make html

unravel/docs/_build/html/_modules/unravel/register/reg.html

@@ -368,7 +368,7 @@ <h1>Source code for unravel.register.reg</h1><div class="highlight"><pre>
 <span class="sd">    ``reg_prep``, [``seg_copy_tifs``], &amp; [``seg_brain_mask``]</span>
 
 <span class="sd">Next steps: </span>
-<span class="sd">    ``reg_check``</span>
+<span class="sd">    ``reg_check`` and ``vstats_prep``</span>
 <span class="sd">&quot;&quot;&quot;</span>
 
 <span class="kn">import</span> <span class="nn">argparse</span>

unravel/docs/_build/html/_modules/unravel/register/reg_prep.html

@@ -356,7 +356,7 @@ <h1>Source code for unravel.register.reg_prep</h1><div class="highlight"><pre>
 
 <span class="sd">Usage:</span>
 <span class="sd">------</span>
-<span class="sd">    reg_prep -i &lt;asterisk&gt;.czi -td &lt;path/brain_mask_tifs&gt; -e &lt;list of paths to exp dirs&gt; -v</span>
+<span class="sd">    reg_prep -i &lt;asterisk&gt;.czi [-e &lt;list of paths to exp dirs&gt;] [-v]</span>
 
 <span class="sd">Run command from the experiment directory w/ sample?? folder(s), a sample?? folder, or provide -e or -d arguments.</span>
 
@@ -408,6 +408,8 @@ <h1>Source code for unravel.register.reg_prep</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">parser</span><span class="o">.</span><span class="n">parse_args</span><span class="p">()</span></div>
 
 
+<span class="c1"># TODO: Remove args.target_dir since this can be done with ``seg_copy_tifs``</span>
+
 
 <div class="viewcode-block" id="reg_prep">
 <a class="viewcode-back" href="../../../unravel/register/reg_prep.html#unravel.register.reg_prep.reg_prep">[docs]</a>

unravel/docs/_build/html/_modules/unravel/segment/copy_tifs.html

@@ -354,9 +354,9 @@ <h1>Source code for unravel.segment.copy_tifs</h1><div class="highlight"><pre>
 <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">Use ``seg_copy_tifs`` from UNRAVEL to copy a subset of .tif files to a target dir for training ilastik.</span>
 
-<span class="sd">Usage to prep for ``seg_brain_mask`` (if --mask_dir &lt;path/mask_dir&gt; and -e &lt;exp dir paths&gt; were not specified in ``reg_prep``):</span>
-<span class="sd">-------------------------------------------------------------------------------------------------------------------------------</span>
-<span class="sd">    seg_copy_tifs -i reg_inputs/autofl_50um_tifs -s 0010 0060 0110 -o ilastik_brain_mask</span>
+<span class="sd">Usage to prep for ``seg_brain_mask``:</span>
+<span class="sd">-------------------------------------</span>
+<span class="sd">    seg_copy_tifs -i reg_inputs/autofl_50um_tifs -s 0000 0005 0050 -o ilastik_brain_mask</span>
 
 <span class="sd">Usage to prep for ``seg_ilastik`` to segment full resolution immunofluorescence images:</span>
 <span class="sd">---------------------------------------------------------------------------------------</span>

unravel/docs/_build/html/_modules/unravel/voxel_stats/vstats_prep.html

@@ -355,7 +355,8 @@ <h1>Source code for unravel.voxel_stats.vstats_prep</h1><div class="highlight"><
 <span class="sd">Use ``vstats_prep`` from UNRAVEL to load an immunofluo image, subtract its background, and warp it to atlas space.</span>
 
 <span class="sd">Usage:</span>
-<span class="sd">    vstats_prep -i ochann -rb 4 -x 3.5232 -z 6 -o ochann_rb4_gubra_space.nii.gz -e &lt;list of paths to experiment directories&gt; -v</span>
+<span class="sd">------</span>
+<span class="sd">    vstats_prep -i &lt;asterisk&gt;.czi -rb 4 -x $XY -z $Z -o ochann_rb4_atlas_space.nii.gz -e [$DIRS] [-v]</span>
 
 <span class="sd">Prereqs: </span>
 <span class="sd">    ``reg``</span>

unravel/docs/_build/html/_modules/unravel/voxel_stats/z_score.html

@@ -367,6 +367,7 @@ <h1>Source code for unravel.voxel_stats.z_score</h1><div class="highlight"><pre>
 <span class="sd">    vstats_z_score -i atlas_space/sample??_cfos_rb4_atlas_space.nii.gz -amas path/RH_mask.nii.gz -s RHz -v</span>
 
 <span class="sd">Next steps: </span>
+<span class="sd">    - Aggregate outputs with ``utils_agg_files``.</span>
 <span class="sd">    - If analyzing whole brains, consider using ``vstats_whole_to_avg`` to average hemispheres together.</span>
 <span class="sd">    - If using side-specific z-scoring, next use ``vstats_hemi_to_avg`` to average the images.</span>
 <span class="sd">    - Run ``vstats`` to perform voxel-wise stats.</span>
@@ -470,15 +471,15 @@ <h1>Source code for unravel.voxel_stats.z_score</h1><div class="highlight"><pre>
 
             <span class="k">if</span> <span class="n">Path</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">input</span><span class="p">)</span><span class="o">.</span><span class="n">is_absolute</span><span class="p">():</span>
                 <span class="n">input_path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">args</span><span class="o">.</span><span class="n">input</span><span class="p">)</span>
-                <span class="k">if</span> <span class="ow">not</span> <span class="n">input_path</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
-                    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2"> [red]The specified input file </span><span class="si">{</span><span class="n">input_path</span><span class="si">}</span><span class="s2"> does not exist.&quot;</span><span class="p">)</span>
-                    <span class="kn">import</span> <span class="nn">sys</span> <span class="p">;</span> <span class="n">sys</span><span class="o">.</span><span class="n">exit</span><span class="p">()</span>
             <span class="k">else</span><span class="p">:</span>
-                <span class="c1"># Handle relative path or pattern replacement</span>
                 <span class="k">if</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">pattern</span><span class="si">}</span><span class="s2">&quot;</span> <span class="ow">in</span> <span class="n">args</span><span class="o">.</span><span class="n">input</span><span class="p">:</span>
                     <span class="n">input_path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">sample_path</span> <span class="o">/</span> <span class="n">args</span><span class="o">.</span><span class="n">input</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">pattern</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">sample_path</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">))</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">input_path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">sample_path</span> <span class="o">/</span> <span class="n">args</span><span class="o">.</span><span class="n">input</span><span class="p">)</span>
+
+            <span class="k">if</span> <span class="ow">not</span> <span class="n">input_path</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
+                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2"> [red]The specified input file </span><span class="si">{</span><span class="n">input_path</span><span class="si">}</span><span class="s2"> does not exist.&quot;</span><span class="p">)</span>
+                <span class="kn">import</span> <span class="nn">sys</span> <span class="p">;</span> <span class="n">sys</span><span class="o">.</span><span class="n">exit</span><span class="p">()</span>
 
             <span class="n">output</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">input_path</span><span class="p">)</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;.nii.gz&#39;</span><span class="p">,</span> <span class="sa">f</span><span class="s1">&#39;_</span><span class="si">{</span><span class="n">args</span><span class="o">.</span><span class="n">suffix</span><span class="si">}</span><span class="s1">.nii.gz&#39;</span><span class="p">))</span>
             <span class="k">if</span> <span class="n">output</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>

unravel/docs/_build/html/_sources/index.rst.txt

@@ -49,6 +49,9 @@ UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet
     * Voxel-wise analysis of fluorescent signals and cluster correction
     * Validation of hot/cold spots via cell/label density quantification at cellular resolution
 * `UNRAVEL GitHub repository <https://github.com/b-heifets/UNRAVEL/tree/main>`_
+* `UNRAVEL can be installed via the Python Package Index (PyPI) <https://pypi.org/project/heifetslab-unravel/>`_ with this command:
+  .. code-block:: bash
+      pip install heifetslab-unravel
 * `Initial UNRAVEL publication <https://www.nature.com/articles/s41386-023-01613-4>`_
 * UNRAVEL was developed by `the Heifets lab <https://heifetslab.stanford.edu/>`_ and `TensorAnalytics <https://sites.google.com/view/tensoranalytics/home?authuser=0>`_
 * Additional support/guidance was provided by:

unravel/docs/_build/html/_sources/installation.md.txt

@@ -6,7 +6,8 @@
 
 
 ## TL;DR
-* Activate a virtual environment in python
+* Activate a virtual environment in Python
+* Install UNRAVEL via [PyPI](https://pypi.org/project/heifetslab-unravel/):
 ```bash
 pip install heifetslab-unravel
 ```

unravel/docs/_build/html/index.html

@@ -351,9 +351,9 @@
     </div>
 </div><br><section id="un-biased-high-resolution-analysis-and-validation-of-ensembles-using-light-sheet-images">
 <h1>UN-biased high-Resolution Analysis and Validation of Ensembles using Light sheet images<a class="headerlink" href="#un-biased-high-resolution-analysis-and-validation-of-ensembles-using-light-sheet-images" title="Link to this heading">#</a></h1>
-<ul class="simple">
+<ul>
 <li><dl class="simple">
-<dt>UNRAVEL is a <a class="reference external" href="https://www.python.org/">Python</a> package &amp; command line tool for the analysis of brain-wide imaging data, automating:</dt><dd><ul>
+<dt>UNRAVEL is a <a class="reference external" href="https://www.python.org/">Python</a> package &amp; command line tool for the analysis of brain-wide imaging data, automating:</dt><dd><ul class="simple">
 <li><p>Registration of brain-wide images to a common atlas space</p></li>
 <li><p>Quantification of cell/label densities across the brain</p></li>
 <li><p>Voxel-wise analysis of fluorescent signals and cluster correction</p></li>
@@ -363,10 +363,16 @@ <h1>UN-biased high-Resolution Analysis and Validation of Ensembles using Light s
 </dl>
 </li>
 <li><p><a class="reference external" href="https://github.com/b-heifets/UNRAVEL/tree/main">UNRAVEL GitHub repository</a></p></li>
+<li><p><a class="reference external" href="https://pypi.org/project/heifetslab-unravel/">UNRAVEL can be installed via the Python Package Index (PyPI)</a> with this command:
+.. code-block:: bash</p>
+<blockquote>
+<div><p>pip install heifetslab-unravel</p>
+</div></blockquote>
+</li>
 <li><p><a class="reference external" href="https://www.nature.com/articles/s41386-023-01613-4">Initial UNRAVEL publication</a></p></li>
 <li><p>UNRAVEL was developed by <a class="reference external" href="https://heifetslab.stanford.edu/">the Heifets lab</a> and <a class="reference external" href="https://sites.google.com/view/tensoranalytics/home?authuser=0">TensorAnalytics</a></p></li>
 <li><dl class="simple">
-<dt>Additional support/guidance was provided by:</dt><dd><ul>
+<dt>Additional support/guidance was provided by:</dt><dd><ul class="simple">
 <li><p><a class="reference external" href="https://med.stanford.edu/neurosurgery/research/shamloo.html">The Shamloo lab</a></p></li>
 <li><p><a class="reference external" href="https://profiles.stanford.edu/robert-malenka">The Malenka lab</a></p></li>
 <li><p><a class="reference external" href="https://med.stanford.edu/nidap50.html">The Stanford-based P50 center funded by NIDA</a></p></li>

unravel/docs/_build/html/installation.html

@@ -366,7 +366,8 @@ <h1>Installation<a class="headerlink" href="#installation" title="Link to this h
 <section id="tl-dr">
 <h2>TL;DR<a class="headerlink" href="#tl-dr" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p>Activate a virtual environment in python</p></li>
+<li><p>Activate a virtual environment in Python</p></li>
+<li><p>Install UNRAVEL via <a class="reference external" href="https://pypi.org/project/heifetslab-unravel/">PyPI</a>:</p></li>
 </ul>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>heifetslab-unravel
 </pre></div>

unravel/docs/_build/html/unravel/register/reg.html

@@ -504,7 +504,7 @@ <h2>Usage:<a class="headerlink" href="#usage" title="Link to this heading">#</a>
 </dd>
 <dt>Prereqs:</dt><dd><p><code class="docutils literal notranslate"><span class="pre">reg_prep</span></code>, [<code class="docutils literal notranslate"><span class="pre">seg_copy_tifs</span></code>], &amp; [<code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code>]</p>
 </dd>
-<dt>Next steps:</dt><dd><p><code class="docutils literal notranslate"><span class="pre">reg_check</span></code></p>
+<dt>Next steps:</dt><dd><p><code class="docutils literal notranslate"><span class="pre">reg_check</span></code> and <code class="docutils literal notranslate"><span class="pre">vstats_prep</span></code></p>
 </dd>
 </dl>
 </section>

unravel/docs/_build/html/unravel/register/reg_prep.html

@@ -492,7 +492,7 @@
 <section id="usage">
 <h2>Usage:<a class="headerlink" href="#usage" title="Link to this heading">#</a></h2>
 <blockquote>
-<div><p>reg_prep -i &lt;asterisk&gt;.czi -td &lt;path/brain_mask_tifs&gt; -e &lt;list of paths to exp dirs&gt; -v</p>
+<div><p>reg_prep -i &lt;asterisk&gt;.czi [-e &lt;list of paths to exp dirs&gt;] [-v]</p>
 </div></blockquote>
 <p>Run command from the experiment directory w/ sample?? folder(s), a sample?? folder, or provide -e or -d arguments.</p>
 <dl class="simple">

unravel/docs/_build/html/unravel/segment/copy_tifs.html

@@ -489,10 +489,10 @@
   <section id="module-unravel.segment.copy_tifs">
 <span id="unravel-segment-copy-tifs-module"></span><span id="unravel-segment-copy-tifs"></span><h1>unravel.segment.copy_tifs module<a class="headerlink" href="#module-unravel.segment.copy_tifs" title="Link to this heading">#</a></h1>
 <p>Use <code class="docutils literal notranslate"><span class="pre">seg_copy_tifs</span></code> from UNRAVEL to copy a subset of .tif files to a target dir for training ilastik.</p>
-<section id="usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep">
-<h2>Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code> (if –mask_dir &lt;path/mask_dir&gt; and -e &lt;exp dir paths&gt; were not specified in <code class="docutils literal notranslate"><span class="pre">reg_prep</span></code>):<a class="headerlink" href="#usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep" title="Link to this heading">#</a></h2>
+<section id="usage-to-prep-for-seg-brain-mask">
+<h2>Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code>:<a class="headerlink" href="#usage-to-prep-for-seg-brain-mask" title="Link to this heading">#</a></h2>
 <blockquote>
-<div><p>seg_copy_tifs -i reg_inputs/autofl_50um_tifs -s 0010 0060 0110 -o ilastik_brain_mask</p>
+<div><p>seg_copy_tifs -i reg_inputs/autofl_50um_tifs -s 0000 0005 0050 -o ilastik_brain_mask</p>
 </div></blockquote>
 </section>
 <section id="usage-to-prep-for-seg-ilastik-to-segment-full-resolution-immunofluorescence-images">
@@ -575,7 +575,7 @@ <h2>Usage to prep for <code class="docutils literal notranslate"><span class="pr
   </div>
   <nav class="bd-toc-nav page-toc" aria-labelledby="pst-page-navigation-heading-2">
     <ul class="visible nav section-nav flex-column">
-<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code> (if –mask_dir &lt;path/mask_dir&gt; and -e &lt;exp dir paths&gt; were not specified in <code class="docutils literal notranslate"><span class="pre">reg_prep</span></code>):</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usage-to-prep-for-seg-brain-mask">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code>:</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usage-to-prep-for-seg-ilastik-to-segment-full-resolution-immunofluorescence-images">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_ilastik</span></code> to segment full resolution immunofluorescence images:</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#unravel.segment.copy_tifs.parse_args"><code class="docutils literal notranslate"><span class="pre">parse_args()</span></code></a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#unravel.segment.copy_tifs.copy_specific_slices"><code class="docutils literal notranslate"><span class="pre">copy_specific_slices()</span></code></a></li>

unravel/docs/_build/html/unravel/segment/toc.html

@@ -494,7 +494,7 @@ <h1>unravel.segment package<a class="headerlink" href="#unravel-segment-package"
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="copy_tifs.html">unravel.segment.copy_tifs module</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="copy_tifs.html#usage-to-prep-for-seg-brain-mask-if-mask-dir-path-mask-dir-and-e-exp-dir-paths-were-not-specified-in-reg-prep">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code> (if –mask_dir &lt;path/mask_dir&gt; and -e &lt;exp dir paths&gt; were not specified in <code class="docutils literal notranslate"><span class="pre">reg_prep</span></code>):</a></li>
+<li class="toctree-l2"><a class="reference internal" href="copy_tifs.html#usage-to-prep-for-seg-brain-mask">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_brain_mask</span></code>:</a></li>
 <li class="toctree-l2"><a class="reference internal" href="copy_tifs.html#usage-to-prep-for-seg-ilastik-to-segment-full-resolution-immunofluorescence-images">Usage to prep for <code class="docutils literal notranslate"><span class="pre">seg_ilastik</span></code> to segment full resolution immunofluorescence images:</a></li>
 <li class="toctree-l2"><a class="reference internal" href="copy_tifs.html#unravel.segment.copy_tifs.parse_args"><code class="docutils literal notranslate"><span class="pre">parse_args()</span></code></a></li>
 <li class="toctree-l2"><a class="reference internal" href="copy_tifs.html#unravel.segment.copy_tifs.copy_specific_slices"><code class="docutils literal notranslate"><span class="pre">copy_specific_slices()</span></code></a></li>