*Values in blue needs to be agreed upon*

- We wish to take a registered set, perturb it, and then evaluate its model
- Given a perturbation method which behaves the way we expect,
- Run a series of [10] instantiations. This means
re-selecting random warps and averaging the results to get smoother
curves.
- Run a series of progressively increasing warps. A large enough series
is required in order to sample the model quality curve. The more points,
the smoother the curve; [7] point might be a
reasonable number.
- Try a variety of shuffle distances in the evaluation, e.g. Euclidean, 5 neighbours, 9, and 12 neighbours? (totalling in [4]shuffle radii)
- Investigate the inclusion of a different number of modes in the evaluation. Will just [1] choice (say [5]principal modes) suffice?

- Run a series of progressively increasing warps. A large enough series
is required in order to sample the model quality curve. The more points,
the smoother the curve; [7] point might be a
reasonable number.

- Run a series of [10] instantiations. This means
re-selecting random warps and averaging the results to get smoother
curves.
- Compare results with overlap measures
**Open questions:**which results to compare specifically? How can different results, corresponding to different parameters, be composed in a single figure?