went through documentation, going to use as template for paper

docs/_build_html/_sources/clustergrammer_js.txt

@@ -5,7 +5,7 @@ Clustergrammer-JS
 |npm-version|
 |license|
 
-Clustergrammer-JS is the front-end JavaScript library that builds the interactive heatmap visualization in `SVG`_ using the visualization library `D3.js`_
+Clustergrammer-JS is the front-end JavaScript library that builds the interactive heatmap visualization in `SVG`_ using the visualization library `D3.js`_. The library is free and open-source and can be found on `GitHub`_.
 
 .. _clustergrammer_js_dependencies:
 
@@ -33,21 +33,29 @@ JavaScript Workflow Example
 This workflow shows how to generate a visualization using the JSON produced by Clustergrammer.py
 ::
 
-  // load visualization JSON to network_data
+  // the visualization JSON (produced by Clustergrammer-PY)
+  var network_data = {
+                        "row_nodes":[...],
+                        "col_nodes":[...],
+                        "mat": [...]
+                      }
+  // args must contain root of container and the visualization JSON
   var args = {
     'root': '#id_of_container',
     'network_data': 'network_data'
   }
 
+  // Clustergrammer returns a Clustergrammer object in addition to making
+  // the visualization
   var cgm = Clustergrammer(args);
 
-The ``id`` of the container where the visualization will be made is passed as ``root`` (this root container must be made by the user). The :ref:`visualization_json` contains the information necessary to generate the visualization and is passed as ``network_data``. See the :ref:`clustergrammer_js_api` for additional arguments that can be passed to Clustergrammer.js.
+The ``id`` of the container where the visualization will be made is passed as ``root`` (this root container must be made by the user). The :ref:`visualization_json` (produced by :ref:`clustergrammer_py`) contains all the information necessary to generate the visualization and is passed in this example as ``network_data``. See the :ref:`clustergrammer_js_api` for additional arguments that can be passed to Clustergrammer.js.
 
 .. _example_pages:
 
 Example Pages
 =============
-The `Clustergrammer GitHub repo`_ contains several example pages demonstrating how to build a webpage with a Clustergrammer heatmap. The page `index.html`_ and corresponding script `load_clustergram.js`_ show how to make a full-screen resizable visualization. The page `multiple_clust.html`_ and corresponding script `load_multiple_clustergrams.js`_ show how to visualize multiple clustergrams on one page. Note that each heatmap requires its own container.
+The `Clustergrammer GitHub repo`_ contains several example pages demonstrating how to build a webpage with a Clustergrammer visualization. The page `index.html`_ and corresponding script `load_clustergram.js`_ show how to make a full-screen resizable visualization. The page `multiple_clust.html`_ and corresponding script `load_multiple_clustergrams.js`_ show how to visualize multiple clustergrams on one page. Note that each visualization requires its own container.
 
 .. _clustergrammer_js_api:
 
@@ -297,6 +305,7 @@ The Clustergrammer-JS source code can be found in the `Clustergrammer GitHub rep
 
 Please :ref:`contact` Nicolas Fernandez and Avi Ma'ayan with questions or use the GitHub `issues`_ feature to report an issue.
 
+.. _`GitHub`: https://github.com/MaayanLab/clustergrammer
 .. _`SVG`: https://en.wikipedia.org/wiki/Scalable_Vector_Graphics
 .. _`Clustergrammer GitHub repo`: https://github.com/MaayanLab/clustergrammer
 .. _`npm package`: https://www.npmjs.com/package/clustergrammer

docs/_build_html/_sources/clustergrammer_py.txt

@@ -4,7 +4,7 @@ Clustergrammer-PY
 -----------------
 |pypi-version|
 
-Clustergrammer-PY is the back-end Python library that is used to hierarchically cluster the data and generate the :ref:`visualization_json` for the front end :ref:`clustergrammer_js` visualization library. Clustergrammer-PY is compatible with Python 2 and 3.
+Clustergrammer-PY is the back-end Python library that is used to hierarchically cluster the data and generate the :ref:`visualization_json` for the front end :ref:`clustergrammer_js` visualization library. Clustergrammer-PY is compatible with Python 2 and 3. The library is free and open-source and can be found on `GitHub`_.
 
 .. _clustergrammer_py_dependencies:
 
@@ -90,6 +90,7 @@ Clustergrammer-PY's source code can be found in the `clustergrammer-py`_ GitHub
 
 Please :ref:`contact` Nicolas Fernandez and Avi Ma'ayan with questions or use the GitHub `issues`_ feature to report an issue.
 
+.. _`GitHub`: http://github.com/MaayanLab/clustergrammer-py
 .. _`GitHub repo`: http://github.com/MaayanLab/clustergrammer-py
 .. _`package index`: https://pypi.python.org/pypi?:action=display&name=clustergrammer
 .. _`clustergrammer-py`: https://github.com/MaayanLab/clustergrammer-py

docs/_build_html/_sources/clustergrammer_widget.txt

@@ -6,7 +6,7 @@ Clustergrammer Jupyter Widget
 |pypi-version|
 |npm-version|
 
-`Jupyter`_ notebooks are ideal for generating reproducible workflows and analysis. They are also the best way to share Clustergrammer's interactive visualizations while providing context, analysis, and the underlying data to enable reproducibility (see :ref:`clustergrammer_widget_examples`). The Clustergrammer Widget enables users to easily produce interactive visualizations within a Jupyter notebook that can be shared with collaborators (using `nbviewer`_). Clustergrammer-Widget can be used to visualize a matrix of data from a file or from a `Pandas`_ DataFrame (see :ref:`matrix_format_io` for more information).
+`Jupyter`_ notebooks are ideal for generating reproducible workflows and analysis. They are also the best way to share Clustergrammer's interactive visualizations while providing context, analysis, and the underlying data to enable reproducibility (see :ref:`clustergrammer_widget_examples`). The Clustergrammer Widget enables users to easily produce interactive visualizations within a Jupyter notebook that can be shared with collaborators (using `nbviewer`_). Clustergrammer-Widget can be used to visualize a matrix of data from a file or from a `Pandas`_ DataFrame (see :ref:`matrix_format_io` for more information). The library is free and open-source and can be found on `GitHub`_.
 
 Clustergrammer has been applied to a wide variety of biological and non-biological data. See the Jupyter notebook examples below and :ref:`case_studies` for more information:
 
@@ -147,6 +147,7 @@ Clustergrammer-Widget's source code can be found in the `clustergrammer-widget`_
 
 Please :ref:`contact` Nicolas Fernandez and Avi Ma'ayan with questions or use the GitHub `issues`_ feature to report an issue.
 
+.. _`GitHub`: https://github.com/MaayanLab/clustergrammer-widget
 .. _`ipywidgets version 6`: https://github.com/ipython/ipywidgets/releases
 .. _`ipywidgets`: http://ipywidgets.readthedocs.io/en/latest/
 .. _`cookie cutter`: https://github.com/jupyter/widget-cookiecutter

docs/_build_html/_sources/index.txt

@@ -2,7 +2,7 @@
 
 Welcome to Clustergrammer's Documentation!
 ------------------------------------------
-Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap (see :ref:`intro_heatmap_clustergram` for more information). Clustergrammer's front end (:ref:`clustergrammer_js`) is built using `D3.js`_ and its back end (:ref:`clustergrammer_py`) is built using `Python`_. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see :ref:`biology_specific_features`) to facilitate the exploration of gene-level biological data. Press play or interact with the gene-expression demo below to see some of Clustergrammer's interactive features and refer to :ref:`interacting_with_viz` for more information:
+Clustergrammer is a web-based tool for visualizing and analyzing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap (see :ref:`intro_heatmap_clustergram` for more information). Clustergrammer's front end (:ref:`clustergrammer_js`) is built using `D3.js`_ and its back end (:ref:`clustergrammer_py`) is built using `Python`_. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see :ref:`biology_specific_features`) to facilitate the exploration of gene-level biological data. The library is free and open-source and can be found on `GitHub`_. Press play or interact with the gene-expression demo below to see some of Clustergrammer's interactive features and refer to :ref:`interacting_with_viz` for more information:
 
 .. raw:: html
 
@@ -64,6 +64,7 @@ Contents:
    developing_with_clustergrammer
    license
 
+.. _`GitHub`: https://github.com/MaayanLab/clustergrammer
 .. _`https://amp.pharm.mssm.edu/clustergrammer/`: https://amp.pharm.mssm.edu/clustergrammer/
 .. _`D3.js`: https://d3js.org/
 .. _`Python`: https://www.python.org/

docs/_build_html/clustergrammer_js.html

@@ -154,7 +154,7 @@
 <span id="id1"></span><h1>Clustergrammer-JS<a class="headerlink" href="#clustergrammer-js" title="Permalink to this headline">¶</a></h1>
 <p><a class="reference external" href="https://www.npmjs.com/package/clustergrammer"><img alt="version" src="https://img.shields.io/npm/v/clustergrammer.svg" /></a>
 <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/LICENSES/LICENSE"><img alt="license" src="https://img.shields.io/npm/l/clustergrammer.svg" /></a></p>
-<p>Clustergrammer-JS is the front-end JavaScript library that builds the interactive heatmap visualization in <a class="reference external" href="https://en.wikipedia.org/wiki/Scalable_Vector_Graphics">SVG</a> using the visualization library <a class="reference external" href="https://d3js.org/">D3.js</a></p>
+<p>Clustergrammer-JS is the front-end JavaScript library that builds the interactive heatmap visualization in <a class="reference external" href="https://en.wikipedia.org/wiki/Scalable_Vector_Graphics">SVG</a> using the visualization library <a class="reference external" href="https://d3js.org/">D3.js</a>. The library is free and open-source and can be found on <a class="reference external" href="https://github.com/MaayanLab/clustergrammer">GitHub</a>.</p>
 <div class="section" id="clustergrammer-js-dependencies">
 <span id="id2"></span><h2>Clustergrammer-JS Dependencies<a class="headerlink" href="#clustergrammer-js-dependencies" title="Permalink to this headline">¶</a></h2>
 <ul class="simple">
@@ -175,20 +175,28 @@ <h2>Installation<a class="headerlink" href="#installation" title="Permalink to t
 <div class="section" id="javascript-workflow-example">
 <span id="id3"></span><h2>JavaScript Workflow Example<a class="headerlink" href="#javascript-workflow-example" title="Permalink to this headline">¶</a></h2>
 <p>This workflow shows how to generate a visualization using the JSON produced by Clustergrammer.py</p>
-<div class="highlight-default"><div class="highlight"><pre><span></span><span class="o">//</span> <span class="n">load</span> <span class="n">visualization</span> <span class="n">JSON</span> <span class="n">to</span> <span class="n">network_data</span>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="o">//</span> <span class="n">the</span> <span class="n">visualization</span> <span class="n">JSON</span> <span class="p">(</span><span class="n">produced</span> <span class="n">by</span> <span class="n">Clustergrammer</span><span class="o">-</span><span class="n">PY</span><span class="p">)</span>
+<span class="n">var</span> <span class="n">network_data</span> <span class="o">=</span> <span class="p">{</span>
+                      <span class="s2">&quot;row_nodes&quot;</span><span class="p">:[</span><span class="o">...</span><span class="p">],</span>
+                      <span class="s2">&quot;col_nodes&quot;</span><span class="p">:[</span><span class="o">...</span><span class="p">],</span>
+                      <span class="s2">&quot;mat&quot;</span><span class="p">:</span> <span class="p">[</span><span class="o">...</span><span class="p">]</span>
+                    <span class="p">}</span>
+<span class="o">//</span> <span class="n">args</span> <span class="n">must</span> <span class="n">contain</span> <span class="n">root</span> <span class="n">of</span> <span class="n">container</span> <span class="ow">and</span> <span class="n">the</span> <span class="n">visualization</span> <span class="n">JSON</span>
 <span class="n">var</span> <span class="n">args</span> <span class="o">=</span> <span class="p">{</span>
   <span class="s1">&#39;root&#39;</span><span class="p">:</span> <span class="s1">&#39;#id_of_container&#39;</span><span class="p">,</span>
   <span class="s1">&#39;network_data&#39;</span><span class="p">:</span> <span class="s1">&#39;network_data&#39;</span>
 <span class="p">}</span>
 
+<span class="o">//</span> <span class="n">Clustergrammer</span> <span class="n">returns</span> <span class="n">a</span> <span class="n">Clustergrammer</span> <span class="nb">object</span> <span class="ow">in</span> <span class="n">addition</span> <span class="n">to</span> <span class="n">making</span>
+<span class="o">//</span> <span class="n">the</span> <span class="n">visualization</span>
 <span class="n">var</span> <span class="n">cgm</span> <span class="o">=</span> <span class="n">Clustergrammer</span><span class="p">(</span><span class="n">args</span><span class="p">);</span>
 </pre></div>
 </div>
-<p>The <code class="docutils literal"><span class="pre">id</span></code> of the container where the visualization will be made is passed as <code class="docutils literal"><span class="pre">root</span></code> (this root container must be made by the user). The <a class="reference internal" href="#visualization-json"><span class="std std-ref">Visualization-JSON</span></a> contains the information necessary to generate the visualization and is passed as <code class="docutils literal"><span class="pre">network_data</span></code>. See the <a class="reference internal" href="#clustergrammer-js-api"><span class="std std-ref">Clustergrammer-JS API</span></a> for additional arguments that can be passed to Clustergrammer.js.</p>
+<p>The <code class="docutils literal"><span class="pre">id</span></code> of the container where the visualization will be made is passed as <code class="docutils literal"><span class="pre">root</span></code> (this root container must be made by the user). The <a class="reference internal" href="#visualization-json"><span class="std std-ref">Visualization-JSON</span></a> (produced by <a class="reference internal" href="clustergrammer_py.html#clustergrammer-py"><span class="std std-ref">Clustergrammer-PY</span></a>) contains all the information necessary to generate the visualization and is passed in this example as <code class="docutils literal"><span class="pre">network_data</span></code>. See the <a class="reference internal" href="#clustergrammer-js-api"><span class="std std-ref">Clustergrammer-JS API</span></a> for additional arguments that can be passed to Clustergrammer.js.</p>
 </div>
 <div class="section" id="example-pages">
 <span id="id4"></span><h2>Example Pages<a class="headerlink" href="#example-pages" title="Permalink to this headline">¶</a></h2>
-<p>The <a class="reference external" href="https://github.com/MaayanLab/clustergrammer">Clustergrammer GitHub repo</a> contains several example pages demonstrating how to build a webpage with a Clustergrammer heatmap. The page <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/index.html">index.html</a> and corresponding script <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/js/load_clustergram.js">load_clustergram.js</a> show how to make a full-screen resizable visualization. The page <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/multiple_clustergrams.html">multiple_clust.html</a> and corresponding script <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/js/load_multiple_clustergrams.js">load_multiple_clustergrams.js</a> show how to visualize multiple clustergrams on one page. Note that each heatmap requires its own container.</p>
+<p>The <a class="reference external" href="https://github.com/MaayanLab/clustergrammer">Clustergrammer GitHub repo</a> contains several example pages demonstrating how to build a webpage with a Clustergrammer visualization. The page <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/index.html">index.html</a> and corresponding script <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/js/load_clustergram.js">load_clustergram.js</a> show how to make a full-screen resizable visualization. The page <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/multiple_clustergrams.html">multiple_clust.html</a> and corresponding script <a class="reference external" href="https://github.com/MaayanLab/clustergrammer/blob/master/js/load_multiple_clustergrams.js">load_multiple_clustergrams.js</a> show how to visualize multiple clustergrams on one page. Note that each visualization requires its own container.</p>
 </div>
 <div class="section" id="clustergrammer-js-api">
 <span id="id5"></span><h2>Clustergrammer-JS API<a class="headerlink" href="#clustergrammer-js-api" title="Permalink to this headline">¶</a></h2>

docs/_build_html/clustergrammer_py.html

@@ -151,7 +151,7 @@
   <div class="section" id="clustergrammer-py">
 <span id="id1"></span><h1>Clustergrammer-PY<a class="headerlink" href="#clustergrammer-py" title="Permalink to this headline">¶</a></h1>
 <p><a class="reference external" href="https://pypi.python.org/pypi?:action=display&amp;name=clustergrammer"><img alt="version" src="https://img.shields.io/pypi/v/clustergrammer.svg" /></a></p>
-<p>Clustergrammer-PY is the back-end Python library that is used to hierarchically cluster the data and generate the <a class="reference internal" href="clustergrammer_js.html#visualization-json"><span class="std std-ref">Visualization-JSON</span></a> for the front end <a class="reference internal" href="clustergrammer_js.html#clustergrammer-js"><span class="std std-ref">Clustergrammer-JS</span></a> visualization library. Clustergrammer-PY is compatible with Python 2 and 3.</p>
+<p>Clustergrammer-PY is the back-end Python library that is used to hierarchically cluster the data and generate the <a class="reference internal" href="clustergrammer_js.html#visualization-json"><span class="std std-ref">Visualization-JSON</span></a> for the front end <a class="reference internal" href="clustergrammer_js.html#clustergrammer-js"><span class="std std-ref">Clustergrammer-JS</span></a> visualization library. Clustergrammer-PY is compatible with Python 2 and 3. The library is free and open-source and can be found on <a class="reference external" href="http://github.com/MaayanLab/clustergrammer-py">GitHub</a>.</p>
 <div class="section" id="clustergrammer-py-dependencies">
 <span id="id2"></span><h2>Clustergrammer-PY Dependencies<a class="headerlink" href="#clustergrammer-py-dependencies" title="Permalink to this headline">¶</a></h2>
 <ul class="simple">