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scientific-computing-2/auto_examples_jupyter_2/exercises/plot_exercise_8.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Exercise 8\n\nExercise 8 with matplotlib.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\n\nplt.figure(figsize=(8, 5), dpi=80)\nplt.subplot(111)\n\nX = np.linspace(-np.pi, np.pi, 256, endpoint=True)\nC = np.cos(X)\nS = np.sin(X)\n\nplt.plot(X, C, color=\"blue\", linewidth=2.5, linestyle=\"-\", label=\"cosine\")\nplt.plot(X, S, color=\"red\", linewidth=2.5, linestyle=\"-\", label=\"sine\")\n\nax = plt.gca()\nax.spines[\"right\"].set_color(\"none\")\nax.spines[\"top\"].set_color(\"none\")\nax.xaxis.set_ticks_position(\"bottom\")\nax.spines[\"bottom\"].set_position((\"data\", 0))\nax.yaxis.set_ticks_position(\"left\")\nax.spines[\"left\"].set_position((\"data\", 0))\n\nplt.xlim(X.min() * 1.1, X.max() * 1.1)\nplt.xticks(\n    [-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi],\n    [r\"$-\\pi$\", r\"$-\\pi/2$\", r\"$0$\", r\"$+\\pi/2$\", r\"$+\\pi$\"],\n)\n\nplt.ylim(C.min() * 1.1, C.max() * 1.1)\nplt.yticks([-1, +1], [r\"$-1$\", r\"$+1$\"])\n\nplt.legend(loc=\"upper left\")\n\nplt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "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": "3.12.11"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}