Expose diverse probes in Python API. (#1225)

Major changes in Python library and documentation:

* Add global state (immutable after initialization) for the Python module that
  manages the mapping between probe metadata types and the method by which the
  corresponding [sample data can be collected and presented as Python objects.
  This is necessary for decoupling the implementation of the simulation wrapper
  from that of the various cable cell probe types.

* Wrap each of the C++ cable cell probe types with a Python function that
  returns a `probe_info` object.

* Add code for converting and accumulating C++ probe metadata and sample
  data, registered in the module global state against the metadata type info.

* Make the `arbor.simulator` object responsible for recording all spike and
  sample data, with corresponding new methods.

* Use NumPy arrays and structured datatypes for returning spike and
  sample data.

* Place Python schedule proxies under an abstract interface so that consumers
  of the proxies can be made generic over schedule types.

* Add unit tests for the `arbor.simulator` class and its new functionality,
  including distributed spike collection.

* Rework all Python API documentation concerning probes, sampling, and spike
  recording; add information on newly exposed cable cell probe addresses.

* Add new python example `single_cell_recipe.py` which is a generic recipe
  version of `single_cell_model.py`.

* Adjust other code in the wrapper and examples to accommodate these changes.

Minor changes in Python library:

* Add equality tests for `arbor.location` and `arbor.cable` Python classes.

* Use the `py::` namespace shorthand more often in the Python wrapping sources.

* Add an implicit conversion for a pair of numbers to `arbor.cell_member`, so
  that e.g. probe ids can be specified simply as `(gid, index)`.

* Add an implicit conversion from a tuple to `arbor.mpoint` so that a
  morphological point can be specified simply as `(x, y, z, radius)`.

* Modify the interface to `arbor.regular_schedule` so that the overloads
  correspond more closely to the C++ API. In particular,
  `arbor.regular_schedule(dt)` now describes a schedule with times 0, dt, 2*dt,
  etc.

Minor changes in C++ library:

* Change test in FVM lowered cell implementation and exception message for
  `bad_source_description`: assert number of detectors is exactly the number
  of sources promised by the recipe.

* Add comment describing `probe_metadata` object in `sampling.hpp` which
  asserts that the type and value of probe-specific metadata completely
  determines the correct interpretation of sampled data provided to a callback.