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edwardchalstrey1edwardchalstrey1
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load from catalog in starting points tutorial
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‎doc/tutorials/advanced_tutorials/starting_points.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "57df88bc-3ff1-4f0a-848e-02724351976c",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"\n",
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"import pygambit as gbt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "493cafb8",
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"metadata": {},
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"outputs": [
@@ -39,14 +51,13 @@
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"Game(title='2x2x2 Example from McKelvey-McLennan, with 9 Nash equilibria, 2 totally mixed')"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import pygambit as gbt\n",
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"g = gbt.read_nfg(\"../../2x2x2.nfg\")\n",
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"g = gbt.catalog.Game2x2x2NFG()\n",
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"g"
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]
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},
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},
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{
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"cell_type": "code",
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"id": "b32adf22",
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"metadata": {},
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"outputs": [
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"[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5]]"
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]
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"outputs": [
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{
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"data": {
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"text/latex": [
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"$\\left[[0.3999999026224355, 0.6000000973775644],[0.49999981670851457, 0.5000001832914854],[0.3333329684317666, 0.6666670315682334]\\right]$"
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"$\\left[[0.4000002947381336, 0.5999997052618664],[0.4999994065053205, 0.5000005934946796],[0.3333334410505316, 0.6666665589494684]\\right]$"
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"[[0.3999999026224355, 0.6000000973775644], [0.49999981670851457, 0.5000001832914854], [0.3333329684317666, 0.6666670315682334]]"
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"[[0.4000002947381336, 0.5999997052618664], [0.4999994065053205, 0.5000005934946796], [0.3333334410505316, 0.6666665589494684]]"
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},
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"metadata": {},
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{
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"outputs": [
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"[[0.9, 0.1], [0.9, 0.1], [0.9, 0.1]]"
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]
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},
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{
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"execution_count": 20,
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"id": "08a22505",
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"metadata": {},
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"outputs": [
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{
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"text/latex": [
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"$\\left[[1.0, 0.0],[0.9999999944750116, 5.524988446860122e-09],[0.9999999991845827, 8.154173380971617e-10]\\right]$"
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"$\\left[[0.9999999968173041, 3.1826958638999237e-09],[0.9999999929853859, 7.014614077736281e-09],[0.999999999193891, 8.061090096721423e-10]\\right]$"
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"text/plain": [
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"[[1.0, 0.0], [0.9999999944750116, 5.524988446860122e-09], [0.9999999991845827, 8.154173380971617e-10]]"
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"[[0.9999999968173041, 3.1826958638999237e-09], [0.9999999929853859, 7.014614077736281e-09], [0.999999999193891, 8.061090096721423e-10]]"
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"outputs": [
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"data": {
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"text/latex": [
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"$\\left[[0.7187961367413075, 0.2812038632586925],[0.1291105793795489, 0.8708894206204512],[0.12367227612277114, 0.876327723877229]\\right]$"
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"$\\left[[0.5816023335384932, 0.41839766646150667],[0.14988214487024656, 0.8501178551297536],[0.1633565719798093, 0.8366434280201908]\\right]$"
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"text/plain": [
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"[[0.7187961367413075, 0.2812038632586925], [0.1291105793795489, 0.8708894206204512], [0.12367227612277114, 0.876327723877229]]"
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"[[0.5816023335384932, 0.41839766646150667], [0.14988214487024656, 0.8501178551297536], [0.1633565719798093, 0.8366434280201908]]"
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"text/latex": [
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"$\\left[[0.5000003932357804, 0.4999996067642197],[0.3999998501612186, 0.6000001498387814],[0.2500001518113522, 0.7499998481886477]\\right]$"
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"$\\left[[0.5000006764533134, 0.49999932354668664],[0.39999957335142133, 0.6000004266485787],[0.24999957325483269, 0.7500004267451672]\\right]$"
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"text/plain": [
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"[[0.5000003932357804, 0.4999996067642197], [0.3999998501612186, 0.6000001498387814], [0.2500001518113522, 0.7499998481886477]]"
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"[[0.5000006764533134, 0.49999932354668664], [0.39999957335142133, 0.6000004266485787], [0.24999957325483269, 0.7500004267451672]]"
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{
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"True"
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"source": [
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"import numpy as np\n",
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"gen = np.random.default_rng(seed=1234567890)\n",
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"p1 = g.random_strategy_profile(gen=gen)\n",
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"gen = np.random.default_rng(seed=1234567890)\n",
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"outputs": [
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"[[Rational(1, 2), Rational(1, 2)], [Rational(7, 10), Rational(3, 10)], [Rational(0, 1), Rational(1, 1)]]"
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]
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"[[Rational(1, 1), Rational(0, 1)], [Rational(1, 1), Rational(0, 1)], [Rational(1, 1), Rational(0, 1)]]"
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"[[Rational(1, 10), Rational(9, 10)], [Rational(3, 5), Rational(2, 5)], [Rational(3, 5), Rational(2, 5)]]"
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]
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"[[Rational(0, 1), Rational(1, 1)], [Rational(0, 1), Rational(1, 1)], [Rational(1, 1), Rational(0, 1)]]"
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"[[Rational(7, 10), Rational(3, 10)], [Rational(4, 5), Rational(1, 5)], [Rational(0, 1), Rational(1, 1)]]"
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"[[Rational(1, 1), Rational(0, 1)], [Rational(1, 1), Rational(0, 1)], [Rational(1, 1), Rational(0, 1)]]"
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"metadata": {
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"kernelspec": {
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"display_name": "gambitvenv313",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},

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