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day 4, jupyter notebook

This commit is contained in:
setop 2022-02-21 23:24:17 +01:00
parent a877bc5bed
commit 6435f86126
3 changed files with 1057 additions and 0 deletions
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228
d04/.ipynb_checkpoints/d04-checkpoint.ipynb Normal file
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{
"cells": [
{
"cell_type": "markdown",
"id": "e4d43863",
"metadata": {},
"source": [
"# setup"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "f81b055e",
"metadata": {},
"outputs": [],
"source": [
"sample = \"\"\"7,4,9,5,11,17,23,2,0,14,21,24,10,16,13,6,15,25,12,22,18,20,8,19,3,26,1\n",
"\n",
"22 13 17 11 0\n",
" 8 2 23 4 24\n",
"21 9 14 16 7\n",
" 6 10 3 18 5\n",
" 1 12 20 15 19\n",
"\n",
" 3 15 0 2 22\n",
" 9 18 13 17 5\n",
"19 8 7 25 23\n",
"20 11 10 24 4\n",
"14 21 16 12 6\n",
"\n",
"14 21 17 24 4\n",
"10 16 15 9 19\n",
"18 8 23 26 20\n",
"22 11 13 6 5\n",
" 2 0 12 3 7\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "61075998",
"metadata": {},
"outputs": [],
"source": [
"input = open(\"input\",\"rt\").read()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "e8a71b8a",
"metadata": {},
"outputs": [],
"source": [
"splinput = input.split(\"\\n\\n\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "fd29a42b",
"metadata": {},
"outputs": [],
"source": [
"numbers = list(map(int, splinput[0].split(',')))"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "1a0fb4f1",
"metadata": {},
"outputs": [],
"source": [
"grids = []\n",
"ingrids = [l.splitlines() for l in splinput[1:]]\n",
"for grid in ingrids:\n",
" rows = []\n",
" for row in grid:\n",
" rows.append(list(map(lambda x: (int(x), False),row.strip().replace(' ',' ').split(' '))))\n",
" grids.append(rows)"
]
},
{
"cell_type": "markdown",
"id": "2891f090",
"metadata": {},
"source": [
"# commons"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a460886c",
"metadata": {},
"outputs": [],
"source": [
"def mark(ingrids, number):\n",
" grids = []\n",
" for grid in ingrids:\n",
" rows = []\n",
" for row in grid:\n",
" rows.append(list(map(lambda x: (x[0], x[1] or x[0]==number), row)))\n",
" grids.append(rows)\n",
" return grids\n",
"\n",
"def atleast1_row_completed(grid):\n",
" for row in grid:\n",
" if all(map(lambda x: x[1], row)):\n",
" return True\n",
" return False\n",
"\n",
"def wining_grid(grid):\n",
" return atleast1_row_completed(grid) or atleast1_row_completed(list(map(list,zip(*grid))))\n",
"\n",
"from itertools import chain\n",
"\n",
"def sum_unmarked(grid):\n",
" return sum(map(lambda x: x[0], filter(lambda x: not x[1], list(chain(*grid)))))"
]
},
{
"cell_type": "markdown",
"id": "504cbf6d",
"metadata": {},
"source": [
"# part 1"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "e18c276b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"74320"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def run_1(grids, numbers):\n",
" for number in numbers:\n",
" grids = mark(grids, number)\n",
" for grid in grids:\n",
" if wining_grid(grid):\n",
" return number *sum_unmarked(grid) \n",
"\n",
"run_1(grids, numbers)"
]
},
{
"cell_type": "markdown",
"id": "48f45375",
"metadata": {},
"source": [
"# part 2"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "61f6c035",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"17884"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def run_2(grids, numbers):\n",
" for (i, number) in enumerate(numbers):\n",
" grids = mark(grids, number)\n",
" # stop if all grid are winning except one\n",
" loosing_grids = list(filter(lambda g: not wining_grid(g), grids))\n",
" if len(loosing_grids) == 1:\n",
" lg = loosing_grids[0]\n",
" return run_1([lg], numbers[i+1:])\n",
"\n",
"run_2(grids, numbers)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "128cac38",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.9.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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d04/d04.ipynb Normal file
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{
"cells": [
{
"cell_type": "markdown",
"id": "e4d43863",
"metadata": {},
"source": [
"# setup"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "f81b055e",
"metadata": {},
"outputs": [],
"source": [
"sample = \"\"\"7,4,9,5,11,17,23,2,0,14,21,24,10,16,13,6,15,25,12,22,18,20,8,19,3,26,1\n",
"\n",
"22 13 17 11 0\n",
" 8 2 23 4 24\n",
"21 9 14 16 7\n",
" 6 10 3 18 5\n",
" 1 12 20 15 19\n",
"\n",
" 3 15 0 2 22\n",
" 9 18 13 17 5\n",
"19 8 7 25 23\n",
"20 11 10 24 4\n",
"14 21 16 12 6\n",
"\n",
"14 21 17 24 4\n",
"10 16 15 9 19\n",
"18 8 23 26 20\n",
"22 11 13 6 5\n",
" 2 0 12 3 7\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "9bda4c17",
"metadata": {},
"outputs": [],
"source": [
"input = open(\"input\",\"rt\").read()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "e8a71b8a",
"metadata": {},
"outputs": [],
"source": [
"splinput = input.split(\"\\n\\n\")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "fd29a42b",
"metadata": {},
"outputs": [],
"source": [
"numbers = list(map(int, splinput[0].split(',')))"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "1a0fb4f1",
"metadata": {},
"outputs": [],
"source": [
"grids = []\n",
"ingrids = [l.splitlines() for l in splinput[1:]]\n",
"for grid in ingrids:\n",
" rows = []\n",
" for row in grid:\n",
" rows.append(list(map(lambda x: (int(x), False),row.strip().replace(' ',' ').split(' '))))\n",
" grids.append(rows)"
]
},
{
"cell_type": "markdown",
"id": "2891f090",
"metadata": {},
"source": [
"# commons"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "a460886c",
"metadata": {},
"outputs": [],
"source": [
"def mark(ingrids, number):\n",
" grids = []\n",
" for grid in ingrids:\n",
" rows = []\n",
" for row in grid:\n",
" rows.append(list(map(lambda x: (x[0], x[1] or x[0]==number), row)))\n",
" grids.append(rows)\n",
" return grids\n",
"\n",
"def atleast1_row_completed(grid):\n",
" for row in grid:\n",
" if all(map(lambda x: x[1], row)):\n",
" return True\n",
" return False\n",
"\n",
"def wining_grid(grid):\n",
" return atleast1_row_completed(grid) or atleast1_row_completed(list(map(list,zip(*grid))))\n",
"\n",
"from itertools import chain\n",
"\n",
"def sum_unmarked(grid):\n",
" return sum(map(lambda x: x[0], filter(lambda x: not x[1], list(chain(*grid)))))"
]
},
{
"cell_type": "markdown",
"id": "504cbf6d",
"metadata": {},
"source": [
"# part 1"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "e18c276b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"74320"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def run_1(grids, numbers):\n",
" for number in numbers:\n",
" grids = mark(grids, number)\n",
" for grid in grids:\n",
" if wining_grid(grid):\n",
" return number *sum_unmarked(grid) \n",
"\n",
"run_1(grids, numbers)"
]
},
{
"cell_type": "markdown",
"id": "48f45375",
"metadata": {},
"source": [
"# part 2"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "61f6c035",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"17884"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def run_2(grids, numbers):\n",
" for (i, number) in enumerate(numbers):\n",
" grids = mark(grids, number)\n",
" # stop if all grid are winning except one\n",
" loosing_grids = list(filter(lambda g: not wining_grid(g), grids))\n",
" if len(loosing_grids) == 1:\n",
" lg = loosing_grids[0]\n",
" return run_1([lg], numbers[i+1:])\n",
"\n",
"run_2(grids, numbers)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "128cac38",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.9.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

601
d04/input Normal file
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46,12,57,37,14,78,31,71,87,52,64,97,10,35,54,36,27,84,80,94,99,22,0,11,30,44,86,59,66,7,90,21,51,53,92,8,76,41,39,77,42,88,29,24,60,17,68,13,79,67,50,82,25,61,20,16,6,3,81,19,85,9,28,56,75,96,2,26,1,62,33,63,32,73,18,48,43,65,98,5,91,69,47,4,38,23,49,34,55,83,93,45,72,95,40,15,58,74,70,89
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