R语言 flowViz包 gpoints-methods()函数中文帮助文档(中英文对照)

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gpoints-methods(flowViz)
gpoints-methods()所属R语言包：flowViz

                                         Adding points within a gate to a plot
                                         内门点添加图

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

These methods extend the basic graphics points methods for drawing of points contained within a filter. They allow for multiple dispatch, since not all filter types need to be evaluated for plotting, but this decision should be made internally. In any case, we need the raw data in the form of a
这些方法延长points内包含的点绘制的基本图形filter方法。它们允许多个调度，因为并不是所有的filter类型需要进行评估的图，但这一决定应在内部。在任何情况下，我们需要在原始数据的一种形式


Details

详情----------Details----------

When plotting flowFrames using the plot method provided by flowViz, the plotted parameters are recorded, which makes it possible to correctly overlay the points within filters assuming that they are defined for the respective parameters. Warnings and error will be
当图flowFrameSplot方法提供flowViz，绘制参数都记录下来，这使得有可能正确地叠加在filter的假设它们点定义为相应的参数。警告和错误


方法----------Methods----------

General method for all objects inheriting from filter. This is used as the default when no more explicit method is found. It tries to find the plotted parameters from the internal flowViz.state environment. This only works if the flow data has been plotted using the plot methods provided by this flowViz
为所有filter继承对象的一般方法。这是作为默认时，发现没有更明确的方法。它试图找到从内部flowViz.state环境绘制的参数。这只有当流量数据已绘制使用这plotflowViz方法




x = "filter", data = "missing", channels = "ANY"  This gives
=“过滤器”，数据“失踪”，渠道=“ANY”，这使

"character"</dt>  We can get all the information about a filter from its filterResult without the need to
“字符”</ DT>我们可以得到，而不需要filterfilterResult从所有有关信息




x = "curv1Filter", data = "ANY"  We either need a filterResult or the raw data as a flowFrame for
X =“curv1Filter”数据=“任何”我们需要一个filterResultflowFrame或原始数据




x = "curv1Filter", data = "flowFrame"  see above
X =“curv1Filter”，数据=的“flowFrame”见上面




x = "curv1Filter", data = "missing"  see above
=“curv1Filter”，数据“失踪”见上面




x = "curv1Filter", data = "multipleFilterResult"  see above
X =“curv1Filter”，数据=的“multipleFilterResult”见上面




x = "curv2Filter", data = "ANY"  We either need a filterResult or the raw data as a flowFrame for
X =“curv2Filter”数据=“任何”我们需要一个filterResultflowFrame或原始数据

"character"</dt>  We evaluate the filter on the flowFrame and plot the subset of selected points. By default, every subpopulation (if there are
“字符”</ DT>评估filter和图选定点的子集的flowFrame。默认情况下，每一个亚群（如果有

see above
见上文

"character"</dt>  see above
“字符”</ DT>见上面

"character"</dt>  see above
“字符”</ DT>见上面

"character"</dt>  see above
“字符”</ DT>见上面

see above
见上文

"character"</dt>  see above
“字符”</ DT>见上面


作者（S）----------Author(s)----------


F. Hahne



参见----------See Also----------

filter, flowFrame,  glines, gpolygon
filter，flowFrame，glines，gpolygon

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


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