longitude", ylab = "latitude",main="Nimrod analysis 29/05/99 15:00",
col=c(0,8,8,8,8,5,5,4,4,4,2,2,2),breaks=c(0,2^seq(-5,7,1)))
world(xlim=c(-12,8),ylim=c(46.5,59.5), add = TRUE, lwd = 3)
Nimrod.colorbar()
#[]
par(oma=c(3,3,3,3))
image(seq(-12,8,length=256), seq(46.5,59.5,length=256), forecast.dat,
xlim = c(-12,8), ylim = c(46.5,59.5), zlim = c(0,128),
xlab = "longitude", ylab = "latitude",main="Nimrod forecast T+3h",
col=c(0,8,8,8,8,5,5,4,4,4,2,2,2),breaks=c(0,2^seq(-5,7,1)))
world(xlim=c(-12,8),ylim=c(46.5,59.5), add = TRUE, lwd = 3)
Nimrod.colorbar()
#[]
par(oma=c(3,3,3,3))
image(seq(-6,6,1),seq(1,9),t(NIMROD.SSul),xlim=c(-6.5,8.5),zlim=c(-4,1),
xlab="threshold (mm/h)",ylab="scale (km)",axes=FALSE,
main="Intensity-Scale Skill Score", col=c(4,4,4,4,5,5,5,5,7,7))
axis(1,at = seq(-6,6,1), labels = c("0","1/32", "1/16", "1/8", "1/4", "1/2",
"1", "2","4", "8", "16", "32", "64"))
axis(2,at = seq(1,9),labels=5*2^seq(0,8,1))
rect(xleft=-6.5, ybottom=0.5, xright=6.5, ytop=9.5)
colorbar(xlimbar=c(7.5,8.5),ylimbar=c(0.5,9.5),colors=c(4,4,4,4,5,5,5,5,7,7),barlabels=seq(-4,1,0.5))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:21:56
