mpld3: matplotlib to D3js

http://mpld3.github.io

  • Package by Jake Vanderplas (hey that's me!)

  • Reads the object structure of matplotlib figures and converts them to D3js

  • An extensible plugin system for adding new interactivity

  • Because it uses mpl, it is automatically compatible with PrettyPlotLib, ggplot, and Seaborn


In [1]:
#%run talktools
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.display import HTML

# CSS formatting
from IPython.display import HTML
HTML("""
<style>
h1 {text-align:center; color:#111133; font-size: 220%;}
h2 {text-align:center; color:#111155; font-size: 150%;}
h3 {text-align:center; font-size: 140%;}
</style>
""")


Out[1]:

As we saw, matplotlib can be used with the IPython notebook to embed visualizations...


In [2]:
x, y = np.random.normal(0, 1, [2, 100])
c, s = 800 * np.random.random([2, 100])

fig = plt.figure()
points = plt.scatter(x, y, c=c, s=s, alpha=0.3)
plt.grid(color="lightgray");


But this is annoyingly static...

The Solution: translate matplotlib to D3js!


In [3]:
import mpld3
mpld3.enable_notebook()
fig


Out[3]:

What is this actually doing?

Using the mplexporter package to scrape info from the matplotlib object

Outputs a JSON representation of the figure


In [4]:
mpld3.fig_to_dict(fig)


Out[4]:
{'axes': [{'axes': [{'fontsize': 10.0,
     'grid': {'alpha': 1.0,
      'color': '#D3D3D3',
      'dasharray': '2,2',
      'gridOn': True},
     'nticks': 9,
     'position': 'bottom',
     'scale': 'linear',
     'tickformat': None,
     'tickvalues': None},
    {'fontsize': 10.0,
     'grid': {'alpha': 1.0,
      'color': '#D3D3D3',
      'dasharray': '2,2',
      'gridOn': True},
     'nticks': 6,
     'position': 'left',
     'scale': 'linear',
     'tickformat': None,
     'tickvalues': None}],
   'axesbg': '#FFFFFF',
   'axesbgalpha': None,
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   [0.27245788714873853, -0.6207460229221919],
   [-1.853937638180583, 0.18889677731391594],
   [0.1265975832991032, 1.053464291988132],
   [0.9980439565989615, -0.23345902357977796],
   [-0.1097540129406351, -0.28405698032106447],
   [-0.7519576136420723, 0.056638483852095356],
   [-0.6627895114782915, 0.5765271713845989],
   [0.13120208390452465, 0.9825943627143522],
   [0.27877571149743996, 0.2543922218305604],
   [1.1278303738772, -0.2006391780047112],
   [-2.5122639880258015, 1.1285465220394728],
   [0.48343467966638987, 0.6702929397639165],
   [-0.6021947400264485, 1.5764529774841523],
   [-1.166974286157769, -0.2585098030979472],
   [-0.6770470850477514, 1.563189465719086],
   [-1.4035092448121866, -1.1105604086579122],
   [-0.5590505164731143, 0.852337662482413],
   [-0.06434234713592306, -1.2207334222323765],
   [0.30956898853279646, -0.8365648638931428],
   [-0.5521251386832189, -0.16851395942332204],
   [0.8624021794326409, 0.16893174589469592],
   [1.1415270967023723, -1.2339714902333412],
   [0.09770556253245943, 0.39632322662992825],
   [-0.43856454359354724, 0.3852825272229884],
   [0.6341993627975028, 0.4684747563190834],
   [-1.1730465362480262, 0.36610229371224534]]},
 'height': 320.0,
 'id': 'el323334328933648',
 'plugins': [{'type': 'reset'},
  {'button': True, 'enabled': False, 'type': 'zoom'},
  {'button': True, 'enabled': False, 'type': 'boxzoom'}],
 'width': 480.0}

This is interpreted by mpld3.js

~1500 line JS library

mpld3 produces a pure client-side view of a Matplotlib plot

No requirement for a server-side callback!

Easy to embed on any static website

But there's more... mpld3 allows you to add plugins:

Plugins = endless possibilities for interactive behavior!

Tooltip Plugin:


In [5]:
from mpld3 import plugins

labels = ['Point {0}'.format(i) for i in range(100)]

tooltips = plugins.PointLabelTooltip(points, labels)
plugins.connect(fig, tooltips)
fig


Out[5]:

Linked Brushing plugin:


In [6]:
from sklearn.datasets import load_iris
iris = load_iris()

# dither the data for clearer plotting
iris.data += 0.1 * np.random.random(iris.data.shape)

fig, ax = plt.subplots(4, 4, sharex="col", sharey="row", figsize=(8, 8))
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=0.95,
                    hspace=0.1, wspace=0.1)

for i in range(4):
    for j in range(4):
        points = ax[3 - i, j].scatter(iris.data[:, j], iris.data[:, i],
                                      c=iris.target, s=40, alpha=0.6)

# remove tick labels
for axi in ax.flat:
    for axis in [axi.xaxis, axi.yaxis]:
        axis.set_major_formatter(plt.NullFormatter())

# Here we connect the linked brush plugin
plugins.connect(fig, plugins.LinkedBrush(points))


/Users/jakevdp/anaconda/lib/python2.7/site-packages/numpy/oldnumeric/__init__.py:11: ModuleDeprecationWarning: The oldnumeric module will be dropped in Numpy 1.9
  warnings.warn(_msg, ModuleDeprecationWarning)

Custom Plugins:

Just write a bit of Python + JS


In [7]:
from mpld3 import plugins, utils


class HighlightLines(plugins.PluginBase):
    """A plugin to highlight lines on hover"""

    JAVASCRIPT = """
    mpld3.register_plugin("linehighlight", LineHighlightPlugin);
    LineHighlightPlugin.prototype = Object.create(mpld3.Plugin.prototype);
    LineHighlightPlugin.prototype.constructor = LineHighlightPlugin;
    LineHighlightPlugin.prototype.requiredProps = ["line_ids"];
    LineHighlightPlugin.prototype.defaultProps = {alpha_bg:0.3, alpha_fg:1.0}
    function LineHighlightPlugin(fig, props){
        mpld3.Plugin.call(this, fig, props);
    };

    LineHighlightPlugin.prototype.draw = function(){
      for(var i=0; i<this.props.line_ids.length; i++){
         var obj = mpld3.get_element(this.props.line_ids[i]),
             alpha_fg = this.props.alpha_fg;
             alpha_bg = this.props.alpha_bg;
         obj.elements()
             .on("mouseover", function(d, i){
                            d3.select(this).transition().duration(50)
                              .style("stroke-opacity", alpha_fg); })
             .on("mouseout", function(d, i){
                            d3.select(this).transition().duration(200)
                              .style("stroke-opacity", alpha_bg); });
      }
    };
    """
    def __init__(self, lines):
        self.lines = lines
        self.dict_ = {"type": "linehighlight",
                      "line_ids": [utils.get_id(line) for line in lines],
                      "alpha_bg": lines[0].get_alpha(),
                      "alpha_fg": 1.0}


x = np.linspace(0, 10, 100)
y = 0.1 * (np.random.random((50, 100)) - 0.5)
y = y.cumsum(1)

fig, ax = plt.subplots(subplot_kw={'xticks': [], 'yticks': []})
lines = ax.plot(x, y.T, color='blue', lw=4, alpha=0.1)
plugins.connect(fig, HighlightLines(lines))



In [8]:
# from http://mpld3.github.io/examples/heart_path.html

import matplotlib as mpl
import matplotlib.path as mpath
import matplotlib.patches as mpatches

class LinkedDragPlugin(plugins.PluginBase):
    JAVASCRIPT = r"""
    mpld3.register_plugin("drag", DragPlugin);
    DragPlugin.prototype = Object.create(mpld3.Plugin.prototype);
    DragPlugin.prototype.constructor = DragPlugin;
    DragPlugin.prototype.requiredProps = ["idpts", "idline", "idpatch"];
    DragPlugin.prototype.defaultProps = {}
    function DragPlugin(fig, props){
        mpld3.Plugin.call(this, fig, props);
    };

    DragPlugin.prototype.draw = function(){
        var patchobj = mpld3.get_element(this.props.idpatch, this.fig);
        var ptsobj = mpld3.get_element(this.props.idpts, this.fig);
        var lineobj = mpld3.get_element(this.props.idline, this.fig);

        var drag = d3.behavior.drag()
            .origin(function(d) { return {x:ptsobj.ax.x(d[0]),
                                          y:ptsobj.ax.y(d[1])}; })
            .on("dragstart", dragstarted)
            .on("drag", dragged)
            .on("dragend", dragended);

        lineobj.path.attr("d", lineobj.datafunc(ptsobj.offsets));
        patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets,
                                                  patchobj.pathcodes));
        lineobj.data = ptsobj.offsets;
        patchobj.data = ptsobj.offsets;

        ptsobj.elements()
           .data(ptsobj.offsets)
           .style("cursor", "default")
           .call(drag);

        function dragstarted(d) {
          d3.event.sourceEvent.stopPropagation();
          d3.select(this).classed("dragging", true);
        }

        function dragged(d, i) {
          d[0] = ptsobj.ax.x.invert(d3.event.x);
          d[1] = ptsobj.ax.y.invert(d3.event.y);
          d3.select(this)
            .attr("transform", "translate(" + [d3.event.x,d3.event.y] + ")");
          lineobj.path.attr("d", lineobj.datafunc(ptsobj.offsets));
          patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets,
                                                    patchobj.pathcodes));
        }

        function dragended(d, i) {
          d3.select(this).classed("dragging", false);
        }
    }

    mpld3.register_plugin("drag", DragPlugin);
    """

    def __init__(self, points, line, patch):
        if isinstance(points, mpl.lines.Line2D):
            suffix = "pts"
        else:
            suffix = None

        self.dict_ = {"type": "drag",
                      "idpts": utils.get_id(points, suffix),
                      "idline": utils.get_id(line),
                      "idpatch": utils.get_id(patch)}


fig, ax = plt.subplots(figsize=(8, 6))

Path = mpath.Path
path_data = [
    (Path.MOVETO, (1.58, -2.57)),
    (Path.CURVE4, (0.35, -1.1)),
    (Path.CURVE4, (-1.75, 2.0)),
    (Path.CURVE4, (0.375, 2.0)),
    (Path.LINETO, (0.85, 1.15)),
    (Path.CURVE4, (2.2, 3.2)),
    (Path.CURVE4, (3, 0.05)),
    (Path.CURVE4, (2.0, -0.5)),
    (Path.CLOSEPOLY, (1.58, -2.57)),
    ]
codes, verts = zip(*path_data)
path = mpath.Path(verts, codes)
patch = mpatches.PathPatch(path, facecolor='r', alpha=0.5)
ax.add_patch(patch)

# plot control points and connecting lines
x, y = zip(*path.vertices[:-1])
points = ax.plot(x, y, 'go', ms=10)
line = ax.plot(x, y, '-k')

ax.grid(True, color='gray', alpha=0.5)
ax.axis('equal')
ax.set_title("Drag Points to Change Path", fontsize=18)

plugins.connect(fig, LinkedDragPlugin(points[0], line[0], patch))