From 46bc84429d5e1dfb39587bb4085f3cc6167ad271 Mon Sep 17 00:00:00 2001
From: visr <visr@users.noreply.github.com>
Date: Mon, 9 Sep 2024 09:10:18 +0000
Subject: [PATCH] deploy: 3510ef2baf77a1371a1bea1c4d5daf971d9b9837

---
 concept/allocation.html                       |  24 +++++++++---------
 .../figure-html/cell-18-output-1.png          | Bin 87076 -> 86942 bytes
 .../figure-html/cell-19-output-1.png          | Bin 113446 -> 113408 bytes
 .../figure-html/cell-68-output-1.png          | Bin 44271 -> 44258 bytes
 reference/node/basin.html                     |  14 +++++-----
 reference/node/discrete-control.html          |   2 +-
 reference/node/manning-resistance.html        |   2 +-
 reference/node/tabulated-rating-curve.html    |   2 +-
 reference/test-models.html                    |   2 +-
 reference/validation.html                     |   4 +--
 search.json                                   |   2 +-
 11 files changed, 26 insertions(+), 26 deletions(-)

diff --git a/concept/allocation.html b/concept/allocation.html
index 27c624b12..f77bec248 100644
--- a/concept/allocation.html
+++ b/concept/allocation.html
@@ -574,7 +574,7 @@ <h2 data-number="4.3" class="anchored" data-anchor-id="the-optimization-constrai
 <section id="example" class="level2" data-number="4.4">
 <h2 data-number="4.4" class="anchored" data-anchor-id="example"><span class="header-section-number">4.4</span> Example</h2>
 <p>The following is an example of an optimization problem for the example shown <a href="../guide/examples.html#model-with-allocation-user-demand">here</a>:</p>
-<div id="3f232767" class="cell" data-execution_count="1">
+<div id="09f6d869" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Ribasim</span></span>
@@ -597,27 +597,27 @@ <h2 data-number="4.4" class="anchored" data-anchor-id="example"><span class="hea
 <span id="cb1-18"><a href="#cb1-18" aria-hidden="true" tabindex="-1"></a><span class="fu">println</span>(p.allocation.allocation_models[<span class="fl">1</span>].problem)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-stdout">
-<pre><code>Min F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²
+<pre><code>Min F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²
 Subject to
- flow_conservation[Basin #5] : -F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] = 0
+ flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #8)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0
+ flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] = 0
  flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0
  flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0
- flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, Terminal #8)] = 0
- flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] = 0
- F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
+ flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] + F[(UserDemand #3, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0
+ F[(UserDemand #6, Basin #5)] ≥ 0
  F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
  F[(LinearResistance #4, Basin #5)] ≥ 0
  F[(Basin #5, LinearResistance #4)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
- F[(UserDemand #6, Basin #5)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
+ F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
+ F[(Basin #5, UserDemand #6)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
- F[(Basin #5, UserDemand #6)] ≥ 0
- F[(FlowBoundary #1, Basin #2)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
  source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
- source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
  source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
+ source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
 </code></pre>
 </div>
 </div>
diff --git a/guide/examples_files/figure-html/cell-18-output-1.png b/guide/examples_files/figure-html/cell-18-output-1.png
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diff --git a/reference/node/basin.html b/reference/node/basin.html
index 504f6a682..ffacefffe 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="time"><span class="header
 <section id="interpolation" class="level3" data-number="1.2.1">
 <h3 data-number="1.2.1" class="anchored" data-anchor-id="interpolation"><span class="header-section-number">1.2.1</span> Interpolation</h3>
 <p>At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.</p>
-<div id="a808fb5e" class="cell" data-execution_count="1">
+<div id="cf1ef654" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
@@ -671,7 +671,7 @@ <h3 data-number="1.4.1" class="anchored" data-anchor-id="interpolation-1"><span
 <section id="level-to-area" class="level4" data-number="1.4.1.1">
 <h4 data-number="1.4.1.1" class="anchored" data-anchor-id="level-to-area"><span class="header-section-number">1.4.1.1</span> Level to area</h4>
 <p>The level to area relationship is defined with the <code>Basin / profile</code> data using linear interpolation. An example of such a relationship is shown below.</p>
-<div id="0064e521" class="cell" data-execution_count="2">
+<div id="abf0078a" class="cell" data-execution_count="2">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>fig, ax <span class="op">=</span> plt.subplots()</span>
@@ -754,7 +754,7 @@ <h4 data-number="1.4.1.2" class="anchored" data-anchor-id="level-to-storage"><sp
 <p><span class="math display">\[
     S(h) = \int_{h_0}^h A(h')\text{d}h'.
 \]</span></p>
-<div id="3963c0d7" class="cell" data-execution_count="3">
+<div id="681a765b" class="cell" data-execution_count="3">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>storage <span class="op">=</span> np.diff(level) <span class="op">*</span> area[:<span class="op">-</span><span class="dv">1</span>] <span class="op">+</span> <span class="fl">0.5</span> <span class="op">*</span> np.diff(area) <span class="op">*</span> np.diff(level)</span>
@@ -799,7 +799,7 @@ <h4 data-number="1.4.1.2" class="anchored" data-anchor-id="level-to-storage"><sp
 <section id="interactive-basin-example" class="level4" data-number="1.4.1.3">
 <h4 data-number="1.4.1.3" class="anchored" data-anchor-id="interactive-basin-example"><span class="header-section-number">1.4.1.3</span> Interactive basin example</h4>
 <p>The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.</p>
-<div id="10e485ed" class="cell" data-execution_count="4">
+<div id="02f07d43" class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.graph_objects <span class="im">as</span> go</span>
@@ -914,9 +914,9 @@ <h4 data-number="1.4.1.3" class="anchored" data-anchor-id="interactive-basin-exa
 <span id="cb5-110"><a href="#cb5-110" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
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+var gd = document.getElementById('cb0176a7-a954-456c-9ea1-5d9be02d56d5');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -1223,7 +1223,7 @@ <h2 data-number="2.1" class="anchored" data-anchor-id="sec-reduction-factor"><sp
     \end{cases}
 \end{align}\]</span></p>
 <p>Here <span class="math inline">\(p &gt; 0\)</span> is the threshold value which determines the interval <span class="math inline">\([0,p]\)</span> of the smooth transition between <span class="math inline">\(0\)</span> and <span class="math inline">\(1\)</span>, see the plot below.</p>
-<div id="30bd9417" class="cell" data-execution_count="5">
+<div id="49d60b65" class="cell" data-execution_count="5">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
diff --git a/reference/node/discrete-control.html b/reference/node/discrete-control.html
index bcdc900f0..ab3afea6a 100644
--- a/reference/node/discrete-control.html
+++ b/reference/node/discrete-control.html
@@ -379,7 +379,7 @@ <h1 class="title">DiscreteControl</h1>
 
 
 <p>Set parameters of other nodes based on model state conditions (e.g.&nbsp;Basin level). The table below shows which parameters are controllable for a given node type.</p>
-<div id="58a1d2d8" class="cell" data-execution_count="1">
+<div id="6e04d875" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Ribasim</span></span>
diff --git a/reference/node/manning-resistance.html b/reference/node/manning-resistance.html
index 018cc03d4..60ff15138 100644
--- a/reference/node/manning-resistance.html
+++ b/reference/node/manning-resistance.html
@@ -535,7 +535,7 @@ <h1 data-number="2"><span class="header-section-number">2</span> Equations</h1>
   \end{cases}
 \end{align}
 \]</span></p>
-<div id="1c8cae94" class="cell" data-execution_count="1">
+<div id="5db4c8f5" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
diff --git a/reference/node/tabulated-rating-curve.html b/reference/node/tabulated-rating-curve.html
index dd29fba3d..9c3c1603e 100644
--- a/reference/node/tabulated-rating-curve.html
+++ b/reference/node/tabulated-rating-curve.html
@@ -476,7 +476,7 @@ <h2 data-number="1.1" class="anchored" data-anchor-id="static"><span class="head
 <section id="interpolation" class="level3" data-number="1.1.1">
 <h3 data-number="1.1.1" class="anchored" data-anchor-id="interpolation"><span class="header-section-number">1.1.1</span> Interpolation</h3>
 <p>The <span class="math inline">\(Q(h)\)</span> relationship of a tabulated rating curve is defined as a linear interpolation.</p>
-<div id="d5f481de" class="cell" data-execution_count="1">
+<div id="9489aa0a" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
diff --git a/reference/test-models.html b/reference/test-models.html
index 60ae48625..fdebbf726 100644
--- a/reference/test-models.html
+++ b/reference/test-models.html
@@ -339,7 +339,7 @@ <h1 class="title">Test models</h1>
 
 
 <p>Ribasim developers use the following models in their testbench and in order to test new features.</p>
-<div id="7112de84" class="cell" data-execution_count="1">
+<div id="9b78f461" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ribasim_testmodels</span>
diff --git a/reference/validation.html b/reference/validation.html
index d5096fad7..1502e5a96 100644
--- a/reference/validation.html
+++ b/reference/validation.html
@@ -349,7 +349,7 @@ <h1 class="title">Validation</h1>
 <section id="connectivity" class="level1" data-number="1">
 <h1 data-number="1"><span class="header-section-number">1</span> Connectivity</h1>
 <p>In the table below, each column shows which node types are allowed to be downstream (or ‘down-control’) of the node type at the top of the column.</p>
-<div id="d4fe02b2" class="cell" data-execution_count="1">
+<div id="e045d236" class="cell" data-execution_count="1">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">using</span> <span class="bu">Ribasim</span></span>
@@ -699,7 +699,7 @@ <h1 data-number="1"><span class="header-section-number">1</span> Connectivity</h
 <section id="neighbor-amounts" class="level1" data-number="2">
 <h1 data-number="2"><span class="header-section-number">2</span> Neighbor amounts</h1>
 <p>The table below shows for each node type between which bounds the amount of in- and outneighbors must be, for both flow and control edges.</p>
-<div id="dce9162e" class="cell" data-execution_count="2">
+<div id="9cb733cf" class="cell" data-execution_count="2">
 <details class="code-fold">
 <summary>Code</summary>
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>flow_in_min <span class="op">=</span> <span class="fu">Vector</span><span class="dt">{String}</span>()</span>
diff --git a/search.json b/search.json
index 6d6cad7ab..6dcc001ee 100644
--- a/search.json
+++ b/search.json
@@ -1555,7 +1555,7 @@
     "href": "concept/allocation.html#example",
     "title": "Allocation",
     "section": "4.4 Example",
-    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, 1, 1.0, u)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²\nSubject to\n flow_conservation[Basin #5] : -F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] = 0\n flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0\n flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0\n flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, Terminal #8)] = 0\n flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] = 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0",
+    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, 1, 1.0, u)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²\nSubject to\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #8)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0\n flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] = 0\n flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0\n flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0\n flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] + F[(UserDemand #3, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0",
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       "Concepts",
       "Implementation",