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Transfer of Observations to CES (particular focus on high-dimensional covariances) #384
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #384 +/- ##
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+ Coverage 94.09% 94.24% +0.15%
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Files 10 10
Lines 1625 1807 +182
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+ Hits 1529 1703 +174
- Misses 96 104 +8 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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ArneBouillon
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LGTM
Purpose
Content
For dimension reduction
encoder_kwargs_from(...)utility to easily get theobs_noise_cov,observation,prior_covetc. for dimension reduction in the correct forms (extensible for the likelihood informed quantities)StructureMatrixobjects intoLinearMapobjects.retain_varin situations where not all s.v.s are computedLinearMaps under repeated applicationpredict(...,transform_to_real=true)) the encoded structure matrices are decoded and provided back as full matricesFor MCMC