- BREAKING: Rename spike detector -> threshold detector in Python
- `spike_detector` is still around, will throw a deprecation error; will be removed 0.9
- this brings Python closer to the C++ API and removes lots of ambiguities in the docs.

* Add segment tree editing: join and split
* Add equivalence and equality on trees
* Apply isometries to trees
* Add raw loaders to NeuroLucida ASC and SWC that return segment trees instead of morphologies

Spike source cells can now generate events based on the interleaving of arbitrarily many schedules.
This should simplify the required connectivity.

Until now, point mechanisms applied a weighting factor when updating internal/external concentrations.
This was an oversight and is only correct in density mechanisms. This has been rectified, but might change
point mechanism semantics for injecting/modifying Xi/Xo values.

- Print better modcc errors
- Catch errors in symbolic diff in linearity test
- Abort upon such errors and advise for a different solver

- Remove the old, multi-target `event_generator` class in favour of `schedule_generator(tgt, weight, explicit_schedule)`
- Much simplification ensues, `event_generator` is no longer a type-erasing container, but just what 
   `schedule_generator` was before
- Make the label resolution in generators a bit more eager, no longer at simulation time, 
   but now during setup (bit give a wee bit of perf as well)

Closes #1488 

Add functionality, docs, and examples on editing the connection table.  This is a first, small PR
on the topic, further functionality will come as requested.

Teaser example
```cxx
    // This recipe -- omitted -- implements a mutable connection table 
    // and returns it via the `connections_on` callback. New entries are
    // added using `add_connection` which makes one link from a central 
    // `spike_source_cell` to the given `gid`
    auto rec = recipe();
    rec.add_connection(1);

    auto sim = arb::simulation(rec, ctx);

    // Record spikes
    std::vector<arb::spike> spikes;
    sim.set_local_spike_callback([&spikes](const auto& s) { spikes.insert(spikes.end(), s.begin(), s.end()); });

    // Run and print all spikes per gid
    sim.run(0.25, 0.025);
    show_spikes(spikes);

    // Add a new connection
    rec.add_connection(2);
    sim.update_connections(rec);

    // Run and print all spikes per gid
    sim.run(0.5, 0.025);
    show_spikes(spikes);
```

# Update July '22

- added re-wiring of Event Generators
- implemented a split between a recipe and a recipe-update (cheekily dubbed `topping` until further notice)
- `recipes` are `toppings` via inheritance

**BREAKING** Remove access to time `t` in NMODL.

- Enhance `run_cpp_examples.sh` to do some very basic checking of spikes counts
- Add a script to check all releases
- The former must succeed for all commits to master

Here's the expected spike counts as of 0.7
- brunel 6998
- bench 972
- ring 94 (19 pre-v0.7)
- gap_junctions 30

- allow arbor to be build against py3.11
- modernise!

Document use and care of spike detectors.

Enable pyArborio input routines to consume Stream objects in addition to files by name.
- NML
- NeuroLucida ASC
- SWC

Closes #1459 

Do not abuse `pybind::arg_v("name", T default, "description")` as `pybind::arg_v("name", "description")`.
Use descriptive names and `pybind::arg` instead.

Closes #1754 

Functionality to
- delete ions from global properties
- peek into global properties
- expose painted, placed, and defaulted items
- expose voltage limit to python
- make voltage limit an optional to allow for arbitrary values.
- Add ion_settings view to python = (valence, ion_data, rev_pot_method)

Documentation
- cable cell properties in python

Closes #1578 
Closes #1577 
Closes #1607 

* Add find_private_gpu and arbor.env.

- Add stacktraces to
   1. arbor_exception (and all derived) as `where`
   2. arbor_internal_error as `where`
   3. arb_assert
- Propagate stacktraces to Python exceptions derived from the above.
- Expand dev/doc on debugging

* Clean up the bundled mechanisms. Closes #1155

Remove the redundant fvm_(value|size|index)_type aliases and replace them with the raw ABI types.

Throw error if WATCH encountered in NMODL.

- elaborate probing API
- add definitions for different kinds of probes (vector, scalar, set).
- add sketches and example for data layout

- It's actually a Github cache trick: https://github.com/actions/cache/issues/342#issuecomment-673371329
  - First run: 1h 7m 38s 
  - Second run: same duration. Hmm....
  - Third run: ~10 minutes!
  - 4th: ~7.5 min.
- Bump in configs: macos 10.15 will disappear in a month: https://github.com/actions/virtual-environments/issues/5583
  - Bump clang-max to 14, gcc-max to 11
  - macos-min to 11, macos-max to 12.

- Generate timestamped VERSION once, to properly group on Test.PyPI. Example:
  - https://github.com/arbor-sim/arbor/actions/runs/2696804929
  - https://test.pypi.org/project/arbor/0.7rc20220719101015/
- Update/simplify release documentation.
- Update to v0.7

* - Weekly CI Python wheel build pushes to Test.PyPI.org
    - Easy availability at https://test.pypi.org/project/arbor/
- Small change in documentation around VERSION
- Delete superfluous setup.py file.

Move Python build to `pyproject.toml`, bump Python minver to 3.7, fix macos wheel generation (#1916)

* Failing Macos Python wheel builds fixed.
* Macos Python wheels now come with dual-arch (x86-64 and arm64)
* Moved (nearly) all Python build instructions to `pyproject.toml`
  * Enables 'build isolation', and need to specify build-deps only once, no need for users or CI scripts to pre-install them.
  * Enables editable `pip` installs (`pip install -e ./arbor`)
  * Compatible with 'build frontends' `pip` and `build`.
  * Passing CMake options actually got shorter
* Drop Python 3.6 support.

- Fix line numbers in tutorials, fallout from #1906
- Mention arbor-contrib in a few relevant places
- Correct some fallout from #1904
- A new hardware and profiling tutorial, and covers things moved out of other examples in #1904
- Various other documentation fixes

Adds the ability to scale parameters of (density) mechanisms based on inhomogeneous properties along a cell.
Two new types are added:
- iexpr: An expression describing the scaling factor computation.
- scaled_mechanism: A wrapper struct around a mechanisms with iexpr attached to selected parameters.

Closes #1650

Post-Merge clean-up for the diffusion PR
- remove redundant `WRITE`s in mechanisms
- diffusion.py is now closer in functionality to diffusion.cpp
- diffusion.py now prints a table of results