[kzrdude]

I tried showing the flies using matplotlib.animation.FuncAnimation in a notebook, animating even 1000 frames is slow and it warns the animation becomes too large. Maybe there's a better way to do it? Preferably in a notebook interface.

[immmmmm]

pyqtgraph is a nice matplotlib replacement when speed matters, but doesn't work in a notebook

[kzrdude]

I ended up writing some very rudimentary HTML canvas + javascript drawing code into the notebook and for my purposes it's fast and does the job. Just to note to others, that this is a possibility within a Jupyter notebook.

One obvious benefit is that it can start rendering "live" and continuously and doesn't have to generate the whole animation before starting to show it.

[maverickleopard]

How exactly do you that and can you interop with python?

[kzrdude]

I just used this in the Jupyter notebook (toldya it was very simple, written today :).

It interoperates with python by being passed data to the draw call.

Usage like: c = Canvas(); c.draw(xs); xs is a numpy array of shape (N, 2), the points to draw on the canvas.

It's not fancy. But it drew animations faster than matplotlib (I ran this for thousands of frames, just to watch the simulation).

    import IPython.display as ipydisplay
    import json
    import numpy as np

    class Canvas:
        def __init__(self, canvas_id=None, width=500, height=500):
            self.display_id = None
            self._canvas_id = canvas_id or ('canvas_' + str(np.random.randint(0, 10000)))
            display(ipydisplay.HTML(f"""

            <canvas id="{self._canvas_id}" width="{width}" height="{height}" style="border:1px solid #d3d3d3;">
            Your browser does not support the HTML5 canvas tag.</canvas>
            """))

        def draw(self, xs, world_size):
            xs_string = json.dumps(xs.tolist())
            obj = ipydisplay.HTML(f"""
            <script>
            var c = document.getElementById("{self._canvas_id}");
            var ctx = c.getContext("2d");
            var xs = {xs_string};
            var size = {world_size};
            ctx.clearRect(0, 0, c.width, c.height);
            var scale = c.width / size;
            for (let i = 0; i < xs.length; i++) {{
                ctx.fillRect(xs[i][0] * scale, c.height - xs[i][1] * scale, 2, 2)
            }}
            </script>
            """)
            if self.display_id:
                ipydisplay.update_display(obj, display_id=self.display_id)
                return self.display_id
            self.display_id = display(obj, display_id=True).display_id

[maverickleopard]

That's awesome. I'm probably gonna start using this instead of matplotlib

[kzrdude]

Maybe just use ipycanvas instead - it's on PyPI :) It works the same way except it's not a hack. I found it after I posted.

I went through:

- matplotlib animations (super slow, not live)

- writing an image with PIL and updating display (flickers)

- custom html+canvas code

- ipycanvas

I call display() on the canvas and then run the draw update loop on the canvas later in the same cell. That way the canvas is first displayed and then "live" updated.

[maverickleopard]

Oh wow even better. Thanks for enlightening me on this