test time

TeachBooks · May 1, 2024 · 55db9d3 · 55db9d3
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diff --git a/book/_config.yml b/book/_config.yml
@@ -3,6 +3,7 @@ author: Tom van Woudenberg and Maria Nogal
 email: [email protected] 
 logo: pages/figures/logo.jpg
 only_build_toc_files : True
+copyright: Delft University of Technology, CC BY 4.0
 
 execute:
   execute_notebooks: 'off'
@@ -15,7 +16,6 @@ html:
 sphinx:
   config:
     bibtex_reference_style: author_year
-    html_show_copyright: false
     html_js_files:
     - https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js
     thebe_config:

diff --git a/book/pages/moo_example.ipynb b/book/pages/moo_example.ipynb
@@ -9,22 +9,19 @@
     "\n",
     "Click {fa}`rocket` --> {guilabel}`Live Code` to activate live coding on this page!\n",
     "\n",
-    "\n",
-    "\n",
-    "\n",
     "## Problem\n",
     "In this problem we're trying to optimize a diesel engine for maximum power and minimum CO<sub>2</sub> emissions. Depending on the optimal engine speed, the power and CO<sub>2</sub> emissions change.\n",
     "\n",
     "The following data is available:\n",
     "\n",
-    "| Rotations per minute  | CO<sub>2</sub> Emissions | Power   |\n",
+    "| Rotations per minute | CO<sub>2</sub> Emissions | Power   |\n",
     "|------|---------------|---------|\n",
-    "| 800  | 708.       | 161.141 |\n",
+    "| 800  | 708           | 161.141 |\n",
     "| 1000 | 696.889       | 263.243 |\n",
-    "| 1200 | 688.247       | 330.51 |\n",
+    "| 1200 | 688.247       | 330.51  |\n",
     "| 1400 | 682.897       | 381.561 |\n",
-    "| 1700 | 684.955       | 391.17 |\n",
-    "| 1800 | 697.3       | 370. |\n",
+    "| 1700 | 684.955       | 391.17  |\n",
+    "| 1800 | 697.3         | 370     |\n",
     "\n",
     "This data is interpolated to obtain a continuous relation:"
    ]
@@ -191,6 +188,8 @@
     ":::{card} Test yourself\n",
     "Try and adjust the values for $x$. Can you find the optimal solution? How does it change for different models?\n",
     "<iframe src=\"../_static/power.html\" style=\"overflow:hidden;height:580;width:100%\" height=\"580\" width=\"100%\"> frameborder=\"0\"></iframe>\n",
+    "\n",
+    "<iframe src=\"https://tudelft.h5p.com/content/1292260165388503037/embed\" aria-label=\"Pareto optimal\" width=\"1088\" height=\"637\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" allow=\"autoplay *; geolocation *; microphone *; camera *; midi *; encrypted-media *\"></iframe><script src=\"https://tudelft.h5p.com/js/h5p-resizer.js\" charset=\"UTF-8\"></script>\n",
     ":::"
    ]
   },
@@ -419,14 +418,14 @@
    "id": "18dba09c",
    "metadata": {},
    "source": [
-    "Now let's solve the problem for each of the three models.\n",
+    "Now let's solve the problem for each of the three models. We're gonna time them to see how long the analysis takes.\n",
     "\n",
     "#### Weighted objective function"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 48,
    "id": "d2d014c1",
    "metadata": {},
    "outputs": [
@@ -443,11 +442,14 @@
       "      jac: [-5.684e-06]\n",
       "     nfev: 26\n",
       "     njev: 13\n",
-      " hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>\n"
+      " hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>\n",
+      "CPU times: total: 46.9 ms\n",
+      "Wall time: 20.6 ms\n"
      ]
     }
    ],
    "source": [
+    "%%time\n",
     "result = sp.optimize.minimize(fun = weighted_obj, x0 = x0, bounds = bounds)\n",
     "print(result)"
    ]
@@ -462,7 +464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 49,
    "id": "89a9bfc1",
    "metadata": {},
    "outputs": [
@@ -479,11 +481,14 @@
       "      jac: [-5.684e-06]\n",
       "     nfev: 50\n",
       "     njev: 25\n",
-      " hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>\n"
+      " hess_inv: <1x1 LbfgsInvHessProduct with dtype=float64>\n",
+      "CPU times: total: 31.2 ms\n",
+      "Wall time: 25 ms\n"
      ]
     }
    ],
    "source": [
+    "%%time\n",
     "result2 = sp.optimize.minimize(fun = goal_attainment, x0 = x0, bounds=bounds)\n",
     "print(result2)"
    ]
@@ -500,11 +505,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 50,
    "id": "476d4e0d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: total: 922 ms\n",
+      "Wall time: 945 ms\n"
+     ]
+    }
+   ],
    "source": [
+    "%%time\n",
     "x_pareto_opt =[]\n",
     "for delta_p in np.linspace(0,1,100):\n",
     "    delta_c = 1- delta_p\n",