diff --git a/book/_toc.yml b/book/_toc.yml
index 17ebf32850e43599db649aa095b71f5c8835c0b4..32719929f6bc5cb501bcb8db98ac25a470df7c52 100644
--- a/book/_toc.yml
+++ b/book/_toc.yml
@@ -67,6 +67,7 @@ parts:
- file: cookbook/benchmarks/benchmark_load_dont_execute.ipynb
- file: cookbook/widgets_dont_execute.ipynb
- file: cookbook/exercise_checking_dont_execute.ipynb
+ - file: cookbook/example_gumbel_dont_execute.ipynb
- caption: Old Material
chapters:
- file: old/blank
diff --git a/book/cookbook/example_gumbel.py b/book/cookbook/example_gumbel.py
new file mode 100644
index 0000000000000000000000000000000000000000..e8fa8cf322649f6d95a9205ec715860f97eac673
--- /dev/null
+++ b/book/cookbook/example_gumbel.py
@@ -0,0 +1,35 @@
+from grading import check
+from math import isclose
+
+tolerance = 0.001
+
+# Using rel_tol is more reliable in the face of aliasing, but to fit the instructions give we use abs_total
+check_float = lambda a, b: isclose(a, b, rel_tol=0, abs_tol=tolerance)
+
+# We have to pass in the globals object since we need to have access to changes as well
+@check
+def check_example(glob):
+ mu, beta = glob["mu"], glob["beta"]
+ if (check_float(mu, 5.0) and check_float(beta, 3.0)):
+ print(f"You got the parameters right, well done! (checked with tolerance {tolerance})")
+ else:
+ print(f"Your parameters are incorrect, your inverse won't be graded until these are right. (checked with tolerance {tolerance})")
+ return
+
+ function = glob["find_x_with_probability_p"]
+
+ test_inputs = [(0.1, 2.49790266426), (0.2, 3.57234501402), (0.9, 11.7511019819)]
+ failed = []
+
+ for x, out in test_inputs:
+ result = function(x)
+ if not check_float(result, out):
+ failed.append((x, out, result))
+
+ if len(failed) == 0:
+ print(f"Well done, your inverse function is correct! (checked with tolerance {tolerance})")
+ else:
+ print(f"Your function failed some tests. Keep in mind the tolerance is {tolerance}")
+ print("Failed inputs:")
+ for case in failed:
+ print(f"{case[0]} gave {case[2]}, expected {case[1]}")
\ No newline at end of file
diff --git a/book/cookbook/example_gumbel_dont_execute.ipynb b/book/cookbook/example_gumbel_dont_execute.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..023869937a18e0f5c950e4189ee7b89d35b101b5
--- /dev/null
+++ b/book/cookbook/example_gumbel_dont_execute.ipynb
@@ -0,0 +1,143 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Gumbel Distribution Exercise"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "tags": [
+ "thebe-init"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "%pip install ipywidgets\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "from math import log, e\n",
+ "import numpy as np\n",
+ "from example_gumbel import check_example"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "tags": [
+ "thebe-init"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "x_1 = 4\n",
+ "p_e_1 = 0.7523186963342055\n",
+ "x_2 = 10\n",
+ "p_e_2 = 0.17211051260760846"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "def gumbel_2_points(x_1, p_e_1, x_2, p_e_2): \n",
+ " \"\"\"Compute Gumbel distribution parameters from two points of the CDF.\n",
+ " Arguments:\n",
+ " x_1 (float): point one\n",
+ " p_e_1 (float): probability of exceedance for point one\n",
+ " x_2 (float): point two\n",
+ " p_e_2 (float): probability of exceedance for point two\n",
+ " \"\"\"\n",
+ "\n",
+ " # YOUR CODE GOES HERE #\n",
+ " beta = _\n",
+ " mu = _\n",
+ " #######################\n",
+ " return mu, beta"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mu, beta = gumbel_2_points(x_1, p_e_1, x_2, p_e_2)\n",
+ "\n",
+ "print(f\"Your mu: {mu}\\nYour beta: {beta}\")\n",
+ "\n",
+ "gumbel_distribution = lambda x: e**(-e**(-(x-mu)/beta))\n",
+ "\n",
+ "plt.title(\"Gumbel distribution\")\n",
+ "plt.ylabel(\"Cumulative probability\")\n",
+ "plt.grid(color='black', linestyle='-', linewidth=0.1)\n",
+ "plt.plot(x_1, 1-p_e_1, 'ro')\n",
+ "plt.annotate(\"Point 1\", (x_1 + 0.4, 1-p_e_1-0.03))\n",
+ "plt.plot(x_2, 1-p_e_2, 'ro')\n",
+ "plt.annotate(\"Point 2\", (x_2 + 0.4, 1-p_e_2-0.03))\n",
+ "x_axis = np.arange(0, 20, 0.1)\n",
+ "plt.plot(x_axis, np.vectorize(gumbel_distribution)(x_axis))\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_x_with_probability_p(p): \n",
+ " \"\"\" Compute point in the gumbel distribution for which the CDF is p\n",
+ " Use the global variables mu and beta defined above!\n",
+ " \"\"\"\n",
+ " # YOUR CODE GOES HERE #\n",
+ " p = _\n",
+ " #######################\n",
+ " return p"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "tags": [
+ "thebe-remove-input-init"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "check_example(globals())"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/book/cookbook/grading.py b/book/cookbook/grading.py
new file mode 100644
index 0000000000000000000000000000000000000000..a4c16360d38ae02c082c7103503958ceba948d7a
--- /dev/null
+++ b/book/cookbook/grading.py
@@ -0,0 +1,13 @@
+import ipywidgets as widgets
+from IPython.display import display
+
+def check(f):
+ def wrapper(*args, **kwargs):
+ output = widgets.Output()
+ button = widgets.Button(description="Check answer")
+ @output.capture(clear_output=True,wait=True)
+ def _inner_check(button):
+ f(*args, **kwargs)
+ button.on_click(_inner_check)
+ display(button, output)
+ return wrapper
\ No newline at end of file