Add logistic decay

[florence-bockting]

Description

• add logistic decay

Checklist

Please confirm that this pull request has done the following:

• Tests added
• Documentation added (where applicable)
• Changelog item added to changelog/

[florence-bockting]

The scaling of the logistic function is still quite "wilde".
I think I lost the focus and made it overly complicated. Need to look at it again with a fresh mind.
Suggestions for better shifting/scaling of the logistic function are welcome.

[znichollscr]

Nice. Let's please add the extra tests suggested so we have a record of how this behaves in practice, then we should be good to merge

[znichollscr]

Suggested change

	+ include support for logistic-decay
	+ we added three new classes/functions to the API in the module `convergence`
	+ `LogisticDecaySplineHelper`
	+ `LogisticDecaySplineHelperDerivative`
	+ `get_logistic_decay_harmonised_spline`
	+ whereby the function `get_logistic_decay_harmonised_spline` is mainly meant as user-interface
	This function can be used as value for the `get_harmonise_spline` parameter in `harmonise`.
	The function takes the same arguments as `get_cosine_decay_harmonised_spline` and additionally a
	`slope` and `shift` argument.
	+ These arguments determine slope and location of the logistic function and can be passed using
	`functools.partial(get_logistic_decay_harmonised_spline, slope = 0., shift = 0.)`
	+ An example use-case is added to the `getting-started-tutorial`.
	+ Include supported for logistic-decay
	+ Added new features to [convergence][gradient_aware_harmonisation.convergence]
	+ [LogisticDecaySplineHelper][gradient_aware_harmonisation.convergence.LogisticDecaySplineHelper]
	+ [LogisticDecaySplineHelperDerivative][gradient_aware_harmonisation.convergence.LogisticDecaySplineHelperDerivative]
	+ [get_logistic_decay_harmonised_spline][gradient_aware_harmonisation.convergence.get_logistic_decay_harmonised_spline]
	+ The function [get_logistic_decay_harmonised_spline][gradient_aware_harmonisation.convergence.get_logistic_decay_harmonised_spline] is an adapter between the underlying classes and the interface required for the `get_harmonise_spline` parameter in [harmonise][gradient_aware_harmonisation.harmonise].
	The function takes the same arguments as [get_cosine_decay_harmonised_spline][gradient_aware_harmonisation.convergence.get_cosine_decay_harmonised_spline] and additional
	`slope` and `shift` arguments. These arguments determine the slope and location of the logistic function and can be can be 'pre-passed' to the function using [functools.partial](https://docs.python.org/3/library/functools.html#functools.partial) e.g. `harmonise(..., get_harmonise_spline=functools.partial(get_logistic_decay_harmonised_spline, slope = 0., shift = 0.)...)`
	+ An example use-case is included in the [getting started tutorial][gradient-aware-harmonisation-getting-started].

Same reasoning as #16 (comment)

[znichollscr]

Can you please add some tests of what happens at a few key values of x e.g.

• x is very negative
• x equal to the initial time
• x halfway between the initial and final time
• x equal to the final time
• x is very positive

Also tests that summing a spline with apply_to_convergence=True and apply_to_convergence=False gives 1 everywhere.

I'm assuming these things all hold, but it's good to check so we have the proof for ourselves, should we ever need it.