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@shane5ul
Created May 15, 2017 18:08
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Using built-in and user-defined styles in Matplotlib
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us define a function that calls a basic 2D plot."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def plot1():\n",
" x = np.linspace(0,1)\n",
" y = x**2\n",
" plt.plot(x,y,'o-')\n",
" plt.xlabel('x')\n",
" plt.ylabel('y')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Using the default or ('classic') style, we get something that looks like this."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEPCAYAAABY9lNGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f22adb3a978>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot1()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Not bad, but pretty basic. Two features that I don't like: (i) some default parameters like text size, and line width, and (ii) the color scheme. Fortunately, both of them have easy fixes.\n",
"\n",
"The jarring color scheme is a holdover from an era when people printed stuff to read. They are set to improve in the next release of matplotlib. Even now, there are a number of more pleasing \"styles\" that are available. You can find out which ones are available on your system by:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['seaborn-pastel', 'dark_background', 'classic', 'seaborn-dark', 'seaborn-notebook', 'bmh', 'seaborn-darkgrid', 'seaborn-talk', 'seaborn-ticks', 'seaborn-whitegrid', 'seaborn-bright', 'seaborn-poster', 'grayscale', 'seaborn-dark-palette', 'ggplot', 'seaborn-white', 'fivethirtyeight', 'seaborn-muted', 'seaborn-colorblind', 'myjournal', 'seaborn-deep', 'seaborn-paper']\n"
]
}
],
"source": [
"print(plt.style.available)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A style I am fond of is bmh. You can invoke it quite simply by:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"plt.style.use('bmh')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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fvi2dNbMzgXuccyMjx3cCzjl3X6XzhgPzgXOdcztjfda8efPc9ddf39hDDgRt\nkuapLRYVtYnt+4opKC2nqNdQtqx8hS5Dr0q57cR1XXgUC09Dls76mSwygU8IF7g3A+8DY5xzH0ed\ncxrwLDDCOfd5dZ+lPgs5UnmhEBOnz8EGjzmsZ2Lo8JGsefcfZJ415rDmuic03SQpKBDPs3DOlQE/\nAJYDq4FnnHMfm9kMM/tm5LT7gVbAs2b2bzP7q1/jk9R29/zHDiUK8GoTzTavYskvbqNf/gqOXrWM\nfvkrlChEYvC1ZuGc+xtwcqXX7o76+cK6fI6eZ+HRLbYnViy2FZSw6F+bWLlhD936xH4gUSpu+qfr\nwqNYxEdSFrhF6quiLrFt3wH2lTiKew8lo30XMixDPRMiDRDIXWfVZ+HRX0ye7tnZTJw+h9XdhvPl\nqVdx4NRvkZ/zFwa23s8Td38f3nkmkD0T9aHrwqNYxEcgk4VIZeXOcfvcR2PWJQ6s+jtn9O3NE7Om\nqTYhUk+BnIZSzcKTjvOx0dtzdGrVnAtHfZuXN2Xywf8+o+epsesSkF4PJErH66I6ikV8BDJZSPqq\nvG341pIiXr33ITqffTlNM1WXEGksgZyGUs3Ck25/MVW3PUf7L97g+QX3plVdoibpdl3URLGIj0Am\nC0lP63YW8a8Ne2JuG966qXFiz+NVlxBpJIGchlLNwpOq87HRdYkWTZvQ4asXsWp/S/YWl5NVzVRT\nRSzSpS5Rk1S9LupDsYgP3VlI0qm8bXhezxG89McnKdu9lTFjrqHs7WBuGy4SZHoGtySd8VPvYmOv\nkVXuHnrnLWfhffccuuvQs69FjoyewS2BVHkJ7MjLr+T17U35VzVbcxQcKAXSawmsSLII5DSUnsHt\nCerzhStPNa0+bjhTZ83n3dWf0yQj49A0U4W6LIENaiwag2LhUSziI5DJQoJvzoJFMZfAtlv3Or//\nfzdrCaxIkgnkNJT6LDzJvsrjsKmm1s353oRryd2XxZtf7KJLr6pTTW2aZdC3d0+emDXtiB9nmuyx\n8JNi4VEs4iOQyUKCIVa39VW33Ufnsy+nzFmN3daqS4gkl0BOQ6lm4Unm+di5jyyOOdXE//7OnGnf\nxb0T3yWwyRwLvykWHsUiPnRnIXERPd3ULqspAy+4lLe+2EWnnlWnmrq2bcbFZ/Sl76zbjniqSUQS\nQ30W0mCVp5sqnm8NxrEXXVdlqqlf/gpNMYkkQCCewS2pqai0jKlzFsacbjqpY/O4TzWJSGIEchpK\ne0N5/Nxxl1puAAAKH0lEQVT3JnqqqVmTTI4/62JyC1ry2dYCug2Isblf69Y8NHWSb1NN2gPIo1h4\nFIv4CGSyEP/lhUJMmD6HjMiT6MpKinjvqcV0Pvty2rVoWu3KJq1qEkkNqlnIYSr3Rfzwu+PZZu35\nyYxZZJx+WZWE0GPdK9w95YYqNQveeUbbg4skGe0NJXERqy/i0lt+QaezLmdHQTHdYjxHorj0ID2y\ns+vVRCciwRHIZKGahac+87GV7x4qdm2d+fDjVQrVXS8cT8Hbf6J3p1YUJHkTneamPYqFR7GID62G\nSjNVNvDrNpyrbpvNtY/+k3fzdsd8Cl2vji146M4btV+TSBpTzSLNTJk+k9Xdhle5Q9j6+rNkZhid\nzrmy2r4IPUdCJNhUs5AqoqeaOrZqzhVXXc36g21564tddDyh6t3D8e2b8eCdk5l01wOUVSpUT501\nDUiOqSYRSYxATkNpbyhPrH1v8kIhJk6fc2iq6X/HDeemGb9k8WsfUVxGzGdF9OzUit4nHM8Ts6bR\nL38FR69aRr/8FYFa0aQ9gDyKhUexiA/dWQRYXijEQ48t4TfPvkyn1s0ZN3Ysm2nHA3MepmmkHwK8\njuom/36e+6d+l7kPL6Asql9Cdw8iUptAJot0e55FrNVLQKRJbuKhZa4Tps+h89mXs3N/Scxlrp1a\nZnLJoL70S9EN/LTixaNYeBSL+AhkskgnsXofrpw2G8xoO3RclbsH96+/0rdLa75M8mWuIhIsqlkk\nibxQiCnTZzL2h9OZMn0meaEQhSVl/OSB31bpfWh73rXs2rmDzGZZ7P3ci0VmsyyOadOUubdNSstl\nrpqb9igWHsUiPnRn4aPqmuEqCtIWqSNsLSniWz/6BR0GX8aOTXvpdkrVKaWWlMQsVFfsx6SOahGJ\nJ/VZxFlNCaHy/kkH3vwdV4ybwHPL/kjTQZdXmTba9vqztGmeSdaZV1R5L3vNnwntKtF+TCJSZ+qz\n8FldE8LWkiImTp/DzNtu5qHHnqwyndTinHEsemopzpXHLEif0qUls6dN4vrpc6v0PtwTWb2kuwcR\n8YOvycLMRgIPEq6VPO6cu6/S+82AJ4GvATuA0c65UOXP8WNvqCNJCNdPn8sjM27l3t8sqpIQygaP\n4cZZC8IJ4dSqCaFzyyZ0btuc7TEK0ke3qX1K6eqLL9BqjwjtAeRRLDyKRXz4lizMLAP4FTAM2ASs\nNLPnnHNrok67AfjSOXeimY0G7geuqfxZa9euPaLfXd0Xf3XvATHvEB666xbmPrI4RkK4hst/PD+c\nEL5SNSE0zYB2Wc1jPvPhlGPbMHXShJh3D3XpfVi1apX+IUQoFh7FwqNYeHJzcxk2bFi9/ls/7ywG\nAZ855/IAzOwZYBQQnSxGAXdHfl5GOLlUUVhYyJTpM2v90q/pTuCJyBdx5cLymDvuo31Ws5h3CNf8\n9OFwQuhTNSHgymnZrEnMhHBOzw41JoSGFKT37NlT6znpQrHwKBYexcLzn//8p97/rZ/JohuwIep4\nI+EEEvMc51yZme02s6Occ19W/rDV3YYz7s77+ektN1Hu4BcP/prmQ8Yd+tIffft9TLz+Bl78y7Mx\n7wSu/sl8SssdHYYc3umcdc44Pv3zfHqeVTUhZODIah47IZzfuyPTbqx/QlDvg4gks2QvcMes2m/Z\nsoXM/lk0HzKWaXN/C0CXSg1qrc4dx8OPP1Vt8big5OChnyu/17SsOGZCOK/XUUytJiFMS1BCCIWq\nlHTSlmLhUSw8ikV8+LZ01szOBO5xzo2MHN8JuOgit5m9HDnnPTPLBDY75zpX/qzJkye7wsLCQ8cD\nBgxIuy1AKuTm5qbt//fKFAuPYuFJ51jk5uYeNvXUqlUrFixYUK+ls34mi0zgE8IF7s3A+8AY59zH\nUefcBJzinLvJzK4BLnPOVSlwi4iIv3ybhorUIH4ALMdbOvuxmc0AVjrnXgQeB54ys8+AncRYCSUi\nIv4LZAe3iIj4K6k3EjSzkWa2xsw+NbM7YrzfzMyeMbPPzOwdM0vZ9uU6xOIWM1ttZrlm9qqZdU/E\nOP1QWyyizvu2mZWbWXLuDRMHdYmFmV0duTZWmdnTfo/RL3X4N9LdzP5hZh9G/p1cnIhxNjYze9zM\ntprZRzWc81DkezPXzOpW0HHOJeX/CCeytUAPoCmQC3yl0jmTgd9Efh4NPJPocScwFkOBFpGfb0zn\nWETOaw28DrwNfDXR407gddEb+ABoGznulOhxJzAWC4FJkZ/7AF8ketyNFIshwEDgo2revxj4v8jP\nXwfercvnJvOdxaEmPudcKVDRxBdtFLAk8vMywsXzVFRrLJxzrzvnDkQO3yXcs5KK6nJdAPwcmA0U\n+zk4n9UlFt8Ffu2c2wvgnNvh8xj9UpdYlANtIz+3B/J9HJ9vnHM5wK4aThlFeFslnHPvAe3MrEtt\nn5vMySJWE1/lL8DDmviA3WZ2lD/D81VdYhHtBuDlRh1R4tQaCzM7DTjOOZeqMahQl+viJOBkM8sx\ns7fNbIRvo/NXXWIxA/iOmW0AXgRu9mlsyaZyrPKpwx+Xyd6Ud6TqtX44lZjZtYQ3Yhya6LEkgpkZ\n8AAwPvrlBA0nGTQhPBV1LpANvGFmp1TcaaSZMcAi59wvI31fTwP9EjymwEjmO4t8whd3heOoetu4\nEegOh/o42roYW4OkgLrEAjMbDvwY+FbkVjwV1RaLNoS/AF4zsy+AM4HnUrTIXdd/I88758qdc+uB\nT4ET/Rmer+oSixuAPwI4594FWphZJ3+Gl1TyiXxvRsT8PqksmZPFSqC3mfWIbF1+DfB8pXNewPsL\n8irgHz6Oz0+1xiIy9fIIcKlzbmcCxuiXGmPhnNvrnOvsnOvpnDuBcP3mW865DxM03sZUl38jfwXO\nB4h8MZ4IrPN1lP6oSyzygOEAZtYHaJ7CNRyj+jvq54Hr4NDOGrudc1tr+8CknYZyauI7pI6xuB9o\nBTwbmYrJc85dlrhRN446xuKw/4QUnYaqSyycc6+Y2UVmtho4CExzztVU/AykOl4X04DfmtkthIvd\n46v/xOAys6XAeUBHMwsR3sm7GeHtlR51zr1kZpeY2VqgEJhYp8+NLJ8SERGpVjJPQ4mISJJQshAR\nkVopWYiISK2ULEREpFZKFiIiUislCxERqZWShYiI1ErJQkREaqVkISIitVKyEGkgM+tpZjsrnjhm\nZsea2TYzOzfRYxOJFyULkQZyzq0DbgeeNrMsYBHhrbDfSOzIROJHe0OJxImZ/RXoSXiTujNSeJt4\nSUO6sxCJn8cIP0vjYSUKSTW6sxCJAzNrBfyH8DNVLgb6O+d2J3ZUIvGjZCESB2b2OJDlnBtrZguB\n9s650Ykel0i8aBpKpIHM7FLgIuCmyEu3AqeZ2ZjEjUokvnRnISIitdKdhYiI1ErJQkREaqVkISIi\ntVKyEBGRWilZiIhIrZQsRESkVkoWIiJSKyULERGplZKFiIjU6v8D7xTiUJKbFlgAAAAASUVORK5C\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f22adb65630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot1()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"One can also add custom specifications to set default parameters. One way of doing it is by altering \"rcParams\""
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from matplotlib import rcParams\n",
"rcParams['axes.labelsize'] = 24 \n",
"rcParams['xtick.labelsize'] = 16\n",
"rcParams['ytick.labelsize'] = 16 \n",
"rcParams['legend.fontsize'] = 14\n",
"rcParams['lines.linewidth'] = 3"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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yjq9W7voWQOkYi6ZSLOJDCUkkg2wo28at7yxm5SZtASThozkkn+aQJB3VLFxo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\nCkpIIiISCkpIIiISCkpIIiISCv8/wjkyTRvWOeEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f22ada8d400>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot1()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A more elegant way is to define a style, and call it as necessary. For example, you may want a different set of parameters for a journal article, and a presentation. You can define [custom styles](http://matplotlib.org/users/customizing.html) by creating a file with the desired parameter attributes and placing it in an appropriate location.\n",
"\n",
"In my case, I created a file \"myjournal.mplstyle\" which contained the following statements"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"axes.labelsize : 24\n",
"lines.linewidth : 3\n",
"xtick.labelsize : 16\n",
"ytick.labelsize : 16\n",
"legend.fontsize : 14"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"and placed in the directory ~/.config/matplotlib/stylelib/.\n",
"\n",
"You can find the correct location for your installation by the command matplotlib.get_configdir()."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"'/home/sachins/.config/matplotlib'"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mpl.get_configdir()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I am now ready to use my style in any python program by calling the style file. I don't have to manually enter all the rcParams."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"plt.style.use('myjournal')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The best part is you can combine styles. Thus, I can use the bmh and myjournal styles together."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"plt.style.use(['bmh','myjournal'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this case, styles on the right override attributes that are defined in multiple places."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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gE5KIBMvXG4r4OBS9km5LsSrppPGUkDyah+TTYK1PsQDnHH/+7/e8sLGDNtTz\n6LqIDyUkEalRyc5yHnw/xIyP8ih30L7XENbOT69lgCQ4lJA8GkPyqX/cl6mxCIXDXHHTnfQZeT3P\nTJ9KSf46tizPpefhB/Hc/TfRPW8BHZbMpXvegrQs665Lpl4X8RbIKjsRSZ5QOMyIWx4k+9Th7Ht4\nZD7Rmnmz6N3rOCb/9DCaZzVh2oT0WQZIgkN3SB6NIfnUP+7LtFg45xj3wAyyTx2+WyVd66LvaZ6l\nXxmQeddFoujqEhEACkvLuGvBCr7ZUBi1km5jYUmSWiaZQgnJozEkn/rHfZkSi283FvPLvyzjw1AB\nZk2iVtLtKPg+Sa0Lnky5LhJNY0giGSoUDjPlsZl8vb6QvC2ltDshsgRQ+15DKPj7s7T50SW7rEl3\n4c/OSHaTJc0Fci27ZNBadpJJdtlMr7lfuNC177mM/9lJHNRsK1Mem6k16aROab+WnYjE1z2/fzLq\nZno5377Njw45A2inSjpJOI0heTSG5FP/uC8dY7FwRX6NSwBt37GzxvPSMRYNpVjEh+6QRDJE6c5y\nHv84j9c+30C5twRQ1aSUiUsASbBoDMmjMSRJRxWFC3mbi8nbsoPsYwaR3a4TJfnr2Lj4FToNSv/N\n9CS+NIYkInUKhcOMGT8Zel9E1kEtaeUVLnTscy4DjzuCoefezIynn/ULF5SMJMk0huTRGJJP/eO+\nVI7Fg9OfjiSjaoUL7UML+e3Abhx96MFMm3A7z02dwLQJt9eZjFI5FrGmWMSHEpJIGvp6QxGLV26O\nWrjQMsswi0kPi0hMqcvOo7XsfFqny5dqsSh3jj//dz1P/WsNpeXEtHAh1WIRT4pFfCghiaS4isKF\ntVu2s3brDqz7wMoVF76bN4sfDN61cOH6CTcku8kiUanLzqMxJJ/6x31Bj0VF4cLSLoPY3HMYzU48\nl+8/eIWS/HX0OOwgnp5wY8z2Lgp6LBJJsYgP3SGJpLCaCheyP3uNh349mGZZTThJKy5IitAdkkdj\nSD71j/uCHIsvvi+ssXChXYssmsV476IgxyLRFIv40B2SSIrZWe547v/W8qfctTEvXBBJJt0heTSG\n5FP/uC9IsQiFw1x+wx30vvTXTHrwQYo3rassXKjYv6iycGHs6Ji/f5BikWyKRXzoDkkkBawIhbjo\n5gdp3W8E7Y5syT7eqgt9zxnOlPtuZPZzc7TigqQ8rWXn0Vp2ElR5BSVcMG48LU46b7euuaNXL+CR\n+1S0IMnubGDaAAAW2ElEQVSjtexEMkC5c7y6NDLJdXPxDrpEKV7YVFiSpNaJxJ7GkDwaQ/Kpf9yX\n6FiEwmHGjb+b8395K31H38jDb35KSZnDrEnlOFGFRBcv6LrwKRbxoYQkEhAV24ov7TKIrcddQIuT\nzquc5HrMgLMo/WBOQooXRJJFY0gejSFJsl1+wx2sPHjIbuNELf7zOq/8YQLf5a1mymMz/eKFsaNV\nvCBJpzEkkTRSWlbOC5+t45/hzex/5O7jRG2zm9A8qwkH5uQwTasuSBpTl51HY0g+9Y/74h2Lz9cV\n8stXlvHMp2shAONEtdF14VMs4iOwCcnMuprZXDPbbGYFZvaymR1Qj/NOMLPHzOwLMys0s5CZPWtm\n3eLfapG6hcJhfnHLXZw2+gYuGPcbvloRAqB9ryGsf2e2xokkYwVyDMnMWgL/AYqB8d7hCUBL4Bjn\nXHEt504CTgaeA5YCXYDbgY5AT+dcXrTzNIYkibAyFGLELQ/Sou+Iyi0h1sybRde+5/KLIcfTs3Ux\nDz8xS+NEkjIyYQzpCqAbcLhzbgWAmS0BvgbGAg/Xcu4DzrmNVQ+Y2YfACuB/gTvj0F6ROn23tYRR\nd/6+MhmBvzp3t5XzOPd/zgDQOJFkrKB22Z0FfFSRjACccyuBD4BzajuxejLyjoWB9UTulqLSGJJP\n/eO+WMRiR1k5f8pdyxVzv2BDYWnU1bmLSnY0+n3iTdeFT7GIj6DeIXUH/hLl+FJg6J6+mJkdRaTL\n7vNGtkukXip2cV25qYi1W3fQsufpZLfrVDnBVatzi+wuqHdI+wL5UY5vAtrtyQuZWRYwA/geeKqm\n52k/JJ/2evE1JBahcJhRt0UmuG4/4UL2PuX8ygmuxw06O2UnuOq68CkW8RHUO6RY+gORIocfO+cK\nkt0YSW+lZeWMe2AGWadcvNs40T5L32DmIxNYPeSQXSe4anVuESC4CSmf6HdCNd05RWVmDwA/B0Y6\n596p7blTp06lVatW5Hi/GNq0aUOPHj0q/xKq6DPOhMdV+8eD0J5kPq4ek9qe/8W6Qj4oO4BvNhSy\n96plAOxzSOTOu3DVMpptWENWE+PAnBwuOHNAID7fnjxesmQJV111VWDak8zH06dPz+jfD3PmzAEg\nJyeHjh07MnDgQGIhqGXf7wDNnHP9qh1/D8A5178erzEeuBv4lXNuel3PnzJlihszZkwDW5xeFi1a\npC4JT22xqBgnyttczIainXD0QLLbdWLN/Nl0Om3YbuNE3fMWpHQFna4Ln2Lhi2XZd1DHkF4DTq46\nmdX7fx/g1bpONrNxwD3AbfVJRqAxpKr0g+arLRmNrrIQatMfnls5TtT15DPYtvC5lBwnqo2uC59i\nER9BTUhPACuBV83sbDM7m0jVXQh4vOJJZpZjZjvN7DdVjl0EPAS8CfzdzE6q8nVUQj+FpKWd5Y5r\nJ86gSe/dx4myv3qP568cwIsP3kz3vAV0WDKX7nkLeErjRCJ1CuQYknOuyMwGEEksswEDFgDXOeeK\nqjzVqnxVGOL9e4b3VdX7wIBo75mbm4tWaohQd4Svaiycc3wU3sITH+fx1frCqBvmddirKW1bNqNt\nGi6EquvCp1jERyATEoBzbjUwrI7nhICsascuAy6LY9Mkg6xbt45x4+9mVX4x6wt3kvU/AzWfSCRO\ngtpll3AaQ/LpL7+IUDjMtFfeY2mXQRQefwHZJ/njRF1OGsK299NvnKg2ui58ikV8BPYOSSSZ8ot2\nMPaeR2l6yvDdxoma/t9rvDDtHgqGHq35RCIxpITk0RiSLxP7xytKuL/fup2tpY7Sw05jTUExe69a\nVjmXCCJJab+9stJ2nKg2mXhd1ESxiA8lJMl4oXCYy8ZPwryquYotIcAo31Gyy3M1TiQSPxpD8mgM\nyZdJf/mV7izn2okzKpMR+F1zLbMczfKWZNQ4UW0y6bqoi2IRH7pDkoxUWlbOW8s28nzuuhpLuI/s\nuh/3Xz9W40QiCaKE5NEYki9d+8dD4TCTpj/N1+sL2VC0k9bHDa61hHu/1tmsCoczapyoNul6XTSE\nYhEf6rKTjPD1tyu58KaJfHHA6biTL6btqUMrS7gP7nNmWi71I5JqArm4ajK88847TndI6aewtIw3\nvtjAAw9MZN++Q3e7C9p76Ru8MPVe1q5ZvWvX3NjR6poTqYdYLq6qLjtJKxXl2+u2bGfbDkfZET+i\nfO+OlJaVRd06vFVTI7tpEw7MsBJukSBSl50nNzc32U0IjKp7AaWSqju15vccxvZjziL0/p8pyV9X\nOU5UVX1KuFM1FvGgWPgUi/hQQpK0sGx9IZfd9fuoO7UWfTafm64cjVv8J40TiQSYuuw8mofkC3r1\nUEW33IZtJTiM1j0HESpvw7qtJVHLtw9r34KR/Xty2iE37nEJd9BjkUiKhU+xiA8lJEkpFRvjNamy\nqkLua7Po2OfcWsu3AY0TiQScuuw8GkPyBbV/fNXm7Yy999GoG+Nt+uRtzjpvGDs+mBPTbrmgxiIZ\nFAufYhEfukOSQNq1W64J+55wOl+X7k3e5uLoqyp0bMn9F55CqHdXrawgkqKUkDwaQ/Ilu388FA4z\n+rZJNDmlSrfcn2vvlvvBPi2A2HfLJTsWQaJY+BSL+FCXnQRGuXN8snoLo+/8fWUyAr9bbuMnbzPo\nrPMpWaRVFUTSke6QPFrLzpeodboquuW+K9jO9jJH8+4D2dqiPd9vi14td2SHFjx8yamE+uUkrFtO\na5b5FAufYhEfSkiSFF9/u5JR4yfRsu8Isg6KdMt9M6/2brn920Qeq1pOJD1pLTuP1rKLn6oFCk2z\nsuh2ypm8OvdF9us3bLeks/Efc7ngogt568VnaNZneOUYEouf5ykVKIgEjtayk5QRCocZeduDND3F\nTy7/enYmWJOoa8sd1bElt51zEiOO+4Gq5UQyjBKSR2NIvob0j1e9C9qvdTaXDh/O8p2teXjyNFp5\nyQj8AoUVz0+M2i3XIWCTWDVW4FMsfIpFfCghSaOFwmHGjJ8MvS8iq3lL1pUWM3L8JDr2OZetJTvY\nJ9pyPt26smPxnyirsuICi5/n+gk3JOlTiEiyaQzJozGkPeecY9XmEn51210U9jhrt7udde+/BECn\n03YfK+qet4Drx47WHkQiKU5jSJIUoXCYyTNmsiq/iNJy2PvY08lvti95G4uilmnv3bwJV/98FE/8\n8QmIcicUlG45EQkGTYz1aC07X/V1uraW7OSFfyzhvOvv5/Ougyg64UJKep7Nf95+sda9hn6Y04bh\npx3DzAk30j1vAR2WzKV73oKUqpbTmmU+xcKnWMSH7pBkF6FwmGlPzGLKnL9S5qBDryHk0YbV82bT\nqf+luxUnrF/4Emf8bCgfvPoce/UbEXU8SHdCIlIfSkieTFrLrnpF3K+vGEXzdp2Z/+8vmPqHx2g3\n4LLKxPL165HJqs6VRy3T7t5xLyZf3IdQnwPSskxblVQ+xcKnWMSHElKGiVYR99Nr76P9Keey8ZO3\n6TRg97ugde+/xD4tmkUv0947WGXaIpK6NIbkSbcxpFA4zLjxdzP8mvFcfdvdvJ+7jFeXrueyu35f\nmYwgknQ6nR5ZuLTiLmjLcj8Wkbugljx/7zhY/HzGLWqqsQKfYuFTLOIjsHdIZtYVeBgYBBiwALjW\nObeqHudmA/cCI4C2QC5ws3PuH/FrcXJU7367fuxo8ot28Mu7fkeLviMq74KuvPN3dOxzLhtq2Obb\ncLRv1TxqcUKnfVpwYE4OT024IS275UQkGAI5D8nMWgL/AYqB8d7hCUBL4BjnXHFN53rnPwecCdwA\nrAB+5T0+2Tn3n2jnBHkeUrSkc2BODitDIUaPn0xWlX2D1s6fRbkz9h88co/mBR29egE3XDl6l+48\nrSEnInXJhHlIVwDdgMOdcysAzGwJ8DUwlsidU1Rm1hO4GBjtnJvtHVsILAXuBn4W15Y3UE1JJ9qY\nz/nXP0Cvn1zIR2+/Svu+u+4b1Pn0UYT+PDVqAUKb7CaMvnQEs2c+RfNqC5fe4CUd3QWJSLIENSGd\nBXxUkYwAnHMrzewD4BxqSUjA2UAp8GKVc8vM7HngZjNr5pzbUf2kRKxltydJ54KbJvLjYZey4PWX\naV5tzKdN/0tY9OZLNVa+udLiqAUIJxzQhv89/XgGH7FfjUnnwJwcLjhzgKqIPFqzzKdY+BSL+Ahq\nQuoO/CXK8aXA0DrOPRpY4ZzbHuXc5sChwBfVT/rmm2/q3biaEktt31sZCnHZbybTxFuxYF1pMcNu\nfIBB51/Cwr++Qna1pNO63wheevEFnCuPOubjXHmN+wb163k44cXPU1at662+84KWLFmiHzaPYuFT\nLHyKhS83N5eBAwfG5LWCmpD2BfKjHN8EtGvEuRXf301hYSHjxt9dZ3IBuGz8JKxKYrnklge54eqr\nKCwtY+r0x2jdzy8mOPu6+zh84FCWLfwrHfrt2r2292mX8NrLLzUo6Rzzg324fuwobrp/6m4LlN7p\nJZ6Gdr0VFBTU63mZQLHwKRY+xcL32Wefxey1gpqQkmJpl0Gcfd19nPTTiykrd/zrb8/TYeDIyuTy\n42smAEbn00fuklianzqc8Q//EYBOp43Y5Xv7DRzJF+/X0r1WS9I5rEMrRl8ygof+MB1O2XXM5wEv\nwTw94cYaE4/mBYlIKglqQson+p1QTXc/1c+NditQcWe0Kcr3WLt2LVk9Ignkw7e8arSBuyae2goG\nnCuv/H+079WUdI7s2JrRlw5n8rTpUK3QYKqXXI7rclOtYz6xTjzhcDimr5fKFAufYuFTLOIjqGXf\n7wDNnHP9qh1/D8A517+Wc39LpFS8bdVxJDO7E7gZ2CdaUcNVV13lCgsLKx/37Nkzo5YTqio3Nzdj\nP3t1ioVPsfBlcixyc3N36aZr1aoV06dPj0nZd1AT0jXAJCJl3yu9Y92Ar4CbnHO1lX0fC3wKjHLO\nPeMdywKWAF855wJZ9i0ikumCmpD2IrK6QjHwW+/w3UAroKdzrsh7Xg7wLXCnc+7eKuf/CRgM3ERk\nYuwvgB8DvZ1zsRuBExGRmAnkWnZewhlA5I5oNvAMsBwYWJGMPFblq6rRwNPAPcAbQBdgiJKRiEhw\nBTIhATjnVjvnhjnn2jrn2jjnznfOhas9J+Scy3LO3VPteIlz7gbgROBvwFHAG2b2spkdUJ/3N7Ns\nM5tkZmvMrMjMPjSzvrH6fIlmZl3NbK6ZbTazgvrGwsxOMLPHzOwLMys0s5CZPet1oaakhsYiyuvc\nYmbl3kogKamxsTCzo8zsRTNb7/2cfGlmV8ezzfHSmFiY2QFmNsv7+Sgys2Vmdo/X25NyzKyLmT3i\n/d4r9K7zes0bsYhbzWyFmRWbWa6ZnVefcwObkBrLWw/vPeBw4FLgEuAw4F3ve3V5Crgc+A3wE+A7\n4G0zOyY+LY6fRsbiIiKTjacCZxApDDke+MTMusSt0XESg+ui4nUOJlI8sy4e7UyExsbCzHoBHxGZ\ncH45kfUiJwNZ8WpzvDQmFl7SeQc4lcg1cSbwBHA98GQcmx1PhxJZhGATsBDYk7Gde4HbgWlEfmcs\nBl4yszPqPNM5l5ZfwDXADuCgKse6eceurePcnkA5MLLKsSzgS+Avyf5sCY5F+yjHcoAyImN3Sf98\niYpFtdd5C5hO5JfYwmR/riRcF0Zk9ZO5yf4cAYjF6d7Pw8Bqx+8nsoxZi2R/vkbG5nLv8+XU47kd\ngO3A7dWOLwBy6zo/be+QqGE9PKBiPbzaRF0PD3geGGJmzWLe2vhqcCyccxujHAsD64mMzaWaxlwX\nAJjZcOA44NZ4NDCBGhOL/sCRwO/i1rrEakwsmnv/bq12vIBIL1RMSqJTxBlAM+C5asefBXqY2YG1\nnZzOCak78N8ox5cS6YKqTX3Ww0sljYnFbszsKKAj8Hkj25UMjYqFmbUl8kv4Rufc5hi3LdEaE4s+\n3r97mdliMys1s3VmNtXMWsS0lYnRmFgsILITwURvTK2VmQ0AxgHTXR3b5aSZo4ES59zyaseXEknM\ntcYynRNSwtfDC7DGxGIX3pyuGcD3RMbZUk1jYzEZWOa8rU1SXGNisT+RXzDPE+m+HARMBH7O7n8d\np4IGx8I5VwL0JdKtv5TIndJ84HXnXEoWeDTCvkC0P9Tq9bszqEsHSXD9ATgZ+LFzLqNWmPSqLC8h\n0l2X6ZoQGeh+xjl3l3dsoZk1Be43syOcc8uS17zE8XaofpHI+MkIYBWRCt87zKzMOfeLZLYvlaRz\nQkr4engB1phYVDKzB4j8BTzSOfdOjNqWaI2JxQwiVVNrzKwNkTuEpkAT73Gxc640lo2Ns8bEomJs\ncUG14/OAB4gk7VRKSI2Jxc+BfsAh3rgTwCIz2wI8ZmbTnXNLYtbSYMsH2kY5Xq/fnencZbeUSL9w\ndUdT99jHUuCgKH3h3YkUO9R/86RgaEwsADCz8cCNwNXOuTkxbFuiNSYWRwFXEvmhyyfyw9UH6O39\n/8rYNTMhGvszUpvyBrUoeRoTi/8B8qskowofE/mj5ahGty51LAWyvWkRVXUnckddayzTOSG9Bpxc\ndQKn9/8+wKt1nPs6keKFYVXOzQIuAN52URZnDbjGxAIzG0dk1YvbnHPT49LCxGlMLH5EpLrsR1W+\nPiOyTuKPgLkxbGciNCYWbxL542xIteNnEvnF80mM2pgojYnFWqBdlF/CJxOJRV6sGpkC3gJ2Eum6\nrOoS4L/OuVCtZye7xj2OtfN7EVl66DMiZdxnE1kf72tgryrPy/EC+Jtq5/+JSLfE5USWMZoLFBFZ\nSy/pny9RsSAyMbYM+CtwUrWvo5L92RJ9XUR5vVSeh9TYn5HbiSSlCcBA4BbvZ+TJZH+2RMYCOJDI\nQP6XwEgif5zcSKTs+5/J/myNiMn53td0Ine8V3qP+1V5zk7giWrn3e9dB9cBp3nn7wTOrPM9k/2h\n4xzQrsBL3sVSALxMtcld3sVUBvy22vFsIhVVa7zgLgb6JvszJToWRNYELKvh691kf65EXxdRXus9\n4P1kf6ZkxQK41vtFvp3IQsZ3AFnJ/lyJjgWROVnPAyGg0EtOE4E2yf5cjYhHeV0/997jJ6udZ8Bt\n3vVQTCSxn1uf9wzkat8iIpJ50nkMSUREUogSkoiIBIISkoiIBIISkoiIBIISkoiIBIISkoiIBIIS\nkoiIBIISkoiIBIISkoiIBIISkoiIBIISkoiIBIISkoiIBIISkkiAmNkEMys3s+/NrGMNz3nLe86/\nvH26RNKCEpJIsNwBfAq0B56q/k0z+xUwmMiWKCOcc2WJbZ5I/CghiQSIc24nkd01twNnmlnltuhm\ndgSRPXYccJNz7qvktFIkPrQfkkgAeXdC04hs9nY88C3wkff/t51zP05i80TiQglJJKDM7E1gCPAJ\nMB+4FdgI9HDOrU1m20TiQQlJJKDMrDOwBNiXyLbQDrjAOfdyUhsmEicaQxIJKO8u6Db8ZPSSkpGk\nMyUkkYAysybA6IqHwLFm1jJ5LRKJLyUkkeC6FegNbAbCwOHAlKS2SCSONIYkEkBmdjywGGgKXArk\nAe963/6Jc+6tZLVNJF50hyQSMGbWAniWSDJ6yTk3xzn3PvAQka67J81s32S2USQelJBEgudB4Ehg\nDXBlleO3AUuBzsBjSWiXSFwpIYkEiJkNBn5JpKpujHNuc8X3nHOlRFZx2AmcZ2ajktNKkfhQQhIJ\nCDNri79+3R+cc/OrP8c59xlwu/fwYTPLSVT7ROJNRQ0iIhIIukMSEZFAUEISEZFAUEISEZFAUEIS\nEZFAUEISEZFAUEISEZFAUEISEZFAUEISEZFAUEISEZFAUEISEZFAUEISEZFA+H9YAae4QDfN0AAA\nAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f22ada4fcf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot1()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another class of style files I am fond of is seaborn. I make some small tweaks to it for journal quality pictures."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import seaborn as sns\n",
"plt.style.use(['seaborn-ticks','myjournal'])\n",
"sns.set_style({\"xtick.direction\": \"in\",\"ytick.direction\": \"in\"})\n",
"sns.set_style({\"xtick.direction\": \"in\",\"ytick.direction\": \"in\"})"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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qpp5LexsQwwUREdmMlPSr2LAvRf067LbueP2pEbC354N8Q+LdJCIim5BdUIZ3t56CUtW4\noEUfP08seGIYg4UR8I4SEZHVu15egzc/+xWVf46z6OzpgiXP3IkOLo5mrsw6MVwQEZFVq61X4p3P\nT6GopAoA4OJkjyXPcDMyY+KYCyIiskqJyXLs+TEdWQV/rWdhJwALngxDYEBHM1Zm/RguiIjI6uha\n2vvusB4YMdDHDBXZFnaLEBGR1dG1tHeGXGHiSmwTwwUREVmdrIIyre05Opb8JsNiuCAiIquSnn1d\n5zEu7W0aDBdERGQ1Coor8dZnv0IUtR/n0t6mwQGdRERkFcoq6/DGJ0koragF0DjltIuXKwqKK7m0\nt4kxXBARkcWrrVfi7c9/Re6f26U7OtjhzWdHYWCfLmauzDaxW4SIiCyaUiXi/e1nkHalBAAgCMAr\n04cxWJgRwwUREVm0z+PPIyk1X/36H9EhuOt2PzNWROwWISIii5OYLMfehEvIKihrNnjzwYhAREcE\nmq8wAsBwQUREFkbX6pv9e3bC0xMHmaEiuhm7RYiIyKLoWn2ztq4BdnaCiashbRguiIjIomQXaF9l\nU15UYeJKSBeGCyIishhFJVUQdDyc4Oqb0sFwQUREFqGssg5LNidBqdK+/CZX35QODugkIiLJq6lt\nwH8+O4ncq41dH3aCgG6dXXH1ejVX35QghgsiIpK0BqUKy7edxsWsxg3JBAFY8OQwjA71N3NlpAu7\nRYiISLJEUcSGvSk4nVaobnt20mAGC4ljuCAiIsnadjANP/6WrX49JaofHhjd14wVUVuwW4SIiCRF\n1+qb94zoiScn3Ga+wqjNGC6IiEgydK2+2dffCy9MDoWgax4qSQq7RYiISDJ0rb6pVKpgb88fWZaC\n/08REZFkZBeUaW3n6puWheGCiIgkIadQ+7LeAFfftDQMF0REZHZFJVVYvOkEdCy+ydU3LQwHdBIR\nkVmVltdi8aYTKFbUAAAcHQR07dgBRSVVXH3TQkk2XBQUFGDZsmU4ceIERFFEeHg4XnvtNfj6+rbp\n+oyMDKxduxa//vorqqur4evri+nTp+PJJ580cuVERNRWldX1WPpJEvKuVQIAHOztsPSZOxHa39vM\nlZE+JBkuampqMGPGDDg7O2PFihUAgNWrV2PmzJmIj4+Hi4tLi9enpqZi1qxZGDlyJN555x14eHgg\nKysLlZWVpiifiIjaoLZeibc+/xWZuQoAgJ0AvPrkMAYLKyDJcLF7927k5ubi0KFD6NGjBwCgf//+\nGD9+PHbt2oVZs2bpvFYURfzrX//CXXfdhbVr16rbR4wYYeyyiYiojRqUKqyIO43fM4vVbTFThmDU\nYD8zVkWGIslwcfToUYSGhqqDBQAEBARg6NChSEhIaDFcnDx5EpmZmXjrrbdMUCkREd2KxGQ59vyY\njuyCcjQdu/nUA4Nwz8heZquLDEuSs0VkMhn69dMcGRwUFISMjIwWrz179iyAxq6VadOmISQkBOHh\n4Xj77bdRW1trlHqJiKh1N1bfzLopWIwc5IOH7w4yW11keJIMF6WlpfDy8tJo9/LyQlmZ9gVWbigq\nKoIoipg3bx7GjBmDLVu2YPbs2di3bx/mz59vrJKJiKgVulbfLCypMnElZGyS7BbRhyiKEAQBDz74\nIGJiYgAAw4cPR0NDAz744ANkZmaib1/uqEdEZGpZOlbfbGnxLLJMkgwXXl5eUCgUGu0KhQKenp4t\nXtuxY0cAQHh4eLP20aNH4/3330daWlqbwkVUVJRGW0xMDGJjY1u9loiImjuYdKXZDqdNcfVN01m3\nbh3Wr19v9M+RZLgICgqCTCbTaJfJZAgMDGz12pa0dUe9hIQEBARw0RYiIn0dPZODj75K0Xmcq2+a\nTmxsrMYvyXK5XOsv1PqQ5JiLyMhIpKSkQC6Xq9vkcjmSk5NbvQERERFwdHTE8ePHm7UnJiZCEAQM\nHjzYKDUTEZGmpNQ8fLgrWf3UwqdLB/T08YC9nYDevp5Y8MQwrr5phST55GLq1KnYsWMH5syZg7lz\n5wIA1q5dCz8/P0ybNk19Xl5eHsaNG4eYmBjMmTMHQGO3yLPPPouPP/4Ybm5uuPPOO5GamoqNGzfi\noYceaja9lYiIjOfshSKs2HYaqj83DOnl44Flc0bD083JzJWRsUkyXLi6umLr1q1YtmwZFi5cqF7+\ne9GiRXB1dVWfJ4qi+k9TMTExcHd3x86dO/H555/D29sbs2fPxvPPP2/qr0JEZJPOZ1zDO1+cQoOy\n8d9nv65ueOuf4QwWNkIQb/7JbONu9D1xzAURUfukZ1/H6x+fQHVtAwDAu5Mr3nthNLp16mDmykgb\nY/zck+STCyIisjyJyXJsP3RBvQkZAHTycMbbz4UzWNgYhgsiItLbjdU3b/bg2ED4dXU3Q0VkTpKc\nLUJERJZlx+GLWtt/OiPX2k7WjeGCiIj0UlRShdyrFVqPcfVN28RwQURE7XattBqvffSLzuNcfdM2\nMVwQEVG7FCuq8e+Pfmlx4zGuvmmbGC6IiOiWXS+vwesfn1DPDHGwF/DQ34LQ29eTq28SZ4sQEdGt\nUVTUYvHHJyAvahxnYWcn4NUnwzBqsB8wcZCZqyMp4JMLIiJqs/KqOizZlISsgsaBmnYCMH/6sMZg\nQfQnPrkgIqJWJSbLsetIerPZH4IAzHtsKMYM8TdjZSRFDBdERNQiXQtkjb+zN/42jJtBkiZ2ixAR\nUYt2H0nX2n7hSomJKyFLwXBBREQ6VdXUI1vHQlhcIIt0YbggIiKtqmrqsXRzks7jXCCLdGG4ICIi\nDTeCxYWs6zrP4QJZpAsHdBIRUTOV1fVY+kkSLjYJFpFhAcjMLUNOYTl6dPfAlKh+XCCLdGK4ICIi\ntcrqxicWF7P/ChbPThqMiWP6mrEqsjQMF0REBEB7sPjnQ4PxwGgGC7o1DBdERDYuMVmO3UfSNWaF\nPPfQYNzPYEHtcMsDOk+cOGGMOoiIyAxuLJB1c7AYN7wngwW12y2Hi6effhpRUVFYv349cnNzjVET\nERGZyC4dC2TJ5KUmroSsyS2HC1dXV+Tm5mLDhg2455578NRTT+HAgQOoq6szRn1ERGQkiopanQth\ncYEs0sctj7n45ZdfcODAAXz99ddITk5GUlISTp48CQ8PDzzwwAN4+OGHERISYoxaiYjIQErKavD6\nx7q7ublAFunjlp9cdOjQAVOmTMHOnTtx6NAhzJ49G97e3igrK8POnTsxZcoUREdHY9u2bSgt5WM1\nIiKpuVZajUUbjrf4dIILZJE+9Fqhs3fv3njllVfw008/YdOmTbjnnnvg4OCA9PR0LFu2DBEREXjp\npZeQmJgIURQNVTMREbVTYUkV/rXhOPKuVQIA7OwETBzdF719PWFvJ6C3rycWPDGMC2SRXgwyFdXO\nzg5jx47F2LFjcf36dezfvx979+7FpUuXcPjwYRw+fBjdu3fH5MmTMW3aNHh7exviY4mI6BbkXa3A\nvz8+gWul1QAAB3sBrz4ZhlGD/cxcGVkbg+8tkpubi8uXL6OoqAiCIEAURYiiiIKCAmzYsAHjxo3D\n+vXrDf2xRETUguyCMizaeFwdLBwd7PDarBEMFmQUBnlyUVJSgvj4eHz11VeQyWQAAFEUcdttt2Hy\n5Mn4+9//jqSkJOzatQtnz57Fhg0b4OzsjNmzZxvi44mISIvEZDn2JlxCdkEZIAhQqRq7p50c7bH4\n6REY0r+bmSska9XucKFSqfDTTz/hq6++ws8//wylUglRFOHu7o77778fU6dOxaBBg9TnR0dHIzo6\nGnv37sXixYuxZ88ehgsiIiO5sTiW2p/j3hwdBLw5+06EBHY1U2VkC245XMhkMnz11VfYv38/iouL\n1QM177jjDkydOhUTJkyAi4uLzuunTJmCVatWIS8vr/1VExFRi/YmXNLa3tWrA4MFGd0th4sHHnhA\nPZaiU6dOmDRpEiZPnozAwMA2v4ebmxvKyspu9aOJiKiNsgq0/xtbdL3KxJWQLWpXt0h4eDgmT56M\ncePGwdHR8Zav37lzJxoaGtrz0URE1IpfUvKga/Y/F8ciU7jlcJGQkAB/f3+9PrR79+56XU9ERNod\n+TUL6/ee03mci2ORKdxyuNA3WBARkXF8l5iBT787r37dycMZbq6OyL9WiR7dPTAlqh8XxyKTMMhU\nVCIiMh9RFLHrh4vY8cNFdVtfPy+8+ewodPRwNmNlZKsYLoiILJgoivg0/jziEzPVbbf17owl/7gT\n7q63PiaOyBAYLoiILFBishx7fkxHdkE5mo7dvKO/N16bNQIuzvznncyHf/uIiCyMxgJZf+rfsyMW\nPzMSjg72ZqiK6C8G31uEiIiMa/eRdK3tdfUqBguSBIYLIiILUlpei+zCcq3HcnS0E5kau0WIiCxE\nQXEllm5O0nmcC2SRVDBcEBFZgMt5CrzxSRJKymp1nsMFskgqGC6IiCTu98xivPXZSVTWNG6b4Ohg\nh/vCeyPl0jXkFJZzgSySHIYLIiIJ+/V8PlZsO426BhUAwNXZAYufHonBQdzZlKSL4YKISGISk+XY\nm3AJWQVlzTYg6+jhjDf+cScCAzqarziiNmC4ICKSEF1rWHi5O2FFzBj4dnUzQ1VEt4ZTUYmIJGTP\nj9rXsPB0c2KwIIvBcEFEJBG19UpkFWhfqyLvaqWJqyFqP8mGi4KCArz44osICwvDsGHDEBsbi/z8\n/Ft+n82bNyM4OBjTp083QpVERIZRVlmHxR+f0Hmca1iQJZFkuKipqcGMGTNw+fJlrFixAitXrsSV\nK1cwc+ZM1NTUtPl9cnJy8NFHH6FrV46qJiLpKiiuxKvrEpF2pUTnOVzDgiyJJAd07t69G7m5uTh0\n6BB69OgBAOjfvz/Gjx+PXbt2YdasWW16nzfeeAPR0dHIzMyESqUyYsVERO0jyynFm5+dRGl54+JY\nggCMHRqAK3llXMOCLJYkw8XRo0cRGhqqDhYAEBAQgKFDhyIhIaFN4WL//v1IS0vD6tWr8cILLxix\nWiKi9jmdVojlcb+hpk4JoHFxrJcfH4rRof5mroxIP5IMFzKZDFFRURrtQUFBOHz4cKvXl5WV4b33\n3sOrr74KT09PY5RIRNQuutawcHd1xOtPj8Sgvl3MVxyRgUgyXJSWlsLLy0uj3cvLC2VlZa1ev3z5\ncvTp0weTJk0yRnlERO2iaw0LTzdHvPfCGA7aJKshyXChj9OnTyM+Ph7ffvutuUshImpG1xoWXu7O\nDBZkVSQZLry8vKBQKDTaFQpFq90cS5cuxeTJk9GtWzeUl5dDFEUolUqoVCqUl5fD2dkZTk5Ordag\nrVsmJiYGsbGxbf8iRER/Kq+q4xoWZHbr1q3D+vXrjf45kgwXQUFBkMlkGu0ymQyBgYEtXpuRkYHM\nzEzs3LlT49iIESOwaNEizJgxo9UaEhISEBDA0dlEpL+8axV485OTOo/zqQWZSmxsrMYvyXK5XOsv\n1PqQZLiIjIzEypUrIZfL1T/g5XI5kpOTMX/+/Bav3bZtm0bbO++8A5VKhSVLljSbgUJEZGy/Zxbj\nnS2nUF5Vp/McrmFB1kaS4WLq1KnYsWMH5syZg7lz5wIA1q5dCz8/P0ybNk19Xl5eHsaNG4eYmBjM\nmTMHADB8+HCN9/Pw8IBKpUJYWJhpvgAREYCfzuRgze5zaFA2rrPj5GCHe8N743+XrnENC7JqkgwX\nrq6u2Lp1K5YtW4aFCxdCFEWEh4dj0aJFcHV1VZ8niqL6T2sEQTBmyUREaqIoYucPF7Hzh4vqto7u\nznj96REY0KuzGSsjMg1JhgsA8PHxwdq1a1s8x9/fH2lpaa2+l7auEiIiQ0tMlmPPj+kaAzd7dPfA\n0n/cie6dO5ipMiLTkmy4ICKyJLrWsOjl44HlMWPg5upohqqIzEOSG5cREVma7YcuaG0XBIHBgmwO\nwwURkZ5O/V6AvGva16rIKdS+tgWRNWO3CBFRO4miiK+PyrD1+z90nsM1LMgWMVwQEbVDXb0S6/ee\nw9Ez8hbP4xoWZIsYLoiIbtH1shq888UpXMy6rm4b1LcL/jY0AAd+ucw1LMjmMVwQEbXBja3SswvK\nIAgClKq/1te5Z0RPPP9IKBwd7HDvqN7mK5JIIhguiIhaoTHN9M+F+wQA/3gwBBPH9OVCfURNMFwQ\nEbVC11ZfCEM9AAAeJElEQVTp3Tp3QHREy5spEtkiTkUlImpBRXW9zq3Sr5VWm7gaIsvAJxdERDpk\nF5ThnS2ndB7nNFMi7RguiIi0SErNx+qdZ1Bdq9R5DqeZEmnHcEFE1IRKJWLHDxew+8hf4yycnezx\n9xG9kJrBrdKJ2oLhgojoTxXV9Xh/+xmcTitUt3Xv3AH/fmoE+vh5mbEyIsvCcEFENi8xWY7thy5o\n7A9yR39vLHgyDB4dnMxUGZFlYrggIpuma6v0EQO747WnRsLejutXEN0qTkUlIpvVoFRh0zepWo8V\nXa9msCBqJz65ICKbVKyoxoptp1FWWaf1OLdKJ2o/hgsisjmpsmtY8eVplJbX6jyHa1gQtR/DBRHZ\nDFEU8fVRGeK+/wM39h0TAIhazuUaFkTtx3BBRDahoroeH+48i19/L1C3ebk7YcETYVBU1GJvwiWu\nYUFkIAwXRGTVdE0zva13ZyycEYYuXq4AwDBBZEAMF0RktX4+K8eq7ZrTTIcFd8PrT4+Egz0nzBEZ\nA//LIiKrVFVTj4+++p/WY8WKGgYLIiPikwsisjqX8xRYHvcbKmvqtR7nNFMi42K4ICKrIYoiDiVd\nwSffnUd9g0rneZxmSmRcDBdEZBUqq+uxbu85/JKSp25ztBdQr9ScaMpppkTGxXBBRBYrMVmOvQmX\nkF1QBjs7AQ1NgkRvX08snBGGzFwFp5kSmRjDBRFZpJs3HFM1CRYTRvXGMw+GwNnRHgHdPBgmiEyM\n4YKILNKuIxe1tnt3csWcyaEmroaImuJcLCKyOMkXi5BTWKH1WImixsTVENHN+OSCiCxGfYMScd+n\n4dufM3Sew5kgRObHcEFEFiGnsByrvjyDzDxFi+dxJgiR+TFcEJGkiaKIQyez8Ol351FXr1S3Dwvu\nhpGDfPD9iSucCUIkMQwXRCQ56immheVwcbRHVW2D+pijgx1mPTAQE0f3hSAImBDex4yVEpE2DBdE\nJCk3TzFtGix6+nhgwRNh6O3raY7SiKiNGC6ISFJ2/5iutd2jgxM+eGksnB3tTVwREd0qTkUlIslI\nz76O7ALtm4pV1dQzWBBZCD65ICKza1CqsOvIRexNuKTzHE4xJbIcDBdEZFbZBWX4YOdZZMg5xZTI\nWjBcEJFJNZ0J4uXmhLLKOihVf+0LMqhvF4QP9sWRU9mcYkpkoRguiMhkbp4Jcr28Vv2/HeztMOO+\n2xAdEQh7OwHREYHmKJGIDIDhgohMZo+OmSBODnb44KWx6MUppkRWgbNFiMgkCoorkaVjJohSJTJY\nEFkRPrkgIqNSqUT895dMxH2fpvMczgQhsi4MF0RkNLlXK7BmVzLSrpS0eB5nghBZF4YLIjKY1maC\n9PLxQMQd/jh2Lo8zQYisGMMFERlESzNB7O0ETInqj6nj+sPRwQ5Txw0wR4lEZCIMF0RkEC3NBFn5\nYgT6+nuZuCIiMhfJhouCggIsW7YMJ06cgCiKCA8Px2uvvQZfX98Wrzt//jz27NmD3377Dfn5+ejU\nqROGDRuGl156CQEBfPRKZAznM661OBOEwYLItkgyXNTU1GDGjBlwdnbGihUrAACrV6/GzJkzER8f\nDxcXF53XHjhwADKZDDNmzEC/fv1QWFiIDRs24JFHHkF8fDy6d+9uqq9BZPUqquqw5b9/4Idfs3Se\nw5kgRLZHkuFi9+7dyM3NxaFDh9CjRw8AQP/+/TF+/Hjs2rULs2bN0nnts88+i06dOjVru+OOOxAV\nFYU9e/YgNjbWmKUT2QRRFHHsXC4++fY8SitqWzyXM0GIbI8kw8XRo0cRGhqqDhYAEBAQgKFDhyIh\nIaHFcHFzsAAAPz8/dO7cGYWFhcYol8gmqGeCFJTDyckONbXKZsdHDfZFaL+uOJSUxZkgRDZOkuFC\nJpMhKipKoz0oKAiHDx++5ffLyMhAcXExgoKCDFEekc25eSZI02DRxcsF/3zodowa3Dge6v67+pq8\nPiKSFkmGi9LSUnh5aQ4A8/LyQllZ2S29l1KpxNKlS9GlSxc88sgjhiqRyKZs07G6pkcHJ2x8NRId\nXBxNXBERSZkkw4Uhvfnmmzh37hw++eQTeHi0fWCZticnMTExHLNBNuV6WQ0+/+/vKCip0nq8qqae\nwYLIgqxbtw7r1683+udIMlx4eXlBoVBotCsUCnh6tn1zo1WrVmHfvn1Yvnw5Ro0adUs1JCQkcOoq\n2SylUoUDJy5j+6ELqKpp0HkeZ4IQWZbY2FiNX5LlcrnWX6j1IclwERQUBJlMptEuk8kQGBjYpvf4\n6KOP8Nlnn2Hx4sWYOHGioUsksipNl+3u1skVSpWIq9erW72OM0GISBtJbrkeGRmJlJQUyOVydZtc\nLkdycnKb0lVcXBzWrFmDefPm4fHHHzdmqUQW78ZgzSv5ZVCpRBQUVzULFv7ebnjz2VFY8MQw9Pb1\nhL2dgN6+nljwxDDOBCEirST55GLq1KnYsWMH5syZg7lz5wIA1q5dCz8/P0ybNk19Xl5eHsaNG4eY\nmBjMmTMHQOMiWu+++y4iIiIwcuRIpKSkqM93d3dv85MPIluha9luAcATE27DQ38LhKODPQAwTBBR\nm0gyXLi6umLr1q1YtmwZFi5cqF7+e9GiRXB1dVWfJ4qi+s8Nx48fBwAcO3YMx44da/a+w4cPR1xc\nnGm+BJEFOHOhUOey3XZ2AqaO62/iiojIGkgyXACAj48P1q5d2+I5/v7+SEtrPkXu3XffxbvvvmvM\n0ogsnryoHJ/F/47TaboXluNgTSJqL8mGCyIyvIrqeuz64SL+ezwTSpXY4rkcrElE7cVwQWTlEpPl\n2PNjOrILyyFAgKpJN6IgAPeM6IWgAC98f+IKl+0mIoNguCCyYjcv2y3ir2AxqG8XzH4wBIEBHQEA\nE8L7mLw+IrJODBdEViozV4F1e85pPebdyRXvzrkLgiCYuCoisgUMF0RWpuh6FbYfuoCjZ3Ig6hhW\nUaKoYbAgIqNhuCCyEhXV9diXkI74Y5mob1C1eC5nghCRMTFcEFmw5oM1gZsngAT6eyEjV3OfHs4E\nISJjYrggslA/nZXj/e1NB2v+pV+Pjnhq4iAMDuyq3jeEM0GIyFQYLogsjEolIik1H2t3J2s97t3J\nFe/PjVCPqYi4I4BhgohMiuGCyEKIoogzF4qw7WAaMrV0ddzAwZpEZG4MF0QS1Wwb9I6usLMTkHet\nstXrOFiTiMyN4YJIgm5e/KqgpKrZcSdHe4QGdcVvWvYG4WBNIjI3hgsiCdp2ME3nsQfu6oMp4/qj\ns6cLB2sSkSQxXBBJyO+Zxdh15CIKiqu0Hre3E/DPh29Xv+ZgTSKSIoYLIjMTRRGpGdew64d0pGZc\na/FcjqcgIkvAcEFkBonJcuxJSEdOQTkcHexRW69sdlxA83UrbuB4CiKyBAwXRCZ28+JXTYOFnZ2A\nu4cFYGpUf8jkpRxPQUQWieGCyETqG1T4+awcG79K0XrcvYMjVr80Fj5d3AAAft7uDBNEZJEYLoiM\nrKqmHodPZuG7xAwUK2p0nldd06AOFkRElozhgsiAmi585d/VDX7e7jifcQ2VNQ2tXsvBmkRkLRgu\niAzk5oWvcooqkFNU0eycjh7OGBzYBcfO5Wlcz8GaRGQtGC6IDEAURcR9r3vhK7+ubnjob0GIDOsB\nJ0d73BnCxa+IyHoxXBDpoaauAUfPyLH/WAYKS7QvfGUnCNi4MAr2dn9tJsbFr4jImjFcELVR0/EU\nfl3d4NfVDX9cLkFFdX2L1/X08WgWLIiIrB3DBVEb3DyeQl5UAflN4ykcHexQ36DSuJZjKYjI1jBc\nELWisroen8X/rvO4T5cOmDi6L8aN6InTaYUcS0FENo/hgkgHWU4pvj9xGYnnclFbp9R6jp0g4ON/\njVN3e3AsBRERwwURgObjKTp5OMPBwQ6FOnYmbYrjKYiINDFckM37+awcq5rs9aFtFc2uHV1xrbRa\no53jKYiINDFckM0qLa/FT2fliPv+D53n3D0sABNG9UFw7044di6X4ymIiNqA4YKsXtMujx7d3HHH\ngG7Iv1aJ02mFUKq0bWzeyN5OwMuPD1O/5ngKIqK2Ybggq3bzFNKsgnJkFZS36Vru9UFE1D525i6A\nyFgKS6rwyXfnWzzntt6d8feRvbQe43gKIqL24ZMLsmhNuzx6dvfAfeF9oFKp8HNyLtKulOi8ThCA\nja9GIqBb49OJ0H5dOZ6CiMhAGC7IYt3c5XElvwwbv0pp07W9fDzVwQLgeAoiIkNitwhZpPKqOmzZ\nr3vVTACwsxPQx89T6zF2eRARGQ+fXJBkaXZ59AYAnEjNR6rsWoszPZ57+HaMDvWDl7uz+n3Y5UFE\nZBoMFyRJ2rs8/tema3v7euL+u/qoX7PLg4jItNgtQpKiVIn443IxNn+b2uq5vl3ctLazy4OIyLz4\n5ILMommXh7+3O0L7dUVFVT3OXChCeVVdi9c+O2kw7gzxhXcnV3Z5EBFJEMMFmdxPZ+V4v8leHjmF\n5cgpbNvCVr19PTFxTF/1a3Z5EBFJD8MFGdzNAzGnRPXDgF6dcS79KlIuXcUvKXktXt/Z0xn+3TyQ\nKrumcYxdHkRE0sdwQQalbSBm09ctEQTgg5fGItDfC4IgsMuDiMhCMVyQQRQrqvFHZgk+/rptMzq0\n6eXjiaCAjurX7PIgIrJMDBd0SxKT5diTkI6cggp08nSGTxc3lChqkF9c2eq1Q4O7YUg/byhVKmw9\nkKZxnF0eRETWgeGCWlVRXQ9ZznUcPpmF403GSxQralCsqGnTe/Ty9cCbs0epX3fr1IFdHkREVorh\nggA0H4TZvZMrbuvTBaIoIj27FLlXK1q93snBDv17dYKHqyOSzhdoHJ8a1b/Za3Z5EBFZL4YLG6Bt\n9kbEHQFQVNTicp4CCb/l4KezcvX5+cVVyC+uavP729kJ2PXOfXB0sG/2eXwqQURkmyQbLgoKCrBs\n2TKcOHECoigiPDwcr732Gnx9fVu9tq6uDqtXr8b+/ftRXl6O2267DfPnz0dYWJgJKpcWXbM3Nu5L\nQWVNQ5vew/7PDcAKS6pQXlWvcbxndw91sAD4VIKIyNZJMlzU1NRgxowZcHZ2xooVKwAAq1evxsyZ\nMxEfHw8XF5cWr1+0aBGOHTuGV199FQEBAdi+fTueeeYZ7N69G8HBwab4CibT9KmEX1c3jBrsiy6e\nLpAXVUB+tULrWhEA2hQsBAFYETsGff284ORorxFUbmjPQMx169YhNjb2lq+jtuM9Ng3eZ+PjPbY8\ngiiKureWNJOtW7dixYoVOHToEHr06AEAkMvlGD9+PBYsWIBZs2bpvPbChQuYNGkS3nvvPUyaNAkA\noFQqcf/996Nv377YuHFji58tl8sRFRWFhIQEBASY97fvm7szosf0RVCPjigsqUJhSRWSLxThzMWi\ndr+/k6M9evt6IO9aJSq0PJHo7euJdfPv1lqTvl0eAwYMwMWLF9tdO7WO99g0eJ+Nj/fYuIzxc0+S\nTy6OHj2K0NBQdbAAgICAAAwdOhQJCQkthouEhAQ4OjpiwoQJ6jZ7e3vcf//9+OSTT1BfXw9HR0dj\nlq9zjIOuc3p0c8eE8N4Y0LMzSsprUKKoQfLFIpxIzVeffyW/DGv3nDNYjf7e7tjwaiTs7YRbeiLB\nLg8iImqNJMOFTCZDVFSURntQUBAOHz7c4rUZGRkICAiAs7OzxrX19fXIzs5GYGBgqzW88UkSZkwa\n1WIouBEcxgzxR32DCjV1SvycLMfmb/7a0fPGGIeT5/Ph3bEDyqvqcCW/DJdyStXnZBWU4+OvW98F\ntK0EAZhx30D4e7ujoLgSn+//XeOcx8cPgL2dAADq78hBmEREZAiSDBelpaXw8vLSaPfy8kJZWVmL\n1yoUCq3XduzYUf3ebSEvqsDKL89g5w8X4dHBCUqVCoqKWhSWVKvPuREcVn15Bq31LR071/J+Grdi\naHA3dO/UASfP5+N6ea3G8V4+npgc+ddThy5eLq0GBz6RICIiQ5FkuDAnpVIJAKivbgwhl6+UmPTz\nB/XtAi93Z6TKrmqdmRHQzR2zJzR2F/l41GPzt5pPPO4e7A+5/K+ppX29gYWPNu/iaHrcXKRQg7Xj\nPTYN3mfj4z02noKCxrWJbvz8MwRJhgsvLy8oFAqNdoVCAU9Pzxav9fT0RF6e5lOCG08sbjzB0OXq\n1asAAHnSx20t16Au/18rxwFE7Wr5nEWtvIdUaOv6IsPiPTYN3mfj4z02vqtXr6JXr14GeS9Jhoug\noCDIZDKNdplM1up4iaCgIPz444+ora1tNu5CJpPB0dERPXv2bPH6kJAQbN++Hd7e3rC3t2/xXCIi\nIkunVCpx9epVhISEGOw9JRkuIiMjsXLlSsjlcvW0GLlcjuTkZMyfP7/Va9etW4eDBw82m4p68OBB\njB49utWZIi4uLja52BYREdkuQz2xuMH+jTfeeMOg72gAAwYMwPfff4/Dhw+jW7duuHz5MpYuXQpX\nV1e8/fbb6oCQl5eHkSNHQhAEDB8+HADg7e2NzMxM7NixAx07dkRZWRlWrVqF1NRUrFq1Cl27djXn\nVyMiIrJ6knxy4erqiq1bt2LZsmVYuHChevnvRYsWwdXVVX2eKIrqP0299957WL16NdasWYPy8nIE\nBwfjs88+s7rVOYmIiKRIkit0EhERkeWyM3cBREREZF0YLoiIiMigbCZcFBQU4MUXX0RYWBiGDRuG\n2NhY5Ofnt34hGrdwX758OUaPHo3Q0FA8+uijOH36tJErtjztvcfnz5/HkiVLMGHCBAwZMgR33303\n5s+fz0VzdNDn73JTmzdvRnBwMKZPn26EKi2bvvc4IyMDc+fOxZ133onQ0FDce++92LZtmxErtjz6\n3OP8/HwsXLgQd999N0JDQzF+/Hh8+OGHqK6ubv1iG1JYWIi33noLjz76KIYMGYLg4GCt60BpI4oi\nNm3ahMjISNx+++148MEH8cMPP7T5s21izEVNTQ2io6Ph7OyMefPmAWjcwr22trZNW7i/8sorGlu4\nJyYmWuUW7u2lzz1evnw5UlJSMHHiRPTr1w+FhYXYsGEDiouLER8fj+7du5vqa0ievn+Xb8jJyUF0\ndDTc3NzQq1cvbN++3ZhlWxR973FqaipmzZqFkSNH4pFHHoGHhweysrJQWVnZ4qaLtkSfe1xdXY1J\nkyZBqVQiNjYWvr6+SE1Nxdq1axEVFYUPPvjAVF9D8k6dOoWXX34ZgwYNglKpxC+//IKEhAT4+fm1\neu3q1auxZcsWvPzyyxg4cCAOHDiAPXv2YNOmTYiIiGj9w0Ub8MUXX4gDBw4Us7Oz1W05OTniwIED\nxS1btrR4bVpamjhgwADxm2++Ubc1NDSI48ePF59//nljlWxx9LnHJSUlGm25ublicHCwuHbtWkOX\natH0uc9NPf300+KSJUvEJ554Qnz88ceNUKnl0uceq1Qq8b777hNjY2ONXKVl0+ceHz9+XAwODhZP\nnDjRrH3VqlXioEGDxJqaGmOUbPH27NkjBgcHi7m5ua2eW1xcLIaEhIjr1q1r1j5z5kwxOjq6TZ9n\nE90irW3h3pKWtnA/fvw46us19/+wRfrc406dOmm0+fn5oXPnzigsLDR4rZZMn/t8w/79+5GWloZX\nXnnFWGVaNH3u8cmTJ5GZmcknFK3Q5x7f+DfXzc2tWbuHhwdUKpXG0gR06xITE9HQ0IDo6Ohm7dHR\n0UhPT0dubm6r72ET4UImk6Ffv34a7UFBQcjIyGjx2rZs4U763WNtMjIyUFxcjKCgIEOUZzX0vc9l\nZWV477338Oqrr7a6T4+t0ucenz17FkDjY/9p06YhJCQE4eHhePvtt1Fbq7mDsa3S5x6Hh4ejV69e\nWLlyJTIyMlBVVYWkpCTExcXhsccea3PXIOmWkZEBJycnje0ygoKCIIqi1u05bmYT4UIKW7hbO33u\n8c2USiWWLl2KLl264JFHHjFUiVZB3/u8fPly9OnTR700PmnS5x4XFRVBFEXMmzcPY8aMwZYtWzB7\n9mzs27ev1a0LbIk+99jJyQk7duyASqXC/fffj6FDh+Lpp59GZGQkFi9ebKySbYpCoYCHh4dG+42f\ne9o2Fr2ZJFfoJNv25ptv4ty5c/jkk0+0/gWn9jl9+jTi4+Px7bffmrsUqyWKIgRBwIMPPoiYmBgA\nwPDhw9HQ0IAPPvgAmZmZ6Nu3r5mrtGx1dXWYO3cuSkpKsGrVKvj4+CA1NRXr16+HnZ0dJLijhU2y\niXBhzi3cbYU+97ipVatWYd++fVi+fDlGjRplyBKtgj73eenSpZg8eTK6deuG8vJyiKIIpVIJlUqF\n8vJyODs7w8nJyVilWwx97vGNfw/Cw8ObtY8ePRrvv/8+0tLSGC6g3z3eu3cvTp8+jSNHjqg3tgwL\nC4O7uzuWLFmCxx57DAMGDDBK3bbC09MT5eXlGu03fu5pe+p0M5voFtF3C3e5XK7RX9rWLdxthT73\n+IaPPvoIn332GV5//XVMnDjR0CVaBX3uc0ZGBnbt2oXhw4dj+PDhGDFiBM6ePYtz585hxIgR2LVr\nl7HKtij6/nvREkEQ9KrNWuhzj9PT0+Hp6akOFjcMHjwYoii2a4wXNRcUFIS6ujrk5OQ0a5fJZBAE\noU1j4WwiXERGRiIlJaXZokw3tnCPiopq9dr6+nocPHhQ3XYrW7jbCn3uMQDExcVhzZo1mDdvHh5/\n/HFjlmrR9LnP27ZtQ1xcHLZt26b+ExwcjP79+2Pbtm0YP368scu3CPrc44iICDg6OuL48ePN2hMT\nEyEIAgYPHmyUmi2NPvfY29sbZWVlGj/4UlJSIAgC18UxgIiICNjb2yM+Pr5Ze3x8PPr16wd/f/9W\n30OSW64bGrdwNz597vGBAwewZMkSRERE4KGHHkJhYaH6T2VlJTp37mzOryYp+txnf39/jT8HDhyA\nk5MTYmNj4e7ubs6vJhn63GMXFxcolUp88cUX6qedBw8exMaNGxEdHY2HH37YbN9LSvT9e/zVV18h\nISEB7u7uUCgUOHToENasWYMBAwZg7ty55vxqknP48GFkZGTgzJkzOH/+PHr37o28vDxcv35dHRIG\nDhyI/Px8REZGAmjcmby6uhqff/45XF1dUVdXh82bN+PIkSN455130Lt371Y/1ybGXHALd+PT5x7f\n+C3v2LFjOHbsWLP3HT58OOLi4kzzJSyAvn+XteGj+ub0vccxMTFwd3fHzp078fnnn8Pb2xuzZ8/G\n888/b+qvIln63GN/f3/s3r0b69evx5o1a3D9+nX4+Pjg0UcfxXPPPWeOryNpc+fOVf83LggC/vOf\n/wBo/m+rKIpQqVTNrnv55Zfh5uaGuLg4XLt2DX369MGaNWswduzYNn2uTSz/TURERKZjE2MuiIiI\nyHQYLoiIiMigGC6IiIjIoBguiIiIyKAYLoiIiMigGC6IiIjIoBguiIiIyKAYLoiIiMigGC6IiIjI\noBguiIiIyKAYLoiIiMigGC6IiIjIoBguiMjkVq9ejeDgYIwaNQrFxcVaz3nmmWcQHByMRx55BEql\n0sQVEpE+GC6IyORiY2MxcOBAlJaW4rXXXtM4/uWXX+KXX36Bq6srVq1aBXt7ezNUSUTtxXBBRCbn\n4OCAlStXwtnZGYmJidi5c6f6WGZmJlatWgVBEDB//nz06dPHjJUSUXswXBCRWQQGBmL+/PkQRREr\nVqzAlStXoFQqsWDBAtTW1mL06NGYPn26ucskonYQRFEUzV0EEdmuf/zjHzh+/DhCQkJw1113YdOm\nTejYsSP2798Pb29vc5dHRO3AcEFEZnX16lVMnDgRCoUCoihCEAR8+OGHGD9+vLlLI6J2YrcIEZmV\nt7c3Xn75ZXWwuPfeexksiCwcwwURmZVKpcLXX38NABBFEWlpaaipqTFzVUSkD4YLIjKrTZs24dy5\nc/D09ISfnx+uXLmC9957z9xlEZEeOOaCiMzm999/x7Rp06BUKrFixQp0794dM2fOBNAYOiIiIsxc\nIRG1B59cEJFZ1NbWYsGCBVAqlbj33nsxceJEjBgxArNmzYIoivj3v/+N0tJSc5dJRO3AcEFEZrFy\n5UpkZmaiW7duePPNN9Xt8+bNQ79+/XDt2jUsWbLEjBUSUXsxXBCRyR0/fhzbt2+HIAhYtmwZPD09\n1cecnJywcuVK2Nvb48iRI/jmm2/MWCkRtQfDBRGZVFlZmXo/kenTp+Ouu+7SOCc4OBgvvvgiAGDZ\nsmXIy8szaY1EpB8O6CQiIiKD4pMLIiIiMiiGCyIiIjIohgsiIiIyKIYLIiIiMiiGCyIiIjIohgsi\nIiIyKIYLIiIiMiiGCyIiIjIohgsiIiIyKIYLIiIiMqj/B983H8IQtjtgAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f22adb25ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot1()"
]
}
],
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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