Bayar Menzat added file figures/2xraster/plot for authorea.ipynb  almost 9 years ago

Commit id: 46f6f55433b88647310bb93545753dc845ce9055

deletions | additions      

         

{  "cells": [  {  "cell_type": "code",  "execution_count": 1,  "metadata": {  "collapsed": false  },  "outputs": [  {  "name": "stdout",  "output_type": "stream",  "text": [  "hello world\n"  ]  }  ],  "source": [  "print 'hello world'"  ]  },  {  "cell_type": "code",  "execution_count": 2,  "metadata": {  "collapsed": true  },  "outputs": [],  "source": [  "import numpy as np"  ]  },  {  "cell_type": "code",  "execution_count": 3,  "metadata": {  "collapsed": true  },  "outputs": [],  "source": [  "import matplotlib.pyplot as plt"  ]  },  {  "cell_type": "code",  "execution_count": 4,  "metadata": {  "collapsed": true,  "run_control": {  "marked": true  }  },  "outputs": [],  "source": [  "%matplotlib inline"  ]  },  {  "cell_type": "code",  "execution_count": 8,  "metadata": {  "collapsed": false  },  "outputs": [  {  "data": {  "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEACAYAAACuzv3DAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",  "text/plain": [  ""  ]  },  "metadata": {},  "output_type": "display_data"  }  ],  "source": [  "plt.plot(np.random.random((10,)))\n",  "plt.show()"  ]  },  {  "cell_type": "code",  "execution_count": null,  "metadata": {  "collapsed": true  },  "outputs": [],  "source": []  }  ],  "metadata": {  "kernelspec": {  "display_name": "Python 2",  "language": "python",  "name": "python2"  },  "language_info": {  "codemirror_mode": {  "name": "ipython",  "version": 2  },  "file_extension": ".py",  "mimetype": "text/x-python",  "name": "python",  "nbconvert_exporter": "python",  "pygments_lexer": "ipython2",  "version": "2.7.9"  }  },  "nbformat": 4,  "nbformat_minor": 0  }