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add pointwise sampling distribution class for model comparison #212

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merged 6 commits into from
Jul 2, 2024

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LegrandNico
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  • Add a pointwise HGF distribution, returning log probability for each observation.
  • Use squares to plot binary state nodes in the plot_network function.
  • Re-write tutorial (2nd part) on reinforcement learning applications with better sampling methods and models.
  • The main log methods return pointwise estimates
  • All response functions now return surprises, instead of the sum of surprises.

@LegrandNico LegrandNico added documentation Improvements or additions to documentation plotting sampling Interface with PyMC and sampling neural networks labels Jul 2, 2024
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Contributes to #194

@LegrandNico LegrandNico self-assigned this Jul 2, 2024
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All modified and coverable lines are covered by tests ✅

Project coverage is 95.09%. Comparing base (7a1fc03) to head (a891a93).

Additional details and impacted files
@@            Coverage Diff             @@
##           master     #212      +/-   ##
==========================================
+ Coverage   95.02%   95.09%   +0.07%     
==========================================
  Files          23       23              
  Lines        1165     1182      +17     
==========================================
+ Hits         1107     1124      +17     
  Misses         58       58              

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@LegrandNico LegrandNico merged commit bc21082 into master Jul 2, 2024
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@LegrandNico LegrandNico deleted the sampling branch July 2, 2024 13:24
LegrandNico added a commit to KoraTMontemagno/pyhgf that referenced this pull request Aug 9, 2024
…tationalPsychiatry#212)

* update the exercises with better sampling functions for model comparison

* return pointwise log likelihood by default

* add pointwise class for sampling

* use square for binary state nodes

* rewrite the HGF tutorial

* add sphinx exercise in docs requirements
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2 participants