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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"new_data = pd.read_csv(\"sudoku-3m.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>puzzle</th>\n",
" <th>solution</th>\n",
" <th>clues</th>\n",
" <th>difficulty</th>\n",
" </tr>\n",
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" <th>0</th>\n",
" <td>1</td>\n",
" <td>1..5.37..6.3..8.9......98...1.......8761.........</td>\n",
" <td>1985437266432785915276198439147352688761924352...</td>\n",
" <td>27</td>\n",
" <td>2.2</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>...81.....2........1.9..7...7..25.934.2..........</td>\n",
" <td>9348172567286534196159427381764258934523981673...</td>\n",
" <td>23</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>..5...74.3..6...19.....1..5...7...2.9....58..7...</td>\n",
" <td>2159837463876542194692713855387169249413258677...</td>\n",
" <td>25</td>\n",
" <td>2.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>........5.2...9....9..2...373..481.....36....5...</td>\n",
" <td>4738169256285397411954278637329481569413652785...</td>\n",
" <td>26</td>\n",
" <td>1.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>.4.1..............653.....1.8.9..74...24..91.....</td>\n",
" <td>9471536821286493576532874913819267455724389164...</td>\n",
" <td>25</td>\n",
" <td>1.1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id puzzle \\\n",
"0 1 1..5.37..6.3..8.9......98...1.......8761......... \n",
"1 2 ...81.....2........1.9..7...7..25.934.2.......... \n",
"2 3 ..5...74.3..6...19.....1..5...7...2.9....58..7... \n",
"3 4 ........5.2...9....9..2...373..481.....36....5... \n",
"4 5 .4.1..............653.....1.8.9..74...24..91..... \n",
"\n",
" solution clues difficulty \n",
"0 1985437266432785915276198439147352688761924352... 27 2.2 \n",
"1 9348172567286534196159427381764258934523981673... 23 0.0 \n",
"2 2159837463876542194692713855387169249413258677... 25 2.6 \n",
"3 4738169256285397411954278637329481569413652785... 26 1.4 \n",
"4 9471536821286493576532874913819267455724389164... 25 1.1 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"new_data['puzzle'] = new_data['puzzle'].apply(lambda x: x.replace('.','0'))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"quizzes = []\n",
"solutions = []\n",
"for idx, row in new_data.iterrows():\n",
" quizz = row[\"puzzle\"]\n",
" solution = row[\"solution\"]\n",
" quizzes.append(np.array([int(x) for x in quizz],).reshape(9,9).astype(np.uint8))\n",
" solutions.append(np.array([int(x) for x in solution]).reshape(9,9).astype(np.uint8))\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((3000000, 9, 9), (3000000, 9, 9))"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"quizzes = np.stack(quizzes)\n",
"solutions = np.stack(solutions)\n",
"quizzes.shape, solutions.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"sol = np.zeros((solutions.shape[0],2,9,9,9), dtype=np.uint8)\n",
"quizz = np.zeros((solutions.shape[0],2,9,9,9), dtype=np.uint8)\n",
"for i in range(9):\n",
" sol[:,1,:,:,i] = (solutions==i+1).astype(np.uint8)\n",
" sol[:,0,:,:,i] = ((solutions!=i+1) & (solutions!=0)).astype(np.uint8)\n",
" quizz[:,1,:,:,i] = (quizzes==i+1).astype(np.uint8)\n",
" quizz[:,0,:,:,i] = ((quizzes!=i+1) & (quizzes!=0)).astype(np.uint8)\n",
" \n",
"np.savez(\"sudoku_reshaped_3_million.npz\",quizzes=quizz[:1000000],solutions=sol[:1000000])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"display_name": "Python 3 (ipykernel)",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"pygments_lexer": "ipython3",
"version": "3.10.4"
},
"toc": {
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"title_cell": "Table of Contents",
"title_sidebar": "Contents",
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