From 0f7aee7ea7bf76fd3030f9d95bff3a7f776d62da Mon Sep 17 00:00:00 2001
From: Matthew Dippel <mdip226@gmail.com>
Date: Sat, 29 Jul 2023 18:02:07 -0400
Subject: [PATCH 1/2] clearer

---
 spatialpy/core/timespan.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spatialpy/core/timespan.py b/spatialpy/core/timespan.py
index d32ea1ee..f467bb86 100644
--- a/spatialpy/core/timespan.py
+++ b/spatialpy/core/timespan.py
@@ -25,10 +25,10 @@ class TimeSpan(Iterator):
     the species populations during the simulation.
 
     :param items: Evenly-spaced list of times at which to sample the species populations during the simulation. 
-            Best to use the form np.linspace(<start time>, <end time>, <number of time-points, inclusive>)
+            Best to use the form np.linspace(0, <end time>, <number of time-points, inclusive>)
     :type items: list, tuple, range, or numpy.ndarray
     
-    :param timestep_size: Size of each timestep in seconds
+    :param timestep_size: Size of each timestep
     :type timestep_size: int | float
 
     :raises TimespanError: items is an invalid type.

From fd5ecfe21ba0e0bcf84a9d73fa221ddb900a59f0 Mon Sep 17 00:00:00 2001
From: Matthew Dippel <mdip226@gmail.com>
Date: Tue, 1 Aug 2023 17:48:11 -0400
Subject: [PATCH 2/2] docs build and save

---
 docs/build/html/.buildinfo                    |    2 +-
 .../.doctrees/classes/spatialpy.core.doctree  |  Bin 2047370 -> 2062169 bytes
 .../html/.doctrees/classes/spatialpy.doctree  |  Bin 3569 -> 3580 bytes
 .../classes/spatialpy.solvers.doctree         |  Bin 216463 -> 218544 bytes
 .../classes/spatialpy.stochss.doctree         |  Bin 10805 -> 10870 bytes
 docs/build/html/.doctrees/environment.pickle  |  Bin 752241 -> 3794078 bytes
 docs/build/html/.doctrees/index.doctree       |  Bin 14685 -> 14678 bytes
 docs/build/html/_modules/index.html           |    6 +-
 docs/build/html/_static/basic.css             |    5 +-
 docs/build/html/_static/doctools.js           |    2 +-
 docs/build/html/_static/language_data.js      |    2 +-
 docs/build/html/_static/searchtools.js        |    2 +-
 docs/build/html/classes/spatialpy.core.html   |    8 +-
 docs/build/html/classes/spatialpy.html        |    8 +-
 .../build/html/classes/spatialpy.solvers.html |   10 +-
 .../build/html/classes/spatialpy.stochss.html |    8 +-
 docs/build/html/genindex.html                 |    6 +-
 docs/build/html/index.html                    |    8 +-
 docs/build/html/py-modindex.html              |    6 +-
 docs/build/html/search.html                   |    6 +-
 docs/build/html/searchindex.js                |    2 +-
 examples/mdippel.ipynb                        | 6837 +++++++++++++++++
 22 files changed, 6861 insertions(+), 57 deletions(-)
 create mode 100644 examples/mdippel.ipynb

diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo
index 6c634e76..6532c43a 100644
--- a/docs/build/html/.buildinfo
+++ b/docs/build/html/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: cda440a90b02806b8875d767ce4b3688
+config: 0cb4dce3458a66b690cafc7e7336da8c
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/docs/build/html/.doctrees/classes/spatialpy.core.doctree b/docs/build/html/.doctrees/classes/spatialpy.core.doctree
index 8cb7bdee43fe23af61937721f3995fc168974fb5..0af1f4b3290fe8d21ad4e34dac92aeb65340b15a 100644
GIT binary patch
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diff --git a/docs/build/html/.doctrees/classes/spatialpy.solvers.doctree b/docs/build/html/.doctrees/classes/spatialpy.solvers.doctree
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index 1fdc4a36ab8b9c21628843730bdb5cf863398001..c66dd0097d8d42be4c9fbeb6a844f1427398b520 100644
GIT binary patch
delta 78
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delta 67
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       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
       |
diff --git a/docs/build/html/classes/spatialpy.solvers.html b/docs/build/html/classes/spatialpy.solvers.html
index 2669b67e..8a827686 100644
--- a/docs/build/html/classes/spatialpy.solvers.html
+++ b/docs/build/html/classes/spatialpy.solvers.html
@@ -1,19 +1,15 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
   <head>
     <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
     <title>spatialpy.solvers package &#8212; SpatialPy 1.2.2 documentation</title>
     <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
     <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
     <link rel="stylesheet" type="text/css" href="../_static/css/spatialpy_alabaster_customizations.css" />
     <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/jquery.js"></script>
-    <script src="../_static/underscore.js"></script>
-    <script src="../_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="../_static/doctools.js"></script>
     <script src="../_static/sphinx_highlight.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
@@ -336,7 +332,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py attribute">
 <dt class="sig sig-object py" id="spatialpy.solvers.build_expression.BuildExpression.operator_map">
-<span class="sig-name descname"><span class="pre">operator_map</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{'!':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Not'&gt;,</span> <span class="pre">'!=':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.NotEq'&gt;,</span> <span class="pre">'%':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Mod'&gt;,</span> <span class="pre">'&amp;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.BitAnd'&gt;,</span> <span class="pre">'*':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Mult'&gt;,</span> <span class="pre">'**':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Pow'&gt;,</span> <span class="pre">'+':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Add'&gt;,</span> <span class="pre">'-':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Sub'&gt;,</span> <span class="pre">'/':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Div'&gt;,</span> <span class="pre">'//':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.FloorDiv'&gt;,</span> <span class="pre">':=':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Assign'&gt;,</span> <span class="pre">'&lt;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Lt'&gt;,</span> <span class="pre">'&lt;&lt;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.LShift'&gt;,</span> <span class="pre">'&lt;=':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.LtE'&gt;,</span> <span class="pre">'=':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Assign'&gt;,</span> <span class="pre">'==':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Eq'&gt;,</span> <span class="pre">'&gt;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Gt'&gt;,</span> <span class="pre">'&gt;=':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.GtE'&gt;,</span> <span class="pre">'&gt;&gt;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.RShift'&gt;,</span> <span class="pre">'&#64;':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.MatMult'&gt;,</span> <span class="pre">'^':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.BitXor'&gt;,</span> <span class="pre">'and':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.And'&gt;,</span> <span class="pre">'or':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.Or'&gt;,</span> <span class="pre">'|':</span> <span class="pre">&lt;class</span> <span class="pre">'_ast.BitOr'&gt;}</span></em><a class="headerlink" href="#spatialpy.solvers.build_expression.BuildExpression.operator_map" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">operator_map</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{'!':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Not'&gt;,</span> <span class="pre">'!=':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.NotEq'&gt;,</span> <span class="pre">'%':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Mod'&gt;,</span> <span class="pre">'&amp;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.BitAnd'&gt;,</span> <span class="pre">'*':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Mult'&gt;,</span> <span class="pre">'**':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Pow'&gt;,</span> <span class="pre">'+':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Add'&gt;,</span> <span class="pre">'-':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Sub'&gt;,</span> <span class="pre">'/':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Div'&gt;,</span> <span class="pre">'//':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.FloorDiv'&gt;,</span> <span class="pre">':=':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Assign'&gt;,</span> <span class="pre">'&lt;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Lt'&gt;,</span> <span class="pre">'&lt;&lt;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.LShift'&gt;,</span> <span class="pre">'&lt;=':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.LtE'&gt;,</span> <span class="pre">'=':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Assign'&gt;,</span> <span class="pre">'==':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Eq'&gt;,</span> <span class="pre">'&gt;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Gt'&gt;,</span> <span class="pre">'&gt;=':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.GtE'&gt;,</span> <span class="pre">'&gt;&gt;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.RShift'&gt;,</span> <span class="pre">'&#64;':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.MatMult'&gt;,</span> <span class="pre">'^':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.BitXor'&gt;,</span> <span class="pre">'and':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.And'&gt;,</span> <span class="pre">'or':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.Or'&gt;,</span> <span class="pre">'|':</span> <span class="pre">&lt;class</span> <span class="pre">'ast.BitOr'&gt;}</span></em><a class="headerlink" href="#spatialpy.solvers.build_expression.BuildExpression.operator_map" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
@@ -954,7 +950,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
       |
diff --git a/docs/build/html/classes/spatialpy.stochss.html b/docs/build/html/classes/spatialpy.stochss.html
index d5ac440d..9c299917 100644
--- a/docs/build/html/classes/spatialpy.stochss.html
+++ b/docs/build/html/classes/spatialpy.stochss.html
@@ -1,19 +1,15 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
   <head>
     <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
     <title>spatialpy.stochss package &#8212; SpatialPy 1.2.2 documentation</title>
     <link rel="stylesheet" type="text/css" href="../_static/pygments.css" />
     <link rel="stylesheet" type="text/css" href="../_static/alabaster.css" />
     <link rel="stylesheet" type="text/css" href="../_static/css/spatialpy_alabaster_customizations.css" />
     <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-    <script src="../_static/jquery.js"></script>
-    <script src="../_static/underscore.js"></script>
-    <script src="../_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="../_static/doctools.js"></script>
     <script src="../_static/sphinx_highlight.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
@@ -160,7 +156,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
       |
diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index bf239fcc..97c13174 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -1,4 +1,3 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
@@ -10,9 +9,6 @@
     <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
     <link rel="stylesheet" type="text/css" href="_static/css/spatialpy_alabaster_customizations.css" />
     <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/jquery.js"></script>
-    <script src="_static/underscore.js"></script>
-    <script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="_static/doctools.js"></script>
     <script src="_static/sphinx_highlight.js"></script>
     <link rel="index" title="Index" href="#" />
@@ -1719,7 +1715,7 @@ <h2 id="X">X</h2>
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
     </div>
diff --git a/docs/build/html/index.html b/docs/build/html/index.html
index 2b7779d3..2389f172 100644
--- a/docs/build/html/index.html
+++ b/docs/build/html/index.html
@@ -1,19 +1,15 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
   <head>
     <meta charset="utf-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.19: https://docutils.sourceforge.io/" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
     <title>Documentation for SpatialPy 1.2.2 &#8212; SpatialPy 1.2.2 documentation</title>
     <link rel="stylesheet" type="text/css" href="_static/pygments.css" />
     <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
     <link rel="stylesheet" type="text/css" href="_static/css/spatialpy_alabaster_customizations.css" />
     <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/jquery.js"></script>
-    <script src="_static/underscore.js"></script>
-    <script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="_static/doctools.js"></script>
     <script src="_static/sphinx_highlight.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
@@ -159,7 +155,7 @@ <h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Pe
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
       |
diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index 5bbe957f..679ee4a2 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -1,4 +1,3 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
@@ -10,9 +9,6 @@
     <link rel="stylesheet" type="text/css" href="_static/alabaster.css" />
     <link rel="stylesheet" type="text/css" href="_static/css/spatialpy_alabaster_customizations.css" />
     <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/jquery.js"></script>
-    <script src="_static/underscore.js"></script>
-    <script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="_static/doctools.js"></script>
     <script src="_static/sphinx_highlight.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
@@ -245,7 +241,7 @@ <h1>Python Module Index</h1>
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
     </div>
diff --git a/docs/build/html/search.html b/docs/build/html/search.html
index f923a57f..d23d621e 100644
--- a/docs/build/html/search.html
+++ b/docs/build/html/search.html
@@ -1,4 +1,3 @@
-
 <!DOCTYPE html>
 
 <html lang="en">
@@ -11,9 +10,6 @@
     <link rel="stylesheet" type="text/css" href="_static/css/spatialpy_alabaster_customizations.css" />
     
     <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-    <script src="_static/jquery.js"></script>
-    <script src="_static/underscore.js"></script>
-    <script src="_static/_sphinx_javascript_frameworks_compat.js"></script>
     <script src="_static/doctools.js"></script>
     <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/searchtools.js"></script>
@@ -134,7 +130,7 @@ <h1 id="search-documentation">Search</h1>
       &copy;Copyright (C) 2019-2023.
       
       |
-      Powered by <a href="http://sphinx-doc.org/">Sphinx 5.3.0</a>
+      Powered by <a href="http://sphinx-doc.org/">Sphinx 7.0.1</a>
       &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.13</a>
       
     </div>
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index 3e6346b5..11e471b1 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
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diff --git a/examples/mdippel.ipynb b/examples/mdippel.ipynb
new file mode 100644
index 00000000..5884b0e9
--- /dev/null
+++ b/examples/mdippel.ipynb
@@ -0,0 +1,6837 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Introduction\n",
+    "***\n",
+    "Running a simmulation with SpatialPy requires only 2 components: a model (data), and a solver (algorithm).\n",
+    "***\n",
+    "### Setup the Environment\n",
+    "***\n",
+    "'os' and 'sys' allow us to modify the directory Python searches for source code. If you wish to use an installed SpatialPy package, you do not need to run this cell. If this notebook is being run from within the SpatialPy source code directory we need to let Python know that we want to use it, not the SpatialPy package."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import sys\n",
+    "sys.path.insert(1, os.path.abspath(os.path.join(os.getcwd(), '../')))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import the types that'll be needed to define your Model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import spatialpy"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "***\n",
+    "## Creating a SpatialPy Model\n",
+    "***\n",
+    "A SpatialPy model must include a domain, which may be fixed (not moving) or subject to fluid motion (SDPD method).\n",
+    "To add a biochemical network the model must also include Species, Parameters, Initial Conditions, and Reactions.\n",
+    "\n",
+    "Your model is declared and configured as a Python class. As such, the name can be of your choosing. For this example we'll be modeling Spatial Birth and Death, so lets set the name accordingly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_birth_death(parameter_values=None):\n",
+    "    # Intialize the Model with a name of your choosing.\n",
+    "    model = spatialpy.Model(name='Spatial Birth-Death')\n",
+    "    \n",
+    "    # Define Domain Type IDs as constants of the Model\n",
+    "    model.HABITAT = \"Habitat\"\n",
+    "\n",
+    "    \"\"\"\n",
+    "    A domain defines points and attributes of a regional space for simulation.\n",
+    "\n",
+    "    Create a filled 2D domain\n",
+    "    - xlim: highest and lowest coordinate in the x dimension.\n",
+    "    - ylim: highest and lowest coordinate in the y dimension.\n",
+    "    - numx: number of particle spacing in the x dimension.\n",
+    "    - numy: number of particle spacing in the y dimension.\n",
+    "    - type_id: default type ID of particles to be created. Defaults to 1.\n",
+    "    - mass: default mass of particles to be created. Defaults to 1.0.\n",
+    "    - nu: default viscosity of particles to be created. Defaults to 1.0.\n",
+    "    - c: default artificial speed of sound of particles to be created. Defaults to 0.0.\n",
+    "    - rho: default density of particles to be created.\n",
+    "    - fixed: spatially fixed flag of particles to be created. Defaults to false.\n",
+    "    - rho0: Background density for the system.\n",
+    "    - c0: Speed of sound for the system.\n",
+    "    - P0: Background pressure for the system.\n",
+    "    - gravity: Acceleration of gravity for the system.\n",
+    "    - apply_action: If true, apply the action, else, add the action to Domain.actions.\n",
+    "    \"\"\"\n",
+    "    domain = spatialpy.Domain.create_2D_domain(\n",
+    "        xlim=(0, 1), ylim=(0, 1), numx=10, numy=10, type_id=model.HABITAT, fixed=True\n",
+    "    )\n",
+    "\n",
+    "    # Set the Models Domain\n",
+    "    model.add_domain(domain)\n",
+    "\n",
+    "    \"\"\"\n",
+    "    Variables (SpatialPy.Species) can be anything that participates in or is produced by a reaction channel.\n",
+    "\n",
+    "    - name: A user defined name for the species.\n",
+    "    - diffusion_coefficient: Non-constant coefficient of diffusion for the Species.\n",
+    "    - restrict_to: Restricts the movement of Species to  a type or list of types within the Domain.\n",
+    "    \"\"\"\n",
+    "    Rabbits = spatialpy.Species(name='Rabbits', diffusion_coefficient=0.1)\n",
+    "\n",
+    "    # Add the Variables to the Model.\n",
+    "    model.add_species(Rabbits)\n",
+    "\n",
+    "    \"\"\"\n",
+    "    Scatter the initial condition for a species randomly over the list of types.\n",
+    "    If the list of types is None scatter over all types.\n",
+    "\n",
+    "    - species: The species to set the initial condition.\n",
+    "    - count: The initial condition for the target species.\n",
+    "    - types: Type IDs of the particles to place the initial condition.\n",
+    "    \"\"\"\n",
+    "    init_rabbit_pop = spatialpy.ScatterInitialCondition(species='Rabbits', count=100)\n",
+    "\n",
+    "    # Add Initial Conditions to the Model\n",
+    "    model.add_initial_condition(init_rabbit_pop)\n",
+    "\n",
+    "    \"\"\"\n",
+    "    Parameters are constant values relevant to the system, such as reaction kinetic rates.\n",
+    "\n",
+    "    - name: A user defined name for reference.\n",
+    "    - expression: Some constant value.\n",
+    "    \"\"\"\n",
+    "    kb = spatialpy.Parameter(name='k_birth', expression=10)\n",
+    "    kd = spatialpy.Parameter(name='k_death', expression=0.1)\n",
+    "\n",
+    "    # Add the Parameters to the Model.\n",
+    "    model.add_parameter([kb, kd])\n",
+    "\n",
+    "    \"\"\"\n",
+    "    Reactions are the reaction channels which cause the system to change over time.\n",
+    "\n",
+    "    - name: A user defined name for the reaction.\n",
+    "    - reactants: A dictionary with participant reactants as keys, and consumed per reaction as value.\n",
+    "    - products: A dictionary with reaction products as keys, and number formed per reaction as value.\n",
+    "    - rate: A parameter rate constant to be applied to the propensity of this reaction firing.\n",
+    "    - propensity_function: Can be used instead of rate in order to declare a custom propensity function\n",
+    "                           in string format.\n",
+    "    - restrict_to: Restrict reaction channels to a type or list of types within the Domain.\n",
+    "    \"\"\"\n",
+    "    birth = spatialpy.Reaction(\n",
+    "        name='birth',\n",
+    "        reactants={},\n",
+    "        products={\"Rabbits\":1},\n",
+    "        rate=\"k_birth\"\n",
+    "    )\n",
+    "\n",
+    "    death = spatialpy.Reaction(\n",
+    "        name='death',\n",
+    "        reactants={\"Rabbits\":1},\n",
+    "        products={},\n",
+    "        rate=\"k_death\"\n",
+    "    )\n",
+    "\n",
+    "    # Add the Reactions to the Model.\n",
+    "    model.add_reaction([birth, death])\n",
+    "\n",
+    "    # Define the Timespan of the Model\n",
+    "    tspan = spatialpy.TimeSpan.linspace(t=10, num_points=11, timestep_size=1)\n",
+    "    \n",
+    "    # Set the Timespan of the Model\n",
+    "    model.timespan(tspan)\n",
+    "    return model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Instantiate the Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = create_birth_death()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "***\n",
+    "## Running the Simulation\n",
+    "***\n",
+    "Run a spatial stochastic simulation on the Model and store the results in the 'results' variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results = model.run()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You can find a thorough list of `model.run()` arguments in the [documentation](https://stochss.github.io/SpatialPy/docs/build/html/classes/spatialpy.core.html#spatialpy.core.model.Model.run) to customize the behavior of your simulations.\"\n",
+    "***\n",
+    "## Visualizations\n",
+    "***\n",
+    "Plot the results of the simulation.\n",
+    "\n",
+    "There are a multitude of arguments that can be set to tweak the behavior and visuals of the plot. \n",
+    "For now though, lets plot the populations of `Rabbits` at the end of the simulation using MatPlotLib."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 460.8x345.6 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results.plot_species(\n",
+    "    # Set the target species to visualize\n",
+    "    species='Rabbits',\n",
+    "    \n",
+    "    # Set the time value to visualize (t_val defaults the 0)\n",
+    "    t_val=10,\n",
+    "    \n",
+    "    # Set to True to use MatPlotLib plotting\n",
+    "    use_matplotlib=True\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That plot is somewhat boring though, so lets plot the populations of `Rabbits` over time using Plotly anumation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "        <script type=\"text/javascript\">\n",
+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
+       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        requirejs.config({\n",
+       "            paths: {\n",
+       "                'plotly': ['https://cdn.plot.ly/plotly-2.4.2.min']\n",
+       "            }\n",
+       "        });\n",
+       "        require(['plotly'], function(Plotly) {\n",
+       "            window._Plotly = Plotly;\n",
+       "        });\n",
+       "        }\n",
+       "        </script>\n",
+       "        "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
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+     "data": {
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+       "                        }).then(function(){\n",
+       "                            Plotly.animate('7b01b45a-27bd-4580-b21e-f8e04ed3e3a6', null);\n",
+       "                        }).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('7b01b45a-27bd-4580-b21e-f8e04ed3e3a6');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results.plot_species(\n",
+    "    # Set the target species to visualize\n",
+    "    species='Rabbits',\n",
+    "    \n",
+    "    # Set to True to use Plotly animation\n",
+    "    animated=True,\n",
+    "    \n",
+    "    # Set the size of the Particles\n",
+    "    size=20\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### A more complete list of `results.plot_species()` arguments can be found in the [documentation](https://stochss.github.io/SpatialPy/docs/build/html/classes/spatialpy.core.html#spatialpy.core.result.Result.plot_species).\n",
+    "***\n",
+    "## Where to go now?\n",
+    "***\n",
+    "For a more advanced example on reaction diffusion follow the link below:\n",
+    "\n",
+    "- [3D Cylinder Demo](./3D_Cylinder_Demo.ipynb)\n",
+    "\n",
+    "For examples on Fluid Dynamic models follow the links below:\n",
+    "\n",
+    "- [Gravity](./Gravity.ipynb)\n",
+    "- [Weir](./weir.ipynb)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}