split.ppp(spatstat)
split.ppp()所属R语言包：spatstat
Divide Point Pattern into Sub-patterns
分点模式到子模式
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Divides a point pattern into several sub-patterns, according to their marks, or according to any user-specified grouping.
划分成若干子模式的点模式，根据他们的标记，或根据用户指定的任何分组。
用法----------Usage----------
## S3 method for class 'ppp'
split(x, f = marks(x), drop=FALSE, un=NULL, ...)
## S3 replacement method for class 'ppp'
split(x, f = marks(x), drop=FALSE, un=missing(f), ...) <- value
参数----------Arguments----------
参数：x
A two-dimensional point pattern. An object of class "ppp".
一个二维点模式。对象的类"ppp"。
参数：f
Data determining the grouping. Either a factor, a pixel image with factor values, a tessellation, or the name of one of the columns of marks.
分组的数据确定。无论是一个因素，像素的图像与系数的值，镶嵌，或标记的列的名称之一。
参数：drop
Logical. Determines whether empty groups will be deleted.
逻辑。确定是否为空的组将被删除。
参数：un
Logical. Determines whether the resulting subpatterns will be unmarked (i.e. whether marks will be removed from the points in each subpattern).
逻辑。决定是否子模式将标记的（即在每个子模式是否标记将被删除从点）。
参数：...
Other arguments are ignored.
其他参数将被忽略。
参数：value
List of point patterns.
点模式的列表。
Details
详细信息----------Details----------
The function split.ppp divides up the points of the point pattern x into several sub-patterns according to the values of f. The result is a list of point patterns.
函数split.ppp将点的点模式x成若干子模式根据的值f。其结果是一个列表中的点图案。
The argument f may be
的参数f可能是
a factor, of length equal to the number of points in x. The levels of f determine the destination of each point in x. The ith point of x will be placed in the sub-pattern split.ppp(x)$l where l = f[i].
一个因素，长度相等的点的数量在x。 f的水平确定的目的地的每个点的x。 ix个点的子模式将被放置在split.ppp(x)$l其中l = f[i]。
a pixel image (object of class "im") with factor values. The pixel value of f at each point of x will be used as the classifying variable.
像素的图像（类的对象"im"）因子值。的像素值f在每个点x将作为分级的变量。
a tessellation (object of class "tess"). Each point of x will be classified according to the tile of the tessellation into which it falls.
镶嵌（类的对象"tess"）。每个点的x将根据它下降到镶嵌瓷砖的分类。
a character string, matching the name of one of the columns of marks, if marks(x) is a data frame. This column should be a factor.
一个字符串，匹配的列标记的名称之一，如果marks(x)是一个数据框。此栏应是一个重要因素。
If f is missing, then it will be determined by the marks of the point pattern. The pattern x can be either
f如果丢失，然后将确定的点模式的标志。的模式x可以是
a multitype point pattern (a marked point pattern whose marks vector is a factor). Then f is taken to be the marks vector. The effect is that the points of each type are separated into different point patterns.
一个多类型的点图案（标记点图案，其标记矢量是一个因素）。然后f的标志矢量。其效果是，每种类型的点被分离成不同的点图案。
a marked point pattern with a data frame of marks, containing at least one column that is a factor. The first such column will be used to determine the splitting factor f.
显着的点图案与一个数据框的标记，包含至少一列，这是一个因素。第一个这样的列将被用来确定分裂因子f。
Some of the sub-patterns created by the split may be empty. If drop=TRUE, then empty sub-patterns will be deleted from the list. If drop=FALSE then they are retained.
某些由分割创建的子模式可能是空的。如果drop=TRUE，然后空的子模式将被从列表中删除。如果drop=FALSE“然后他们被保留。
The argument un determines how to handle marks in the case where x is a marked point pattern. If un=TRUE then the marks of the points will be discarded when they are split into groups, while if un=FALSE then the marks will be retained.
参数un决定如何处理的情况下标记，其中x是一个显着的点模式。如果un=TRUE那么的点的标记将被丢弃时，他们分成不同的小组，而如果un=FALSE那么该商标将被保留。
If f and un are both missing, then the default is un=TRUE for multitype point patterns and un=FALSE for marked point patterns with a data frame of marks.
如果f和un都失踪，那么默认的是un=TRUE下的多点模式和un=FALSE一个数据框标记的标记点模式。
The result of split.ppp has class "splitppp" and can be plotted using plot.splitppp.
split.ppp类"splitppp"可以绘制使用plot.splitppp。
The assignment function split<-.ppp updates the point pattern x so that it satisfies split(x, f, drop, un) = value. The argument value is expected to be a list of point patterns, one for each level of f. These point patterns are expected to be compatible with the type of data in the original pattern x.
分配功能split<-.ppp更新点模式x，所以它满足split(x, f, drop, un) = value的。的参数value预计将列表中的点模式，每个级别的f。预期这些点图案是兼容的数据类型中的原始图案x。
Splitting can also be undone by the function superimpose.
也可以分割百废待兴的功能superimpose。
值----------Value----------
The value of split.ppp is a list of point patterns. The components of the list are named by the levels of f. The list also has the class "splitppp".
split.ppp点模式的列表。组件列表中被命名为水平f。该列表也有类"splitppp"。
The assignment form split<-.ppp returns the updated point pattern x.
分配形式split<-.ppp返回更新后的点模式x。
（作者）----------Author(s)----------
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
and Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参见----------See Also----------
cut.ppp, plot.splitppp, superimpose, im, tess, ppp.object
cut.ppp，plot.splitppp，superimpose，im，tess，ppp.object
实例----------Examples----------
# (1) Splitting by marks[（1）分离标记]
# Multitype point pattern: separate into types[多类型的点模式：单独分为不同的类型]
data(amacrine)
u <- split(amacrine)
# plot them[绘制出来]
plot(split(amacrine))
# the following are equivalent:[以下是等效的：]
amon <- split(amacrine)$on
amon <- unmark(amacrine[amacrine$marks == "on"])
# the following are equivalent:[以下是等效的：]
amon <- split(amacrine, un=FALSE)$on
amon <- amacrine[amacrine$marks == "on"]
# Scramble the locations of the 'on' cells[加扰的位置的“on”的单元]
u <- split(amacrine)
u$on <- runifpoint(amon$n, amon$window)
split(amacrine) <- u
# Point pattern with continuous marks[连续标记的点模式]
data(longleaf)
# cut the range of tree diameters into three intervals[削减范围内的树直径分为三个区间]
# using cut.ppp[使用cut.ppp]
long3 <- cut(longleaf, breaks=3)
# now split them[现在将它们分割]
long3split <- split(long3)
# (2) Splitting by a factor[（2）的一个因素的劈裂]
# Unmarked point pattern[未标记的点模式]
data(swedishpines)
# cut & split according to nearest neighbour distance[根据最近邻距离剪切和分割]
f <- cut(nndist(swedishpines), 3)
u <- split(swedishpines, f)
# (3) Splitting over a tessellation[（3）分割的一个Tessellation（曲面细分）]
tes <- tess(xgrid=seq(0,96,length=5),ygrid=seq(0,100,length=5))
v <- split(swedishpines, tes)
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。
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发表于 2012-9-30 14:15:40
