Bayesian post-analysis using BUMPS DREAM

[rozyczko]

A new Bayesian MCMC sampling interface. This enables users to perform posterior sampling using the BUMPS DREAM sampler directly from both the MultiFitter and BUMPS minimizer classes.

• Added a sample method to MultiFitter that flattens multi-dataset arrays, resolves parameter aliases, and delegates to the minimizer’s sampling method, supporting both 1D and vectorized multi-dimensional fits.
• Implemented a sample method in the BUMPS minimizer (minimizer_bumps.py) that builds a BUMPS FitProblem and runs the DREAM sampler, returning posterior draws, parameter names, sampler state, and log-probabilities.

[codecov]

Codecov Report

❌ Patch coverage is 94.66667% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.75%. Comparing base (d4a4c23) to head (f072fd6).

Files with missing lines	Patch %	Lines
.../easyscience/fitting/minimizers/minimizer_bumps.py	93.22%	4 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop     #244      +/-   ##
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+ Coverage    82.55%   82.75%   +0.20%     
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  Files           62       62              
  Lines         4946     5021      +75     
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+ Hits          4083     4155      +72     
- Misses         863      866       +3     

Flag	Coverage Δ
integration	44.03% <78.66%> (+0.54%)	⬆️
unittests	82.21% <92.00%> (+0.93%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
src/easyscience/fitting/multi_fitter.py	98.83% <100.00%> (+1.69%)	⬆️
.../easyscience/fitting/minimizers/minimizer_bumps.py	97.96% <93.22%> (-1.50%)	⬇️

[rozyczko]

I might want to extend this to multiprocessing, since BUMPS already supports this.
The implementation should speed things up quite noticeably.