Merge pull request #105 from amarquand/dev

fix module index docs
amarquand · Oct 31, 2022 · 829ba14 · 829ba14
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diff --git a/doc/build/doctrees/environment.pickle b/doc/build/doctrees/environment.pickle
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diff --git a/doc/build/doctrees/pages/acknowledgements.doctree b/doc/build/doctrees/pages/acknowledgements.doctree
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diff --git a/doc/build/doctrees/pages/modindex.doctree b/doc/build/doctrees/pages/modindex.doctree
diff --git a/doc/build/doctrees/pages/normative_modelling_walkthrough.doctree b/doc/build/doctrees/pages/normative_modelling_walkthrough.doctree
diff --git a/doc/build/doctrees/pages/other_predictive_models.doctree b/doc/build/doctrees/pages/other_predictive_models.doctree
diff --git a/doc/build/doctrees/pages/pcntoolkit_background.doctree b/doc/build/doctrees/pages/pcntoolkit_background.doctree
diff --git a/doc/build/doctrees/pages/post_hoc_analysis.doctree b/doc/build/doctrees/pages/post_hoc_analysis.doctree
diff --git a/doc/build/doctrees/pages/visualizations.doctree b/doc/build/doctrees/pages/visualizations.doctree
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   <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 <span></span>from __future__ import print_function
 from __future__ import division
@@ -104,7 +187,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 from scipy.linalg import LinAlgError
 
 
-<div class="viewcode-block" id="BLR"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR">[docs]</a>class BLR:
+<div class="viewcode-block" id="BLR"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR">[docs]</a>class BLR:
     &quot;&quot;&quot;Bayesian linear regression
 
     Estimation and prediction of Bayesian linear regression models
@@ -237,7 +320,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 
         return beta, alpha, gamma
 
-<div class="viewcode-block" id="BLR.post"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.post">[docs]</a>    def post(self, hyp, X, y, Xv=None):
+<div class="viewcode-block" id="BLR.post"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.post">[docs]</a>    def post(self, hyp, X, y, Xv=None):
         &quot;&quot;&quot; Generic function to compute posterior distribution.
 
             This function will save the posterior mean and precision matrix as
@@ -290,7 +373,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
         self.D = D
         self.hyp = hyp</div>
 
-<div class="viewcode-block" id="BLR.loglik"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.loglik">[docs]</a>    def loglik(self, hyp, X, y, Xv=None):
+<div class="viewcode-block" id="BLR.loglik"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.loglik">[docs]</a>    def loglik(self, hyp, X, y, Xv=None):
         &quot;&quot;&quot; Function to compute compute log (marginal) likelihood &quot;&quot;&quot;
 
         # hyperparameters (alpha not needed)
@@ -348,7 +431,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
         self.nlZ = nlZ
         return nlZ</div>
 
-<div class="viewcode-block" id="BLR.penalized_loglik"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.penalized_loglik">[docs]</a>    def penalized_loglik(self, hyp, X, y, Xv=None, l=0.1, norm=&#39;L1&#39;):
+<div class="viewcode-block" id="BLR.penalized_loglik"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.penalized_loglik">[docs]</a>    def penalized_loglik(self, hyp, X, y, Xv=None, l=0.1, norm=&#39;L1&#39;):
         &quot;&quot;&quot; Function to compute the penalized log (marginal) likelihood 
 
             :param hyp: hyperparameter vector
@@ -367,7 +450,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
             print(&quot;Requested penalty not recognized, choose between &#39;L1&#39; or &#39;L2&#39;.&quot;)
         return L</div>
 
-<div class="viewcode-block" id="BLR.dloglik"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.dloglik">[docs]</a>    def dloglik(self, hyp, X, y, Xv=None):
+<div class="viewcode-block" id="BLR.dloglik"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.dloglik">[docs]</a>    def dloglik(self, hyp, X, y, Xv=None):
         &quot;&quot;&quot; Function to compute derivatives &quot;&quot;&quot;
 
         # hyperparameters
@@ -470,7 +553,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
         return dnlZ</div>
 
     # model estimation (optimization)
-<div class="viewcode-block" id="BLR.estimate"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.estimate">[docs]</a>    def estimate(self, hyp0, X, y, **kwargs):
+<div class="viewcode-block" id="BLR.estimate"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.estimate">[docs]</a>    def estimate(self, hyp0, X, y, **kwargs):
         &quot;&quot;&quot; Function to estimate the model 
 
             :param hyp: hyperparameter vector
@@ -523,7 +606,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 
         return self.hyp</div>
 
-<div class="viewcode-block" id="BLR.predict"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.predict">[docs]</a>    def predict(self, hyp, X, y, Xs, 
+<div class="viewcode-block" id="BLR.predict"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.predict">[docs]</a>    def predict(self, hyp, X, y, Xs, 
                 var_groups_test=None, 
                 var_covariates_test=None, **kwargs):
         &quot;&quot;&quot; Function to make predictions from the model
@@ -575,7 +658,7 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 
         return ys, s2       </div>
 
-<div class="viewcode-block" id="BLR.predict_and_adjust"><a class="viewcode-back" href="../modindex.html#bayesreg.BLR.predict_and_adjust">[docs]</a>    def predict_and_adjust(self, hyp, X, y, Xs=None, 
+<div class="viewcode-block" id="BLR.predict_and_adjust"><a class="viewcode-back" href="../pages/modindex.html#bayesreg.BLR.predict_and_adjust">[docs]</a>    def predict_and_adjust(self, hyp, X, y, Xs=None, 
                              ys=None, 
                              var_groups_test=None,
                              var_groups_adapt=None, **kwargs):
@@ -667,30 +750,42 @@ <h1>Source code for bayesreg</h1><div class="highlight"><pre>
 </pre></div>
 
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