更新 pyplot.scatter 的位置和颜色 [英] Updating the positions and colors of pyplot.scatter

问题描述

我已经为此苦苦挣扎了一段时间，但无法让它发挥作用.我正在读取文件，并从中散点数据，我想通过更新 for 循环中每个块的散点图来动画化"该文件(并使它适应实时变化)数据流).

I have been struggling with this for a while and can't get it to work. I am reading a file in chunks and scatter plotting data from it, and I would like to "animate" it by updating the scatter plot for each chunk in a for loop (and also adapt it to a live stream of data).

因此，类似此丑陋示例的示例适用于单个图:

So something like this ugly example works for a single plot:

x = [1, 2, 3, 4]
y = [4, 3, 2, 1]
alpha = [0.2, 0.3, 0.8, 1.0]
c = np.asarray([(0, 0, 1, a) for a in alpha])
s = scatter(x, y, marker='o', color=c, edgecolors=c)

但是如何在不重复调用 s.remove() 和 scatter() 的情况下更新绘图?完全不直观的 s.set_array 和 s.set_offsets 可以更新颜色以及x和y位置，但是我不知道如何使用它们上面我有x，y，alpha数据的类型.

But how do I update the plot without calling s.remove() and scatter() repeatedly? The completely unintuitively-named s.set_array and s.set_offsets are supposed to update the colors and the x and y positions, but I can't figure out how to use them with the type of x, y, alpha data I have above.

(还有，在上面的图中有更好的方法做alpha吗?)

(Also, is there a better way to do the alpha in the above plot?)

推荐答案

我为此找到的解决方案包括使用 Normalize 根据相关数据制作标准化颜色列表，将其映射到 ScalarMappable，并使用它来设置动画每一帧的面部颜色和c限制.使用 scat 散点图的句柄和 speedList 提供颜色数据:

The solution I found for this involves using Normalize to make a normalised colour list based on the relevant data, mapping it to a ScalarMappable, and using that to set the face colour and c limits on each frame of the animation. With scat the handle of the scatter plot and speedsList provides the colour data:

n = mpl.colors.Normalize(vmin = min(speedsList), vmax = max(speedsList))
m = mpl.cm.ScalarMappable(norm=n, cmap=mpl.cm.afmhot)
scat.set_facecolor(m.to_rgba(speedsList))
scat.set_clim(vmin=min(speedsList), vmax=max(speedsList))

这正是我所期望的.

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