kmeansFilter-class(flowCore)
kmeansFilter-class()所属R语言包：flowCore
Class "kmeansFilter"
类“kmeansFilter”
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A filter that performs one-dimensional k-means (Lloyd-Max) clustering
一个过滤器，执行一维的k-means聚类（劳埃德 - 马克斯）
用法----------Usage----------
kmeansFilter(..., filterId="defaultKmeansFilter")
参数----------Arguments----------
参数：...
kmeansFilter are defined by a single flow parameter and an associated list of k population names. They can be given as a character vector via a named argument, or as a list with a single named argument. In both cases the name will be used as the flow parameter and the content of the list or of the argument will be used as population names, after coercing to character. For example kmeansFilter(FSC=c("a", "b", "c")) or kmeansFilter(list(SSC=1:3)) If the parameter is not fully realized, but instead is the result of a transformation operation, two arguments need to be passed to the constructor: the first one being the transform object and the second being a vector of population names which can be coerced to a character. For example kmeansFilter(tf, c("D", "E"))
kmeansFilter是指由一个单一的流动参数和k人口名称列表。他们可以通过命名参数作为特征向量，或作为一个单一的命名参数列表。在这两种情况下，该名称将用作流动参数和强迫字符后，将被用来作为人口名称列表或内容的说法。例如kmeansFilter(FSC=c("a", "b", "c"))或kmeansFilter(list(SSC=1:3))如果该参数没有完全实现，而是是一个transformation操作的结果，两个参数需要传递给构造函数：第一个是transform对象，第二个向量的人口可以强制转换为一个字符的名称。例如kmeansFilter(tf, c("D", "E"))的
参数：filterId
An optional parameter that sets the filterId of the object. The filter can later be identified by this name.
可选参数设置filterId对象的。该过滤器可以在以后确定了这个名字。
Details
详情----------Details----------
The one-dimensional k-means filter is a multiple population filter capable of operating on a single flow parameter. It takes a parameter argument associated with two or more populations and results in the generation of an object of class multipleFilterResult. Populations are considered to be ordered such that the population with the smallest mean intensity will be the first population in the list and the population with the highest mean intensity will be the last population listed.
一个三维k手段过滤器是一个多人口的过滤器能够在一个单一的流参数运行。它需要两个或两个以上的人口和结果生成一个对象类multipleFilterResult相关参数参数。人群被视为责令等，最小的平均强度的人口将在列表与人口的平均强度最高的人口将是最后列出的人口。
值----------Value----------
Returns a kmeansFilter object for use in filtering flowFrames or other flow cytometry objects.
返回用于过滤kmeansFilter或其他流式单元仪检测对象的flowFrames对象。
延伸----------Extends----------
Class parameterFilter, directly.
类parameterFilter，直接。
Class concreteFilter, by class parameterFilter, distance 2.
类concreteFilter类parameterFilter，距离2。
Class filter, by class parameterFilter, distance3.
类filter类parameterFilter，distance3。
插槽----------Slots----------
populations: Object of class character. The names of the k populations (or clusters) that will be created by the kmeansFilter. These names will later be used for the respective subpopulations in split
populations类character的对象。 k人口（或聚类）的名称，将创建由kmeansFilter。这些名称，稍后将用于split各自的亚
parameters: Object of class parameters, defining a single parameter for which the data in the flowFrame is to be clustered. This may also
parameters：Object类的parameters，定义一个参数为在flowFrame数据是要聚集。这也可能
filterId: Object of class character, an identifier or name to reference the kmeansFilter object
filterId：Object类的character，标识符或名称来引用kmeansFilter对象
类的对象----------Objects from the Class----------
Like all other filter objects in flowCore, kmeansFilter objects should be instantiated through their constructor kmeansFilter(). See the Usage section for details.
象所有其他filter对象flowCore，kmeansFilter对象，应通过其构造kmeansFilter()实例。见Usage细节部分。
方法----------Methods----------
%in% signature(x = "flowFrame", table = "kmeansFilter"): The workhorse used to evaluate the filter on data.
在％signature(x = "flowFrame", table = "kmeansFilter")：主力用来评估对数据的过滤器。
Usage:
用法：
This is usually not called directly by the user, but internally by
这通常不是直接调用的用户，但内部
show signature(object = "kmeansFilter"): Print information about the filter.
显示signature(object = "kmeansFilter")：打印有关过滤器的信息。
Usage:
用法：
The method is called automatically whenever the object is printed
每当打印对象的方法被称为自动
注意----------Note----------
See the documentation in the flowViz package for plotting of kmeansFilters.
看到图flowVizkmeansFilters包的文档。
作者（S）----------Author(s)----------
F. Hahne, B. Ellis, N. LeMeur
参见----------See Also----------
flowFrame, flowSet, filter for evaluation of kmeansFilters and split for splitting of flow cytometry data sets based on the result of the filtering operation.
flowFrame，flowSet，filter评价kmeansFilters和split流式单元仪的基础上，过滤操作的结果数据集的分裂。
举例----------Examples----------
## Loading example data[＃载入数据为例]
dat <- read.FCS(system.file("extdata","0877408774.B08",
package="flowCore"))
## Create the filter[＃创建过滤器]
kf <- kmeansFilter("FSC-H"=c("Pop1","Pop2","Pop3"), filterId="myKmFilter")
## Filtering using kmeansFilters[＃过滤使用kmeansFilters]
fres <- filter(dat, kf)
fres
summary(fres)
names(fres)
## The result of quadGate filtering are multiple sub-populations[＃quadGate过滤的结果是多个子种群]
## and we can split our data set accordingly[＃我们可以分裂我们的数据进行相应的设置]
split(dat, fres)
## We can limit the splitting to one or several sub-populations[＃我们可以限制一个或几个子群体的分裂]
split(dat, fres, population="Pop1")
split(dat, fres, population=list(keep=c("Pop1","Pop2")))
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 2012-2-25 17:44:47
