Remove matplotlib examples

These are broken because using Matplotlib in output widgets is brittle.

The right approach might be to rewrite these with ipympl.

Author: pbugnion

docs/source/tutorials.rst

@@ -95,129 +95,3 @@ We note the following:
   To render different widgets conditionally, we anchor a container (an ``HBox``)
   and swap the container's children.
 
-
-Using IPywidget server with Matplotlib
---------------------------------------
-
-Let's build a simple application that updates a matplotlib plot every second. We
-use an ``Output`` widget to get capture the matplotlib plot. We then embed our
-output widget in a top-level container. Every second, we generate a new output
-widget containing a new plot and swap it into the container. The code for this
-example is in `examples/matplotlib_random
-<https://github.com/pbugnion/ipywidgets_server/tree/master/examples/matplotlib_random>`_::
-
-    # example.py
-
-    import time
-
-    import matplotlib.pyplot as plt
-
-    import numpy as np
-
-    import ipywidgets as widgets
-    from IPython.display import display
-
-    SIZE = 50
-    XBASIS = np.linspace(0.0, 1.0, SIZE)
-
-    container = widgets.VBox()
-
-    def update():
-        """ Generate a new random plot and embed it into the container """
-        output = widgets.Output()
-        with output:
-            fig, ax = plt.subplots(figsize=(12, 8))
-            ax.plot(XBASIS, np.random.rand(SIZE))
-            ax.set_ylim(0.0, 1.0)
-            plt.show()
-        container.children = [output]
-
-    display(container)
-
-    while True:
-        # Update the plot in a busy loop
-        time.sleep(1)
-        update()
-
-
-Save this script to a file called `example.py`. You can then run::
-
-    $ ipywidgets-server example:container
-
-Head over to ``http://127.0.0.1:8866`` in your browser. You should see the widget.
-
-.. image:: images/matplotlib-simple.png
-
-For a more complex example, let's build a widget to explore how the `sin`
-changes depending on the parameters that are passed. We will plot ``a *
-sin(k*x)``, with sliders to change the value of ``a`` and ``k``. The code for
-this example is also available at `examples/matplotlib_sine_waves
-<https://github.com/pbugnion/ipywidgets_server/tree/master/examples/matplotlib_sine_waves>`_::
-
-    # example.py
-
-    import matplotlib.pyplot as plt
-
-    import numpy as np
-
-    import ipywidgets as widgets
-
-    XBASIS = np.linspace(-2*np.pi, 2*np.pi)
-
-
-    class SineRenderer(object):
-
-        def __init__(self):
-            self._amplitude_slider = widgets.FloatSlider(
-                1.0, min=-2.0, max=2.0, description='amplitude'
-            )
-            self._frequency_slider = widgets.FloatSlider(
-                1.0, min=0.1, max=3.0, description='frequency'
-            )
-            self._bind_callbacks()
-            self._controls_container = widgets.VBox([
-                self._amplitude_slider,
-                self._frequency_slider
-            ])
-            self._plot_container = widgets.HBox([])
-            self._application_container = widgets.HBox([
-                self._controls_container, self._plot_container
-            ])
-
-        def _bind_callbacks(self):
-            self._amplitude_slider.observe(
-                self._on_param_change, names='value')
-            self._frequency_slider.observe(
-                self._on_param_change, names='value')
-
-        def _on_param_change(self, change):
-            self.render()
-
-        def render(self, change=None):
-            amplitude = self._amplitude_slider.value
-            frequency = self._frequency_slider.value
-            output = widgets.Output()
-            with output:
-                fig, ax = plt.subplots(figsize=(12, 8))
-                ax.plot(XBASIS, amplitude * np.sin(frequency*XBASIS))
-                ax.set_ylim(-2.5, 2.5)
-                plt.show()
-            self._plot_container.children = [output]
-            return self._application_container
-
-
-    container = SineRenderer().render()
-
-Save this script to a file called `example.py`. You can then run::
-
-    $ ipywidgets-server example:container
-
-.. image:: images/matplotlib-sine.png
-
-It is worth noting the following:
-
- - we wrap the application into a controller class responsible both for generating the view and for reacting to user actions. Using a class provides better encapsulation and re-use.
- - in the class constructor, we handle rendering the static components of the view. We create two container widgets, one to hold the sliders and one to hold the plot. We stack these two containers in an ``HBox``, the top level widget holding our application.
- - We handle reacting to changes in the sliders by `observing` the ``value`` traitlet of the slider. The ``.observe`` method takes a callback as first argument. The callback that we pass in just re-renders the plot. The second argument to ``.observe`` is a list of attributes of the slider to observe. We only want to react to changes in the slider value (rather than, say, its maximum or minimum).
- - The ``render`` method of our application renders the dynamic components and returns the top level widget.
-