[python] Python & Matplotlib: Make 3D plot interactive in Jupyter Notebook

A solution I came up with is to use a vis.js instance in an iframe. This shows an interactive 3D plot inside a notebook, which still works in nbviewer. The visjs code is borrowed from the example code on the 3D graph page

A small notebook to illustrate this: demo

The code itself:

from IPython.core.display import display, HTML
import json

def plot3D(X, Y, Z, height=600, xlabel = "X", ylabel = "Y", zlabel = "Z", initialCamera = None):

    options = {
        "width": "100%",
        "style": "surface",
        "showPerspective": True,
        "showGrid": True,
        "showShadow": False,
        "keepAspectRatio": True,
        "height": str(height) + "px"
    }

    if initialCamera:
        options["cameraPosition"] = initialCamera

    data = [ {"x": X[y,x], "y": Y[y,x], "z": Z[y,x]} for y in range(X.shape[0]) for x in range(X.shape[1]) ]
    visCode = r"""
       <link href="https://cdnjs.cloudflare.com/ajax/libs/vis/4.21.0/vis.min.css" type="text/css" rel="stylesheet" />
       <script src="https://cdnjs.cloudflare.com/ajax/libs/vis/4.21.0/vis.min.js"></script>
       <div id="pos" style="top:0px;left:0px;position:absolute;"></div>
       <div id="visualization"></div>
       <script type="text/javascript">
        var data = new vis.DataSet();
        data.add(""" + json.dumps(data) + """);
        var options = """ + json.dumps(options) + """;
        var container = document.getElementById("visualization");
        var graph3d = new vis.Graph3d(container, data, options);
        graph3d.on("cameraPositionChange", function(evt)
        {
            elem = document.getElementById("pos");
            elem.innerHTML = "H: " + evt.horizontal + "<br>V: " + evt.vertical + "<br>D: " + evt.distance;
        });
       </script>
    """
    htmlCode = "<iframe srcdoc='"+visCode+"' width='100%' height='" + str(height) + "px' style='border:0;' scrolling='no'> </iframe>"
    display(HTML(htmlCode))

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