Reran so all cells are sequentially executed.

05-Multivariate-Gaussians.ipynb

@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
@@ -255,7 +255,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -373,16 +373,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAD9CAYAAAC1Fh+gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x48af668>"
+       "<matplotlib.figure.Figure at 0x45cc320>"
       ]
      },
      "metadata": {},
@@ -434,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
@@ -456,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
@@ -474,7 +474,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -492,7 +492,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -511,7 +511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -537,7 +537,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -547,7 +547,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x818fa90>"
+       "<matplotlib.figure.Figure at 0x45cc710>"
       ]
      },
      "metadata": {},
@@ -581,16 +581,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAD9CAYAAAC1Fh+gAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXl4E1Xb/79Zmu4tLWBboICI7JtY1LKIUkA2QVB+rmyK\nwPuADw+gKCoIvmwqPg8qmz4qIOACrwiCsgqiLGoVQTZBZJGWtqxt6Za0TX5/9DrHk2mSWTIzmaTn\nc11cJOnM5MzkzMx37vM9921yuVwucDgcDofD4XA4NQBzoBvA4XA4HA6Hw+HoBRe/HA6Hw+FwOJwa\nAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+Fw\nOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6H\nw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/\nHA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwaAxe/HA6Hw+FwOJwa\ngzXQDeBwODUbl8uFyspKOJ1OOBwOAIDJZKL/m81mmM1mt9fsMhwOh8PhyIGLXw6Hoyus2HU6nR7/\n7nK56Gv2c8Bd9BJBTF6zApkIZvKPw+FwOByAi18Oh6MxrNhlhS0gHr0VCl1PsAKaFc3C5YVCmAhl\ni8VCX7N/43A4HE5owsUvh8NRFTGxq6WwFBOvnqLKbPvYdYViWGi94FFlDofDCU64+OVwOH6hptg1\nmUzVxKhWKBHK7GthVFoYVbZYLNWEsq/v43A4HI4+mFx63Wk4HE5I4HK54HQ6UVlZKdvGIEZ5eblu\n4ldLfEWVvdkveFSZw+Fw9IFHfjkcjk+I2CX/9LQxBCtKosqVlZUoKysDAFgsFkRERNBtsMeZndDH\nhTKHw+HIh4tfDofjBit2b9y4QaOx0dHRsNlsmnt2QyHyKwdvx5P9nBXLlZWV9DPhst6iymxkmYtl\nDodT0+Hil8Op4fiK7JK/kdccffB1rLXyKvNUcRwOp6bAxS+HU8PgNoaag5RUcb4yYIhN6uMFSDgc\nTjDCxS+HE+IIxS75DBAXu8Khd60htgcungKDmqnieAESDodjVLj45XBCDDGxy/4vht7ityYTbCJQ\nSl/iBUg4HI4R4eKXwwly1BS7Yt/D4SjFn6iyw+GgfdtmsyEsLIyniuNwOIrh4pfDCTL0ErtqbofD\nkYOwHwsnXvpTgMRbqjjhehwOJ3Th4pfDMThiE9TY/9VGD9uDy+VCeXk5ysvLUVFRAafTWS165+0f\np+bhyTLh7W8EsVRxZF1egITDqRlw8cvhGAxW7LIRL0D/bAxaiF+Xy4WKigoqeIkYYfH0mbf2ecpf\ny4Uyxxs8VRyHw+Hil8MJMEYSu1pAxC4RvBUVFapuW3jMvOFNqHiL+HGMQ6D85jxVHIcTmnDxy+Ho\nTDCJXSWRX5fLhcrKSip0y8vLRdexWCwICwuDxWJxG5b29U8uctbzFUHmPtHAYuTj7W9UWbgNniqO\nw9EGLn45HI0hN7zKykqUlJTA4XDA5XIhIiIC4eHhhr55SRG/RMCzvl0xkWk2mxEWFoawsDBYrVZ6\nkycPAmLHhGyfPEAYVSizokXKfnFqDlKiylJTxZFzzmQy0YdIniqOw/EOF78cjsqwYlcY2a2srKTD\n/sGQOsyb+CX7QQSvFLFrtVqp4CVi0Nf3SWmXxWIRXZYVDaxNwmhC2VskkOM5MlrT8CVeKyoq6IgJ\n25e8FSARimE+qY9T0+Dil8PxE3YWOZt+DKhuY9BiApleOJ1OFBcXo7y8XNRjSyJQRPBKEalaISfi\n5Uko+xLMcpG6nsvlQlFRkeSsF1yk1GyEDwdaTeoj70lkmVuAOMEKF78cjkzkiF0hwSJ+nU4nKioq\n4HA46Gculwt2u93j8iaTiQpdq9VKh1uDDbk3cTG7BSuYlSBlIh/bdl8T+bhQ5nhCyaQ+T9YmbxNH\neVSZY0S4+OVwJEBsDEKxC8iLdrDLyhE2WiMl/ZgQYWS3Jt7M5NzEpQhlf/oEK1DEfj+xiXxGi+Zp\nYXtwOBy4cuUK6tSpA5vNpso2A4WethAto8reCpAYoQ9yQgsufjkcD7BiVxi58+dCbJTILxG7ctOP\nRUZGwmq1wmq18huSTMRu4pWVlSgtLaXLRkZGSprMF+gJfUaeTOVwOLB9+3bs2bMHv//+Oy5evIj8\n/HwUFxejrKwMTqcTNpsNqampGDhwIF544QVERkYGutmyMaonWm5U2VMBErZveYoqs5FlLpY5UjG5\njDz2yuHohFZiV4jD4UBRUREAwGq1Ii4uTrVt+4Lsn9z0Y1ar1c3qkJCQoOmNxeVyweFw1MibFyt+\nzWYzoqKiJK2ndeYLOUj1J8sVKOScAYDo6GjRdR0OB8aNG4fNmzejrKxM8vdYrVbUq1cPPXv2xMyZ\nM1GrVi3J6wYKl8uF4uJi+l7K8QkF5ESV2c9ZWxYXyjUXLn45NRK9xK6QiooKFBYWAqgSl/Hx8Zp8\nDxlGl5N+jIhdYfqxa9eu0WW4+NUOpeJXDlpnvpCDHIFcUlJC1xMTdwsWLMDChQvpeaYUi8WC1NRU\nrF+/Hk2bNvVrW1oiFL8xMTEBbI1xKS8vpw/yFosFERER9G9Soso8XWFowW0PnBoBucmT9GPeZkdr\njZa2ByXpx1jfrq/0Y6xo0stTyFEfNSf0CUWzXJSuZ7fbPYrk7du341//+hdycnLcljeZTIiKikJ0\ndDQSEhJQr149tG7dGhkZGWjZsiVmzJiBvXv3Ii8vz80rXVlZiXPnzqFz586YP38+nnzySdlt1QOj\nWh6Mhtg135NX2dOkPvI/L0AS3PDILyckERO7gcLpdCI/P5+2IyEhwa9tsTYGqenH2IwMUsjPz6fb\njo+P1zRtmcvlkmTJCEX0iPxqiRTLBRHManL+/Hk89dRTOHHiRLVtN2zYEO+88w66dOkiar3Iz8/H\nrFmzsGPHDly8eNHNB282m3H//fdj1apVqrZdDYK93+iF3W6n1xabzabqJEdfwQFPUWWSKs7onvlQ\nhotfTkjAzpYX3mCNdEFxuVy4fv06fZ+YmCh5XZJ+jER2pYhdYWEJJcdCT/ELwC29Wk2iJokYqRP5\nxKLDM2bMwMqVK6s9MCUkJGDq1KkYMWKEaFs8CeKysjI89thj2Lt3r9v3N2nSBLt27ZJ13mpNRUUF\n9TWHer/xh7KyMvpAEx4ejrCwsIC0w1dU2Zv9QmjD4FFl/+HilxOUOJ1OOBwO6ttlL2RGvigIxa8v\nDy2JghLBG6j0YwUFBfS74+LiYLVq45YiPmxvw9qhTk0Sv3JgjwtQJVxcLheefPJJbNq0yU1EREZG\n4qGHHsJrr72myncvWrQICxYscHsgi42NxXvvvYeMjIxqfTQQUTxW/FoslqDMVqEHpaWl9DoWERGh\n2XVMTeRM6gOAkydPomPHjvo2Mkjh4pcTFAgju6x9ANB+IpaaXL9+nV7IatWqRb1jLpfLLfWYlPRj\n7AQ1rdKPFRYW0rbExsaqFjGROykv1KudcfHrGafTSSe8mUwmREdHo1+/fti7dy9dxmKxoHPnzvj0\n008RExMjOpFPjt/48OHDePzxx90mflqtVowaNQqzZs3yup7Uvupvn2UnclmtVreJXJy/KSkpoSNY\nkZGRAa06qRV9+/Z1Oy843jH+ow+nRiJmY9BT4JCZ1NHR0apsj51ARuwLUnPtWiwWN9+u3kLP32dl\nodiVU9RB6rJ6iQ6OPrB9rry8HJ07d8bRo0fpZ+Hh4ViyZAmGDh1KP2MnJIltVyzzRYcOHZCZmYkH\nHngAR44cAVAVbf3vf/+La9eu4Z133vG6fanniz991qgWL6MR6sepvLw8KKLZRoEfKY4hEIpd8hng\nWeySmxtZ1ul0avIk//XXX2PYsGEoLS1Fy5Yt8dVXXyE5OVnRtsiwPnsRZlMUecJb+jE98edGQawb\nROxKqTxmsVj8SrmltujgKY6MQWlpKTIyMnDu3Dn6WVRUFD777DN0795d9vbk2BOio6Oxd+9eTJo0\nCStXrqT9+IsvvkDz5s0xceJEXTNfsH2TfSgkk3z5w507Rpr0rBXZ2dmoV69eoJsRNHDxywkIYmKX\n/d8b7N+1cO9cuXIFI0aMoAL12LFjaNmyJaZMmYKXX35ZdH12WJ/YGdRKP6Ynco4zsW7IqRxHItlk\nf4X2B6mTopSUBlZTKPNZ29px/fp19OjRA3l5efSzuLg4bN++Ha1atdKlDSaTCQsXLkRGRgZGjRoF\nh8MBp9OJN954A23atMGAAQPoslr2WXb7wvWF/mjSbk/91NsEq5pAKO5ndnY2GjZsGOhmBA3c88vR\nBSliVy6sFzUmJkbV1DUA0LZtW/zxxx8e/9aiRQts2rQJqampbp/LHdY3mZSlH9OT4uJi6imMiopy\n8xSSaDabhUIMMZ+ylIcEb0gVHFpf9pQIZe759czp06eRkZHhNlG0Tp062Lt3b8AiXUuWLMGLL75I\nz++oqCjs2bMHzZs3l70ttTJfqIFYfw1WoezJNx5qfPrppygvL8c//vGPQDclKOCRX44mqBHZFYON\niqp9Uxg2bJib8E1JSUFeXh7dl99//x1t27bFRx99hD59+shKP8a2NyIiIuhmZ8stpkF8ykT0annT\nlDPUK1Ukaz2M7c3HWVFREdSCQw3++usvdO/eHTdu3KCfNWjQAD/99FNAK5n94x//wO+//44VK1YA\nqJpMdd999+Ho0aOy2+Vvn3U4HLSvsZNn9eq3wWAZYq/LgW6LVmRlZaFTp06BbkbQwLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x82d3a20>"
+       "<matplotlib.figure.Figure at 0x7a4ca20>"
       ]
      },
      "metadata": {},
@@ -625,9 +625,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAFaCAYAAABSeZjAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAFaCAYAAABSeZjAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7c12748>"
+       "<matplotlib.figure.Figure at 0x7be0d30>"
       ]
      },
      "metadata": {},
@@ -667,9 +667,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAE6CAYAAADZSa6hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3X2wHXV9P/D3Pu+e53vuc54gqQEUK0MaLGSm/AgIJVJT\naXwCCkodUYtWEHWkQ0nUFAfbUq2iVh3bqGPFsVYdUcQWECOoCTZYiCKaB0KSe3MfzvPZ593fHyf3\nSkgCZ/fszTn33vdrBoVzzu5+707m5J1PPvv5CmEYhiAiIiIiotjEbi+AiIiIiGi+Y6gmIiIiIuoQ\nQzURERERUYcYqomIiIiIOsRQTURERETUIYZqIiIiIqIOMVQTEXXZli1bIIoinnnmmW4v5TiiKOL6\n66/v9jKIiHoeQzURUY96/PHH8aEPfQh/8id/gqVLl0LTNCxZsgSbNm3Cj3/841jnfPTRR3HFFVeg\nWCwilUrhnHPOwSc+8QkEQXDSYwRBiPsjEBEtGnK3F0BERCf29re/HT//+c9x7rnn4rWvfS3y+Tx2\n796Nb3/72/iv//ovfPKTn8SNN97Y9vm+/e1vY9OmTUilUnjjG9+IYrGI73znO7j55pvxk5/8BF//\n+tfn8KchIlrYGKqJiHrUNddcgy9/+ctYvXr1Ma8/+OCD+NM//VPccssteN3rXofh4eEXPVe1WsXb\n3vY2KIqChx56CGvWrAEAfPjDH8bFF1+Mb3zjG7jnnnvwxje+cU5+FiKihY7tH0REPerd7373cYEa\nANavX4+LLroIjuPgJz/5SVvn+sY3voHJyUm86U1vmg3UAKBpGrZu3QoA+MxnPpPMwomIFiGGaiKi\neUhRlGP+/8U88MADAIDLL7/8uPcuvPBCGIaBRx99FK7rJrdIIqJFhKGaiGie2b9/P/7nf/4H6XQa\nF154YVvHPPXUUwCAM84447j3JEnCypUr4Xke9uzZk+haiYgWC/ZUExHNI6Zp4k1vehMcx8Edd9yB\nfD7f1nGVSgWCIJz08/l8HmEYolwuJ7lcIqJFg5VqIqJ5wnEcvOENb8DPfvYzXHPNNXjve9/b7SUR\nEdFRDNVERPOAbdvYtGkT7r33Xlx77bX40pe+FOn4mUp0pVI54fszrxcKhY7XSkS0GDFUExH1uGaz\nide85jW499578da3vhXbtm2LvCHLmWeeCeD3vdXP5Xke9u7dC0VRsGrVqkTWTES02DBUExH1sFqt\nhg0bNuC///u/ceONN+Lzn/98rPNccsklAID77rvvuPcefvhhmKaJdevWtT1NhIiIjsVQTUTUo8rl\nMi699FL8+Mc/xi233IJPfvKTsc/1ute9DgMDA/ja176Gxx57bPZ1y7Jw2223AQDe+c53drxmIqLF\nitM/iIh61JVXXomf//znWLZsGTKZDLZs2XLcZ9avX4//9//+34ueK5vN4gtf+AI2bdqEiy66CG96\n05vQ19eH73znO/jNb36D17/+9XjDG94wBz8FEdHiwFBNRNSj9u3bB0EQcPDgQXzoQx867n1BECCK\nYluhGgA2btyIH//4x/jIRz6C//zP/4RlWVi9ejX++Z//GX/zN3+T9PKJiBYVhmoioh61d+/exM95\n/vnn49577038vEREix17qomIiIiIOsRQTURERETUIYZqIiIiIqIOMVQTEXWZIAiRN3MhIqLeIoRh\nGHZ7EURERERE8xkr1UREREREHWKoJiIiIiLqEEM1EVGXbdmyBaIo4plnnun2Uo4jiiKuv/76bi+D\niKjnMVQTEfW4e++9F+vXr0c+n0c2m8X555+PL33pS5HPU6/Xcfvtt+NlL3sZDMNAoVDA+vXr8a1v\nfesFj+NDlEREL46hmoioh9199914zWtegyeffBLXXXcdbrjhBhw6dAhvectb8P73v7/t85TLZVxw\nwQXYunUrBEHA29/+dlx11VV4+umn8Rd/8RfYunXrHP4UREQLH7cpJyLqUfv27cMtt9yC/v5+7Ny5\nEytWrAAA/N3f/R3OO+88/NM//RM2bdqE888//0XPtWXLFjz55JO48sor8fWvfx2SJAEA7rzzTlx4\n4YXYsmULrrjiCpx77rlz+jMRES1UrFQTEfWoL37xi3AcB+9617tmAzUAFAoF/O3f/i0A4LOf/Wxb\n5/rmN78JQRDwkY98ZDZQA0Aul8Ntt92GIAhw9913J/sDEBEtIgzVREQ96oEHHgAAXH755ce9t2HD\nBgDAgw8+2Na5xsbGAACrVq067r2Z12auR0RE0TFUExH1qKeeegqCIOCMM8447r2RkRGkUik8++yz\nsCzrRc81MDAAANizZ89x7/3ud78DAOzfvx+2bXe4aiKixYmhmoioR1UqFQBAPp8/4fszr8987oVs\n3LgRYRji9ttvh+/7s69Xq1X8/d///ex/l8vlTpZMRLRo8UFFIqJF4MMf/jB++MMf4pvf/CbOOecc\nXHLJJbBtG9/97nehaRry+Tyq1SpEkbUWIqI4+O1JRNSjXqwS/WKV7OcaGhrCjh07cNNNN8E0TXz2\ns5/Ft771LVx22WXYvn07PM+DLMsoFovJ/QBERIsIQzURUY8688wzEYYhnnrqqePeO3z4MJrNJpYt\nWwZd19s6X7FYxF133YXf/e53sG0bY2Nj+OIXvwjTNNFoNHDuueceMxmEiIjax1BNRNSjLrnkEgDA\nfffdd9x73//+9wEAF198ccfX+fd//3cAwDXXXNPxuYiIFiuGaiKiHnX99ddD0zR86lOfwv79+2df\nL5VKuOOOOyAIAt7xjne0da4wDFGv1497/fvf/z4+9rGP4ayzzsINN9yQ2NqJiBYbPqhIRNSjTj/9\ndPzjP/4j3v3ud2Pt2rV44xvfCEVR8I1vfAMHDx7E+973PvzxH/9xW+dqNBoYGhrCpZdeij/4gz+A\nLMvYuXMnHnroIZx22mn4zne+A03T5vgnIiJauNqqVH/0ox/Feeedh3w+j6GhIWzcuBFPPvnkcZ/b\nsmULli5dilQqhfXr12P37t2JL5iIaDG58cYb8d3vfhdnn302vvSlL+ELX/gClixZgm3btuFjH/tY\n2+fRdR3XXHMNnnrqKXzuc5/Dpz/9aUxOTuL222/HL3/5S7zkJS+Zw5+CiGjha6tS/aMf/Qjvete7\ncN555yEIAtx+++141atehd27d6Ovrw8AcOedd+Kuu+7Ctm3bcMYZZ+DDH/4wLr30Ujz11FPIZDJz\n+kMQES1kr371q/HqV7+6o3PIsozPf/7zCa2IiIier61Q/fyHZL785S8jn8/jkUcewRVXXIEwDPHx\nj38ct956K6688koAwLZt2zA0NISvfvWr7NMjIiIiogUt1oOK1WoVQRDMVqn37t2L8fFxXHbZZbOf\n0XUdF154IR555JFkVkpERERE1KNiher3vOc9OPfcc3HBBRcAAMbGxgAAw8PDx3xuaGho9j0iIiIi\nooUq8vSP9773vXjkkUewfft2CILwop9//mdOtjMYEdFiZds2BEFAtVrtye9Ix3F6cl1ERN1yop1s\nI4Xqm2++GV//+tfx4IMP4vTTT599fWRkBAAwPj6OZcuWzb4+Pj4++x4REZ3YBz/4QXzwgx/s9jJO\nqFQqdXsJRETzQtvtH+95z3twzz334IEHHsAZZ5xxzHsrV67EyMgI7r///tnXLMvC9u3bsW7duuRW\nS0RERETUg9qqVN944434yle+gm9961vI5/OzfdLZbBbpdBqCIOCmm27CHXfcgbPOOgurV6/G1q1b\nkc1mcfXVV5/0vCcqnXfTzp07AQBr167t8koWH9777uL97x7e++7i/e8u3v/u4b2P7sXa4NoK1Z/5\nzGcgCAIuueSSY17fsmULbr/9dgDABz7wAZimiRtvvBGlUgnnn38+7r//fqTT6ZhLJyIiIiKaH9oK\n1UEQtHWyzZs3Y/PmzR0tiIiIiIhovok1Uo+IiIiIiH6PoZqIiIiIqEMM1UREREREHWKoJiIiIiLq\nEEM1EREREVGHGKqJiIiIiDrEUE1ERERE1CGGaiIiIiKiDjFUExERERF1iKGaiIiIiKhDDNVERERE\nRB1iqCYiIiIi6hBDNRERERFRhxiqiYiIiIg6xFBNRERERNQhhmoiIiIiog4xVBMRERERdYihmoiI\niIioQwzVREREREQdYqgmIiIiIuoQQzURERERUYcYqomIiIiIOsRQTURERETUIYZqIiIiIqIOMVQT\nEREREXWIoZqIiIiIqEMM1UREREREHWKoJiIiIiLqEEM1EREREVGHGKqJiIiIiDrEUE1ERERE1CGG\naiIiIiKiDsndXgAREUXn+QEapoOm7aJhuWhaLvwgQBgCggCIggBdlZE2VKR1BWldhapI3V42EdGC\nxVBNRDSPVBs2JsoNlOomGm4TlmfBck1YngU/DBCGAQABkihCk3Tosg5D0WHIBvLpFIYKafRldQiC\n0O0fhYhoQWGoJiLqcWEYYrLSxJFSA+VmAyVrGjWnBk0VYGgS8mkZw5oBSRQgCEAYAkEQwnJ8WHYd\nZbuCsYYPvZ7CeLWIPiOHgXwKw31pSBK7AImIksBQTUTUw5qWi/3jZRyplTHZmIQXWijkVKwaSkM+\nSSAWBEAUBWRkEZmUAqAVzCt1FxPVgxivj6O/XsRkpR/Lh3Loyxqn8kciIlqQGKqJiHpQEIQ4NFXD\noakKxurjMP0ahosGsulcrPMJgoBCVkUhq8K0PBwpTaA8WUHdHsVwPocVw3koMnuuiYjiavvv/R5+\n+GFs3LgRy5YtgyiK2LZt2zHvv+Utb4Eoisf8s27dusQXTES00NmOh1/tn8BvDh/CntIeKLqFVUuz\nyKaVRM5v6DJOG82gUACeqezDb488iyf2HkG1YSdyfiKixajtSnWj0cArXvEKvPnNbLine truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtUAAAE6CAYAAADZSa6hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x833b898>"
+       "<matplotlib.figure.Figure at 0x8225a58>"
       ]
      },
      "metadata": {},
@@ -702,7 +702,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP0AAAD9CAYAAAB3NXH8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x831deb8>"
+       "<matplotlib.figure.Figure at 0x87282b0>"
       ]
      },
      "metadata": {},
@@ -780,9 +780,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7b39438>"
+       "<matplotlib.figure.Figure at 0x798db38>"
       ]
      },
      "metadata": {},
@@ -815,9 +815,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7b24cc0>"
+       "<matplotlib.figure.Figure at 0x79800b8>"
       ]
      },
      "metadata": {},
@@ -860,7 +860,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8213f98>"
+       "<matplotlib.figure.Figure at 0x7c0ea90>"
       ]
      },
      "metadata": {},
@@ -913,9 +913,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x822ee48>"
+       "<matplotlib.figure.Figure at 0x7bc89e8>"
       ]
      },
      "metadata": {},
@@ -944,9 +944,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x87f5ba8>"
+       "<matplotlib.figure.Figure at 0x7bdb080>"
       ]
      },
      "metadata": {},
@@ -979,7 +979,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9008748>"
+       "<matplotlib.figure.Figure at 0x8bebb00>"
       ]
      },
      "metadata": {},
@@ -1015,9 +1015,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x92ab588>"
+       "<matplotlib.figure.Figure at 0x8bfa2e8>"
       ]
      },
      "metadata": {},
@@ -1048,7 +1048,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9319630>"
+       "<matplotlib.figure.Figure at 0x8cfd9e8>"
       ]
      },
      "metadata": {},
@@ -1086,9 +1086,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEWCAYAAABL+3CVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9006080>"
+       "<matplotlib.figure.Figure at 0x87c80b8>"
       ]
      },
      "metadata": {},
@@ -1116,9 +1116,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAARgAAAEWCAYAAAC9hIj8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x906c358>"
+       "<matplotlib.figure.Figure at 0x8c937f0>"
       ]
      },
      "metadata": {},
@@ -1172,7 +1172,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x92d0a58>"
+       "<matplotlib.figure.Figure at 0x8cd4630>"
       ]
      },
      "metadata": {},
@@ -1205,7 +1205,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ab5160>"
+       "<matplotlib.figure.Figure at 0x7989240>"
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      },
      "metadata": {},
@@ -1254,7 +1254,7 @@
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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x933b4e0>"
+       "<matplotlib.figure.Figure at 0x916c2e8>"
       ]
      },
      "metadata": {},
@@ -1284,7 +1284,7 @@
      "data": {
       "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x933b4a8>"
+       "<matplotlib.figure.Figure at 0x7a4cef0>"
       ]
      },
      "metadata": {},
@@ -1317,9 +1317,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7a1c320>"
+       "<matplotlib.figure.Figure at 0x8c203c8>"
       ]
      },
      "metadata": {},
@@ -1346,9 +1346,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xt8FPW9//H37Oaym/sFQggg94sXVBRRaUuBnyD0gvao\nVTmgaI/YWuvt1FZP7QH8efTY9mHVA/oTq5ZK0eppbZVSwbYKotSCihfwAhgQgURCQu7X3fn9MTuT\nbEJigCQzu/t6Ph48kp35Bj8MmLzzyWe+Y5imaQoAAABAzPK5XQAAAACA40OoBwAAAGIcoR4AAACI\ncYR6AAAAIMYR6gEAAIAYR6gHAAAAYhyhHgAAAIhxMRPqN2zYoDlz5mjw4MHy+XxasWJF1PkFCxbI\n5/NF/Zo8ebJL1QIAAAB9J2ZCfW1trU499VQ98MADCgaDMgwj6rxhGJoxY4ZKSkqcX2vWrHGpWgAA\nAKDvJLldQHfNnj1bs2fPlmR15dszTVMpKSkqKCjo48oAAAAAd8VMp/6LGIahjRs3asCAARo7dqwW\nLlyogwcPul0WAAAA0OtiplP/RWbNmqWLLrpIw4cPV3Fxse644w5Nnz5db775plJSUtwuDwAAAOg1\ncRPqL730Uuf9k08+WWeeeaaGDh2qP//5z/rWt77lnKusrHSjPAAAAKBHZGdndzgWN+M37Q0cOFCD\nBw/Wzp073S4FAAAA6FVxG+oPHjyoffv2aeDAgW6XAgAAAPSqmBm/qa2t1Y4dOyRJ4XBYe/bs0dat\nW5Wfn6+8vDwtWrRIF198sQoLC7V7927dfvvtGjBgQNToTXtH+tFFX9myZYskaeLEia7VkMi4/u7h\n2ruL6+8err27uP7u4vofvy8aIY+ZTv3mzZt1xhln6IwzzlBDQ4MWLVqkM844Q4sWLZLf79f777+v\nCy64QGPHjtWCBQt04oknatOmTUpPT3e7dAAAAKBXxUynfurUqQqHw52ef/HFF/uwGgAAAMA7YqZT\nDwAAAODICPUAAABAjCPUAwAAADGOUA8AAADEOEI9AAAAEOMI9QAAAECMI9QDAAAAMY5QDwAAAMQ4\nQj0AICZseGePzr91pf7nD2+4XQoAeE7MPFEWAJC4mltCWnDvH1V84LDWbdmlqacP0/gRA9wuCwA8\ng049AMDzXnt/r4oPHHZeP/W3912sBgC8h1APAPC8F/+5U5I0fkSBJOkvkdcAAAuhHgDgeX9/u1iS\n9F/fma5ASpK27izRoco6l6sCAO8g1AMAPM00TX2895Ak6ZyTBmvcCf0kSTv3lbtZFgB4CqEeAOBp\n5VX1qqxtVGZaivplp2lkUa4k6ZMDFS5XBgDeQagHAHiaHd5HDMyVYRhOqN+1n1APADZCPQDA0+zw\nPrIoT5IV7iXpE0I9ADgI9QAAT9u135qdH1GUI0kaOSgvcpxQDwA2Qj0AwNM+adepbx2/4UZZALAR\n6gEAntY6fmOF+SEF2Ury+7SvrFoNTS1ulgYAnkGoBwB4WtsbZSUpye/T0AHZkqRidsABAEmEegCA\nhzU2teizg1Xy+wydEAnykjSiiJtlAaAtQj0AwLP2HqySaUqD+2cpOcnvHB9eaN00u7vksFulAYCn\nEOoBAJ51qLJOktQ/Jz3quP26vLq+z2sCAC8i1AMAPKuipkGSlJcZjDpuvybUA4CFUA8A8KzyKiu0\n52W1C/WR1+VVDX1eEwB4EaEeAOBZdic+LzMQdZxOPQBEI9QDADzrizv1hHoAkAj1AAAPa+3UM1MP\nAF0h1AMAPMvuxOe2C/W5kXEcQj0AWAj1AADP6qxTb4f88qp6mabZ53UBgNcQ6gEAnuWE+nYz9YGU\nJKUFktUSCqumvsmN0gDAUwj1AADPcm6Ubdepb3uMm2UBgFAPAPCwytpGSVJORqDDOfuYvQYAEhmh\nHgDgWVV1VmDPSk/tcC4rLTVqDQAkMkI9AMCTWkJh1TU0yzCk9ECy3vxov75+2yqtfOldSa1Bv4pO\nPQAoye0CAAA4EvsG2Ky0VBmGoR/+v5f0ytbdenHzTs2ZPFaZwRRJUjWdegCInU79hg0bNGfOHA0e\nPFg+n08rVqzosGbx4sUaNGiQ0tLSNG3aNG3fvt2FSgEAPcHuwGempaq8ql6vvrtHkhQOm1q7eWdr\np55QDwCxE+pra2t16qmn6oEHHlAwGJRhGFHn7733Xt13331aunSpNm/erIKCAs2YMUM1NTUuVQwA\nOB7OPH1aql7ZuluhcOt+9C9t+YSZegBoI2ZC/ezZs3XXXXfpoosuks8XXbZpmrr//vt1++2361vf\n+pZOPvlkrVixQtXV1Vq1apVLFQMAjkd1m5tkd+w7JEk6aWh/SdLO/eXKTLPGb5ipB4AYCvVdKS4u\nVmlpqWbOnOkcCwQCmjJlil5//XUXKwMAHCs7rGelpWrXvgpJ0oyJIyRJu/ZXOOM31XU8fAoA4iLU\nl5SUSJIGDBgQdbygoMA5BwCILfZYTWZainbtt0L99AnD5fMZ2vt5pYIpyVHrACCRxf3uN+1n79va\nsmVLH1bi3RoSGdffPVx7d8XC9X93+6eSpKb6an242xq/aa46oMLsgPZX1GvHJ8WSpD2flcTEn8cW\nS7XGI66/u7j+x2706NFdno+LTn1hYaEkqbS0NOp4aWmpcw4AEFtqG0OSpGCyXyWH6+UzpKLcNBXl\np0mS6hpbIutaXKsRALwiLjr1w4cPV2FhodatW6czzzxTktTQ0KCNGzfqF7/4RacfN3HixL4qsQP7\nO1U3a0hkXH/3cO3dFUvXf822Wknb1b+gQGFzj4YOyNa550zShI2l2rLzkNKy8iRJRlIgJv48sXTt\n4xHX311c/+NXWVnZ5fmYCfW1tbXasWOHJCkcDmvPnj3aunWr8vPzNWTIEN100026++67NW7cOI0e\nPVp33XWXMjMzNXfuXJcrBwAci9oG6wbY5harYz+4f5YkaUiB9da+kdZeBwCJLGZC/ebNmzV9+nRJ\n1pz8okWLtGjRIi1YsECPP/64fvSjH6m+vl7f//73VVFRoXPOOUfr1q1Tenq6y5UDAI5FUyTMN4fC\nkqT8LGvsJi8zKKn1ibP2OgBIZDET6qdOnapwONzlGjvoAwBiX2OTFdabmq23eVnBqLf2VpaNzYR6\nAIiLG2UBAPHH7sA3Nls3wuZlBiJvI6He7tQT6gGAUA8A8Ca7A98Q6djnZkZ36itrGiLr2P0GAAj1\nAABPanJCfbOk1g69/bayriFqHQAkMkI9AMCT7A58XUNk/KbdTP3hartTT6gHAEI9AMCT7Jn6ukar\nU5+TYc3UZ6dbb6vq2P0GAGyEegCAJ9m73zQ2WZ36rLRUSZLPZygjmOK8Hw6bagl1vTsaAMQ7Qj0A\nwJPad+qz0lOdc/b7yX7ryxhz9QASHaEeAOBJzky9HerT2oT6yPspSf6otQCQqAj1AJAg/rH9M339\nrr9p4cObnJEWL7O773UNHTv1mWnW+E0SnXoAkESoB4CEccP//EWfVzbo7U/KteyPm90u5wvZu9rU\nRkJ9ZmSOXmrt1PsjoZ4dcAAkOkI9ACSAvZ9XavOH+53Xv9/wgYvVdE/bXW3SA8lOgJdau/Z+n9Fh\nLQAkIkI9ACSAF/+5U5I0cVS+/D5D//jgM5VX1btcVdfajtRktpmnl6TMYOtOOO3XAkAiItQDQAJ4\n9d1PJUnTTinUqcNyFQ6ben3bXper6lrbm1/TA8lR5zKC1mufYXRYCwCJiFAPAAlg5/5ySdLIwkyN\nKMiQJO3aV+5mSV+obfc9kJIUdSw12Xrtp1MPAJII9QCQED7ZXyFJGpSfpkH5adaxAxVulvSF2t78\nmpLs14FD1Tr9mv+nv735iVKSra0sDadTT6gHkNgI9QAQ52rqm1RaUauUZL/6ZwWcUL9rv7dDfdub\nX1OS/LrloXX6YE+ZLlnyrBPqfdwoCwCSCPUAEPfsLv3wwhz5fYYG56dL8naobwmFFQ6bzsx8anKS\n3vukVJJUUd3gjNsYinTqY2DffQDoTYR6AIhz9pjNyKI8SdKgPKtTX3ygQuGw6VpdXbFDe3KSz3nb\n9puQqtpGSZIv8lWMTj2AREeoB4A4tytyk+yIohxJUnogSf1z0tTYHNL+Q9VultYpezcb+4mxpik1\ntOnGV9TUt1tPqAeQ2Aj1ABDndu2L7tS3fd+rO+DYnXo71De127LS3mPfHr9h9xsAiY5QDwBxzh6/\nGTEw1zlmv+/VHXDszrs/Ml8TMqPHhOoamtutZ6YeQGIj1ANAnLNn0UcWtYZ6+32v3ixrz8jbnXp7\n9r8g17rJt77djbF06gEkOkI9AMS5zw5WSZKGFuY4x4YOyJYk7f28ypWavoi9m439cKlQKCxJGhUZ\nG6qNdOrtBj4z9QASHaEeAOJYfWOzGppalJLsV3og2Tmen23tgNP+hlOvsDv19j70LWEr1A8faH1j\nUtcYCfUyo9YDQKIi1ANAHLNvKM3LDDpPX7Vftz3vNXbn3Q719vjNwPyMyHmrk9/aqWemHkBiI9QD\nQBwrr24N9W3lZQWjznuNPSPvN+xOvZXeC/OsUN/QaIX4cCTVM1MPINER6gEgjjmd+qx2od7jnXpn\nnMaInqkfkGuFevtGWSfUM34DIMER6gEgjnXWqc/NDDjnTdN7T5W1a7LftkRCff/sNBlGa2feDvse\n/CMAQJ8i1ANAHKuobpDUsVMfTE1WMDVJzS3hDnu+e4Ed0u23zZFOfFZ6qtIDKc66UDg6/ANAoiLU\nA0Aca+3UBzqcc0ZwPDhX375T39RideQzginKCLaG+pZQKLKujwsEAI8h1ANAHOtspr7tMS/O1dsZ\nvfVGWGuGvn2oD4Ui4V+kegCJjVAPAHGss5n6tse83am3XttbXKYH2nXqw8zUA4BEqLine truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7a31e48>"
+       "<matplotlib.figure.Figure at 0x7b36358>"
       ]
      },
      "metadata": {},
@@ -1375,9 +1375,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x83492e8>"
+       "<matplotlib.figure.Figure at 0x87b6e48>"
       ]
      },
      "metadata": {},
@@ -1406,9 +1406,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAEtCAYAAACIx59SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": 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truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7ab1a58>"
+       "<matplotlib.figure.Figure at 0x7bff6d8>"
       ]
      },
      "metadata": {},