Reran cells so output is correct.

06-Multivariate-Kalman-Filters.ipynb

@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 114,
    "metadata": {
     "collapsed": false
    },
@@ -264,7 +264,7 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 69,
+     "execution_count": 114,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -369,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 115,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -379,7 +379,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtYAAAEgCAYAAACQMzRfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9c97f60>"
+       "<matplotlib.figure.Figure at 0x806e5c0>"
       ]
      },
      "metadata": {},
@@ -409,7 +409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 116,
    "metadata": {
     "collapsed": true
    },
@@ -481,7 +481,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 117,
    "metadata": {
     "collapsed": false
    },
@@ -493,7 +493,7 @@
        "       [  4.5]])"
       ]
      },
-     "execution_count": 72,
+     "execution_count": 117,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -516,7 +516,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 118,
    "metadata": {
     "collapsed": false
    },
@@ -528,7 +528,7 @@
        "       [  4.5]])"
       ]
      },
-     "execution_count": 73,
+     "execution_count": 118,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -547,7 +547,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 119,
    "metadata": {
     "collapsed": true
    },
@@ -586,7 +586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 120,
    "metadata": {
     "collapsed": false
    },
@@ -598,7 +598,7 @@
        "       [   0.,  400.]])"
       ]
      },
-     "execution_count": 75,
+     "execution_count": 120,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -617,7 +617,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 121,
    "metadata": {
     "collapsed": false
    },
@@ -629,7 +629,7 @@
        "       [   0.,  400.]])"
       ]
      },
-     "execution_count": 76,
+     "execution_count": 121,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -734,7 +734,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 122,
    "metadata": {
     "collapsed": false
    },
@@ -764,7 +764,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 123,
    "metadata": {
     "collapsed": false
    },
@@ -796,7 +796,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 124,
    "metadata": {
     "collapsed": false
    },
@@ -833,7 +833,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 125,
    "metadata": {
     "collapsed": false
    },
@@ -845,7 +845,7 @@
        "       [ 120.,  400.]])"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 125,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -865,7 +865,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 126,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -875,7 +875,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt4AAAEWCAYAAABRx5AbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xt8zvX/x/HHtZOxsbGaYXM+JjlNbCHnQ0V89a0fRXRw\nlkNSpJy+RCoqQn0rfRWhQiWnQgsjpzGHUJFTGzmMjdnp+v3xtjGGza7T7Hm/3a7bde36vK+P1/Vh\n87zeex8sVqvVioiIiIiI2JWbswsQEREREckPFLxFRERERBxAwVtERERExAEUvEVEREREHEDBW0RE\nRETEARS8RUREREQcQMFbRERERMQBbBq8p0+fTs2aNfHz88PPz4/w8HB++OGHTG1Gjx5NqVKlKFSo\nEE2bNmXPnj22LEFERERExCXZNHiHhITw5ptvsn37drZu3UqzZs3o0KED0dHRAEyaNIl33nmHadOm\nsXnzZgIDA2nZsiXx8fG2LENERERExOVY7L1zZUBAABMnTuS5556jZMmSvPDCCwwfPhyAxMREAgMD\neeutt+jZs6c9yxARERERcSq7jfFOTU3lyy+/JCEhgfDwcA4ePEhsbCytWrXKaOPt7U3jxo3ZsGGD\nvcoQEREREXEJHrY+YXR0NGFhYVy6dAlfX18WLVpE9erVM8J18eLFM7UPDAzk+PHjti5DRERERMSl\n2Dx4V61alZ07dxIXF8fChQvp1q0ba9euvelrLBZLpq/j4uJsXZaIiIiIiMP4+fld95zNh5p4enpS\nvnx5ateuzYQJE6hVqxZTpkyhRIkSAMTGxmZqHxsbS1BQkK3LEBERERFxKXZfxzs1NZWkpCTKlStH\nUFAQK1euzDiWmJjIunXrCA8Pt3cZIiIiIiJOZdOhJq+88gqPPPIIwcHBnD9/nrlz5/Lzzz9nrOU9\naNAgJkyYQNWqValUqRL/+c9/KFy4MF26dLnhObPqpk+3ZcsWAEJDQ235NiSbdP2dR9feuXT9nUvX\n33l07Z1L1995snvtbzVc2qbBOzY2lqeeeoqYmBj8/PyoWbMmy5cvp2XLlgAMGzaMixcv0q9fP86c\nOUODBg1YuXIlPj4+tixDRERERMTl2DR4f/rpp7dsM2rUKEaNGmXLP1ZERERExOXZfYy3iIiIiIgo\neIuIiIiIOISCt4iIiIiIAyh4i4iIiIg4gIK3iIiIiIgDKHiLiIiIiDiAgreIiIiIiAMoeIuIiIiI\nOICCt4iIiIiIAyh4i4iIiIg4gIK3iIiIiIgDKHiLiIiIiDiAgreIiIiIiAMoeIuIiIiIOICCt4iI\niIiIAyh4i4iIiIg4gIK3iIiIiIgDKHiLiIiIiDiAgreIiIiIiAMoeIuIiIiIOICHswsQEZHbkJYG\np09DbGzm24kTmb8+dQqSkyElBVJTzX1KCri5gYeHubm7m3tfXwgMhOLFOe3nxwE3N054eHDGw4Mz\nFgsNmzWjbosW4O2dqZRhw4Yxc+ZMPDw88PT0zLiNGDGC559//rrSFy9eTEREBCEhIQQHBxMcHExI\nSAhBQUF4eOi/JRG5c+knnIiIK0tJgQMHIDoadu40t+hoOHLEBGlb27OHwcDULA5NnDKFugB+flCt\nGtSoAffdh/vx45w/f/669vHx8Vn+ET/++CPTp0+/7vlJkyYxbNiwLM9TqFAh3Nz0S1oRydsUvEVE\nXMXJk7Bjx5VwvXMn7N4Nly5l3b5o0Ywe6ozbtV/fdRd4eXE+MZHIqCh++fVXtu/axb4DB+jxf//H\niAEDTLhPTob4eIiNJeTTT/H56isq+/tTwsuLomlpFE1Opk5aGpw7B3FxsHGjuQGvAq8AKSVKkHzP\nPSRXqUJypUoUrVfPnPuaXuzHH3+c0qVLc/ToUY4ePcqRI0c4evQopUuXzvJtvvjii8ybN4+aNWtS\nt25dihcvzn333WfDCy8i4hgK3iIiznLhAvzyC6xaBStXmrCdlTJl4L77zO1yLzPly0OBAtn6Y/77\n3//Sq1cv0tLSMj2/+9AhCArK3LhGDfo3bszgzz/HYrFcfzKr1XxA2L07owfeNzoadu2Cv/82t59+\nutLe3x+aNYNWraBlSyhfnsaNG9O4ceNs1Q5w9OhRzp8/z7p161i3bl3G819//TX/+te/sn0eERFn\nU/AWEXGUtDTTo50etNety9ybXbAg1K59JWTfdx/ce68Z2nELv//+O7GxsTzwwAPXHatSpQpubm7U\nq1ePhg0b0qBBA6pWrUrFihWzPJeXl9eN/yCLxfSqBwZC06ZXnk9NhT/+yNxbHxUFhw7BN9+YG0CF\nCiaAt2plXu/vf8v3tnTpUk6cOMH27dv59ddfWbZsGbt27aJevXpZto+NjaV48eK3PK+IiKMpeIuI\n2NO5c7B4MaxYYQL3yZNXjlksULfulSAaHp7tXmyr1UpUVBRff/01X3/9Nb/99hvVqlVjz54917UN\nCwvj7Nmz+Pj42OpdXc/dHSpXNrfHHrvy/MGDVz5o/PSTCed//AEzZ5oJnvXrm/ffoQPUqmWuSRYC\nAwNp3bo1rVu3pm3btqSlpRESEnJdu6SkJKpUqUKJEiXo0KEDHTp0oF69ehofLiIuQcFbRMTWUlPh\nxx/hs89g0SJITLxyLDjYhOxWraB5czMGO4fOnDlD3bp1OXjwYMZzxYoVo3r16qSkpFy3MoiHh4fz\nVgspVw569jS31FTYsuVKEI+MvHIbO9YMo3n6aXjyyeuHwFzjRkH6wIEDuLm58dtvvzFx4kQmTpxI\niRIl+Ne//sW7776Lu7u7Pd6liEi2KHiLiNjKnj0mbH/+ORw/fuX5Bx+Ef/3LhO0qVW7Yq5tdRYsW\npVChQhQvXpyOHTvSqVMnHnzwQTw9PXP5BuzM3d30cNevDyNHwvnzsHYtLFsG8+ebISpDh8LLL0Pr\n1tCtGzz66HXLF95M9erViY2N5ZdffmHx4sUsXryYI0eO8Oeffyp0i4jTKXiLiOTGP//Al1+awL1l\ny5XnK1Qwvbddu0LZsjk+7a5du5gxYwa9evXKcgWP5cuXU6JEibwdJgsXhnbtzG3qVFi61FzHpUvh\nhx/Mzc8PnnjCXMuwsGx9aPH09KRZs2Y0a9aMd999l23btlEgm0N4RETsScFbROQ2FNy3DyZPNkNJ\nkpPNk0WKXAmJ4eE57tlOSkpi0aJFfPDBB0RERACmdzur4B0cHJzr9+BSvLygY0dzO3kS5s2D//0P\ntm6FDz80t0qVYPBgLPfdhzWbQdpisVC3bt0bHu/fvz9JSUm88MIL3HvvvbZ6NyIiWVLwFhHJiXXr\nqPTyy/ht2GC+dnODtm1N2G7f3qxMchtWrlxJt27diI2NBcDX15euXbvSuXNnW1Wed9x9N7zwgrnt\n2mUC+Oefm42E+valRkAAsU8+aYbtFC5823/MuXPn+Pjjj0lMTOSjjz6iZcuWTJw4kTp16tjwzYiI\nXKFp3iIit2K1mlVJGjeGRo3w27CBVG9vGDIE/vrLDIl44onbDt0AFStW5MSJE1SvXp0PPviA48eP\n88EHH1C9enUbvpE86N574c034fBhWLAAatfG69QpQt57z6xvPno0nDp1W6cuUqQI27dvp1+/fvj4\n+LBq1SpCQ0Pp0aPHdWuei4jYgoK3iMiNpKXB119DaCi0aWM2u/H35/izzxL93Xfw9ttmlZIcuHSD\nXSjLly/Pjh07iI6Opk+fPhTORU/uHcnDA/79b9i6lf1Tp3K+Zk04cwbGjDEBfOjQzBNas6lq1apM\nmzaNI0eOMHToUDw8PLBYLFp+UETsQj9ZRESulZZmhjZUr27WpN62zWy/PmkS/PUXx3v3JiUbG79c\nLT4+nsmTJ1O6dGm2bt2aZZsaNWpkvVukXGGxcO6BB9j33/9CRIRZ/SQhwXwIKlcOeveGI0dyfNqi\nRYsyefJk9u7dy4QJE+xQuIiIgreISGZbtpjVM7p2hd9+g9KlYdo0sxHMsGFmAmUOnDt3jjfeeIOy\nZcsybNgwTpw4wfz58+1UfD7TqBEsX27+zjp1MpNcZ82CqlXhjTcy7wqaTRUqVCDoBmuI//bbb7mt\nWETyOQVvEREw44R79YL774dff4USJeCTT+D336FfvxyP37548SKTJ0+mUqVKjBgxglOnThEWFsby\n5cuZNGmSnd5EPlW3Lnz1FezebQL4hQswYoTZkGf5cpv8Edu2beOee+6hT58+XLhwwSbnFJH8R8Fb\nRPK31FSzfXnlymbJOnd3eOkl2LcPevSAHG5Kk5yczKxZs6hYsWJGD3dYWBirVq1i/fr1tG7dWsNJ\n7KVaNRPAV60yvd4HDpgVZzp2hEOHcnXqvXv34unpycyZMwkNDWXHjh22qVlE8hWbBe833niDevXq\n4efnR2BgIO3bt2f37t3XtRs9ejSlSpWiUKFCNG3alD179tiqBBGRnNm40fRw9+kDp0+bLdx37jSr\naNzG5MYFCxZwzz330Lt3b44fP07t2rVZtmwZ69evp0WLFgrcjtKiBezYYf4efXxg8WITyseOhcTE\n2zrlk08+yaZNm6hatSp79+7l/vvv591338Vqtdq4eBG5k9kseP/888/079+fyMhIVq9ejYeHBy1a\ntODMmTMZbSZNmsQ777zDtGnT2Lx5M4GBgbRs2ZL4+HhblSEicmsnTsAzz5ix3Nu2mZVJFiwwPaXV\nqt32aVetWsXvv/9O5cqVWbBgAVu2bKFNmzYK3M7g5XXlNxedO5vAPWqUmTD73Xe3dcpatWqxdetW\nevXqRVJSEmPGjMlYd11EJDtstoHO8mvG0c2ZMwc/Pz82bNjAww8/jNVqZerUqQwfPpyOHTsC8Nln\nnxEYGMjcuXPp2bOnrUoREbmxZcvMZjcnT5phJEOHwquvmp7RXJo4cSL169ene/fueLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9a5d6d8>"
+       "<matplotlib.figure.Figure at 0x896ef28>"
       ]
      },
      "metadata": {},
@@ -937,7 +937,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 127,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -950,7 +950,7 @@
        "       [ 0.001175  ,  0.0235    ]])"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 127,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -987,7 +987,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 128,
    "metadata": {
     "collapsed": false
    },
@@ -1031,7 +1031,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 129,
    "metadata": {
     "collapsed": false
    },
@@ -1040,7 +1040,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtYAAAEgCAYAAACQMzRfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9be2c50>"
+       "<matplotlib.figure.Figure at 0x7e7b518>"
       ]
      },
      "metadata": {},
@@ -1106,7 +1106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 130,
    "metadata": {
     "collapsed": true
    },
@@ -1145,7 +1145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 131,
    "metadata": {
     "collapsed": true
    },
@@ -1185,7 +1185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 132,
    "metadata": {
     "collapsed": false
    },
@@ -1204,7 +1204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 133,
    "metadata": {
     "collapsed": false
    },
@@ -1245,7 +1245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 134,
    "metadata": {
     "collapsed": true
    },
@@ -1282,7 +1282,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 135,
    "metadata": {
     "collapsed": false
    },
@@ -1366,7 +1366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 136,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1374,9 +1374,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE6CAYAAACFw+2FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE6CAYAAACFw+2FAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9b33208>"
+       "<matplotlib.figure.Figure at 0xc73c908>"
       ]
      },
      "metadata": {},
@@ -1386,7 +1386,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtoAAAEoCAYAAABmXFa8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9b2cf28>"
+       "<matplotlib.figure.Figure at 0x7c99470>"
       ]
      },
      "metadata": {},
@@ -1425,7 +1425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 137,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1435,7 +1435,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAE5CAYAAACZGEi2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9b65e80>"
+       "<matplotlib.figure.Figure at 0xbc629e8>"
       ]
      },
      "metadata": {},
@@ -1512,7 +1512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 138,
    "metadata": {
     "collapsed": false
    },
@@ -1521,7 +1521,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvEAAAEoCAYAAADR4a6bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88ab6a0>"
+       "<matplotlib.figure.Figure at 0x9b23d68>"
       ]
      },
      "metadata": {},
@@ -1560,7 +1560,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 139,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1570,7 +1570,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuwAAAFQCAYAAADkwCtvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x46fa6a0>"
+       "<matplotlib.figure.Figure at 0xb567908>"
       ]
      },
      "metadata": {},
@@ -1624,7 +1624,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 140,
    "metadata": {
     "collapsed": false,
     "scrolled": true
@@ -1634,7 +1634,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtYAAADICAYAAADMU6YEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9bb3588>"
+       "<matplotlib.figure.Figure at 0x9992ba8>"
       ]
      },
      "metadata": {},
@@ -1794,7 +1794,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 141,
    "metadata": {
     "collapsed": false
    },
@@ -1814,7 +1814,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 142,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1824,7 +1824,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuoAAAEjCAYAAABkaCRHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xcbdaba8>"
+       "<matplotlib.figure.Figure at 0x9c7c240>"
       ]
      },
      "metadata": {},
@@ -1905,7 +1905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 143,
    "metadata": {
     "collapsed": false
    },
@@ -1914,7 +1914,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuoAAAEjCAYAAABkaCRHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x99de438>"
+       "<matplotlib.figure.Figure at 0xbc0de80>"
       ]
      },
      "metadata": {},
@@ -1934,7 +1934,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 144,
    "metadata": {
     "collapsed": false
    },
@@ -1943,7 +1943,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvMAAAEjCAYAAAC/045lAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xbbfafd0>"
+       "<matplotlib.figure.Figure at 0x9b7a0f0>"
       ]
      },
      "metadata": {},
@@ -1986,7 +1986,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 145,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -1996,7 +1996,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE/CAYAAADVDnw2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xl8TNf7wPHPvUkm+4qQxL4TW4m9JWqniir1pQtaraJK\n22+raKlvS/2qaKuli5YuWqpq30msofY9RBYSkUQ22SfJ3PP7Y2QmaSzZI5z369VX59y5d+6ZuOS5\n5z7nOYoQQiBJkiRJkiRJ0kNLLe8OSJIkSZIkSZJUumTQL0mSJEmSJEkPORn0S5IkSZIkSdJDTgb9\nkiRJkiRJkvSQk0G/JEmSJEmSJD3kZNAvSZIkSZIkSQ85GfRLkiRJkiRJ0kNOBv2SJEmSJEmS9JCz\nLO8OSJIkSQ++I0eOcPDgQZKTkwkICGDatGl06dKlvLslPaLk9ShJhSeDfkmSJOme0tLSWLduHXPn\nzgXgr7/+om/fvgQFBeHp6VnOvZMeNfJ6lKSikek9kiRJ0j1duXKFefPmERISAkCvXr1IT0/n0KFD\n5dwz6VEkr0dJKhoZ9EuSJEn31KJFCw4dOkTdunUBCA8PB6BBgwbl2S3pESWvR0kqGhn0S9JDTFXV\nPP9ZWFjg6upK586dWbx4MdnZ2eXdxQonPj6eZcuWMWTIEBo2bIi9vT3Ozs506NCBL7/88o4/06Ic\nU7t27Xx/fjn/eXh4lMVXzaNDhw6m13PnzmXy5Mm0bNmy1M976tQpXnnlFRo0aICDgwNOTk54e3sz\nefJkrl69WurnfxgV5XoEiIiI4OWXX8bT0xMbGxvq1KnDlClTSExMLONvUH7XoyRVZIoQQpR3JyRJ\nKh2qqqIoCjNnzgQgOzubsLAw1q5dS1paGk8//TTr1q0r515WLEuXLmX8+PFUrVqVbt26UadOHW7e\nvMmGDRuIiYnh8ccfZ9euXeh0umIdU7t2ba5du8asWbPy9cHBwYG33nqrLL5uPsuWLSMwMJDPPvus\n1M81Y8YM5syZg6WlJd27d6dFixZomsY///zD/v370el0LF26lFGjRpV6Xx4mRbkeQ0JC6NSpEzEx\nMQwaNIjGjRtz5MgR/Pz8aNSoEQcPHsTNza3Mv0tZXo+SVOEJSZIeWoqiCFVV822/fPmycHBwEIqi\niL1795ZDzyquPXv2iA0bNghN0/JsT0pKEo899phQFEUsWLCg2MfUqlXrjn925WnTpk3ixx9/FEII\nkZGRIcLCwkrtXB9//LFQFEXUqlVLnD59Ot/7fn5+ws3NTSiKItavX19q/XgYFeV67NWrl1AURSxe\nvDjP9rfeeksoiiLGjRtX6v3+t7K8HiXpYSCDfkl6iN0t6BdCiH79+glFUcTnn39e6M8NCAgQiqKI\nAQMG3HWfNm3aCFVVTb+If/rpJ/HMM8+IOnXqCFtbW+Hk5CQ6d+4sfv755zseHxoaKhRFEb6+vuL6\n9eti9OjRolq1asLCwkKsW7eu0H0uCytXrhSKooinn3662Mc8aEG/v7+/WLZsmYiKihI3btwQa9eu\nFQEBAaVyrrCwMGFpaSl0Op04c+bMXffbvHmzUBRFeHh4CL1eX+DPL8r1K8Sjew1fuXJFKIoi6tat\nm2//5ORkYW9vLxwcHERqamqZ9bMsr0dJeljIkp2S9IgStzP7rKysCn1shw4daNy4Mdu2bePmzZtU\nqVIlz/vnz5/nxIkT+Pr6UqtWLQDGjx9Ps2bN8PX1xcPDg9jYWLZs2cJLL71EYGAgn3zyyR3PFRcX\nR6dOnXBxceG5555D0zQqVapU6D6XBUtLyzz/L+4xQghWr15NcHAwNjY2NG/eHF9f30J9fkkICQlh\nwIABpKSkmLYpisKtW7dK5Xw//vgjBoOBIUOG0Lx587vu169fP3x8fDh27Bh///03zz33XIE+vyjX\nLzy617Cfnx9grJLzbw4ODnTu3JmdO3dy+PBhnnzyyVLvY1lfj5L0sJBBvyQ9gi5evMjevXtRFIXH\nH3+8SJ8xatQopk6dym+//cbkyZPzvLdixQrTPjnOnz9PnTp18uyXlZVF3759+b//+z/Gjx+Pl5dX\nvvOcO3eOF198kR9//BFVLVjtgUWLFhVqcmGdOnV46aWXCrz/3SxbtgyAPn36FPsYRVEAGD58eJ7t\nNWrU4Mcff6R79+4FPsfff/+Nn58fZ8+eZfny5cTGxrJ27VqEEBw6dIh33nmHPn36sGjRIqKjo0lP\nTyc8PJxffvkFJycn6tatS1JSUoHPV1wHDhwAoGfPnvfdt2fPnhw7doz9+/cXOOiHwl+/8Ohew5cu\nXQKgYcOGdzymQYMG7Ny5k6CgoAIF/RXtepSkh0b5PmiQJKk0KYoiFEURs2bNEjNnzhTTp08XI0eO\nFLa2tkJVVfHuu+8W+bMjIyOFpaWlaNWqVZ7t2dnZwsPDQzg6Ohbocf9ff/0lFEXJlyKRkxphY2Mj\nbt68Wai+1a5d2/TdC/Jft27dCvX5d7Jw4UKhKIpo06aNyM7OLvYxH330kfDz8xMxMTEiPT1dnDt3\nTowbN06oqipsbGzE8ePHC3SOjIwM8dZbbwkhhPDx8RGPP/64WLRoken9efPmCXd3dzFx4kRx8eJF\n0/YmTZqIjz76qEDnKGlNmjQRiqKI7du333ffb775RiiKIgYOHFioc5TU9SvEw38Njx07ViiKIpYt\nW3bH46ZNmyYURRGffvrpfc9REa9HSXpYyJF+SXoEfPTRR/m2ffLJJ7z//vtF/kwPDw969uzJtm3b\nOH36tKlc3o4dO4iKimLUqFHY2dmZ9r927Rrz5s1j9+7dhIeHk56enufzIiMj73ie2rVrU7ly5UL1\nLTQ0tJDfpnh+++033n77bby8vFi7di0WFhbFPubDDz/M0/b29mbJkiU4ODjw+eefM3v27AJVXvL3\n96dr164IIQgODqZXr168+eabpvctLS2JjY1l6NChNG7c2LTdysqKmzdv3vfzHxQZGRmF2r+w1y/I\na7gkPCrXoyQ9iGSdfkl6yCmKgqZpaJpGWloa/v7+NGrUiBkzZvDHH38U67NHjx4NmNMhcr/OnRoR\nEhJC69at+fbbb/H09GTs2LF88MEHzJo1y5SSoNfr73iOatWqFauPpe3nn3/mxRdfpEaNGuzdu5ea\nNWuWyjE5xo0bB8DBgwcLtH+LFi3o3bs3p06dIjExkSlTpuR5/+jRozRv3pwuXbqYtiUnJ3Px4sVy\nq3uesw7BtWvX7rtvzsJM7u7uhT5PQa9feLSvYWdnZ4C75sznbHdxcbnvuSri9ShJDws50i9JjxAb\nGxu6dOnCtm3b8Pb25tVXX8XX17fIQcnAgQNxdXVl5cqVzJ8/n6SkJNavX0/dunXz/NJesGAB8fHx\nLF++nBdffDHPZ/z+++95gq5/y8ltL4yyyof+7rvvGDduHHXr1mXPnj0FCt6LckxuOSPGqampBdo/\nJ4D28/PD3t6etm3b5nl/7969+XLhN2/ejKZp9O/fv1B9KylPPPEEfn5+7Ny5k1deeeWe++7atQsA\nHx+fQp+noNcvPNrXcM6Ie05u/78FBQUBd8/5z60iXo+S9NAo7/wiSZJKz71Kds6ePVsoiiLGjh1b\nrHOMHz9eKIoiNmzYIJYuXSoURcmXe9u7d2+hqqpISUnJd/xrr712x2Ny8qGLkqtcFvnQixYtEoqi\niEaNGonr16+X2jH/tm3bNqEoivD29i7Ucf379xd9+vTJs+3SpUt3rHM/cOBA0b17dyGEEBEREYUq\nh1kSrl69KqysrIROpxNnz569635btmwx5cwX9edZkOtXiEf7Gg4ODjaV7LxTbf+ckp1paWkFPndF\nuh4l6WEhg35JeojdK+hPTk4WVapUEVZWVuLy5ctFPsfRo0eFoihiyJAhomPHjsLCwiLfIjnjxo0T\niqKIjRs35tm+bds2YWFhUeIBU2mbM2eOUBRFNGvWTERHR5f4MRcvXrxjcBkaGirq168vFEURc+fO\nLXB/s7OzhbOzc76Jlt9++62wsLAQiYmJpm2JiYlCp9OJX3/9VQghxIQJE0RWVlaBz3UnL730kmlC\neUHlLM5Vu3btO9bq9/f3Ny3OVZwJngW5foWQ13Dv3r2Foijiq6++yrN9ypQpQlEU8frrrxf43OV9\nPUrSo0qm90jSI8rBwYGpU6fyzjvv8MEHHxQ5v9/Hxwdvb282bNhAdnZ2vtrmYKxv/tNPPzF06FCe\nffZZPDw8OHfuHNu3b2fYsGGsWrWqJL5SmVixYgXTp09HURR8fX355ptv8u3j6uqaZ3JiYY/5448/\n+Pzzz+natSs1a9bE0dGR4OBgNm/ejF6vp3///rzzzjsF7vPRo0dJSkrC19c3z3Z/f38ee+wxU842\nQHBwMFlZWQwYMIDz589To0aNYq8LoGkaADqdrsDHTJ8+nbS0NObOnUvr1q3p0aMHzZs3R9M0jh07\nxr59+1AUhRdeeCHfpOfCKMj1C/Ia/uabb+jUqROTJk1i9+7dNG7cmCNHjpjmCN1tjYI7Ke/rUZIe\nWeV91yFJUum510i/EEKkp6cLLy8vYWFhIU6dOlXk88yfP990rhUrVtxxn0OHDoknn3xSuLq6CkdH\nR/HEE0+I9evXC39//wo1Sjpr1izTd71bqkWdOnWKdczevXvFf/7zH9GoUSPh4uIirKyshLu7u+jV\nq5f45ZdfCt3nv//+W7Rs2VIYDIY823v16iW+/PLLPNs0TRPDhw8Xr732mpg6dWqBy4/eS8uWLYVO\npxOhoaGFPvbEiRPi5ZdfFvXq1RO2tramn5ezs7NYs2ZNsfsmRMGuXyEe7WtYCGNqzZgxY4SHh4fQ\n6XSidu3aYsqUKXlG5guivK9HSXpUKULcXpbzAXfjxg2mTp3K1q1bSU5Opm7duixZsLine truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xb56b6d8>"
+       "<matplotlib.figure.Figure at 0xc768be0>"
       ]
      },
      "metadata": {},
@@ -2006,7 +2006,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE/CAYAAADVDnw2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xb7736a0>"
+       "<matplotlib.figure.Figure at 0x7c869e8>"
       ]
      },
      "metadata": {},
@@ -2046,7 +2046,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 146,
    "metadata": {
     "collapsed": false,
     "scrolled": false
@@ -2056,7 +2056,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE/CAYAAADVDnw2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xbc24a90>"
+       "<matplotlib.figure.Figure at 0x9c4eef0>"
       ]
      },
      "metadata": {},
@@ -2077,7 +2077,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 147,
    "metadata": {
     "collapsed": false
    },
@@ -2086,7 +2086,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE/CAYAAADVDnw2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x88d0358>"
+       "<matplotlib.figure.Figure at 0xbc41e48>"
       ]
      },
      "metadata": {},
@@ -2108,7 +2108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 148,
    "metadata": {
     "collapsed": false
    },
@@ -2117,7 +2117,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAv0AAAE/CAYAAADVDnw2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9c3a7f0>"
+       "<matplotlib.figure.Figure at 0xb6465f8>"
       ]
      },
      "metadata": {},
@@ -2155,7 +2155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 149,
    "metadata": {
     "collapsed": false
    },
@@ -2164,7 +2164,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAE9CAYAAACLEZ3JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9b3f780>"
+       "<matplotlib.figure.Figure at 0xbbcf9b0>"
       ]
      },
      "metadata": {},
@@ -2174,7 +2174,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtsAAAEoCAYAAACJnj2CAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9c4ceb8>"
+       "<matplotlib.figure.Figure at 0x9a10c88>"
       ]
      },
      "metadata": {},
@@ -2209,7 +2209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 150,
    "metadata": {
     "collapsed": false
    },
@@ -2218,7 +2218,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAE9CAYAAACLEZ3JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9bd7128>"
+       "<matplotlib.figure.Figure at 0x9bf6e10>"
       ]
      },
      "metadata": {},
@@ -2228,7 +2228,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtIAAAEoCAYAAAB1ixZIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x99954e0>"
+       "<matplotlib.figure.Figure at 0x9c3a9e8>"
       ]
      },
      "metadata": {},
@@ -2253,7 +2253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 151,
    "metadata": {
     "collapsed": false
    },
@@ -2262,7 +2262,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAE9CAYAAACLEZ3JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa205c50>"
+       "<matplotlib.figure.Figure at 0x9cdc940>"
       ]
      },
      "metadata": {},
@@ -2287,7 +2287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 152,
    "metadata": {
     "collapsed": false
    },
@@ -2296,7 +2296,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAvUAAAE9CAYAAACLEZ3JAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xc7666a0>"
+       "<matplotlib.figure.Figure at 0x9c28828>"
       ]
      },
      "metadata": {},
@@ -2327,7 +2327,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 153,
    "metadata": {
     "collapsed": false
    },
@@ -2336,7 +2336,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt0AAAEXCAYAAABxrPi9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x99899e8>"
+       "<matplotlib.figure.Figure at 0xbc16a20>"
       ]
      },
      "metadata": {},
@@ -2346,7 +2346,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt0AAAEkCAYAAADzQo2+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0xa1de828>"
+       "<matplotlib.figure.Figure at 0xb56ef28>"
       ]
      },
      "metadata": {},
@@ -2429,7 +2429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 154,
    "metadata": {
     "collapsed": false
    },
@@ -2438,7 +2438,7 @@
      "data": {
       "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhEAAAEmCAYAAADcCcKaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9b1d390>"
+       "<matplotlib.figure.Figure at 0x9a290b8>"
       ]
      },
      "metadata": {},
@@ -2489,7 +2489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 155,
    "metadata": {
     "collapsed": false
    },
@@ -2564,16 +2564,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 156,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtMAAAEPCAYAAACA4Ej4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtMAAAEPCAYAAACA4Ej4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x8924c88>"
+       "<matplotlib.figure.Figure at 0xa1de278>"
       ]
      },
      "metadata": {},
@@ -2615,16 +2615,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 157,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAEWCAYAAAAq41LXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuYAAAEWCAYAAAAq41LXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x9580278>"
+       "<matplotlib.figure.Figure at 0x9b35cf8>"
       ]
      },
      "metadata": {},
@@ -2656,16 +2656,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 158,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuoAAAEWCAYAAAAw37JZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuoAAAEWCAYAAAAw37JZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x92272e8>"
+       "<matplotlib.figure.Figure at 0x9b0e2e8>"
       ]
      },
      "metadata": {},
@@ -2697,7 +2697,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 159,
    "metadata": {
     "collapsed": true
    },
@@ -2715,16 +2715,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 160,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt0AAAEWCAYAAAC68CsYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt0AAAEWCAYAAAC68CsYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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 truncated
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x948ee10>"
+       "<matplotlib.figure.Figure at 0x9c50828>"
       ]
      },
      "metadata": {},