res4_r=3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import random\n",
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "import time "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def nNumber(G,r,step):\n",
    "    n=len(G)\n",
    "    z=n\n",
    "    t=0\n",
    "    M_array=np.zeros(step)\n",
    "    M={random.randint(0,n-1)}\n",
    "    D={j for j in range(0,n)}\n",
    "    R=D-M;u=0\n",
    "    while u<step:\n",
    "        i=len(M)     \n",
    "        k=random.random()\n",
    "        pi_neg=(n-i)/((n-i)+(i*r))\n",
    "        pi_pos=(i*r)/((n-i)+(i*r))\n",
    "        pii=1-(pi_neg+pi_pos)\n",
    "        if k<(1-pii) and i!=0  :\n",
    "\n",
    "        \n",
    "            if k<pi_pos:  ###probabililty for a mutant to reproduce\n",
    "                ch=random.sample(M,1)\n",
    "                NE=[n for n in G.neighbors(ch[0])]\n",
    "                chh=random.sample(NE,1)\n",
    "                if chh[0]  in R:\n",
    "                    M.add(chh[0])\n",
    "                    R.remove(chh[0])\n",
    "                    t+=1\n",
    "\n",
    "            else:   ###of course when p <(1-pii) and >pi_pos so this is obvious this is for a mutant to die lonely\n",
    "                chre=random.sample(R,1)\n",
    "                NEre=[n for n in G.neighbors(chre[0])]\n",
    "                chhre=random.sample(NEre,1)\n",
    "                if chhre[0]  in M:\n",
    "                    R.add(chhre[0])\n",
    "                    M.remove(chhre[0])\n",
    "                    t+=1\n",
    "        M_array[u]=len(M)/n\n",
    "        u=u+1\n",
    "            \n",
    "    return(t,M_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def addedge(G):  ###for connecting degrees=1\n",
    "    a=nx.adjacency_matrix(G).toarray()\n",
    "    degree=np.sum(a,axis=0)\n",
    "    v=np.nonzero(degree==1)[0] ##identifying deg=1 vertices\n",
    "   \n",
    "    def chk(choice):\n",
    "        if choice[0]!=choice[1]:\n",
    "            return True\n",
    "        else:\n",
    "            return False\n",
    "        \n",
    "    \n",
    "    choice=np.random.choice(v,2)\n",
    "    while chk(choice)==False :\n",
    "        choice=np.random.choice(v,2)\n",
    "    \n",
    "    a[choice[0]][choice[1]]=1;a[choice[1]][choice[0]]\n",
    "\n",
    "    G_new=nx.from_numpy_matrix(a,create_using=nx.Graph())\n",
    "    \n",
    "    return G_new\n",
    "\n",
    "\n",
    "\n",
    "def check_stability(mm):\n",
    "    c=False\n",
    "    if mm[-1]==1 or mm[-1]==0:\n",
    "        c=True\n",
    "    return c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_175718/3074412905.py:28: DeprecationWarning: Sampling from a set deprecated\n",
      "since Python 3.9 and will be removed in a subsequent version.\n",
      "  chre=random.sample(R,1)\n",
      "/tmp/ipykernel_175718/3074412905.py:19: DeprecationWarning: Sampling from a set deprecated\n",
      "since Python 3.9 and will be removed in a subsequent version.\n",
      "  ch=random.sample(M,1)\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[0;32mIn [8]\u001b[0m, in \u001b[0;36m<cell line: 12>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     18\u001b[0m G\u001b[38;5;241m=\u001b[39mnx\u001b[38;5;241m.\u001b[39mfrom_numpy_array(A,create_using\u001b[38;5;241m=\u001b[39mnx\u001b[38;5;241m.\u001b[39mGraph())  \n\u001b[1;32m     20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m h \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m (num):\n\u001b[1;32m     21\u001b[0m     \u001b[38;5;66;03m#print('h=',h)\u001b[39;00m\n\u001b[0;32m---> 23\u001b[0m     t,m\u001b[38;5;241m=\u001b[39m\u001b[43mnNumber\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43mr\u001b[49m\u001b[43m,\u001b[49m\u001b[43mstep\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     25\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m check_stability(m)\u001b[38;5;241m==\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m:\n\u001b[1;32m     26\u001b[0m         \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnum=\u001b[39m\u001b[38;5;124m'\u001b[39m, h)\n",
      "Input \u001b[0;32mIn [6]\u001b[0m, in \u001b[0;36mnNumber\u001b[0;34m(G, r, step)\u001b[0m\n\u001b[1;32m     19\u001b[0m ch\u001b[38;5;241m=\u001b[39mrandom\u001b[38;5;241m.\u001b[39msample(M,\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m     20\u001b[0m NE\u001b[38;5;241m=\u001b[39m[n \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m G\u001b[38;5;241m.\u001b[39mneighbors(ch[\u001b[38;5;241m0\u001b[39m])]\n\u001b[0;32m---> 21\u001b[0m chh\u001b[38;5;241m=\u001b[39m\u001b[43mrandom\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msample\u001b[49m\u001b[43m(\u001b[49m\u001b[43mNE\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     22\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chh[\u001b[38;5;241m0\u001b[39m]  \u001b[38;5;129;01min\u001b[39;00m R:\n\u001b[1;32m     23\u001b[0m     M\u001b[38;5;241m.\u001b[39madd(chh[\u001b[38;5;241m0\u001b[39m])\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.9/random.py:427\u001b[0m, in \u001b[0;36mRandom.sample\u001b[0;34m(self, population, k, counts)\u001b[0m\n\u001b[1;32m    375\u001b[0m \u001b[38;5;124;03m\"\"\"Chooses k unique random elements from a population sequence or set.\u001b[39;00m\n\u001b[1;32m    376\u001b[0m \n\u001b[1;32m    377\u001b[0m \u001b[38;5;124;03mReturns a new list containing elements from the population while\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    401\u001b[0m \n\u001b[1;32m    402\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    404\u001b[0m \u001b[38;5;66;03m# Sampling without replacement entails tracking either potential\u001b[39;00m\n\u001b[1;32m    405\u001b[0m \u001b[38;5;66;03m# selections (the pool) in a list or previous selections in a set.\u001b[39;00m\n\u001b[1;32m    406\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    424\u001b[0m \u001b[38;5;66;03m# too many calls to _randbelow(), making them slower and\u001b[39;00m\n\u001b[1;32m    425\u001b[0m \u001b[38;5;66;03m# causing them to eat more entropy than necessary.\u001b[39;00m\n\u001b[0;32m--> 427\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mpopulation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_Set\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m    428\u001b[0m     _warn(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mSampling from a set deprecated\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    429\u001b[0m           \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msince Python 3.9 and will be removed in a subsequent version.\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    430\u001b[0m           \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m, \u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m    431\u001b[0m     population \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(population)\n",
      "File \u001b[0;32m~/anaconda3/lib/python3.9/abc.py:119\u001b[0m, in \u001b[0;36mABCMeta.__instancecheck__\u001b[0;34m(cls, instance)\u001b[0m\n\u001b[1;32m    117\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__instancecheck__\u001b[39m(\u001b[38;5;28mcls\u001b[39m, instance):\n\u001b[1;32m    118\u001b[0m     \u001b[38;5;124;03m\"\"\"Override for isinstance(instance, cls).\"\"\"\u001b[39;00m\n\u001b[0;32m--> 119\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_abc_instancecheck\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minstance\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "t1=time.time()\n",
    "num=300\n",
    "step=100000\n",
    "size=500\n",
    "r=3\n",
    "start=750;end=1000\n",
    "no_graph=np.arange(start,end)\n",
    "fix_time_total=[]\n",
    "ext_time_total=[]\n",
    "#G_tot=[];\n",
    "#M=[]\n",
    "for j in (no_graph):\n",
    "    mm=[]\n",
    "    #mm=np.zeros(num*step)\n",
    "    fix_time=[];ext_time=[]\n",
    "\n",
    "    A=np.loadtxt('G'+str(j)+'.txt')    \n",
    "    G=nx.from_numpy_array(A,create_using=nx.Graph())  \n",
    "\n",
    "    for h in range (num):\n",
    "        #print('h=',h)\n",
    "\n",
    "        t,m=nNumber(G,r,step)\n",
    "        \n",
    "        if check_stability(m)==False:\n",
    "            print('num=', h)\n",
    "            print('no=', j)\n",
    "        \n",
    "        #mm[0:step]=m\n",
    "        mm.append(m)\n",
    "        if m[-1]==1:\n",
    "            for tt in range (len(m)):\n",
    "                if m[tt]==m[-1]:\n",
    "                    fix_time.append(tt)\n",
    "                    break\n",
    "            \n",
    "        elif m[-1]==0:\n",
    "            for tt in range (len(m)):\n",
    "                if m[tt]==m[-1]:\n",
    "                    ext_time.append(tt)\n",
    "                    break\n",
    "    M_avg=mm[0]                      \n",
    "    for muts in mm[1:]:\n",
    "        M_avg=muts+M_avg\n",
    "    M_avg=M_avg/num\n",
    "    np.savetxt('M_avg'+str(j)+'.dat',M_avg)\n",
    "    np.savetxt('fixtime_r3_'+str(j)+'.dat',np.array(fix_time))\n",
    "    np.savetxt('exttime_r3_'+str(j)+'.dat',np.array(ext_time))\n",
    "    #M.append(mm)\n",
    "    \n",
    "#np.savetxt('fixation'+str(start)+'-'+str(end)+'.dat',fix_time_total)\n",
    "#np.savetxt('extinction'+str(start)+'-'+str(end)+'.dat',ext_time_total)\n",
    "t2=time.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for k in range(10):\n",
    "    plt.plot(M[0][k])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "47913.43322610855\n"
     ]
    }
   ],
   "source": [
    "print(t2-t1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fefd4969d00>]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(M_avg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean3=[]\n",
    "for q in fix_time_total:\n",
    "    mean3.append(np.sum(q)/len(q))\n",
    "np.savetxt('qmean3-750-1000.txt',mean3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_206491/1759016155.py:1: UserWarning: loadtxt: Empty input file: \"fmean3-0-250.txt\"\n",
      "  q1=np.loadtxt('fmean3-0-250.txt')\n",
      "/tmp/ipykernel_206491/1759016155.py:2: UserWarning: loadtxt: Empty input file: \"fmean3-250-500.txt\"\n",
      "  q2=np.loadtxt('fmean3-250-500.txt')\n",
      "/tmp/ipykernel_206491/1759016155.py:3: UserWarning: loadtxt: Empty input file: \"fmean3-500-750.txt\"\n",
      "  q3=np.loadtxt('fmean3-500-750.txt')\n",
      "/tmp/ipykernel_206491/1759016155.py:4: UserWarning: loadtxt: Empty input file: \"fmean3-750-1000.txt\"\n",
      "  q4=np.loadtxt('fmean3-750-1000.txt')\n"
     ]
    }
   ],
   "source": [
    "q1=np.loadtxt('fmean3-0-250.txt')\n",
    "q2=np.loadtxt('fmean3-250-500.txt')\n",
    "q3=np.loadtxt('fmean3-500-750.txt')\n",
    "q4=np.loadtxt('fmean3-750-1000.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fix_time_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "204"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fix_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "96"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ext_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_fix=[]\n",
    "for i in range (1000):\n",
    "    test_fix.append(np.loadtxt('fixtime_r3_'+str(i)+'.dat'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "211"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(test_fix[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "f3_mean=[]\n",
    "for f in test_fix:\n",
    "    f3_mean.append(np.sum(f)/len(f))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(f3_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'fixation time_r3')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZkAAAEGCAYAAAC3lehYAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAyeUlEQVR4nO3deXhdVb3/8fcnSZtOdE5LaVpaoAxlhsoMIiiDoCAXpF6Fiig/lYui14v04hXUi4J61YsKiIIgVxkElKJMlVmGQhlLoaWFFggtnSeatpm+vz/2SnoyNEnbc5om/bye5zzZZ+299l7rND3frGGvrYjAzMysEIo6ugBmZtZ1OciYmVnBOMiYmVnBOMiYmVnBOMiYmVnBlHR0AbYmgwcPjlGjRnV0MczMOpXnn39+cUSUtbTPQSbHqFGjmDp1akcXw8ysU5H09ob2ubvMzMwKxkHGzMwKxkHGzMwKxkHGzMwKxkHGzMwKxkHGzMwKxkHGzMwKxkEmDxauXMvPHpzJrAWrOrooZmZbFQeZPFi+ppqrHp7NTAcZM7NGHGTyoFf3YgAqq2o7uCRmZlsXB5k86N09W52ncl1NB5fEzGzr4iCTBz1TS2a1WzJmZo04yORBaUkRxUVijYOMmVkjDjJ5IIle3YpZXeXuMjOzXA4yedKrtJjKdW7JmJnlcpDJk27FRVTX1nV0MczMtioFDTKSbpC0UNKrLez7lqSQNDgnbaKk2ZJmSjo+J/1ASdPSvqskKaWXSrotpU+RNConzwRJs9JrQiHrmV0PotAXMTPrZArdkrkROKFpoqQRwMeAd3LSxgLjgT1TnqslFafd1wDnAWPSq/6c5wLLImIX4OfAlelcA4FLgYOBg4BLJQ3Ic90a1wkR4TBjZparoEEmIh4Hlraw6+fARTT+4/8U4NaIWBcRc4DZwEGShgF9I+LpyL7F/wCcmpPnprR9B3BsauUcD0yOiKURsQyYTAvBLp/ckjEza26Lj8lI+iTwXkS83GTXcODdnPcVKW142m6a3ihPRNQAK4BBrZyrpfKcJ2mqpKmLFi3apDoBCHBDxsyssS0aZCT1Ai4BvtvS7hbSopX0Tc3TODHiuogYFxHjysrKWjqkXSS5JWNm1sSWbsnsDIwGXpY0FygHXpC0PVlrY0TOseXAvJRe3kI6uXkklQD9yLrnNnSugslaMg4zZma5tmiQiYhpETEkIkZFxCiyYHBARLwPTALGpxljo8kG+J+NiPnAKkmHpPGWs4G70yknAfUzx04HHk7jNg8Ax0kakAb8j0tpBeMxGTOz5koKeXJJtwBHA4MlVQCXRsT1LR0bEdMl3Q68BtQA50dE/d2NXyGbqdYTuC+9AK4HbpY0m6wFMz6da6mkHwDPpeO+HxEtTUDIG8mzy8zMmipokImIz7Sxf1ST95cDl7dw3FRgrxbS1wJnbODcNwA3bERxN4sH/s3MmvMd/3kiOciYmTXlIJMnQoRHZczMGnGQyRO3ZMzMmnOQySPHGDOzxhxk8iSbXdbRpTAz27o4yORJkcBtGTOzxhxk8kSCOscYM7NGHGTyxEv9m5k15yCTJ15WxsysOQeZPPEd/2ZmzTnI5IuX+jcza8ZBJk+81L+ZWXMOMnmilh6TZma2jXOQyZMi34xpZtaMg0yeCKhzlDEza8RBJk+8QKaZWXMOMnnipf7NzJpzkMkXt2TMzJpxkMkT4Tv+zcyacpDJEznKmJk14yCTJx6TMTNrrqBBRtINkhZKejUn7SeSZkh6RdJfJPXP2TdR0mxJMyUdn5N+oKRpad9VUnbro6RSSbel9CmSRuXkmSBpVnpNKGQ9AYqKPCZjZtZUoVsyNwInNEmbDOwVEfsAbwATASSNBcYDe6Y8V0sqTnmuAc4DxqRX/TnPBZZFxC7Az4Er07kGApcCBwMHAZdKGlCA+jUQ8n0yZmZNFDTIRMTjwNImaQ9GRE16+wxQnrZPAW6NiHURMQeYDRwkaRjQNyKejmxxsD8Ap+bkuSlt3wEcm1o5xwOTI2JpRCwjC2xNg11eeal/M7PmOnpM5gvAfWl7OPBuzr6KlDY8bTdNb5QnBa4VwKBWztWMpPMkTZU0ddGiRZtVGTdkzMwa67AgI+kSoAb4Y31SC4dFK+mbmqdxYsR1ETEuIsaVlZW1XuhWyEv9m5k10yFBJg3Enwx8Ntavj18BjMg5rByYl9LLW0hvlEdSCdCPrHtuQ+cqGIGbMmZmTWzxICPpBODbwCcjojJn1yRgfJoxNppsgP/ZiJgPrJJ0SBpvORu4OydP/cyx04GHU9B6ADhO0oA04H9cSitgvTwmY2bWVEkhTy7pFuBoYLCkCrIZXxOBUmBymon8TER8OSKmS7odeI2sG+38iKhNp/oK2Uy1nmRjOPXjONcDN0uaTdaCGQ8QEUsl/QB4Lh33/YhoNAEh73XFDRkzs6YKGmQi4jMtJF/fyvGXA5e3kD4V2KuF9LXAGRs41w3ADe0u7GYqkqcwm5k11dGzy7oML/VvZtacg0zeeHaZmVlTDjJ5krVkHGbMzHI5yORJSzfmmJlt6xxk8sRjMmZmzTnI5ImX+jcza85BJk/ckjEza85BJk98n4yZWXMOMvniZWXMzJpxkMmTbIHMji6FmdnWxUEmT7zUv5lZcw4yeZItkOkwY2aWy0EmT7zUv5lZcw4yeeKl/s3MmnOQyZMi+WZMM7OmWg0ykraXdI2kX0saJOkySdMk3S5p2JYqZKcgqKvr6EKYmW1d2mrJ3Ej2pMp3gUeANcBJwBPAtQUtWScjL5FpZtZMW0FmaET8MiKuAPpHxJUR8U5E/BLYcQuUr9PwUv9mZs21FWRy9/9hI/NuU4Rnl5mZNdVWoLhbUh+AiPhOfaKkXYA3ClmwzsYLZJqZNddqkImI7wKVkj7dJH12RJze1skl3SBpoaRXc9IGSposaVb6OSBn30RJsyXNlHR8TvqBacLBbElXSVJKL5V0W0qfImlUTp4J6RqzJE1oz4exObzUv5lZc212eUVEHfBvm3j+G4ETmqRdDDwUEWOAh9J7JI0FxgN7pjxXSypOea4BzgPGpFf9Oc8FlkXELsDPgSvTuQYClwIHAwcBl+YGs0JwS8bMrLn2jqtMlvQtSSNSS2Rg+iJvVUQ8DixtknwKcFPavgk4NSf91ohYFxFzgNnAQWmqdN+IeDqykfU/NMlTf647gGNTK+d4YHJELI2IZcBkmge7vPLaZWZmzZW087gvpJ/n56QFsNMmXHNoRMwHiIj5koak9OHAMznHVaS06rTdNL0+z7vpXDWSVgCDctNbyFMQnl1mZtZcu4JMRIxubb+kj0XE5M0sS0s3mkQr6Zuap/FFpfPIuuIYOXJk26XcAC8rY2bWXL6mIV+5EccuqF8tIP1cmNIrgBE5x5UD81J6eQvpjfJIKgH6kXXPbehczUTEdRExLiLGlZWVbUQ1GvMCmWZmzeUryGzM7e6TgPrZXhOAu3PSx6cZY6PJBvifTV1rqyQdksZbzm6Sp/5cpwMPp3GbB4DjJA1IA/7HpbSCEXJ3mZlZE+0dk2nLhrqibgGOBgZLqiCb8XUFcLukc4F3gDMAImK6pNvJlrGpAc6PiNp0qq+QzVTrCdyXXgDXAzdLmk3WghmfzrVU0g+A59Jx34+IphMQ8sotGTOz5vIVZFoUEZ/ZwK5jN3D85cDlLaRPBfZqIX0tKUi1sO8G4IZ2F3YzeUzGzKy5fHWXzc3TeTqtoiJRV+coY2aWq11BRlIvSf8l6bfp/RhJJ9fvj4jTClXAzqJ7SRFVtV7r38wsV3tbMr8H1gGHpvcVwH8XpESdVPfiIqodZMzMGmlvkNk5In5MdmMkEbGGjZtR1uV1Ky6iLqDGgcbMrEF7g0yVpJ6kCVSSdiZr2VjSvST7KKtrPS5jZlavvbPLLgXuB0ZI+iNwOPD5QhWqM+pWnAWZqpo6enYvbuNoM7NtQ3uXlZks6QXgELJusq9HxOKClqyT6V6c9R568N/MbL2NmcI8HCgGugNHSdrmZ5TlWt9d5iBjZlavXS0ZSTcA+wDTgfpv0QDuKlC5Op3c7jIzM8u0d0zmkIgYW9CSdHL1QcYtGTOz9drbXfZ0enKlbUB9d5nHZMzM1mtvS+YmskDzPtnU5Wyproh9ClayTqa7u8vMzJppb5C5ATgLmMb6MRnLsb67zPfJmJnVa2+QeSciJhW0JJ2cZ5eZmTXX3iAzQ9KfgHvIudM/Ijy7LOlWf5+Mu8vMzBq0N8j0JAsux+WkeQpzjoYpzG7JmJk1aO8d/+cUuiCdXam7y8zMmmk1yEi6KCJ+LOmXtPB04Yj4WsFK1sn4Zkwzs+baasm8nn5OLXRBOrtubsmYmTXTapCJiHvSZmVE/Dl3n6QzClaqTqjhPhlPYTYza9DeO/4ntjNtm+WbMc3Mmms1yEg6MY3HDJd0Vc7rRqBmcy4s6RuSpkt6VdItknpIGihpsqRZ6eeAnOMnSpotaaak43PSD5Q0Le27SpJSeqmk21L6FEmjNqe8bfF9MmZmzbXVkplHNh6zFng+5zUJOL6VfK2SNBz4GjAuIvYie4TAeOBi4KGIGAM8lN6T1k0bD+wJnABcLan+yWDXAOcBY9LrhJR+LrAsInYBfg5cuanlbQ/fJ2Nm1lxbYzIvAy9L+lNEVBfg2j0lVQO9yALaRODotP8m4FHg28ApwK0RsQ6YI2k2cJCkuUDfiHgaQNIfgFOB+1Key9K57gB+JUkRUZBBk+IiIbklY2aWq11jMvkOMBHxHvBT4B1gPrAiIh4EhkbE/HTMfGBIyjIceDfnFBUpbXjabpreKE9E1AArgEFNyyLpPElTJU1dtGjRJtdJEt2Li9ySMTPLsTFPxsybNNZyCjAa2AHoLelzrWVpIS1aSW8tT+OEiOsiYlxEjCsrK2u94G3o2b2YNdW1m3UOM7OupEOCDPBRYE5ELEqtpLuAw4AFkoYBpJ8L0/EVwIic/OVk3WsVabtpeqM8kkqAfsDSgtQm6d29hNXrHGTMzOq1K8hI2lXSbyU9KOnh+tdmXPcd4BBJvdJssGPJbvycBExIx0wA7k7bk4DxacbYaLIB/mdTl9oqSYek85zdJE/9uU4HHi7UeEy9Xt2LqazarEl3ZmZdSnsXyPwzcC3wW2Cz/1SPiCmS7gBeIJsK/SJwHdAHuF3SuWSB6Ix0/HRJtwOvpePPj4j6cnwFuJFsEc/70gvgeuDmNElgKdnstILqVVrC6iq3ZMzM6rU3yNRExDX5vHBEXApc2iR5HVmrpqXjLwcubyF9KrBXC+lrSUFqS+ndvZjKdW7JmJnVa++YzD2SvippWLphcqCkgQUtWSfUq3sJU99exqvvrejoopiZbRXaG2QmAP8BPMX6GzK9aGYTew/vB8Bjb2z6VGgzs66kvffJjG7htVOhC9fZfPUjOwNQ4PkFZmadRrvGZCR1IxtgPyolPQr8pgCrAHRqxdmyadTUOciYmUH7B/6vAboBV6f3Z6W0LxaiUJ1VUZEoEtQ6yJiZAe0PMh+KiH1z3j8s6eVCFKizKykqckvGzCxp78B/raSd699I2ok83C/TFRUXyS0ZM7OkvS2Z/wAekfQW2ZpgOwLnFKxUnVhJkajx0zHNzIB2BpmIeEjSGGA3siAzIy27b00UF4vaOq/EbGYGbQQZScdExMOSTmuya2dJRMRdBSxbp1RSJI/JmJklbbVkPgw8DHyihX1Btnqy5fCYjJnZem09GbN+bbHvR8Sc3H1pNWRrwrPLzMzWa+/ssjtbSLsjnwXpKtySMTNbr60xmd2BPYF+TcZl+gI9ClmwzspjMmZm67U1JrMbcDLQn8bjMquALxWoTJ1a1pLx7DIzM2h7TOZu4G5Jh0bE01uoTJ1ase+TMTNr0N6bMV+UdD5Z11lDN1lEfKEgperESoo9JmNmVq+9A/83A9sDxwOPAeVkXWbWRLFnl5mZNWhvkNklIv4LWB0RNwEnAXsXrlidV4lnl5mZNWhvkKl/bsxySXsB/YBRBSlRJ1dcJGo88G9mBrR/TOY6SQOA7wCTgD7AdwtWqk6sZ7dilqz2sm5mZtD+xy//LiKWRcTjEbFTRAyJiGs358KS+ku6Q9IMSa9LOlTSQEmTJc1KPwfkHD9R0mxJMyUdn5N+oKRpad9VUvZ4Skmlkm5L6VMkjdqc8rbXqEG9mLu40o9gNjOjnUFG0s2S+uW831HSQ5t57f8F7o+I3YF9gdeBi4GHImIM8FB6j6SxwHiy2W0nAFdLKk7nuQY4DxiTXiek9HOBZRGxC/Bz4MrNLG+7jBzUmw/W1bC80k+mNjNr75jMP4Epkj4u6UvAZOAXm3pRSX2Bo4DrASKiKiKWA6cAN6XDbgJOTdunALdGxLq0htps4CBJw4C+EfF0ZE2HPzTJU3+uO4Bj61s5hTSwdzcAlq9xkDEza+/zZH4jaTrwCLAY2D8i3t+M6+4ELAJ+L2lf4Hng68DQiJifrjlf0pB0/HDgmZz8FSmtOm03Ta/P8246V42kFcCgVP4Gks4jawkxcuTIzahSpl/PFGQqq4Dem30+M7POrL3dZWcBNwBnAzcC96bgsKlKgAOAayJif2A1qWtsQ0VoIS1aSW8tT+OEiOsiYlxEjCsrK2u91O3Qr2d3AE675imPy5jZNq+93WX/AhwREbdExETgy6zvitoUFUBFRExJ7+8gCzoLUhcY6efCnONH5OQvB+al9PIW0hvlkVRCNu166WaUuV3698paMhHw3vI1hb6cmdlWrb2zy06NiIU5758FDtrUi6autncl7ZaSjgVeI5sePSGlTQDuTtuTgPFpxthosgH+Z1PX2ipJh6TxlrOb5Kk/1+nAw7EFmhajB/Vm+77ZyjsPvb6wjaPNzLq2tpb6vygifizpl7TQ1QR8bTOufQHwR0ndgbeAc8iC3u2SzgXeAc4AiIjpkm4nC0Q1wPkRUZvO8xWyLryewH3pBdmkgpslzSZrwYzfjLK2W1GReHriMRz7s8d4YtZiJhw2aktc1sxsq9TWwP9r6efUfF84Il4CxrWw69gNHH85cHkL6VOBvVpIX0sKUluaJPbcoR8PvPo+Kyqr6Ze60MzMtjVtBZkzgb8B/SPif7dAebqMY3cfwj0vz2PmglUcNHpgRxfHzKxDtDUmc6CkHYEvSBqQ7shveG2JAnZWO5Vl05dX+H4ZM9uGtdWSuRa4n+y+ludpPC04Urq1oG+PrItspYOMmW3DWm3JRMRVEbEHcENas2x0zssBphV9002ZK9c6yJjZtqu9U5i/UuiCdDV9e2SNxO/d8xp/f2V+B5fGzKxjtPdmTNtIJcXrP9of3vt6B5bEzKzjOMgUUHFRNoS1rqa2jSPNzLomB5kCmnji7gB0K/bHbGbbJn/7FdAXj9yJ0/YfTlWNH8dsZtsmB5kC23lIH5asrmLp6qqOLoqZ2RbnIFNgx+yePRJn0kvvdXBJzMy2PAeZAttjWF/2Ke/Hbx5/q6OLYma2xTnIbAEf33sY81es9Y2ZZrbNcZDZAkYM6AXAe8v8EDMz27Y4yGwB5QN6AvC1W17s4JKYmW1ZDjJbQH2QmbXwA/7x2oIOLo2Z2ZbjILMFDOzdvWH7i3+YynNzlzJv+Rrq6gr+NGgzsw7lILMFSOK5Sz7Kf348WwHgjGuf5rArHubKB2Z0cMnMzArLQWYLKduulC8duRPD+vVoSPvNY29RXevVAMys63KQ2YIk8eS3j+GHn9q7IW3MJfdxyV+mUbGssgNLZmZWGB0aZCQVS3pR0t/S+4GSJkualX4OyDl2oqTZkmZKOj4n/UBJ09K+qyQppZdKui2lT5E0aotXsAVFReJfDx7Jb846sCHtj1Pe4YgrH+ECzz4zsy6mo1syXwdyH7ZyMfBQRIwBHkrvkTQWGA/sCZwAXC2pOOW5BjgPGJNeJ6T0c4FlEbEL8HPgysJWZeMcv+f2zL3ipEZp97w8jwhPBjCzrqPDgoykcuAk4Hc5yacAN6Xtm4BTc9JvjYh1ETEHmA0cJGkY0Dcino7s2/kPTfLUn+sO4Nj6Vs7W5JXLjuP1759AevQMiz5Y17EFMjPLo45syfwCuAjIHfkeGhHzAdLPISl9OPBuznEVKW142m6a3ihPRNQAK4BBTQsh6TxJUyVNXbRo0WZWaeP17dGNnt2L+b8vHgzA428sZtEqBxoz6xo6JMhIOhlYGBHPtzdLC2nRSnpreRonRFwXEeMiYlxZWVk7i5N/e+7QjyLBt/78Mh+6/B/uNjOzLqGjWjKHA5+UNBe4FThG0v8BC1IXGOnnwnR8BTAiJ385MC+ll7eQ3iiPpBKgH7C0EJXJh349u3HN59ZPBvjePa8xrWJFB5bIzGzzdUiQiYiJEVEeEaPIBvQfjojPAZOACemwCcDdaXsSMD7NGBtNNsD/bOpSWyXpkDTecnaTPPXnOj1dY6tuHhy/5/Z88YjRANz41Fw+8at/8rGfPeZWjZl1Wh09u6ypK4CPSZoFfCy9JyKmA7cDrwH3A+dHRG3K8xWyyQOzgTeB+1L69cAgSbOBb5Jmqm3tvnPyWL578tiG97MWfsCM91d1YInMzDad/FfyeuPGjYupU6d2dDEAWF6ZPbL5mP95jNKSIm74/Ic4fJfBHV0sM7NmJD0fEeNa2re1tWQs6d+rOyMHZs+hWVdTx2d/N4WZbtGYWSfjILMVKyku4obPr//j4B+vL6DWKzebWSfiILOVO2b3ocz50ccB+MkDM7nglhf4YF0NNV5Y08w6AQeZTkAS+5b3A+Deae+z16UPMO7yf7CisrqDS2Zm1joHmU7irq8ezt3nH97wfnllNft+/0HOun4Ka6pqW8lpZtZxHGQ6ieIise+I/lz1mf0bpT8xazF7fPd+DvnhQ9z90nsc+z+Psmx1Fcsrq/jJAzNYW+0AZGYdx1OYc2xNU5g3pK4uuH/6++w/sj+H/ujhNo8/db8d+OFpe/PWotUs/mAdR+82pM08ZmYbo7UpzA4yOTpDkMlVsayS/r26s666lkkvz+PXj7zJ4jZWcW76eAEzs83l+2S6qPIBvehTWsKgPqWcc/hopn7nozxx0Uca9l9x2t7N8oy6+O/8+P4ZjdIiwo+BNrOCcEsmR2drybTHa/NWcv+r86mN4NePvNlo39eOHcPpB5RzyV+nMeWtpbxx+YkdVEoz68zcXdZOXTHI5Fqxppp7p81n4l3TWtz/yLeOZvTg3lu4VGbW2bm7zIDscQKfOWgkr37vePYf2b/Z/o/89FFefW8FcxevZsb7K3nsjUXMeH/lli+omXUZbsnk6Ootmaamzl3KQzMWcs2jb7Z63Cf23YF11bX06FbMRSfsxtS5yzhlvx3YCp9mbWYdwN1l7bStBZlcsxeu4pwbn6OmNpi/Ym2bx9923iEcvFP2NOu11bWUlhQ56Jhtoxxk2mlbDjJNvfreCs658TkWrdrwlOhe3YupTKsNDO/fk1+M349xOw5g6tvLuPTu6Vx0wm4csctgSordK2vWlTnItJODTGN1dcGS1VXU1mVTnH/8wEzueXleq3l6ditmTZNVBkYN6sXyNdVc+7kDqVi2hrteqODCj+7KKxXLKS4Snz14R7qXNA9EEcEzby3lkJ0GNrSSVlRW07u02IHLbCviINNODjKtiwgemL6At5es5hP77sDHr3qC5ZXVfGjUAF6bt5LVqVWz1/C+7D9iADc/83a7z73HsL58bI8hnLr/cN5eWsn9095nypwlzF1SCUDZdqU8cOFRHPCDyQzv35PLPrkn3YrFPuX9Gdi7e6NzvfreCvr36kb5gF4N71+fv5LTDyxnWWV1s+PNbPM4yLSTg8zGq6sLpOzBagtWruX5t5dx6n7DKSoSoy7+OwD3/NsRfOP2l5i98IOClOHLH96ZY3YfQnGRePyNRfzvQ7MA+M1ZB3LPy/P42yvzGx3/7RN2Z6/hfVlbXcfKNdW8vbSST+0/nGH9elAXQWVVLYP7lBakrGZdkYNMOznI5NeFt77Iu8vWcOdXDgNgyQfrmLN4NYP7lPKP1xdw6M6DWLGmmn/97ZQW8w/uU8qwfj2Y9t6KRunD+/dk16F9KC0p5v7p7+e1zGOG9GFWCoY//NTe/MuBw+lWVERR0fpJDVU1dVxx3wwWrFrLZZ/Yk7LtGgekurqguq6O0pLiDV5nXU0tr89fxX4j+ue1/GYdwUGmnRxkOlbFskqmVazgxL2HNaRVVtUw9rsPNLx/+N8/zE5lfRreP/PWEsZf90yj8+zQrwfzcmbInXbAcO564T0Azhw3gtumvtuwb3CfUo7dfUijtKa279uDU/cfzhnjytm5rA/fu2c6v39yLgD7j+zPZZ/Yk3U1dby3vJIHpy/gvlezwPelI0ez2/Z9OXq3Mh6esZBiiUv+Oo3HL/oIn/r1U7y3fE2z+myMtdW1dC9uHADbMvm1BQzr14O9hvfbpGuatcRBpp0cZLZOiz9Yx7SKFdzzyjx+9un9mu2f8f5KxgzZjreXrGbUoN4NX7pzFq+mpraOMUO3Y+b7q7j5mbl89+Q9KSkSL1UsZ/8R/RsmFPxpyjv8519aXgmh0G4+9yAO33kwldW19CktYU1VLW8sWMWS1es4akxZwySHt5es5uI7p7F9vx78zxn7stN/3gvAs5ccS1mfUt5ctJpdhmQB681FH/CT+2fyszP3pWe3YmYuWMXu2/dt6MLMXSi1sqqGXt1LmpVr6tylnH7t0/zs0/ty5wsVTDxxD+YsXk11bR2nHVBe6I/FOpGtLshIGgH8AdgeqAOui4j/lTQQuA0YBcwFPh0Ry1KeicC5QC3wtYh4IKUfCNwI9ATuBb4eESGpNF3jQGAJcGZEzG2tXA4y27ZHZixkyeoq9h7ej6Wrq/ju3a8ya+EH/O2CI/jxAzN5/I1FABy44wBO2HN7jt6tjMqqWk759ZMATDh0Rx6ZuYh/OaCcXz8ym6pNWHT09APLueP5ikZpA3t35xsfHcN/3T29xTyDendnyeoqAI7erYxe3YuZMX8Vby1eTdl2pZy09zBufGouvzhzPy687SUgWzx1j2F9+cuL73HjU3P56Rn7slNZb25++m32H9mfD40ayC8fnsW901rujvRq3pZrawwyw4BhEfGCpO2A54FTgc8DSyPiCkkXAwMi4tuSxgK3AAcBOwD/AHaNiFpJzwJfB54hCzJXRcR9kr4K7BMRX5Y0HvhURJzZWrkcZCxXXV1QF9HQkli4ai29upfQp7TxX/1/ebGCwX1KOXJMWaP0/3lwJlW1dUw8cQ/mr1jDkVc+Qk3d+v9vnz9sFDc+Nbfg9SgEBxnLtdUFmWaFkO4GfpVeR0fE/BSIHo2I3VIrhoj4UTr+AeAystbOIxGxe0r/TMr//+qPiYinJZUA7wNl0UqFHWSskG745xz69Cjh0+NGUFcXFBWJdTW1rF5Xy3///TVKS4p5Z+lqnpy9BIALjtmFD+9axunXPt1wjn85oJwJh+3IJ3/1JMP69aC6Npo9Q2i3odsxc8GqFsvQrVhU127+//mLT9ydL394Z1atrebxNxbzcsVyPj2unPIBvZCge3ERNXXB20sqG7rwrOtqLcg074jdwiSNAvYHpgBDI2I+QAo09Y9xHE7WUqlXkdKq03bT9Po876Zz1UhaAQwCFje5/nnAeQAjR47MW73MmvrCEaMbtuvHjUpLiiktKW401rSmqpZXKpZz8E6DGgLI/iP7c9dXDmsYQ3rzhx9HwLwVa4iAF99dznWPv8n5R+/CMXsMYXllNf16duODdTUM7lNKxbJKXnhnOXvt0Jdh/XoCcNmk6Zx2wHD22KEvdz5fwc8mv8Fln9iTIX1LOev6ZxuVfe/h/Zj23gq+c9Ie/PffX+eK+2Zw3eNvsTR10wFc9/hbDdvdi4saugvvv/BIFq5cx6JV63hk5kJO3W84Hx07tOHYpaurqK6tY2jfHnn4lG1r06EtGUl9gMeAyyPiLknLI6J/zv5lETFA0q+BpyPi/1L69WRdY+8AP4qIj6b0I4GLIuITkqYDx0dERdr3JnBQRCzZUHnckrGt0bSKFYwZ2oce3TY8JTrfIqLRWnTVtXVUrqtl4aq1fOznj2/WuUcO7MXfv3YEr763kilzlvCLf8xq2PfVo3fmj1Pe4Zsf25WqmjrOOXwUJcVFjcpT34359FtLGDmwF4/PWsznDh650Wvn1dUFNXXR4moTtnG2ypaMpG7AncAfI+KulLxA0rCc7rKFKb0CGJGTvRyYl9LLW0jPzVORusv6AUsLUhmzAtq7fMtPN276hd2tuIh+vYro16sbT1z0EZ6cvZjbp77LqEG9OfNDI3h32Rq+9eeX23Xud5ZWsvdlD7a47+q0Ivilk7JJDpff+3rDvguO2YW11bX89ok5zfLd89I8bv/yoaytruWpNxeztrqOE/favlk9Vq+rYeXaag790cMNaXN+9PFmx81bvoZh/Xo0pC9atY63l6xm3xH9ueK+GZy8zzD2Le+/UdPHt1UdNfAv4CayQf4Lc9J/AizJGfgfGBEXSdoT+BPrB/4fAsakgf/ngAvIutvuBX4ZEfdKOh/YO2fg/7SI+HRr5XJLxmzzrFxbzXalJcxe+AGX3/s6v/7XA1i6uoofPzCTfz1oJL98eBZPvbm+M2HUoF4NSwdtrh7dilhb3XhG3/D+Pdm+Xw92Hbodf3t5HqvW1TTLN/HE3fnRfTOalWXfEf3p2yP7O/yJWYub5SspEv918ljOPnRH3l+5lsWrqhr+IKgfc6v31qIP+Padr/Dvx+3G8P49Wbm2mnnL1zK0byljh/Vl+ZpqBvcpbdaC7Cy2uoF/SUcATwDTyKYwA/wnWaC4HRhJ1hV2RkQsTXkuAb4A1AAXRsR9KX0c66cw3wdckKYw9wBuJhvvWQqMj4j1ncYtcJAxK6w1VbVMfn0B7y6tpG+PEs46dBQR2QSBqW8vY9aCVew/cgBjh/Xl/unzWbGmmufmLOOkfYZx6aTpHL1bGacdUM4Lby9j5yF9GNirO4s/WNfQ8ukIQ/uWsmBlNnZ28Ym7s7yymmsfy1pkZduVMvHE3fnm7W238sYM6cPqdTV89pAdWVddy8n77sBDry/kydmL+f05H6JbcRGVVTV0Ly7iLy++x0f3GMqdL1Tw8b2HMWS7UkqKi1hXU0uxxMwFqxBi9+23Q2reMs23rS7IbK0cZMy2XtW1dZQUqdkX5qq11Vx5/wyeeWspsxd+QPmAnnzpyJ0Yu0NfZry/il3K+nDLs+8w6eV5lA/oScWyNUz6t8PpVlzED+99ncN2HszA3t349p3T6NGtiEe/9REen7WIx95YxKDe3Xl05iIWrlpLv57d2GVIH56cvYRvfmxXZi38oM1VyfPlpL2HcfRuZfzHHa9sUv4Jh+7I2YeNYuec1SUqq2pYuHId2/Uo4buTprP70O244Ngxm3R+B5l2cpAx67wigoplaygf0LNgf7nX1gXzV6yhfEAvIoJrH3uLe16ex2vzVzaaUXfkmMHsNLg3Hx07lKWrq6iL4NGZi/jswTvyvw+9wbrqOn43YRyf//1zDO5TysfGDuHxWYv5xD478LPJM3ljQbZ+3k5lvXlr0eq8lX+XIX34zkl78OjMRQ33aPXuXszqqlpO2nsYv/7sAZt0XgeZdnKQMbONFRG8+t5K9hrel4pla3i5Yjkn77NDXs69pqqWT139JDPeb3zf05FjBjeME3UvLuIX4/fjq398Achm7/37cbuyvLKaR2Yu5NGZi9p1raN3K+PGcw7apHJulbPLzMy6AkkNA/4jBvZixMBeeTt3z+7F3H/hUaytruX2qe/ymYNG0i2tQPHe8jVU1dQxenBvAP70xYOpCzhizOCG/BMOG8XUuUuZ/NoCXnx3OR+srWHEwJ6M/9BI/jjlbf7x+sKGY7sX6EGAbsnkcEvGzLYVdXXBE7MX86FRA/jVw7M569AdG27U3VhuyZiZWSNFReLDu2br7V10wu6Fu07BzmxmZts8BxkzMysYBxkzMysYBxkzMysYBxkzMysYBxkzMysYBxkzMysYBxkzMysY3/GfQ9Ii4O3NOMVgmjzeeRuwrdV5W6svuM7bis2p844RUdbSDgeZPJI0dUNLK3RV21qdt7X6guu8rShUnd1dZmZmBeMgY2ZmBeMgk1/XdXQBOsC2Vudtrb7gOm8rClJnj8mYmVnBuCVjZmYF4yBjZmYF4yCTB5JOkDRT0mxJF3d0efJF0ghJj0h6XdJ0SV9P6QMlTZY0K/0ckJNnYvocZko6vuNKv+kkFUt6UdLf0vsuXV8ASf0l3SFpRvr3PrQr11vSN9Lv9KuSbpHUoyvWV9INkhZKejUnbaPrKelASdPSvqskqd2FiAi/NuMFFANvAjsB3YGXgbEdXa481W0YcEDa3g54AxgL/Bi4OKVfDFyZtsem+pcCo9PnUtzR9diEen8T+BPwt/S+S9c31eUm4ItpuzvQv6vWGxgOzAF6pve3A5/vivUFjgIOAF7NSdvoegLPAocCAu4DTmxvGdyS2XwHAbMj4q2IqAJuBU7p4DLlRUTMj4gX0vYq4HWy/6CnkH0pkX6emrZPAW6NiHURMQeYTfb5dBqSyoGTgN/lJHfZ+gJI6kv2ZXQ9QERURcRyuna9S4CekkqAXsA8umB9I+JxYGmT5I2qp6RhQN+IeDqyiPOHnDxtcpDZfMOBd3PeV6S0LkXSKGB/YAowNCLmQxaIgCHpsK7wWfwCuAioy0nryvWFrBW+CPh96ib8naTedNF6R8R7wE+Bd4D5wIqIeJAuWt8WbGw9h6ftpunt4iCz+Vrqm+xS88Il9QHuBC6MiJWtHdpCWqf5LCSdDCyMiOfbm6WFtE5T3xwlZF0q10TE/sBqsm6UDenU9U5jEKeQdQntAPSW9LnWsrSQ1mnquxE2VM/Nqr+DzOarAEbkvC8na3p3CZK6kQWYP0bEXSl5QWpCk34uTOmd/bM4HPikpLlk3Z7HSPo/um5961UAFRExJb2/gyzodNV6fxSYExGLIqIauAs4jK5b36Y2tp4Vabtpers4yGy+54AxkkZL6g6MByZ1cJnyIs0guR54PSJ+lrNrEjAhbU8A7s5JHy+pVNJoYAzZgGGnEBETI6I8IkaR/Ts+HBGfo4vWt15EvA+8K2m3lHQs8Bpdt97vAIdI6pV+x48lG2/sqvVtaqPqmbrUVkk6JH1eZ+fkaVtHz37oCi/g42Qzr94ELuno8uSxXkeQNYtfAV5Kr48Dg4CHgFnp58CcPJekz2EmGzEDZWt7AUezfnbZtlDf/YCp6d/6r8CArlxv4HvADOBV4GayGVVdrr7ALWTjTtVkLZJzN6WewLj0Wb0J/Iq0Wkx7Xl5WxszMCsbdZWZmVjAOMmZmVjAOMmZmVjAOMmZmVjAOMmZmVjAOMtZpSXpU0rgtcJ2vpZWJ/7iJ+W+UdHoL6UfXr/S8Eefa5DpLGpW7Gm++pfocVqjzb6wNfe62ZZV0dAHMOoKkkoioaefhXyW7Z2BOIcvUBRwNfAA8lc+TphsAFRF1bR5sWx23ZKyg0l/Pr0v6bXp+x4OSeqZ9DX+VSxqclnNB0ucl/VXSPZLmSPo3Sd9Mizc+I2lgziU+J+mp9FyQg1L+3uk5Gs+lPKfknPfPku4BHmyhrN9M53lV0oUp7VqyBSQnSfpGC3V7QtIL6XVYSpekX0l6TdLfWb8AYf2zh2ZI+idwWk76hsrcU9Ktkl6RdBvQcwOf84GSHpP0vKQHcpYNOVDSy5KeBs7POb6XpNvrzytpSs6/xXGSnk51+rOyteuQdEWq0yuSftr0swC+DHxD0kuSjpS0o6SH0vEPSRrZQrnLlD3T5AVJv5H0dvpdqP+9uRp4ARgh6RpJU9Pv0fdyzjFX0pWSnk2vXXIucVT6/XjLrZoO0tF3pPrVtV/AKKAG2C+9vx34XNp+FBiXtgcDc9P258mWGd8OKANWAF9O+35OtlBnff7fpu2jSM/MAH6Yc43+ZKsx9E7nrSDnDuecch4ITEvH9QGmA/unfXOBwS3k6QX0SNtjgKlp+zRgMtmzhnYAlgOnAz3IVrkdQ7bo4O2sX1VgQ2X+JnBDSt8nfZbjmpSjG1nroSy9PzMnzyvAh9P2T3I+o28Bv0nbe9WfN/07PA70Tvu+DXwXGEh2F3j9Ddz9W/g8LgO+lfP+HmBC2v4C8NcW8vwKmJi2TyBbYWIw2e9NHXBIzrED08/i9G+/T86/zyVp++ycz/RG4M9kf0yPJXskR4f/n9jWXm7J2JYwJyJeStvPk32BtOWRiFgVEYvIgsw9KX1ak/y3QMNzM/pK6g8cB1ws6SWyL6MeQP1f0ZMjounzNSBbQucvEbE6Ij4gWzTxyDbK2A34raRpZF9mY1P6UcAtEVEbEfOAh1P67mSfxazIvgX/L+dcGyrzUfXHRcQrZEGjqd3IAsXklP87QLmkfmTB4LF03M1N6ntrOu+rOec9JNXjyXSuCcCOwEpgLfA7SacBlW18NpA95OpPOdc+ooVjcstxP7AsZ9/bEfFMzvtPS3oBeBHYk/WfN6Tfg/Tz0Jz0v0ZEXUS8BgxtR5ktzzwmY1vCupztWtZ3+dSwvsu2Ryt56nLe19H497bpukj1S5P/S0TMzN0h6WCyZexb0v7Hya73DWABsC9ZPda2Uq620jdU5tby5OadHhGHNkrMAm5r19tQ+uSI+EyzHVl35LFki4f+G3BMG+VqqqWytPa5N/xbKVuw8VvAhyJimaQbafw7ExvYzv092pR/Y9tMbslYR5pL1k0FWXfSpjgTQNIRZA+fWgE8AFyg9A0taf92nOdx4NQ0VtEb+BTwRBt5+gHzIxuQPousG6f+XOMlFaexkY+k9BnAaEk7p/e5X+QbKvPjwGdT2l5kXWZNzQTKJB2ajusmac/Inm65In021J8n+Sfw6XT8WGDvlP4McHj9uEb6PHZN4zL9IuJe4EKyBTWbWkXWxVnvKbKAVH/tf7aQJ7ccx5EtzNmSvmRBZ4WkocCJTfafmfPz6Q2cwzqAWzLWkX4K3C7pLNZ3KW2sZZKeIvsS+kJK+wHZEy5fSV/ac4GTWztJRLyQ/jquX8L9dxHxYhvXvhq4U9IZwCOs/8v7L2R/5U8jG1t5LF1jraTzgL9LWkz2BbtXG2W+huyJlfUrYTdbYj4iqtKg9lWpi6wknWs6cA5wg6RKskCWW/ab0nlfJOsuWxERiyR9HrhFUmk69jtkAeRuST3IWgSNJkEk9wB3pEkLFwBfS9f+D7Inb57TQp7vpWudmT6n+elafZrU8WVJL6Y6vQU82eQ8pZKmkP3h3KwVZh3HqzCbbYMkFQPdUuDbmWzJ910jomoLl6MUqI2ImtQSuyYi9tvIc8wlmwyxuABFtM3klozZtqkX8IiyJ58K+MqWDjDJSLLWbBFQBXypA8pgBeSWjJmZFYwH/s3MrGAcZMzMrGAcZMzMrGAcZMzMrGAcZMzMrGD+P44NqCqac87IAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(f3_mean)\n",
    "plt.xlabel('number of added edges to graph');plt.ylabel('fixation time_r3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[147452.17535545025,\n",
       " 142917.96208530807,\n",
       " 96202.44549763034,\n",
       " 87916.69483568076,\n",
       " 79623.74509803922,\n",
       " 75270.38888888889,\n",
       " 75305.10328638498,\n",
       " 75436.69035532995,\n",
       " 62349.18348623853,\n",
       " 60994.01442307692,\n",
       " 57998.692307692305,\n",
       " 57737.586854460096,\n",
       " 58640.89175257732,\n",
       " 57556.8064516129,\n",
       " 57201.53431372549,\n",
       " 56029.99033816425,\n",
       " 55909.44041450777,\n",
       " 52682.65048543689,\n",
       " 51462.78217821782,\n",
       " 50855.08571428571,\n",
       " 52621.97129186603,\n",
       " 51277.83084577115,\n",
       " 49391.17840375587,\n",
       " 48741.0,\n",
       " 48259.70506912442,\n",
       " 47992.45327102804,\n",
       " 46502.28217821782,\n",
       " 44715.08571428571,\n",
       " 45746.58823529412,\n",
       " 45236.60368663594,\n",
       " 45120.98484848485,\n",
       " 44641.11009174312,\n",
       " 44095.93969849246,\n",
       " 44216.42639593909,\n",
       " 43477.12182741117,\n",
       " 43548.14027149321,\n",
       " 43287.89705882353,\n",
       " 44095.96860986547,\n",
       " 43384.293023255814,\n",
       " 42964.41176470588,\n",
       " 43943.05641025641,\n",
       " 42421.58293838862,\n",
       " 42873.92270531401,\n",
       " 42203.60091743119,\n",
       " 42405.51256281407,\n",
       " 42527.30275229358,\n",
       " 42533.64179104478,\n",
       " 41364.63981042654,\n",
       " 42138.42788461538,\n",
       " 41754.87614678899,\n",
       " 41518.10344827586,\n",
       " 42025.58762886598,\n",
       " 41626.16113744076,\n",
       " 41008.739130434784,\n",
       " 41804.41747572816,\n",
       " 40737.354368932036,\n",
       " 39497.90306122449,\n",
       " 39146.40182648402,\n",
       " 39232.41981132075,\n",
       " 38992.20952380952,\n",
       " 38387.11961722488,\n",
       " 39294.362790697676,\n",
       " 38106.93908629441,\n",
       " 38444.36842105263,\n",
       " 37755.10837438424,\n",
       " 37339.394230769234,\n",
       " 37881.05940594059,\n",
       " 37488.53299492386,\n",
       " 38005.029411764706,\n",
       " 37617.31746031746,\n",
       " 37484.55348837209,\n",
       " 37754.67289719626,\n",
       " 37024.474178403754,\n",
       " 35787.46700507614,\n",
       " 36296.251184834124,\n",
       " 36003.91428571429,\n",
       " 35431.03553299492,\n",
       " 35702.75862068965,\n",
       " 36014.56807511737,\n",
       " 35398.852040816324,\n",
       " 34002.98591549296,\n",
       " 34472.118226600986,\n",
       " 34383.07109004739,\n",
       " 34486.142857142855,\n",
       " 33667.97607655502,\n",
       " 33582.063725490196,\n",
       " 33913.47263681592,\n",
       " 33784.37373737374,\n",
       " 32587.1164021164,\n",
       " 32404.587677725118,\n",
       " 33695.88262910798,\n",
       " 33793.358744394616,\n",
       " 33207.013824884794,\n",
       " 32615.51690821256,\n",
       " 32727.094527363184,\n",
       " 32640.78391959799,\n",
       " 31858.049019607843,\n",
       " 33015.30927835051,\n",
       " 32007.039408866996,\n",
       " 32114.353233830847,\n",
       " 32515.130841121496,\n",
       " 32221.572093023256,\n",
       " 32185.206572769952,\n",
       " 31854.354066985645,\n",
       " 32291.915492957745,\n",
       " 31857.925742574258,\n",
       " 31803.454106280195,\n",
       " 31552.22380952381,\n",
       " 31506.234146341463,\n",
       " 31855.46818181818,\n",
       " 31706.595,\n",
       " 32339.480952380953,\n",
       " 31623.518348623853,\n",
       " 31215.738095238095,\n",
       " 31522.938095238096,\n",
       " 30714.701570680627,\n",
       " 31243.062801932367,\n",
       " 30731.430693069306,\n",
       " 30974.131707317072,\n",
       " 31445.78672985782,\n",
       " 31152.8078817734,\n",
       " 32139.746268656716,\n",
       " 31312.892156862745,\n",
       " 31135.059113300493,\n",
       " 30964.331818181818,\n",
       " 31316.015625,\n",
       " 30957.78341013825,\n",
       " 30244.018348623853,\n",
       " 30807.824390243903,\n",
       " 30843.164383561645,\n",
       " 30687.61951219512,\n",
       " 30772.17910447761,\n",
       " 30364.953846153847,\n",
       " 31401.66964285714,\n",
       " 30074.283018867925,\n",
       " 30072.219047619048,\n",
       " 30006.256281407033,\n",
       " 29731.141463414635,\n",
       " 30232.55023923445,\n",
       " 30300.6018957346,\n",
       " 29971.861386138615,\n",
       " 29370.140096618357,\n",
       " 29658.845794392524,\n",
       " 29646.831683168315,\n",
       " 28979.531100478467,\n",
       " 29268.480952380953,\n",
       " 28987.895,\n",
       " 29394.014084507042,\n",
       " 28432.121827411167,\n",
       " 29046.04954954955,\n",
       " 28575.903846153848,\n",
       " 28995.072463768116,\n",
       " 29201.616822429907,\n",
       " 28009.264423076922,\n",
       " 28979.428571428572,\n",
       " 28116.4,\n",
       " 29757.153110047846,\n",
       " 29165.623853211007,\n",
       " 28370.48275862069,\n",
       " 28368.572115384617,\n",
       " 27523.281914893618,\n",
       " 28212.75,\n",
       " 27736.51776649746,\n",
       " 27485.748768472906,\n",
       " 27365.295,\n",
       " 27525.731343283584,\n",
       " 27645.601990049752,\n",
       " 27534.614285714284,\n",
       " 27841.848484848484,\n",
       " 27622.489361702126,\n",
       " 27860.66346153846,\n",
       " 27165.919786096256,\n",
       " 27468.485294117647,\n",
       " 27027.08173076923,\n",
       " 27192.365,\n",
       " 28014.361809045226,\n",
       " 26561.023255813954,\n",
       " 27432.757009345794,\n",
       " 26642.124378109453,\n",
       " 26448.420792079207,\n",
       " 27444.79146919431,\n",
       " 27040.535,\n",
       " 26898.247572815533,\n",
       " 27176.5,\n",
       " 27395.131221719457,\n",
       " 26426.203125,\n",
       " 27375.72380952381,\n",
       " 26736.984848484848,\n",
       " 27205.867346938776,\n",
       " 25894.11374407583,\n",
       " 26269.445,\n",
       " 26001.43203883495,\n",
       " 25539.13,\n",
       " 27321.52606635071,\n",
       " 25830.85436893204,\n",
       " 26137.10824742268,\n",
       " 26367.330188679247,\n",
       " 26309.80751173709,\n",
       " 25808.18536585366,\n",
       " 25841.6,\n",
       " 25867.48181818182,\n",
       " 25320.063725490196,\n",
       " 26261.10138248848,\n",
       " 25673.62,\n",
       " 25279.351485148516,\n",
       " 25288.54773869347,\n",
       " 26365.906403940888,\n",
       " 26004.815384615384,\n",
       " 26377.151515151516,\n",
       " 26214.598086124402,\n",
       " 25322.3133640553,\n",
       " 25193.431472081218,\n",
       " 25301.36842105263,\n",
       " 25860.781553398057,\n",
       " 25417.306976744185,\n",
       " 25065.384615384617,\n",
       " 24982.19387755102,\n",
       " 25358.4776119403,\n",
       " 25433.11,\n",
       " 25634.855072463768,\n",
       " 25765.004926108373,\n",
       " 25635.811320754718,\n",
       " 25635.143540669855,\n",
       " 26243.898550724636,\n",
       " 25941.286384976527,\n",
       " 25670.57476635514,\n",
       " 25364.06796116505,\n",
       " 25768.626865671642,\n",
       " 23935.746192893403,\n",
       " 24856.649746192892,\n",
       " 25376.128205128207,\n",
       " 25567.725,\n",
       " 25488.611650485436,\n",
       " 25476.3631840796,\n",
       " 25453.492822966506,\n",
       " 24923.50234741784,\n",
       " 25343.82125603865,\n",
       " 25463.910447761195,\n",
       " 24665.65024630542,\n",
       " 24971.32057416268,\n",
       " 24831.154639175256,\n",
       " 24469.277777777777,\n",
       " 24395.980392156864,\n",
       " 24604.46907216495,\n",
       " 25155.914285714287,\n",
       " 25577.121827411167,\n",
       " 25195.721698113208,\n",
       " 24475.33823529412,\n",
       " 24756.58549222798,\n",
       " 24281.353233830847,\n",
       " 25153.83769633508,\n",
       " 25264.546341463414,\n",
       " 24418.81818181818,\n",
       " 25145.47263681592,\n",
       " 24947.225490196077,\n",
       " 25311.85714285714,\n",
       " 24618.304347826088,\n",
       " 25073.838541666668,\n",
       " 24226.645161290322,\n",
       " 23965.825,\n",
       " 24664.93301435407,\n",
       " 24057.686274509804,\n",
       " 24656.0625,\n",
       " 24176.444444444445,\n",
       " 24619.52380952381,\n",
       " 24004.167441860463,\n",
       " 24573.242105263158,\n",
       " 24358.68075117371,\n",
       " 23613.79203539823,\n",
       " 24007.871134020617,\n",
       " 24044.381188118812,\n",
       " 24534.039408866996,\n",
       " 24441.995283018867,\n",
       " 24051.169082125605,\n",
       " 24461.259615384617,\n",
       " 24236.266009852217,\n",
       " 24657.087378640776,\n",
       " 23924.209677419356,\n",
       " 24657.44600938967,\n",
       " 24503.033492822968,\n",
       " 24352.26767676768,\n",
       " 24263.61274509804,\n",
       " 25202.741293532337,\n",
       " 24605.018691588786,\n",
       " 24144.061855670105,\n",
       " 24760.920930232558,\n",
       " 23136.025510204083,\n",
       " 24254.154639175256,\n",
       " 24952.140845070422,\n",
       " 24111.10606060606,\n",
       " 24231.08173076923,\n",
       " 22707.745,\n",
       " 24059.902564102566,\n",
       " 23844.146226415094,\n",
       " 23828.73113207547,\n",
       " 24324.175,\n",
       " 25079.58910891089,\n",
       " 24402.326424870465,\n",
       " 24408.5175879397,\n",
       " 24577.47596153846,\n",
       " 23960.85714285714,\n",
       " 24210.325,\n",
       " 24350.927184466018,\n",
       " 24608.99526066351,\n",
       " 24569.15736040609,\n",
       " 24324.0,\n",
       " 24284.82843137255,\n",
       " 24023.509523809524,\n",
       " 24399.351485148516,\n",
       " 23793.12254901961,\n",
       " 23924.174757281555,\n",
       " 23932.406862745098,\n",
       " 23079.5,\n",
       " 23531.31308411215,\n",
       " 23335.333333333332,\n",
       " 23779.71497584541,\n",
       " 23778.930348258706,\n",
       " 23903.456989247312,\n",
       " 23106.668393782384,\n",
       " 23381.79891304348,\n",
       " 23225.871287128713,\n",
       " 23678.831775700935,\n",
       " 23882.47263681592,\n",
       " 23581.0,\n",
       " 24127.520833333332,\n",
       " 23677.882653061224,\n",
       " 24562.81603773585,\n",
       " 23343.984771573603,\n",
       " 23916.6358974359,\n",
       " 23839.124423963134,\n",
       " 23516.55238095238,\n",
       " 23290.20297029703,\n",
       " 23860.185,\n",
       " 23001.578680203045,\n",
       " 23797.60476190476,\n",
       " 23472.567708333332,\n",
       " 24066.20634920635,\n",
       " 24223.50505050505,\n",
       " 23857.238805970148,\n",
       " 23472.333333333332,\n",
       " 24680.82380952381,\n",
       " 24266.843434343435,\n",
       " 23891.79716981132,\n",
       " 23056.95673076923,\n",
       " 22801.613526570047,\n",
       " 24223.730964467006,\n",
       " 24033.015,\n",
       " 24402.08530805687,\n",
       " 23727.94581280788,\n",
       " 23555.863849765257,\n",
       " 23503.158653846152,\n",
       " 23445.156565656565,\n",
       " 24017.44976076555,\n",
       " 23444.646766169153,\n",
       " 23026.704225352114,\n",
       " 23325.177033492822,\n",
       " 23653.051643192488,\n",
       " 23930.359375,\n",
       " 23449.813829787236,\n",
       " 23366.92924528302,\n",
       " 23285.725806451614,\n",
       " 23625.663366336634,\n",
       " 24020.585365853658,\n",
       " 23693.60101010101,\n",
       " 23692.918367346938,\n",
       " 23907.746268656716,\n",
       " 23711.696969696968,\n",
       " 23395.257142857143,\n",
       " 23060.197916666668,\n",
       " 23710.848484848484,\n",
       " 23435.748792270533,\n",
       " 22321.848958333332,\n",
       " 23204.25806451613,\n",
       " 22872.316326530614,\n",
       " 22851.641791044774,\n",
       " 22215.967441860466,\n",
       " 23770.0,\n",
       " 23316.950980392157,\n",
       " 23463.29591836735,\n",
       " 22863.88780487805,\n",
       " 22724.487562189053,\n",
       " 23612.271844660194,\n",
       " 22250.247524752474,\n",
       " 22559.769585253456,\n",
       " 23062.3184079602,\n",
       " 22982.004784688994,\n",
       " 21852.66515837104,\n",
       " 22900.94527363184,\n",
       " 23007.60696517413,\n",
       " 22413.385416666668,\n",
       " 22581.594202898552,\n",
       " 22499.047846889953,\n",
       " 22481.079601990048,\n",
       " 22566.572815533982,\n",
       " 22207.61650485437,\n",
       " 22548.160975609757,\n",
       " 22357.857843137255,\n",
       " 21814.839024390243,\n",
       " 22195.75376884422,\n",
       " 21817.440594059404,\n",
       " 21930.03317535545,\n",
       " 22195.39719626168,\n",
       " 22212.268292682926,\n",
       " 22161.70616113744,\n",
       " 22455.276699029127,\n",
       " 22312.094786729856,\n",
       " 22701.88780487805,\n",
       " 23341.990476190476,\n",
       " 22273.0,\n",
       " 22678.202898550724,\n",
       " 23404.236714975847,\n",
       " 23059.28502415459,\n",
       " 22758.171717171717,\n",
       " 22452.03092783505,\n",
       " 22439.243781094527,\n",
       " 22437.549295774646,\n",
       " 22481.12626262626,\n",
       " 22136.63157894737,\n",
       " 21495.244019138758,\n",
       " 22400.180555555555,\n",
       " 22474.65581395349,\n",
       " 22340.624390243902,\n",
       " 22271.068965517243,\n",
       " 22202.89393939394,\n",
       " 22534.39893617021,\n",
       " 22510.98514851485,\n",
       " 22701.825870646768,\n",
       " 21970.980487804878,\n",
       " 22228.268656716416,\n",
       " 22648.695,\n",
       " 22959.072538860102,\n",
       " 22378.158163265307,\n",
       " 23008.32338308458,\n",
       " 22421.3981042654,\n",
       " 22014.72857142857,\n",
       " 22640.383838383837,\n",
       " 21934.48275862069,\n",
       " 22439.607655502394,\n",
       " 21316.963157894737,\n",
       " 22584.811881188118,\n",
       " 22326.31067961165,\n",
       " 21952.67757009346,\n",
       " 22135.09375,\n",
       " 22017.425,\n",
       " 21930.71782178218,\n",
       " 22501.094786729856,\n",
       " 21893.23786407767,\n",
       " 22503.351485148516,\n",
       " 22085.94660194175,\n",
       " 21756.48598130841,\n",
       " 21376.780612244896,\n",
       " 20742.682926829268,\n",
       " 22886.764423076922,\n",
       " 21587.336633663366,\n",
       " 22470.859296482413,\n",
       " 21483.58962264151,\n",
       " 21482.383177570093,\n",
       " 21492.402985074626,\n",
       " 21651.65071770335,\n",
       " 21205.995145631066,\n",
       " 22565.407960199005,\n",
       " 22532.48113207547,\n",
       " 23167.616822429907,\n",
       " 21956.193717277485,\n",
       " 21404.295566502464,\n",
       " 21885.066326530614,\n",
       " 22352.348039215685,\n",
       " 21547.54106280193,\n",
       " 21119.740384615383,\n",
       " 21521.843434343435,\n",
       " 21243.917050691245,\n",
       " 21365.190476190477,\n",
       " 21075.3981042654,\n",
       " 21316.953846153847,\n",
       " 20674.985849056604,\n",
       " 21683.76388888889,\n",
       " 21398.471962616823,\n",
       " 21051.306976744185,\n",
       " 21227.4,\n",
       " 20979.439393939392,\n",
       " 21085.671497584543,\n",
       " 20728.397959183672,\n",
       " 21211.905660377357,\n",
       " 21142.31553398058,\n",
       " 21710.923423423425,\n",
       " 20314.716346153848,\n",
       " 21352.56783919598,\n",
       " 21847.881188118812,\n",
       " 20878.14285714286,\n",
       " 21765.4797979798,\n",
       " 21517.415,\n",
       " 21632.29797979798,\n",
       " 21333.772277227723,\n",
       " 21414.553921568626,\n",
       " 21161.28205128205,\n",
       " 21271.17948717949,\n",
       " 19664.183098591548,\n",
       " 21363.459821428572,\n",
       " 20387.493023255814,\n",
       " 20549.80769230769,\n",
       " 21013.075757575756,\n",
       " 21147.542056074766,\n",
       " 20529.41904761905,\n",
       " 21351.145728643216,\n",
       " 21894.256157635467,\n",
       " 20902.881818181817,\n",
       " 21248.32512315271,\n",
       " 22215.413265306124,\n",
       " 21804.11214953271,\n",
       " 21542.29081632653,\n",
       " 21580.180904522615,\n",
       " 20797.97512437811,\n",
       " 21411.562814070352,\n",
       " 20515.720930232557,\n",
       " 20901.217391304348,\n",
       " 20870.866972477063,\n",
       " 22344.952631578948,\n",
       " 21795.460396039605,\n",
       " 22294.108374384236,\n",
       " 21229.188118811882,\n",
       " 20349.963133640555,\n",
       " 20625.0206185567,\n",
       " 21162.263414634148,\n",
       " 21398.46192893401,\n",
       " 20544.70616113744,\n",
       " 21484.360576923078,\n",
       " 20942.854922279792,\n",
       " 20026.067357512955,\n",
       " 21769.68544600939,\n",
       " 20810.11707317073,\n",
       " 20163.926829268294,\n",
       " 20804.347619047618,\n",
       " 20709.164102564104,\n",
       " 21445.534562211982,\n",
       " 21284.05213270142,\n",
       " 21339.09661835749,\n",
       " 20852.82564102564,\n",
       " 20405.846534653465,\n",
       " 20615.463414634145,\n",
       " 20617.19523809524,\n",
       " 21319.960199004974,\n",
       " 22125.502590673575,\n",
       " 21015.385416666668,\n",
       " 20480.839805825242,\n",
       " 20462.47474747475,\n",
       " 21408.81463414634,\n",
       " 20617.952153110047,\n",
       " 20982.424731182797,\n",
       " 20966.04433497537,\n",
       " 20802.424528301886,\n",
       " 20616.24226804124,\n",
       " 21782.859903381643,\n",
       " 21172.56862745098,\n",
       " 20328.221153846152,\n",
       " 20618.44549763033,\n",
       " 20480.18407960199,\n",
       " 20319.323529411766,\n",
       " 20549.5,\n",
       " 21294.986175115206,\n",
       " 22637.6,\n",
       " 21621.17,\n",
       " 20970.13,\n",
       " 20491.06334841629,\n",
       " 20996.478494623654,\n",
       " 21038.924170616112,\n",
       " 21251.712765957447,\n",
       " 20568.056872037916,\n",
       " 21074.369158878504,\n",
       " 20055.752427184467,\n",
       " 20235.635922330097,\n",
       " 20991.487684729065,\n",
       " 20583.79695431472,\n",
       " 21209.643902439024,\n",
       " 20621.618090452263,\n",
       " 21680.835680751174,\n",
       " 20463.39512195122,\n",
       " 21111.72864321608,\n",
       " 21069.109004739337,\n",
       " 20330.634146341465,\n",
       " 20935.980487804878,\n",
       " 20089.779411764706,\n",
       " 20784.113989637306,\n",
       " 20165.24742268041,\n",
       " 21357.486910994765,\n",
       " 21000.212962962964,\n",
       " 20376.02427184466,\n",
       " 21238.752525252527,\n",
       " 21216.543689320388,\n",
       " 20379.769607843136,\n",
       " 20274.704761904763,\n",
       " 21113.805970149253,\n",
       " 20409.23618090452,\n",
       " 19861.305263157894,\n",
       " 20995.85576923077,\n",
       " 20151.0,\n",
       " 20017.27536231884,\n",
       " 20889.377880184333,\n",
       " 22276.08040201005,\n",
       " 20090.877551020407,\n",
       " 21764.199029126212,\n",
       " 19884.1164021164,\n",
       " 21052.903553299493,\n",
       " 20373.049261083743,\n",
       " 22010.14358974359,\n",
       " 20822.42654028436,\n",
       " 21955.62254901961,\n",
       " 19771.302752293577,\n",
       " 20593.815384615384,\n",
       " 21104.56157635468,\n",
       " 20760.38785046729,\n",
       " 21290.725,\n",
       " 21419.985436893203,\n",
       " 22055.82722513089,\n",
       " 19598.927184466018,\n",
       " 19064.83408071749,\n",
       " 19638.090425531915,\n",
       " 19981.038834951458,\n",
       " 19336.51530612245,\n",
       " 19297.91089108911,\n",
       " 18628.13775510204,\n",
       " 18922.91904761905,\n",
       " 19371.039800995026,\n",
       " 19246.064516129034,\n",
       " 18842.076923076922,\n",
       " 19661.995,\n",
       " 18952.119791666668,\n",
       " 19001.374384236453,\n",
       " 19343.369791666668,\n",
       " 19943.683060109288,\n",
       " 19450.616161616163,\n",
       " 19847.125603864733,\n",
       " 19180.043062200955,\n",
       " 18677.622448979593,\n",
       " 19738.303482587064,\n",
       " 18584.07981220657,\n",
       " 19271.195,\n",
       " 19485.28804347826,\n",
       " 18442.38349514563,\n",
       " 19666.901041666668,\n",
       " 19175.443349753696,\n",
       " 19090.31527093596,\n",
       " 18604.572916666668,\n",
       " 19207.523076923077,\n",
       " 18710.410256410258,\n",
       " 19023.84263959391,\n",
       " 19598.666666666668,\n",
       " 17981.646464646463,\n",
       " 18912.01388888889,\n",
       " 19039.821782178216,\n",
       " 19755.01463414634,\n",
       " 18515.973958333332,\n",
       " 19121.528205128205,\n",
       " 18965.114285714284,\n",
       " 18674.803921568626,\n",
       " 18842.302564102563,\n",
       " 18522.83243243243,\n",
       " 18041.147959183672,\n",
       " 18513.08695652174,\n",
       " 19304.68137254902,\n",
       " 18485.071794871794,\n",
       " 18503.484444444446,\n",
       " 18303.037914691944,\n",
       " 18337.582474226805,\n",
       " 19375.244791666668,\n",
       " 19372.035532994923,\n",
       " 17752.639423076922,\n",
       " 17594.87434554974,\n",
       " 17693.399061032866,\n",
       " 18325.147959183672,\n",
       " 17948.47,\n",
       " 17699.572972972972,\n",
       " 17365.82857142857,\n",
       " 18361.31313131313,\n",
       " 18431.02380952381,\n",
       " 17996.04109589041,\n",
       " 17990.126829268294,\n",
       " 18145.5,\n",
       " 18398.29756097561,\n",
       " 18859.268656716416,\n",
       " 17969.605633802817,\n",
       " 18002.330275229357,\n",
       " 19085.0,\n",
       " 17794.889473684212,\n",
       " 18901.065989847717,\n",
       " 18118.14351851852,\n",
       " 17506.54081632653,\n",
       " 18848.602150537634,\n",
       " 18630.660194174758,\n",
       " 18218.155660377357,\n",
       " 18246.869791666668,\n",
       " 17381.835051546394,\n",
       " 17607.107317073172,\n",
       " 18840.8995215311,\n",
       " 17874.953125,\n",
       " 18394.108374384236,\n",
       " 17705.698412698413,\n",
       " 18422.641791044774,\n",
       " 18496.333333333332,\n",
       " 18025.407582938387,\n",
       " 18490.26633165829,\n",
       " 17418.014285714286,\n",
       " 17746.700483091787,\n",
       " 17969.477272727272,\n",
       " 18031.026315789473,\n",
       " 17718.685990338163,\n",
       " 17286.243902439026,\n",
       " 18107.717391304348,\n",
       " 17826.52195121951,\n",
       " 17831.617647058825,\n",
       " 18239.175879396986,\n",
       " 17578.47572815534,\n",
       " 17858.16230366492,\n",
       " 17323.43269230769,\n",
       " 17137.052884615383,\n",
       " 17491.75647668394,\n",
       " 17560.861386138615,\n",
       " 17956.87019230769,\n",
       " 17785.845,\n",
       " 17574.14150943396,\n",
       " 18237.68181818182,\n",
       " 18203.433497536946,\n",
       " 17762.20895522388,\n",
       " 17424.048076923078,\n",
       " 18046.430051813473,\n",
       " 18113.78350515464,\n",
       " 18458.613402061856,\n",
       " 17544.463541666668,\n",
       " 18279.336585365854,\n",
       " 17649.97,\n",
       " 17952.289215686276,\n",
       " 17799.764705882353,\n",
       " 18598.10714285714,\n",
       " 17869.096153846152,\n",
       " 17720.515151515152,\n",
       " 18088.777777777777,\n",
       " 16719.968421052632,\n",
       " 16904.216346153848,\n",
       " 17197.707692307693,\n",
       " 17028.674311926607,\n",
       " 17387.106976744188,\n",
       " 16637.23181818182,\n",
       " 16391.90594059406,\n",
       " 16413.70202020202,\n",
       " 17519.08133971292,\n",
       " 17725.529411764706,\n",
       " 16774.487562189053,\n",
       " 17279.331658291456,\n",
       " 17907.86069651741,\n",
       " 17017.907692307694,\n",
       " 16862.908212560385,\n",
       " 17564.09574468085,\n",
       " 17144.964646464647,\n",
       " 17091.49494949495,\n",
       " 17329.487684729065,\n",
       " 16962.0,\n",
       " 17201.89552238806,\n",
       " 16929.218274111674,\n",
       " 17137.900943396227,\n",
       " 17355.266666666666,\n",
       " 17022.34825870647,\n",
       " 17116.54066985646,\n",
       " 17093.418367346938,\n",
       " 17162.88613861386,\n",
       " 16594.218905472637,\n",
       " 17257.412621359224,\n",
       " 16792.31683168317,\n",
       " 16962.883838383837,\n",
       " 17532.49756097561,\n",
       " 17630.295566502464,\n",
       " 16666.190476190477,\n",
       " 17456.17,\n",
       " 16500.303482587064,\n",
       " 16984.35576923077,\n",
       " 17495.54314720812,\n",
       " 17964.88,\n",
       " 17589.17525773196,\n",
       " 18146.936274509804,\n",
       " 17309.5625,\n",
       " 17250.44549763033,\n",
       " 17005.132352941175,\n",
       " 18294.091370558377,\n",
       " 16726.52195121951,\n",
       " 16715.33510638298,\n",
       " 16949.726368159205,\n",
       " 16923.099056603773,\n",
       " 16967.40099009901,\n",
       " 17057.539603960395,\n",
       " 17503.396907216495,\n",
       " 17049.666666666668,\n",
       " 17385.009615384617,\n",
       " 16762.078534031414,\n",
       " 16866.1261682243,\n",
       " 16562.689814814814,\n",
       " 17483.578680203045,\n",
       " 16782.245098039217,\n",
       " 17175.82383419689,\n",
       " 17290.18009478673,\n",
       " 17234.856459330145,\n",
       " 17470.506976744186,\n",
       " 17098.6875,\n",
       " 17003.540404040403,\n",
       " 17685.473684210527,\n",
       " 17024.318840579712,\n",
       " 16762.143564356436,\n",
       " 17117.615763546797,\n",
       " 17147.285714285714,\n",
       " 16819.975,\n",
       " 17084.38164251208,\n",
       " 17374.696335078534,\n",
       " 16840.668341708544,\n",
       " 17049.923076923078,\n",
       " 16747.571428571428,\n",
       " 17071.445544554455,\n",
       " 17498.853260869564,\n",
       " 16643.119047619046,\n",
       " 17201.852791878173,\n",
       " 17807.729468599035,\n",
       " 16628.321243523314,\n",
       " 17605.280952380952,\n",
       " 17142.831632653062,\n",
       " 17094.670050761422,\n",
       " 17277.574879227053,\n",
       " 17187.417840375587,\n",
       " 16361.683673469388,\n",
       " 17985.279187817257,\n",
       " 17426.517073170733,\n",
       " 17680.88,\n",
       " 16845.30476190476,\n",
       " 17135.83653846154,\n",
       " 17585.995098039217,\n",
       " 16984.336492890994,\n",
       " 16936.28502415459,\n",
       " 16687.970297029704,\n",
       " 17230.60621761658,\n",
       " 16169.78,\n",
       " 16396.894472361808,\n",
       " 16271.51923076923,\n",
       " 16504.62895927602,\n",
       " 16330.88717948718,\n",
       " 16610.05339805825,\n",
       " 15640.848341232228,\n",
       " 16504.48514851485,\n",
       " 17129.214659685866,\n",
       " 16970.99043062201,\n",
       " 16070.942583732058,\n",
       " 15913.788659793814,\n",
       " 16455.81,\n",
       " 16419.841025641024,\n",
       " 15802.169902912621,\n",
       " 15511.463541666666,\n",
       " 16470.15025906736,\n",
       " 16089.539215686274,\n",
       " 16176.547738693467,\n",
       " 16906.98611111111,\n",
       " 16686.824120603014,\n",
       " 16046.604761904762,\n",
       " 16789.048309178743,\n",
       " 16475.20105820106,\n",
       " 16237.289099526066,\n",
       " 16787.47263681592,\n",
       " 16692.355450236966,\n",
       " 16310.612745098038,\n",
       " 16319.492753623188,\n",
       " 16264.538860103627,\n",
       " 16276.185567010309,\n",
       " 16271.990099009901,\n",
       " 16553.558974358974,\n",
       " 16568.835897435896,\n",
       " 17116.22966507177,\n",
       " 15987.738461538462,\n",
       " 17345.54716981132,\n",
       " 16907.030303030304,\n",
       " 17007.755,\n",
       " 16425.798076923078,\n",
       " 16273.934673366834,\n",
       " 16288.80193236715,\n",
       " 16213.995024875621,\n",
       " 17035.648514851484,\n",
       " 16000.586206896553,\n",
       " 17050.81094527363,\n",
       " 16232.157407407407,\n",
       " 16696.964467005077,\n",
       " 16531.50731707317,\n",
       " 16930.76818181818,\n",
       " 17218.562814070352,\n",
       " 16662.8115942029,\n",
       " 16217.059113300493,\n",
       " 16463.45728643216,\n",
       " 15888.192118226601,\n",
       " 16721.67757009346,\n",
       " 16792.015463917527,\n",
       " 16847.857868020306,\n",
       " 16989.193236714975,\n",
       " 16248.637254901962,\n",
       " 16833.184331797234,\n",
       " 16267.628712871287,\n",
       " 16017.081632653062,\n",
       " 16380.617647058823,\n",
       " 16481.66990291262,\n",
       " 16701.468599033815,\n",
       " 16895.76923076923,\n",
       " 16341.568720379148,\n",
       " 16038.20202020202,\n",
       " 15887.140625,\n",
       " 15966.232227488152,\n",
       " 16468.276699029127,\n",
       " 16209.464864864865,\n",
       " 16498.034146341462,\n",
       " 15864.257281553399,\n",
       " 15943.708737864077,\n",
       " 16224.633165829146,\n",
       " 16128.098591549297,\n",
       " 16317.333333333334,\n",
       " 16454.906403940888,\n",
       " 16287.253731343284,\n",
       " 16710.28426395939,\n",
       " 15255.725490196079,\n",
       " 15198.915343915343,\n",
       " 15353.623255813953,\n",
       " 15874.912621359223,\n",
       " 15930.142857142857,\n",
       " 15634.175,\n",
       " 14819.8,\n",
       " 15628.56,\n",
       " 15422.393034825871,\n",
       " 15598.914141414141,\n",
       " 16277.030769230769,\n",
       " 15468.14705882353,\n",
       " 15629.87,\n",
       " 15185.640776699029,\n",
       " 16077.521126760563,\n",
       " 15834.069892473119,\n",
       " 16516.57843137255,\n",
       " 15488.390374331551,\n",
       " 15757.245098039215,\n",
       " 15284.76119402985,\n",
       " 16296.567164179105,\n",
       " 14928.91133004926,\n",
       " 15733.668341708542,\n",
       " 16567.808510638297,\n",
       " 16077.784688995216,\n",
       " 15325.034482758621,\n",
       " 16253.073684210527,\n",
       " 15434.165876777251,\n",
       " 15999.746606334842,\n",
       " 16247.849765258215,\n",
       " 15827.6,\n",
       " 15957.766169154229,\n",
       " 15442.680628272252,\n",
       " 16018.929648241206,\n",
       " 14785.077319587628,\n",
       " 15893.092307692308,\n",
       " 15905.620689655172,\n",
       " 16270.725888324872,\n",
       " 15283.47572815534,\n",
       " 15214.0206185567,\n",
       " 15760.971291866028,\n",
       " 15869.38383838384,\n",
       " 16376.026178010472,\n",
       " 15648.740384615385,\n",
       " 15918.051643192488,\n",
       " 16390.75238095238,\n",
       " 15518.518518518518,\n",
       " 15551.74,\n",
       " 15860.330097087379,\n",
       " 15575.795918367347,\n",
       " 16240.966346153846,\n",
       " 15401.907692307692,\n",
       " 15811.573604060914,\n",
       " 16173.629441624365,\n",
       " 14764.722772277228,\n",
       " 15582.35294117647,\n",
       " 15596.636815920398,\n",
       " 15794.128078817734,\n",
       " 14639.07960199005,\n",
       " 15544.570707070707,\n",
       " 14987.851162790697,\n",
       " 15241.303482587065,\n",
       " 14822.572727272727,\n",
       " 15002.782407407407,\n",
       " 14631.342995169081,\n",
       " 14971.717592592593,\n",
       " 15011.024752475247,\n",
       " 15039.2,\n",
       " 15265.363636363636,\n",
       " 15194.113636363636,\n",
       " 14882.747368421053,\n",
       " 14810.537313432837,\n",
       " 15119.187165775402,\n",
       " 15438.928909952607,\n",
       " 15702.939086294416,\n",
       " 14244.93607305936,\n",
       " 14619.885416666666,\n",
       " 14428.278606965174,\n",
       " 14982.272300469484,\n",
       " 15320.903381642513,\n",
       " 15726.065326633166,\n",
       " 15385.301020408164,\n",
       " 14051.372448979591,\n",
       " 15985.921568627451]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f3_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "147452.17535545025"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f3_mean[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15985.921568627451"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f3_mean[999]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import arange\n",
    "from scipy.optimize import curve_fit\n",
    "plt.loglog(f_mean,'o-')\n",
    "popt,pcov=curve_fit(lambda x,c,a:c*x**(a),np.arange(0,1000)[5:],f_mean[5:])\n",
    "plt.plot(np.arange(0,1000)[5:],popt[0]*np.arange(0,1000)[5:]**(popt[1]))\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 1.23367235e+05, -2.89564564e-01]),\n",
       " array([[ 4.12333521e+05, -6.05236699e-01],\n",
       "        [-6.05236699e-01,  9.52383134e-07]]))"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popt,pcov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'fixation time-log_r3')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(f_mean,'ko-')\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "plt.xlabel('number of added edges to graph-log');plt.ylabel('fixation time-log_r3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "lastm_avg=[]\n",
    "for i in range (1000):\n",
    "    M_avg=np.loadtxt('M_avg'+str(i)+'.dat')\n",
    "    lastm_avg.append(M_avg[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'fixation probablity_r3')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(lastm_avg)\n",
    "plt.ylim(0,1)\n",
    "plt.xlabel('number of added edges to graph');plt.ylabel('fixation probablity_r3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import arange\n",
    "from scipy.optimize import curve_fit\n",
    "#plt.plot(lastm_avg)\n",
    "popt,pcov=curve_fit(lambda x,c,a:c*x**(a),np.arange(0,1000)[5:],lastm_avg[5:])\n",
    "plt.plot(np.arange(0,1000)[5:],popt[0]*np.arange(0,1000)[5:]**(popt[1]))\n",
    "plt.ylim(0,1)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.71199231, -0.00803381])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Mu=(np.sum(lastm_avg)/len(lastm_avg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6789833333333334"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Mu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aa=(lastm_avg-Mu)**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5.92922500e-04, 5.92922500e-04, 5.92922500e-04, 9.62033611e-04,\n",
       "       1.03361111e-06, 1.68236694e-03, 9.62033611e-04, 4.98033611e-04,\n",
       "       2.27370028e-03, 2.05922500e-04, 2.05922500e-04, 9.62033611e-04,\n",
       "       1.04436694e-03, 1.96692250e-03, 1.03361111e-06, 1.21366944e-04,\n",
       "       1.27092250e-03, 5.90336111e-05, 3.19225000e-05, 4.41700278e-04,\n",
       "       3.12700278e-04, 8.07002778e-05, 9.62033611e-04, 8.07002778e-05,\n",
       "       1.96692250e-03, 1.17992250e-03, 3.19225000e-05, 4.41700278e-04,\n",
       "       1.03361111e-06, 1.96692250e-03, 3.60366944e-04, 2.27370028e-03,\n",
       "       2.44922500e-04, 4.98033611e-04, 4.98033611e-04, 3.32736694e-03,\n",
       "       1.03361111e-06, 4.14092250e-03, 1.42003361e-03, 1.03361111e-06,\n",
       "       8.40033611e-04, 5.92922500e-04, 1.21366944e-04, 2.27370028e-03,\n",
       "       2.44922500e-04, 2.27370028e-03, 8.07002778e-05, 5.92922500e-04,\n",
       "       2.05922500e-04, 2.27370028e-03, 5.36694444e-06, 1.04436694e-03,\n",
       "       5.92922500e-04, 1.21366944e-04, 5.90336111e-05, 5.90336111e-05,\n",
       "       6.57922500e-04, 2.60270028e-03, 7.66366944e-04, 4.41700278e-04,\n",
       "       3.12700278e-04, 1.42003361e-03, 4.98033611e-04, 3.12700278e-04,\n",
       "       5.36694444e-06, 2.05922500e-04, 3.19225000e-05, 4.98033611e-04,\n",
       "       1.03361111e-06, 2.39936694e-03, 1.42003361e-03, 1.17992250e-03,\n",
       "       9.62033611e-04, 4.98033611e-04, 5.92922500e-04, 4.41700278e-04,\n",
       "       4.98033611e-04, 5.36694444e-06, 9.62033611e-04, 6.57922500e-04,\n",
       "       9.62033611e-04, 5.36694444e-06, 5.92922500e-04, 5.36694444e-06,\n",
       "       3.12700278e-04, 1.03361111e-06, 8.07002778e-05, 3.60366944e-04,\n",
       "       2.39936694e-03, 5.92922500e-04, 9.62033611e-04, 4.14092250e-03,\n",
       "       1.96692250e-03, 1.21366944e-04, 8.07002778e-05, 2.44922500e-04,\n",
       "       1.03361111e-06, 1.04436694e-03, 5.36694444e-06, 8.07002778e-05,\n",
       "       1.17992250e-03, 1.42003361e-03, 9.62033611e-04, 3.12700278e-04,\n",
       "       9.62033611e-04, 3.19225000e-05, 1.21366944e-04, 4.41700278e-04,\n",
       "       1.89225000e-05, 2.95392250e-03, 1.51700278e-04, 4.41700278e-04,\n",
       "       2.27370028e-03, 4.41700278e-04, 4.41700278e-04, 1.79070028e-03,\n",
       "       1.21366944e-04, 3.19225000e-05, 1.89225000e-05, 5.92922500e-04,\n",
       "       5.36694444e-06, 8.07002778e-05, 1.03361111e-06, 5.36694444e-06,\n",
       "       2.95392250e-03, 1.51970028e-03, 1.96692250e-03, 2.27370028e-03,\n",
       "       1.89225000e-05, 2.60270028e-03, 1.89225000e-05, 8.07002778e-05,\n",
       "       8.40033611e-04, 4.58103361e-03, 7.66366944e-04, 4.41700278e-04,\n",
       "       2.44922500e-04, 1.89225000e-05, 3.12700278e-04, 5.92922500e-04,\n",
       "       3.19225000e-05, 1.21366944e-04, 1.17992250e-03, 3.19225000e-05,\n",
       "       3.12700278e-04, 4.41700278e-04, 1.51700278e-04, 9.62033611e-04,\n",
       "       4.98033611e-04, 3.72303361e-03, 2.05922500e-04, 1.21366944e-04,\n",
       "       1.17992250e-03, 2.05922500e-04, 1.96692250e-03, 1.51700278e-04,\n",
       "       3.12700278e-04, 2.27370028e-03, 5.36694444e-06, 2.05922500e-04,\n",
       "       2.73703361e-03, 1.51700278e-04, 4.98033611e-04, 5.36694444e-06,\n",
       "       1.51700278e-04, 8.07002778e-05, 8.07002778e-05, 4.41700278e-04,\n",
       "       3.60366944e-04, 2.73703361e-03, 2.05922500e-04, 3.09692250e-03,\n",
       "       1.03361111e-06, 2.05922500e-04, 1.51700278e-04, 2.44922500e-04,\n",
       "       1.42003361e-03, 1.17992250e-03, 8.07002778e-05, 3.19225000e-05,\n",
       "       5.92922500e-04, 1.51700278e-04, 5.90336111e-05, 1.68236694e-03,\n",
       "       3.32736694e-03, 1.51970028e-03, 4.41700278e-04, 3.60366944e-04,\n",
       "       6.57922500e-04, 5.92922500e-04, 1.51700278e-04, 5.90336111e-05,\n",
       "       1.51700278e-04, 5.92922500e-04, 5.90336111e-05, 1.04436694e-03,\n",
       "       7.66366944e-04, 9.62033611e-04, 1.89225000e-05, 4.41700278e-04,\n",
       "       2.95392250e-03, 1.03361111e-06, 1.96692250e-03, 1.51700278e-04,\n",
       "       3.19225000e-05, 2.44922500e-04, 5.36694444e-06, 8.40033611e-04,\n",
       "       3.60366944e-04, 3.12700278e-04, 1.96692250e-03, 4.98033611e-04,\n",
       "       2.08392250e-03, 5.90336111e-05, 1.42003361e-03, 2.05922500e-04,\n",
       "       6.57922500e-04, 8.07002778e-05, 1.51700278e-04, 1.21366944e-04,\n",
       "       5.36694444e-06, 7.66366944e-04, 3.12700278e-04, 1.21366944e-04,\n",
       "       9.62033611e-04, 1.17992250e-03, 5.90336111e-05, 8.07002778e-05,\n",
       "       4.98033611e-04, 4.98033611e-04, 8.40033611e-04, 1.51700278e-04,\n",
       "       5.90336111e-05, 8.07002778e-05, 3.12700278e-04, 9.62033611e-04,\n",
       "       1.21366944e-04, 8.07002778e-05, 5.36694444e-06, 3.12700278e-04,\n",
       "       1.04436694e-03, 3.60366944e-04, 1.03361111e-06, 1.04436694e-03,\n",
       "       4.41700278e-04, 4.98033611e-04, 7.66366944e-04, 1.03361111e-06,\n",
       "       1.27092250e-03, 8.07002778e-05, 4.41700278e-04, 1.89225000e-05,\n",
       "       3.12700278e-04, 8.07002778e-05, 1.03361111e-06, 6.57922500e-04,\n",
       "       1.21366944e-04, 1.51970028e-03, 1.96692250e-03, 1.51700278e-04,\n",
       "       3.12700278e-04, 1.03361111e-06, 2.05922500e-04, 1.21366944e-04,\n",
       "       4.41700278e-04, 1.42003361e-03, 2.08392250e-03, 9.62033611e-04,\n",
       "       5.52792250e-03, 1.04436694e-03, 3.19225000e-05, 5.36694444e-06,\n",
       "       7.66366944e-04, 1.21366944e-04, 2.05922500e-04, 5.36694444e-06,\n",
       "       5.90336111e-05, 3.47903361e-03, 9.62033611e-04, 3.12700278e-04,\n",
       "       3.60366944e-04, 1.03361111e-06, 8.07002778e-05, 1.17992250e-03,\n",
       "       1.04436694e-03, 1.42003361e-03, 6.57922500e-04, 1.04436694e-03,\n",
       "       9.62033611e-04, 3.60366944e-04, 2.05922500e-04, 1.51700278e-04,\n",
       "       8.40033611e-04, 7.66366944e-04, 7.66366944e-04, 1.51700278e-04,\n",
       "       3.19225000e-05, 1.27092250e-03, 2.44922500e-04, 2.05922500e-04,\n",
       "       1.96692250e-03, 1.51700278e-04, 5.90336111e-05, 5.92922500e-04,\n",
       "       4.98033611e-04, 1.42003361e-03, 1.03361111e-06, 4.41700278e-04,\n",
       "       3.19225000e-05, 1.03361111e-06, 5.90336111e-05, 1.03361111e-06,\n",
       "       2.05922500e-04, 1.17992250e-03, 1.51970028e-03, 1.21366944e-04,\n",
       "       8.07002778e-05, 3.47903361e-03, 1.27092250e-03, 4.30992250e-03,\n",
       "       3.19225000e-05, 1.17992250e-03, 8.07002778e-05, 5.90336111e-05,\n",
       "       1.51970028e-03, 6.57922500e-04, 7.66366944e-04, 4.98033611e-04,\n",
       "       8.40033611e-04, 1.96692250e-03, 4.41700278e-04, 3.19225000e-05,\n",
       "       1.51700278e-04, 4.98033611e-04, 4.41700278e-04, 1.51970028e-03,\n",
       "       2.39936694e-03, 3.60366944e-04, 8.07002778e-05, 3.60366944e-04,\n",
       "       4.41700278e-04, 3.60366944e-04, 7.66366944e-04, 2.05922500e-04,\n",
       "       1.21366944e-04, 4.98033611e-04, 1.51700278e-04, 5.92922500e-04,\n",
       "       5.36694444e-06, 9.62033611e-04, 2.05922500e-04, 3.60366944e-04,\n",
       "       3.12700278e-04, 8.07002778e-05, 9.62033611e-04, 3.12700278e-04,\n",
       "       9.62033611e-04, 1.51970028e-03, 2.73703361e-03, 7.66366944e-04,\n",
       "       3.47903361e-03, 3.19225000e-05, 1.89225000e-05, 3.60366944e-04,\n",
       "       6.57922500e-04, 8.07002778e-05, 3.60366944e-04, 4.41700278e-04,\n",
       "       1.51970028e-03, 3.60366944e-04, 1.21366944e-04, 1.51970028e-03,\n",
       "       1.96692250e-03, 6.57922500e-04, 8.07002778e-05, 1.42003361e-03,\n",
       "       8.40033611e-04, 1.03361111e-06, 6.57922500e-04, 1.89225000e-05,\n",
       "       8.07002778e-05, 5.90336111e-05, 3.19225000e-05, 1.96692250e-03,\n",
       "       8.07002778e-05, 3.12700278e-04, 3.32736694e-03, 8.07002778e-05,\n",
       "       8.07002778e-05, 1.51970028e-03, 1.21366944e-04, 3.12700278e-04,\n",
       "       8.07002778e-05, 5.90336111e-05, 5.90336111e-05, 1.89225000e-05,\n",
       "       1.03361111e-06, 1.89225000e-05, 2.44922500e-04, 3.19225000e-05,\n",
       "       5.92922500e-04, 1.17992250e-03, 1.89225000e-05, 5.92922500e-04,\n",
       "       5.90336111e-05, 5.92922500e-04, 1.89225000e-05, 4.41700278e-04,\n",
       "       3.19225000e-05, 1.21366944e-04, 1.21366944e-04, 1.21366944e-04,\n",
       "       3.60366944e-04, 1.04436694e-03, 8.07002778e-05, 9.62033611e-04,\n",
       "       3.60366944e-04, 3.12700278e-04, 3.12700278e-04, 1.68236694e-03,\n",
       "       1.42003361e-03, 1.89225000e-05, 5.36694444e-06, 3.60366944e-04,\n",
       "       2.73703361e-03, 3.19225000e-05, 8.07002778e-05, 1.89225000e-05,\n",
       "       8.07002778e-05, 1.51700278e-04, 1.27092250e-03, 6.57922500e-04,\n",
       "       8.07002778e-05, 5.92922500e-04, 4.41700278e-04, 3.60366944e-04,\n",
       "       5.36694444e-06, 3.12700278e-04, 2.08392250e-03, 3.19225000e-05,\n",
       "       5.90336111e-05, 1.17992250e-03, 1.51970028e-03, 1.51700278e-04,\n",
       "       3.19225000e-05, 5.92922500e-04, 5.90336111e-05, 3.19225000e-05,\n",
       "       5.90336111e-05, 1.17992250e-03, 6.57922500e-04, 1.89225000e-05,\n",
       "       2.05922500e-04, 3.19225000e-05, 2.44922500e-04, 7.66366944e-04,\n",
       "       1.17992250e-03, 8.07002778e-05, 3.12700278e-04, 5.90336111e-05,\n",
       "       8.07002778e-05, 7.66366944e-04, 1.17992250e-03, 1.79070028e-03,\n",
       "       5.36694444e-06, 6.57922500e-04, 1.03361111e-06, 1.21366944e-04,\n",
       "       2.05922500e-04, 3.60366944e-04, 1.96692250e-03, 4.41700278e-04,\n",
       "       5.92922500e-04, 8.40033611e-04, 7.66366944e-04, 1.68236694e-03,\n",
       "       1.17992250e-03, 1.42003361e-03, 1.89225000e-05, 3.60366944e-04,\n",
       "       1.21366944e-04, 6.57922500e-04, 7.66366944e-04, 5.90336111e-05,\n",
       "       3.72303361e-03, 2.05922500e-04, 2.44922500e-04, 3.19225000e-05,\n",
       "       5.36694444e-06, 3.60366944e-04, 1.51700278e-04, 3.60366944e-04,\n",
       "       3.19225000e-05, 1.03361111e-06, 8.40033611e-04, 8.40033611e-04,\n",
       "       9.62033611e-04, 4.58103361e-03, 1.42003361e-03, 2.05922500e-04,\n",
       "       3.60366944e-04, 1.17992250e-03, 4.41700278e-04, 2.44922500e-04,\n",
       "       5.36694444e-06, 2.95392250e-03, 5.36694444e-06, 6.57922500e-04,\n",
       "       1.17992250e-03, 6.57922500e-04, 2.44922500e-04, 8.07002778e-05,\n",
       "       2.44922500e-04, 1.42003361e-03, 1.21366944e-04, 2.27370028e-03,\n",
       "       2.08392250e-03, 3.19225000e-05, 5.36694444e-06, 3.19225000e-05,\n",
       "       1.96692250e-03, 1.04436694e-03, 1.89225000e-05, 4.98033611e-04,\n",
       "       5.92922500e-04, 2.05922500e-04, 1.27092250e-03, 1.27092250e-03,\n",
       "       9.62033611e-04, 1.89225000e-05, 1.89225000e-05, 4.41700278e-04,\n",
       "       8.40033611e-04, 1.96692250e-03, 5.92922500e-04, 1.21366944e-04,\n",
       "       8.40033611e-04, 3.19225000e-05, 1.89225000e-05, 4.41700278e-04,\n",
       "       8.07002778e-05, 1.27092250e-03, 1.51970028e-03, 5.90336111e-05,\n",
       "       3.60366944e-04, 1.89225000e-05, 3.12700278e-04, 3.47903361e-03,\n",
       "       5.36694444e-06, 7.66366944e-04, 1.04436694e-03, 1.21366944e-04,\n",
       "       1.03361111e-06, 2.05922500e-04, 5.92922500e-04, 8.07002778e-05,\n",
       "       1.03361111e-06, 1.04436694e-03, 1.96692250e-03, 1.51700278e-04,\n",
       "       1.51700278e-04, 1.51700278e-04, 3.32736694e-03, 3.47903361e-03,\n",
       "       5.92922500e-04, 2.73703361e-03, 5.92922500e-04, 1.17992250e-03,\n",
       "       5.90336111e-05, 5.90336111e-05, 5.36694444e-06, 4.98033611e-04,\n",
       "       1.89225000e-05, 2.44922500e-04, 9.62033611e-04, 1.89225000e-05,\n",
       "       2.44922500e-04, 5.92922500e-04, 1.89225000e-05, 1.89225000e-05,\n",
       "       1.03361111e-06, 1.27092250e-03, 1.04436694e-03, 1.79070028e-03,\n",
       "       1.68236694e-03, 5.90336111e-05, 3.60366944e-04, 5.90336111e-05,\n",
       "       1.03361111e-06, 4.41700278e-04, 8.07002778e-05, 2.44922500e-04,\n",
       "       2.08392250e-03, 2.05922500e-04, 2.05922500e-04, 1.21366944e-04,\n",
       "       1.96692250e-03, 2.44922500e-04, 6.57922500e-04, 5.90336111e-05,\n",
       "       2.39936694e-03, 4.98033611e-04, 5.36694444e-06, 8.40033611e-04,\n",
       "       5.92922500e-04, 1.03361111e-06, 2.27370028e-03, 8.40033611e-04,\n",
       "       5.36694444e-06, 1.17992250e-03, 1.51700278e-04, 5.90336111e-05,\n",
       "       1.79070028e-03, 5.90336111e-05, 4.14092250e-03, 2.73703361e-03,\n",
       "       5.90336111e-05, 6.57922500e-04, 3.19225000e-05, 6.57922500e-04,\n",
       "       4.41700278e-04, 8.07002778e-05, 1.96692250e-03, 8.40033611e-04,\n",
       "       1.51700278e-04, 1.51970028e-03, 5.36694444e-06, 1.51970028e-03,\n",
       "       4.75870028e-03, 3.60366944e-04, 1.21366944e-04, 3.12700278e-04,\n",
       "       6.57922500e-04, 8.07002778e-05, 9.62033611e-04, 1.51700278e-04,\n",
       "       4.30992250e-03, 5.90336111e-05, 1.51970028e-03, 5.36694444e-06,\n",
       "       5.36694444e-06, 1.51970028e-03, 8.40033611e-04, 8.40033611e-04,\n",
       "       4.98033611e-04, 3.60366944e-04, 3.60366944e-04, 1.68236694e-03,\n",
       "       3.19225000e-05, 1.89225000e-05, 1.51970028e-03, 8.40033611e-04,\n",
       "       4.41700278e-04, 1.03361111e-06, 8.40033611e-04, 3.88336694e-03,\n",
       "       6.57922500e-04, 1.21366944e-04, 1.03361111e-06, 8.40033611e-04,\n",
       "       5.04336694e-03, 5.92922500e-04, 1.04436694e-03, 1.51970028e-03,\n",
       "       4.98033611e-04, 2.05922500e-04, 1.79070028e-03, 9.62033611e-04,\n",
       "       6.57922500e-04, 1.51700278e-04, 3.88336694e-03, 9.14892250e-03,\n",
       "       3.60366944e-04, 4.41700278e-04, 2.60270028e-03, 1.89225000e-05,\n",
       "       4.41700278e-04, 1.89225000e-05, 8.07002778e-05, 9.62033611e-04,\n",
       "       2.27370028e-03, 1.51700278e-04, 2.08392250e-03, 4.98033611e-04,\n",
       "       1.68236694e-03, 6.57922500e-04, 3.47903361e-03, 5.90336111e-05,\n",
       "       7.66366944e-04, 1.51970028e-03, 1.04436694e-03, 1.89225000e-05,\n",
       "       3.12700278e-04, 1.51970028e-03, 5.36694444e-06, 2.39936694e-03,\n",
       "       8.07002778e-05, 1.03361111e-06, 5.92922500e-04, 2.44922500e-04,\n",
       "       4.41700278e-04, 1.21366944e-04, 2.95392250e-03, 2.08392250e-03,\n",
       "       1.21366944e-04, 1.89225000e-05, 4.30992250e-03, 1.89225000e-05,\n",
       "       1.03361111e-06, 2.44922500e-04, 5.90336111e-05, 1.79070028e-03,\n",
       "       2.05922500e-04, 2.05922500e-04, 1.27092250e-03, 3.19225000e-05,\n",
       "       2.05922500e-04, 1.51700278e-04, 7.66366944e-04, 3.60366944e-04,\n",
       "       5.36694444e-06, 8.07002778e-05, 2.05922500e-04, 1.27092250e-03,\n",
       "       1.04436694e-03, 1.04436694e-03, 1.51970028e-03, 1.89225000e-05,\n",
       "       1.51700278e-04, 1.03361111e-06, 3.09692250e-03, 6.57922500e-04,\n",
       "       2.05922500e-04, 3.60366944e-04, 1.21366944e-04, 2.08392250e-03,\n",
       "       2.05922500e-04, 8.40033611e-04, 2.27370028e-03, 1.42003361e-03,\n",
       "       2.95392250e-03, 3.19225000e-05, 3.60366944e-04, 3.12700278e-04,\n",
       "       1.03361111e-06, 8.07002778e-05, 2.44922500e-04, 8.07002778e-05,\n",
       "       8.40033611e-04, 1.21366944e-04, 6.57922500e-04, 3.12700278e-04,\n",
       "       8.52236694e-03, 2.44922500e-04, 4.98033611e-04, 8.07002778e-05,\n",
       "       4.98033611e-04, 7.66366944e-04, 4.41700278e-04, 8.07002778e-05,\n",
       "       3.12700278e-04, 6.57922500e-04, 3.19225000e-05, 8.07002778e-05,\n",
       "       5.90336111e-05, 3.19225000e-05, 3.60366944e-04, 1.89225000e-05,\n",
       "       5.36694444e-06, 4.41700278e-04, 1.51700278e-04, 8.07002778e-05,\n",
       "       2.05922500e-04, 4.98033611e-04, 1.51700278e-04, 1.04436694e-03,\n",
       "       1.03361111e-06, 2.05922500e-04, 5.92922500e-04, 1.03361111e-06,\n",
       "       4.98033611e-04, 1.89225000e-05, 2.73703361e-03, 8.07002778e-05,\n",
       "       7.66366944e-04, 3.19225000e-05, 3.19225000e-05, 1.04436694e-03,\n",
       "       3.60366944e-04, 2.05922500e-04, 1.79070028e-03, 1.17992250e-03,\n",
       "       1.68236694e-03, 4.98033611e-04, 1.03361111e-06, 1.27092250e-03,\n",
       "       5.92922500e-04, 3.12700278e-04, 1.42003361e-03, 1.51970028e-03,\n",
       "       3.60366944e-04, 3.12700278e-04, 1.21366944e-04, 3.19225000e-05,\n",
       "       5.36694444e-06, 5.36694444e-06, 1.51700278e-04, 1.21366944e-04,\n",
       "       1.79070028e-03, 2.44922500e-04, 8.40033611e-04, 6.57922500e-04,\n",
       "       3.19225000e-05, 4.30992250e-03, 4.41700278e-04, 4.98033611e-04,\n",
       "       1.21366944e-04, 1.27092250e-03, 4.41700278e-04, 6.57922500e-04,\n",
       "       4.98033611e-04, 1.21366944e-04, 9.62033611e-04, 6.57922500e-04,\n",
       "       4.98033611e-04, 1.89225000e-05, 5.04336694e-03, 4.41700278e-04,\n",
       "       2.05922500e-04, 1.03361111e-06, 5.92922500e-04, 1.21366944e-04,\n",
       "       3.19225000e-05, 1.27092250e-03, 1.51700278e-04, 2.44922500e-04,\n",
       "       2.05922500e-04, 3.32736694e-03, 8.40033611e-04, 5.90336111e-05,\n",
       "       5.92922500e-04, 3.19225000e-05, 1.79070028e-03, 3.12700278e-04,\n",
       "       3.12700278e-04, 1.04436694e-03, 1.51700278e-04, 8.40033611e-04,\n",
       "       5.90336111e-05, 1.51970028e-03, 1.27092250e-03, 1.03361111e-06,\n",
       "       2.44922500e-04, 1.68236694e-03, 2.44922500e-04, 4.41700278e-04,\n",
       "       1.21366944e-04, 2.39936694e-03, 5.92922500e-04, 8.07002778e-05,\n",
       "       5.92922500e-04, 1.03361111e-06, 1.21366944e-04, 1.27092250e-03,\n",
       "       1.04436694e-03, 3.19225000e-05, 8.40033611e-04, 8.40033611e-04,\n",
       "       3.12700278e-04, 8.40033611e-04, 7.66366944e-04, 3.60366944e-04,\n",
       "       1.51700278e-04, 2.05922500e-04, 2.44922500e-04, 1.21366944e-04,\n",
       "       8.07002778e-05, 3.19225000e-05, 5.36694444e-06, 8.07002778e-05,\n",
       "       1.68236694e-03, 4.98033611e-04, 1.89225000e-05, 2.95392250e-03,\n",
       "       2.44922500e-04, 1.21366944e-04, 5.36694444e-06, 2.44922500e-04,\n",
       "       5.36694444e-06, 1.17992250e-03, 1.04436694e-03, 4.98033611e-04,\n",
       "       1.21366944e-04, 1.03361111e-06, 1.96692250e-03, 3.19225000e-05,\n",
       "       6.57922500e-04, 1.03361111e-06, 5.90336111e-05, 1.21366944e-04,\n",
       "       8.40033611e-04, 5.92922500e-04, 3.60366944e-04, 1.51970028e-03,\n",
       "       5.92922500e-04, 5.90336111e-05, 3.88336694e-03, 1.89225000e-05,\n",
       "       5.90336111e-05, 5.90336111e-05, 2.44922500e-04, 9.62033611e-04,\n",
       "       8.40033611e-04, 5.36694444e-06, 8.07002778e-05, 4.98033611e-04,\n",
       "       1.03361111e-06, 2.39936694e-03, 1.42003361e-03, 5.90336111e-05,\n",
       "       4.41700278e-04, 1.51700278e-04, 1.51700278e-04, 1.51700278e-04,\n",
       "       8.07002778e-05, 3.60366944e-04, 8.40033611e-04, 1.03361111e-06,\n",
       "       1.51700278e-04, 5.90336111e-05, 9.62033611e-04, 3.47903361e-03,\n",
       "       1.03361111e-06, 3.09692250e-03, 1.03361111e-06, 8.07002778e-05,\n",
       "       8.07002778e-05, 5.36694444e-06, 2.44922500e-04, 2.73703361e-03,\n",
       "       3.12700278e-04, 5.36694444e-06, 2.08392250e-03, 5.92922500e-04,\n",
       "       3.32736694e-03, 9.62033611e-04, 4.41700278e-04, 8.07002778e-05,\n",
       "       1.79070028e-03, 2.44922500e-04, 1.04436694e-03, 8.40033611e-04,\n",
       "       5.36694444e-06, 4.98033611e-04, 5.90336111e-05, 1.04436694e-03,\n",
       "       3.12700278e-04, 3.60366944e-04, 1.79070028e-03, 2.05922500e-04,\n",
       "       9.62033611e-04, 4.41700278e-04, 2.39936694e-03, 1.51700278e-04,\n",
       "       5.90336111e-05, 6.57922500e-04, 2.05922500e-04, 8.40033611e-04,\n",
       "       4.98033611e-04, 4.98033611e-04, 3.19225000e-05, 1.03361111e-06,\n",
       "       8.07002778e-05, 5.36694444e-06, 8.07002778e-05, 3.60366944e-04,\n",
       "       1.42003361e-03, 8.07002778e-05, 2.95392250e-03, 1.68236694e-03,\n",
       "       1.21366944e-04, 1.68236694e-03, 3.19225000e-05, 1.89225000e-05,\n",
       "       3.09692250e-03, 2.95392250e-03, 2.08392250e-03, 8.07002778e-05,\n",
       "       3.09692250e-03, 5.92922500e-04, 4.98033611e-04, 2.60270028e-03,\n",
       "       1.51970028e-03, 8.07002778e-05, 9.62033611e-04, 1.21366944e-04,\n",
       "       2.44922500e-04, 6.57922500e-04, 6.57922500e-04, 1.03361111e-06])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len((lastm_avg-(np.sum(lastm_avg)/len(lastm_avg)))**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7205552777777777"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(np.sum(Aa))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nn=1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Nn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "SIGMA=np.sqrt(np.sum(Aa)/Nn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.02684316072629633"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SIGMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "RSD=SIGMA/Mu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.039534344082519934"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "L=(np.sqrt(0.5)/np.sqrt(300))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0408248290463863"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}