Update CHANGELOG, rebuild docs

CHANGELOG.md

@@ -7,8 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.0.9] -- 2022-06-28
+
 ### Fixed
-- Bug that prevented named instances from being loaded correctly
+- Bug that prevented named instances from being loaded correctly using ``load_instance()``
 
 ### Added
 - Methods to convert objects to and from dicts

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

@@ -4,10 +4,11 @@
 Stockpyl
 ========
 
-|sp| is a Python package for inventory optimization. It implements
+|sp| is a Python package for inventory optimization and simulation. It implements
 classical single-node inventory models like the economic order quantity (EOQ), newsvendor,
 and Wagner-Whitin problems. It also contains algorithms for multi-echelon inventory optimization
 (MEIO) under both stochastic-service model (SSM) and guaranteed-service model (GSM) assumptions. 
+And, it has extensive features for simulating multi-echelon inventory systems.
 
 .. note:: |fosct_notation|
 
@@ -16,7 +17,7 @@ and Wagner-Whitin problems. It also contains algorithms for multi-echelon invent
 Some Examples
 -------------
 
-Solve the EOQ problem with :math:`K=8`, :math:`h=0.225`, and :math:`\lambda=1300` (Example 3.1 in *FoSCT*):
+Solve the EOQ problem with a fixed cost of 8, a holding cost of 0.225, and a demand rate of 1300 (Example 3.1 in *FoSCT*):
 
 .. doctest::
 
@@ -27,7 +28,8 @@ Solve the EOQ problem with :math:`K=8`, :math:`h=0.225`, and :math:`\lambda=1300
  >>> cost
  68.41052550594829
 
-Or the newsvendor problem with :math:`h=0.18`, :math:`p=0.70`, and :math:`D\sim N(50, 8^2)` (Example 4.3 in *FoSCT*):
+Or the newsvendor problem with a holding cost of 0.18, a stockout cost of 0.70, and demand that is normally
+distributed with mean 50 and standard deviation 8 (Example 4.3 in *FoSCT*):
 
 .. doctest::
 

docs/_build/html/genindex.html

@@ -163,14 +163,14 @@ <h2 id="C">C</h2>
 <h2 id="D">D</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="api/datatypes/supply_chain_network.html#stockpyl.supply_chain_network.SupplyChainNetwork.deep_equal_to">deep_equal_to() (SupplyChainNetwork method)</a>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.deep_equal_to">deep_equal_to() (NodeStateVars method)</a>
 
  <ul>
+ <li><a href="api/datatypes/supply_chain_network.html#stockpyl.supply_chain_network.SupplyChainNetwork.deep_equal_to">(SupplyChainNetwork method)</a>
+</li>
  <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.SupplyChainNode.deep_equal_to">(SupplyChainNode method)</a>
 </li>
  </ul></li>
- <li><a href="api/other/instances.html#stockpyl.instances.DEFAULT_JSON_FILEPATH">DEFAULT_JSON_FILEPATH (in module stockpyl.instances)</a>
-</li>
  <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.demand_cumul">demand_cumul (NodeStateVars attribute)</a>
 </li>
  <li><a href="api/datatypes/demand_source.html#stockpyl.demand_source.DemandSource.demand_distribution">demand_distribution (DemandSource property)</a>
@@ -277,12 +277,24 @@ <h2 id="F">F</h2>
 </li>
  <li><a href="api/other/helpers.html#stockpyl.helpers.find_nearest">find_nearest() (in module stockpyl.helpers)</a>
 </li>
- </ul></td>
- <td style="width: 33%; vertical-align: top;"><ul>
  <li><a href="api/seio/finite_horizon.html#stockpyl.finite_horizon.finite_horizon_dp">finite_horizon_dp() (in module stockpyl.finite_horizon)</a>
 </li>
  <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.SupplyChainNode.forward_echelon_lead_time">forward_echelon_lead_time (SupplyChainNode property)</a>
 </li>
+ <li><a href="api/datatypes/demand_source.html#stockpyl.demand_source.DemandSource.from_dict">from_dict() (DemandSource class method)</a>
+
+ <ul>
+ <li><a href="api/datatypes/disruption_process.html#stockpyl.disruption_process.DisruptionProcess.from_dict">(DisruptionProcess class method)</a>
+</li>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.from_dict">(NodeStateVars class method)</a>
+</li>
+ <li><a href="api/datatypes/policy.html#stockpyl.policy.Policy.from_dict">(Policy class method)</a>
+</li>
+ <li><a href="api/datatypes/supply_chain_network.html#stockpyl.supply_chain_network.SupplyChainNetwork.from_dict">(SupplyChainNetwork class method)</a>
+</li>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.SupplyChainNode.from_dict">(SupplyChainNode class method)</a>
+</li>
+ </ul></li>
  </ul></td>
 </tr></table>
 
@@ -939,12 +951,26 @@ <h2 id="S">S</h2>
 <h2 id="T">T</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
- <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.total_cost_incurred">total_cost_incurred (NodeStateVars attribute)</a>
+ <li><a href="api/datatypes/demand_source.html#stockpyl.demand_source.DemandSource.to_dict">to_dict() (DemandSource method)</a>
+
+ <ul>
+ <li><a href="api/datatypes/disruption_process.html#stockpyl.disruption_process.DisruptionProcess.to_dict">(DisruptionProcess method)</a>
 </li>
- <li><a href="api/meio/meio_general.html#stockpyl.meio_general.truncate_and_discretize">truncate_and_discretize() (in module stockpyl.meio_general)</a>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.to_dict">(NodeStateVars method)</a>
+</li>
+ <li><a href="api/datatypes/policy.html#stockpyl.policy.Policy.to_dict">(Policy method)</a>
+</li>
+ <li><a href="api/datatypes/supply_chain_network.html#stockpyl.supply_chain_network.SupplyChainNetwork.to_dict">(SupplyChainNetwork method)</a>
 </li>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.SupplyChainNode.to_dict">(SupplyChainNode method)</a>
+</li>
+ </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
+ <li><a href="api/datatypes/supply_chain_node.html#stockpyl.supply_chain_node.NodeStateVars.total_cost_incurred">total_cost_incurred (NodeStateVars attribute)</a>
+</li>
+ <li><a href="api/meio/meio_general.html#stockpyl.meio_general.truncate_and_discretize">truncate_and_discretize() (in module stockpyl.meio_general)</a>
+</li>
  <li><a href="api/datatypes/demand_source.html#stockpyl.demand_source.DemandSource.type">type (DemandSource attribute)</a>
 
  <ul>

docs/_build/html/index.html

@@ -71,18 +71,19 @@
 
  <section id="stockpyl">
 <h1>Stockpyl<a class="headerlink" href="#stockpyl" title="Permalink to this heading">¶</a></h1>
-<p>Stockpyl is a Python package for inventory optimization. It implements
+<p>Stockpyl is a Python package for inventory optimization and simulation. It implements
 classical single-node inventory models like the economic order quantity (EOQ), newsvendor,
 and Wagner-Whitin problems. It also contains algorithms for multi-echelon inventory optimization
-(MEIO) under both stochastic-service model (SSM) and guaranteed-service model (GSM) assumptions.</p>
+(MEIO) under both stochastic-service model (SSM) and guaranteed-service model (GSM) assumptions.
+And, it has extensive features for simulating multi-echelon inventory systems.</p>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
 <p>The notation and references (equations, sections, examples, etc.) used below refer to Snyder and Shen, <em>Fundamentals of Supply Chain Theory</em> (<em>FoSCT</em>), 2nd edition (2019).</p>
 </div>
 <hr class="docutils" />
 <section id="some-examples">
 <h2>Some Examples<a class="headerlink" href="#some-examples" title="Permalink to this heading">¶</a></h2>
-<p>Solve the EOQ problem with <span class="math notranslate nohighlight">\(K=8\)</span>, <span class="math notranslate nohighlight">\(h=0.225\)</span>, and <span class="math notranslate nohighlight">\(\lambda=1300\)</span> (Example 3.1 in <em>FoSCT</em>):</p>
+<p>Solve the EOQ problem with a fixed cost of 8, a holding cost of 0.225, and a demand rate of 1300 (Example 3.1 in <em>FoSCT</em>):</p>
 <div class="highlight-pycon3 notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">stockpyl.eoq</span> <span class="kn">import</span> <span class="n">economic_order_quantity</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">Q</span><span class="p">,</span> <span class="n">cost</span> <span class="o">=</span> <span class="n">economic_order_quantity</span><span class="p">(</span><span class="n">fixed_cost</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">holding_cost</span><span class="o">=</span><span class="mf">0.225</span><span class="p">,</span> <span class="n">demand_rate</span><span class="o">=</span><span class="mi">1300</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">Q</span>
@@ -91,7 +92,8 @@ <h2>Some Examples<a class="headerlink" href="#some-examples" title="Permalink to
 <span class="go">68.41052550594829</span>
 </pre></div>
 </div>
-<p>Or the newsvendor problem with <span class="math notranslate nohighlight">\(h=0.18\)</span>, <span class="math notranslate nohighlight">\(p=0.70\)</span>, and <span class="math notranslate nohighlight">\(D\sim N(50, 8^2)\)</span> (Example 4.3 in <em>FoSCT</em>):</p>
+<p>Or the newsvendor problem with a holding cost of 0.18, a stockout cost of 0.70, and demand that is normally
+distributed with mean 50 and standard deviation 8 (Example 4.3 in <em>FoSCT</em>):</p>
 <div class="highlight-pycon3 notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">stockpyl.newsvendor</span> <span class="kn">import</span> <span class="n">newsvendor_normal</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">S</span><span class="p">,</span> <span class="n">cost</span> <span class="o">=</span> <span class="n">newsvendor_normal</span><span class="p">(</span><span class="n">holding_cost</span><span class="o">=</span><span class="mf">0.18</span><span class="p">,</span> <span class="n">stockout_cost</span><span class="o">=</span><span class="mf">0.70</span><span class="p">,</span> <span class="n">demand_mean</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">demand_sd</span><span class="o">=</span><span class="mi">8</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">S</span>