diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle
index 2ac92cb0654c54086e353004bc7d91191ab1b71e..b2e0863886180fc1aa05b2007d0471193138f92b 100644
Binary files a/docs/build/doctrees/environment.pickle and b/docs/build/doctrees/environment.pickle differ
diff --git a/docs/build/doctrees/index.doctree b/docs/build/doctrees/index.doctree
index d8a14b3bd17e9ae0beadb9c2ca656cb20a59f4d4..6274b03111a42b7f4e02e11ea170f4c14f510dd6 100644
Binary files a/docs/build/doctrees/index.doctree and b/docs/build/doctrees/index.doctree differ
diff --git a/docs/build/doctrees/surrogate_description.doctree b/docs/build/doctrees/surrogate_description.doctree
index dc30e72b8151e5358bb8a15ff692dc42dc2200a5..0c4941c5424b03f3bdb35a35f68fb22aa3e7b881 100644
Binary files a/docs/build/doctrees/surrogate_description.doctree and b/docs/build/doctrees/surrogate_description.doctree differ
diff --git a/docs/build/html/_sources/index.rst.txt b/docs/build/html/_sources/index.rst.txt
index 48215bbbc3e3d0e4d55b5cb9ee3b007467332885..dd9bb06fb0d2e92d10a644de1f03f8bd6e112265 100644
--- a/docs/build/html/_sources/index.rst.txt
+++ b/docs/build/html/_sources/index.rst.txt
@@ -53,6 +53,10 @@ Further contents
    examples
    api
    
+Contact
+-------
+#TODO Add options here
+   
    
 Indices and tables
 ==================
diff --git a/docs/build/html/_sources/surrogate_description.rst.txt b/docs/build/html/_sources/surrogate_description.rst.txt
index 3b32fbe2eeea9fcdeb4d726d806bee68268c902f..6cd7bcd296ddd884cc3b07399f82b21d4f84d81e 100644
--- a/docs/build/html/_sources/surrogate_description.rst.txt
+++ b/docs/build/html/_sources/surrogate_description.rst.txt
@@ -31,11 +31,21 @@ This needs to be given three things: the metamodel itself, the model that the me
 The standard method of training the surrogate is performed by the function ``train_normal()``.
 Other available training methods in BayesValidRox are presented in :any:`al_description`.
 
-For training the engine performs three main steps.
+.. container:: twocol
 
-1) Generating training samples from the experimental design.
-2) Evaluating the model on the training samples.
-3) Fitting the surrogate to the training dataset.
+   .. container:: leftside
+   
+      For training the engine performs three main steps.
+
+      1) Generating training samples from the experimental design.
+      2) Evaluating the model on the training samples.
+      3) Fitting the surrogate to the training dataset.
+	  
+   .. container:: rightside
+   
+      .. image:: ../diagrams/engine_train_normal.png
+         :width: 800
+         :alt: Diagram of main steps in ``Engine.train_normal()``
 
 Example
 =======
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index 73eb5a83969857400cd0116ccc7dfa0f48ee5b87..9fd0f8c02f314f19c4cf3f22c086cf6074b1b757 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -408,6 +408,10 @@ The functionality and options for the different classes is described more in-dep
 </ul>
 </div>
 </section>
+<section id="contact">
+<h2>Contact<a class="headerlink" href="#contact" title="Link to this heading">¶</a></h2>
+<p>#TODO Add options here</p>
+</section>
 </section>
 <section id="indices-and-tables">
 <h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Link to this heading">¶</a></h1>
@@ -470,6 +474,7 @@ The functionality and options for the different classes is described more in-dep
 <li><a class="reference internal" href="#see-also">See also</a></li>
 <li><a class="reference internal" href="#license">License</a></li>
 <li><a class="reference internal" href="#further-contents">Further contents</a></li>
+<li><a class="reference internal" href="#contact">Contact</a></li>
 </ul>
 </li>
 <li><a class="reference internal" href="#indices-and-tables">Indices and tables</a></li>
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index 76ddf25291fa5a07e2ce8ce53dfbf77a77333270..2c5216d904c474708409c83d7bc3bf40e9532482 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"API": [[66, "api"]], "Active learning: iteratively expanding the training set": [[64, "active-learning-iteratively-expanding-the-training-set"]], "Arguments": [[29, "arguments"], [42, "arguments"], [42, "id2"]], "Attributes": [[3, "attributes"], [5, "attributes"], [7, "attributes"], [9, "attributes"], [13, "attributes"], [16, "attributes"], [25, "attributes"], [26, "attributes"], [39, "attributes"], [42, "attributes"], [47, "attributes"], [49, "attributes"], [50, "attributes"], [52, "attributes"], [55, "attributes"], [58, "attributes"], [60, "attributes"]], "Bayesian Inference": [[81, "bayesian-inference"]], "Bayesian inference and multi-model comparison": [[67, "bayesian-inference-and-multi-model-comparison"]], "Define probabilistic input model": [[81, "define-probabilistic-input-model"]], "Define surrogate (meta) model": [[81, "define-surrogate-meta-model"]], "Define the data uncertainty": [[81, "define-the-data-uncertainty"]], "Define the model with PyLinkForwardModel": [[81, "define-the-model-with-pylinkforwardmodel"]], "Discrepancy": [[65, "id3"], [68, "id3"]], "EXAMPLES": [[70, "examples"]], "Example": [[72, "example"], [74, "example"], [79, "example"], [80, "example"]], "Example: Analytical function": [[65, "example-analytical-function"]], "Example: OHagan-function": [[76, "example-ohagan-function"]], "Example: beam": [[68, "example-beam"]], "Example: borehole": [[69, "example-borehole"]], "Example: ishigami": [[73, "example-ishigami"]], "Example: model comparison": [[75, "example-model-comparison"]], "Example: pollution": [[78, "example-pollution"]], "Examples": [[49, "examples"]], "Further contents": [[71, "further-contents"]], "Import necessary libraries": [[81, "import-necessary-libraries"]], "Indices and tables": [[71, "indices-and-tables"]], "Installation": [[71, "installation"], [77, "installation"]], "License": [[71, "license"]], "Links": [[71, "links"]], "MetaModel and Engine classes": [[80, 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"bayesvalidrox-bayes-inference-discrepancy-discrepancy"]], "bayesvalidrox.bayes_inference.mcmc": [[8, "module-bayesvalidrox.bayes_inference.mcmc"]], "bayesvalidrox.bayes_inference.mcmc.MCMC": [[9, "bayesvalidrox-bayes-inference-mcmc-mcmc"]], "bayesvalidrox.bayes_inference.mcmc.gelman_rubin": [[10, "bayesvalidrox-bayes-inference-mcmc-gelman-rubin"]], "bayesvalidrox.post_processing": [[11, "module-bayesvalidrox.post_processing"]], "bayesvalidrox.post_processing.post_processing": [[12, "module-bayesvalidrox.post_processing.post_processing"]], "bayesvalidrox.post_processing.post_processing.PostProcessing": [[13, "bayesvalidrox-post-processing-post-processing-postprocessing"]], "bayesvalidrox.pylink": [[14, "module-bayesvalidrox.pylink"]], "bayesvalidrox.pylink.pylink": [[15, "module-bayesvalidrox.pylink.pylink"]], "bayesvalidrox.pylink.pylink.PyLinkForwardModel": [[16, "bayesvalidrox-pylink-pylink-pylinkforwardmodel"]], "bayesvalidrox.pylink.pylink.within_range": [[17, 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"bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule": [[34, "bayesvalidrox-surrogate-models-eval-rec-rule-eval-rec-rule"]], "bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary": [[35, "bayesvalidrox-surrogate-models-eval-rec-rule-eval-rec-rule-arbitrary"]], "bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis": [[36, "bayesvalidrox-surrogate-models-eval-rec-rule-eval-univ-basis"]], "bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs": [[37, "bayesvalidrox-surrogate-models-eval-rec-rule-poly-rec-coeffs"]], "bayesvalidrox.surrogate_models.exp_designs": [[38, "module-bayesvalidrox.surrogate_models.exp_designs"]], "bayesvalidrox.surrogate_models.exp_designs.ExpDesigns": [[39, "bayesvalidrox-surrogate-models-exp-designs-expdesigns"]], "bayesvalidrox.surrogate_models.exp_designs.check_ranges": [[40, "bayesvalidrox-surrogate-models-exp-designs-check-ranges"]], "bayesvalidrox.surrogate_models.exploration": [[41, "module-bayesvalidrox.surrogate_models.exploration"]], "bayesvalidrox.surrogate_models.exploration.Exploration": [[42, "bayesvalidrox-surrogate-models-exploration-exploration"]], "bayesvalidrox.surrogate_models.glexindex": [[43, "module-bayesvalidrox.surrogate_models.glexindex"]], "bayesvalidrox.surrogate_models.glexindex.cross_truncate": [[44, "bayesvalidrox-surrogate-models-glexindex-cross-truncate"]], "bayesvalidrox.surrogate_models.glexindex.glexindex": [[45, "bayesvalidrox-surrogate-models-glexindex-glexindex"]], "bayesvalidrox.surrogate_models.input_space": [[46, "module-bayesvalidrox.surrogate_models.input_space"]], "bayesvalidrox.surrogate_models.input_space.InputSpace": [[47, "bayesvalidrox-surrogate-models-input-space-inputspace"]], "bayesvalidrox.surrogate_models.inputs": [[48, "module-bayesvalidrox.surrogate_models.inputs"]], "bayesvalidrox.surrogate_models.inputs.Input": [[49, "bayesvalidrox-surrogate-models-inputs-input"]], "bayesvalidrox.surrogate_models.inputs.Marginal": [[50, "bayesvalidrox-surrogate-models-inputs-marginal"]], "bayesvalidrox.surrogate_models.orthogonal_matching_pursuit": [[51, "module-bayesvalidrox.surrogate_models.orthogonal_matching_pursuit"]], "bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit": [[52, "bayesvalidrox-surrogate-models-orthogonal-matching-pursuit-orthogonalmatchingpursuit"]], "bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr": [[53, "bayesvalidrox-surrogate-models-orthogonal-matching-pursuit-corr"]], "bayesvalidrox.surrogate_models.reg_fast_ard": [[54, "module-bayesvalidrox.surrogate_models.reg_fast_ard"]], "bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD": [[55, "bayesvalidrox-surrogate-models-reg-fast-ard-regressionfastard"]], "bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions": [[56, "bayesvalidrox-surrogate-models-reg-fast-ard-update-precisions"]], "bayesvalidrox.surrogate_models.reg_fast_laplace": [[57, "module-bayesvalidrox.surrogate_models.reg_fast_laplace"]], "bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace": [[58, "bayesvalidrox-surrogate-models-reg-fast-laplace-regressionfastlaplace"]], "bayesvalidrox.surrogate_models.surrogate_models": [[59, "module-bayesvalidrox.surrogate_models.surrogate_models"]], "bayesvalidrox.surrogate_models.surrogate_models.MetaModel": [[60, "bayesvalidrox-surrogate-models-surrogate-models-metamodel"]], "bayesvalidrox.surrogate_models.surrogate_models.corr_loocv_error": [[61, "bayesvalidrox-surrogate-models-surrogate-models-corr-loocv-error"]], "bayesvalidrox.surrogate_models.surrogate_models.create_psi": [[62, "bayesvalidrox-surrogate-models-surrogate-models-create-psi"]], "bayesvalidrox.surrogate_models.surrogate_models.gaussian_process_emulator": [[63, "bayesvalidrox-surrogate-models-surrogate-models-gaussian-process-emulator"]]}, "docnames": ["_autosummary/bayesvalidrox", 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\ No newline at end of file
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diff --git a/docs/build/html/surrogate_description.html b/docs/build/html/surrogate_description.html
index 7868bbdab6e15f9728bd7d140765131557526626..cbaf39a07c0daf3614e576bb3a4949c656b23ab0 100644
--- a/docs/build/html/surrogate_description.html
+++ b/docs/build/html/surrogate_description.html
@@ -170,6 +170,7 @@
 <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>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">TUTORIAL</a></li>
@@ -357,12 +358,19 @@ Training is performed by the class <a class="reference internal" href="_autosumm
 This needs to be given three things: the metamodel itself, the model that the metamodel should replace and the experimental design that matches the uncertain inputs for the model and metamodel.</p>
 <p>The standard method of training the surrogate is performed by the function <code class="docutils literal notranslate"><span class="pre">train_normal()</span></code>.
 Other available training methods in BayesValidRox are presented in <a class="reference internal" href="al_description.html"><span class="doc">Active learning: iteratively expanding the training set</span></a>.</p>
+<div class="twocol docutils container">
+<div class="leftside docutils container">
 <p>For training the engine performs three main steps.</p>
 <ol class="arabic simple">
 <li><p>Generating training samples from the experimental design.</p></li>
 <li><p>Evaluating the model on the training samples.</p></li>
 <li><p>Fitting the surrogate to the training dataset.</p></li>
 </ol>
+</div>
+<div class="rightside docutils container">
+<a class="reference internal image-reference" href="_images/engine_train_normal.png"><img alt="Diagram of main steps in ``Engine.train_normal()``" src="_images/engine_train_normal.png" style="width: 800px;" /></a>
+</div>
+</div>
 </section>
 <section id="example">
 <h2>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h2>
diff --git a/docs/diagrams/.$Structure_BayesInf.drawio.bkp b/docs/diagrams/.$Structure_BayesInf.drawio.bkp
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->>>>>>> 32b0e925 (Customized webpage design, started on user guide)
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diff --git a/docs/source/surrogate_description.rst b/docs/source/surrogate_description.rst
index 3b32fbe2eeea9fcdeb4d726d806bee68268c902f..6cd7bcd296ddd884cc3b07399f82b21d4f84d81e 100644
--- a/docs/source/surrogate_description.rst
+++ b/docs/source/surrogate_description.rst
@@ -31,11 +31,21 @@ This needs to be given three things: the metamodel itself, the model that the me
 The standard method of training the surrogate is performed by the function ``train_normal()``.
 Other available training methods in BayesValidRox are presented in :any:`al_description`.
 
-For training the engine performs three main steps.
+.. container:: twocol
 
-1) Generating training samples from the experimental design.
-2) Evaluating the model on the training samples.
-3) Fitting the surrogate to the training dataset.
+   .. container:: leftside
+   
+      For training the engine performs three main steps.
+
+      1) Generating training samples from the experimental design.
+      2) Evaluating the model on the training samples.
+      3) Fitting the surrogate to the training dataset.
+	  
+   .. container:: rightside
+   
+      .. image:: ../diagrams/engine_train_normal.png
+         :width: 800
+         :alt: Diagram of main steps in ``Engine.train_normal()``
 
 Example
 =======