Deploying to gh-pages from @ 49916b6 🚀

_sources/examples/optimal_control_rocket.md.txt

@@ -111,7 +111,9 @@ After solving the problem, we can plot the results.
 
 ```{code-cell}
 model.optimize()
+```
 
+```{code-cell}
 h_value = []
 for i in range(T):
     h_value.append(model.get_value(h[i]))

_sources/examples/optimal_power_flow.md.txt

@@ -236,7 +236,9 @@ After optimization, we can retrieve the optimal solution:
 
 ```{code-cell}
 model.optimize()
+```
 
+```{code-cell}
 print(model.get_model_attribute(poi.ModelAttribute.TerminationStatus))
 
 P_value = P.map(model.get_value)

_sources/nonlinear.md.txt

@@ -177,7 +177,9 @@ model.add_nl_constraint(con_f, nlfunc.Vars(x=x,y=y), ub = [4.0, -1.0])
 model.add_nl_objective(obj_f, nlfunc.Vars(x=x,y=y))
 
 model.optimize()
+```
 
+```{code-cell}
 x_value = model.get_value(x)
 y_value = model.get_value(y)
 
@@ -241,7 +243,9 @@ rosenbrock_f = model.register_function(rosenbrock)
 model.add_nl_objective(rosenbrock_f, nlfunc.Vars(x=x, y=y))
 
 model.optimize()
+```
 
+```{code-cell}
 x_value = model.get_value(x)
 y_value = model.get_value(y)
 
@@ -286,7 +290,9 @@ for i in range(N):
     model.add_linear_constraint(t[i+1] - t[i] - 0.5 * h * u[i+1] - 0.5 * h * u[i] , poi.Eq, 0.0)
 
 model.optimize()
+```
 
+```{code-cell}
 objective_value = model.get_model_attribute(poi.ModelAttribute.ObjectiveValue)
 
 print(f"Objective value: {objective_value}")

constraint.html

@@ -304,12 +304,12 @@ <h1>Constraint<a class="headerlink" href="#constraint" title="Link to this headi
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>2024-11-27 17:18:09 [INFO] checks license for COPT v7.2.2 20241023
-2024-11-27 17:18:09 [WARN] no license files in current working folder: /home/runner/work/PyOptInterface/PyOptInterface/docs/source
-2024-11-27 17:18:09 [WARN] no license files in binary folder: /opt/hostedtoolcache/Python/3.12.7/x64/bin
-2024-11-27 17:18:09 [WARN] no license files in HOME folder: /home/runner/copt
-2024-11-27 17:18:09 [INFO] empty environment variable: COPT_LICENSE_DIR
-2024-11-27 17:18:09 [WARN] no license files in EV &#39;COPT_LICENSE_DIR&#39;: 
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>2024-11-27 17:28:19 [INFO] checks license for COPT v7.2.2 20241023
+2024-11-27 17:28:19 [WARN] no license files in current working folder: /home/runner/work/PyOptInterface/PyOptInterface/docs/source
+2024-11-27 17:28:19 [WARN] no license files in binary folder: /opt/hostedtoolcache/Python/3.12.7/x64/bin
+2024-11-27 17:28:19 [WARN] no license files in HOME folder: /home/runner/copt
+2024-11-27 17:28:19 [INFO] empty environment variable: COPT_LICENSE_DIR
+2024-11-27 17:28:19 [WARN] no license files in EV &#39;COPT_LICENSE_DIR&#39;: 
 
 No license found. Starting COPT with size limitations for non-commercial use
 Please apply for a license from www.shanshu.ai/copt

examples/optimal_control_rocket.html

@@ -394,12 +394,6 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">optimize</span><span class="p">()</span>
-
-<span class="n">h_value</span> <span class="o">=</span> <span class="p">[]</span>
-<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">T</span><span class="p">):</span>
-    <span class="n">h_value</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_value</span><span class="p">(</span><span class="n">h</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Optimal altitude: &quot;</span><span class="p">,</span> <span class="n">h_value</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
 </pre></div>
 </div>
 </div>
@@ -483,11 +477,26 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
 Number of equality constraint Jacobian evaluations   = 24
 Number of inequality constraint Jacobian evaluations = 0
 Number of Lagrangian Hessian evaluations             = 23
-Total CPU secs in IPOPT (w/o function evaluations)   =      0.111
+Total CPU secs in IPOPT (w/o function evaluations)   =      0.108
 Total CPU secs in NLP function evaluations           =      0.004
 
 EXIT: Optimal Solution Found.
-Optimal altitude:  1.012779392216388
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">h_value</span> <span class="o">=</span> <span class="p">[]</span>
+<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">T</span><span class="p">):</span>
+    <span class="n">h_value</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_value</span><span class="p">(</span><span class="n">h</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Optimal altitude: &quot;</span><span class="p">,</span> <span class="n">h_value</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Optimal altitude:  1.012779392216388
 </pre></div>
 </div>
 </div>

examples/optimal_power_flow.html

@@ -520,15 +520,6 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">optimize</span><span class="p">()</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_model_attribute</span><span class="p">(</span><span class="n">poi</span><span class="o">.</span><span class="n">ModelAttribute</span><span class="o">.</span><span class="n">TerminationStatus</span><span class="p">))</span>
-
-<span class="n">P_value</span> <span class="o">=</span> <span class="n">P</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_value</span><span class="p">)</span>
-
-<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Optimal active power output of the generators:&quot;</span><span class="p">)</span>
-
-<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">N_gen</span><span class="p">):</span>
-    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Generator </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">P_value</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </div>
@@ -592,13 +583,6 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
 iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls
   20  1.4997039e+04 9.74e-09 2.33e-05  -8.6 1.52e-03    -  1.00e+00 9.99e-01h  1
   21  1.4997039e+04 5.94e-12 2.83e-12  -8.6 1.03e-03    -  1.00e+00 1.00e+00f  1
-TerminationStatusCode.LOCALLY_SOLVED
-Optimal active power output of the generators:
-Generator 0: 0.4
-Generator 1: 1.7
-Generator 2: 1.9623464660959797
-Generator 3: 0.0
-Generator 4: 6.0
 
 Number of Iterations....: 21
 
@@ -617,14 +601,39 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
 Number of equality constraint Jacobian evaluations   = 22
 Number of inequality constraint Jacobian evaluations = 22
 Number of Lagrangian Hessian evaluations             = 21
-Total CPU secs in IPOPT (w/o function evaluations)   =      0.006
+Total CPU secs in IPOPT (w/o function evaluations)   =      0.007
 Total CPU secs in NLP function evaluations           =      0.000
 
 EXIT: Optimal Solution Found.
 </pre></div>
 </div>
 </div>
 </div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_model_attribute</span><span class="p">(</span><span class="n">poi</span><span class="o">.</span><span class="n">ModelAttribute</span><span class="o">.</span><span class="n">TerminationStatus</span><span class="p">))</span>
+
+<span class="n">P_value</span> <span class="o">=</span> <span class="n">P</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">get_value</span><span class="p">)</span>
+
+<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Optimal active power output of the generators:&quot;</span><span class="p">)</span>
+
+<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">N_gen</span><span class="p">):</span>
+    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Generator </span><span class="si">{</span><span class="n">i</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">P_value</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>TerminationStatusCode.LOCALLY_SOLVED
+Optimal active power output of the generators:
+Generator 0: 0.4
+Generator 1: 1.7
+Generator 2: 1.9623464660959797
+Generator 3: 0.0
+Generator 4: 6.0
+</pre></div>
+</div>
+</div>
+</div>
 <p>As shown by the result, the generator with less cost efficient has the highest active power output. The total generation power is also greater than the total demand due to the network loss.</p>
 </section>
 </section>

expression.html

@@ -361,8 +361,8 @@ <h2>Efficient expression construction<a class="headerlink" href="#efficient-expr
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 642 μs, sys: 99 μs, total: 741 μs
-Wall time: 744 μs
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 593 μs, sys: 129 μs, total: 722 μs
+Wall time: 726 μs
 </pre></div>
 </div>
 </div>
@@ -374,8 +374,8 @@ <h2>Efficient expression construction<a class="headerlink" href="#efficient-expr
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 18 ms, sys: 0 ns, total: 18 ms
-Wall time: 17.9 ms
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 17.6 ms, sys: 341 μs, total: 17.9 ms
+Wall time: 17.8 ms
 </pre></div>
 </div>
 </div>