{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n",
    "___\n",
    "# Matplotlib Styling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `matplotlib.pyplot` module under the name `plt` (the tidy way):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# COMMON MISTAKE!\n",
    "# DON'T FORGET THE .PYPLOT part\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**NOTE: For users running .py scripts in an IDE like PyCharm or Sublime Text Editor. You will not see the plots in a notebook, instead if you are using another editor, you'll use: *plt.show()* at the end of all your plotting commands to have the figure pop up in another window.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(0,10)\n",
    "y = 2 * x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Legends"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the **label=\"label text\"** keyword argument when plots or other objects are added to the figure, and then using the **legend** method without arguments to add the legend to the figure: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x151b84e0c08>"
      ]
     },
     "execution_count": 83,
     "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": [
    "fig = plt.figure()\n",
    "\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "\n",
    "ax.plot(x, x**2, label=\"x**2\")\n",
    "ax.plot(x, x**3, label=\"x**3\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how legend could potentially overlap some of the actual plot!\n",
    "\n",
    "The **legend** function takes an optional keyword argument **loc** that can be used to specify where in the figure the legend is to be drawn. The allowed values of **loc** are numerical codes for the various places the legend can be drawn. See the [documentation page](http://matplotlib.org/users/legend_guide.html#legend-location) for details. Some of the most common **loc** values are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lots of options....\n",
    "\n",
    "ax.legend(loc=1) # upper right corner\n",
    "ax.legend(loc=2) # upper left corner\n",
    "ax.legend(loc=3) # lower left corner\n",
    "ax.legend(loc=4) # lower right corner\n",
    "\n",
    "# .. many more options are available\n",
    "\n",
    "# Most common to choose\n",
    "ax.legend(loc=0) # let matplotlib decide the optimal location\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.legend(loc=(1.1,0.5)) # manually set location\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting colors, linewidths, linetypes\n",
    "\n",
    "Matplotlib gives you *a lot* of options for customizing colors, linewidths, and linetypes. \n",
    "\n",
    "There is the basic MATLAB like syntax (which I would suggest you avoid using unless you already feel really comfortable with MATLAB). Instead let's focus on the keyword parameters.\n",
    "\n",
    "### Quick View:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Colors with MatLab like syntax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With matplotlib, we can define the colors of lines and other graphical elements in a number of ways. First of all, we can use the MATLAB-like syntax where `'b'` means blue, `'g'` means green, etc. The MATLAB API for selecting line styles are also supported: where, for example, 'b.-' means a blue line with dots:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x151b8c263c8>]"
      ]
     },
     "execution_count": 45,
     "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": [
    "# MATLAB style line color and style \n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x, x**2, 'b.-') # blue line with dots\n",
    "ax.plot(x, x**3, 'g--') # green dashed line"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Suggested Approach: Use keyword arguments\n",
    "\n",
    "### Colors with the color parameter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also define colors by their names or RGB hex codes and optionally provide an alpha value using the `color` and `alpha` keyword arguments. Alpha indicates opacity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x151b8c7fa08>]"
      ]
     },
     "execution_count": 46,
     "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": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.plot(x, x+1, color=\"blue\", alpha=0.5) # half-transparant\n",
    "ax.plot(x, x+2, color=\"#8B008B\")        # RGB hex code\n",
    "ax.plot(x, x+3, color=\"#FF8C00\")        # RGB hex code "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Line and marker styles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linewidth\n",
    "\n",
    "To change the line width, we can use the `linewidth` or `lw` keyword argument. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x151b6dda608>]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Use linewidth or lw\n",
    "ax.plot(x, x-1, color=\"red\", linewidth=0.25)\n",
    "ax.plot(x, x-2, color=\"red\", lw=0.50)\n",
    "ax.plot(x, x-3, color=\"red\", lw=1)\n",
    "ax.plot(x, x-4, color=\"red\", lw=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linestyles\n",
    "\n",
    "There are many linestyles to choose from, here is the selection:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x151b6df5d48>]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# possible linestype options ‘--‘, ‘–’, ‘-.’, ‘:’, ‘steps’\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "ax.plot(x, x-1, color=\"green\", lw=3, linestyle='-') # solid\n",
    "ax.plot(x, x-2, color=\"green\", lw=3, ls='-.') # dash and dot\n",
    "ax.plot(x, x-3, color=\"green\", lw=3, ls=':') # dots\n",
    "ax.plot(x, x-4, color=\"green\", lw=3, ls='--') # dashes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom linestyle dash\n",
    "\n",
    "The dash sequence is a sequence of floats of even length describing\n",
    "the length of dashes and spaces in points.\n",
    "\n",
    "For example, (5, 2, 1, 2) describes a sequence of 5 point and 1 point\n",
    "dashes separated by 2 point spaces.\n",
    "\n",
    "First, we see we can actually \"grab\" the line from the .plot() command"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n"
     ]
    },
    {
     "data": {
      "image/png": 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paUBIIHIBALiEGlq6tXlHuX7ycq18fqsVs9L10NICFaTFOz0NCClELgAAl0BNU5c2lnr03JE6SdKtczL14NJ8ZY+Mc3gZEJqIXAAAAqj8bIc2lHj0wrEGucKM7pyfpQeW5CsjOcbpaUBII3IBAAiAN063qdjt0W+On1J0uEv3LczR5xbnaXRitNPTgGGByAUAYBAdr2tVkbtML71+RnGRLn1+Sb7uvypXI+OjnJ4GDCtELgAAg+Bw9XkVu8tU8uZZJUaH64tXj9d9V+YoOTbS6WnAsETkAgDwEeyvaFKRu0x7PE0aERuhL318ou69IluJ0RFOTwOGNSIXAICLZK3VrrJzKnZ7dLCqWanxUfqXGybrrsuzFBfFUysQDPiXCADAAFlr5X6jUUVuj47VtmhsUrT+/RNTdftl4xQd4XJ6HoC/MKDINcYkS9omaZokK+kz1tp9gRwGAECw8Putfv/aaRW5PXr9VJsyR8ToP1dO161zMxQVTtwCwWigZ3IflvQ7a+0qY0ykpNgAbgIAICj4/Fa/frVBG0o8eutMh/JS4/S922Zqxax0RbjCnJ4H4H18YOQaYxIlLZb0aUmy1vZJ6gvsLAAAnNPv8+t/jtZrY2m5Ks91asLoeD18xywtn5EuV5hxeh6AARjImdw8SWclPWaMmSnpsKQvWms7//JOxpjVklZLUlZW1mDvBAAg4Hq9Pj17uE6bSstVd75bU8YmavM9c3TtlDEKI26BIcVYa9//DsbMk7Rf0pXW2gPGmIcltVlrv3qh3zNv3jx76NChwV0KAECA9PT79JODNdqys0KnWns0a1yyvnB1gZZNTJMxxC0QrIwxh621897rtoGcya2TVGetPfDO289K+qfBGgcAgFM6e716+kC1tu6s1LmOXs3PSdF3V83QVQWpxC0wxH1g5FprTxtjao0xE621b0q6WtLrgZ8GAEBgtPX068l91dq2q0Lnu/p1VUGq1hXO1uV5I52eBmCQDPTVFdZJevqdV1aokHRf4CYBABAYLV19enRPlR7fU6m2Hq8KJ6VpzbICzc0e4fQ0AINsQJFrrT0m6T2vdwAAINid6+jVtl2VenJflTr7fPr41NFaVzhe0zKSnJ4GIED4iWcAgJB1pq1HW3dW6OkD1er1+rV8RrrWLivQxDEJTk8DEGBELgAg5NS3dGtzabl+eqhWPr/VzbMy9NCyfOWPind6GoBLhMgFAISM6qZObSwp13NH6mSMtGpuph5cUqCskfygTmC4IXIBAEOep7FDG0s8euGVBrnCjO6+PEurl+QrIznG6WkAHELkAgCGrDdOt6nI7dGLx08pOtyl+xbmaPXiPKUlRjs9DYDDiFwAwJBzvK5VRe4yvfT6GcVHhevBJfn67FW5Ghkf5fQ0AEGCyAUADBmHq8+ryF2m0jfPKjE6XF+8erzuuzJHybGRTk8DEGSIXABAULPWan9Fs4rcZdpb3qSUuEh96eMT9akrspUQHeH0PABBisgFAAQla612lZ1TkbtML1edV2p8lP7lhsm6e0GWYiN5+gLw/niUAAAEFWuttp9sVFGJR6/UtmhsUrT+/RNTdftl4xQd4XJ6HoAhgsgFAAQFv9/qd6+dVpHbo5On2jQuJUbfvmW6bpmToahw4hbAxSFyAQCO8vr8+s3xUyp2e1TW2KG81Dh977aZWjErXRGuMKfnARiiiFwAgCP6fX49f7ReG0s8qmrq0oTR8Vp/52zdOH2sXGHG6XkAhjgiFwBwSfV6fXr2cJ02lZar7ny3pqYnavM9c3TtlDEKI24BDBIiFwBwSfT0+/TMwRpt2VGh0209mjUuWd9YMVXLJqbJGOIWwOAicgEAAdXZ69VT+6v1w12VOtfRq/m5KfrebTN1ZcFI4hZAwBC5AICAaOvp1xN7q/TI7kqd7+rXovGpWrtsti7PG+n0NADDAJELABhULV19enR3pR7bW6X2Hq8KJ6VpbWGB5mSNcHoagGGEyAUADIpzHb364a4KPbWvWp19Pl03dYzWFhZoWkaS09MADENELgDgIznT1qMtOyr044PV6vX6tXxGutYuK9DEMQlOTwMwjBG5AIAPpe58lzbvKNfPXq6Tz1rdPCtDDy3LV/6oeKenAQCRCwC4OFXnOrWptFzPHamTMdKquZl6cEmBskbGOj0NAP6MyAUADIinsV0bSsr1wrF6hbvCdPflWXpgSb7Sk2OcngYA70LkAgDe18lTbSp2e/TiiVOKDnfps1fl6nOL8pSWGO30NAC4ICIXAPCeXq1rUZHboz+8fkbxUeF6cEm+PntVrkbGRzk9DQA+EJELAPhfDlc3a/12j3a8dVaJ0eH622vG676FuUqKjXB6GgAMGJELAJC1VvsqmlS03aN9FU1KiYvUl6+bqHsXZCshmrgFMPQQuQAwjFlrtbPsnIq2l+lQ9XmNSojSv944WXddnqXYSJ4iAAxdPIIBwDBkrdUfTzaq2F2mV+palZ4UrW+smKpPzhun6AiX0/MA4CMjcgFgGPH7rX574rSKSzw6eapN41Ji9O1bpuvWOZmKDA9zeh4ADBoiFwCGAa/Pr1+/ekrFJR55GjuUlxqn/3vbTK2Yla5wF3ELIPQQuQAQwvp9fj1/pF4bSz2qaurSxNEJKrpztm6YPlauMOP0PAAIGCIXAEJQr9ennx+q06bSctW3dGtqeqI23zNX104ZrTDiFsAwQOQCQAjp7vPpmYM12rKzXGfaejU7K1nfvHmalk4cJWOIWwDDB5ELACGgo9erp/ZXa9uuCp3r6NPluSn6/idnaWH+SOIWwLBE5ALAENbW068f7anSI3sq1dLVr0XjU7WucLzm56Y4PQ0AHEXkAsAQdL6zT4/uqdTje6vU3uPV1ZPStLawQLOzRjg9DQCCApELAEPI2fZebdtVoSf3V6urz6frpo7R2sICTctIcnoaAAQVIhcAhoDTrT3asrNczxysUZ/Xr+Uz0rW2sEATRic4PQ0AghKRCwBBrO58lzaVluvnh+rks1YrZ2fooaX5yhsV7/Q0AAhqRC4ABKGqc53aWOrRL47Uyxhp1dxxemhpvsalxDo9DQCGBCIXAIKIp7FdxW6PfvlKgyJcYbpnQbYeWJKnsUkxTk8DgCGFyAWAIPB6Q5uKS8r02xOnFR3u0v2L8nT/olylJUQ7PQ0AhiQiFwAc9Epti4rcHv3x5BnFR4XroaX5+uxVeUqJi3R6GgAMaUQuADjgUFWz1rs92vnWWSXFROjvrpmgTy/MUVJshNPTACAkELkAcIlYa7WvvElFbo/2VTQpJS5SX75uou5dkK2EaOIWAAYTkQsAAWat1Y63zqrI7dHh6vNKS4jSv944WXddnqXYSB6GASAQeHQFgACx1uoPr59RcYlHr9a1Kj0pWv+xYqpumzdO0REup+cBQEgjcgFgkPn8Vr87cVpF7jK9cbpdWSmx+s4t03XLnExFhoc5PQ8AhgUiFwAGidfn169ebVCx26Pys53KGxWn739ypj4xM13hLuIWAC4lIhcAPqI+r1/PH63TxtJyVTd1adKYBBXfNVvXTxsrV5hxeh4ADEtELgB8SD39Pv38cJ02l5arvqVb0zISteXeufrY5NEKI24BwFFELgBcpO4+n358sEZbd5brTFuv5mQl65srp2nphFEyhrgFgGBA5ALAAHX0evXkvmpt21Whps4+XZ6bou9/cpYW5o8kbgEgyBC5APABWrv79aO9VXp0T6Vauvq1aHyq1hWO1/zcFKenAQAugMgFgAto7uzTo7sr9aO9VWrv9eqayWlaWzhes8YlOz0NAPABiFwA+Ctn23u1bVeFntxfra4+n66fNkZrCws0NT3J6WkAgAEacOQaY1ySDkmqt9YuD9wkAHDG6dYebd5RrmcO1qjf59dNM9O1ZlmBJoxOcHoaAOAiXcyZ3C9KOikpMUBbAMARtc1d2rSjXM8eqpPfWq2cnaGHlhUoNzXO6WkAgA9pQJFrjMmUdKOkb0n6+4AuAoBLpPJcpzaWePT80XqFGaNV8zL14JJ8jUuJdXoaAOAjGuiZ3B9I+rKkC37NzhizWtJqScrKyvroywAgQMrOtKu4xKNfvdKgCFeY7lmQrQeW5GlsUozT0wAAg+QDI9cYs1xSo7X2sDFm6YXuZ63dKmmrJM2bN88O2kIAGCSvNbSq2O3R7147rZgIl+5flKf7F+UqLSHa6WkAgEE2kDO5V0r6hDHmBknRkhKNMU9Za+8J7DQAGBzHaltU7C7TH082KiEqXGuWFugzV+UqJS7S6WkAgAD5wMi11n5F0lck6Z0zuf9I4AIYCl6uatb67WXaVXZOSTER+vuPTdDfLMxRUkyE09MAAAHG6+QCCCnWWu0rb9J6d5n2VzRrZFyk/s91k3TvFdmKj+IhDwCGi4t6xLfWlkoqDcgSAPgIrLUqfeusiraX6UhNi9ISovTV5VN01/wsxUS6nJ4HALjEOK0BYEjz+63+cPKMit0eHa9vVUZyjP7j5mm6bW6moiOIWwAYrohcAEOSz2/12xOnVOz26I3T7cpKidV/3TpdK2dnKjI8zOl5AACHEbkAhhSvz69fvtKgDSUelZ/tVP6oOP2/22fqphnpCncRtwCAtxG5AIaEPq9fzx+t08bSclU3dWnSmAQV3zVb108bK1eYcXoeACDIELkAglpPv08/P1SrzTsqVN/SrekZSdp671xdM3m0wohbAMAFELkAglJ3n09PH6jW1p0Vamzv1dzsEfrWymlaMmGUjCFuAQDvj8gFEFQ6er16cl+1tu2qUFNnnxbkpegHt8/SFfkjiVsAwIARuQCCQmt3vx7fU6VH91SqtbtfiyeM0rrCAl2Wk+L0NADAEETkAnBUc2efHtldoSf2Vqu916trJo/W2sICzRqX7PQ0AMAQRuQCcERje4+27arUU/ur1d3v0/XTxmjNsgJNTU9yehoAIAQQuQAuqVOt3dqyo0LPHKxRv8+vT8xM15plBRo/OsHpaQCAEELkArgkapu7tGlHuZ49VCe/tbplToYeXFqg3NQ4p6cBAEIQkQsgoCrPdWpDiUfPH62XyxjdNi9Tn1+Sr3EpsU5PAwCEMCIXQEC8daZdG0o8+tUrDYpwhelTV2TrgcX5GpMU7fQ0AMAwQOQCGFSvNbSq2O3Rb0+cVmykS59blKf7F+VpVEKU09MAAMMIkQtgUByrbVGxu0x/PNmohKhwrSss0GeuzNWIuEinpwEAhiEiF8BH8nJVs9ZvL9OusnNKjo3QP3xsgj61MEdJMRFOTwMADGNELoCLZq3V3vImrd9epgOVzUqNj9Q/XT9J9yzIVnwUDysAAOfxbARgwKy1Kn3zrIrcZTpS06LRiVH6t+VTdOf8LMVEupyeBwDAnxG5AD6Q32/1h5NnVOz26Hh9qzKSY/TNm6dp1dxMRUcQtwCA4EPkArggn9/qxeOntKHEozdOtyt7ZKy+e+sMrZyToQhXmNPzAAC4ICIXwLt4fX69cKxBG0o9qjjbqYK0eP3g9llaPmOswolbAMAQQOQC+LM+r1+/OFKnjaXlqmnu0qQxCdpw1xxdP22MwsKM0/MAABgwIheAevp9+tmhWm0uLVdDa49mZCbpq8vn6epJacQtAGBIInKBYayrz6sfH6jR1p0Vamzv1dzsEfrPW6ZryYRRMoa4BQAMXUQuMAx19Hr1xL4qPbKrUk2dfboib6R+cMcsXZE3krgFAIQEIhcYRlq7+vX43io9uqdSrd39WjJhlNYVFmheTorT0wAAGFRELjAMNHf26ZHdFXpib7Xae726ZvJorSss0MxxyU5PAwAgIIhcIIQ1tvfohzsr9NT+GvV4fbph2litWVagKemJTk8DACCgiFwgBJ1q7daWHRV65mCN+n1+rZiVoTXL8lWQluD0NAAALgkiFwghtc1d2lharmcP18pa6ZY5GXpoaYFyUuOcngYAwCVF5AIhoOJshzaWluv5o/VyGaPbLxunzy/JV+aIWKenAQDgCCIXGMLeOtOuYrdHv361QZHhYfqbK3K0enGexiRFOz0NAABHEbnAEHSivlXFbo9+99ppxUa69LnFebr/qjyNSohyehoAAEGByAWGkKM151Xs9mj7G41KiA7XFwoLdN+VuRoRF+n0NAAAggqRC1WFDR8AABHWSURBVAwBByubVeQu066yc0qOjdA/XjtB916Ro6SYCKenAQAQlIhcIEhZa7XH06T17jIdrGxWanykvnL9JN2zIFtxUfzTBQDg/fBMCQQZa61K3zyr9e4yHa1p0ZjEaH3tpim647IsxUS6nJ4HAMCQQOQCQcLvt3rp9TMqLinTifo2ZSTH6Js3T9Nt8zIVFU7cAgBwMYhcwGE+v9Vvjp/SBrdHb55pV87IWH131QytnJ2hCFeY0/MAABiSiFzAIV6fXy8ca9CGUo8qznaqIC1eP7h9lpbPGKtw4hYAgI+EyAUusT6vX88dqdPGUo9qm7s1eWyiNt49R9dNHaOwMOP0PAAAQgKRC1wiPf0+/exQrTaXlquhtUczM5P0teVTdfXkNBlD3AIAMJiIXCDAuvq8+vGBGm3ZWaGz7b2alz1C3751hhaPTyVuAQAIECIXCJD2nn49sa9aj+yuVHNnnxbmj9T6O2ZrQV4KcQsAQIARucAga+3q12N7K/XYniq1dvdr6cRRWldYoLnZKU5PAwBg2CBygUHS1NGrR3ZX6ol91ero9eraKaO1trBAMzKTnZ4GAMCwQ+QCH1FjW49+uKtCT+2vUY/Xpxumj9XaZQWaPDbR6WkAAAxbRC7wITW0dGvLjnI983KtfH6rFTPT9dCyfBWkJTg9DQCAYY/IBS5STVOXNu3w6NnDdbJWunVOph5alq/skXFOTwMAAO8gcoEBKj/boY0l5fqfY/VyGaM7LsvS55fmKyM5xulpAADgrxC5wAd483S7iks8+s2rDYoMD9OnF+Zo9eI8jU6MdnoaAAC4ACIXuIAT9a0qcpfp96+dUVykS6sX5+v+RblKjY9yehoAAPgARC7wV47UnFex2yP3G41KiA7XF64er/sW5mhEXKTT0wAAwAARucA7DlQ0qcjt0W7POY2IjdA/XjtBn1qYo8ToCKenAQCAi0TkYliz1mq355yKtnt0sKpZqfFR+ucbJunuy7MVF8U/DwAAhiqexTEsWWtV8maj1m/36Fhti8YkRuvrN03RHfOzFB3hcnoeAAD4iD4wco0x4yQ9IWmMJL+krdbahwM9DAgEv9/qpddPq8jt0WsNbcocEaNvrZymVXMzFRVO3AIAECoGcibXK+kfrLVHjDEJkg4bY/5grX09wNuAQePzW/3m+CltcHv05pl25abG6b9XzdDNszMU4Qpzeh4AABhkHxi51tpTkk698+t2Y8xJSRmSiFwEvX6fXy8ca9DGEo8qznVqfFq8Hr5jlpbPSJcrzDg9DwAABMhFXZNrjMmRNFvSgfe4bbWk1ZKUlZU1CNOAD6/X69Nzh+u1aYdHtc3dmjw2UZvunqOPTx2jMOIWAICQN+DINcbES3pO0t9aa9v++nZr7VZJWyVp3rx5dtAWAhehp9+nn75cq807ynWqtUczxyXr6zdNVeGkNBlD3AIAMFwMKHKNMRF6O3Cfttb+IrCTgIvX1efV0/trtHVXhc629+qynBH6r1tnaNH4VOIWAIBhaCCvrmAkPSLppLX2+4GfBAxce0+/nthXrUd2V6q5s09XFoxU0Z2ztSBvpNPTAACAgwZyJvdKSfdKOm6MOfbO+/7ZWvti4GYB76+1q1+P7qnUY3sq1dbj1bKJo7S2cLzmZo9wehoAAAgCA3l1hd2S+HovgkJTR6+27a7Uk/uq1dHr1bVTRmtd4XhNz0xyehoAAAgi/MQzDAmNbT3aurNCTx+oUY/Xpxunj9XawgJNGpPo9DQAABCEiFwEtYaWbm3eUa6fvFwrn99qxax0PbS0QAVp8U5PAwAAQYzIRVCqaerSxlKPnjtSJ0m6dU6mHlyar+yRcQ4vAwAAQwGRi6BSfrZDG0o8euFYg1xhRnfOz9IDS/KVkRzj9DQAADCEELkICm+cblOx26PfHD+lqPAwfXphjlYvztPoxGinpwEAgCGIyIWjTtS3av32Mr30+hnFRbr0+SX5+uxVuUqNj3J6GgAAGMKIXDjiSM15FW0vU8mbZ5UYHa4vXj1e912Zo+TYSKenAQCAEEDk4pLaX9GkIneZ9niaNCI2Ql/6+ETde0W2EqMjnJ4GAABCCJGLgLPWarfnnIq2e3Swqlmp8VH6lxsm667LsxQXxSEIAAAGH4WBgLHWyv1Go4rcHh2rbdGYxGh9/aYpumN+lqIjXE7PAwAAIYzIxaDz+61+/9ppFbk9ev1UmzJHxOg/V07XrXMzFBVO3AIAgMAjcjFofH6rX7/aoA0lHr11pkO5qXH63m0ztWJWuiJcYU7PAwAAwwiRi4+s3+fX/xyt18bSclWe69SE0fF6+I5ZWj4jXa4w4/Q8AAAwDBG5+NB6vT49e7hOm0rLVXe+W1PTE7X5njm6dsoYhRG3AADAQUQuLlpPv08/OVijLTsrdKq1R7PGJesbK6Zq2cQ0GUPcAgAA5xG5GLDOXq+ePlCtrTsrda6jV/NzUvTdVTN0VUEqcQsAAIIKkYsP1NbTryf3VWvbrgqd7+rXVQWpWlc4W5fnjXR6GgAAwHsicnFBLV19enRPlR7fU6m2Hq8KJ6VpzbICzc0e4fQ0AACA90Xk4l3OdfRq265KPbmvSp19Pn186mitKxyvaRlJTk8DAAAYECIXf9bY1qMtOyv09IFq9Xr9Wj4jXWuW5WvSmESnpwEAAFwUIheqb+nW5tJy/fRQrXx+q5tnZeihZfnKHxXv9DQAAIAPhcgdxqqbOrWptFzPHamTJK2am6kHlxQoa2Ssw8sAAAA+GiJ3GPI0dmhjiUcvvNIgV5jRXfOztHpJvjKSY5yeBgAAMCiI3GHkjdNtKnJ79OLxU4oOd+m+hTlavThPaYnRTk8DAAAYVETuMHC8rlVF7jK99PoZxUeF68El+frsVbkaGR/l9DQAAICAIHJD2OHq8ypyl6n0zbNKjA7XF68er/uuzFFybKTT0wAAAAKKyA0x1lrtr2hWcUmZ9nialBIXqS99fKI+dUW2EqIjnJ4HAABwSRC5IcJaq11l51TkLtPLVec1KiFK/3LDZN29IEuxkfw1AwCA4YX6GeKstdp+slFFJR69UtuisUnR+vdPTNXtl41TdITL6XkAAACOIHKHKL/f6nevnVaR26OTp9o0LiVG375lum6dk6nI8DCn5wEAADiKyB1ivD6/fnP8lIrdHpU1digvNU7fu22mVsxKV4SLuAUAAJCI3CGj3+fX80frtbHEo6qmLk0YHa/1d87WjdPHyhVmnJ4HAAAQVIjcINfr9enZw3XaVFquuvPdmpqeqM33zNW1U0YrjLgFAAB4T0RukOrp9+mZgzXasqNCp9t6NGtcsr6xYqqWTUyTMcQtAADA+yFyg0xnr1dP7a/WD3dV6lxHr+bnpuh7t83UlQUjiVsAAIABInKDRFtPv57YW6VHdlfqfFe/Fo1P1dpls3V53kinpwEAAAw5RK7DWrr69OjuSj22t0rtPV5dPSlNawoLNCdrhNPTAAAAhiwi1yHnOnr1w10VempftTr7fLpu6hitLSzQtIwkp6cBAAAMeUTuJXamrUdbdlToxwer1ef1a/mMdK1ZVqCJYxKcngYAABAyiNxLpO58lzbvKNfPXq6Tz1qtnJ2hh5bmK29UvNPTAAAAQg6RG2BV5zq1qbRczx2pkzHSqrnj9NDSfI1LiXV6GgAAQMgicgPE09iuDSXleuFYvSJcYbpnQbZWL85TenKM09MAAABCHpE7yE6ealOx26MXT5xSdLhLn70qV59bnKe0hGinpwEAAAwbRO4gebWuRUVuj/7w+hnFR4XroaX5+syVuRoZH+X0NAAAgGGHyP2IDlc3a/12j3a8dVaJ0eH622vG676FuUqKjXB6GgAAwLBF5H4I1lrtq2hS0XaP9lU0KSUuUl++bqLuXZCthGjiFgAAwGlE7kWw1mpn2TkVbS/ToerzSkuI0r/eOFl3XZ6l2Ej+KAEAAIIFZTYA1lr98WSjit1leqWuVelJ0frGiqn65Lxxio5wOT0PAAAAf4XIfR9+v9VvT5xWkbtMb5xuV1ZKrL5zy3TdMidTkeFhTs8DAADABRC578Hr8+vXr55ScYlHnsYO5Y2K0/+9baZWzEpXuIu4BQAACHZE7l/o9/n1/JF6bSz1qKqpSxNHJ6joztm6YfpYucKM0/MAAAAwQESupF6vTz8/VKdNpeWqb+nWtIxEbbl3rj42ebTCiFsAAIAhZ1hHbnefT88crNGWneU609ar2VnJ+ubN07R04igZQ9wCAAAMVcMycjt6vXpqf7W27arQuY4+XZ6bou9/cpYW5o8kbgEAAELAsIrc1u5+PbG3So/sqVRLV78WjU/VusLxmp+b4vQ0AAAADKJhEbnnO/v06J5KPb6nSu29Xl0zOU1rlhVodtYIp6cBAAAgAEI6cs+292rbrgo9ub9aXX0+XT9tjNYWFmhqepLT0wAAABBAA4pcY8x1kh6W5JK0zVr7nYCu+ohOt/Zoy85yPXOwRn1ev26ama41ywo0YXSC09MAAABwCXxg5BpjXJI2SPqYpDpJLxtjfmmtfT3Q4y5W3fkubSot188P1clvrVbOztCDS/OVNyre6WkAAAC4hAZyJne+JI+1tkKSjDE/kbRCUlBF7r+9cEI/PlAjY6Tb5o3Tg0vyNS4l1ulZAAAAcMBAIjdDUu1fvF0n6fK/vpMxZrWk1ZKUlZU1KOMuRkykS/csyNYDS/I0Ninmkn9+AAAABI+BRO57vXCsfdc7rN0qaaskzZs37123B9pXrp98qT8lAAAAglTYAO5TJ2ncX7ydKakhMHMAAACAj24gkfuypPHGmFxjTKSkOyT9MrCzAAAAgA/vAy9XsNZ6jTFrJf1eb7+E2KPW2tcCvgwAAAD4kAb0OrnW2hclvRjgLQAAAMCgGMjlCgAAAMCQQuQCAAAg5BC5AAAACDlELgAAAEIOkQsAAICQQ+QCAAAg5BC5AAAACDlELgAAAEIOkQsAAICQY6y1g/9BjTkrqXrQP/AHS5V0zoHPi+DHsYH3w/GBC+HYwIVwbASHbGvtqPe6ISCR6xRjzCFr7TyndyD4cGzg/XB84EI4NnAhHBvBj8sVAAAAEHKIXAAAAIScUIvcrU4PQNDi2MD74fjAhXBs4EI4NoJcSF2TCwAAAEihdyYXAAAACJ3INcZcZ4x50xjjMcb8k9N7EByMMeOMMSXGmJPGmNeMMV90ehOCizHGZYw5aoz5tdNbEDyMMcnGmGeNMW+88/hxhdObEDyMMX/3znPKCWPMM8aYaKc34d1CInKNMS5JGyRdL2mKpDuNMVOcXYUg4ZX0D9bayZIWSFrDsYG/8kVJJ50egaDzsKTfWWsnSZopjhG8wxiTIekLkuZZa6dJckm6w9lVeC8hEbmS5kvyWGsrrLV9kn4iaYXDmxAErLWnrLVH3vl1u95+ospwdhWChTEmU9KNkrY5vQXBwxiTKGmxpEckyVrbZ61tcXYVgky4pBhjTLikWEkNDu/BewiVyM2QVPsXb9eJkMFfMcbkSJot6YCzSxBEfiDpy5L8Tg9BUMmTdFbSY+9cyrLNGBPn9CgEB2ttvaTvSaqRdEpSq7X2JWdX4b2ESuSa93gfLxuBPzPGxEt6TtLfWmvbnN4D5xljlktqtNYednoLgk64pDmSNllrZ0vqlMT3ekCSZIwZobe/WpwrKV1SnDHmHmdX4b2ESuTWSRr3F29nii8d4B3GmAi9HbhPW2t/4fQeBI0rJX3CGFOlty9xKjTGPOXsJASJOkl11to/fdXnWb0dvYAkXSOp0lp71lrbL+kXkhY6vAnvIVQi92VJ440xucaYSL19AfgvHd6EIGCMMXr7urqT1trvO70HwcNa+xVrbaa1NkdvP2a4rbWcjYGstacl1RpjJr7zrqslve7gJASXGkkLjDGx7zzHXC2+MTEohTs9YDBYa73GmLWSfq+3v8vxUWvtaw7PQnC4UtK9ko4bY469875/tta+6OAmAMFvnaSn3zlxUiHpPof3IEhYaw8YY56VdERvv4LPUfHTz4ISP/EMAAAAISdULlcAAAAA/ozIBQAAQMghcgEAABByiFwAAACEHCIXAAAAIYfIBQAAQMghcgEAABByiFwAAACEnP8PCDgz/x9Xi5wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "lines = ax.plot(x,x)\n",
    "\n",
    "print(type(lines))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0tO69916NHz9ezZo1c2khgPKC+AUAhK1vvvlGmZmZWrx4sU6dOlXsbWxsrB544AElJyerUaNGLi0EUN4QvwCAsPP5558rMzNTS5YsUUFBQbG3FSpU0IMPPqikpCTVr1/fpYUAyiviFwAQNjZu3Kj09HQtW7ZM1tpibytXrqzBgwdr7NixuvTSS11aCKC8I34BAJ7bsGGDQqGQnn/+ecfbKlWqaNiwYRo9erQSEhJcWAcgkhC/AADPrF+/XqFQSK+88orjbbVq1TRy5EiNGDFCNWrUcGEdgEhE/AIAXJefn6/bb79db7zxhuNtzZo1NWbMGD300EOqWrWqC+sARDLiFwDgupiYGF188cXF3tSuXVvjxo3T4MGDFR8f79IyAJEuyusBAAB/CgQC53y8Xr16mjlzprZs2aLExETCF0CpIn4BAJ648sor1aNHjx9/3bBhQ82fP1+5ubkaNmyYKlWq5OE6AJGKlz0AADwTCAS0adMmpaSkqHfv3oqNjfV6EoAIR/wCADzz29/+Vp999pmiovgPkQDcwZ82AABPEb4A3MSfOAAAAPAN4hcAAAC+QfwCAADAN4hfAAAA+AbxCwAAAN8gfgEAAOAbxC8AAAB8g/gFAACAbxC/AAAA8A3iFwAAAL5B/AIAAMA3iF8AAAD4BvELAAAA3yB+AQAA4BvELwAAAHyD+AWAcqywsFDZ2dk6cuSI11MAoFwgfgGgHMrPz9eSJUvUsmVL9ezZU3PmzPF6EgCUC8QvAJQjp06d0l//+le1aNFCffr00ebNmyVJWVlZOn78uMfrACD8Eb8AUA6cPHlSc+fOVZMmTdSvXz/l5ub+5OO7du3SY4895tE6ACg/iF8ACGPHjh3TjBkz1LhxYw0ZMkRbt24t8nbixInKy8tzcR0AlD8xXg8AAPzckSNHNGfOHGVlZWnXrl2O9506dVJqaqpiY2NdWAcA5RfxCwBh5ODBg5o5c6amTp2qffv2Od536dJFwWBQHTt2dGEdAJR/xC8AhIG9e/dq+vTpmjFjhg4ePOh4361bNwUCAf3+9793YR0ARA7iFwA8tGvXLk2ePFmPPvroeb1Xb48ePRQMBtW6dWsX1gFA5CF+AcAD33//vbKysjRv3jzHtyiLiopSr169NH78eF155ZUuLQSAyET8AoCLtm7dqgkTJmjhwoWO78wQHR2t++67TykpKWratKlLCwEgshG/AOCC3NxcZWZm6oknnlB+fn6xt7GxserXr58efvhhNWzY0KWFAOAPxC8AlKHNmzcrIyNDTz/9tAoLC4u9rVixogYMGKCkpCTVq1fPpYUA4C/ELwCUgU8++UShUEjLly+XtbbY2/j4eA0ZMkSJiYm65JJLXFoIAP5E/AJAKcrJyVEoFNILL7zgeFulShUNHz5co0ePVs2aNV1YBwAgfgGgFLzzzjtKS0vTa6+95nhbvXp1jRo1SsOHD1f16tVdWAcA+A/iFwBKyFqrt956S2lpaVqzZo3jfUJCghITEzVkyBBVrVrVhYUAgLMRvwDwC1lr9frrrysUCmndunWO95deeqnGjRungQMHKj4+3oWFAICiEL8AcJ6stXrppZcUCoX0/vvvO95fdtllSk5OVr9+/VSxYkUXFgIAnBC/AOCgsLBQ2dnZCoVC+uSTTxzvGzVqpJSUFP33f/+34uLiXFgIADhfxC8AFCE/P1/PPvus0tPTtXnzZsf7Zs2aKRAI6J577lFMDH+8AkA4cvzT2RizSFJXSbustS3PPDZJUjdJeZK+ltTXWnugLIcCgFtOnTqlJ598UpmZmcrNzXW8b9WqlYLBoHr06KHo6GgXFgIASirqPG4el3TLWY+tktTSWnuVpC8lpZTyLgDwhLVW119/vfr37+8Yvm3atNHf/vY3ffTRR7rrrrsIXwAoBxzj11q7VtK+sx57w1r7nx9O/y9J/BxOABHBGKOePXsWe9OhQwe98sorysnJUffu3RUVdT5fRwAAhIPS+BO7n6RXi/qgMWagMSbHGJOze/fuUng6AChbgwcPPudPXOvUqZNWr16tdevW6dZbb5UxxoN1AIALcUHxa4wJSMqXtKSoG2vtfGttO2ttu4SEhAt5OgBwRXx8vMaMGfPjr7t06aK1a9fqrbfe0k033UT0AkA5VuJvRzbG3K/T3wh3k7XWlt4kAPDeQw89pE8++USjRo3S73//e6/nAABKSYni1xhzi6SHJXWy1h4r3UkA4L2qVatq6dKlXs8AAJQyx5c9GGOWSlovqZkxZrsxpr+kWZKqSFpljPnIGDO3jHcCAAAAF8zxK7/W2nvO8fDCMtgCAAAAlCnenwcAAAC+QfwCAADAN4hfAAAA+AbxCwAAAN8gfgEAAOAbxC8AAAB8g/gFAACAbxC/AAAA8A3iFwAAAL5B/AIAAMA3iF8AAAD4BvELAAAA3yB+AQAA4BvELwAAAHyD+AVQJg4cOKC0tDRt2rTJ6ykAAPwoxusBACLL3r17NXXqVM2cOVOHDh3SZ599pqVLl3o9CwAASXzlF0Ap+eGHH5SUlKTLL79c6enpOnTokCTp2Wef1RdffOHxOgAATiN+AVyQ77//XiNHjlSDBg00adIkHT169Ccft9YqIyPDo3UAAPwU8QugRL799lsNHjxYjRo10owZM3TixIkib5ctW6Z9+/a5uA4AgHMjfgH8Il999ZX69eunJk2aaN68ecrLyyvyNi4uToMHD9bmzZtVo0YNF1cCAHBufMMbgPPy2WefKT09Xc8884wKCwuLva1YsaIGDRqksWPHql69ei4tBADAGfELoFgfffSR0tPTlZ2dLWttsbfx8fEaOnSoEhMTVbt2bZcWAgBw/ohfAOf03nvvKRQK6aWXXnK8rVq1qkaMGKFRo0bp4osvdmEdAAAlQ/wC+Il//vOfSktL0xtvvOF4W6NGDY0ePVrDhg1TtWrVXFgHAMCFIX4ByFqrNWvWKC0tTW+99Zbjfa1atZSYmKghQ4aoSpUqZT8QAIBSQvwCPmat1Wuvvaa0tDStX7/e8b5OnTpKSkrSgAEDVLlyZRcWAgBQuohfwIcKCwv14osvKhQKacOGDY739evXV3Jysvr27auKFSu6sBAAgLJB/AI+UlBQoOzsbIVCIW3cuNHxvnHjxho/frz69OmjuLg4FxYCAFC2iF/AB/Lz87V06VJlZGTo888/d7xv3ry5AoGAevXqpZgY/pgAAEQO/q0GRLC8vDw98cQTyszM1DfffON4f9VVVykYDOrOO+9UdHS0CwsBAHAX8QtEoBMnTmjRokWaMGGCtm3b5njfrl07paamqmvXroqK4qeeAwAiF/ELRJBjx45p3rx5mjRpknbs2OF4f8011yg1NVV//OMfZYxxYSEAAN4ifoEIcPjwYc2ePVtTpkzR7t27He//8Ic/KDU1VTfccAPRCwDwFeIXKMcOHDigGTNmaNq0adq/f7/j/S233KJgMKhrr73WhXUAAIQf4hcoh/bs2aOpU6dq1qxZOnTokOP9n/70JwUCAf3ud79zYR0AAOGL+AXKkZ07dyorK0tz5szRsWPHir01xqhnz54KBAL6zW9+49JCAADCG/ELlCP9+vXTq6++WuxNVFSUevfurZSUFF1xxRUuLQMAoHzgPY2AciQpKanIj8XExKhfv3764osv9OSTTxK+AACcA/ELlCOdOnXSdddd95PH4uLiNGTIEOXm5mrhwoX69a9/7dE6AADCH/ELlCPGGKWmpkqSKlWqpFGjRumbb77Ro48+qssvv9zjdQAAhD9e8wuUMzfffLOmTZumXr16qXbt2l7PAQCgXCF+gXLGGKORI0d6PQMAgHKJlz0AAADAN4hfAAAA+AbxCwAAAN8gfgEAAOAbxC8AAAB8g/gFAACAbxC/AAAA8A3iFwAAAL5B/AIAAMA3iF8AAAD4BvELAAAA3yB+AQAA4BvELwAAAHyD+AUAAIBvEL8AAADwDcf4NcYsMsbsMsZs+j+P1TDGrDLGfHXmr9XLdiYAAABw4c7nK7+PS7rlrMeSJf3dWttE0t/P/BooFzZt2qTevXvrqaee8noKAABwmWP8WmvXStp31sN/krT4zN8vltS9lHcBpe7DDz9Ujx491KpVKy1dulRpaWkqKCjwehYAAHBRSV/zW9tau0OSzvy1VlGHxpiBxpgcY0zO7t27S/h0QMm9++676tq1q9q0aaMVK1b8+PiXX36p5557zsNlAADAbWX+DW/W2vnW2nbW2nYJCQll/XTAj9auXasuXbqoffv2Wrly5TlvQqGQCgsLXV4GAAC8UtL4/cEYc6kknfnrrtKbBJSctVarV69Wp06d1KlTJ61atarY+z179mjLli0urQMAAF4rafy+KOn+M39/v6QXSmcOUDLWWq1cuVLXXHONbr75Zq1du7bY+7p162r69OnasmWLGjdu7NJKAADgtRinA2PMUkk3SKppjNku6S+SHpG0zBjTX9I2SX8uy5FAUQoLC/XCCy8oFArpgw8+cLxv0KCBkpOT9cADD6hChQouLAQAAOHEMX6ttfcU8aGbSnkLcN4KCgr03HPPKT09XZs2bXK8b9KkicaPH697771XsbGxLiwEAADhyDF+gXCSn5+vJUuWKCMjQ19++aXj/RVXXKFAIKC7775b0dHRLiwEAADhjPhFuZCXl6fFixcrMzPzvL5BrXXr1goGg7rjjjsUFcVP8QYAAKcRvwhrJ06c0IIFCzRhwgRt377d8f7qq69Wamqqbr/9dhljXFgIAADKE+IXYeno0aOaN2+eJk2apJ07dzreX3fddUpNTdXNN99M9AIAgCIRvwgrhw4d0uzZszVlyhTt2bPH8f6mm25SamqqOnXq5MI6AABQ3hG/CAv79+/XjBkzNH36dO3fv9/x/rbbblMwGFSHDh1cWAcAACIF8QtP7d69W1OnTtWsWbN0+PBhx/vu3bsrGAyqbdu2LqwDAACRhviFJ3bs2KHJkydrzpw5OnbsWLG3xhjdddddCgQCatWqlUsLAQBAJCJ+4arvvvtOEydO1GOPPaaTJ08WexsdHa17771X48ePV7NmzVxaCAAAIhnxC1ds2bJFmZmZevzxx3Xq1Klib2NjY3X//fcrOTlZjRs3dmkhAADwA+IXZerLL79URkaGnnrqKRUUFBR7W6FCBT344INKSkpS/fr1XVoIAAD8hPhFmdi0aZPS09O1bNkyFRYWFntbuXJlDR48WImJiapTp45LCwEAgB8RvyhVH374oUKhkFasWOF4e9FFF2nYsGEaM2aMEhISXFgHAAD8jvhFqXjvvff0P//zP1q5cqXjbbVq1TRy5EiNGDFCNWrUcGEdAADAacQvSkV2drZj+NasWVNjxozR0KFD9atf/cqlZQAAAP8ryusBiAyJiYmqVKnSOT9Wu3ZtZWVl6dtvv1VKSgrhCwAAPEP8olTUqlVLgwYN+slj9erV08yZM7VlyxYlJiYqPj7eo3UAAACnEb8oNWPHjlVcXJwaNGigefPmKTc3V8OGDSvyK8IAAABu4zW/KDV169bV22+/rbZt2yo2NtbrOQAAAD9D/KJUtW/f3usJAAAAReJlDwAAAPAN4hcAAAC+QfwCAADAN4hfAAAA+AbxCwAAAN8gfgEAAOAbxC8AAAB8g/gFAACAbxC/AAAA8A3iFwAAAL5B/AIAAMA3iF8AAAD4BvELAAAA3yB+AQAA4BvELwAAAHyD+A0z1lodP37c6xkAAAARifgNE4WFhcrOzlabNm2UnJzs9RwAAICIRPx6rKCgQEuXLtVVV12lnj176qOPPtL8+fO1c+dOr6cBAABEHOLXI6dOndLjjz+uFi1aqHfv3vr0009//NiJEyc0efJkD9cBAABEJuLXZSdPntS8efPUtGlT9e3bV1999dU57+bMmaM9e/a4vA4AACCyxXg9wC+OHz+uBQsWaOLEidq+fbvjfcuWLbVr1y7VrFnThXUAAAD+QPyWsSNHjmju3LnKysrSDz/84HjfsWNHpaamqnPnzjLGuLAQAADAP4jfMnLw4EHNnj1bU6ZM0d69ex3vO3furNTUVF1//fUurAMAAPAn4reU7du3T9OnT9eMGTN04MABx/vbb79dwWBQ7du3d2EdAACAvxG/pWTXrl2aMnxqkwwAAAckSURBVGWKZs+erSNHjjje33HHHQoGg2rTpo0L6wAAACARvxdsx44dmjRpkubOnev4k9mMMbr77rsVCATUsmVLlxYCAADgP4jfEtq2bZsmTJighQsX6uTJk8XeRkdHq0+fPkpJSVGzZs1cWggAAICzEb+/0Ndff63MzEwtXrxY+fn5xd7GxsbqgQceUHJysho1auTSQgAAABSF+D1Pn3/+uTIyMvT000+roKCg2NsKFSpowIABSkpK0mWXXebSQgAAADghfh1s3LhRoVBIzz33nKy1xd5WrlxZQ4YMUWJioi699FKXFgIAAOB8Eb9F2LBhg0KhkJ5//nnH2ypVqmjYsGEaPXq0EhISXFgHAACAkiB+z7J+/XqlpaXp1VdfdbytVq2aRo0apREjRqh69eourAMAAMCFIH4lWWv19ttvKy0tTW+++abjfc2aNZWYmKihQ4eqatWqLiwEAABAafB1/FprtWrVKqWlpemf//yn4/0ll1yicePGadCgQYqPj3dhIQAAAEqTL+PXWquXX35ZoVBI7733nuP9ZZddpocfflj9+/dXxYoVXVgIAACAsuCr+C0sLNSKFSsUCoX08ccfO943bNhQKSkpuv/++xUXF+fCQgAAAJQlX8Rvfn6+li1bpvT0dH322WeO902bNlUgEFDv3r0VE+OLf0QAAAC+cEFlZ4wZLelBSVbSRkl9rbUnSmNYaXnppZc0ZswY5ebmOt62bNlSwWBQPXv2VHR0tAvrAAAA4Kaokv5GY0xdSSMktbPWtpQULalXaQ0rLSdOnHAM3zZt2mjFihX6+OOPdffddxO+AAAAEarE8XtGjKRKxpgYSZUl/fvCJ5WuO++8U82bNz/nx9q3b6+VK1cqJydHd9xxh6KiLvQfBwAAAMJZiWvPWvu9pCxJ2yTtkHTQWvvG2XfGmIHGmBxjTM7u3btLvrSEoqOjFQgEfvJYp06dtHr1ar3zzju67bbbZIxxfRcAAADcZ6y1JfuNxlSXlC3pbkkHJD0nabm19qmifk+7du1sTk5OiZ7vQuTn56t58+Zq1KiRUlNT1bFjR9c3AAAAwD3GmA3W2nZnP34h3/DWWdIWa+3uM0+wQtI1koqMX6/ExMTo/fff50cQAwAA+NyFvMh1m6T2xpjK5vTrBm6StLl0ZpU+whcAAAAX8prfdyUtl/SBTr/NWZSk+aW0CwAAACh1F/Q+v9bav0j6SyltAQAAAMoU7+0FAAAA3yB+AQAA4BvELwAAAHyD+AUAAIBvEL8AAADwDeIXAAAAvkH8AgAAwDeIXwAAAPgG8QsAAADfMNZa957MmN2Strr2hP+rpqQ9Hjwvygc+P1AUPjdQFD43UBQ+N8LH5dbahLMfdDV+vWKMybHWtvN6B8ITnx8oCp8bKAqfGygKnxvhj5c9AAAAwDeIXwAAAPiGX+J3vtcDENb4/EBR+NxAUfjcQFH43AhzvnjNLwAAACD55yu/AAAAQOTHrzHmFmPMF8aYXGNMstd7EB6MMZcZY9YYYzYbYz41xoz0ehPCizEm2hjzoTHmZa+3ILwYY6oZY5YbYz4/82dIB683ITwYY0af+XfKJmPMUmNMRa834eciOn6NMdGSZku6VdIVku4xxlzh7SqEiXxJidbaFpLaS3qIzw2cZaSkzV6PQFiaLuk1a21zSb8RnyeQZIypK2mEpHbW2paSoiX18nYVziWi41fS1ZJyrbXfWGvzJD0j6U8eb0IYsNbusNZ+cObvD+v0v7zqersK4cIYU0/S7ZIWeL0F4cUYU1XS9ZIWSpK1Ns9ae8DbVQgjMZIqGWNiJFWW9G+P9+AcIj1+60r67v/8ersIHJzFGNNA0m8lvevtEoSRaZKSJBV6PQRhp5Gk3ZL+euZlMQuMMfFej4L3rLXfS8qStE3SDkkHrbVveLsK5xLp8WvO8Rhvb4EfGWMukpQtaZS19pDXe+A9Y0xXSbustRu83oKwFCOpjaQ51trfSjoqie8ngYwx1XX6vy43lFRHUrwxpo+3q3AukR6/2yVd9n9+XU/8JwicYYyJ1enwXWKtXeH1HoSNayX9lzHmW51+qdSNxpinvJ2EMLJd0nZr7X/+S9FynY5hoLOkLdba3dbaU5JWSLrG4004h0iP3/clNTHGNDTGxOn0C89f9HgTwoAxxuj0a/Y2W2uneL0H4cNam2KtrWetbaDTf2a8aa3lqzeQJFlrd0r6zhjT7MxDN0n6zMNJCB/bJLU3xlQ+8++Ym8Q3Q4alGK8HlCVrbb4xZpik13X6uy4XWWs/9XgWwsO1ku6TtNEY89GZx8Zba1/xcBOA8mG4pCVnvqjyjaS+Hu9BGLDWvmuMWS7pA51+R6EPxU97C0v8hDcAAAD4RqS/7AEAAAD4EfELAAAA3yB+AQAA4BvELwAAAHyD+AUAAIBvEL8AAADwDeIXAAAAvkH8AgAAwDf+P7qAMDbfuujxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "# custom dash\n",
    "lines = ax.plot(x, x+8, color=\"black\", lw=5)\n",
    "lines[0].set_dashes([10, 10]) # format: line length, space length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "# custom dash\n",
    "lines = ax.plot(x, x+8, color=\"black\", lw=5)\n",
    "lines[0].set_dashes([1, 1,1,1,10,10]) # format: line length, space length"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Markers\n",
    "\n",
    "We've technically always been plotting points, and matplotlib has been automatically drawing a line between these points for us. Let's explore how to place markers at each of these points.\n",
    "\n",
    "### Markers Style\n",
    "\n",
    "Huge list of marker types can be found here: https://matplotlib.org/3.2.2/api/markers_api.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x151b89eed08>]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r/QxwQCn1JU3TLIAcTCeEEEIEKb9f8V5dO3aHk/0nmuhz+7BNi2DHytkU5aYzJ3kS97VWvDD6XeDfM+lT3Ar/H4PWEyMx6hCsaVoscBfwNQCllBsw6r8OIYQQQkwi/3TgDKWVThpdg0SHhbA5J5Wi3HRuy4zHZJoCb+/XHx39LvDv+eHy+watJUbKiJ3gWcAV4D80TVsCHAN2KqX6DFhbCCGEEBNYe+8Q5VWNlFQ6Afj57y6yIiuRRzctYO2C6URYJkmf73B11hu8Xp2x64lhMyIEhwB5wDeVUu9rmvYM8Cjw40++SNO07cB2gJkzZxpwWyGEEEKMh6cP1fLM4XPDeq3Przhy9gpHzl753NfsXJNl+GS5ceMz+M1uo9cTw2ZECG4AGpRSH+/n/xY9BP8RpdRzwHMA+fn5yoD7CiGEEGIc7Fo7l2/fk8WH9Z2UVDawt7qJnkEv02PD2JZrozg3nXkpMWQ8uo/6n20OdLljy2wxNriaLcatJUZk1CFYKdWsadplTdPmKaXOAmuAU6MvTQghhBCBVtfWR4mjgZLjTi53DBBpMbNhUQrFeeksm52AeSr0+Q6X36cfY9btNG7NuBGOUBaGMep0iG8C/3X1ZIiLwNcNWlcIIYQQ46yr382e6ibsjgYqL3WhaXDn7ER23TOX9YtSiAoLsmO8mmv0QRbVL0Nvs3HrambIXGHcemJEDPmvWCl1HMg3Yi0hhBBCjD+3188bZ1uxOxp4/UwrHp9i7vRoHt04n8KlaaRaIwJd4vjqaYETL+vji1tOgCkEstbBzGXwxj/e+LS4TzJbIP+B0a8jbkiQ/SgnhBBCiI8ppai83EWJw8me6ka6+j0kRlv482UZFOXaWJQWO7HHFxvN3Q9n9um7vhdeB+WHtDzY+M+QXQxRifrrTu8B57HRHZWmmSE1B6YvMqZ2MWISgoUQQoggc7mjn5JKJyWVTura+ggLMbFuUQrFeTZWzEkkxGwKdInjx++Hj97Sd3xPlYG7F6wzYPkufZBF0jVOsSh+Dp5dBp5R7AaHWPR1RMBICBZCCCGCgGvAw/4TTdgdTj6o7wDg9lnx7Lh7NhsXpxATHhrgCsfZlbN68K3+DXQ3gCUGFm3Tg+9Nd4LpC34QiM+EwmehdMeNtUWEROjXx2XccPli9CQECyGEEFOUx+fnd7VXsFc6OXSqBbfXz6ykKL6/fh6FS9NIj4sMdInjq/cK1OzW2x0aK/WWhNmrYe2TMG8TWEbw9cgu0n8t26GPUR5Oa4Rm1neAC5/9w/UiYCQECyGEEFOIUooTThd2h5M9VY2097mJiwzlK7fMoDgvnZx0a3D1+XoGoXa/vut7/jXweyElB9b/I2R/CWKm3/ja2UWQthRKHoKmav384GuFYc2sPwSXmqO3QMgO8IQgIVgIIYSYAhq7Big97sTucHK+tReL2cQ9C5Mpyk3n7rlJWELGvs9355qsMb/HsCgFl97Vg+/JUhhyQUwqLHtYb3eYvtC4e8VnwoMHoeUkVLwAdUf1Ucg+tx584zL1Y9DyH5iSD8ElhCfQPthu6HrjRVNq/Ie35efnq4qKinG/rxBCCDGV9A552X+iiZJKJ+9ebEcpyL8pjuK8dDYvTsUaGWR9vu0Xrvb5vgRdH0FoFCzYCkvuh8y7wGQOdIUiADRNO6aU+sxRvrITLIQQQkwiXp+fty+0Y3c08OrJZgY9fm5KiGTnmiyKcm3clBAV6BLHV38HnLTr4bfhQ0CDWSth1WMwfwuERQe4QDFRSQgWQgghJoFTjd2UVDZQeryRKz1DxIaHcG9eOsV5NvJmxgVXn693CM4d1INv7avg90DyQlj7U1j8JxCbFugKxSQgIVgIIYSYoFq6Bym72ud7prmHEJPGqvnJ3JtnY9X8ZMJCgujtfaWgoQKqfq3v/A50QlQS3Lpdb3dIWQzB9IOAGDUJwUIIIcQNevpQLbvWXmOYwij0u70cPNnCbkcDb59vw69gyYxp/LRwEVty0oiPshh6v1FpOQkf/gLqj0Jn/SceBsuAjBVwy4Ojfxiss14/y7fqRei4ACHhMH8zLPkKzFoF5vGNMitfWmn4g2BH7jti2Hpi+CQECyGEEDfomcPnDAnBfr/ivYvt7HY4OVDTRJ/bh21aBH+9cg5FeTZmJ02wvtaOOrBvh5YTnz0j1+eGttqrD6n9Sj+OrOjn+ikKwzXQpU9vq3oRLr2jfyxjhT7FbWEhhMca+/mMgJEBeCzWE8MnIVgIIYQIkHMtPex2OCk77qTJNUhMWAhbctIoyrNxa0Y8JtMEfHu/pmR4AyKUTx8r3FChjxi+3oAInwfOH9YHWZx5BXxDkJAFq38MOV+GaTON/1xEUJMQLIQQQoyjtt4hyo83Yq9soMbZjdmkcVdWIo9tWsDahdMJD53Afb41JSMfFfxxGC7dof/+k0FYKX1yW/VLcOK30N8GkQlw81/ofb5pedLnK8aMhGAhhBBijA16fBw61UJJpZM3a6/g8yuybbH8eMtCCpakkRQTFugSr6+j7uoO8AgC8Cd5B/TrbblgCtGDb9VL0HZW7yOet1EfZDHnHn20sBBjTEKwEEIIMQb8fsWH9R2UVDrZV91Ez5CXlNhwvrFiFsV5NuZOjwl0iSNj3663QIyGdwj+9woY6gEUzLgdtvwrLNoGEXGGlCkCo+3550FBwte/hhY6/CEtyuOh/T9+CRokfuMbY1fgNUgIFkIIIQx08UovJZVOSiqdNHQOEGkxsyE7hXvz0rl9VgLmidjnez3NNfpDcF/UAzwcyq8H4PwH4I6/gfhZxtQnAi52wwaan/wp3Xv2kPLkk0Tm5V73mn5HJc2PP07I9OmkPP6Tcajyj0kIFkIIIUaps8/N3upGdjucHL/chUmDO+ck8t11c1m/KIVIyyT/dlvxwuh3gT+mmfQ+XwnAU4plxgxmPP8cPfv349y5k+jVq0n+zi7MVutnXutzuWh96ml6X3+d6T98lJiNGwMy7GWS/6kUQgghAmPIq++Kbv/PCt4424rHp5ifEsNjm+ZTuNTG9NjwAFdooPqjo98F/pjyQd1RY9YSE4qmacRu2kTU8uW0PvUUF7dsJfnRR4hetQrP5QbC5mbR/cortP7sfxC9ZjWz9u3FHBu44+4kBAshhBDDpJTCcakLu6OBvdVNAFRe7uIvlmVQnJfOwrTAfUMfU531Bq9XZ+x6YkIxx8aS8pOf0Dl7Ds1P/hT/Dx7BPG0a4Qvm421pxfZvzxCZe/12ibEmIVgIIYT4lKcP1fLM4XPDeu2VniH+/a06/v2tzw92O9dkGT5Zblz5DGqFGKv1xIQxdPEirrJyXHvK8TY2oUVGEr5gPoM1J4m89bYRPzg3liQECyGEEJ+ya+1cHlieyb7qJkoqG/iwvhOAZbMSKMqzsTE7hZjwUDIe3Uf9zzYHuNpxYLYYG1zNcgTaVOLt6KB73yu4yssZPHECzGailt9J8ne/S8zq1ZgiIjg9fwGJ28f39IfrkRAshBBCXOXx+Xnz7BXslQ28droVt9fP7KQovr9+HttybdimRQS6xPHVewVqfgsY/NBS3AhGKIsJyT80RO8bR3CVldF79Ch4vYQtXEDyo49g3byZkKSkQJd4XRKChRBCBDWlFCecLuwOJ+VVjXT0uYmPsvCnt86kOM/GYps1IE+uB4xnAM7uh6oX4fxr+oNskQnQ7wbU6NfXzJC5YvTriHGnlGLA4cBVVk73/v34e3oISU4m4Wt/QWxBAeFzJ1fLj4RgIYQQQcnZNUBppRO7o4ELV/qwhJhYu2A6Rbk27p6XRKjZFOgSx4/fD5feheoX4WQpDHVDTBrc8U19fLHfB7+4Rw/Io2W26OcEi0nD/dFHV/t89+C5fBktMpLYtfdgLSwk8rbb0MwTeNT3F5AQLIQQImj0DHrYX9NMicPJe3XtKAW3ZMTxlytmsWlxKtaIifHAzrhpO68H3+qXoOsShEbBwgI9+GasANMnws30xeA8Nrqj0jQzpObA9EWjr12MKV9XF90HDuAqLWPg+HHQNKKWLSPpbx4m5p57MEVFBbrEUZMQLIQQYkrz+vy8db4Nu8PJwVPNDHr8ZCRE8u01cynKtTEzITLQJY6v/g6o2a23Ozgr9OEVs1bCqh/Bgi1g+ZxwU/wcPLtsdLvBIRZ9HTEhKbeb3t/9DldZOb1HjqA8HsKyskj+/veI3bKF0OnTA12ioSQECyGEmJJONXZjdzRQVtXIlZ4hrBGh3JuXTnFeOnkzpwVXn693CM4d1INv7avg90DyQlj7U1j8JxCbdv014jOh8Fko3QHeGwjCIRH69XEZI79WjBmlFIPV1bjKyuh+ZT++ri7MiYnE/emfYt1WSNj8+VP2z4qEYCGEEFNGS/cgZced2B1OzjT3EGrWWDUvmeI8G6vmJxMWMjl7F2+IUtDwoR58a3bDYBdEJcNtD0HOfZCyWB9fPBLZRfqvZTv0McrDaY3QzPoOcOGzf7heBJy7wUn3nnJcZeW46+vRwsKIuecerIUFRN1xB1rI1I+IU/8zFEIIMaX1u728erIZu8PJ2+fb8CtYOmMaf1e4iC05acRFBdmZtB11UP0bvde346K+Azt/Myz5it72YB7lt/7sIkhbCiUPQVO1fn7wtcKwZtYfgkvN0VsgZAc44Hw9PXQfOEB3WTn9FRUARN56Kwnf+Eti1q/HHB0d4ArHl4RgIYQQk47Pr3jvYju7HQ0cqGmm3+0jPS6Ch1fNoSjXxqyk8flmvnNN1rjc57oGuuBUqb7re+ld/WMZK2DFd2FBAYQbPM45PhMePAgtJ6HiBag7qo9C9rn14BuXqR+Dlv/AlHsILiE8gfbBdkPXG0vK46H37bf183xffwM1NIQlM5Okb38b69YthNpsY3r/jyU+/PC43GckNKUMOPNvhPLz81XF1Z9AhBBCiOGqbenB7nBSWumkuXuQmLAQNuekUpRr45aMeEymqdm7eE0+j36Ob9WL+rm+viFInKuf7LD4yzBtRqArFAGilGLw5Clc5WV0792Hr6MD87RpxG7ejHVbIeHZ2VO2z/daNE07ppTK//THZSdYCCHEhNbWO0T58UbslQ3UOLsxmzTunpvEj7Ys4J4F0wkPDbI+38bKP/T59rfpgyxu/poeftNyR97nK6YMT1MTrj17cZWX4T5/AS00lOjVq7EWFhC9fDmaJchag65DQrAQQogJZ9Dj49CpFkoqnbxZewWfX7HYZuUnWxZSsDSNxOiwQJc4vrouw4nf6OG3rVZvOZi3SQ++c+4Bc5Cdbyx+z9fbR8+hQ7jKy+h/731Qioi8PFKefJLYDesxW62BLnHCkhAshBBiRJ4+VMuutcaPR/X7FR/Wd2B3OHnlRBM9Q15SreF8Y8UsivNszJ0eY/g9R6zlJHz4C6g/Cp31n+iBzdB7cG950Lge2KEeOFUOVb+G+rcABTOXwZZ/hUXbICLOmPsMw8qXVhreB3vkviOGrRdslM9H3zvv4iovp+e111ADA4TOmEHiww9jLdiKZebMQJc4KUgIFkIIMSLPHD5naAi+eKWXkkr9WDNn1wCRFjMbs1MpzrNx+6wEzBOhz7ejDuzboeXEZ48G87n13dn2C1D1K0jJgaKf6w+PjZTPCxeP6Cc7nN6rn8cblwkrfwg5X76xNQ1gZAAei/WCxeDZs7hKy+jeuxfvlSuYYmOxFhRgLSwkIndpUPX5GkFCsBBCiHHX2edmT3UjdoeT45e7MGlw55xEvr9+HusWTSfSMoG+PdWUDO9cXOXTp6k1VOiT1UZyLm7zCb3V4cTL0NsC4dNg6Vf0Y83Sb5E+3yDmaW2le+8+XGVlDJ09CyEhRN99N9aCAqJXrcQkfb43bAL9LSOEEGIqG/L6eONMK3aHkzfOtuLxKeanxPDYpvkULrUxPTY80CV+Vk3JyCekfRyGS3fov/+8INzdpIfeqheh9SSYQmHuen2Qxdz1EBJkfc/i9/z9/fQcPoyrrJy+d94Bv5/wnBym//hHxG7aREjc+LXCTGUSgoUQQowZpRSOS13YHQ3srW7CNeAhKSaMr92RQVFuOgvTDD6/1kgddVd3gG9gRDDo15XtAFvuHwZFuPv0NofqF/W2B+UHWz5s+hfIvhci442qXkwyyu+n/4MPcBHcekAAACAASURBVJWV0/Pqq/j7+wlNSyNh+zewFhQSNiswrTBTmYRgIYQQhrvU3k9JpZOSygbq2/sJDzWxflEKxXnp3Dk7gRCzKdAlXp99u94CMRpeN9i/Aav+Vt/xPVUOnj6YNlMfZJFzPyTOMaZeMa7ann8eFCR8/WtoocM/nUN5PLT/xy9Bg8RvfIOh8+dxlZXj2rsXb1MTpqgoYjZtxFpQQGR+PpppEvxZmaQkBAshhDCEa8DDvuomSiob+LC+E02DZbMSeHjVHDYuTiU6bBJ9y2mu0R+C+6Ie4OFQPrj8AfxnIYTFwuJ79eA7cxlIuJnUYjdsoPnJn9K9Zw8pTz5JZF7uda/pd1TS/PjjmOPjiMi7mbp7v8TgyZNgNhO1/E6mf/97RK9ejSl8ArYGTUGG/Y2kaZoZqACcSqktRq0rhBBi4vL4/Lx59gr2ygZeO92K2+tnTnI0318/j225NmzTIgJd4o2peGH0u8CfNHsV3P9rCJ2kXw/xGZYZM5jx/HP07N+Pc+dOolevJvk7u655Lq/P5aLln/+FnoMHCU1Pp//DCvrf/4CwhQuY/sNHid28mZDExAB8FsHNyB/LdwKngQnc4CWEEMIIVZe7KKl0Ul7VSEefm/goC39660yK82wstlkn/1FN9UdHvwv8Sa5GCcBTkKZpxG7aRNTy5bQ+9RQXt2wl+dFHiN20CU3T8Pt8tP+v/0X7L15A+Xzg8eBrbyfhga8TW1BA+Fzjz9sWw2dICNY0LR3YDPwD8B0j1hRCCDGxOLsGKK10AlD4/76NJcTE2gXTKc6zcdfcJEInQ5/vcHXWG7xenbHriQnFHBtL6hNP0F9QSPPjj9P5q18TmpZGz8GDqKEhCAvDumkT1sICIm+7Dc0cRKO+JzCjdoL/FfgB8LnjfDRN2w5sB5gpk0yEEGLCefpQLc8cPjfs17u9fvadaGLfiaZr/vuda7LGZLLcuPAZ2AoxFuuJCcfb2cngmdNoEREMHDvGwLFjhM6cSeJfPUTs+vWYoqICXaL4lFGHYE3TtgCtSqljmqat/LzXKaWeA54DyM/PV6O9rxBCCGPtWjuXXWvn4vX5eet8G3aHk4Onmhn0+MlIiKQoN52iXBt3/fMb1P9sc6DLHVtmi7HB1SwDDaYiv9tN75tv4ioro/fN34HHQ1hWFsnf/x6t//wvzDn4aqBLFF/AiJ3gO4ECTdM2AeFArKZp/1cp9d8MWFsIIcQ4UEpxqqmbEoeT0uONtPUOYY0I5Us3p1Ocl07ujGmTv893JKbdBO3D3xW/rjg543WqUEoxcPw4rvJyul/Zj9/lwpyYSPxXv4q1sICw+fPRNI3Wf/6XQJcqrmPUIVgp9UPghwBXd4K/JwFYCCEmh5buQUornZRUOjnT3EOoWWPVvGSK89JZNT+JsJAg6l1USj/OrPpF6PrIuHU1M2SuMG49ERDuy5dxlZfjKi/H89EltLAwYu65B+u2QqKWLUMLmURHAApAzgkWQoig0+/28urJZuwOJ2+fb8OvIHfmNP6ucBFbctKIiwqyt+476qD6N1D1a/0BtpAIyLwb6t40piXCbIH8B0a/jhh3vu5uug8cwFVWzsCxYwBE3noridsfImb9OszR0QGuUIyGoSFYKXUEOGLkmkIIIUbP51e8e6Ede2UDB2qa6Xf7SI+L4G9WzWFbro1ZSUH2zXygE06WQvVLcOldQIOM5XDX92HBVgiPhX9fC85jozsqTTNDag5MX2RY6WJsKY+H3rfewlVWTu/rr6PcbiyzZpH07W9j3bqFUJst0CUKg8hOsBBCTGG1LT3sdjRQVtlIc/cgMeEhFCxJozgvnfyb4jCZgqjP1+eB86/pO75nD4BvCBLnwZqfwOIvw7QZf/z64ufg2WXgGbjxe4ZY9HXEhKaUYrDmpN7nu28fvo4OzHFxTPvyl7EWFhCenR1cPfFBQkKwEEJMMVd6hiivasTuaOBkYzdmk8bKuUn8aMsC7lkwnfDQIOvzbXRA1UtQ81vob4fIBMj/OuTcB2m58HnhJj4TCp+F0h3gvYEgHBKhXx+XMapPQYwdT2Mjrj17cZWX475wAS00lOjVq7EWFhK9YjlaaGigSxRjSEKwEEJMAYMeHwdPtVDiaOB359rw+RWLbVYe37qQrUvSSIwOC3SJ46vrst7qUP0StNWCOQzmbYQlX4E5a8A8zHCTXaT/WrZDH6M8nNYIzazvABc++4frxYTh6+2j5+BBXGVl9H/wAShFxM03k/Lkk8RuWH/NscdiapIQLIQQk5Tfr/igvgO7o4H9J5rpGfKSag1n+12zKM61kTX9c+cXTU2D3XC6HKpe1MceA8y8A7Y+DAu3QcS0G1s3uwjSlkLJQ9BUrT8sd60wrJn1h+BSc/QWCNkBnjCU10vfu+/iKiun57XXUIOD+iCLv3kYa0EBlhkzrr+ImHIkBAshxCRz4UovJQ79WDNn1wBRFjMbF6dSnGvj9lkJY97nu3NN1piuPyI+L1x8Qw++Z/bpbQvxs2DV30LOl40LovGZ8OBBaDkJFS9A3VH9JAmfWw++cZn6MWj5D0zJh+ASwhNoH2w3dL3xMHjmDK7SMlz79uK70obJasW6rRBrYSERS5eOaZ9v4sMPj9nawhiaUuM/vC0/P19VVFSM+32FEGKy6uhzs7e6kd0OJ1WXuzBpsDwriXvzbKxdOJ1ISxDtaSgFzSf04HviZehrhfBpkH2v3u6Qnv/5fb5iyvO0tNK9dy+usjKGamshNJTou+/CWlBA9MqVmCxBdgSgQNO0Y0qp/E9/PIj+1hRCiMllyOvj9dOt2CudvHGmFa9fsSA1lr/dtIDCpWkkx4YHusTx1d0EJ36jh9/WU2AKhbnrYcn9kLUOQoKs71n8nr+/n57XXsNVVk7fu++C30/4khym/+THxG7cSEhcXKBLFBOQhGAhhJhAlFI4LnWy2+FkX3UTrgEPyTFhPLA8k6JcGwtSYwNd4vhy98HpvfqxZnVvgvJD+i2w+X/ComKIjA90hSJAlM9H/wcf4Coto/vQIVR/P6E2GwkPbcdaUEBYpoyqFl9MQrAQQkwAH7X3UXJ1fPFH7f2Eh5rYsCiF4rx07pyTiDmYzvP1+6Dud/rJDqfKwdMH02bCiu/pu74JswNdoQigoXPnro4v3oO3pQVTdDTWzZuwFhQQcfPNaCZToEsUk4SEYCGEuI6nD9Wya+1cw9d19XvYe6KREoeTio860TRYNiuBb67OYkN2CtFhE+Sv6JaT8OEv9BMXOus/8TBYBmSsgFseNOZhsJZTUP0iVL8MPY0QZoXFV/t8Z9wO4xhuVr600vAHwY7cd8Sw9YKNt72d7n37cJWWMXjqFJjNRC9fjvWRHxC9ejWm8CBrDRKGmCB/wwohxMT1zOFzhoVgt9fPm7VXsDsaOHy6FbfPT1ZyND/YMI9tS22kTYsw5D6G6KgD+3ZoOfHZM3J9bv383fYLUPUrSMmBop/rpyiMRG+r/nBb1YvQXK0fM5a1Ftb/g36ub2hgvh5GBuCxWC8Y+AcH6X39dX188Vtvgc9H+MKFTH/sh8Ru2kRIYmKgSxSTnIRgIYQYY0opqhpclDgaKK9qpLPfQ0KUha/ePpPi3HSybbETbyRrTcnwBkQonz5WuKFCHzE8nAERngH9OLPql+D8YX2N1KWw4X/oJzxEJxn7uYhJQ/n9DBw7RldZGT0HXsXf20tISgoJD3xd7/PNmkDH84lJT0KwEEKMkYbOfkorndgrnVy80oclxMS6hdMpzrOxIiuJUPME7V2sKRn5qOCPw3DpDv33nw7Cfj9cekd/wO1UOQx1Q6wN7vwW5NwPyfONq19MOkN1dbjKy+kuK8fT2IgWGUnsunVYCwuIvPVWNHMQjfoW40ZCsBBCGKhn0MP+E83sdjTwfl0HALdmxrN9xSw2Lk7FGjHMcb2B0lF3dQd4BAH4k7wD+vW2XL1nuO2c3upQ/RtwXQJLNCwshJz79H5ieYgpaHk7O+l+5RVcZeUMVleDyUTUsmUk7fo2MWvWYIqMDHSJYoqTECyEEKPk9fk5eq4Ne6WTgyebGfL6yUyM4rtr57It18aM+En0zdy+XW+BGA2vG/5PIUQlgPMYaCaYtQrW/ATmbwJLlDG1inHX9vzzoCDh619DCx3+D3TK46H9P36J8vsIy5yFq7yc3jffBK+XsLlzSf7+94ndsoXQ6cljWL0Qf0xCsBBC3AClFCcbu7E7nJRXNdLWO8S0yFC+nD+D4jwbS2dMm3h9vtfTXKM/BPdFPcDDoXzQVa8Ps1j397D4TyAmxZASRWDFbthA85M/pXvPHlKefJLIvNzrXtPncND0yKMojwdfXx+qpwdzUiLxf/ZnWAsLCJ8vrTAiMCQECyHECDS7Bik97qTE4eRsSw+hZo0186dTlGdj1bxkLCGT+O39ihdGvwv8Mc0Es++GO75pzHpiQrDMmMGM55+jZ/9+nDt3Er16Ncnf2YXZav3MawdOnaL5xz9h8MwZ8PkgLIzYtWuxFhYStex2tBCJICKw5L9AIYQYht3HGiipdPL2hTaUgryZ0/j7bdlsyUllWqQl0OUZo/7o6HeBP6b8UHfUmLXEhKJpGrGbNhG1fDmtTz3FxS1bSX70EWI3bcLf3Y1r/wE6fvlLPPX1AETk5zOtuJiYdeswR0srjJg4JAQLIcQ1+PyKdy60UeJwAvDdl6uYER/BN1dnUZRrIzNxCn4z76w3eL06Y9cTE4o5NpbUJ56gb9MmGh/9IS3/+N/xdXWBz4dmsTDt/vtJfGg7oampgS5ViGuSECyECFpPH6rlmcPnhv36yx0D/Nvhc/zb51yzc03WmEyWGzc+g1ohxmo9MWEopRisqcFVWkb3K6/g6+xEi4gAn4+4r36V5Ed+gMkyRd4hEVOWhGAhRNDatXYuu9bOpbVnkPLjjdgdTk41dRNi0lg5L4nivHRWz09m/o8PUP+zzYEud+yZLcYGV7OEoKnG09iIq3wPrvJy3BcvolksRK9ejbWwgOjlyzmzOIeUH/8o0GUKMSwSgoUQQWnA7ePgqWZKKp0cPdeGz69Ykm7lia0L2bokjYTosECXOL66LkFYDPQbON43boQjlMWE5OvtpefVV3GVldP/wQcAROTfTMrXniR2wwbMsbEBrlCIGyMhWAgRNPx+xft1HdgdDeyvaaZ3yEuaNZyH7ppFcZ6NOckxgS5xfA12w6kyfZjFR28Zu7ZmhswVxq4pxo3yeul75x1cpWX0HD6MGhoi9KaZJH7rm1gLCrCkpwe6RCFGTUKwEGLKO9/aS0llA6WVjTi7BoiymNm0OJWiPBu3ZyZgMk2y83xHw+eFi2/o44vP7APvIMTPhlU/gtQl8PKf6+OPR8tsgfwHRr+OGDdKKYbOnMFVWoZr3z58bW2YrFasxUVMKywkfMmSyXf2tRBfQEKwEGJK6uhzs6eqEbujgaoGFyYNVmQl8YMN81i3MIUIiznQJY4fpaC5GqpeghMvQ18rRMRB7n+DJV8B283wcbiZvlif8jaao9I0M6TmwPRFxtQvxpSnpYXuvXtxlZYxdO4chIYSs/JuYgsKiL77bnnATUxZEoKFEFPGoMfH62dasTsaOHL2Cl6/YmFqLD/avICCJWkkx4YHusTx1d0I1b+B6peg9ZQ+wW3eBsi5H7LWQcg1wk3xc/DsstHtBodY9HXEhOXv66PntddwlZXT9+67oBQRS5aQ8vhPiNmwgZC4uECXKMSYkxAshJjUlFIc+6iT3Q4n+6ob6R70khwTxgPLMynKtbEgNcge2hnqhTN79XaHi28CCtJvhc1PwaIiiIz/4uvjM6HwWSjdAd4bCMIhEfr1cRk3Ur0YQ8rno//993GVldF96DVUfz+hNhuJO/5K7/PNyAh0iUKMKwnBQohJ6aP2PuwOJyWVTi519BMRamZDdgpFuTbunJOIOZj6fP0+qHtTb3c4vQc8fTDtJrj7B5BzHyTMHtl62UX6r2U79DHKw2mN0Mz6DnDhs3+4XkwIg7W1dJeX49qzF29LC6aYGKybN2EtLCQiLw/NNIlHfQsxChKChRCTRle/m73VTZRUOjn2USeaBnfMTmDnmiw2ZKcQFRZkf6W1nNJ3fE+8DD1NEGaFxV/S+3xn3v6HPt8bkV0EaUuh5CFoqtbPD75WGNbM+kNwqTl6C4TsAE8I3rY2XHv34iovZ+jUaTCbiV6xAuujjxC9ahWm8CBrDRLiGoLsO4YQYrJxe/0cOduK3eHk9TOtuH1+spKjeWTDfLblppFqjRjzGnauyRrzewxbTwvU/FYPv80nwBQCc9bChv8OczdCqIHhJj4THjwILSeh4gWoO6qPQva59eAbl6kfg5b/wJR7CC4hPIH2QePOTE4ITzBsrc/jHxyk5/BhXOXl9L31Nvh8hC9axPTHHiN28yZCEsa+hsSHHx7zewhhFE0pNe43zc/PVxUVFeN+XyHE5KCUoqrBhd3RwJ6qRjr7PSRGWyhYYqM4z8aitNjgOqrJM6AfZ1b1Ilx4Xd+RTcvVd3yz74WoxEBXKAJE+f30V1TgKiuj59WD+Ht7CUlJwbp1K9bCAsLmzAl0iUIEnKZpx5RS+Z/+uOwECyEmjIbOfkorndgdTi629WEJMbFu4XTuzUtneVYioeYg6l30++Gjt6H6RThZBu4eiE2HO3fCkvshaV6gKxQBNHSxDld5Gd3le/A0NmKKjCRm/XqshQVE3nqr9PkKMQwSgoUQAdU96GH/iSbsDifv13UAcGtmPA/dPYuNi1OJDQ8NcIXj7EqtHnyrfwOuy2CJhoXbYMl9cNNykHATtLydnXTvewVXeTmD1dVgMhF1xx0k7dpFzJrVmCIjA12iEJOKhGAhxLjz+vwcPdfGbkcDh061MOT1Mysxiu+uncu2XBsz4oPsm3lfO9Ts1vt8Gx2gmWD2aljzOMzfDJYg+3qI3/O73fS+cQRXWRm9v/sdeL2EzZtH8g9+QOyWzYQmJwe6RCEmLQnBQojPePpQLbvWzjV0TaUUJxu7sTuclFc5aet1My0ylPtumUFRro2lM6ZNnD7flpPw4S+g/ih01n/iQbAMyFgBtzw4+gfBPINQe0AfZHHuIPi9+rS2df+gn/AQk2LEZzIiK19aafjDYEfuO2LYesFCKcVA5XH9PN8DB/C7XJiTEon/sz/DWlhA+Pz5gS5RiClBQrAQ4jOeOXzOsBDc5BqgtLKRksoGalt6sZhNrJ6fTHGejZXzkrGETKC39zvqwL4dWk589nxcnxvaaqH9AlT9ClJyoOjn+gkKw6UUXH5f3/E9WQKDLohOgdt36FPcUrKN/5xGwMgAPBbrTXXuS5dwle/BVV6O59IltPBwYtauxVpQQNSy29FC5Fu2EEaSP1FCCMP1DXk5UNOMvbKBdy60oxTcfFMcf78tmy05qUyLvMa43kCrKRnecAjl009raKjQxwsPZzhEx0V9kEX1i/rOcmgkLNiqD7KYtRJMZgM/ETGZ+FwuuvcfwFVezoDDAZpG5G23kbhjBzFr12KOjgp0iUJMWRKChRCG8PkV71xow+5wcqCmmQGPjxnxEXxrdRZFuTYyEifwN/OakpGPCf44DJfu0H//6SA80Knv9la9qO/+okHmXXD3o7BgC4TFGFa+mFyU203vW2/hKi2j9403UB4PltmzSfrOd7Bu3UJoamqgSxQiKEgIFkKMypnmbkocTkqPO2npHiImPIRtufp5vvk3xU2cPt/P01F3dQd4BAH4k7wD+vW2XIhJg/OH9OBbe0BvoUiaD/c8AYu/DFabkZWLSUQpxeCJE7jKyunetw9fVxfm+HimfeV+rAWFhC9aOPH/rAgxxUgIFkKMWGvPIOXHG7E7nJxq6ibEpLFyXhKPb01n9fxkwkMn0dv79u16C8RoeIfgF+vA54GBDohKglv+Um93SF0yuvHFIqDann8eFCR8/WtoocM/rk95PLT/xy/xd3djio7GVVaGu64OzWIhes1qrIWFRN9554jWFEIYa9QhWNO0GcB/AimAH3hOKfXMaNcVQkwsA24fB081Y3c4OXruCn4FS9KtPLF1IVuXpJEQHRboEkeuuUZ/CO6LeoCHQ/mhtwVmr4HbHtKPNzNLuJkKYjdsoPnJn9K9Zw8pTz5JZF7uda/pffttmh77W/yDg/hdLgAi8m8m5YGvE7t+PebY2LEuWwgxDEbsBHuB7yqlHJqmxQDHNE07pJQ6ZcDaQogA8vsV79W1U+Jwsr+mmd4hL2nWcHasnE1RbjpzkqMDXeLoVLww+l3gj2lm/aSIueuNWU9MCJYZM5jx/HP07N+Pc+dOolevJvk7uzBbrX/0OuX10nPoEK1PPY3n8mUAQmfOJP4v/hxrQQGW9PRAlC+E+AKjDsFKqSag6eo/92iadhqwARKChZjE/unAGcqON+LsGiA6LISN2SkU56VzW2Y8JtMUeXu//ujod4E/pnxQd9SYtcSEomkasZs2EbV8Oa1PPcXFLVtJfvQRYjZuxH3mDF2lZXSVlKB6etAsFqxfupe4L32J8CVLpM9XiAnM0J5gTdMygFzgfSPXFUKMvfbeIfZUNVJS6QTgf795gRVZSfxgwzzWLUwhwjKJ+nyHq7Pe4PXqjF1PTCjm2FhSn3iC7hUraH78CZp+/BNUfz9oGqaoSBK/8x0SvvYXaJYJeASgEOIzDAvBmqZFA7uBbyuluq/x77cD2wFmzpxp1G2FECPw9KFanjl8bliv9St4s/YKb9Ze+dzX7FyTZfhkuXHlM6gVYqzWExOGv6+Pntdew1VWRt+774FShKSm4u3vJ2HHX5G0Y4c85CbEJGNICNY0LRQ9AP+XUsp+rdcopZ4DngPIz89XRtxXCDEyu9bO5dv3ZFHxUSd2h5O91Y30DHpJjgmjKNdGUZ6N+SmxZDy6j/qfbQ50uWPPbDE2uJplB3AqUT4ffe+9R3d5Od2HXkP19xOank7ijh1YC7Ziycjg9PwFJH/rW4EuVQhxA4w4HUIDfgGcVko9NfqShBBjob6tD3ulk9JKJ5c6+okINbMhO4XiPBt3zE7EPFX6fIfD74O6NyEkzNgQHDeCEcpiwhqsraW7vBxX+R68ra2YYmKwbt6MdVshEXl50ucrxBRhxE7wncCfASc0TTt+9WOPKaVeMWBtIcQodPW72VvdhN3RgONSF5oGd85OZOeaLDZkpxAVFmRHhbec1AdZnHgZeprAZAE0wIA3pzQzZK4Y/ToiILxXruDatw9XeTlDp05DSAjRy5djfeyHRK9ahSlsEh4BKIT4QkacDvEW+ncRIcQE4Pb6eeNsKyUOJ6+facXt8zN3ejSPbpxP4dI0Uq0RgS5xfPW06KG3+kVoPgGmEJizFjb8DKwz4P9s1scfj5bZAvkPjH4dMW78g4P0HD6s9/m+/Q74fIRnZzP9sceI3byJkISEQJcohBhDQbYNJMTUpJTi+OUuSiqd7KlqpLPfQ2K0hf92+00U59lYlBYbXG/huvvh7Cv6ru+Fw/owi7Q82PhPkH0vRCX+4bXTF4Pz2OiOStPMkJoD0xeNvnYxppTfT/+HFbjKy+g58Cr+vj5CUlNJePBBrIUFhM2eHegShRDjREKwEJPY5Y5+SiudlFQ6udjWR1iIiXWLUijOtbEiK5EQsynQJY4fvx8+elsPvqfKwN0DsemwfBfk3A9Jn3OKRfFz8Oyy0e0Gh1j0dcSENXTxIq6yclx7yvE2NmGKjCRm/XqshYVE3noLmimI/qwIIQAJwUJMOt2DHvafaGK3w8kHdR0A3JYZz1/dPZsNi1OIDQ+yY5qu1OqtDtW/AddlsMTAwkJYcj/cdCdcL9zEZ0Lhs1C6A7w3EIRDIvTr4zJuqHwxdrydnXTvewVXWRmDJ06AyUTUnXeSvOs7xNyzBlNEkLUGCSH+iIRgISYBj8/P0XNXsDucHDrVwpDXz6zEKL63bi6FS23MiI8MdInjq68Nanbru76NDtBMMHsN3PMEzNsElhF+PbKL9F/LduhjlIfTGqGZ9R3gwmf/cL0IOL/bTe8bR3CVldH7u9+B10vY/PkkP/IIsZs3EZqcHOgShRAThIRgISYopRQnG7vZ7WhgT1Ujbb1u4iJDue+WGRTnpbMk3Rpcfb6eQag9oAff84fA74WUxbD+HyH7SxAzfXTrZxdB2lIoeQiaqvWj064VhjWz/hBcao7eAiE7wAGnlGKgshJXWTnd+/fj7+4mJCmJ+D//c6yFBYTPmxfoEoUQE5CEYCEmmCbXAKWVjdgdDZxr7cViNrFmQTJFuTZWzkvGEjL2vYs712SN+T2GRSm49J7e7nCyBAZdEJMKt/+13u5g9INo8Znw4EH9KLWKF6DuqD4K+f9v787Doy7zfO+/71T2pQqSEAIBBBRk18RIi6CyCrJUCXa33c7mMm2PbZ9mtBdtx26l5zxn+jwzxx7nmrk8I9PLPOeZHu3RQFVYRZQWd2IimyggICYECAEqe1LL/fzxw24fBQ2kkqqkPq/r6ouuouqub3lVkg93vr/7G+lygu/gMc4xaOV3D8iL4AoyC2jsaIzper2p6+jRc32+lYSOHsVkZZG3YD4er4+cGddhXL0/6rvw/vt7/TVEpHcYa/t+eFt5ebmtqqrq89cVSVQtnWE27TnOmppaXv+wEWvhmssGs6KshKVTh+PJTrI+38YPYdezzv/OHIG0bJjohatuhzE3QUrvhxtJTJFgkKaNmwgGArRXV4MxZF/3FTw+H3nzF+DKzYl3iSKSYIwx71hryz97v3aCReIkErW8dvAUa2rq2LTnOO2hCKPys/ne3HEsLy1hdGGS/TBvO+3s9u56Fj5+CzAw9ia46WGYuAwycuNdocSJ7eqiZft2gv4ALS+/jA2FSL/icoZ8/0E8y5aRVlwc7xJFpB9SCBbpY+8fb6Kiug7/u3WcaOrEnZnK8rISVpSWcM1lg5Orzzfc5fT37vxP2L/ZaTsYMhHmr4KpXwNPSbwr4b+CywAAIABJREFUlDix1tKxe7fT57t+PZGzZ3EVFDD4jm/i9nrJnDQpub5WRCTmFIJFzvnFlv08sOACZ8n20MnmDgLvHuP56jr21TeRmmKYfWURjy8rYc6EIjLT4vzr/RN7Yccv4ch2p/3gDz2wo2H0DXDtPbHrgbXWGU6x8xnnhIf205AzBK79S6fPt3ga9FG4mf3s7Jj3wG67fVvM1ktGobo6gpWVBP0Bug4fxqSnkzd/Hm6vl9yZMzFpSdYaJCK9RiFY5Jwntx6IaQhu74rwwnvHqaiuY/uBBqIWrho5iFXeySydNoyC3IyYvdYlO30YKu6FE7s/fzRYpAtO7Xf6c3f+1gmny//VuXjsUpz5yDnLd9cz0HgQUjNhwhJnkMXlc8HV99+OYhmAe2O9ZBFpaaF582aCa/207dgBQHZ5OQX33E3ewoW48vLiXKGIDEQKwSIxFI1a3jzcSEW10+fb0hmmZFAW35l9BbeWlnBFUQL1te5Z071zcW3EmaZWW+VMVruYc3E7gs70tp3PwkevOvddNgtm/jVM8kKmp+fvQ/olGw7T+vrrBNf6ad66FdvZSfro0QxZ+T3cy7ykj1ArjIj0LoVgkRg4eLKZiuo61tbUcSzYQW5GKounFrOibATTR+eTkpJgvYt71lz8hLRPwvDa+5zbFwrCkRB8+JLT7vDBBgh3QME4mPsoTP06DL6s5/VLv2StpXPfPudYs/XriZw6hcvjYdBttznn+U6bpj5fEekzCsEil6ixpZPAzmOsqaljV20QV4rhxnGFPLx4IgsmDiUrPUGP8Tp9+NwO8CWMCAbnef77oKT0j4MirIX6nef6fJ+D1gbIyoeyP3faHUrK+qzPVxJP6MQJms71+XYeOIBJSyN3zhw8Pi+5N9yASU+Pd4kikoQUgkUuQkcowtZ9J1lTU8u2DxoIRy2Th7v5ydJJeK8azpC8BOjz/TIV9zotED0R7nLW+eqvYffvnHaHhn3OxXTjF8FV34Qr5jtjhaXfObV6NVgouOvOi7oQzYZCNP76N2Ag/447aH7xRYJ+P61vvAnWklVaSvHjj+FetAjXoEG99wZERLpBIVjkS1hrqfroDBXVtazbVU9zR5ih7gzuuWEMK0pHcGVxP7po5/ge5yK4L+oB7g4bgdod8ItJzu2R18HSX8Dk5ZA1uOd1Sly5Fy3i+Kqf0VRZSfGqVWSXlX7pc9qqazj+2GOYjHTSiovZ/9T/xra1kTZiBIXf+Q4e7zLSL1MrjIgkDoVgkQs4cqqVipo61tTU8vHpdrLTXSya7PT5zri8AFei9fl2R9Wver4L/AkbheGlcNsvoeDy2KwpCSF95EhGrn6a5o0bqVu5kty5cyl68AFcns9fyBgJBql/7DFaXnkFk5pGtKmJrqMf41m6FM+tPrJKS9XnKyIJSSFY5FPOtnVRuaueNdW1VB89izEw64pCHpg/noWTi8nJ6OdfMke293wX+NO62hSAByhjDO7Fi8mZNYuTTzzBoaXLKHr4IdyLF2OMIXTyJCf/4R9o2rARwmFwuci5bgYer5fcObNJyegHrUEiktT6+U90kZ7rCkd5+YOTAEz/v7bSFYly5dA8fnzLBHxXl1DsyYxzhTF05kiM1zsc2/Uk4bjcboY9/jhtXh/1P/0pjU+vxqSn0bF7DwDpY8cy+I47cC++hdT8/DhXKyLSfQrBMuD9Yst+ntx6oFuP7YpEAfjgRDN/t/F9/m7j+597zMp543ptslyvi8SoFaK31pOEY6NR2nZUEQz4CR07hm1rAyD7K19h6N88Qub4fvq1ICJJTyFYBrwHFoz/Q2j9+HQba2rqWFNTx+FTrWSkprBwcjHLy0q469c7OPLzJXGutpe50mMbXF06/WGg6jx0yDnPtzJA+Fg9KTk5uBctwuP1cvTOO7ns338T7xJFRHpEIVgGvKaOEBt21VNRXcfbR04DcN3YfO6bfTm3TCkmL7P7R0D1e4NHO6OQY7beJY5QloQUPnOGpvUbCPr9dOze7fT5zryeou9/n7y5c0nJyop3iSIiMaMQLANSKBJl+4EGnq+uY8t7J+gKR7l8SA4/XHglvquHM2JwdrxL7Futp2DP89B2OnZrGheMuSF260lcRDs7aXl5G8FAgJZXXoFwmIxJEyl6+CE8S5aQOmRIvEsUEekVCsEyYFhr2VPXREVNLYF3j9HY2kV+Tjp3TB/F8tISpo3wJNdRTaEO2L/RGWRxcAtEw8744o4gREM9X9+VDuV393wd6XPWWtpragiu9dO0aRPRpiZSi4rI/4s/x+P1kXml+nxFZOBTCJZ+79jZdta+W8ea6joOnGwh3ZXC/ElFLC8dwU3jh5CemhLvEvuOtXD0Tdj5n7B3LXQGIW8YzLjfGV88dBL82wKoe6dnR6UZFwybBkMnx6526XVdR486fb6BAKGPP8ZkZeG+eQFur5ec667DuBJ01LeISC9QCJZ+qaUzzKY9x6moruWNQ41YC9eOHsz/WD6VJVOH4clOoj5fgMYPYdezsPMZOPsRpOXAxGVw1TdgzI2Q8qlws+JpeGoGhNov/fVS0511JOFFzp6ladMmgv4A7TU1YAw5M65jyHfvJ2/+fFJycuJdoohIXCgES78RiVpePXiKNdW1bNp7nI5QlMsKslk5bxzLS0u4rCDJfpi3nYa9FU67Q+3bgIGxs2HOIzBhKWTknv95+WPA9xSsvQ/ClxCEU7Oc5w8efem1S6+yXV20bN9OcK2flm3bsKEQGeOuoOgH38e9dClpxcXxLlFEJO4UgiXh7atvoqK6Fv+7xzjZ3Ik7M5XbykawoqyEslGDk6vPN9wFB15w2h32b3Z6e4smwYKfwdSvgXt499aZstz503+fs2Z3WiOMy9kB9j31x+dLwrDW0rF7t9Pnu2EDkbNncRUUMPiOb+Lx+ciYODG5vlZERL6EQrAkpJNNHfjfPcbz1bW8f7yZNJdh9pVF3FZWwpwJRWSkJlHvorVQWwW7nnFOeGg/AzlFMP1ep92heCpcSriZshyGXw1rvg31u5zzg88Xho3LuQhu2DSnBUI7wAklVFdHsLKS4Fo/XUeOYDIyyJs3D4/PS87MmZhUfZsXETkffXeUhNHWFeaFvSeoqKnj1QMNRC1cPXIQP/NNZum04eTn9O5ghpXzxvXq+hftzBHY9Tunz/f0h5Ca6bQ5XPUNGDsHXDH48s0fA/e8ACf2QtWv4PB2ZxRypMsJvoPHOMegld89IC+CK8gsoLGjMabr9YVIczPNmzcT9Ado27EDgOxrr6XgW39J3s0348rL69XXL7z//l5dX0SkLxhrbZ+/aHl5ua2qqurz15XEE41a3jzUyPPVdWzaU09rV4SSQVksLy1heVkJlw+5QF/rQNURdE512PkMHH3duW/0DTDtdpjkg0x3fOuTuLGhEC2vvUZTIEDz1pewnZ2kjxmDx+fFvXQZ6SNK4l2iiEhCMsa8Y60t/+z92gmWuDhwopmKmjrW1tRRH+wgLyOVpdOGs7yshOmj80lJSaLexUgIDm512h3e3wCRTuc837k/gWlfh0Gj4l2hxIm1lo733iPo99O0fgORxkZcgwYx6KtfxePzkjl1qvp8RUQukUKw9JlTLZ0E3j3Gmpo6dtcFcaUYbhxXyCOLJ7Jg0lAy05Ksz7f+XWfHd/dz0HYKsgvgmr9w2h2Gl11an68MCKHjx50+X7+froMfYtLSyJ0zB8+tPnJnzcKk925rkIhIMlAIll7VEYrw4r4TVFTX8fv9DUSiliklbn6ydBLeq4YzJC8j3iX2rWDtH/t8T33g9N1eeYszyOKK+c7pC5KUoq2tNG3ZQtDvp+3Nt8BassrKKH78cdy3LMLl8cS7RBGRAUUhOIn9Yst+HlgQ+/Go0ail6qMzVFTXsn53Pc0dYYrdmXzrhrGsKCth/NDevWin207shR2/hCPbnYvQ/nAx2GinD/fae2JzMVhnM+yrdI41O7wdsDDyOlj6jzD5Vsga3PPX6KbZz86O+YVg227fFrP1ko2NRGh9402CAT/NW17EtreTNnIkhd/5Dh7vMtIvuyzeJYqIDFgKwUnsya0HYhqCD59qZU11LRU1ddSeaSc73cWiKcXcVjaC68YW4EqUPt/Th6HiXjix+/Nn5Ea64NR+ZwLbzt9C8TRY/q/OKQoXIxqBQy87gyz2VTpDKQaPgdkPO32++WNj+566KZYBuDfWSxYdH+x3+nzXrSN88iQpbjcerxePz0tWaan6fEVE+oBCsPTImdYu1u06RkVNHTVHz5JiYOYVhXz/5vEsnFxMdnqCfcT2rOnegAgbccYK11Y5I4a7OyDi+B5nx3f3c9ByHDI9cPU3nXaHkdPV55vEwg0NBNetJ+j30/n++5CaSu6NN+Lx+cidfRMpGUnWGiQiEmcJllCkP+gMR3j5/QYqqmt5+YOThCKWK4fm8eNbJuC7uoRiT2a8Szy/PWsuflTwJ2F47X3O7fMF4ebjsPu/nD7fE3sgJRXGLYSrbofxiyBV4SZZRdvbaX5xK8FAgNbXXoNolMxp0xj66KO4F99Can5+vEsUEUlaCsHSLdZaqo+eZU1NLZU76wm2hyjMzeAvZoxmeVkJk4a5E/tXuKcPn9sBvogA/Gnhduf5JaVOz3BXK7y/3gm+h14GG4WSa2DxP8DkFZDTN0MTJPHYaJS2t3cQ9Ptp3ryZaFsbqcOHUXDvt/B4vWSMjU8rjIiI/P8pBMsXOtrYxpqaOtbU1HKksY3MtBRunlTMirISZl1RSKorJd4ldk/FvU4LRE+Eu+C3tzvHl+0LQFcLeEbBrAedY80KE2zinHTbqdWrwULBXXdi0tK6/TwbCtH469+Agby5cwn6AwQrKwnX15OSk0PeLYvw+Hxkl5djUvrJ14qISJJQCJbPCbaH2LC7norqWnYcOQPAjLEFfGfOFdwypZi8zO6HhIRwfI9zEdwX9QB3h41Aw/tw5ihMvc0JvqOuB4Wbfs+9aBHHV/2MpspKiletIrus9Euf01ZdQ/2jjzo3UlNp+F9PgMtFzszrKfrB98mbO5eUrKxerlxERC5VTEKwMWYR8CTgAv7NWvvzWKwrfScUifL7DxpYU1PHln0n6ApHuXxIDj9ceCW3lpZQMqgf/zCv+lXPd4H/IAWu+josezJG60kiSB85kpGrn6Z540bqVq4kd+5cih584Lxn84YaGjj20EO0V72DDYchGiVj0kSKHn4Iz5IlpA4ZEod3ICIiF6vHIdgY4wL+BVgA1AI7jDEBa+17PV1bet+u2rNUVNdRufMYja1d5Oekc8f0UawoK2FqiSex+3y768j2nu8C/0EUPnojRmtJIjHG4F68mJxZszj5xBMcWrqMoocfwr14MQBtVVWc+ud/oe3tt8FaXIWFDLrVh9vrJXN87M/bFhGR3hWLneDpwEFr7SEAY8wzgA9QCE5QdWfbWVtTB4D3n18j3ZXCgklDWV5awk1XDiGtv/T5dteZIzFe73Bs15OE4nK7Gfb447R5fdQ/8ggN//gk0fZ2IqdOgTHkzJpJwV13kf2Vr2BcSTTqW0RkgIlFCC4BPv7U7VrgK599kDHmXuBegFGjRsXgZeVCfrFlP09uPdDtx3dFoqzfXc/63fXn/fuV88b1ymS5PhOJVStEL60nCSVy9ixNGzcS9AfoOnLkD/fn3bKIYY89jmuQxheLiAwEsQjB5/t9uf3cHdY+DTwNUF5e/rm/l9h5YMF4HlgwnnAkyqsHT7Gmpo7Ne4/TEYpyWUE2K0pHsLy0hBv//mWO/HxJvMvtfa702AZXV3rs1pKEYLu6aHnlFedYs22/h1CIjHHjKPrhD3AvXcrBm2Yz4he/iHeZIiISQ7EIwbXAyE/dHgEci8G6coneO9ZERXUt/p3HaGjuxJOVxm1lI1hRNoKyUYMGRp9vd4U7IbsQmmP4kRx8kSOUJSFZa+nYuZNgIEDT+g1EgkFchYXk33EHnlt9ZEyYkFxfKyIiSSYWIXgHMM4YMwaoA74B3BGDdeUinGjqYG1NHWtq6nj/eDNpLsOcK4tYUVbCnAlFZKQmUe+itVC7wxlksed56Dgbu7WNC8bcELv1pM911dY6wdcfoOujjzAZGeTNn4/H5yXn+usxqTo5UkQkGfT4u721NmyM+S6wGeeItF9Za/f2uDL5Um1dYTbvPU5FdR2vHTxF1MLVIwfxt77JLJ02nME5SfZr+9OHYdfvYNczcPoQpGbBhCUwaga88OilT4v7NFc6lN/d83WkT0Wam2natImg30971TsAZE+fTsG93yJv4UJcublxrlBERPpaTLY8rLUbgA2xWEu+WCRqefNQI89X17Jpz3HauiKMGJzF/XOuYHlpCWOHJNkP8/az8N5aZ9f36Lmjy0bfADd8HyZ6IdPt3LfrWah7p2dHpRkXDJsGQyf3vG7pdTYUouXVVwkGArRsfQnb1UX6mDEM+eu/xrNsKWklJfEuUURE4ki/9+sn9p9opqK6jrU1dRxv6iAvIxXvVcNZXlrCtaPzSUlJot7FSAgOboWd/wkfbIRIJxSOh3k/halfh0EjP/+cFU/DUzMg1IPd4NR0Zx1JWNZaOva+RzDgp2ndeiKnT+MaPJhBX/sanlt9ZE6Zoj5fEREBFIITWkNzJ4Gdx1hTU8ueuiZcKYabxg/h0aUTmT9xKJlpSdbne6zG2dHd/Ry0nYLsArjmTmd88fBS+KJwkz8GfE/B2vsurS0iNct5/uDRl/oOpBeF6usJVq4jGPDTdfBDTFoauXPn4vF5yZ01C5OeZK1BIiLypRSCE0xHKMKW905QUV3LKwdOEYlappZ4+OnSSXivHk5hbka8S+xbZz+G3b+Dnc/CqQ/AlQFX3uIE3yvmgyut+2tNWe786b/PGaPcndYI43J2gH1P/fH5khAiLa00b9lC0O+n7a23wFqyysooXrUK96KF5x15LCIi8gmF4AQQjVp2HDlNRXUdG3bX09wZZpgnk3tvHMuK0hLGDc2Ld4l9q7MZ3gs47Q5HXgWsc3Hbsidh0q2QNejS156yHIZfDWu+DfW7nPODzxeGjcu5CG7YNKcFQjvACcFGIrS+/gbBQIDmLVuwHR2kjRpF4f334/EuI12DeEREpJsUguPoUEMLa2rqqKiuo+5sO9npLm6ZMowVZSVcN7YAVy/3+a6cN65X178okTAc2uac7LBvndOyMHgMzP4xTPu6084QK/lj4J4X4MReqPoVHN7ujEKOdDnBd/AY5xi08rsH3EVwBZkFNHY0xnS9vtDxwQcE1/ppWreOcEMDKW43nlt9eLw+skqv7vU+38L77+/V9UVEpO8Za/t+eFt5ebmtqqrq89dNBKdbu1i36xjPV9ex8+OzpBiYeUUht5WN4ObJQ8lOT7J/lxzf7ZzssPu/oOUEZA6CKSvgqm/CiGu/uM9XBrTQyZM0rVtP0O+n84MPIDWV3Jtucvp8Z88mRX2+IiLSDcaYd6y15Z+9P8kSV3x0hiO8tO8kFTV1vPz+ScJRy4TiPB5ZPAHf1SUMdWfGu8S+1VTvhN6dz8DJvZCSBuMXwrTbnT9Tk6zvWf4g2tZG89atBP0BWl9/HaJRMqdNY+hPHsW9eDGpgwfHu0QRERkgFIJ7ibWW6qNnqKiuY92ueoLtIYbkZXDXzNEsLx3BpOHueJfYt7pa4f31Tp/voW1go1BSDov/AabcBtn58a5Q4sRGo7S9/TZBf4DmzZuJtrWRNnw4Bfd+C4/XR8ZYjakWEZHYUwiOsaONbVTU1LKmpo6PGtvITEth0eRilpeNYOblBaS6UuJdYt+JRuDIdudkh30B6GqBQaOcQRbTvgGFV8S7QomjzoMHCfoDBNetI1xfT0puLnmLb8Hj9ZJdXo5JSaKvFRER6XNJFYJ/sWU/DywYH/N1g20h1u+up6K6lqqPzmAMzBhbwHfnXMEtU4eRm5Eg/5lP7IUdv3SC6Zkjn7oQbLQzZe3ae2JzIdjJfX/s822qgwy30+c77RvOKQ99HG5mPzs75heDbbt9W8zWSybhxkaa1m8g6PfTsXcvuFzkzJrJ0B/+gNy5c0nJTLLWIBERiZsESWd948mtB2IWgrvCUX6/v4E1NbW8+N5JuiJRrijK5UeLruTWq0sYPigrJq8TE6cPQ8W9cGL358/HjXTBqf3Q+CHs/C0UT4Pl/3rxpzG0NMCe55x2h/qdzhFjV8yHm/+7c65vWvz+e8QyAPfGegNdtLOTlpdeIugP0LJ9O0QiZE6axNAfP4x7yRJSCwvjXaKIiCShpArBPWWtZVdtkIrqWip31XO6tYuCnHTu+MoobisbwZQSd+KNZN2zpnvDIWzEGSlcW+WMF+7OcIhQO3ywwWl3OPiis8awq2HRz2HKVyF3SGzfi/QbNhqlvbqaoN9P06bNRJubSR06lIK778Lj9ZIxLoGO5xMRkaSkENwNdWfbWVtTx/PVtRxqaCU9NYUFk4ayorSEG8cPIS1R+3z3rLn4McGfhOG19zm3PxuEo1E4+oaz4/ueHzqbwF0CM7/ntDsUTYhd/dLvdB05QjAQIOgPEKqrw2Rn416wAM+tPrKnT8e4kmjUt4iIJDSF4Ato7gixcfdxKmpqefPQaQCmj87n3hvGcsvUYXiyLmJcbzycPnxuB/giAvCnhdud55eUOj3Dpw46gyx2PgvBo5CeCxO9zvji0bMgReEmWUXOnqVp40aCa/2079wJKSnkzJjBkJXfI2/+fFKys+NdooiIyOcoBH9KOBJl+8FTVFTX8cLe43SGo4wpzOHBBeNZXlrCyPx+9MO84l6nBaInwl3w7z7IKYS6KjApMHY2zPsJTFgC6TmxqFTi4NTq1WCh4K47MWnd/wedDYVo/PVvsNEIGZdfTlMgQPO230MoRMa4cRT98Ie4ly4lbWhRL1YvIiLSc0kfgq217D3WxJqaOvzvHuNUSyeDstP4evlIlpeVUDpyUOL1+X6Z43uci+C+qAe4O2wEzh6BlFRY8Lcw9WvgHhaTEiW+3IsWcXzVz2iqrKR41Sqyy0q/9Dmt1dXUP/QwNhQi2tpKtLkZV2Eh+X/yJ3h8XjImTOh/XysiIpK0kjYEHw924H+3jorqOj440UyayzB3QhErykYw58oi0lMTtM+3O6p+1fNd4E+YFLh8ttPzKwNG+siRjFz9NM0bN1K3ciW5c+dS9OADuDyezz22fd8+jv/kp3Ts2weRCGRk4J4/H8+tPnJmzMCkJu23ERER6ceS7qdXRbUzyOLVg6ewFspGDeJvb53C0qnDGJyTHu/yYuPI9p7vAn/CRuHw9tisJQnFGIN78WJyZs3i5BNPcGjpMooefgj34sVEm5sJbtzI6X//d0KHDgOQdc01DFqxgryFN+PKzY1z9SIiIj2TNCE4sPMYAA/+bicj87P4b3PHsby0hDGFA7Cv9cyRGK93OLbrSUJxud0Me/xxWpcs4dhDD3Pi735O5OxZCIcxaWkMuv12Cr99L2nDh8e7VBERkZgZECH4F1v28+TWA91+/Men2/mnrQf4pws8Z+W8cb0yWa7PRGLUCtFb60nCsNbSsWcvwUCApvXriZw+jcnKgnCYwX/yJxQ99CNS0gfIb0hEREQ+ZUCE4AcWjO9WaB398HqO/HxJH1QUZ6702AZXl0LQQBOqrycYqCQYCND14YeY9HRy587F4/WSe8Ms3p86jeKfPBrvMkVERHrNgAjB8ilnP4YMN7Sdit2agy9yhLIkpEhLK80vvEAwEKDtrbfAWrKuuYbin63CvWgRLrc73iWKiIj0GYXggaCjCfYFYOczcORVwMZubeOCMTfEbj3pUzYcpvWNNwn6/TS/+CK2o4O0y0ZR+N378Xi9pI8cGe8SRURE4kIhuL+KhOHQNmd88fvrnQlv+WNhziMw7Gr4rz93xh/3lCsdyu/u+TrSpzref5+gP0BwXSWRhlOkeDx4bvXh8fnIuvpqnecrIiJJTyG4P7EWju+GXc/Crt9B60nIGgylfwLTvgEjyuGTcDN0KtS907Oj0owLhk2DoZNjU7/0qtCJkzStW0cwEKDzgw8gLY3cm250+nxnz9YFbiIiIp+iENwfNNXD7t/Bzmfh5F5ISYPxC+Gqb8K4myH1POFmxdPw1Iye7QanpjvrSMKKtrXRvHUrwbV+Wt94A6JRMq+axtCf/gT3LbeQOnhwvEsUERFJSArBiaqrFfatc9odDv/eGVox4lpY8r9g8grIzv/i5+ePAd9TsPY+p1XiYqVmOc8fPPqSypfeYyMR2t5+m6A/QPMLLxBtayOtpISCb9+Lx+slY4wuZBQREfkyCsGJJBqBw6847Q7vBSDUCoNGwQ0/gKu+AQWXX9x6U5Y7f/rvc8Yod6c1wricHWDfU398viSEzoMHCfr9BCvXET5+nJTcXNxLFuPxesm65hpMSj8e9S0iItLHFIITwcl9zo7vrv+C5mOQ4YGpX3WC78jroCfhZspyGH41rPk21O9yzg8+Xxg2LuciuGHTnBYI7QAnhHBjI03r1xNc66fjvffA5SJ31iw8D/2I3DlzSMnMjHeJIiIi/VJSheCV88bFu4Q/ajkJu59zwu/xXU4IHbcAFv0PGH8LpMUw3OSPgXtegBN7oepXcHi7Mwo50uUE38FjnGPQyu8ekBfBFWQW0NjRGNP1elO0o4OWl14i6A/Q8uqrEImQOXkyQx/5Me4lS0gt6N3XByi8//5efw0REZF4MtbG8EzZbiovL7dVVVV9/rpxF2qHDzY45/ke3OrsyA672rnAbcptkDsk3hVKnNholPZ33uGs30/zps1EW1pILS7Gs2yp0+c7LoH+ASciItKPGGPesdaWf/b+pNoJjotoFI6+7gTf9/zQ2QTuEpj5PedYs6IJ8a5Q4qjz8GGCgQBN/gChY8cw2dm4b74Zj89L9vTpGJcr3iWKiIgMSArBveXUASf47vodBI9Cei5M8jl9vpfN6lmfr/Rr4TNnaNq4kaDfT8fOXZCSQs7GxGX3AAASrElEQVSMGQx54K/JmzePlOzseJcoIiIy4CkEx1JrI+ytcPp8694BkwJj58C8n8KEJZCucJOsol1dtGzbRjAQoOX3r0AoRMb48RT98Ie4ly4lbWhRvEsUERFJKgM7BJ/YCzt+CUe2w5kjn7oQbDSMvgGuvafnF4KFO2H/JmeQxYHNEA0709pu/u8w9WuQVxyLd3JRZj87O+YXgm27fVvM1ksW1lra332XoN9P08ZNRINBXEMKyf/TP8Xj85I5Qa0wIiIi8TIwQ/Dpw1BxL5zY/fnzcSNdcGo/NH4IO38LxdNg+b86Jyh0l7Xw8dvOju/eNdBxFnKL4br7nD7f4imxf08XIZYBuDfWG+i6Pv6YYCBAMBAg9NFRTGYmefPn4/H5yJlxHSZ1YH7ZiYiI9CcD76fxnjXdGw5hI85pDbVVznjh7gyHOH3I6fHd+YxzxFhqFkxc5vT5jp0NKbqIKVlFgkGaNm0mGAjQ/s47YAzZ06dT+O2/Iu/mBbhyc+NdooiIiHzKwArBe9Zc/JjgT8Lw2vuc258Nwu1nnN3enc/Cx28CxjlT96YfOQE4Iy9m5Uv/YkMhWra/StDvp+Xll7FdXaRffjlDHngAz7KlpA0fHu8SRURE5AIGTgg+ffjcDvBFBOBPC7c7zy8phbzhcPBFp91h/yanhWLIBJj3GEz7OnhGxLZ26TestXTs2UPQH6Bp/XoiZ87gGjyYQbffjsfrJXPKZIwx8S5TREREvsTACcEV9zotED0R7oRf3gyRELSfhuxCKL8HrrrdGWqhcNOvnVq9GiwU3HUnJi2t28+zoRANT/4THfv2Eaqvp+vQIUx6Orlz5+LxecmdNeui1hMREZH461EINsb8PbAM6AI+BO6y1p6NRWEX5fge5yK4L+oB7g4bhZYTcPlc+MpfOX+6FG4GCveiRRxf9TOaKispXrWK7LLSL3x8pKWFxqdXc/r//B9su/Mbhqzyayi+cxXuRYtwud19UbaIiIj0gp7uBG8BfmytDRtj/ifwY+Chnpd1kap+1fNd4E8YF+SPhfELY7OeJIz0kSMZufppmjdupG7lSnLnzqXowQdweTx/eIwNh2l9/XXOPvc8zVu3QiSCq7CAQX95D4N8PtJHqBVGRERkIOhRCLbWvvCpm28CX+1ZOZfoyPae7wJ/wkbg8PbYrCUJxxiDe/FicmbN4uQTT3Bo6TKKHnqI9LFjaApUcraykmhjIxhD+uWXM/THD5Nz/fXq8xURERlgYtkTfDfwbAzX674zR2K83uHYricJx+V2U3jfdzApKdQ/8gi2qwtcLlyDPKQOG8bw//t/knPttfEuU0RERHrJl4ZgY8yLwPnGnv2NtdZ/7jF/A4SB//iCde4F7gUYNWrUJRV7QZEYtUL01nqSMKJtbTS/+CLBtX5a33wTolEyp00jdUghLVtfIv/OOym48+IunBMREZH+50tDsLV2/hf9vTHmL4ClwDxrrf2CdZ4GngYoLy+/4OMuiSs9tsHVlR67tSTubCRC21tvOceabdmCbWsjraSEwr/6Nu5ly8gY40wL3DdhIoXf+lacqxUREZG+0NPTIRbhXAh3k7W2LTYlXYLBo51RyDFb7yJGKEvC6jxwgKDfT7ByHeETJ0jJy8OzZDEen4+ssjJMSkq8SxQREZE46WlP8D8DGcCWcxcOvWmt/aseV3WxRt8AjR/G5uI443Imwkm/FD51iqb16znr99P53j5wuci94QY8Dz9E7pw5pGRmxrtEERERSQA9PR3iilgV0iPld8PO3zrjj3vKle6sJ/1GtKOD5q1bCQYCtL76GkQiZE6ezNBHHsG9ZDGpBQXxLlFEREQSzMCYGFc8BYZOhbp3erYbbFwwbBoMnRy72qRX2GiUtqoqgoEAzZs2E21pIbW4mIK778bj85JxRWL8+0xEREQS08AIwQArnoanZvRsNzg13VlHElbnocMEA36aApWEjh0jJTubvIUL8fi8ZE+frj5fERER6ZaBE4Lzx4DvKVh7H4QvIQinZjnPHzw65qVJz4TPnKFpwwaC/gAdu3ZBSgo511/PkAceIG/eXFKys+NdooiIiPQzAycEA0xZ7vzpv88Zo9yd1gjjcnaAfU/98fkSd9GuLlpe3kYwEKDl97+HcJiMK6+k6Ec/wr10CWlFRfEuUURERPqxgRWCwQmyw6+GNd+G+l3O+cHnC8PG5VwEN2ya0wKhHeC4s9bSXvMuQb+fpk2biAaDuIYUkv9nf4bH5yVzwoR4lygiIiIDxMALweC0RtzzApzYC1W/gsPbnVHIkS4n+A4e4xyDVn73gLwIriCzgMaOxpiu15u6jh4lGKgkGAgQOnoUk5lJ3oIFeLxecmZch0ntm49p4f3398nriIiISPyZLxjy1mvKy8ttVVVVn7+uJI5IMEjTxk0EAwHaq6vBGLK/8hU8Ph95Cxbgys2Jd4kiIiIyABhj3rHWln/2/oG5EywJyXZ10fLqqwT9AVpeegkbCpF+xeUMefBBPMuWkjZsWLxLFBERkSShECy9ylpLx549BNf6adqwgciZM7jy8xn0zW/g8frInDyJc9MGRURERPrMgAjBs5+dHfMe2G23b4vZeskoVFdHsHIdQb+frsOHMenp5M6bi8fnI3fmTExaWrxLFBERkSQ2IEJwLANwb6yXLCItLTRv3kzQH6Dt7bcByC4vJ//uu3AvXIjL7Y5zhSIiIiKOARGCJX5sOEzr668TXOuneetWbGcn6ZddxpCV38O9bBnpI0bEu0QRERGRz1EIlotmraVz3z6C/gDB9euJnDqFy+Nh0G0r8Ph8ZE6bpj5fERERSWgKwdJtoRMnaKqsJOgP0HngAKSlkTd7Nh6fl9wbb8Skp8e7RBEREZFuUQgewE6tXg0WCu6686IuRLOhEI2//g0YyL/jDppffJGgP0DrG2+AtWRdfTXFjz+Ge9EiXIMG9d4bEBEREeklCsEDmHvRIo6v+hlNlZUUr1pFdlnplz6nrbqG4489hsnIIK14KPuf+t/YtjbSRoyg8L778HiXkT56dO8XLyIiItKLFIIHsPSRIxm5+mmaN26kbuVKcufOpejBB3B5PJ97bCQYpP6xx2h5ZTsmNZVoUxNdH32EZ8kSPLf6yCorU5+viIiIDBgKwQOcMQb34sXkzJrFySee4NDSZRQ9/BDuxYsxxhBqaODk3/89TRs2QjgMLhc558YX586ZTUpGRrzfgoiIiEjMKQQnCZfbzbDHH6fN66P+pz+l8enVmIx0OnbtBiB97FgGf/ObuJcsJjU/P87VioiIiPQuheAkYaNR2nZUEQz4CR07hm1rAyB7+nSG/s0jZF55ZZwrFBEREek7CsEDXOehQ855vpUBwsfqScnOxr1oER6vl6N33sll/8+/x7tEERERkT6nEDwAhc+coWn9BoKBAB27dkFKCjkzZ1L04PfJmzeXlKyseJcoIiIiElcKwQNEtKuLlpe3EfT7aXnlFQiHyZg4kaKHHsK9ZDFpRUXxLlFEREQkYSgE92PWWtpragj6AzRt3Ei0qYnUIUPI/4s/x+P1kXnl+HiXKCIiIpKQFIL7oa6jR8/1+VYSOnoUk5VF3oL5eLw+cmZch3G54l2iiIiISEJTCO4nIsEgTRs3EfT7aa+pAWPImXEdhd+5D/eCBaTk5MS7RBEREZF+QyE4gdmuLlq2byfoD9Dy8svYUIj0Ky5nyPcfxLNsGWnFxfEuUURERKRfUghOMNZaOnbvJrjWT9OGDUTOnsVVUMDgO76J2+slc9IkjS8WERER6SGF4AQRqqsjWFlJcK2friNHMBkZ5M2bi8fnI+f66zFpafEuUURERGTAGBAhuCCzgMaOxpiu1xcizc00b95M0B+gbccOALKvvZaCv7yHvIULceXl9errF95/f6+uLyIiIpKojLW2z1+0vLzcVlVV9fnrJgIbDtP62msE/X6at76E7ewkffRoPLf6cC9dRvqIkniXKCIiIjJgGGPesdaWf/b+AbETnOistXTu20fQ7ye4bj2RxkZcHg+DbrsNj89L5rRp6vMVERER6UMKwb0odOIETZWVBP1+Og8cxKSlkTtnDh6fl9wbbsCkp8e7RBEREZGkpBAcY9HWVpq2bKEpEKD1jTfBWrJKSyl+/DHcixbhGjQo3iWKiIiIJD2F4BiwkQitb77p9PlueRHb3k7aiBEUfuc7eLzLSL/ssniXKCIiIiKfohDcAx0f7CcY8NNUuY7wyZOkuN14li3Dc6uPrNJS9fmKiIiIJCiF4IsUbmgguG49wUCAzn37IDWV3BtvxOP1kjtnNikZGfEuUURERES+hEJwN0Tb22ne+hJBv5/W116DaJTMqVMZ+uijuBffQmp+frxLFBEREZGLoBB8ATYape3tHQQDAZo3byba2krqsGEUfOtbeHxeMsaOjXeJIiIiInKJBlQIPrV6NVgouOvOixozbEMhGn/9GzCQN3cuQX+A4LpKwsfqScnJIW/hQjw+H9nXlmNSUnrvDYiIiIhInxhQE+O6Pv6Y46t+RvjECYpXrSK7rPRLn9NWXUP9o486N1JT6dq/H1JSyJk1E4/XR968uaRkZcW8VhERERHpfb06Mc4Y8wPg74Eh1tpTsVjzUqSPHMnI1U/TvHEjdStXkjt3LkUPPoDL4/ncY0MNDRx76GHaq6qw4TBEo2RMnEjRww/hWbKE1CFD4vAORERERKQv9DgEG2NGAguAoz0vp+eMMbgXLyZn1ixOPvEEh5Yuo+jhh3AvXgxA2zvvcOqf/4W2t94Ca3EVFuLxefF4fWReOT7O1YuIiIhIX+hxO4Qx5jngbwE/UN6dneDeaoc4n7bqGo4/9hikpRFuaCDS0ADGkDNrJvl33knOdddhXK4+qUVERERE+taF2iF6dJWXMcYL1Flrd3bjsfcaY6qMMVUNDQ09edmLkl1WypiK58m6ahqRhgbyblnE+DfeYNTq1eTOnKkALCIiIpKEvnQn2BjzIlB8nr/6G+AR4GZrbdAYc4QE3An+tH0TJjLx/X19/roiIiIiEh+XfGGctXb+BRacCowBdp4bDzwCqDbGTLfWHu9hvSIiIiIiveaSL4yz1u4Gij65fTE7wSIiIiIi8aTJDyIiIiKSdGI2Mc5aOzpWa4mIiIiI9CbtBIuIiIhI0lEIFhEREZGkoxAsIiIiIklHIVhEREREkk5SheDC+++PdwkiIiIikgCSKgQP+W/fjXcJIiIiIpIAkioEi4iIiIiAQrCIiIiIJCGFYBERERFJOsZa2/cvakwD8FGfvzAUAqfi8LrSP+jzIReiz4ZciD4bciH6bCSOy6y1Qz57Z1xCcLwYY6qsteXxrkMSkz4fciH6bMiF6LMhF6LPRuJTO4SIiIiIJB2FYBERERFJOskWgp+OdwGS0PT5kAvRZ0MuRJ8NuRB9NhJcUvUEi4iIiIhA8u0Ei4iIiIgkTwg2xiwyxnxgjDlojHk43vVIYjDGjDTGvGyM2WeM2WuMWRnvmiSxGGNcxpgaY8y6eNciicUYM8gY85wx5v1z30NmxLsmSQzGmAfO/UzZY4z5T2NMZrxrks9LihBsjHEB/wLcAkwCvmmMmRTfqiRBhIHvW2snAtcB9+uzIZ+xEtgX7yIkIT0JbLLWTgCuQp8TAYwxJcD3gHJr7RTABXwjvlXJ+SRFCAamAwettYestV3AM4AvzjVJArDW1ltrq8/9/2acH2Il8a1KEoUxZgSwBPi3eNciicUY4wZuBH4JYK3tstaejW9VkkBSgSxjTCqQDRyLcz1yHskSgkuAjz91uxYFHfkMY8xooBR4K76VSAL5R+BHQDTehUjCGQs0AL8+1y7zb8aYnHgXJfFnra0D/gE4CtQDQWvtC/GtSs4nWUKwOc99OhZD/sAYkws8D/y1tbYp3vVI/BljlgInrbXvxLsWSUipQBnwlLW2FGgFdL2JYIwZjPPb5jHAcCDHGPOn8a1KzidZQnAtMPJTt0egX03IOcaYNJwA/B/W2op41yMJYybgNcYcwWmhmmuM+X/jW5IkkFqg1lr7yW+OnsMJxSLzgcPW2gZrbQioAK6Pc01yHskSgncA44wxY4wx6TgN6oE41yQJwBhjcHr69llrn4h3PZI4rLU/ttaOsNaOxvme8ZK1Vrs5AoC19jjwsTHmynN3zQPei2NJkjiOAtcZY7LP/YyZhy6aTEip8S6gL1hrw8aY7wKbca7S/JW1dm+cy5LEMBP4M2C3Mebdc/c9Yq3dEMeaRKR/+G/Af5zbXDkE3BXneiQBWGvfMsY8B1TjnEBUg6bHJSRNjBMRERGRpJMs7RAiIiIiIn+gECwiIiIiSUchWERERESSjkKwiIiIiCQdhWARERERSToKwSIiIiKSdBSCRURERCTpKASLiIiISNL5/wDL5iY1TzwGcQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# Use marker for string code\n",
    "# Use markersize or ms for size\n",
    "\n",
    "ax.plot(x, x-1,marker='+',markersize=20)\n",
    "ax.plot(x, x-2,marker='o',ms=20) #ms can be used for markersize\n",
    "ax.plot(x, x-3,marker='s',ms=20,lw=0) # make linewidth zero to see only markers\n",
    "ax.plot(x, x-4,marker='1',ms=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom marker edges, thickness,size,and style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "\n",
    "# marker size and color\n",
    "ax.plot(x, x, color=\"black\", lw=1, ls='-', marker='s', markersize=20, \n",
    "        markerfacecolor=\"red\", markeredgewidth=8, markeredgecolor=\"blue\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Final Thoughts\n",
    "\n",
    "After these 4 notebooks on Matplotlib, you should feel comfortable creating simple quick plots, more advanced Figure plots and subplots, as well as styling them to your liking. You may have noticed we didn't cover statistical plots yet, like histograms or scatterplots, we will use the seaborn library to create those plots instead. Matplotlib is capable of creating those plots, but seaborn is easier to use (and built on top of matplotlib!).\n",
    "\n",
    "We have an additional notebook called \"Additional-Matplotlib-Commands\" which you can explore for other concepts, mainly as a quick reference. We also highly encourage you to always do a quick Google Search and StackOverflow search for matplotlib questions, as there are thousands of already answered questions there and almost any quick matplotlib question already has an answer there.\n",
    "\n",
    "----\n",
    "----"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}