saller(SpatialVx)
saller()所属R语言包：SpatialVx
Functions to analyze features in a field (image)
功能分析功能，在一个领域（图片）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Functions to analyze features in a field (image) in conjunction, e.g., with the FeatureSuite function.
在一个领域分析的特征（图片）的功能结合，例如，的FeatureSuite功能。
用法----------Usage----------
saller(x, object, y = NULL, matches = NULL, d = NULL)
参数----------Arguments----------
参数：x
For saller x is a list object returned by convthresh or other feature identification function that returns a list with components X.feats, Y.feats (themselves lists with owin class objects defining separate features in the verification and forecast fields, resp.), and X.labeled, Y.labeled (fields with the numbers from 0 to the number of features also defining the separate feature locations (e.g., as returned by the connected function of package spatstat.
对于sallerx是convthresh或其他特征识别功能，它返回一个列表的组件返回一个列表对象X.feats，Y.feats（自己列出owin类的对象的核查和预报场分别定义不同的功能），以及X.labeled，Y.labeled（领域的数字从0到功能的数量也定义了不同的功能位置（例如，返回connected包spatstat函数。
参数：object
A list object of class "FeatureSuitePrep" as returned by FeatureSuitePrep providing information about the original fields.
FeatureSuitePrep提供信息的原始字段返回一个列表对象的类“FeatureSuitePrep”。
参数：y
(optional) if not NULL, it is used instead of x, and otherwise has the same stucture thereof. When used with FeatureSuite, one might want to merge objects in one or both fields before calling the analysis function. If so, y is the means by which FeatureSuite can ensure that this happens.
（可选）如果不为NULL，它是用来代替x，和其他有相同的金盏。当使用FeatureSuite，可能要在一个或两个领域的合并对象，然后再调用的分析功能。如果是这样，y是手段，FeatureSuite可以确保这种情况的发生。
参数：matches
Not used by saller function. If matching of features between fields is required, this will be a two-column matrix describing which features from the forecast (first column) match to those of the verificaiton field (second column).
不使用saller功能。如果匹配字段之间的功能是必需的，这将是一个两列的矩阵描述的功能与预测（第一列）匹配的verificaiton场（第二列）。
参数：d
(optional) the SAL (saller) method requires division by the longest distance between two border points. If NULL, this is taken to be simply the length of the longest side.
（可选）SAL（saller）方法需要两个边界点之间的距离最长的部门。如果为NULL，这是简单的最长边的长度。
Details
详细信息----------Details----------
saller: Computes S, A, and L of the SAL method introduced by Wernli et al. (2008).
saller计算S，A和L SAL万恩利等人介绍的方法。 （2008年）。
值----------Value----------
saller returns a list with components:
saller返回一个列表的组件：
参数：A
numeric giving the amplitude component.
数值给振幅成分。
参数：L
numeric giving the lcoation component.
数字给lcoation组件。
参数：S
numeric giving the structure component.
数字的结构组件。
注意----------Note----------
There are several ways to identify features, and some are provided by this package, but only a few. For example, the method for identifying features in the SAL method as introduced by Wernli et al. (2008) utilizes information from a contour field of a particular variable, and is therefore not currently included in this package. Users are encouraged to write their own such functions, and should feel free to contribute them to this package by contacing the maintainer.
有几种方法来识别功能，和一些由该软件包中所提供的，但只有少数。例如，该方法用于识别在SAL的方法的功能，如由万恩利等引入。 （2008）利用信息领域的一个特定的变量的轮廓，因此，目前不包括在此程序包。我们鼓励用户写自己的等功能，并应随时贡献给这个包contacing的维护者。
The SAL method typically looks at a small domain, and it is up to the user to set this up before calling these functions, as they are not designed to handle such a situation.
SAL方法通常看起来在一个小领域，它是由用户设置此之前调用这些函数，因为它们不是设计来处理这种情况。
（作者）----------Author(s)----------
Eric Gilleland
参考文献----------References----------
参见----------See Also----------
FeatureSuite, centroid.owin, connected, tiles, tess, deltamm
FeatureSuite，centroid.owin，connected，tiles，tess，deltamm
实例----------Examples----------
grid<- list( x= seq( 0,5,,100), y= seq(0,5,,100))
obj <- stationary.image.cov( grid=grid, V=cbind(c(0.25,0.15),c(0.45,0.75)), setup=TRUE)
look<- sim.rf(obj)
look2 <- sim.rf(obj)
look[look<0] <- 0
look2[look2<0] <- 0
q <- mean( c(c(look[look>0]),c(look2[look2>0])), na.rm=TRUE)
hold <- FeatureSuitePrep("look2", "look")
hold2 <- convthresh(hold, smoothpar=5, thresh=q)
if(!is.null(hold2$X.feats) & !is.null(hold2$Y.feats)) {
N <- max(c(length(hold2$X.feats), length(hold2$Y.feats)), na.rm=TRUE)
par(mfrow=c(1,2))
image.plot(hold2$X.labeled, col=c("grey", rainbow(N)), zlim=c(0,N))
image.plot(hold2$Y.labeled, col=c("grey", rainbow(N)), zlim=c(0,N))
saller(hold2, hold)
} # else try a lower threshold.[其他尝试阈值较低。]
## Not run: [＃不运行：]
data(pert000)
data(pert004)
hold <- FeatureSuitePrep("pert004", "pert000")
look <- convthresh( hold, smoothpar=10.5)
par( mfrow=c(1,2))
zl <- range(c(c(look$X.labeled),c(look$Y.labeled)),finite=TRUE)
image.plot(look$X.labeled, zlim=zl)
image.plot(look$Y.labeled, zlim=zl)
look2 <- deltamm( look, verbose=TRUE)
image.plot(look2$X.labeled)
image.plot(look2$Y.labeled)
## End(Not run)[＃（不执行）]
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。
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发表于 2012-9-30 12:58:11
