R语言 simone包 plot.simone()函数中文帮助文档(中英文对照)

loveR

plot.simone(simone)
plot.simone()所属R语言包：simone

                                        Graphical representation of SIMoNe outputs
                                         西蒙妮输出的图形表示法。

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Plots various outputs associated to a SIMoNe run.
图相关的各种输出到西蒙娜运行。


用法----------Usage----------


## S3 method for class 'simone'
plot(x,
     output    = c("BIC", "AIC", "ROC", "PR", "path.edges",
                   "path.penalty", "sequence"),
     ref.graph = NULL,
     ask       = TRUE,  ...)



参数----------Arguments----------

参数：x
output of a simone run (must be an object of class simone)
输出的simone的run（必须是一个类的对象simone）


参数：output
a vector of character string indicating which outputs must be plotted (picken from "BIC", "AIC", "ROC", "PR", "path.edges", "path.penalty" or "sequence"). Default is to plot everything possible.
一个向量的字符串表示的输出必须绘制（皮肯"BIC"，"AIC"，"ROC"，"PR"，"path.edges"，"path.penalty"或"sequence"“）。默认是绘制千方百计。


参数：ref.graph
a network of reference provided through an adjacency matrix that is used to compute the ROC and PR curves. Only required if "ROC" and "PR" belongs to the output argument.
网络提供的参考是用于计算的ROC和PR曲线通过邻接矩阵。唯一需要的，如果"ROC"和"PR"属于output参数。


参数：ask
a logical indicating if the graphics device should be interactive. Default is TRUE.
一个逻辑说明应该是互动式的图形设备。默认是TRUE。


参数：...
Additonal arguments for generic plot (such as main = "my     title").
通用plot（如main = "my     title"）产生额外的参数。


Details

详细信息----------Details----------

Here are some details about the plots possibly produced:
这里的图可能产生的一些细节：




If "BIC" belongs to the output argument, a plot representing the Bayesian Information Criterion as a function of each network inferred by simone is displayed.
"BIC"如果属于output的说法，图贝叶斯信息标准的函数推断simone显示每个网络。




If "AIC" belongs to the output argument, a ploy representing the Akaike Information Criterion as a function of each network inferred by simone is displayed.
"AIC"如果属于output的说法，代表赤池信息准则的函数推断simone显示每个网络的伎俩。




If "ROC" belongs to the output argument and ref.graph is specified, the ROC curve (Receiver Operating Characteristic) is plotted by representing true positive rate vs. false positive rate.
"ROC"如果属于output参数和ref.graph指定的代表真阳性率和假阳性率，绘制ROC曲线（受试者工作特征）。




If "PR" belongs to the output argument and ref.graph is provided by the user, the PR curve (Precision/Recall) is plotted by representing positive predicted values vs. true positive rate.
"PR"如果属于output参数和ref.graph是由用户提供的，绘制的的PR曲线（精度/召回）代表阳性预测值与真阳性率。




If "path.penalty" belongs to the output argument, a regularization path is plotted by representing the value of each entry of the Theta matrix (that is, of each edge) vs. the penalty level lambda: there are as many values for the penalty as networks stocked in the simone object x.
"path.penalty"如果属于output参数，绘制的正则路径Theta矩阵（即，每边）与罚款额，每个条目的值lambda：有许多值的刑罚如放养在网络simone对象x。




If "path.edges" belongs to the output argument, a regularization path is plotted by representing the value of each entry of the Theta matrix (that is, of each edge) vs. the degree of freedom in Theta (that is, the number of edges in the current network). This is done for all the network stocked in the simone object x.
如果"path.edges"属于output参数，正规化路径绘制代表Theta矩阵（即，每个边缘）的每个条目的值对比的自由度的在Theta（即，在当前的网络）的边的数目。这样做是为了所有的网络摆放在simone对象x。




If "sequence" belongs to the output argument, an interactive plot is provided by starting from the empty network and adding the edges by successively covering the networks stocked in the simone object x.      
如果"sequence"属于output参数，提供一个互动的图从空网络和添加的边缘，先后储备丰富的在simone对象x中的网络。





注意----------Note----------

If the user asked for "PR" and "ROC" curves yet did not specify a network of reference, these curves will not be plotted (no warning or error will be specified).
如果用户要求"PR"和"ROC"曲线还没有指定一个网络范围，不会被绘制这些曲线（将指定的任何警告或错误）。


（作者）----------Author(s)----------


J. Chiquet



参见----------See Also----------

simone.
simone。


实例----------Examples----------


## data set and network generation[＃数据集和网络生成]
g    <- rNetwork(p=50, pi=50)
data <- rTranscriptData(300,g)
attach(data)

## running simone[＃运行西蒙娜]
res <- simone(X, type="steady-state")

## plotting the results: just the ROC curve[＃策划的结果：ROC曲线]
plot(res, output=c("ROC"), ref.graph=g$A)

## plotting the results: just the path as a function of the penalty[＃策划的结果：路径的函数的罚款]
plot(res, output=c("path.penalty"), main="I want to put my own title")

## plotting the results: everything possible (the default)[＃策划的结果：一切可能的（默认）]
plot(res)

detach(data)

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。