Deployed 9ca6bea to v10.0.X with MkDocs 1.6.0 and mike 2.1.2

v10.0.X/part2/bin-wise-stats/index.html

@@ -1407,8 +1407,8 @@ <h2 id="introduction">Introduction</h2>
 <p>By default the script will attempt to assign a single nuisance parameter to scale the sum of the process yields in each bin, constrained by the total uncertainty, instead of requiring separate parameters, one per process. This is sometimes referred to as the <a href="http://inspirehep.net/record/35053">Barlow-Beeston</a>-lite approach, and is useful as it minimises the number of parameters required in the maximum likelihood fit. A useful description of this approach may be found in section 5 of <a href="https://arxiv.org/pdf/1103.0354.pdf">this report</a>.</p>
 <h2 id="usage-instructions">Usage instructions</h2>
 <p>The following line should be added at the bottom of the datacard, underneath the systematics, to produce a new-style workspace and optionally enable the automatic bin-wise uncertainties:</p>
-<pre><code class="language-nohighlight">[channel] autoMCStats [threshold] [include-signal = 0] [hist-mode = 1]
-</code></pre>
+<div class="highlight"><pre><span></span><code>[channel] autoMCStats [threshold] [include-signal = 0] [hist-mode = 1]
+</code></pre></div>
 <p>The first string <code>channel</code> should give the name of the channels (bins) in the datacard for which the new histogram classes should be used. The wildcard <code>*</code> is supported for selecting multiple channels in one go. The value of <code>threshold</code> should be set to a value greater than or equal to zero to enable the creation of automatic bin-wise uncertainties, or <code>-1</code> to use the new histogram classes without these uncertainties. A positive value sets the threshold on the effective number of unweighted events above which the uncertainty will be modeled with the Barlow-Beeston-lite approach described above. Below the threshold an individual uncertainty per-process will be created. The algorithm is described in more detail below.</p>
 <p>The last two settings are optional. The first of these, <code>include-signal</code> has a default value of <code>0</code> but can be set to <code>1</code> as an alternative. By default, the total nominal yield and uncertainty used to test the threshold excludes signal processes. The reason for this is that typically the initial signal normalization is arbitrary, and could unduly lead to a bin being considered well-populated despite poorly populated background templates. Setting this flag will include the signal processes in the uncertainty analysis. Note that this option only affects the logic for creating a single Barlow-Beeston-lite parameter vs. separate per-process parameters - the uncertainties on all signal processes are always included in the actual model! The second flag changes the way the normalization effect of shape-altering uncertainties is handled. In the default mode (<code>1</code>) the normalization is handled separately from the shape morphing via a an asymmetric log-normal term. This is identical to how <span style="font-variant:small-caps;">Combine</span> has always handled shape morphing. When set to <code>2</code>, the normalization will be adjusted in the shape morphing directly. Unless there is a strong motivation we encourage users to leave this on the default setting.</p>
 <h2 id="description-of-the-algorithm">Description of the algorithm</h2>

v10.0.X/part2/bsm-higgs-models/index.html

@@ -1370,8 +1370,8 @@ <h1 id="physics-models-for-extended-higgs-sector-searches">Physics Models for Ex
 <h2 id="two-higgs-models">Two Higgs Models</h2>
 <p>These models are for the case where there are just Two Higgs bosons, one of which is the SM-like Higgs boson that was discovered at the LHC. The two Higgs models are implemented in the python file <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/TwoHiggsModels.py"><code>TwoHiggsModels.py</code></a>. For each of these models, we assume that the SM-like Higgs boson has mass specified by <code>MH_SM</code>, while the additional boson has mass <code>MH</code>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.TwoHiggsModels:model
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.TwoHiggsModels:model
+</code></pre></div>
 <table>
 <thead>
 <tr>
@@ -1416,8 +1416,8 @@ <h2 id="two-higgs-models">Two Higgs Models</h2>
 <h2 id="two-higgs-doublet-models">Two Higgs Doublet Models</h2>
 <p>In these models, the couplings of the SM-like Higgs boson are modified according to the type of 2HDM with parameters <span class="arithmatex">\(\cos(\beta-\alpha)\)</span> and <span class="arithmatex">\(\tan\beta\)</span>. The two Higgs doublet models are implemented in the python file <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/AdditionalModels.py"><code>AdditionalModels.py</code></a>.  In this model, the Higgs boson mass is <code>MH</code>, and it can be promoted to a POI by including the option <code>--PO higgsMassRange=[low,high]</code>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.AdditionalModels:model_name
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.AdditionalModels:model_name
+</code></pre></div>
 <table>
 <thead>
 <tr>
@@ -1462,8 +1462,8 @@ <h2 id="two-higgs-doublet-models">Two Higgs Doublet Models</h2>
 <h2 id="fermiophobic-higgs-model">Fermiophobic Higgs Model</h2>
 <p>This model is for the case where the additional Higgs boson does not couple to fermions. The fermiophobic Higgs model is implemented in the python file <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/HiggsFermiophobic.py"><code>HiggsFermiophobic.py</code></a>. In this model, the Higgs boson mass is <code>MH</code>, and it can be promoted to a POI by including the option <code>--PO higgsMassRange=[low,high]</code>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.HiggsFermiophobic:model_name
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.HiggsFermiophobic:model_name
+</code></pre></div>
 <table>
 <thead>
 <tr>

v10.0.X/part2/higgscouplings/index.html

@@ -1352,9 +1352,8 @@ <h1 id="physics-models-for-sm-higgs-boson-couplings">Physics Models for SM Higgs
 <h2 id="lhc-hcg-models">LHC HCG Models</h2>
 <p>The following models are used in the LHC Higgs Combination Group (LHC HCG) to perform measurements of the Higgs boson couplings. They are well defined only for a SM Higgs boson mass of a few GeV around the measured value <span class="arithmatex">\(m_H \approx 125\)</span> GeV. The models are implemented in the python file  <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/LHCHCGModels.py"><code>LHCHCGModels.py</code></a>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.LHCHCGModels:model
-
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.LHCHCGModels:model
+</code></pre></div>
 <table>
 <thead>
 <tr>
@@ -1440,9 +1439,8 @@ <h2 id="lhc-hcg-models">LHC HCG Models</h2>
 </table>
 <p>The next models are constrained models to study a limited set of ratios of couplings. These are particularly useful to study models such as 2HDM that modify the SM Higgs couplings in a specific way. The models are implemented in the python file  <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/HiggsCouplings.py"><code>HiggsCouplings.py</code></a>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.HiggsCouplings:model
-
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.HiggsCouplings:model
+</code></pre></div>
 <table>
 <thead>
 <tr>
@@ -1480,9 +1478,8 @@ <h2 id="lhc-hcg-models">LHC HCG Models</h2>
 <h2 id="outdated-couplings-modifer-models">Outdated couplings modifer models</h2>
 <p>These models were used early in the Higgs discovery, but are now considered outdated. They are still available for backward compatibility and for simple studies, but are generally not recommended. The models are implemented in the python file  <a href="https://github.com/cms-analysis/HiggsAnalysis-CombinedLimit/blob/main/python/HiggsCouplings_ICHEP2012.py"><code>HiggsCouplings.py</code></a>.</p>
 <p>You can produce the model by including the  following option in the <code>text2workspace.py</code> command:</p>
-<pre><code class="language-sh">-P HiggsAnalysis.CombinedLimit.HiggsCouplings:model
-
-</code></pre>
+<div class="highlight"><pre><span></span><code>-P<span class="w"> </span>HiggsAnalysis.CombinedLimit.HiggsCouplings:model
+</code></pre></div>
 <table>
 <thead>
 <tr>