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butchi/tsp-grid-experiment-2022-07-14.ipynb

Created July 15, 2022 09:46
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巡回セールスマン問題(TSP)を格子で行うとどうなるかシミュレーションしてみた https://twitter.com/butchi_y/status/1547879894142849024
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tsp-grid-experiment-2022-07-14.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 18,
"id": "28e54d8e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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],
"text/plain": [
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics-"
]
},
"execution_count": 18,
"metadata": {
"text/html": [],
"text/plain": []
},
"output_type": "execute_result"
}
],
"source": [
"TableForm[\n",
" Table[\n",
" With[{ ptTbl = Join @@ Table[{x, y}, {x, 0, w}, {y, 0, h}] }, \n",
" Graphics[{AbsoluteThickness[3], Line[ptTbl[[\n",
" Last[FindShortestTour[ptTbl, PerformanceGoal :> \"Quality\"] ]\n",
" ]] ] }]\n",
" ], {w, 8}, {h, 8}\n",
" ]\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "b5dae270",
"metadata": {},
"outputs": [
{
"data": {
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],
"text/plain": [
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-"
]
},
"execution_count": 23,
"metadata": {
"text/html": [],
"text/plain": []
},
"output_type": "execute_result"
}
],
"source": [
"TableForm[\n",
" Table[\n",
" With[{ ptTbl = Join @@ Table[{x, y}, {x, 0, w}, {y, 0, h}] }, \n",
" Graphics[{AbsoluteThickness[3], Line[ptTbl[[\n",
" Last[FindShortestTour[ptTbl, PerformanceGoal :> \"Speed\"] ]\n",
" ]] ] }]\n",
" ], {w, 1, 18, 2}, {h, 1, 18, 2}\n",
" ]\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "d432a9d3",
"metadata": {},
"outputs": [
{
"data": {
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BAAgtZSXAAAAAE2I5hIAgDRz5iUAAACQEyNGjIg5ob6+PpPJXHjhhUnE2YwRI0bU19eXlJTkYa9vTZgwIW97rfPd5nLPPffs3r17/DdrU2bOnJmjyQDApkybNu2WW27J3fxzzz03d8ObiIULFzb2PWo6t115CQBQYO69997QEQrJ/8fenYZJVZ2LAu5mcgCD0DjQHaIxKA6RR6PGBD0KesBEbMAJY9QkeK7BE644RANx6m4HIpGDBC9RMaInGqNoUGiMYlTUCOKQQFAURFFEGkGGNAJiM/T9wXkIB6XZtfeuvWt431/d+K31fXtVCVX7q1rrJz/5ScDI2traFStWZLOWnejVq1d5eXnA4LieBsmvT/CMOaWiomLz5s1pVxHI559/nnzSWNZn7NixlZWVIQaOGDHizjvvDBgcy/p8/PHHHTt2DB6/bNmy6EnzVH19fXV1dcRJKisrk2le3nrrrXV1dQkkStEXO5clJSVz5sxJZoWL3MyZMy+44IK0qwiqf//+4f5OnjBhwrvvvhsw+KOPPgqRonjU1taOHz8++jz3339/9EmAvDNt2rRp06ZlafLjjz++eLpo2fPJJ59ccsklweNvu+227BWTazQvAQDyzMKFC6PfCC4SmS7UgAEDslNIIIsXLw4ePGHChOj7+yW/PuXl5XnavCwpKfn444/TLiG7HnrooSjDU1yfNWvWrFmzJsmMmzdvLvjnAwXpSzuXJOajjz564IEH0q4iqP79+4cbOHv27NmzZ8dbTDGL/pwJ/tk4AHLcli1JioQzLwEAAIrduHHjfv7zn6ddBZBFOpcAAHktydMNUueblwAAAEVt3Lhx//Ef/7HtnwwbNiytYihg3/3ud7/zne8EDF6wYMHEiROzWk/TLrroojZt2qRYQLxWr15dXV199NFHH3300WnXAgBkUfZ2c12yZMmf/vSnLE1eVDJ6jF566aVZs2Zlr5icpXkJAJDHjjjiiCOOOCLtKnLLrFmzor+y79Sp08knnxxLPU0bP378unXrIk5y8sknd+rUKWBw8uuzbt26WI5ryh0zZ87cd999064iNl/sXN53330//vGPQ0+Y0fr8+Mc/fvrpp0NkGThw4MCBA0MMDK1Zs2ZLlixJMmPhOeWUU6qqqgIG19bWptu8rK6uLqS9Fr/yla+MHDky7SqKVB4dNzhy5MiZM2eGGPiNb3wjjy4zTx155JFXXHFFwOBVq1YNHjw4q/UAuSmrr5BfeuklzcvoDjzwwNtvvz14/BVXXKF5CQBAnunXr1/wG8FFoqamJvor+yOOOOLee++NpZ6mPf3009Gbl5deemllZWXA4OTXp66ursCal3vvvXfBNC9j71yWZLg+u+yyS7gsyT8EBfOgA0kK/g90Lhg/fny45uX5558fezFs56tf/Wrwda6rq9O8BCCvOfMSAACgGGWjcwkAAAAR+eYlAABA0dG5BAAK2EMPPbT33nunXUX6Et5mP9umTZvWqlWrBBK1atVqwIABCSQCdkTzEgAAoLjoXAIAhe36669Pu4T0XX311WmXELOHH3744YcfTiDRuHHjEsgCNMG2sQAAAEVE5xIAAIBcpnkJAABQLHQuAQAAyHG2jQUAACgKOpcAQAE76aSTTjrppLSrSNnMmTNfffXVtKuIWTIndz7//PPz5s1LIBEQhOYlAABA4dO5BAAK25133pl2CekbNmxYgTUvR48enUyiCy+8UPMScodtYwEAAAqcziUAAAD5QvMSAACgkOlcAgAAkEdsGwsAAFCwdC4BAKBI3HXXXaE32v3jH//YtWvXeOtJxl133fXYY481HbNs2bJkirnooovatGkTPH7OnDnZKyavaV4CAAAUJp1LAAAoKm+99VbaJSRt+fLly5cvT7uK//Hhhx8GDz7wwAOzV0m+s20sAABAAdK5BAAAIB/55iUAAECh0bmkkKxYseLFF18MGBzX5+5nzJjRoUOHWKYK7oQTTggxKqP1iUvnzp3Ly8sDBocub+HCheEGAgCQ1zQvAUhNRUVF7uzqkOPef//94LeH+vTpM2XKlIgZr7766qqqqoDBtbW1Z511VsSM+SWj9ckdb7zxRtolJGHp0qXRJ1m9enXo5Tr88MOjF0Au+9GPfrTrrrumXUVTFi1aNHv27G3/JEjnsq6u7qc//Wm4jCtXrgw3cFs33HDDXXfdFWLgMccck9G/WeGypOL1119Pu4ScMH369BNPPDHhpGeeeWbCGaurq8M1L1NZn8WLFwcPHjFiRG1tbfaKyWW1tbXvvfdeY2NjaWlpwqkbGxtLSkrOOeec4O8jQhs1alS2U2ynvr4+4YwAead///47fZF8+umnv/POO8nUE6/TTz/99NNPT7uK/3HbbbcFD164cOGpp56avWIKhuYlAGlqaGhIu4TClPzCeijzwgcffNCnT5+0q8gPL7zwQteuXUMMLC8vz+h+Lvno2WefTbuEzAT/zuUTTzyR7WKaELpRd8wxx2QUn+5lAsXm8ssvTzH7Oeeck0CW+vr66urqBBIBEFy7du0OPfTQpmNy/EOZTdjppSUpo2JatmyZvUoKiTMvAQAACpbdYgEAAMgvvnkJAABQmHQuyWvh9lCNonPnzp07d04y48KFC0Mf65j8+syYMSP6ZhuHHXZYWVlZLPUAAFCoNC8ByAkffPBBx44d064it+y///5LliyJOMmECRN69+4dMPimm2668cYbI2bs3bv3hAkTIk6Sm2JZn9zxla98Zb/99ku7ipwT7rjKDRs2zJ07N/ZiyCljx45Nu4Qwgv8TsJ327dv//ve/j7eYLzVw4MCBAweGGPjggw8++OCDEbN/+9vfvv766yNOQpZUVlZWVlYmnPSFF15IOGNNTU24zTZTWZ+Kioq6urqIk/zqV79KvvIcccABB/Tt2zeBRHffffeaNWsSSPSlvvvd737nO99JKzsAUBg0LwHICS1btmzVqlXaVeSW0tLS6JO0aNEi+MI2b948esZmzZoV6kMZy/rkjhNPPHHSpElpV5FbQt8Irqurq6ioiL0eckroLmCe2nXXXZO55NBZQh+Qua199tmn2B5ZIEWHHXbYyJEjE0j08MMPp9i8POWUU6qqqtLKDgAUBs1LAAAAAADy20EHHbRy5crQw/v06TNu3LggkeXl5dG30c6Szz77LO0SAlmzZk2HDh3SruJ/SfFjH8AXaV4CAAAAAJD3VqxYUWCJClVjY6M1BJrQLO0CAAAAAAAAAEpKNC8BAAAAAACAHGHbWAAAAAAACserr756wAEH7DTswQcfHDx4cJREc+bM2WeffaLMUFSWL1+edglAftC8BAAAAACgcOy5555lZWU7DWvTpk3ERO3atQuSiJKSkj322CPtEmjKa6+91vRBpG+88Uboyd96662pU6c2EfDpp59mNGHTszWtS5cu5eXlAYOXL1+eaa4ePXpkXhTb07wEAAAAAAAoXv/n//yf7E1+00033XTTTTFOOH369GuvvTbc2MWLFwcPfumll0466aTg8VOmTMm8Ir6EMy8BAAAAAACAnKB5CQAAAAAAAOQE28YCAAAAAAAUl7Kysqwe0JjM6Y/77bffAQcc0HTM9OnTP//88+BzZlT5P/7xj5UrVwaPJwjNSwAAAAAAgOLy3HPPZW/yBx98MHuTb+v888/f6YGaFRUVdXV1ASfs169fv379ghdwyimnPP3008HjCcK2sQAAAAAAAEBO8M1LAAAAIOsaGhrWrl2bcNLWrVsHD46rvIyShpNHpW5n/fr1oYtPvloAAFKheQlRvfjii2mXQLaccMIJASPz92nQuXPn8vLytKvIWJ8+fVasWJF2FWFMmzYt3MC+ffu2atUqYPDcuXPDZUleXV3d2WefnXYVQS1atCjtEoDUVFVVpV1CSDU1NQlkiWV9jj766MrKyujzBDdv3rw8emSTX5/YDRs2bNiwYUlmLC8vX7x4cfD4gw46KPh+YjsyadKkBB6p5557rk+fPhEnyXR9YtG/f/9wA6urq/Pof9gvtWLFitDvHIO/Od3OjBkzOnToEDA4ljdZCxcuTP4Ncuj1CW3OnDlt27YNGLxw4cKsFgMAhUfzEqKqr6+P/qaRHDRp0qTgwVOnTq2urs5aLVmU/N2KuEyfPj3tEjIWpU/8+uuvx1hJTsnHh7II1dXVff3rX0+7itzV2NgYyzz7779/aWlpwOCNGzfGkpSAfve730VvaSQvsV5XLOuT0auvWLzzzjs33HBDwklDS359gHhNnz79xBNPDDEwSpv5zDPPDDcwtHvvvffee+9NMmMqbfhf/vKXCWcEgKKieQkAwM41NDSkXULh27BhQ9olAAAAAKRM8xIAAADIloTPKWxsbFy3bl30eXbffffg34Zfv379pk2boicNp3nz5rvuumvA4LjWJ1PhngYbNmzw8SkAgCKkeQlxKisrO+yww9KugvDmzJkT/ZCP/fbbb7/99oulniyZMWNGId0C+PWvf33cccelXcUOLV++vG/fvuHGPvLII/EWk+M6dOgwceLEtKsA2Lkrr7xyjz32SLuKHZo3b96DDz6YYgFXXXVV8PX5wx/+MG/evKzW80XJnAMaiwcffDD59YlXVVVVwucU1tXVVVRURJ9n/vz5wff879OnT21tbfSk4Zx66qnBdxWOa30yEnrT45qamjw9nmNb4Y5jbGhomDFjRriMnTt37ty5c7ixoSV86mSU9Yki+cM1KRijR48upFsx4Xz66ad33XVX2lUEUlZWNmDAgLSrgKKmeQlx6tatm6No8losNx0GDBiQ8A2aTFVUVOTjqV07cvDBB3fr1i3tKnYoylLn8nVlQ6tWrYrtkvNUx44dP/jgg7SrKBzvv/9+2iWQscsvvzzKMcbZVltbm27z8rLLLgu+Pq+99lrCzbnKysrEjgKN7vXXX8/35iUUudB/50RpM7/wwgvhBoaWvxJOnxsAACAASURBVB9TyIgbPkR01VVXpV1C+vJlEcaNG5d2CVDsNC8BAMhAaWlpq1at0q6icFhMAAAAgG01S7sAAAAAAAAAgJIS37wEAAAAAIBkfOtb3zrppJPSriJlrVq1Gjx4cNpV/C9PPfXUm2++mXYVcfrLX/7Sv3//4PHXXntt165dmwh46aWXRo8eHbmueLz99tuhxw4cOHC33XYLHj9+/PjQuQhN8xIAAAAAAJJw/PHH33rrrWlXkbJddtkl1xZhxYoVBda8XLBgwYIFC4LHX3vttTuNeeSRRyJUlCsmT54cPLhfv37Zq4Qm2DYWAAAAAAAAyAmalwAAAAAAAEBOsG0sAAAAAABAfmvfvn1GBzReddVVCxcuDJHo4IMPvuGGG0IMTMuoUaOCB7/22mu5tq1xEdK8BAAAAAAAyG9nn312RvE33XRTuEQdOnTINFe6Mqq2ZcuW2auEgGwbCwAAAAAAAOQEzUsAAAAAAAAgJ2heAgAAAAAAADlB8xIAAAAAAADICZqXAAAAAAAAQE5osfWnPn36vPvuuymWUjxatWr1pz/96Rvf+EbTYbW1tUOGDIme7q233goefOihh0bPOHz48MrKyoDBNTU1Dz/8cMSMnTt3njRpUsRJYrFp06a1a9emXUUGWrduHTAyv64rtE2bNkWfpKGhIfnlCv5QFrmampoVK1ZEn2f06NEhRtXX1w8ePDh69uC+973vnXrqqeHGPvnkk8HX6v333w+XZVvJr08UZWVlVVVVaVcBpGPKlCnt27dPOGnfvn1DjPr4448nTpwYMHjlypUhUuSCuXPnBr/M1B1zzDHl5eVpV5GcdN/xLVu2LKM3ucuWLQuRJS5jxowJvlZr1qzJajE71b179xYtWuw87gsyumNQAEK/N1y3bl3ySeOSwK2GKOuz3TypL1cT1q9fn3YJAJCO//VC8+23306rjuLRpUuXIJ3LLaI/Ipm+K66vr6+rq4uYNFPRL7Nz586xVBLdn//85zZt2qRdRVCTJk0K/qZxxIgR1dXV2SyncAwbNmzYsGFJZiwvL1+8eHGSGfPa7bffHnGG0Hdb1q5dGz17Rv7f//t/kydPDte/fOWVV1555ZXYS2pC8usTRQH8lTht2rTjjjsuYHBDQ0PoRMGzZEOvXr2Ct5lra2tvueWW6EmnTZsWPDiW9Rk6dGi4v5ruueeep59+OmBw/na2YnfhhRcmnLG6ujpc8/K1117r169f7PXkmoceeuihhx5Ku4qgivBlW4rv+DZu3JhHNzo++eSTTz75JO0qgpo/f37aJeSH5557rk+fPgknPeigg5K/t7NVdXV18FdfqazPtg488MAUswMAOxLmU3KE1qVLlyeeeCJg5xIAImpsbDzttNNC9y8pbCtXrpw+fXoCiT744IMUb5/16tUro/joa5LpR8fSXZ9FixYtWrQorewAAAAAX6R5mRydSwCSp38JAAAAO/Xf//3ff/jDH4JEbtiwIUqiMWPG3HnnnVFmCOjKK6+8+eabg0TusssumU4e8eilTz/9NETSESNGXHLJJTsNW7Jkyf7775/p5Bs3bsx0CJA9X968HDNmTI8ePRIupcBcc801jz322NZfDz744MmTJ4fuXPbo0WPMmDEBg5ctW9a9e/dwibb1/PPP77333gGDBw0aNHXq1IgZBw0aNGjQoIDBU6dODR6cbXl03OD69eujH+vYqlWrli1bxlJPIUn4adDY2BjXIR9F6/vf//73v//9gMFvvvnm2LFjwyUKd0BmRM8888zWo6GC9y/bt2+ffLWprE84Tz755JNPPpl2FUA6jjnmmIQzzps3b+7cueHGhttjNu/k0WVOmTLFuWUlCb7je+utt8INTF7//v379++fdhVBPfPMM+EGxnLHoAA0b9581113TTjp7rvvXlpamu0sGzZsiHLKwBZJrk8e3cYhSZs3b47+TA5i06ZN0e/OxSuZC08yaSpXlAsyPcA7dMt2w4YNmeZqutewatWqiB8LiFF9fX3aJbCD5mWnTp0OOeSQhEspJBdeeGGMncuSkpI2bdoEf0Tatm0bOtG2DjzwwOD7nsVy0ONee+0V/DLffffd6BljUVlZuWbNmrSrCKpPnz61tbURJ7n66quDn2BRJKqqqhJek7q6uoqKiiQzFp5jjz02yOf1tqitrQ3XvCwvLw+eJUaXXHLJ8OHDhw4duuXXgP3L5EtNa33CWblyZb43L8vKyjI6jjF2EydO7NChQ7azjBs37p577ok4yXHHHffrX/86YPDy5ctjaaJktD6/+MUvwj2aPXv27NmzZ4iBRe7xxx9POGNNTU2443UrKytDH8+cR/Lr5WhFRUWKG0TnjmTe8ZWXl2e6g3eK8uveS+hqY7ljUABOPfXUrZ8vTMz8+fMT+D8i9L9Z20psfYrw7GHItsbGxrRL4H889thjF198cQKJXnnllX322Sd4/IMPPnjuuec2HZPRhBQ828bG78ILL7z33nu3/hq9cwkAIQwZMqSkpCTT/iWFrVu3bukWcPTRRydw++wvf/lL9Enat28ffLni6klktD7t27cPlyX1pwEAAABAEzQvY6ZzCUDu0L8EAACAHTnvvPPOO++8BBJdfPHFyXwfbvjw4ddff32UGT7//PO4itnOLrvsEmLyyy+//Le//W3opPvuu+/ChQtDDwfSonkZJ51LAHKN/iUAAAB8qVatWhVYoubNm0ecIXulhps54hWVlpYmtvi5Zrfddttjjz3inbPpcyu3s3r16nDnvpeWlu61114hBlJINC9jo3MJQG7SvwQAAAAoKj/60Y/uvPPOGCc8/vjjly5dGjz+hz/84R//+McQifbcc8+MElGQmqVdQIHQuQQglw0ZMuSWW27Z+uuW/uWf//znFEsCAAAAAPgizcsY6FwCkPv0LwEAAACA3Kd5GZXOJQD5Qv8SAAAAAMhxmpeR6FwCkF/0LwEAAACAXKZ5GZ7OJQD5SP8SAAAAAMhZmpch6VwCkL/0LwEAAACA3KR5GYbOJQD5Tv8SAAAAAMhBmpcZ07kEoDAMGTLkV7/61dZf9S8BAAAAgNRpXmZG5xKAQjJ06FD9SwAAAAAgd7SIPkVNTc27774bfZ77778/YGRdXd2QIUOiZxw+fHh5eXnw+O06l1/5yle6dOlSXV0dvZIv9dFHH0WfZNWqVRdccEFG8dGTjhw5cvz48QGDZ8+eHT0jQJIWLVp03333pV1FbPbdd9+zzjrr0Ucf3fLrlv7l5MmTTz311OCT1NbWrlixInoxP/nJT4IHJ/8ozJo1K+GMQPZs2rQp9OvtZs2aBX8fETrL6tWrww2M5X1EpjZt2hR9kuXLlydf/Fe/+tWAkXV1dZs3bw6XJZb1KWYzZ87M6I1tLDK9Y7BVRu+I4xL8jsq2Mr1jsK1k1scdAwCA4hRD87KkpOSBBx6IOENlZWXCGUtKSoYPHx48eLvOZUlJyerVqydOnBi9jKz67LPPYlmrjDz//PMJZ0xXbW1tLN30ZCxatCj6JGPGjHn44Yejz1OozjnnnKqqquDxw4YNC/H/6caNGzMdQlxmzZo1YMCAtKvIonD9y+hrUl5enlHz8pprrqmrq4uYtNjU1tb+5S9/iT7P6NGjww287rrrWrduHWJgz549M325uMWTTz4ZvLP+/vvvh0ixnfr6+sGDB2cUHz3p2LFjwz2yZWVlwf/NCv38Wbt2bYhR2bZ06dJOnTqFG7t48eLgwT/72c9qa2vDJQpn5syZffr0STJjXC688MKEM1ZWVk6aNCl4fOjnDBF99NFHyb+xzeiOwbaSf0cc7p/Ikmh3DPJofXLH1KlTDz300HBj33rrrXADu3fv3qJFmLt/w4cPD/3USkBdXd2///u/R5/nmWeeCd6G79OnTyzf3winc+fOGf2bxe23315WVpZ2FXH6+c9/3qZNm7Sr+JeamppkEr366qtRhq9ZsyZEqV/72tcK+87PVll9HN98881wA9evX5/YEyyIjO70PvDAAy+//HITAbF8+r8YxNO8LHhf7FzCtt5+++20S0jUJ5988sknn6RdRYEYNmzYNddck3YVsL1w/Uvywu233x5xhvLy8tDNy3HjxoUb2LNnz3ADX3nllVdeeSXc2HDWrl0bfZEzNXny5HADM91EJPlLA4CCsWbNmnB3D8J9yXWL+fPnhx6b41K5FZPi/Z/OnTunlTpPFd4L15///Odpl/C/NDQ0DBs2LO0qdu7TTz8NsXVi6LeueWfChAk5uM/BZ599lr0NLzPVr1+/jOLD7YfBFznzcud0LoEs0bkklzn/EgAAAABIXszfvDzjjDNOP/30gMEzZ84cOXJkxIzt2rXL6LP/gwcPzuhYxwceeOCkk0466aSTMi8tTcm39/v379+/f/+Ek0Je07nMOxntaFowHnnkkZKSkoy+f9mpU6eTTz45YPC6detiORSqf//+u+++e/R5gIIX/IDD7SxZsiT6sYUdOnTYddddI06SkV133bVDhw5JZgwh9IMSzvr165cvXx5xkubNm3fs2DGWemhC8m9sM71jsFXy74ij3FEJvbB5tD4AAOS1mJuXXbt2Pf/88wMGt23bNnrzcrfddguesaSkZMiQIRm91M5o8hxRXl6efNn5uFDZ0KNHjzFjxqRdRVZ4t9m0MWPGZPTQb9e5bNGixW9/+9vjjz8+C6URj8rKylw+8SWnHHHEEcF3LKirq4uleXnbbbdF2U2rOH3zm9/86U9/GjC4vr7+uuuuC5do6NCh4QaOHTs23AkZ7du3D72xbWjJZ+zZs2e43XSffPLJJ598MmL2jJ4/uaO8vDz0+d8VFRXRz9kdN25cwv+a9OzZM8fPx0q+vNra2uhngu6zzz6xnCVPE1J56ZXpHYOtkn9HHPqOSpQ7Bnm0Prmjc+fO4Y6rXLZsWffu3cMlfeaZZ8INHDRo0NSpU8ONTdHee++d0Vmq3bt3X7ZsWcSkY8aM6dGjR8RJdmrq1KmDBg3KdpZCct5556VdQsyGDRvW0NCQdhU7d/LJJ//bv/1b2lX8LyE2HZ04ceLMmTOzUEve+M///M999tknxQJyZ6vYuXPnPvTQQ8Hju3Xr1q1bt+zVU5yceQlxatOmzSGHHJJ2FVlRqNcVl7322it48Bc7l5MnTz7llFOyUBfADn3961+/5JJLAgbX1dWFbl4Gz7Kdv/zlL+Gal6EzhlZeXp580tAZV65cGb15mdHzBwCKVui30m3btk0+aZs2bUInTVGLFi0yuuQWLWK4HdqpU6cE7pO8++672U5RYKqqqtIuIWYjRozIi+blSSeddPXVV6ddxb907NgxxJNh4cKFRd68vPjii7t27ZpW9nbt2uXO/8KPP/54Rs3L3Km8kDjzEiBROpcAAAAAALAjmpcAydG5BAAAAACAJmheAiRE5xIAAAAAAJqmeQmQBJ1LAAAAAADYKc1LgKzTuQQAAAAAgCA0LwGyS+cSAAAAAAAC0rwEyCKdSwAAAAAACE7zEiBbdC4BAAAAACAjmpcAWaFzCQAAAAAAmdK8BIifziUAAAAAAITQIu0CAArNX//612effXbrrzqXAAAAAECSfv/73z/22GNNx6xcuTL4hC+99NKZZ54ZraisuOiii2666aamYyoqKjZu3Bhwws8//zyjAk455ZRZs2ZlNCS4NWvWZGnmHKd5CRAznUsAAACAWGzevLmhoSGZXK1atQoSFr2egInyxaZNm0KsidXOts8+++yzzz6Ld85ly5bFO2GSslp8Xq9MbvpX83LBggVbf540adJ7770XcIoZM2ZEr2PBggWjRo0KGFxfXx89Y0lJyd133922bdtYpiJ5c+bMSbsE2Amdyxy3dOnSN954I+0qgiorKysvLw8YnPx1LVy4MOGMUcS1Pocffngs8wBAkZgxY0bwN/7RNTY2lpSUXH755eGGJ3nHYEupJWGrzeiOynZJQ69PRiI+7hHXB8h3f/rTn3bZZZcEEg0YMGDcuHFBIvfff/8lS5aETjR48ODf/OY3oYfnoOuvv/7666/PaMgee+yxevXqIJFXXnnl7bffHqqukpKSko4dO9bV1YUeDjll64uiYvCv5uXy5cu3/vy73/0u4TrmzJmT/GvQ6urqhDPCturq6oYMGRJ9nuHDhwdvaVxwwQXRM3bu3LmqqipgcG1t7fjx46Mnvf/++4MHx3KZ/fv3r6ysDD08YOcylfVhizvuuOOOO+5Iu4qgFi9eHDz4mmuuqa2tzV4x+S6W9amuri7a5uW6devuu+++EAN/9KMfNWuWxIHr4cqL0U9+8pPgwclXG8tuNosWLQpdeUbrE6+6urqjjjoq3NhYPkj74x//ONytt4svvjj4q6/QoqzPtv72t78Ff3Xap0+f1157LXrS4DLdA+pLffzxxx07dgw3NqP1KTBPPfXUU089lWTG8vLy0Lcakr9jEDpj6DsqUdYnI88991wsr77iqCVpod/xRfmuTOh3xDNnzgydNLqZM2cGrzz27xJlauTIkeEe2YzuqABA0bJtLKTpgQceiD7J8OHDgwfX19cn/6Yx+mVmen/nueeei/6hqv79+4cem9F3LpNfH4Ao/vnPfw4YMCDEwPHjxz/xxBOlpaWxl7SdhQsXpnh/s7y8PKPm3DXXXJOPHwSeNWtWuKdBpusTu48//jjF7KtWrUoxexCprE+6D0o4mzdvzseygVTE8sY/I7G8I07eRx99lPxahfb888+HG5inbXggX5x++umnn356AomOPfbYSZMmJZBoR0aNGvWrX/0q3Nh//OMf++67b7z1bPXwww937949S5MXFc1LgJjZLRbgSz355JO9e/dOpn8JAADktWTOKdy8efPGjRujzNCyZcsgb3A2bdq0adOmKIlyUIjHKOIBls2bN2/evPlOwxobGzds2BAlUf7ae++9k0nUsmXLxHJ9qdatW4ce26FDh+wVv+eee6a7MgXjX83LioqKioqKLT936tTpgAMOSCB98lvFnnPOOQlnBIqKzmXuy6OtPufOnRv91fZ+++33la98JZZ6ClJG67Ns2bKlS5dmtZ6Cp38JUIQSfuO/Zs2au+++O9zY5O8YzJgx4+WXXw43NtzCRlmfWPTt2zf4Haco6wPktbPPPvvss89OING999574YUXRplh4cKFQTaTHz169KWXXholUa65+eabb7755oyGfPrppxFvUNx2222XXHLJTsOWLFlilzLId/9qXv7tb39LOHdlZWWU8+TCGTlyZMIZIYh27dqNHj06ePzgwYOjbzt2xRVXHHnkkQGDH3vssQkTJkTMeOSRR15xxRUBg1etWjV48OCIGUtKSkaPHt2uXbuAwSNHjoxyyEfEzmUq61Nsqqqq8uh8kYqKiujbPd1+++3J/2ubRzJan5qammLe5Sn0Vp8bN2585plntu6vmHD/8ogjjjjiiCOynWXdunWxHGDcv3//3XffPfo82RPuaRDX+sRr3333TeZkr7Fjx4Yb+F//9V8jRoyIt5jgMl2fI488Mvo2qv/93//dq1eviJNkT7NmzZYsWRJubCzrk6eSf+lVV1cXujmX/B2DmpqacM250HdUoqxPLP7jP/4jo1dfhdS8zOgdX1wyekecivvvvz/tEoLq379/uPNlYrmjAgBFxbaxkBN22223888/P3j8kCFDojcvu3fvHvxN43vvvRf9pfZXv/rV4JdZV1cXS3PuzDPPDP5hq/Hjx4e+jxn9O5eprA9AEOXl5ffee2/o4WvXru3du/cLL7yw5dck+5f9+vVL4L55XV1dLM252267LZc/IBzlRnkONi+bNWuWvWNOthU6S5s2beKtJCOZrk+zZs2iJ23Xrl0yD0o4UWqLZX2AfJfRO764ZPSOOHn59TnL0A9fLHdUAKCoeAcFEA+7xQLsSOvWrZ944okTTzxx659s6V82NjamWBUAAAAAOUjzEiAG3/nOd3QuAZqgfwkAAABAEJqXADHQuQTYKf1LAAAAAHZK8xIAgIToXwIAAADQNM1LAACSo38JAAAAQBM0LwEASJT+JQAAAAA70iLtAgAAKDpb+pe9e/d+4YUXtvzJlv7lE088UVpamm5tAAAAkI8eeeSR7E0+d+7cjOKjFHP22WeHHrtTkydPbteuXYwTLl26NHjw/PnzZ82aFWP27WzevDl7kydJ8xIAgBToXwIAAECMVq5cefHFF6ddxf947LHH/vjHP4YY2K5du6w2LwcOHJi9yYPo379/ugXkBdvGAgCQDvvHAgAAALAdzUsAAFKjfwkAAADAtmwbCwBAmna0f2yLFl6pAgAk5+9///u3vvWttKuAkpKSkkceeeTVV19NINGbb76ZQJZYXHvttS1bttxp2CuvvBIx0VVXXZXpkPbt2//yl7/MaMjnn38eMNG0adMyrYctDjjggKOOOirtKv7Hscce+7Wvfa2JgIaGhokTJ2avgOOOOy57k4fWpk2b73//+2lXkaPcEgIAIGVf2r/ce++9060KAKCoVFdXV1dX61+SI0aMGJF2CbnlN7/5TTKJQqz8sGHDMh3S0NDgIc62nj173nnnnWlX8T8uvfTSc889t4mAVatWtW/fPnsFjB8/PnuTh9axY8fcLCwXaF4CAJC+L/Yvly1blm5JAET34osvxjLPCSecEMs8TYur2uAWLlwYbmDoUpcvXx5u4HZmzJjRoUOHgMErVqyIJSkJOO200yZPnqx/CWTEqR9A7DQvIaptd7FYsGDBqFGjAg6sr6+PpYC77767bdu2AYMXLFgQPeOMGTOCX+acOXOiZ1y7dm3wjFvioyedNGnSe++9F32epuXv+uSpmpqaEJ8HTMuGDRuiT3LGGWc0axbmiOurr766qqoqYHBtbe1ZZ50VIktc73D233//0tLSgMEbN26MJWm+W7169RtvvJFw0rKysvLy8h391y/2L6NbunRp6Ms8/PDD4yojoLlz5+bR7d3k1yddp512WvRJBg4cWFlZGWLggw8++NprrwUMXrp0aYgUeaempib4mmTD5MmTU8yeR6ZOnVpdXR1xksrKymSal+eee25dXV0CiaKrr6/v06dPigWceeaZKWbPUxndMYgiyju+JUuWROxfZnTHILotbyguv/zycMMzuqMS2owZM6JPksodJwBIi+YlxGnOnDmhXzGHFv1eQKaeeuqpp556KsmM9fX1yS/s7373u4QzhpbK+uSvhoaGtEtIVGKNunQXNpZGb7F54YUXunbtmnDSxYsXNx0Qe//yjjvuuOOOO0IMrKysnDRpUiw1BHfyyScnnDG0VNYnXTNnzoze0hg4cGC4ge+8884777wTMXvheeKJJ9JK3cTnMAB2JJU7BiFE7F8mf8egvLw89MImf0cltHx5/mRD165dL7jggmxnCf5x2CQF/0jxF2V0Rbfeemum8z/11FPPPvtspqNCJNoqNx8jIEs0LwEAyCHZ+P4lAADBRf/+JcSoS5cuV155ZdpVpCOxCw+RaNWqVZk2L/fYY4+ifSiBTGleAgCQW/QvAQrSfvvtt99++wUMXrFiRSwnLIT2ne98p1WrVikWEFxZWdlhhx2WQKLOnTt37tw5gUTkAv1LACBFmpcQg21fyp944okJZDznnHMSyLKd5PcnST5j586d82gbljwqNTddd9111157bdpVZMWjjz4abuBNN9104403Rszeu3fvCRMmRJwkiPfffz+BLIUnlXMcQ+zru6V/edpppz3//PMhkoa7zNWrVy9cuDDEwCjKysrKysoSThpOKuuTm37/+9+3b98+YPANN9yw7RHpwR199NFOVQzohz/84Q9/+MNsZ1m5cuWPfvSjbGcpbAMGDMjoRO10z3T805/+lC/7A3fr1i2Zrbx9qCic/H3jllH/MuHLXLNmzd133x1ubCp3VELL3+cPAESheQlR3XjjjdHv9Wdq5MiRCWeMssl+OOXl5clfZvIZQ0tlfQpM8+bN8+XT9JkKfV3NmzePnr1Zs2bJLGyhPnxZVVlZWVlZmXDSioqKcCcFtm7devLkySH6l1VVVeH+2UrlRvns2bMTzhha6o2E3HHyyScHb2ncdddd4bL07t073MAidNBBByWwXNEPPQWKUCqv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],
"text/plain": [
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-\n",
"\n",
"-Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphics- -Graphic\\\n",
" \n",
"> s- -Graphics- -Graphics-"
]
},
"execution_count": 24,
"metadata": {
"text/html": [],
"text/plain": []
},
"output_type": "execute_result"
}
],
"source": [
"TableForm[\n",
" Table[\n",
" With[{ ptTbl = Join @@ Table[{x, y}, {x, 0, w}, {y, 0, h}] }, \n",
" Graphics[{AbsoluteThickness[3], Line[ptTbl[[\n",
" Last[FindShortestTour[ptTbl, PerformanceGoal :> \"Speed\"] ]\n",
" ]] ] }]\n",
" ], {w, 2, 18, 2}, {h, 2, 18, 2}\n",
" ]\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45f99e33",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Wolfram Language 13",
"language": "Wolfram Language",
"name": "wolframlanguage13"
},
"language_info": {
"codemirror_mode": "mathematica",
"file_extension": ".m",
"mimetype": "application/vnd.wolfram.m",
"name": "Wolfram Language",
"pygments_lexer": "mathematica",
"version": "12.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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