{
  "nbformat_minor": 0, 
  "nbformat": 4, 
  "cells": [
    {
      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "%matplotlib inline"
      ], 
      "outputs": [], 
      "metadata": {
        "collapsed": false
      }
    }, 
    {
      "source": [
        "\n# 1D contour with multiple data sets\n\n\nPlot 1D contour with multiple data sets using some default settings.\n\n"
      ], 
      "cell_type": "markdown", 
      "metadata": {}
    }, 
    {
      "execution_count": null, 
      "cell_type": "code", 
      "source": [
        "import coplot.plot_contours as plc\nimport coplot.plots as pl\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\na1 = np.random.randn(10000)\na2 = a1 + 1\n\n# If you want to use some default settings, you can use it like this:\nfig = plc.Plot_1d([a1,a2]).plot(labels=[r'$a$', r'$\\rm PDF$'], legend=True, ticks_size=10)\n# and you can save the figure like this:\n# pl.savefig('test_1d_2.pdf', fig)\nplt.show()"
      ], 
      "outputs": [], 
      "metadata": {
        "collapsed": false
      }
    }
  ], 
  "metadata": {
    "kernelspec": {
      "display_name": "Python 2", 
      "name": "python2", 
      "language": "python"
    }, 
    "language_info": {
      "mimetype": "text/x-python", 
      "nbconvert_exporter": "python", 
      "name": "python", 
      "file_extension": ".py", 
      "version": "2.7.18", 
      "pygments_lexer": "ipython2", 
      "codemirror_mode": {
        "version": 2, 
        "name": "ipython"
      }
    }
  }
}