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targeted_scaling_guide.html
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<title>Scaling against a reference dataset with DIALS — DIALS documentation</title>
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<div class="section" id="scaling-against-a-reference-dataset-with-dials">
<h1>Scaling against a reference dataset with DIALS<a class="headerlink" href="#scaling-against-a-reference-dataset-with-dials" title="Permalink to this headline">¶</a></h1>
<p>This document provides a guide on how to scale a dataset against a reference
dataset, referred to as the target dataset.
The target dataset can be either a dataset scaled with dials.scale, or an mtz
file containing a scaled dataset.
Any number of datasets can be scaled against the reference dataset at once,
giving the same scaling result as if each dataset were scaled as an independent
job. The only difference is that all scaled datasets would be output in one
scaled.refl and scaled.expt, which may be more or less convenient
for further processing.</p>
<div class="section" id="scaling-against-a-dials-reference-dataset">
<h2>Scaling against a dials reference dataset<a class="headerlink" href="#scaling-against-a-dials-reference-dataset" title="Permalink to this headline">¶</a></h2>
<p>In this example, reference.refl and reference.expt are
from a dataset that has already been scaled with dials.scale. To scale another
dataset (datafiles integrated.refl, integrated.expt) against this
target/reference, one should use the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">dials</span><span class="o">.</span><span class="n">scale</span> <span class="n">only_target</span><span class="o">=</span><span class="kc">True</span> <span class="n">integrated</span><span class="o">.</span><span class="n">refl</span> <span class="n">integrated</span><span class="o">.</span><span class="n">expt</span> <span class="n">reference</span><span class="o">.</span><span class="n">refl</span> <span class="n">reference</span><span class="o">.</span><span class="n">expt</span>
</pre></div>
</div>
<p>This will scale the intensities of the dataset to agree as closely as possible
with the intensities of the reference dataset, and save the scaled dataset to
scaled.refl, scaled.expt (the reference files are unchanged).
The <code class="samp docutils literal notranslate"><span class="pre">only_target=True</span></code> command is important, else all the data will be
scaled together and output in a joint output file.</p>
</div>
<div class="section" id="scaling-against-a-reference-mtz-file">
<h2>Scaling against a reference mtz file<a class="headerlink" href="#scaling-against-a-reference-mtz-file" title="Permalink to this headline">¶</a></h2>
<p>In this case, it is assumed that the intensity and variance columns of the mtz
file have already been scaled. Targeted scaling would be run with the following
command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">dials</span><span class="o">.</span><span class="n">scale</span> <span class="n">integrated</span><span class="o">.</span><span class="n">refl</span> <span class="n">integrated</span><span class="o">.</span><span class="n">expt</span> <span class="n">target_mtz</span><span class="o">=</span><span class="n">scaled</span><span class="o">.</span><span class="n">mtz</span>
</pre></div>
</div>
<p>The targeted scaling algorithm is the same regardless of the target datafile type,
likewise the scaled dataset will be saved to scaled.refl and scaled.expt.</p>
</div>
<div class="section" id="general-considerations-for-suitable-options">
<h2>General considerations for suitable options<a class="headerlink" href="#general-considerations-for-suitable-options" title="Permalink to this headline">¶</a></h2>
<p>A common use case for scaling against a reference is to scale thin-wedge
datasets against a high quality full-sweep dataset. To give the best scaling, it
may be necessary to manually set the scaling model parameters: for more details
see the <em>In-depth guide to scaling options in DIALS</em>.
In the case of very thin wedge/stills datasets, or depending on the scientific question under investigation, it may be
suitable to set <code class="samp docutils literal notranslate"><span class="pre">model=KB</span></code>, to give a single global scale and relative B-factor
to each dataset. However, if significant intensity variation/decay is present in each
measurement, it may be best to use <code class="samp docutils literal notranslate"><span class="pre">model=physical</span></code>, setting <code class="samp docutils literal notranslate"><span class="pre">absorption_term=False</span></code>
and specifying values for <code class="samp docutils literal notranslate"><span class="pre">scale_interval</span></code> and <code class="samp docutils literal notranslate"><span class="pre">decay_interval</span></code>.</p>
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