@@ -63,6 +63,21 @@ with built-in support for

 Examples

 --------

+Adaptively learning a 1D function (the `gif` below) and live-plotting the process in a Jupyter notebook is as easy as

+

+.. code:: python

+

+    from adaptive import notebook_extension, Runner, Learner1D

+    notebook_extension()

+

+    def peak(x, a=0.01):

+        return x + a**2 / (a**2 + x**2)

+

+    learner = Learner1D(peak, bounds=(-1, 1))

+    runner = Runner(learner, goal=lambda l: l.loss() < 0.01)

+    runner.live_info()

+

+

 .. raw:: html

   <img src="https://user-images.githubusercontent.com/6897215/38739170-6ac7c014-3f34-11e8-9e8f-93b3a3a3d61b.gif" width='20%'> </img> <img src="https://user-images.githubusercontent.com/6897215/35219611-ac8b2122-ff73-11e7-9332-adffab64a8ce.gif" width='40%'> </img> <img src="https://user-images.githubusercontent.com/6897215/47256441-d6d53700-d480-11e8-8224-d1cc49dbdcf5.gif" width='20%'> </img>