venneuler(venneuler)
venneuler()所属R语言包：venneuler
Calculates Venn and Euler Diagram
计算维恩和欧拉图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
venneuler calculates a Venn diagram from a set specification.
venneuler计算从一组规范的维恩图。
用法----------Usage----------
venneuler(combinations, weights, ...)
参数----------Arguments----------
参数：combinations
This can be one of:
这可以是如下之一：
a character vector (specifies disjoint class combinations as class names separated by the ampersand & character – e.g. c("A","B","A&B"))
字符向量（指定不相交的类组合类“与”&字符分隔的名称 - 例如c("A","B","A&B")）
a named numeric vector (names specify class combinations and values specify weights – e.g. c(A=1, B=2, `A&B`=0.5))
一个名为“数字矢量（名称指定类的组合和值指定砝码 - 例如c(A=1, B=2, A&B=0.5)）
a character matrix of two columns (specifies mapping of elements to sets – elements in the first column and set names in the second column, weights argument is ignored)
两列（在第二列中的第一列和集名称的集 - 元素指定的元素映射到一个字符矩阵，weights参数被忽略）
a logical or numeric matrix whose columns represent sets and co-occurrence is defined by non-zero (rep. TRUE) values in rows (weight for a row being 1 for logical matrices or the row sum for numeric matrices).
一个逻辑或数字的矩阵，它的列代表集和共生非零定义（REP.TRUE）行中的值（权重为1的逻辑矩阵或为数值的矩阵的行和一排）。
For convenience data frames can be passed instead of matrices and they will be coerced using as.matrix().
方便的数据框可以通过，而不是矩阵，他们将被强迫使用as.matrix()。
参数：weights
If combinations is a character vector then this argument specifies the associated weights. It is ignored in all other cases.
如果combinations是一个字符向量，则此参数指定相关权重。在所有其他情况下，它会被忽略。
参数：...
Additional arguments (currently unused).
额外的参数（当前未使用）。
值----------Value----------
An object of the class VennDiagram with following components: <table summary="R valueblock"> <tr valign="top"><td>centers</td> <td> centers of the circles (columns are x and y coordinates)</td></tr> <tr valign="top"><td>diameters</td> <td> diameters of the circles</td></tr> <tr valign="top"><td>colors</td> <td> colors of the circles as values between 0 and 1</td></tr> <tr valign="top"><td>labels</td> <td> labels of the circles</td></tr> <tr valign="top"><td>residuals</td> <td> residuals (percentage difference between input intersection area and fitted intersection area)</td></tr> <tr valign="top"><td>stress</td> <td> stress value for solution</td></tr> <tr valign="top"><td>stress01</td> <td> .01 critical value for stress based on random data</td></tr> <tr valign="top"><td>stress05</td> <td> .05 critical value for stress based on random data</td></tr> </table>
对象的类VennDiagram以下组件：<table summary="R valueblock"> <tr valign="top"> <TD>centers </ TD> <TD>中心的圈子（列是x和y坐标）</ TD> </ TR> <tr valign="top"> <TD>diameters </ TD> <TD>直径的各界</ TD> </ TR> <tr valign="top"> <TD>colors </ TD> <TD>颜色的圆圈为0和1之间的值</ TD> </ TR> <tr valign="top"> <TD>labels </ TD> <TD>标签的圈子</ TD> </ TR> <tr valign="top"> <TD>residuals </ TD> <TD>残差（输入交汇区，并配备交汇区之间的百分比差额）</ TD> </ TR> <tr valign="top"> <TD> stress </ TD> < TD>应力值的解决方案</ TD> </ TR> <tr valign="top"> <TD>stress01 </ TD> <TD> 0.01的临界值压力的基础上随机数据</ TD > </ TR> <tr valign="top"> <TD> stress05 </ TD> <TD> 0.05的临界值压力的基础上随机数据</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Lee Wilkinson <leland.wilkinson@gmail.com>, R package: Simon Urbanek <simon.urbanek@r-project.org>
实例----------Examples----------
vd <- venneuler(c(A=0.3, B=0.3, C=1.1, "A&B"=0.1, "A&C"=0.2, "B&C"=0.1 ,"A&B&C"=0.1))
plot(vd)
# same as c(A=1, `A&B&C`=1, C=1)[相同的C（A = 1，A＆B＆C= 1，C = 1）]
m <- data.frame(elements=c("1","2","2","2","3"), sets=c("A","A","B","C","C"))
v <- venneuler(m)
plot(v)
m <- as.matrix(data.frame(A=c(1.5, 0.2, 0.4, 0, 0),
B=c(0 , 0.2, 0 , 1, 0),
C=c(0 , 0 , 0.3, 0, 1)))
# without weights[没有重量]
v <- venneuler(m > 0)
plot(v)
# with weights[配重块]
v <- venneuler(m)
plot(v)
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 15:20:33
