beating max :-0

0078bf02 · BoB · a3c1c04d · 0078bf02
Commit 0078bf02 authored 7 months ago by BoB
--- a/day 13/day_13_bob.ipynb
+++ b/day 13/day_13_bob.ipynb
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "source": [
+        "#day13 - cleaned up code:\n",
+        "import re\n",
+        "def readfile(filename):\n",
+        "    with open(filename, 'r') as file:\n",
+        "        return [\n",
+        "            [int(num) for num in re.findall(r'[\\+=](\\d+)', line)]\n",
+        "            for line in file if line.strip()\n",
+        "        ]\n",
+        "numbers = readfile('input13.txt')\n",
+        "A, B, Prize = numbers[::3], numbers[1::3], numbers[2::3]\n",
+        "\n",
+        "import numpy as np\n",
+        "extradist = 10000000000000 # part1: extradist = 0\n",
+        "totalcost = 0\n",
+        "for i in range(len(A)):\n",
+        "  M = np.array([A[i], B[i]]).T  # Transpose to get correct 2x2 matrix\n",
+        "  p = np.array(Prize[i])[:, None] + extradist\n",
+        "  x = np.linalg.solve(M, p)\n",
+        "  x_round = np.rint(x).astype(int)\n",
+        "  if np.allclose(M @ x_round - p, np.zeros_like(p)):\n",
+        "    totalcost += int(3*x_round[0]+x_round[1])\n",
+        "print(f\"total cost = {totalcost}\")"
+      ],
+      "metadata": {
+        "id": "fzAQHgYHH6xZ"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
+%% Cell type:code id: tags:
+
+``` 
+#day13 - cleaned up code:
+import re
+def readfile(filename):
+    with open(filename, 'r') as file:
+        return [
+            [int(num) for num in re.findall(r'[\+=](\d+)', line)]
+            for line in file if line.strip()
+        ]
+numbers = readfile('input13.txt')
+A, B, Prize = numbers[::3], numbers[1::3], numbers[2::3]
+
+import numpy as np
+extradist = 10000000000000 # part1: extradist = 0
+totalcost = 0
+for i in range(len(A)):
+  M = np.array([A[i], B[i]]).T  # Transpose to get correct 2x2 matrix
+  p = np.array(Prize[i])[:, None] + extradist
+  x = np.linalg.solve(M, p)
+  x_round = np.rint(x).astype(int)
+  if np.allclose(M @ x_round - p, np.zeros_like(p)):
+    totalcost += int(3*x_round[0]+x_round[1])
+print(f"total cost = {totalcost}")
+```