From 854f346e582d9e81ed81c41e6275c51269cf0d2f Mon Sep 17 00:00:00 2001
From: kohlhaasrebecca <rebecca.kohlhaas@outlook.com>
Date: Wed, 10 Jul 2024 09:35:32 +0200
Subject: [PATCH] User guide for Bayesian Inference
---
...el_comparison.BayesModelComparison.doctree | Bin 87289 -> 86986 bytes
...validrox.bayes_inference.mcmc.MCMC.doctree | Bin 62791 -> 67967 bytes
...x.pylink.pylink.PyLinkForwardModel.doctree | Bin 111332 -> 112974 bytes
...rox.surrogate_models.engine.Engine.doctree | Bin 115431 -> 116640 bytes
...gate_models.exp_designs.ExpDesigns.doctree | Bin 110207 -> 110180 bytes
...gate_models.input_space.InputSpace.doctree | Bin 37739 -> 37712 bytes
..._models.surrogate_models.MetaModel.doctree | Bin 151116 -> 150613 bytes
docs/build/doctrees/bayes_description.doctree | Bin 2983 -> 16927 bytes
docs/build/doctrees/bmc_description.doctree | Bin 0 -> 2910 bytes
docs/build/doctrees/environment.pickle | Bin 3095212 -> 3124130 bytes
docs/build/doctrees/model_description.doctree | Bin 13912 -> 13067 bytes
.../build/doctrees/packagedescription.doctree | Bin 10936 -> 10962 bytes
docs/build/doctrees/post_description.doctree | Bin 14143 -> 13857 bytes
...model_comparison.BayesModelComparison.html | 4 +-
...yesvalidrox.bayes_inference.mcmc.MCMC.html | 26 ++
...drox.pylink.pylink.PyLinkForwardModel.html | 4 +-
...lidrox.surrogate_models.engine.Engine.html | 5 +-
...rrogate_models.exp_designs.ExpDesigns.html | 4 +-
...rrogate_models.input_space.InputSpace.html | 4 +-
...ate_models.surrogate_models.MetaModel.html | 15 +-
.../html/_sources/bayes_description.rst.txt | 65 ++-
.../html/_sources/bmc_description.rst.txt | 7 +
.../html/_sources/model_description.rst.txt | 6 +-
.../html/_sources/packagedescription.rst.txt | 1 +
.../html/_sources/post_description.rst.txt | 8 +-
docs/build/html/bayes_description.html | 98 ++++-
docs/build/html/bmc_description.html | 398 ++++++++++++++++++
docs/build/html/genindex.html | 3 +-
docs/build/html/index.html | 3 +-
docs/build/html/input_description.html | 3 +-
docs/build/html/model_description.html | 9 +-
docs/build/html/objects.inv | Bin 3562 -> 3569 bytes
docs/build/html/packagedescription.html | 6 +-
docs/build/html/post_description.html | 11 +-
docs/build/html/py-modindex.html | 3 +-
docs/build/html/search.html | 3 +-
docs/build/html/searchindex.js | 2 +-
docs/diagrams/bayesian_model_comparison.dot | 18 +
docs/diagrams/bayesian_validation.dot | 3 +
docs/diagrams/class_diagram.py | 82 +++-
docs/source/bayes_description.rst | 93 +++-
docs/source/bmc_description.rst | 7 +
docs/source/model_description.rst | 6 +-
docs/source/packagedescription.rst | 1 +
docs/source/post_description.rst | 8 +-
examples/user_guide/example_user_guide.py | 45 +-
...nce.bayes_inference.BayesInference.doctree | Bin 0 -> 99069 bytes
...ox.bayes_inference.bayes_inference.doctree | Bin 0 -> 5705 bytes
...el_comparison.BayesModelComparison.doctree | Bin 0 -> 86986 bytes
...s_inference.bayes_model_comparison.doctree | Bin 0 -> 5858 bytes
..._inference.discrepancy.Discrepancy.doctree | Bin 0 -> 26382 bytes
...lidrox.bayes_inference.discrepancy.doctree | Bin 0 -> 5669 bytes
.../bayesvalidrox.bayes_inference.doctree | Bin 0 -> 8590 bytes
...validrox.bayes_inference.mcmc.MCMC.doctree | Bin 0 -> 67967 bytes
...bayesvalidrox.bayes_inference.mcmc.doctree | Bin 0 -> 8525 bytes
....bayes_inference.mcmc.gelman_rubin.doctree | Bin 0 -> 8646 bytes
.../_autosummary/bayesvalidrox.doctree | Bin 0 -> 7820 bytes
.../bayesvalidrox.post_processing.doctree | Bin 0 -> 5327 bytes
...ing.post_processing.PostProcessing.doctree | Bin 0 -> 69936 bytes
...ox.post_processing.post_processing.doctree | Bin 0 -> 5800 bytes
.../_autosummary/bayesvalidrox.pylink.doctree | Bin 0 -> 5204 bytes
...x.pylink.pylink.PyLinkForwardModel.doctree | Bin 0 -> 112974 bytes
.../bayesvalidrox.pylink.pylink.doctree | Bin 0 -> 7816 bytes
...alidrox.pylink.pylink.within_range.doctree | Bin 0 -> 7889 bytes
...rrogate_models.adaptPlot.adaptPlot.doctree | Bin 0 -> 6241 bytes
...alidrox.surrogate_models.adaptPlot.doctree | Bin 0 -> 5910 bytes
...ly_construction.apoly_construction.doctree | Bin 0 -> 9342 bytes
...urrogate_models.apoly_construction.doctree | Bin 0 -> 5872 bytes
...es_linear.BayesianLinearRegression.doctree | Bin 0 -> 76316 bytes
...ls.bayes_linear.EBLinearRegression.doctree | Bin 0 -> 116313 bytes
...ls.bayes_linear.VBLinearRegression.doctree | Bin 0 -> 115083 bytes
...drox.surrogate_models.bayes_linear.doctree | Bin 0 -> 11176 bytes
...ate_models.bayes_linear.gamma_mean.doctree | Bin 0 -> 6874 bytes
.../bayesvalidrox.surrogate_models.doctree | Bin 0 -> 22765 bytes
...rox.surrogate_models.engine.Engine.doctree | Bin 0 -> 116640 bytes
...esvalidrox.surrogate_models.engine.doctree | Bin 0 -> 10625 bytes
...e_models.engine.hellinger_distance.doctree | Bin 0 -> 7547 bytes
...rox.surrogate_models.engine.logpdf.doctree | Bin 0 -> 7789 bytes
....surrogate_models.engine.subdomain.doctree | Bin 0 -> 7483 bytes
...rox.surrogate_models.eval_rec_rule.doctree | Bin 0 -> 12970 bytes
...models.eval_rec_rule.eval_rec_rule.doctree | Bin 0 -> 8310 bytes
...l_rec_rule.eval_rec_rule_arbitrary.doctree | Bin 0 -> 8465 bytes
...dels.eval_rec_rule.eval_univ_basis.doctree | Bin 0 -> 9864 bytes
...dels.eval_rec_rule.poly_rec_coeffs.doctree | Bin 0 -> 8916 bytes
...gate_models.exp_designs.ExpDesigns.doctree | Bin 0 -> 110180 bytes
...te_models.exp_designs.check_ranges.doctree | Bin 0 -> 7318 bytes
...idrox.surrogate_models.exp_designs.doctree | Bin 0 -> 8581 bytes
...ate_models.exploration.Exploration.doctree | Bin 0 -> 42181 bytes
...idrox.surrogate_models.exploration.doctree | Bin 0 -> 6053 bytes
...te_models.glexindex.cross_truncate.doctree | Bin 0 -> 12524 bytes
...alidrox.surrogate_models.glexindex.doctree | Bin 0 -> 17512 bytes
...rrogate_models.glexindex.glexindex.doctree | Bin 0 -> 17094 bytes
...gate_models.input_space.InputSpace.doctree | Bin 0 -> 37712 bytes
...idrox.surrogate_models.input_space.doctree | Bin 0 -> 6341 bytes
...drox.surrogate_models.inputs.Input.doctree | Bin 0 -> 17070 bytes
...x.surrogate_models.inputs.Marginal.doctree | Bin 0 -> 12528 bytes
...esvalidrox.surrogate_models.inputs.doctree | Bin 0 -> 7198 bytes
..._pursuit.OrthogonalMatchingPursuit.doctree | Bin 0 -> 102653 bytes
...s.orthogonal_matching_pursuit.corr.doctree | Bin 0 -> 4633 bytes
...models.orthogonal_matching_pursuit.doctree | Bin 0 -> 8517 bytes
...els.reg_fast_ard.RegressionFastARD.doctree | Bin 0 -> 114917 bytes
...drox.surrogate_models.reg_fast_ard.doctree | Bin 0 -> 9316 bytes
...els.reg_fast_ard.update_precisions.doctree | Bin 0 -> 6376 bytes
...fast_laplace.RegressionFastLaplace.doctree | Bin 0 -> 39330 bytes
....surrogate_models.reg_fast_laplace.doctree | Bin 0 -> 5892 bytes
..._models.surrogate_models.MetaModel.doctree | Bin 0 -> 150613 bytes
....surrogate_models.corr_loocv_error.doctree | Bin 0 -> 11892 bytes
...models.surrogate_models.create_psi.doctree | Bin 0 -> 8797 bytes
....surrogate_models.surrogate_models.doctree | Bin 0 -> 12050 bytes
...e_models.gaussian_process_emulator.doctree | Bin 0 -> 11383 bytes
public/.doctrees/al_description.doctree | Bin 0 -> 13400 bytes
public/.doctrees/analyticalfunction.doctree | Bin 0 -> 16622 bytes
public/.doctrees/api.doctree | Bin 0 -> 4596 bytes
public/.doctrees/bayes_description.doctree | Bin 0 -> 20891 bytes
public/.doctrees/beam.doctree | Bin 0 -> 16219 bytes
public/.doctrees/bmc_description.doctree | Bin 0 -> 2910 bytes
public/.doctrees/borehole.doctree | Bin 0 -> 23070 bytes
public/.doctrees/environment.pickle | Bin 0 -> 2959265 bytes
public/.doctrees/examples.doctree | Bin 0 -> 3809 bytes
public/.doctrees/index.doctree | Bin 0 -> 23144 bytes
public/.doctrees/input_description.doctree | Bin 0 -> 23684 bytes
public/.doctrees/ishigami.doctree | Bin 0 -> 19345 bytes
public/.doctrees/model_description.doctree | Bin 0 -> 13067 bytes
public/.doctrees/modelcomparison.doctree | Bin 0 -> 22721 bytes
public/.doctrees/ohaganfunction.doctree | Bin 0 -> 16691 bytes
public/.doctrees/packagedescription.doctree | Bin 0 -> 10962 bytes
public/.doctrees/pollution.doctree | Bin 0 -> 19981 bytes
public/.doctrees/post_description.doctree | Bin 0 -> 13857 bytes
.../.doctrees/surrogate_description.doctree | Bin 0 -> 23453 bytes
public/.doctrees/tutorial.doctree | Bin 0 -> 53798 bytes
...erence.bayes_inference.BayesInference.html | 3 +-
...idrox.bayes_inference.bayes_inference.html | 3 +-
...model_comparison.BayesModelComparison.html | 7 +-
...ayes_inference.bayes_model_comparison.html | 3 +-
...yes_inference.discrepancy.Discrepancy.html | 3 +-
...svalidrox.bayes_inference.discrepancy.html | 3 +-
.../bayesvalidrox.bayes_inference.html | 3 +-
...yesvalidrox.bayes_inference.mcmc.MCMC.html | 29 +-
...rox.bayes_inference.mcmc.gelman_rubin.html | 3 +-
.../bayesvalidrox.bayes_inference.mcmc.html | 3 +-
public/_autosummary/bayesvalidrox.html | 3 +-
.../bayesvalidrox.post_processing.html | 3 +-
...essing.post_processing.PostProcessing.html | 3 +-
...idrox.post_processing.post_processing.html | 3 +-
public/_autosummary/bayesvalidrox.pylink.html | 3 +-
...drox.pylink.pylink.PyLinkForwardModel.html | 7 +-
.../bayesvalidrox.pylink.pylink.html | 3 +-
...esvalidrox.pylink.pylink.within_range.html | 3 +-
....surrogate_models.adaptPlot.adaptPlot.html | 3 +-
...esvalidrox.surrogate_models.adaptPlot.html | 3 +-
...apoly_construction.apoly_construction.html | 3 +-
...x.surrogate_models.apoly_construction.html | 3 +-
...bayes_linear.BayesianLinearRegression.html | 3 +-
...odels.bayes_linear.EBLinearRegression.html | 3 +-
...odels.bayes_linear.VBLinearRegression.html | 3 +-
...rogate_models.bayes_linear.gamma_mean.html | 3 +-
...alidrox.surrogate_models.bayes_linear.html | 3 +-
...lidrox.surrogate_models.engine.Engine.html | 8 +-
...gate_models.engine.hellinger_distance.html | 3 +-
...bayesvalidrox.surrogate_models.engine.html | 3 +-
...lidrox.surrogate_models.engine.logpdf.html | 3 +-
...rox.surrogate_models.engine.subdomain.html | 3 +-
...te_models.eval_rec_rule.eval_rec_rule.html | 3 +-
...eval_rec_rule.eval_rec_rule_arbitrary.html | 3 +-
..._models.eval_rec_rule.eval_univ_basis.html | 3 +-
...lidrox.surrogate_models.eval_rec_rule.html | 3 +-
..._models.eval_rec_rule.poly_rec_coeffs.html | 3 +-
...rrogate_models.exp_designs.ExpDesigns.html | 7 +-
...ogate_models.exp_designs.check_ranges.html | 3 +-
...validrox.surrogate_models.exp_designs.html | 3 +-
...rogate_models.exploration.Exploration.html | 3 +-
...validrox.surrogate_models.exploration.html | 3 +-
...ogate_models.glexindex.cross_truncate.html | 3 +-
....surrogate_models.glexindex.glexindex.html | 3 +-
...esvalidrox.surrogate_models.glexindex.html | 3 +-
.../bayesvalidrox.surrogate_models.html | 3 +-
...rrogate_models.input_space.InputSpace.html | 7 +-
...validrox.surrogate_models.input_space.html | 3 +-
...alidrox.surrogate_models.inputs.Input.html | 3 +-
...drox.surrogate_models.inputs.Marginal.html | 3 +-
...bayesvalidrox.surrogate_models.inputs.html | 3 +-
...ing_pursuit.OrthogonalMatchingPursuit.html | 3 +-
...dels.orthogonal_matching_pursuit.corr.html | 3 +-
...te_models.orthogonal_matching_pursuit.html | 3 +-
...models.reg_fast_ard.RegressionFastARD.html | 3 +-
...alidrox.surrogate_models.reg_fast_ard.html | 3 +-
...models.reg_fast_ard.update_precisions.html | 3 +-
...eg_fast_laplace.RegressionFastLaplace.html | 3 +-
...rox.surrogate_models.reg_fast_laplace.html | 3 +-
...ate_models.surrogate_models.MetaModel.html | 18 +-
...els.surrogate_models.corr_loocv_error.html | 3 +-
...te_models.surrogate_models.create_psi.html | 3 +-
...gate_models.gaussian_process_emulator.html | 3 +-
...rox.surrogate_models.surrogate_models.html | 3 +-
public/_sources/bayes_description.rst.txt | 93 +++-
public/_sources/bmc_description.rst.txt | 7 +
public/_sources/model_description.rst.txt | 6 +-
public/_sources/packagedescription.rst.txt | 1 +
public/_sources/post_description.rst.txt | 8 +-
public/al_description.html | 3 +-
public/analyticalfunction.html | 3 +-
public/api.html | 3 +-
public/bayes_description.html | 126 +++++-
public/beam.html | 3 +-
public/bmc_description.html | 398 ++++++++++++++++++
public/borehole.html | 3 +-
public/examples.html | 3 +-
public/genindex.html | 3 +-
public/index.html | 3 +-
public/input_description.html | 3 +-
public/ishigami.html | 3 +-
public/model_description.html | 9 +-
public/modelcomparison.html | 3 +-
public/objects.inv | Bin 3562 -> 3569 bytes
public/ohaganfunction.html | 3 +-
public/packagedescription.html | 6 +-
public/pollution.html | 3 +-
public/post_description.html | 11 +-
public/py-modindex.html | 3 +-
public/search.html | 3 +-
public/searchindex.js | 2 +-
public/surrogate_description.html | 3 +-
public/tutorial.html | 11 +-
223 files changed, 1717 insertions(+), 214 deletions(-)
create mode 100644 docs/build/doctrees/bmc_description.doctree
create mode 100644 docs/build/html/_sources/bmc_description.rst.txt
create mode 100644 docs/build/html/bmc_description.html
create mode 100644 docs/diagrams/bayesian_model_comparison.dot
create mode 100644 docs/source/bmc_description.rst
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.doctree
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create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.discrepancy.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.doctree
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create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.doctree
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create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.pylink.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.pylink.pylink.doctree
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create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.doctree
create mode 100644 public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.doctree
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create mode 100644 public/_sources/bmc_description.rst.txt
create mode 100644 public/bmc_description.html
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diff --git a/docs/build/doctrees/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.doctree b/docs/build/doctrees/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.doctree
index 0eadb31a4c12108b93f29dd90d78aa1ab60a6449..f7079c9804bd84e0a6882a2b63c4af54fa843ec9 100644
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diff --git a/docs/build/doctrees/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.doctree b/docs/build/doctrees/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.doctree
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diff --git a/docs/build/doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.doctree b/docs/build/doctrees/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.doctree
index 81fa2a1d8dbb91bd830596c9ec8704db54a7235e..85e5048e6702e173fbf5eec5bcb177eb2c2686f2 100644
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index 5650a86ee63013f3fdce3fa09acdb5b73ffd161c..308a36773813ec6eeff34f8fc2e555211ad6a0d7 100644
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index cae46fd3422bafecf80b68c0410a345687b1a617..6cead39f28cd54d324538feb50417014b8a947db 100644
GIT binary patch
delta 151
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index 4d062650a16e06598bac73b9516fc01db5ed2eb1..d8ac431ddf19c175a13a546a445af6960141548c 100644
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diff --git a/docs/build/doctrees/bayes_description.doctree b/docs/build/doctrees/bayes_description.doctree
index 5d94ed288d0b4868bf27b5fb62061007e2756913..c98ceb2eb03163cb759d71f1023fd5d1ef36aff3 100644
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diff --git a/docs/build/doctrees/model_description.doctree b/docs/build/doctrees/model_description.doctree
index 0e9325ae7d2b2dc814460fd4255f705942f3f2a6..d5ddd83b22705a3d1377a224632a476f2d1f02e8 100644
GIT binary patch
delta 1591
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delta 2037
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diff --git a/docs/build/doctrees/packagedescription.doctree b/docs/build/doctrees/packagedescription.doctree
index d0d927b72bae6c2515e380a6dc4861dd9ac39d5f..38b5cbd7ea50fbbf4b6ccf407b7dedfcc50c1019 100644
GIT binary patch
delta 130
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diff --git a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
index 2b9f5ffba..b2a554f9d 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
@@ -388,7 +388,7 @@
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_bayes_factor</span></code></a>(BME_dict[, plot_name])</p></td>
<td><p>Plots the Bayes factor distibutions in a <span class="math notranslate nohighlight">\(N_m \times N_m\)</span> matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the number of the models.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>(model_weights_dict)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>()</p></td>
<td><p>Visualizes the confusion matrix and the model wights for the justifiability analysis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_model_weights</span></code></a>(model_weights, plot_name)</p></td>
@@ -559,7 +559,7 @@ matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the n
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis">
-<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_weights_dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
<dd><p>Visualizes the confusion matrix and the model wights for the
justifiability analysis.</p>
<section id="id13">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
index 1c766909b..582ffdbf1 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
@@ -362,6 +362,32 @@ science, 5(1), pp.65-80.</p>
<dl class="simple">
<dt>BayesOpts<span class="classifier">obj</span></dt><dd><p>Bayes object.</p>
</dd>
+<dt>engine<span class="classifier">bayesvalidrox.Engine</span></dt><dd><p>Engine object that contains the surrogate, model and expdesign</p>
+</dd>
+<dt>mcmc_params<span class="classifier">dict</span></dt><dd><p>Dictionary of parameters for the mcmc. Required are
+- init_samples
+- n_steps
+- n_walkers
+- n_burn
+- moves
+- multiplrocessing
+- verbose</p>
+</dd>
+<dt>Discrepancy<span class="classifier">bayesvalidrox.Discrepancy</span></dt><dd><p>Discrepancy object that described the uncertainty of the data.</p>
+</dd>
+</dl>
+<p>bias_inputs :</p>
+<p>error_model :</p>
+<p>req_outputs :</p>
+<p>selected_indices :</p>
+<p>emulator :</p>
+<dl class="simple">
+<dt>out_dir<span class="classifier">string</span></dt><dd><p>Directory to write the outputs to.</p>
+</dd>
+<dt>name<span class="classifier">string</span></dt><dd><p>Name of this MCMC selection (?)</p>
+</dd>
+<dt>BiasInputs<span class="classifier"></span></dt><dd><p>The default is None.</p>
+</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.mcmc.MCMC.__init__">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html b/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
index 868fd8032..312c77782 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
@@ -339,7 +339,7 @@
<h1>bayesvalidrox.pylink.pylink.PyLinkForwardModel<a class="headerlink" href="#bayesvalidrox-pylink-pylink-pylinkforwardmodel" title="Link to this heading">¶</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>A forward model binder</p>
<p>This calss serves as a code wrapper. This wrapper allows the execution of
@@ -428,7 +428,7 @@ This is only available for one output.</p>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__">
-<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
<dd></dd></dl>
<p class="rubric">Methods</p>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
index d9bc2a754..563940f5f 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
@@ -465,7 +465,7 @@ Run_No : int</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel">
-<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parallel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
<dd><p>Evaluates metamodel at the requested samples. One can also generate
nsamples.</p>
<section id="id3">
@@ -481,6 +481,9 @@ default is None.</p>
</dd>
<dt>return_samples<span class="classifier">bool, optional</span></dt><dd><p>Retun samples, if no <cite>samples</cite> is provided. The default is False.</p>
</dd>
+<dt>parallel<span class="classifier">bool, optional</span></dt><dd><p>Set to true if the evaluations should be done in parallel.
+The default is False.</p>
+</dd>
</dl>
</section>
<section id="id4">
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
index 78f9787e1..6548c9a39 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
@@ -560,12 +560,12 @@ the MetaModel object.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
<dd><p>Initializes parameter space.</p>
<section id="id6">
<h3>Parameters<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
</dd>
</dl>
</section>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
index b5eb76fa2..842557588 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
@@ -417,12 +417,12 @@ the MetaModel object.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
<dd><p>Initializes parameter space.</p>
<section id="id2">
<h3>Parameters<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
</dd>
</dl>
</section>
diff --git a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
index 49744e809..07bf13ba0 100644
--- a/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
+++ b/docs/build/html/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
@@ -449,8 +449,8 @@ For experimental design refer to <cite>InputSpace</cite>.</p>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_polynomials</span></code></a>([max_deg])</p></td>
<td><p>Generates (univariate) polynomials.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target[, verbose])</p></td>
-<td><p>Transforms the targets (outputs) via Principal Component Analysis</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target)</p></td>
+<td><p>Transforms the targets (outputs) via Principal Component Analysis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression"><code class="xref py py-obj docutils literal notranslate"><span class="pre">regression</span></code></a>(X, y, basis_indices[, ...])</p></td>
<td><p>Fit regression using the regression method provided.</p></td>
@@ -720,16 +720,15 @@ The default is False.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation">
-<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
-<dd><p>Transforms the targets (outputs) via Principal Component Analysis</p>
+<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
+<dd><p>Transforms the targets (outputs) via Principal Component Analysis.
+The number of features is set by <cite>self.n_pca_components</cite>.
+If this is not given, <cite>self.var_pca_threshold</cite> is used as a threshold.</p>
<section id="id14">
<h3>Parameters<a class="headerlink" href="#id14" title="Link to this heading">¶</a></h3>
<dl class="simple">
<dt>target<span class="classifier">array of shape (n_samples,)</span></dt><dd><p>Target values.</p>
</dd>
-<dt>verbose<span class="classifier">bool</span></dt><dd><p>Set to True to get more information during functtion call.
-The default is False.</p>
-</dd>
</dl>
</section>
<section id="id15">
@@ -804,7 +803,7 @@ for the fast version of the bootstrapping.</p>
<section id="id20">
<h3>Parameters<a class="headerlink" href="#id20" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set.</p>
+<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set. These samples should be already transformed.</p>
</dd>
<dt>y<span class="classifier">array of shape (n_samples, n_outs)</span></dt><dd><p>The (transformed) model responses.</p>
</dd>
diff --git a/docs/build/html/_sources/bayes_description.rst.txt b/docs/build/html/_sources/bayes_description.rst.txt
index 2cfd3a6a8..0406162ed 100644
--- a/docs/build/html/_sources/bayes_description.rst.txt
+++ b/docs/build/html/_sources/bayes_description.rst.txt
@@ -1,7 +1,62 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
+ .. container:: leftside
+
+ With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+ Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+ The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+ MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include
+
+ * ``init_samples``: initial samples
+ * ``n_steps``: number of steps
+ * ``n_walkers``: number of walkers
+ * ``n_burn``: length of the burn-in
+ * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+ * ``multiprocessing``: setting for multiprocessing
+ * ``verbose``: verbosity
+
+ .. container:: rightside
+
+ .. image:: ../diagrams/bayesian_validation.png
+ :width: 300
+ :alt: UML diagram for classes related to Bayesian inference.
+
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>> if key == 'x_values':
+>>> Model.observations[key]=observation[key]
+>>> else:
+>>> Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
-.. image:: ../diagrams/bayesian_validation.png
- :width: 300
- :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
diff --git a/docs/build/html/_sources/bmc_description.rst.txt b/docs/build/html/_sources/bmc_description.rst.txt
new file mode 100644
index 000000000..10e73bd1e
--- /dev/null
+++ b/docs/build/html/_sources/bmc_description.rst.txt
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+ :width: 400
+ :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/docs/build/html/_sources/model_description.rst.txt b/docs/build/html/_sources/model_description.rst.txt
index bb719886b..923f20a7c 100644
--- a/docs/build/html/_sources/model_description.rst.txt
+++ b/docs/build/html/_sources/model_description.rst.txt
@@ -6,10 +6,10 @@ Models
.. container:: leftside
BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
- Its main function is to run the model on given samples and to read in and contain MC references and observations.
+ Its main function is to run the model on given samples and to read in and contain MC references and observations.
- Models can be defined via python functions, shell commands or as general executables.
- This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+ Models can be defined via python functions, shell commands or as general executables.
+ This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
.. container:: rightside
diff --git a/docs/build/html/_sources/packagedescription.rst.txt b/docs/build/html/_sources/packagedescription.rst.txt
index f245959b8..1d1fd6517 100644
--- a/docs/build/html/_sources/packagedescription.rst.txt
+++ b/docs/build/html/_sources/packagedescription.rst.txt
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
al_description
post_description
bayes_description
+ bmc_description
diff --git a/docs/build/html/_sources/post_description.rst.txt b/docs/build/html/_sources/post_description.rst.txt
index af2172709..987f18e7d 100644
--- a/docs/build/html/_sources/post_description.rst.txt
+++ b/docs/build/html/_sources/post_description.rst.txt
@@ -4,11 +4,11 @@ Postprocessing
.. container:: leftside
- Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
- The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+ Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+ The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
- * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
- * ``check_accuracy``: computing the RMSE error of the surrogate model
+ * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+ * ``check_accuracy``: computing the RMSE error of the surrogate model
.. container:: rightside
diff --git a/docs/build/html/bayes_description.html b/docs/build/html/bayes_description.html
index 62bb18a5a..4d5cfd6c6 100644
--- a/docs/build/html/bayes_description.html
+++ b/docs/build/html/bayes_description.html
@@ -3,10 +3,10 @@
<head><meta charset="utf-8"/>
<meta name="viewport" content="width=device-width,initial-scale=1"/>
<meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="TUTORIAL" href="tutorial.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian multi-model comparison" href="bmc_description.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
<!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
- <title>Bayesian inference and multi-model comparison - bayesvalidrox 1.0.0 documentation</title>
+ <title>Bayesian inference - bayesvalidrox 1.0.0 documentation</title>
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@@ -141,7 +141,7 @@
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
- <label class="toc-overlay-icon toc-header-icon no-toc" for="__toc">
+ <label class="toc-overlay-icon toc-header-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
</label>
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -329,15 +330,71 @@
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
- <label class="toc-overlay-icon toc-content-icon no-toc" for="__toc">
+ <label class="toc-overlay-icon toc-content-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
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<article role="main">
- <section id="bayesian-inference-and-multi-model-comparison">
-<h1>Bayesian inference and multi-model comparison<a class="headerlink" href="#bayesian-inference-and-multi-model-comparison" title="Link to this heading">¶</a></h1>
-<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference and multi-model comparison." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+ <section id="bayesian-inference">
+<h1>Bayesian inference<a class="headerlink" href="#bayesian-inference" title="Link to this heading">¶</a></h1>
+<div class="twocol docutils container">
+<div class="leftside docutils container">
+<p>With Bayesian inference we ask the question ‘how does our understanding of the inputs change given some observation of the outputs of the model?’, i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+Bayesvalidrox provides a dedicated class to perform this task, <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a>, which infers the posterior via <code class="docutils literal notranslate"><span class="pre">rejection-sampling</span></code> or <code class="docutils literal notranslate"><span class="pre">MCMC</span></code>.
+The likelihood in rejection sampling is estimated with the help of <code class="docutils literal notranslate"><span class="pre">bootstrapping</span></code>.
+MCMC-specific parameters are to be given as a dictionary called <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code> and can include</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">init_samples</span></code>: initial samples</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_steps</span></code>: number of steps</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_walkers</span></code>: number of walkers</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_burn</span></code>: length of the burn-in</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">moves</span></code>: function to use for the moves, e.g. taken from <code class="docutils literal notranslate"><span class="pre">emcee</span></code></p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code>: setting for multiprocessing</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">verbose</span></code>: verbosity</p></li>
+</ul>
+</div>
+<div class="rightside docutils container">
+<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+</div>
+</div>
+<p>The observation should be set as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code> in the <code class="docutils literal notranslate"><span class="pre">Engine</span></code>, and an estimation of its uncertainty can be provided as a <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a> object.</p>
+<section id="example">
+<h2>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h2>
+<p>For this example we need to add the following imports.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">bayesvalidrox</span> <span class="kn">import</span> <span class="n">Discrepancy</span><span class="p">,</span> <span class="n">BayesInference</span>
+</pre></div>
+</div>
+<p>In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code>.
+As this expects a 1D-array for each output key, we need to change the format slightly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">true_sample</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">2</span><span class="p">]]</span>
+<span class="gp">>>> </span><span class="n">observation</span> <span class="o">=</span> <span class="n">Model</span><span class="o">.</span><span class="n">run_model_parallel</span><span class="p">(</span><span class="n">true_sample</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span> <span class="o">=</span> <span class="p">{}</span>
+<span class="gp">>>> </span><span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">observation</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="k">if</span> <span class="n">key</span> <span class="o">==</span> <span class="s1">'x_values'</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
+<span class="gp">>>> </span> <span class="k">else</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+</pre></div>
+</div>
+<p>Next we define the uncertainty on the observation with the class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a>.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The <code class="docutils literal notranslate"><span class="pre">parameters</span></code> contain the variance for each point in the observation.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">obsData</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">Model</span><span class="o">.</span><span class="n">Output</span><span class="o">.</span><span class="n">names</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span> <span class="o">=</span> <span class="n">Discrepancy</span><span class="p">(</span><span class="s1">''</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">'Gaussian'</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">obsData</span><span class="o">**</span><span class="mi">2</span>
+</pre></div>
+</div>
+<p>Now we can initialize an object of class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a> with all the wanted properties.
+This object has to be given our <code class="docutils literal notranslate"><span class="pre">Engine</span></code>.
+If it should use the surrogate during inference, set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to <code class="docutils literal notranslate"><span class="pre">True</span></code>, otherwise the model will be evaluated directly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">BayesObj</span> <span class="o">=</span> <span class="n">BayesInference</span><span class="p">(</span><span class="n">Engine_</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">emulator</span> <span class="o">=</span> <span class="kc">True</span>
+</pre></div>
+</div>
+</section>
</section>
</article>
@@ -345,12 +402,12 @@
<footer>
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- <a class="next-page" href="tutorial.html">
+ <a class="next-page" href="bmc_description.html">
<div class="page-info">
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</div>
- <div class="title">TUTORIAL</div>
+ <div class="title">Bayesian multi-model comparison</div>
</div>
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@@ -383,9 +440,28 @@
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- <aside class="toc-drawer no-toc">
+ <aside class="toc-drawer">
+ <div class="toc-sticky toc-scroll">
+ <div class="toc-title-container">
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+ On this page
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+ <div class="toc-tree-container">
+ <div class="toc-tree">
+ <ul>
+<li><a class="reference internal" href="#">Bayesian inference</a><ul>
+<li><a class="reference internal" href="#example">Example</a></li>
+</ul>
+</li>
+</ul>
+
+ </div>
+ </div>
+ </div>
+
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diff --git a/docs/build/html/bmc_description.html b/docs/build/html/bmc_description.html
new file mode 100644
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@@ -0,0 +1,398 @@
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+
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+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html">bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace</a></li>
+</ul>
+</li>
+<li class="toctree-l4 has-children"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html">bayesvalidrox.surrogate_models.surrogate_models</a><input class="toctree-checkbox" id="toctree-checkbox-28" name="toctree-checkbox-28" role="switch" type="checkbox"/><label for="toctree-checkbox-28"><div class="visually-hidden">Toggle navigation of bayesvalidrox.surrogate_models.surrogate_models</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html">bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html">bayesvalidrox.surrogate_models.surrogate_models.create_psi</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html">bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator</a></li>
+<li class="toctree-l5"><a class="reference internal" href="_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html">bayesvalidrox.surrogate_models.surrogate_models.MetaModel</a></li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
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+ <article role="main">
+ <section id="bayesian-multi-model-comparison">
+<h1>Bayesian multi-model comparison<a class="headerlink" href="#bayesian-multi-model-comparison" title="Link to this heading">¶</a></h1>
+<a class="reference internal image-reference" href="_images/bayesian_model_comparison.png"><img alt="UML diagram for classes related to Bayesian multi-model comparison." src="_images/bayesian_model_comparison.png" style="width: 400px;" /></a>
+</section>
+
+ </article>
+ </div>
+ <footer>
+
+ <div class="related-pages">
+ <a class="next-page" href="tutorial.html">
+ <div class="page-info">
+ <div class="context">
+ <span>Next</span>
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+ <div class="title">TUTORIAL</div>
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+ <a class="prev-page" href="bayes_description.html">
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diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index 2b0791a3b..67a702598 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -168,7 +168,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index 460cf3cb7..dcad29fd0 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/input_description.html b/docs/build/html/input_description.html
index 39e16d2b9..15276ff89 100644
--- a/docs/build/html/input_description.html
+++ b/docs/build/html/input_description.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/model_description.html b/docs/build/html/model_description.html
index 2dbaeed95..da41e4667 100644
--- a/docs/build/html/model_description.html
+++ b/docs/build/html/model_description.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -339,12 +340,10 @@
<h1>Models<a class="headerlink" href="#models" title="Link to this heading">¶</a></h1>
<div class="twocol docutils container">
<div class="leftside docutils container">
-<dl>
-<dt>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.</dt><dd><p>Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
+<p>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.
+Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
<p>Models can be defined via python functions, shell commands or as general executables.
This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.</p>
-</dd>
-</dl>
</div>
<div class="rightside docutils container">
<a class="reference internal image-reference" href="_images/model.png"><img alt="UML diagram for the bayesvalidrox class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`." src="_images/model.png" style="width: 150px;" /></a>
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index c76923ed2..875119c27 100644
--- a/docs/build/html/packagedescription.html
+++ b/docs/build/html/packagedescription.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -382,7 +383,8 @@ If multiple (surrogate) models are given, they can be compared against each othe
<li class="toctree-l1"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l1"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l1"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</div>
</section>
diff --git a/docs/build/html/post_description.html b/docs/build/html/post_description.html
index d5eb2c29e..33fa48a7a 100644
--- a/docs/build/html/post_description.html
+++ b/docs/build/html/post_description.html
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<meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
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+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian inference" href="bayes_description.html" /><link rel="prev" title="Active learning: iteratively expanding the training set" href="al_description.html" />
<!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
<title>Postprocessing - bayesvalidrox 1.0.0 documentation</title>
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -341,12 +342,10 @@
<div class="leftside docutils container">
<p>Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
The BayesValidRox class <a class="reference internal" href="_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html#bayesvalidrox.post_processing.post_processing.PostProcessing" title="bayesvalidrox.post_processing.post_processing.PostProcessing"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.post_processing.post_processing.PostProcessing</span></code></a> includes functions that are applicable to all types of surrogate model.</p>
-<blockquote>
-<div><ul class="simple">
+<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">valid_metamodel</span></code>: visualizing some metamodel runs against the corresponding model runs</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">check_accuracy</span></code>: computing the RMSE error of the surrogate model</p></li>
</ul>
-</div></blockquote>
</div>
<div class="rightside docutils container">
<a class="reference internal image-reference" href="_images/postprocessing.png"><img alt="UML diagram for the classes and functions used in active learning in BayesValidRox." src="_images/postprocessing.png" style="width: 300px;" /></a>
@@ -407,7 +406,7 @@ The BayesValidRox class <a class="reference internal" href="_autosummary/bayesva
<div class="context">
<span>Next</span>
</div>
- <div class="title">Bayesian inference and multi-model comparison</div>
+ <div class="title">Bayesian inference</div>
</div>
<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
</a>
diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index a10614c9b..9246a7ee0 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -168,7 +168,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/search.html b/docs/build/html/search.html
index 8fe37498e..5e4d1ba20 100644
--- a/docs/build/html/search.html
+++ b/docs/build/html/search.html
@@ -167,7 +167,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index 3aaa01c41..fec129dec 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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"update_precis": 56, "user": 78, "valid": 72, "vblinearregress": 26, "within_rang": 17}})
\ No newline at end of file
diff --git a/docs/diagrams/bayesian_model_comparison.dot b/docs/diagrams/bayesian_model_comparison.dot
new file mode 100644
index 000000000..7ed29281a
--- /dev/null
+++ b/docs/diagrams/bayesian_model_comparison.dot
@@ -0,0 +1,18 @@
+digraph pyUML {
+ExpDesigns [label="{ExpDesigns||}", shape=record];
+PyLinkForwardModel [label="{PyLinkForwardModel||}", shape=record];
+MetaModel [label="{MetaModel||}", shape=record];
+Engine [label="{Engine||}", shape=record];
+Engine -> PyLinkForwardModel [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Engine -> ExpDesigns [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Engine -> MetaModel [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+Discrepancy [label="{Discrepancy||}", shape=record];
+BayesInference [label="{BayesInference||}", shape=record];
+BayesInference -> Engine [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+BayesInference -> Discrepancy [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC [label="{MCMC||}", shape=record];
+BayesInference -> MCMC [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC -> Discrepancy [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+BayesianModelComparison [label="{BayesianModelComparison|+ justifiability : bool\l+ perturbed_data : array\l+ n_bootstrap : int\l+ data_noise_level : float\l+ use_Bayes_settings : bool\l+ emulator : bool\l+ out_dir : string\l|+ setup()\l+ model_comparison_all()\l+ calc_bayes_factors\l+ calc_model_weights()\l+ calc_justifiability_analysis()\l+ generate_dataset()\l+ perturb_data()\l+ cal_model_weight()\l+ plot_just_analysis()\l+ plot_model_weights()\l+ plot_bayes_factor()\l}", shape=record];
+BayesianModelComparison -> BayesInference [arrowtail=diamond, dir=back, headlabel="\n1..*", taillabel="\n1"];
+}
diff --git a/docs/diagrams/bayesian_validation.dot b/docs/diagrams/bayesian_validation.dot
index 46814289b..1e66b0c1a 100644
--- a/docs/diagrams/bayesian_validation.dot
+++ b/docs/diagrams/bayesian_validation.dot
@@ -10,4 +10,7 @@ Discrepancy [label="{Discrepancy||}", shape=record];
BayesInference [label="{BayesInference|+ engine : Engine\l+ discrepancy : Discrepancy\l+ emulator : bool\l+ name : string\l+ bootatrap : bool\l+ req_outputs : list\l+ selected_indices : list\l+ prior_samples : array\l+ n_prior_samples : int\l+ measured_data : dict\l+ inference_method : string\l+ mcmc_params : dict\l+ bayes_loocv : bool\l+ n_bootstrap_itrs : int\l+ perturbed_data : lsit\l+ bootstrap_noise : double\l+ just_analysis : bool\l+ valid_metrics : list\l+ plot_post_pred : bool\l+ plot_map_pred : bool\l+ max_a_posteriori : string\l+ corner_title_fmt : string\l+ out_dir : string\l+ bmc : bool\l|+ setup_inference()\l+ create_inference()\l+ create_error_model()\l+ perform_bootstrap()\l+ _perturb_data()\l+ _eval_model()\l+ normpdf()\l+ _coor_Factor_BME()\l+ _rejection_sampling()\l+ _posterior_predictive()\l+ _plot_max_a_posteriori()\l+ plot_post_params()\l+ plot_log_BME()\l+ _plot_post_predictive()\l}", shape=record];
BayesInference -> Engine [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
BayesInference -> Discrepancy [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC [label="{MCMC|+ engine : Engine\l+ mcmc_params : dict\l+ Discrepancy : Discrepancy\l+ bias_inputs : dict\l+ error_model : MetaModel\l+ req_outputs : list\l+ selected_indices : array\l+ emulator : bool\l+ out_dir : string\l+ name : string\l|+ run_sampler()\l+ log_prior()\l+ log_likelihood()\l+ log_posterior()\l+ eval_model()\l+ train_error_model()\l+ normpdf()\l}", shape=record];
+BayesInference -> MCMC [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
+MCMC -> Discrepancy [arrowtail=diamond, dir=back, headlabel="\n1", taillabel="\n1"];
}
diff --git a/docs/diagrams/class_diagram.py b/docs/diagrams/class_diagram.py
index 71567b361..3c9e17b18 100644
--- a/docs/diagrams/class_diagram.py
+++ b/docs/diagrams/class_diagram.py
@@ -672,7 +672,6 @@ def generate_al_uml():
print_and_save(graph, 'active_learning')
-
def generate_al_uml_reduced():
"""
Generates the uml for active learning
@@ -868,11 +867,87 @@ def generate_bayes_uml():
graph.add_composition(engine, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
graph.add_composition(disc, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
+ # MCMC class
+ mcmc = UMLClass('MCMC',
+ attributes = {
+ 'engine':'Engine',
+ 'mcmc_params':'dict',
+ 'Discrepancy':'Discrepancy',
+ 'bias_inputs':'dict',
+ 'error_model':'MetaModel',
+ 'req_outputs':'list',
+ 'selected_indices':'array',
+ 'emulator':'bool',
+ 'out_dir':'string',
+ 'name':'string',
+ },
+ methods = [
+ 'run_sampler()', 'log_prior()', 'log_likelihood()',
+ 'log_posterior()', 'eval_model()', 'train_error_model()',
+ 'normpdf()'
+ ]
+ )
+ graph.add_class(mcmc)
+ graph.add_composition(mcmc, bayesinf, multiplicity_parent=1, multiplicity_child=1)
+ graph.add_composition(disc, mcmc, multiplicity_parent=1, multiplicity_child=1)
+
print_and_save(graph, 'bayesian_validation')
+
+def generate_bmc_uml():
+ graph = Graph('pyUML')
+
+ expdesign = UMLClass('ExpDesigns')
+ graph.add_class(expdesign)
+
+ model = UMLClass('PyLinkForwardModel')
+ graph.add_class(model)
+
+ metamod = UMLClass('MetaModel')
+ graph.add_class(metamod)
+
+ engine = UMLClass('Engine')
+ graph.add_class(engine)
+ graph.add_composition(model, engine, multiplicity_parent = 1, multiplicity_child = 1)
+ graph.add_composition(expdesign, engine, multiplicity_parent = 1, multiplicity_child = 1)
+ graph.add_composition(metamod, engine, multiplicity_parent = 1, multiplicity_child = 1)
-
+ disc = UMLClass('Discrepancy')
+ graph.add_class(disc)
+
+ bayesinf = UMLClass('BayesInference')
+ graph.add_class(bayesinf)
+ graph.add_composition(engine, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
+ graph.add_composition(disc, bayesinf, multiplicity_parent = 1, multiplicity_child = 1)
+ # MCMC class
+ mcmc = UMLClass('MCMC')
+ graph.add_class(mcmc)
+ graph.add_composition(mcmc, bayesinf, multiplicity_parent=1, multiplicity_child=1)
+ graph.add_composition(disc, mcmc, multiplicity_parent=1, multiplicity_child=1)
+
+
+ # BMC
+ bmc = UMLClass('BayesianModelComparison',
+ attributes = {'justifiability':'bool',
+ 'perturbed_data':'array',
+ 'n_bootstrap':'int',
+ 'data_noise_level':'float',
+ 'use_Bayes_settings':'bool',
+ 'emulator':'bool',
+ 'out_dir':'string'
+ },
+ methods = ['setup()', 'model_comparison_all()','calc_bayes_factors',
+ 'calc_model_weights()', 'calc_justifiability_analysis()',
+ 'generate_dataset()', 'perturb_data()','cal_model_weight()',
+ 'plot_just_analysis()','plot_model_weights()', 'plot_bayes_factor()']
+ )
+ graph.add_class(bmc)
+ graph.add_composition(bayesinf, bmc, multiplicity_parent=1, multiplicity_child='1..*')
+
+ print_and_save(graph, 'bayesian_model_comparison')
+
+
if __name__ == '__main__':
generate_input_uml()
@@ -883,4 +958,5 @@ if __name__ == '__main__':
generate_al_uml()
generate_al_uml_reduced()
generate_postprocessing_uml()
- generate_bayes_uml()
\ No newline at end of file
+ generate_bayes_uml()
+ generate_bmc_uml()
\ No newline at end of file
diff --git a/docs/source/bayes_description.rst b/docs/source/bayes_description.rst
index 2cfd3a6a8..1c72a3e99 100644
--- a/docs/source/bayes_description.rst
+++ b/docs/source/bayes_description.rst
@@ -1,7 +1,90 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
+ .. container:: leftside
+
+ With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+ Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+ The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+ MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include
+
+ * ``init_samples``: initial samples
+ * ``n_steps``: number of steps
+ * ``n_walkers``: number of walkers
+ * ``n_burn``: length of the burn-in
+ * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+ * ``multiprocessing``: setting for multiprocessing
+ * ``verbose``: verbosity
+
+ .. container:: rightside
+
+ .. image:: ../diagrams/bayesian_validation.png
+ :width: 300
+ :alt: UML diagram for classes related to Bayesian inference.
-.. image:: ../diagrams/bayesian_validation.png
- :width: 300
- :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>> if key == 'x_values':
+>>> Model.observations[key]=observation[key]
+>>> else:
+>>> Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+We also set the defined ``Discrepancy``. and set ``post_plot_pred`` if posterior predictions should be visualized.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
+>>> BayesObj.Discrepancy = DiscrepancyOpts
+>>> BayesObj.plot_post_pred = True
+
+In order to run with rejection sampling, we set the ``inference_method`` accordingly and add properties for ``bootstrap``.
+
+>>> BayesObj.inference_method = 'rejection'
+>>> BayesObj.bootstrap = True
+>>> BayesObj.n_bootstrap_itrs = 500
+>>> BayesObj.bootstrap_noise = 2
+
+If the sampling should be done with MCMC, then this is set as the ``inference_method`` and additional properties are given in ``mcmc_params``.
+For this example we use the python package ``emcee`` to define the MCMC moves.
+
+>>> BayesObj.inference_method = 'MCMC'
+>>> import emcee
+>>> BayesObj.mcmc_params = {
+>>> 'n_steps': 1e4,#5,
+>>> 'n_walkers': 30,
+>>> 'moves': emcee.moves.KDEMove(),
+>>> 'multiprocessing': False,
+>>> 'verbose': False
+>>> }
+
+Then we run the inference.
+
+>>> BayesObj.create_inference()
+
+If the output directory ``BayesObj.out_dir`` is not set otherwise, the outputs are written into the folder ``
\ No newline at end of file
diff --git a/docs/source/bmc_description.rst b/docs/source/bmc_description.rst
new file mode 100644
index 000000000..10e73bd1e
--- /dev/null
+++ b/docs/source/bmc_description.rst
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+ :width: 400
+ :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/docs/source/model_description.rst b/docs/source/model_description.rst
index bb719886b..923f20a7c 100644
--- a/docs/source/model_description.rst
+++ b/docs/source/model_description.rst
@@ -6,10 +6,10 @@ Models
.. container:: leftside
BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
- Its main function is to run the model on given samples and to read in and contain MC references and observations.
+ Its main function is to run the model on given samples and to read in and contain MC references and observations.
- Models can be defined via python functions, shell commands or as general executables.
- This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+ Models can be defined via python functions, shell commands or as general executables.
+ This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
.. container:: rightside
diff --git a/docs/source/packagedescription.rst b/docs/source/packagedescription.rst
index f245959b8..1d1fd6517 100644
--- a/docs/source/packagedescription.rst
+++ b/docs/source/packagedescription.rst
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
al_description
post_description
bayes_description
+ bmc_description
diff --git a/docs/source/post_description.rst b/docs/source/post_description.rst
index af2172709..987f18e7d 100644
--- a/docs/source/post_description.rst
+++ b/docs/source/post_description.rst
@@ -4,11 +4,11 @@ Postprocessing
.. container:: leftside
- Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
- The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+ Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+ The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
- * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
- * ``check_accuracy``: computing the RMSE error of the surrogate model
+ * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+ * ``check_accuracy``: computing the RMSE error of the surrogate model
.. container:: rightside
diff --git a/examples/user_guide/example_user_guide.py b/examples/user_guide/example_user_guide.py
index f118d05a6..3be56216f 100644
--- a/examples/user_guide/example_user_guide.py
+++ b/examples/user_guide/example_user_guide.py
@@ -21,6 +21,9 @@ from bayesvalidrox.surrogate_models.surrogate_models import MetaModel
from bayesvalidrox.surrogate_models.engine import Engine
from bayesvalidrox.post_processing.post_processing import PostProcessing
+from bayesvalidrox.bayes_inference.bayes_inference import BayesInference
+from bayesvalidrox.bayes_inference.discrepancy import Discrepancy
+
if __name__ == '__main__':
#### Priors, input space and experimental design
version = 1
@@ -100,4 +103,44 @@ if __name__ == '__main__':
PostProc.check_accuracy(n_samples=10)
PostProc.plot_moments()
PostProc.sobol_indices()
- PostProc.plot_seq_design_diagnostics()
\ No newline at end of file
+ PostProc.plot_seq_design_diagnostics()
+
+ #### Bayesian inference
+ true_sample = [[2]]
+ observation, sample = Model.run_model_parallel(true_sample)
+ Model.observations = {}
+ for key in observation:
+ if key == 'x_values':
+ Model.observations[key]=observation[key]
+ else:
+ Model.observations[key]=observation[key][0]
+
+
+ obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+ DiscrepancyOpts = Discrepancy('')
+ DiscrepancyOpts.type = 'Gaussian'
+ DiscrepancyOpts.parameters = obsData**2
+
+
+ BayesObj = BayesInference(Engine_)
+ BayesObj.emulator = True
+ BayesObj.Discrepancy = DiscrepancyOpts
+ BayesObj.plot_post_pred = True
+
+ BayesObj.bootstrap = True
+ BayesObj.n_bootstrap_itrs = 500
+
+ BayesObj.inference_method = 'MCMC'#"MCMC"
+ import emcee
+ BayesObj.mcmc_params = {
+ 'n_steps': 1e4,
+ 'n_walkers': 30,
+ 'moves': emcee.moves.KDEMove(),
+ 'multiprocessing': False,
+ 'verbose': False
+ }
+
+ BayesObj.create_inference()
+
+
+
\ No newline at end of file
diff --git a/public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.doctree b/public/.doctrees/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.doctree
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diff --git a/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.doctree b/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.doctree
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diff --git a/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.doctree b/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.doctree
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diff --git a/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.doctree b/public/.doctrees/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.doctree
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diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
index a8fbf9952..d6ae664d3 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
index d5f4bdc76..be2a80de6 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_inference.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
index 2b9f5ffba..8c36c6bea 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -388,7 +389,7 @@
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_bayes_factor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_bayes_factor</span></code></a>(BME_dict[, plot_name])</p></td>
<td><p>Plots the Bayes factor distibutions in a <span class="math notranslate nohighlight">\(N_m \times N_m\)</span> matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the number of the models.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>(model_weights_dict)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_just_analysis</span></code></a>()</p></td>
<td><p>Visualizes the confusion matrix and the model wights for the justifiability analysis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights" title="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_model_weights"><code class="xref py py-obj docutils literal notranslate"><span class="pre">plot_model_weights</span></code></a>(model_weights, plot_name)</p></td>
@@ -559,7 +560,7 @@ matrix, where <span class="math notranslate nohighlight">\(N_m\)</span> is the n
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis">
-<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_weights_dict</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">plot_just_analysis</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison.plot_just_analysis" title="Link to this definition">¶</a></dt>
<dd><p>Visualizes the confusion matrix and the model wights for the
justifiability analysis.</p>
<section id="id13">
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
index 83a052126..0180e21c6 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.bayes_model_comparison.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
index 012f9ca7b..3eea32209 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
index 333585094..e21d3a79b 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.discrepancy.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.html b/public/_autosummary/bayesvalidrox.bayes_inference.html
index c7fdddf41..11f981171 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
index 1c766909b..46c8c0469 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.MCMC.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -362,6 +363,32 @@ science, 5(1), pp.65-80.</p>
<dl class="simple">
<dt>BayesOpts<span class="classifier">obj</span></dt><dd><p>Bayes object.</p>
</dd>
+<dt>engine<span class="classifier">bayesvalidrox.Engine</span></dt><dd><p>Engine object that contains the surrogate, model and expdesign</p>
+</dd>
+<dt>mcmc_params<span class="classifier">dict</span></dt><dd><p>Dictionary of parameters for the mcmc. Required are
+- init_samples
+- n_steps
+- n_walkers
+- n_burn
+- moves
+- multiplrocessing
+- verbose</p>
+</dd>
+<dt>Discrepancy<span class="classifier">bayesvalidrox.Discrepancy</span></dt><dd><p>Discrepancy object that described the uncertainty of the data.</p>
+</dd>
+</dl>
+<p>bias_inputs :</p>
+<p>error_model :</p>
+<p>req_outputs :</p>
+<p>selected_indices :</p>
+<p>emulator :</p>
+<dl class="simple">
+<dt>out_dir<span class="classifier">string</span></dt><dd><p>Directory to write the outputs to.</p>
+</dd>
+<dt>name<span class="classifier">string</span></dt><dd><p>Name of this MCMC selection (?)</p>
+</dd>
+<dt>BiasInputs<span class="classifier"></span></dt><dd><p>The default is None.</p>
+</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.bayes_inference.mcmc.MCMC.__init__">
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
index d00bc5717..69a4d24e1 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.gelman_rubin.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
index 29b44ce99..2038b9495 100644
--- a/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
+++ b/public/_autosummary/bayesvalidrox.bayes_inference.mcmc.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.html b/public/_autosummary/bayesvalidrox.html
index 5c9c7d22e..75828bd7a 100644
--- a/public/_autosummary/bayesvalidrox.html
+++ b/public/_autosummary/bayesvalidrox.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.html b/public/_autosummary/bayesvalidrox.post_processing.html
index ee8c18176..56395e27e 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html b/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
index 1e9cfdbec..1bcb70f69 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.post_processing.post_processing.html b/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
index 1c0ee0798..585410977 100644
--- a/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
+++ b/public/_autosummary/bayesvalidrox.post_processing.post_processing.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.html b/public/_autosummary/bayesvalidrox.pylink.html
index d3b4ddb9d..7637b34f3 100644
--- a/public/_autosummary/bayesvalidrox.pylink.html
+++ b/public/_autosummary/bayesvalidrox.pylink.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html b/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
index 868fd8032..bf9c61131 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -339,7 +340,7 @@
<h1>bayesvalidrox.pylink.pylink.PyLinkForwardModel<a class="headerlink" href="#bayesvalidrox-pylink-pylink-pylinkforwardmodel" title="Link to this heading">¶</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">bayesvalidrox.pylink.pylink.</span></span><span class="sig-name descname"><span class="pre">PyLinkForwardModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="Link to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>A forward model binder</p>
<p>This calss serves as a code wrapper. This wrapper allows the execution of
@@ -428,7 +429,7 @@ This is only available for one output.</p>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__">
-<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">link_type</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'pylink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">py_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">func_args</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shell_command</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_template</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aux_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exe_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_file_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_names</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">[]</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_parser</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_process</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">n_cpus</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meas_file_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_file</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">obs_dict_valid</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mc_ref_dict</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">{}</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">store</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.pylink.pylink.PyLinkForwardModel.__init__" title="Link to this definition">¶</a></dt>
<dd></dd></dl>
<p class="rubric">Methods</p>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.html b/public/_autosummary/bayesvalidrox.pylink.pylink.html
index fd29ae011..6c72ed765 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html b/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
index d13e5d7af..f5fe15661 100644
--- a/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
+++ b/public/_autosummary/bayesvalidrox.pylink.pylink.within_range.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
index 88166ae55..00c0b14a8 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.adaptPlot.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
index dc183669e..31ded8565 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.adaptPlot.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
index 7fd894a2b..cfa685259 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.apoly_construction.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
index bb8064c4a..48f07ba3f 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.apoly_construction.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
index e3f16fb5c..3dee9c980 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
index 1e19d3665..e5b8b3aaf 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
index 3ba8a66cb..49002d5f3 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
index c3b2d5667..f9446b9c3 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.gamma_mean.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
index 5d1164c23..12a692322 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.bayes_linear.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
index d9bc2a754..bc8c4c8df 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.Engine.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -465,7 +466,7 @@ Run_No : int</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel">
-<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">eval_metamodel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sampling_method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'random'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_samples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parallel</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.engine.Engine.eval_metamodel" title="Link to this definition">¶</a></dt>
<dd><p>Evaluates metamodel at the requested samples. One can also generate
nsamples.</p>
<section id="id3">
@@ -481,6 +482,9 @@ default is None.</p>
</dd>
<dt>return_samples<span class="classifier">bool, optional</span></dt><dd><p>Retun samples, if no <cite>samples</cite> is provided. The default is False.</p>
</dd>
+<dt>parallel<span class="classifier">bool, optional</span></dt><dd><p>Set to true if the evaluations should be done in parallel.
+The default is False.</p>
+</dd>
</dl>
</section>
<section id="id4">
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
index d4d269e7f..1468932d5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.hellinger_distance.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
index 885ebd13a..f43c214e2 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
index d1ef23527..edd183342 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.logpdf.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html b/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
index 9e48ba3c3..6d630a958 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.engine.subdomain.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
index cac4d998e..e081f64c3 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
index dde4517e0..936d75c87 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
index cc0f1d31c..8a4325678 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
index 58709347d..e566e9fc9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
index b13d05c48..211d11ec9 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
index 78f9787e1..ebb205a5b 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -560,12 +561,12 @@ the MetaModel object.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.exp_designs.ExpDesigns.init_param_space" title="Link to this definition">¶</a></dt>
<dd><p>Initializes parameter space.</p>
<section id="id6">
<h3>Parameters<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
</dd>
</dl>
</section>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
index c9556e431..3f8c99c60 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.check_ranges.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
index 0a54834e0..12f3e3b7b 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exp_designs.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
index 4496b2d8f..bfc9e4887 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.Exploration.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
index 5482569e1..4fe52523a 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.exploration.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
index 5a03208c8..ef1e59d9f 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.cross_truncate.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
index a950df2ff..128c42630 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.glexindex.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
index 96400f333..f22f12377 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.glexindex.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.html b/public/_autosummary/bayesvalidrox.surrogate_models.html
index 4312aa252..551916f8f 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
index b5eb76fa2..f9d2df3bd 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.InputSpace.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -417,12 +418,12 @@ the MetaModel object.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space">
-<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">init_param_space</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_deg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.input_space.InputSpace.init_param_space" title="Link to this definition">¶</a></dt>
<dd><p>Initializes parameter space.</p>
<section id="id2">
<h3>Parameters<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>None</cite>.</p>
+<dt>max_deg<span class="classifier">int, optional</span></dt><dd><p>Maximum degree. The default is <cite>1</cite>.</p>
</dd>
</dl>
</section>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
index cc003dd63..7c8cd9299 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.input_space.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
index 95f8b8e45..c3b3d9d99 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Input.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
index fca0dcb0d..fcb16dad3 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.Marginal.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
index d5c3b12c1..4e16820e3 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.inputs.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
index 43f20bf42..7e9829327 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
index 274d8319d..8f61f3d06 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
index f159c07b7..17f469e71 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
index 35ea14b81..9dd1a74ff 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
index f1a15392d..dcd0820e6 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
index ff1c030d1..05bcfb125 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
index dc6b45be7..5ea393418 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
index 39bed6efb..8ed5c18d5 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.reg_fast_laplace.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
index 49744e809..b19b79684 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.MetaModel.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
@@ -449,8 +450,8 @@ For experimental design refer to <cite>InputSpace</cite>.</p>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.generate_polynomials"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generate_polynomials</span></code></a>([max_deg])</p></td>
<td><p>Generates (univariate) polynomials.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target[, verbose])</p></td>
-<td><p>Transforms the targets (outputs) via Principal Component Analysis</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pca_transformation</span></code></a>(target)</p></td>
+<td><p>Transforms the targets (outputs) via Principal Component Analysis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression" title="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.regression"><code class="xref py py-obj docutils literal notranslate"><span class="pre">regression</span></code></a>(X, y, basis_indices[, ...])</p></td>
<td><p>Fit regression using the regression method provided.</p></td>
@@ -720,16 +721,15 @@ The default is False.</p>
<dl class="py method">
<dt class="sig sig-object py" id="bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation">
-<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
-<dd><p>Transforms the targets (outputs) via Principal Component Analysis</p>
+<span class="sig-name descname"><span class="pre">pca_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#bayesvalidrox.surrogate_models.surrogate_models.MetaModel.pca_transformation" title="Link to this definition">¶</a></dt>
+<dd><p>Transforms the targets (outputs) via Principal Component Analysis.
+The number of features is set by <cite>self.n_pca_components</cite>.
+If this is not given, <cite>self.var_pca_threshold</cite> is used as a threshold.</p>
<section id="id14">
<h3>Parameters<a class="headerlink" href="#id14" title="Link to this heading">¶</a></h3>
<dl class="simple">
<dt>target<span class="classifier">array of shape (n_samples,)</span></dt><dd><p>Target values.</p>
</dd>
-<dt>verbose<span class="classifier">bool</span></dt><dd><p>Set to True to get more information during functtion call.
-The default is False.</p>
-</dd>
</dl>
</section>
<section id="id15">
@@ -804,7 +804,7 @@ for the fast version of the bootstrapping.</p>
<section id="id20">
<h3>Parameters<a class="headerlink" href="#id20" title="Link to this heading">¶</a></h3>
<dl class="simple">
-<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set.</p>
+<dt>X<span class="classifier">array of shape (n_samples, n_params)</span></dt><dd><p>Training set. These samples should be already transformed.</p>
</dd>
<dt>y<span class="classifier">array of shape (n_samples, n_outs)</span></dt><dd><p>The (transformed) model responses.</p>
</dd>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
index a047d2ad8..85883cb84 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
index 1b72a962c..4a66eb692 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.create_psi.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
index 560f6c733..a38aa4e63 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
index 82a65402e..bb5eaba6c 100644
--- a/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
+++ b/public/_autosummary/bayesvalidrox.surrogate_models.surrogate_models.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="../surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="../al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="../post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="../bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">TUTORIAL</a></li>
diff --git a/public/_sources/bayes_description.rst.txt b/public/_sources/bayes_description.rst.txt
index 2cfd3a6a8..1c72a3e99 100644
--- a/public/_sources/bayes_description.rst.txt
+++ b/public/_sources/bayes_description.rst.txt
@@ -1,7 +1,90 @@
-Bayesian inference and multi-model comparison
-*********************************************
+Bayesian inference
+******************
+.. container:: twocol
+ .. container:: leftside
+
+ With Bayesian inference we ask the question 'how does our understanding of the inputs change given some observation of the outputs of the model?', i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+ Bayesvalidrox provides a dedicated class to perform this task, :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference`, which infers the posterior via ``rejection-sampling`` or ``MCMC``.
+ The likelihood in rejection sampling is estimated with the help of ``bootstrapping``.
+ MCMC-specific parameters are to be given as a dictionary called ``mcmc_params`` and can include
+
+ * ``init_samples``: initial samples
+ * ``n_steps``: number of steps
+ * ``n_walkers``: number of walkers
+ * ``n_burn``: length of the burn-in
+ * ``moves``: function to use for the moves, e.g. taken from ``emcee``
+ * ``multiprocessing``: setting for multiprocessing
+ * ``verbose``: verbosity
+
+ .. container:: rightside
+
+ .. image:: ../diagrams/bayesian_validation.png
+ :width: 300
+ :alt: UML diagram for classes related to Bayesian inference.
-.. image:: ../diagrams/bayesian_validation.png
- :width: 300
- :alt: UML diagram for classes related to Bayesian inference and multi-model comparison.
+The observation should be set as ``Model.observations`` in the ``Engine``, and an estimation of its uncertainty can be provided as a :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy` object.
+
+Example
+=======
+For this example we need to add the following imports.
+
+>>> from bayesvalidrox import Discrepancy, BayesInference
+
+In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as ``Model.observations``.
+As this expects a 1D-array for each output key, we need to change the format slightly.
+
+>>> true_sample = [[2]]
+>>> observation = Model.run_model_parallel(true_sample)
+>>> Model.observations = {}
+>>> for key in observation:
+>>> if key == 'x_values':
+>>> Model.observations[key]=observation[key]
+>>> else:
+>>> Model.observations[key]=observation[key][0]
+
+Next we define the uncertainty on the observation with the class :any:`bayesvalidrox.bayes_inference.discrepancy.Discrepancy`.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The ``parameters`` contain the variance for each point in the observation.
+
+>>> obsData = pd.DataFrame(Model.observations, columns=Model.Output.names)
+>>> DiscrepancyOpts = Discrepancy('')
+>>> DiscrepancyOpts.type = 'Gaussian'
+>>> DiscrepancyOpts.parameters = obsData**2
+
+Now we can initialize an object of class :any:`bayesvalidrox.bayes_inference.bayes_inference.BayesInference` with all the wanted properties.
+This object has to be given our ``Engine``.
+If it should use the surrogate during inference, set ``emulator`` to ``True``, otherwise the model will be evaluated directly.
+We also set the defined ``Discrepancy``. and set ``post_plot_pred`` if posterior predictions should be visualized.
+
+>>> BayesObj = BayesInference(Engine_)
+>>> BayesObj.emulator = True
+>>> BayesObj.Discrepancy = DiscrepancyOpts
+>>> BayesObj.plot_post_pred = True
+
+In order to run with rejection sampling, we set the ``inference_method`` accordingly and add properties for ``bootstrap``.
+
+>>> BayesObj.inference_method = 'rejection'
+>>> BayesObj.bootstrap = True
+>>> BayesObj.n_bootstrap_itrs = 500
+>>> BayesObj.bootstrap_noise = 2
+
+If the sampling should be done with MCMC, then this is set as the ``inference_method`` and additional properties are given in ``mcmc_params``.
+For this example we use the python package ``emcee`` to define the MCMC moves.
+
+>>> BayesObj.inference_method = 'MCMC'
+>>> import emcee
+>>> BayesObj.mcmc_params = {
+>>> 'n_steps': 1e4,#5,
+>>> 'n_walkers': 30,
+>>> 'moves': emcee.moves.KDEMove(),
+>>> 'multiprocessing': False,
+>>> 'verbose': False
+>>> }
+
+Then we run the inference.
+
+>>> BayesObj.create_inference()
+
+If the output directory ``BayesObj.out_dir`` is not set otherwise, the outputs are written into the folder ``
\ No newline at end of file
diff --git a/public/_sources/bmc_description.rst.txt b/public/_sources/bmc_description.rst.txt
new file mode 100644
index 000000000..10e73bd1e
--- /dev/null
+++ b/public/_sources/bmc_description.rst.txt
@@ -0,0 +1,7 @@
+Bayesian multi-model comparison
+*******************************
+
+.. image:: ../diagrams/bayesian_model_comparison.png
+ :width: 400
+ :alt: UML diagram for classes related to Bayesian multi-model comparison.
+
diff --git a/public/_sources/model_description.rst.txt b/public/_sources/model_description.rst.txt
index bb719886b..923f20a7c 100644
--- a/public/_sources/model_description.rst.txt
+++ b/public/_sources/model_description.rst.txt
@@ -6,10 +6,10 @@ Models
.. container:: leftside
BayesValidRox gives options to create interfaces for a variety of models with the class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`.
- Its main function is to run the model on given samples and to read in and contain MC references and observations.
+ Its main function is to run the model on given samples and to read in and contain MC references and observations.
- Models can be defined via python functions, shell commands or as general executables.
- This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
+ Models can be defined via python functions, shell commands or as general executables.
+ This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.
.. container:: rightside
diff --git a/public/_sources/packagedescription.rst.txt b/public/_sources/packagedescription.rst.txt
index f245959b8..1d1fd6517 100644
--- a/public/_sources/packagedescription.rst.txt
+++ b/public/_sources/packagedescription.rst.txt
@@ -69,3 +69,4 @@ The next pages lead through the topics given in BayesValidRox and describe the a
al_description
post_description
bayes_description
+ bmc_description
diff --git a/public/_sources/post_description.rst.txt b/public/_sources/post_description.rst.txt
index af2172709..987f18e7d 100644
--- a/public/_sources/post_description.rst.txt
+++ b/public/_sources/post_description.rst.txt
@@ -4,11 +4,11 @@ Postprocessing
.. container:: leftside
- Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
- The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
+ Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
+ The BayesValidRox class :any:`bayesvalidrox.post_processing.post_processing.PostProcessing` includes functions that are applicable to all types of surrogate model.
- * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
- * ``check_accuracy``: computing the RMSE error of the surrogate model
+ * ``valid_metamodel``: visualizing some metamodel runs against the corresponding model runs
+ * ``check_accuracy``: computing the RMSE error of the surrogate model
.. container:: rightside
diff --git a/public/al_description.html b/public/al_description.html
index 78a5f609e..e3cde5ecd 100644
--- a/public/al_description.html
+++ b/public/al_description.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/analyticalfunction.html b/public/analyticalfunction.html
index 42509cf38..799f0350a 100644
--- a/public/analyticalfunction.html
+++ b/public/analyticalfunction.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/api.html b/public/api.html
index d853aff4e..7f918265a 100644
--- a/public/api.html
+++ b/public/api.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/bayes_description.html b/public/bayes_description.html
index 62bb18a5a..7a9339266 100644
--- a/public/bayes_description.html
+++ b/public/bayes_description.html
@@ -3,10 +3,10 @@
<head><meta charset="utf-8"/>
<meta name="viewport" content="width=device-width,initial-scale=1"/>
<meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="TUTORIAL" href="tutorial.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian multi-model comparison" href="bmc_description.html" /><link rel="prev" title="Postprocessing" href="post_description.html" />
<!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
- <title>Bayesian inference and multi-model comparison - bayesvalidrox 1.0.0 documentation</title>
+ <title>Bayesian inference - bayesvalidrox 1.0.0 documentation</title>
<link rel="stylesheet" type="text/css" href="_static/pygments.css?v=362ab14a" />
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@@ -141,7 +141,7 @@
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
- <label class="toc-overlay-icon toc-header-icon no-toc" for="__toc">
+ <label class="toc-overlay-icon toc-header-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
</label>
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -329,15 +330,99 @@
<svg class="theme-icon-when-light"><use href="#svg-sun"></use></svg>
</button>
</div>
- <label class="toc-overlay-icon toc-content-icon no-toc" for="__toc">
+ <label class="toc-overlay-icon toc-content-icon" for="__toc">
<div class="visually-hidden">Toggle table of contents sidebar</div>
<i class="icon"><svg><use href="#svg-toc"></use></svg></i>
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</div>
<article role="main">
- <section id="bayesian-inference-and-multi-model-comparison">
-<h1>Bayesian inference and multi-model comparison<a class="headerlink" href="#bayesian-inference-and-multi-model-comparison" title="Link to this heading">¶</a></h1>
-<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference and multi-model comparison." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+ <section id="bayesian-inference">
+<h1>Bayesian inference<a class="headerlink" href="#bayesian-inference" title="Link to this heading">¶</a></h1>
+<div class="twocol docutils container">
+<div class="leftside docutils container">
+<p>With Bayesian inference we ask the question ‘how does our understanding of the inputs change given some observation of the outputs of the model?’, i.e. we perform an updating step of the prior distributions to posterior, based on some observations.
+Bayesvalidrox provides a dedicated class to perform this task, <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a>, which infers the posterior via <code class="docutils literal notranslate"><span class="pre">rejection-sampling</span></code> or <code class="docutils literal notranslate"><span class="pre">MCMC</span></code>.
+The likelihood in rejection sampling is estimated with the help of <code class="docutils literal notranslate"><span class="pre">bootstrapping</span></code>.
+MCMC-specific parameters are to be given as a dictionary called <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code> and can include</p>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">init_samples</span></code>: initial samples</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_steps</span></code>: number of steps</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_walkers</span></code>: number of walkers</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">n_burn</span></code>: length of the burn-in</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">moves</span></code>: function to use for the moves, e.g. taken from <code class="docutils literal notranslate"><span class="pre">emcee</span></code></p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">multiprocessing</span></code>: setting for multiprocessing</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">verbose</span></code>: verbosity</p></li>
+</ul>
+</div>
+<div class="rightside docutils container">
+<a class="reference internal image-reference" href="_images/bayesian_validation.png"><img alt="UML diagram for classes related to Bayesian inference." src="_images/bayesian_validation.png" style="width: 300px;" /></a>
+</div>
+</div>
+<p>The observation should be set as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code> in the <code class="docutils literal notranslate"><span class="pre">Engine</span></code>, and an estimation of its uncertainty can be provided as a <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a> object.</p>
+<section id="example">
+<h2>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h2>
+<p>For this example we need to add the following imports.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">bayesvalidrox</span> <span class="kn">import</span> <span class="n">Discrepancy</span><span class="p">,</span> <span class="n">BayesInference</span>
+</pre></div>
+</div>
+<p>In order to run Bayesian inference we first need to provide an observation.
+For this example we take an evaluation of the model on some chosen sample and add the resulting values as <code class="docutils literal notranslate"><span class="pre">Model.observations</span></code>.
+As this expects a 1D-array for each output key, we need to change the format slightly.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">true_sample</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">2</span><span class="p">]]</span>
+<span class="gp">>>> </span><span class="n">observation</span> <span class="o">=</span> <span class="n">Model</span><span class="o">.</span><span class="n">run_model_parallel</span><span class="p">(</span><span class="n">true_sample</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span> <span class="o">=</span> <span class="p">{}</span>
+<span class="gp">>>> </span><span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">observation</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="k">if</span> <span class="n">key</span> <span class="o">==</span> <span class="s1">'x_values'</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
+<span class="gp">>>> </span> <span class="k">else</span><span class="p">:</span>
+<span class="gp">>>> </span> <span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">=</span><span class="n">observation</span><span class="p">[</span><span class="n">key</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
+</pre></div>
+</div>
+<p>Next we define the uncertainty on the observation with the class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.discrepancy.Discrepancy.html#bayesvalidrox.bayes_inference.discrepancy.Discrepancy" title="bayesvalidrox.bayes_inference.discrepancy.Discrepancy"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.discrepancy.Discrepancy</span></code></a>.
+For this example we set the uncertainty to be zero-mean gaussian and dependent on the values in the observation, i.e. larger values have a larger uncertainty associated with them.
+The <code class="docutils literal notranslate"><span class="pre">parameters</span></code> contain the variance for each point in the observation.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">obsData</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">Model</span><span class="o">.</span><span class="n">observations</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">Model</span><span class="o">.</span><span class="n">Output</span><span class="o">.</span><span class="n">names</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span> <span class="o">=</span> <span class="n">Discrepancy</span><span class="p">(</span><span class="s1">''</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">'Gaussian'</span>
+<span class="gp">>>> </span><span class="n">DiscrepancyOpts</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">obsData</span><span class="o">**</span><span class="mi">2</span>
+</pre></div>
+</div>
+<p>Now we can initialize an object of class <a class="reference internal" href="_autosummary/bayesvalidrox.bayes_inference.bayes_inference.BayesInference.html#bayesvalidrox.bayes_inference.bayes_inference.BayesInference" title="bayesvalidrox.bayes_inference.bayes_inference.BayesInference"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.bayes_inference.bayes_inference.BayesInference</span></code></a> with all the wanted properties.
+This object has to be given our <code class="docutils literal notranslate"><span class="pre">Engine</span></code>.
+If it should use the surrogate during inference, set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to <code class="docutils literal notranslate"><span class="pre">True</span></code>, otherwise the model will be evaluated directly.
+We also set the defined <code class="docutils literal notranslate"><span class="pre">Discrepancy</span></code>. and set <code class="docutils literal notranslate"><span class="pre">post_plot_pred</span></code> if posterior predictions should be visualized.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">BayesObj</span> <span class="o">=</span> <span class="n">BayesInference</span><span class="p">(</span><span class="n">Engine_</span><span class="p">)</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">emulator</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">Discrepancy</span> <span class="o">=</span> <span class="n">DiscrepancyOpts</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">plot_post_pred</span> <span class="o">=</span> <span class="kc">True</span>
+</pre></div>
+</div>
+<p>In order to run with rejection sampling, we set the <code class="docutils literal notranslate"><span class="pre">inference_method</span></code> accordingly and add properties for <code class="docutils literal notranslate"><span class="pre">bootstrap</span></code>.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">inference_method</span> <span class="o">=</span> <span class="s1">'rejection'</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">bootstrap</span> <span class="o">=</span> <span class="kc">True</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">n_bootstrap_itrs</span> <span class="o">=</span> <span class="mi">500</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">bootstrap_noise</span> <span class="o">=</span> <span class="mi">2</span>
+</pre></div>
+</div>
+<p>If the sampling should be done with MCMC, then this is set as the <code class="docutils literal notranslate"><span class="pre">inference_method</span></code> and additional properties are given in <code class="docutils literal notranslate"><span class="pre">mcmc_params</span></code>.
+For this example we use the python package <code class="docutils literal notranslate"><span class="pre">emcee</span></code> to define the MCMC moves.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">inference_method</span> <span class="o">=</span> <span class="s1">'MCMC'</span>
+<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">emcee</span>
+<span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">mcmc_params</span> <span class="o">=</span> <span class="p">{</span>
+<span class="gp">>>> </span> <span class="s1">'n_steps'</span><span class="p">:</span> <span class="mf">1e4</span><span class="p">,</span><span class="c1">#5,</span>
+<span class="gp">>>> </span> <span class="s1">'n_walkers'</span><span class="p">:</span> <span class="mi">30</span><span class="p">,</span>
+<span class="gp">>>> </span> <span class="s1">'moves'</span><span class="p">:</span> <span class="n">emcee</span><span class="o">.</span><span class="n">moves</span><span class="o">.</span><span class="n">KDEMove</span><span class="p">(),</span>
+<span class="gp">>>> </span> <span class="s1">'multiprocessing'</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span>
+<span class="gp">>>> </span> <span class="s1">'verbose'</span><span class="p">:</span> <span class="kc">False</span>
+<span class="gp">>>> </span> <span class="p">}</span>
+</pre></div>
+</div>
+<p>Then we run the inference.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">BayesObj</span><span class="o">.</span><span class="n">create_inference</span><span class="p">()</span>
+</pre></div>
+</div>
+<p>If the output directory <code class="docutils literal notranslate"><span class="pre">BayesObj.out_dir</span></code> is not set otherwise, the outputs are written into the folder ``</p>
+</section>
</section>
</article>
@@ -345,12 +430,12 @@
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+ <div class="title">Bayesian multi-model comparison</div>
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@@ -383,8 +468,27 @@
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+
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+<li><a class="reference internal" href="#">Bayesian inference</a><ul>
+<li><a class="reference internal" href="#example">Example</a></li>
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diff --git a/public/beam.html b/public/beam.html
index 6c82f54b9..64c4a4c02 100644
--- a/public/beam.html
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@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
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<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
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+ <section id="bayesian-multi-model-comparison">
+<h1>Bayesian multi-model comparison<a class="headerlink" href="#bayesian-multi-model-comparison" title="Link to this heading">¶</a></h1>
+<a class="reference internal image-reference" href="_images/bayesian_model_comparison.png"><img alt="UML diagram for classes related to Bayesian multi-model comparison." src="_images/bayesian_model_comparison.png" style="width: 400px;" /></a>
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diff --git a/public/borehole.html b/public/borehole.html
index eafbe8618..683c27d0e 100644
--- a/public/borehole.html
+++ b/public/borehole.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/examples.html b/public/examples.html
index 9d6b6cce8..4c621310a 100644
--- a/public/examples.html
+++ b/public/examples.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/genindex.html b/public/genindex.html
index 2b0791a3b..67a702598 100644
--- a/public/genindex.html
+++ b/public/genindex.html
@@ -168,7 +168,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/index.html b/public/index.html
index 460cf3cb7..dcad29fd0 100644
--- a/public/index.html
+++ b/public/index.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/input_description.html b/public/input_description.html
index 39e16d2b9..15276ff89 100644
--- a/public/input_description.html
+++ b/public/input_description.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/ishigami.html b/public/ishigami.html
index 06d5b7d8c..dcf8bda0b 100644
--- a/public/ishigami.html
+++ b/public/ishigami.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/model_description.html b/public/model_description.html
index 2dbaeed95..da41e4667 100644
--- a/public/model_description.html
+++ b/public/model_description.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -339,12 +340,10 @@
<h1>Models<a class="headerlink" href="#models" title="Link to this heading">¶</a></h1>
<div class="twocol docutils container">
<div class="leftside docutils container">
-<dl>
-<dt>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.</dt><dd><p>Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
+<p>BayesValidRox gives options to create interfaces for a variety of models with the class <a class="reference internal" href="_autosummary/bayesvalidrox.pylink.pylink.PyLinkForwardModel.html#bayesvalidrox.pylink.pylink.PyLinkForwardModel" title="bayesvalidrox.pylink.pylink.PyLinkForwardModel"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.pylink.pylink.PyLinkForwardModel</span></code></a>.
+Its main function is to run the model on given samples and to read in and contain MC references and observations.</p>
<p>Models can be defined via python functions, shell commands or as general executables.
This allows for the use of BayesValidRox with a broad range of models and easy extension to models that are defined with e.g. UM-Bridge.</p>
-</dd>
-</dl>
</div>
<div class="rightside docutils container">
<a class="reference internal image-reference" href="_images/model.png"><img alt="UML diagram for the bayesvalidrox class :any:`bayesvalidrox.pylink.pylink.PyLinkForwardModel`." src="_images/model.png" style="width: 150px;" /></a>
diff --git a/public/modelcomparison.html b/public/modelcomparison.html
index 723a66ed1..472be01bb 100644
--- a/public/modelcomparison.html
+++ b/public/modelcomparison.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/objects.inv b/public/objects.inv
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<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/packagedescription.html b/public/packagedescription.html
index c76923ed2..875119c27 100644
--- a/public/packagedescription.html
+++ b/public/packagedescription.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -382,7 +383,8 @@ If multiple (surrogate) models are given, they can be compared against each othe
<li class="toctree-l1"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l1"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l1"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l1"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</div>
</section>
diff --git a/public/pollution.html b/public/pollution.html
index 4b71758ef..e7ae39a11 100644
--- a/public/pollution.html
+++ b/public/pollution.html
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/post_description.html b/public/post_description.html
index d5eb2c29e..33fa48a7a 100644
--- a/public/post_description.html
+++ b/public/post_description.html
@@ -3,7 +3,7 @@
<head><meta charset="utf-8"/>
<meta name="viewport" content="width=device-width,initial-scale=1"/>
<meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian inference and multi-model comparison" href="bayes_description.html" /><link rel="prev" title="Active learning: iteratively expanding the training set" href="al_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="Bayesian inference" href="bayes_description.html" /><link rel="prev" title="Active learning: iteratively expanding the training set" href="al_description.html" />
<!-- Generated with Sphinx 7.3.7 and Furo 2023.09.10 -->
<title>Postprocessing - bayesvalidrox 1.0.0 documentation</title>
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -341,12 +342,10 @@
<div class="leftside docutils container">
<p>Postprocessing refers to evaluations and checks performed on a model to get an understanding of its properties and estimate its quality.
The BayesValidRox class <a class="reference internal" href="_autosummary/bayesvalidrox.post_processing.post_processing.PostProcessing.html#bayesvalidrox.post_processing.post_processing.PostProcessing" title="bayesvalidrox.post_processing.post_processing.PostProcessing"><code class="xref any py py-class docutils literal notranslate"><span class="pre">bayesvalidrox.post_processing.post_processing.PostProcessing</span></code></a> includes functions that are applicable to all types of surrogate model.</p>
-<blockquote>
-<div><ul class="simple">
+<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">valid_metamodel</span></code>: visualizing some metamodel runs against the corresponding model runs</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">check_accuracy</span></code>: computing the RMSE error of the surrogate model</p></li>
</ul>
-</div></blockquote>
</div>
<div class="rightside docutils container">
<a class="reference internal image-reference" href="_images/postprocessing.png"><img alt="UML diagram for the classes and functions used in active learning in BayesValidRox." src="_images/postprocessing.png" style="width: 300px;" /></a>
@@ -407,7 +406,7 @@ The BayesValidRox class <a class="reference internal" href="_autosummary/bayesva
<div class="context">
<span>Next</span>
</div>
- <div class="title">Bayesian inference and multi-model comparison</div>
+ <div class="title">Bayesian inference</div>
</div>
<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
</a>
diff --git a/public/py-modindex.html b/public/py-modindex.html
index a10614c9b..9246a7ee0 100644
--- a/public/py-modindex.html
+++ b/public/py-modindex.html
@@ -168,7 +168,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/search.html b/public/search.html
index 8fe37498e..5e4d1ba20 100644
--- a/public/search.html
+++ b/public/search.html
@@ -167,7 +167,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/searchindex.js b/public/searchindex.js
index 3aaa01c41..d6a472b6a 100644
--- a/public/searchindex.js
+++ b/public/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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diff --git a/public/surrogate_description.html b/public/surrogate_description.html
index c48db82a4..db4708ce6 100644
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<li class="toctree-l2 current current-page"><a class="current reference internal" href="#">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
diff --git a/public/tutorial.html b/public/tutorial.html
index 820f6d348..f4c941291 100644
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<meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
-<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="EXAMPLES" href="examples.html" /><link rel="prev" title="Bayesian inference and multi-model comparison" href="bayes_description.html" />
+<link rel="index" title="Index" href="genindex.html" /><link rel="search" title="Search" href="search.html" /><link rel="next" title="EXAMPLES" href="examples.html" /><link rel="prev" title="Bayesian multi-model comparison" href="bmc_description.html" />
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<title>TUTORIAL - bayesvalidrox 1.0.0 documentation</title>
@@ -170,7 +170,8 @@
<li class="toctree-l2"><a class="reference internal" href="surrogate_description.html">Training surrogate models</a></li>
<li class="toctree-l2"><a class="reference internal" href="al_description.html">Active learning: iteratively expanding the training set</a></li>
<li class="toctree-l2"><a class="reference internal" href="post_description.html">Postprocessing</a></li>
-<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference and multi-model comparison</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bayes_description.html">Bayesian inference</a></li>
+<li class="toctree-l2"><a class="reference internal" href="bmc_description.html">Bayesian multi-model comparison</a></li>
</ul>
</li>
<li class="toctree-l1 current current-page"><a class="current reference internal" href="#">TUTORIAL</a></li>
@@ -596,7 +597,7 @@ The method <code class="docutils literal notranslate"><span class="pre">sobolInd
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<p>If we set <code class="docutils literal notranslate"><span class="pre">emulator</span></code> to be true the Bayesian Inference will be performed based on the emulator.
Some posterior predictions will be plotted by setting <code class="docutils literal notranslate"><span class="pre">plot_post_pred</span></code>.
-More options for Bayesian inference are listed at <a class="reference internal" href="bayes_description.html"><span class="doc">Bayesian inference and multi-model comparison</span></a>.</p>
+More options for Bayesian inference are listed at <a class="reference internal" href="bayes_description.html"><span class="doc">Bayesian inference</span></a>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Setting <code class="docutils literal notranslate"><span class="pre">emulator</span> <span class="pre">=</span> <span class="pre">False</span></code> means that the inference is based on actual model runs and not the surrogate.
@@ -694,14 +695,14 @@ plots of posterior predictions if wanted.</p>
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<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
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- <a class="prev-page" href="bayes_description.html">
+ <a class="prev-page" href="bmc_description.html">
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- <div class="title">Bayesian inference and multi-model comparison</div>
+ <div class="title">Bayesian multi-model comparison</div>
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