This project is mirrored from https://github.com/pymc-devs/pymc3.git. Pull mirroring updated .
  1. 05 Apr, 2021 1 commit
  2. 03 Apr, 2021 1 commit
  3. 27 Mar, 2021 1 commit
  4. 24 Mar, 2021 1 commit
  5. 23 Mar, 2021 1 commit
  6. 22 Mar, 2021 2 commits
  7. 17 Mar, 2021 1 commit
  8. 16 Mar, 2021 1 commit
    • ricardoV94's avatar
      Fix dependence of Uniform logp on bound method (#4541) · b2e64cba
      ricardoV94 authored
      * Fix logp of (Discrete) Uniform to not depend on bound
      * Add unittest
      * Remove redundant `all()` bound conditions in multivariate distributions and improve documentation of dist_math::bound
      * Add recommendation for check_bounds.
      * Add release note
      * Include Release Notes from 3.11.2
      b2e64cba
  9. 10 Mar, 2021 1 commit
  10. 09 Mar, 2021 3 commits
    • Christopher Krapu's avatar
      Conditional autoregression distribution (#4504) · 53b642e4
      Christopher Krapu authored
      * Add conditional autoregression distribution (CAR)
      53b642e4
    • Thomas Wiecki's avatar
      Remove float128 dtype (#4514) · a7c56465
      Thomas Wiecki authored
      * Remove float128 dtype which does not exist on Windows and newer OSX versions and furthermore does not to be properly supported even if it does exist.
      * Add float128 to release-notes. Add link to memoization PR.
      * Remove unused imports.
      a7c56465
    • mpall17's avatar
      Break down tests having multiple checks and xfail decorated (#4497) · d248a0e9
      mpall17 authored
      * Break down tests having multiple checks and xfail decorated
      
      Xfail is going to care only about the first failed assert statement and
      ignore all the other ones in the same test.
      
      Sometimes xfail is being used to decorate a test or class function calling
      several other sub-functions. This makes it hard to monitor what is happening
      for the sub-fuctions that are not failing (given that the failure will take
      priority and mark the test function as xfailed). By breaking down each
      function into individual sub-functions it's easier to monitor individual
      tests behavior
      
      * Remove xfail which seems unnecessary
      
      Also add comment regarding test with unpredictable outcome
      
      * Break down test with multiple sub-checks and xfail where appropriate
      
      * Remove Scipy Xfail from tests not using sp.betabinom
      
      * Add back xfail to potentially failing test when float32 is used
      
      * Temporatily add n_samples=-1 to check tests behavior for all possible parameters
      
      * Remove temporary n_samples and a couple more to do some quick tests
      
      * Remove unnecessary comments
      
      * Replace Xfail with skipif when using Scipy version as condition
      
      Given that betabinom won't exist in previous versions, there should be
      no chance for it's behavior to change, given that it won't exist there
      is no point in monitoring the outcome of these tests, so it may be worth
      skipping them. Skipping them should be faster than running them and
      catching the failures
      
      * Add missing n_samples for test_beta_binomial_selfconsistency
      
      * Remove all the n_samples=-1 added for verifying tests robustness
      
      * Tweak normal_logcdf and moyal tests
      
      Temporarily set n_samples=-1 to test all permutations.
      
      * Reintroduce 32bit xfail on Moyal logcdf, revert n_samples and merge passing normal tests
      
      * Small renaming and reordering
      
      * Reintroduce accidentally removed n_samples from binomial test
      Co-authored-by: default avatarRicardo <ricardo.vieira1994@gmail.com>
      d248a0e9
  11. 08 Mar, 2021 2 commits
  12. 05 Mar, 2021 1 commit
  13. 03 Mar, 2021 1 commit
    • Eelke Spaak's avatar
      proper handling of chain_idx in sample() (#4495) · cf662c9f
      Eelke Spaak authored
      * don't add chain offset in loop already taking care of this
      
      * don't default to chain 0 when computing sampler stats; use provided chain_idx
      
      * adding test script for chain_idx in sample()
      
      * marking test as xfail for now
      
      * take care of chain indices in sample_posterior_predictive
      
      * update test to include sample_posterior_predictive
      
      * use reproducable order of ppc samples wrt multiple chains
      cf662c9f
  14. 02 Mar, 2021 1 commit
  15. 01 Mar, 2021 3 commits
  16. 26 Feb, 2021 1 commit
  17. 24 Feb, 2021 1 commit
  18. 22 Feb, 2021 1 commit
  19. 12 Feb, 2021 3 commits
  20. 08 Feb, 2021 2 commits
  21. 06 Feb, 2021 1 commit
    • Sayam Kumar's avatar
      Fix Dirichlet.logp (#4454) · 0c21de4f
      Sayam Kumar authored
      * Fix Dirichlet.logp by checking number of categories > 1 only at event dims
      
      * Update test_distributions.py
      
      * Removed the shape validation check to even work for last dimensional shape as 1.
      
      Modified the `test_dirichlet` function to check for the same.
      
      * Added a test to check Dirichlet.logp with different batch shapes.
      
      * Tested exact Dirichlet.logp values againt scipy implementation
      
      Given a mention in RELEASE-NOTES.md
      0c21de4f
  22. 05 Feb, 2021 1 commit
  23. 04 Feb, 2021 2 commits
  24. 03 Feb, 2021 1 commit
  25. 02 Feb, 2021 1 commit
  26. 31 Jan, 2021 2 commits
  27. 29 Jan, 2021 1 commit
  28. 28 Jan, 2021 2 commits