Visually summarising a mess of directed line segments

I have a data set of millions of directed line segments. The line segments are sequential – it’s a climatic variable (sensible heat), with observed and simulated values at half-hourly intervals. I’m trying to look for patterns in how the simulation is performing. I’m looking at a scatter plot of obs vs simulation values, and linking them with line segments, (arrows indicate the direction of time). If I plot them, I just get a blurred mess that’s impossible to interpret, like this:

lines

This is a subset of 10000 lines, plotted fine and at low opacity:

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() of the first 700 rows of data (limited by post length):

structure(
    list(
        Qh_sim = c( 56.401439666748, 33.9568634033203, 16.2147789001465, 0.797790050506592, -3.19529962539673, -10.3250732421875, -11.6082448959351, -21.5074787139893, -21.5963478088379, -21.4389324188232, -19.8912830352783, -18.5908279418945, -19.2523441314697, -19.663516998291, -19.1126575469971, -18.4237308502197, -16.6181221008301, -14.7601175308228, -14.5604763031006, -14.3527803421021, -14.6219816207886, -14.791407585144, -15.452392578125, -15.8962726593018, -11.9349966049194, -7.97028636932373, 12.4507570266724, 32.1654815673828, 56.9330673217773, 82.0748443603516, 110.501235961914, 138.745697021484, 150.787033081055, 161.838928222656, 172.895263671875, 184.098617553711, 187.657043457031, 192.906372070312, 193.122268676758, 192.274002075195, 179.315124511719, 164.562591552734, 163.265823364258, 161.703796386719, 133.756286621094, 105.635498046875, 97.0240097045898, 87.8632583618164, 58.3389205932617, 33.2009048461914, 23.2682571411133, 13.6356563568115, 1.51271843910217, 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I’m interested in trying to visually summarise the flow of these lines. Are there any common ways of summarising this kind of information? I could just do a vector field plot, but I think I would lose some relevant information – in particular, some of the denser areas probably have multiple groups of segments. I am considering clustering the segments (using the four variables as features), and then plotting the averages, or perhaps doing a vector-field of wind-roses, but I wanted to see if there were any better ways of going about it.

Answer

You could also split into time chunks and make facetted plots. This would help if the flow goes back and forward over itself a few times.

It may be possible to smooth the segments to get some sense of the flow too, but I think that facetting would be a first step.

Attribution
Source : Link , Question Author : naught101 , Answer Author : Andy W

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