farg | Implementation of ideas from the FARG group

For a start, you place your animation object anim into the loop, so not only the point data but also the animation object is repeatedly overwritten. For ease of use, let's put the data points into numpy arrays, where rows represent the time and columns the different points you want to animate. Then, we calculate the x, y, and z arrays based on the t array (for aesthetics, a seamless loop along the columns with length 2*pi, with each column shifted so that the points are equally distributed) and simply update the x, y, and z data row-wise in each animation step. Closely related to your script, this would look like:

You should never be using a loop when animating in matplotlib.

The animate function gets called automatically based on your interval.

Something like this should work

nx.draw does not expose the matplotlib artists used to represent the nodes and edges, so you cannot alter the properties of the artists in-place. Technically, if you plot the edges separately, you do get some collection of artists back but it is non-trivial to map the list of artists back to the edges, in particular if there are self-loops present.

If you are open for using other libraries to make the animation, I wrote netgraph some time ago. Crucially to your problem, it exposes all artists in easily to index forms such that their properties can be altered in-place and without redrawing everything else. netgraph accepts both full-rank matrices and networkx Graph objects as inputs so it should be simple to feed in your data.

Below is a simple example visualization. If I run the same script with with 400 nodes and 1000 edges, it needs 30 seconds to complete on my laptop.

I modified the SO answer in the question to an animation that works in jupyter and only required code for your code, and changed it to the axes format since I have no experience with pyplot format animations. The issue is due to the removal of the clearing of the graph. `axes[0].clear() is there to remove the previous graph element.

I made a NumPy array of the stock and plotted it. Here my code. I think there is a much more direct way only use of the df above.

One way to do this is to add an if condition to your start function to check if your self.i value reached self.max. If it does you can just reset your self.i value to zero and let the animation start again. Below id the code to do this:

The step function in FuncAnimation normally updates a graphical object, which is also should return (the return statement should end with a comma, as it needs to be part of a list or tuple).

The grid and the graphical object (img_plot in the example code) need to be global variables. If you want to save the animation, FuncAnimation needs a frames= parameter to avoid it would run indefinitely.

Yeah, this is a bit of a funny one, but ([]) is not a one-length tuple, ([],) is. In the above replace fargs=(data_lst,) is all you need to get it to work. Or just use fargs=[data_lst] instead of a tuple.