Sim-tools

* BUILD: Dropped legacy `setuptools` and migrated package build to `hatch`
* BUILD: Removed `setup.py`, `requirements.txt` and `MANIFEST` in favour of `pyproject.toml`

* PATCH: `distributions.Discrete` was not returning numpy arrays.

* Distributions classes now have python type hints.
* Added distributions and time dependent arrivals via thinning example notebooks.
* Added `datasets` module and function to load example NSPP dataset.
* Distributions added
* Erlang (mean and stdev parameters)
* ErlangK (k and theta parameters)
* Poisson
* Beta
* Gamma
* Weibull
* PearsonV
* PearsonVI
* Discrete (values and observed frequency parameters)
* ContinuousEmpirical (linear interpolation between groups)
* RawEmpirical (resample with replacement from individual X's)
* TruncatedDistribution (arbitrary truncation of any distribution)
* Added sim_tools.time_dependent module that contains `NSPPThinning` class for modelling time dependent arrival processes.
* Updated test suite for distributions and thinning
* Basic Jupyterbook of documentation.

* Added `sim_tools.distribution` module. This contains classes representing popular sampling distributions for Discrete-event simulation. All classes encapsulate a `numpy.random.Generator` object, a random seed, and the parameters of a sampling distribution.

* Python has been updated, tested, and patched for 3.10 and 3.11 as well as numpy 1.20+

* Minor linting and code formatting improvement.