feature/find groups

[rhayes777]

Another attempt at concise that separates out the variables that cause branches of the model to differ

[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 80.77%. Comparing base (d46f7a3) to head (9ea688e). Report is 22 commits behind head on main.

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```diff @@ Coverage Diff @@ ## main #971 +/- ## ========================================== - Coverage 80.79% 80.77% -0.02% ========================================== Files 193 193 Lines 14667 14644 -23 ========================================== - Hits 11850 11829 -21 + Misses 2817 2815 -2 ```

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[rhayes777]

If we don't combine priors with different ids then concise model info will have essentially no effect.

[Jammy2211]

If we don't combine priors with different ids then concise model info will have essentially no effect.

The main point was to remove duplication of priors with the same id:

            light_profile_list
                0
                    centre
                        centre_0                                                UniformPrior [425], lower_limit = -0.1, upper_limit = 0.1
                        centre_1                                                UniformPrior [426], lower_limit = -0.1, upper_limit = 0.1
                    ell_comps
                        ell_comps_0                                             GaussianPrior [429], mean = 0.0, sigma = 0.3
                        ell_comps_1                                             GaussianPrior [430], mean = 0.0, sigma = 0.3
                    sigma                                                       0.01
                1
                    centre
                        centre_0                                                UniformPrior [425], lower_limit = -0.1, upper_limit = 0.1
                        centre_1                                                UniformPrior [426], lower_limit = -0.1, upper_limit = 0.1
                    ell_comps
                        ell_comps_0                                             GaussianPrior [429], mean = 0.0, sigma = 0.3
                        ell_comps_1                                             GaussianPrior [430], mean = 0.0, sigma = 0.3
                    sigma                                                       0.012294934136946248
                2
                    centre
                        centre_0                                                UniformPrior [425], lower_limit = -0.1, upper_limit = 0.1
                        centre_1                                                UniformPrior [426], lower_limit = -0.1, upper_limit = 0.1
                    ell_comps
                        ell_comps_0                                             GaussianPrior [429], mean = 0.0, sigma = 0.3
                        ell_comps_1                                             GaussianPrior [430], mean = 0.0, sigma = 0.3
                    sigma                                                       0.01511654054318462
                3
                    centre
                        centre_0                                                UniformPrior [425], lower_limit = -0.1, upper_limit = 0.1
                        centre_1                                                UniformPrior [426], lower_limit = -0.1, upper_limit = 0.1
                    ell_comps
                        ell_comps_0                                             GaussianPrior [429], mean = 0.0, sigma = 0.3
                        ell_comps_1                                             GaussianPrior [430], 

Which the PR does -- all these priors with ids 425, 29, etc are condensed into one.

But we dont want priors with unique ids to be compressed as I think this is useful info to a user.

[rhayes777]

OK that's fine I can implement it that way

[rhayes777]

I think whatever we do with graph visualisation will require some thought

[rhayes777]

Done