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"source": [
"import random\n",
"import numpy as np\n",
"\n",
"\n",
"def iterate(num_exams, A, B):\n",
" \n",
" A_wins = []\n",
" B_wins = [] \n",
" \n",
" for exam in range(0,num_exams):\n",
" rand_questions = [random.randint(0,99) for i in range(0,25)]\n",
" A = [PA[q] for q in rand_questions]\n",
" B = [PB[q] for q in rand_questions]\n",
" \n",
" A_question_wins = 0\n",
" B_question_wins = 0\n",
" Draw = 0\n",
" for idx, p in enumerate(A):\n",
" prob_A_win = p * (1-B[idx])\n",
" prob_B_win = (1-p) * B[idx]\n",
" prob_both_win = (p*B[idx])\n",
" prob_both_lose = ((1-p)*(1-B[idx]))\n",
" prob_draw = prob_both_lose + prob_both_win\n",
" #all_prob = prob_A_win + prob_B_win + prob_both_win + prob_both_lose\n",
" r = random.uniform(0, 1)\n",
" #print(prob_draw)\n",
" #print(\"A\" + str(prob_A_win))\n",
" #print(\"B\" + str(prob_B_win))\n",
" if(r < prob_draw): \n",
" Draw += 1\n",
" elif(r <= (prob_draw + prob_A_win)): \n",
" A_question_wins += 1\n",
" else:\n",
" B_question_wins += 1\n",
" \n",
" if(A_question_wins > B_question_wins):\n",
" A_wins.append(1)\n",
" B_wins.append(0)\n",
" else:\n",
" A_wins.append(0)\n",
" B_wins.append(1)\n",
" A_tot = (np.sum(A_wins))\n",
" B_tot = (np.sum(B_wins))\n",
" \n",
" A_win_prob = A_tot / (A_tot+B_tot)\n",
" \n",
" B_win_prob = B_tot / (A_tot+B_tot)\n",
" \n",
" return A_win_prob\n",
" \n",
" \n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
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"/home/kevin/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:45: RuntimeWarning:\n",
"\n",
"invalid value encountered in double_scalars\n",
"\n",
"/home/kevin/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:47: RuntimeWarning:\n",
"\n",
"invalid value encountered in double_scalars\n",
"\n"
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""
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""
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],
"source": [
"import plotly\n",
"from plotly.graph_objs import Line, Layout\n",
"import plotly.graph_objs as go\n",
"import numpy as np\n",
"\n",
"\n",
"N = 1000\n",
"x = np.linspace(0, N, 100)\n",
"PA = [random.uniform(0, 1) for i in range(0,100)]\n",
"PB = [random.uniform(0, 1) for i in range(0,100)]\n",
"prob_A_win = [iterate(i,PA,PB) for i in range(0,N)]\n",
"\n",
"PA = [random.uniform(0, 1) for i in range(0,100)]\n",
"PB = [random.uniform(0, 1) for i in range(0,100)]\n",
"prob_A_win2 = [iterate(i,PA,PB) for i in range(0,N)]\n",
"\n",
"PA = [random.uniform(0, 1) for i in range(0,100)]\n",
"PB = [random.uniform(0, 1) for i in range(0,100)]\n",
"prob_A_win3 = [iterate(i,PA,PB) for i in range(0,N)]\n",
"\n",
"trace0 = go.Scatter(\n",
" x = x,\n",
" y = prob_A_win,\n",
" mode = 'lines',\n",
" name = 'lines'\n",
")\n",
"trace1 = go.Scatter(\n",
" x = x,\n",
" y = prob_A_win2,\n",
" mode = 'lines',\n",
" name = 'lines'\n",
")\n",
"trace2 = go.Scatter(\n",
" x = x,\n",
" y = prob_A_win3,\n",
" mode = 'lines',\n",
" name = 'lines'\n",
")\n",
"\n",
"\n",
"plotly.offline.init_notebook_mode(connected=True)\n",
"\n",
"data = [trace0, trace1, trace2]\n",
"\n",
"plotly.offline.iplot(data, filename='line-mode')\n"
]
},
{
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"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"language": "python",
"name": "python3"
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