我有一个数百万有向线段的数据集。线段是连续的-这是一个气候变量（显热），每半小时就有观察和模拟的值。我正在尝试寻找模拟执行方式的模式。我正在查看obs与仿真值的散点图，并将它们与线段链接（箭头表示时间方向）。如果我绘制它们，我将得到一个无法解释的模糊混乱，就像这样：
这是10000行的子集，绘制得很好并且具有低不透明度：
ggplot(d, aes(x=Qh_obs, xend=lead(Qh_obs), y=Qh_sim, yend=lead(Qh_sim))) +
geom_segment(size=0.1, alpha=0.2, arrow=arrow(length=unit(2, units='mm')))
dput() 前700行数据（受发布长度限制）：
structure(
list(
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),
.Names = c( "Qh_sim", "Qh_obs"),
row.names = c( NA, -700L),
class = c( "data.table", "data.frame"),
.internal.selfref = <pointer: 0x66d468>
)
我有兴趣尝试直观地总结这些行的流程。是否有汇总这些信息的常用方法？我可以做一个矢量场图，但我想我会丢失一些相关信息-特别是某些较密集的区域可能具有多组线段。我正在考虑对这些片段进行聚类（使用四个变量作为特征），然后绘制平均值，或者绘制风向矢矢量场，但是我想看看是否有更好的方法。
1
如果以代表方向的颜色绘制它们，会看到图案吗？让我想到的是，当发生强烈暴风雨时，我已经在电视上看到雷达图像，其颜色是基于风向的，通过寻找颜色突然变化的地方可以发现龙卷风。
—
罗斯·伦斯
好主意啊。我完全忘记了使用其他视觉变量。我想我也许也可以用线宽指示群集中的元素数量。
—
naught101
我能想到的另一件事是某种类型的动态或动画情节，其滑块可在时间上选择一个狭窄的窗口，但可以平滑移动，以便您可以看到事物的变化。
—
罗斯·伦斯
是的，这也值得尝试，但是我主要是在这里查看一个每日周期，数据以30分钟为间隔，并且是3到7年，因此虽然可行，但可能很难处理。
—
naught101
您写有段，但实际上在图中似乎有分段线性轨迹（即段都端到端连接）？是这样吗？如果是，您可能需要将其编辑为问题，因为它可能会影响可能的答案（很遗憾，我对此一无所知）。
—
Stephan Kolassa 2014年