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update python docs

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Laurent Perron
2019-10-01 11:48:51 -04:00
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@@ -26,7 +26,9 @@ a:link { color: #46641e; text-decoration: none}
</header>
<section id="section-intro">
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python"># This file was automatically generated by SWIG (http://www.swig.org).
# Version 4.0.1
#
@@ -339,7 +341,9 @@ E.g.:</p>
final long profit = solver.solve();
</code></pre></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">class KnapsackSolver(object):
r&#34;&#34;&#34;
This library solves knapsack problems.
@@ -541,7 +545,9 @@ dimensions. This solver is based on Integer Programming solver CBC.</p></section
<dd>
<section class="desc"><p>The membership flag</p></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc=&#34;The membership flag&#34;)</code></pre>
</details>
</dd>
@@ -554,7 +560,9 @@ dimensions. This solver is based on Integer Programming solver CBC.</p></section
<dd>
<section class="desc"><p>Returns true if the item 'item_id' is packed in the optimal knapsack.</p></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def BestSolutionContains(self, item_id: &#34;int&#34;) -&gt; &#34;bool&#34;:
r&#34;&#34;&#34;Returns true if the item &#39;item_id&#39; is packed in the optimal knapsack.&#34;&#34;&#34;
return _pywrapknapsack_solver.KnapsackSolver_BestSolutionContains(self, item_id)</code></pre>
@@ -566,7 +574,9 @@ dimensions. This solver is based on Integer Programming solver CBC.</p></section
<dd>
<section class="desc"><p>Initializes the solver and enters the problem to be solved.</p></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def Init(self, profits: &#34;std::vector&lt; int64 &gt; const &amp;&#34;, weights: &#34;std::vector&lt; std::vector&lt; int64 &gt; &gt; const &amp;&#34;, capacities: &#34;std::vector&lt; int64 &gt; const &amp;&#34;) -&gt; &#34;void&#34;:
r&#34;&#34;&#34;Initializes the solver and enters the problem to be solved.&#34;&#34;&#34;
return _pywrapknapsack_solver.KnapsackSolver_Init(self, profits, weights, capacities)</code></pre>
@@ -578,7 +588,9 @@ dimensions. This solver is based on Integer Programming solver CBC.</p></section
<dd>
<section class="desc"><p>Solves the problem and returns the profit of the optimal solution.</p></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def Solve(self) -&gt; &#34;int64&#34;:
r&#34;&#34;&#34;Solves the problem and returns the profit of the optimal solution.&#34;&#34;&#34;
return _pywrapknapsack_solver.KnapsackSolver_Solve(self)</code></pre>
@@ -592,7 +604,9 @@ dimensions. This solver is based on Integer Programming solver CBC.</p></section
<p>When a finite time limit is set the solution obtained might not be optimal
if the limit is reached.</p></section>
<details class="source">
<summary>Source code</summary>
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def set_time_limit(self, time_limit_seconds: &#34;double&#34;) -&gt; &#34;void&#34;:
r&#34;&#34;&#34;
Time limit in seconds.
@@ -609,7 +623,9 @@ if the limit is reached.</p></section>
<dd>
<section class="desc"></section>
<details class="source">
<summary>Source code</summary>
<summary>
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</summary>
<pre><code class="python">def set_use_reduction(self, use_reduction: &#34;bool&#34;) -&gt; &#34;void&#34;:
return _pywrapknapsack_solver.KnapsackSolver_set_use_reduction(self, use_reduction)</code></pre>
</details>
@@ -655,7 +671,7 @@ if the limit is reached.</p></section>
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