{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from __future__ import print_function\n",
    "import matplotlib\n",
    "matplotlib.use('Agg') \n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from urllib import urlopen\n",
    "import os\n",
    "from IPython import get_ipython\n",
    "import string\n",
    "from scipy.signal import argrelextrema\n",
    "import scipy.optimize as spo\n",
    "\n",
    "\n",
    "\n",
    "def is_interactive(): # are we in jupyter ??\n",
    "    import __main__ as main\n",
    "    return not hasattr(main, '__file__')\n",
    "\n",
    "\n",
    "\n",
    "if is_interactive():\n",
    "    %matplotlib inline\n",
    "    \n",
    "   \n",
    "baseURL = \"http://golem.fjfi.cvut.cz/utils/data/\" #global\n",
    "#baseURL = \"/golem/database/operation/shots/\" #local\n",
    "\n",
    "        \n",
    "\n",
    "def mkdir(dir):  \n",
    "    try:os.makedirs(dir) \n",
    "    except OSError:pass\n",
    "\n",
    "FigSize=10,8\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#ShotNo=str(int(np.loadtxt('../../../../ShotNo' )))\n",
    "#ShotNo=string.replace(os.path.basename(os.getcwd()),'#','') # get ShotNumber from discharge database where we currently are\n",
    "ShotNo='0' #Last shot\n",
    "#ShotNo='23172' \n",
    "ReferenceShot=ShotNumber=ShotNo # sorry'\n",
    "\n",
    "\n",
    "\n",
    "#Plasma parameters\n",
    "PlasmaStart=int(float(np.loadtxt(urlopen(baseURL+ShotNo+'/plasma_start')))*1e6) # in us\n",
    "PlasmaEnd=int(float(np.loadtxt(urlopen(baseURL+ShotNo+'/plasma_end')))*1e6) # in us\n",
    "ShotNumber=int(np.loadtxt(urlopen(baseURL+ShotNo+'/shotno')))\n",
    "\n",
    "toroidal_field=np.loadtxt(urlopen(baseURL+str(ShotNumber)+'/toroidal_field'))\n",
    "loop_voltage=np.loadtxt(urlopen(baseURL+str(ShotNumber)+'/loop_voltage'))\n",
    "photodiode=np.loadtxt(urlopen(baseURL+str(ShotNumber)+'/photodiode'))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reference discharge ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c32b38ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YR/8LsWbThZzY0f9U4GtgIPBDEa8FBTQRATwe+PlnmDEDZs6EH36Atm2hVy8LZR07qmO/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\nERERERERERERERERERERERERERG/+n8Uw+pWeK3rUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2c32b38f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Reference discharge ...\")\n",
    "\n",
    "f = plt.figure(figsize=(20.0, 5.0))\n",
    "f,ax = plt.subplots(3,sharex=True);plt.subplots_adjust(hspace=0.001)\n",
    "f.set_size_inches(FigSize)\n",
    "ax[0].set_title('#' + str(ShotNumber))\n",
    "ax[0].plot(toroidal_field[0:,0]*1000,toroidal_field[0:,1]);ax[0].set_ylabel('$B_t$ [T]');ax[0].set_ylim(0,)\n",
    "ax[1].plot(loop_voltage[0:,0]*1000,loop_voltage[0:,1]);ax[1].set_ylabel('$U_l$ [V]');ax[1].set_ylim(0,)\n",
    "ax[2].plot(photodiode[0:,0]*1000,photodiode[0:,1]);ax[2].set_ylabel('$I_{rad}$ [a.u.]');ax[2].set_ylim(0,)\n",
    "ax[2].set_xlim(PlasmaStart*0.6/1000,PlasmaEnd*1.4/1000)\n",
    "#ax[2].set_xlim(0,30)\n",
    "ax[2].set_xlabel('Time $t$ [ms]');\n",
    "plt.savefig('BasicDiagnostics.jpg', bbox_inches='tight')\n",
    "if is_interactive():plt.show();\n",
    "plt.close();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finding sweeping intervals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "html generation ...\n"
     ]
    }
   ],
   "source": [
    "print(\"html generation ...\")\n",
    "\n",
    "os.system('rm index.html');\n",
    "fileid = open('index.html','a+')\n",
    "fileid.write('<html><head><title>Tokamak GOLEM fusion promo</title>\\\n",
    "<style>\\\n",
    "</style>\\\n",
    "<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\\\n",
    "<style></style>\\\n",
    "<script type=\"text/x-mathjax-config\">MathJax.Hub.Config({tex2jax: {inlineMath: [[\\'$\\',\\'$\\'], [\\'\\\\(\\',\\'\\\\)\\']]}});</script>\\\n",
    "<script src=\"https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML\"></script>\\\n",
    "</head><body><center>')\n",
    "fileid.write('<h1>Tokamak GOLEM fusion promo</h1>')\n",
    "fileid.write('<h2>Basic parameters</h2><ul>')\n",
    "fileid.write('<li>Plasma start: '+str(float(np.loadtxt(urlopen(baseURL+ShotNo+'/plasma_start'))*1e3))+' ms</li>')\n",
    "fileid.write('<li>Plasma end: '+str(float(np.loadtxt(urlopen(baseURL+ShotNo+'/plasma_end'))*1e3))+' ms</li>')\n",
    "fileid.write('<li>Plasma life: '+str(float(np.loadtxt(urlopen(baseURL+ShotNo+'/plasma_life'))*1e3))+' ms</li>')\n",
    "fileid.write('<li>Maximal (electron) temperature :~ '+str(int(float(np.loadtxt(urlopen(baseURL+ShotNo+'/electron_temperature_max'))*11600)/1000))+' 000 K</li>')\n",
    "fileid.write('</ul>')\n",
    "fileid.write('<h2>Basic diagnostics</h2>')\n",
    "fileid.write('<img src=\"BasicDiagnostics.jpg\">')\n",
    "fileid.write('</center></body></html>')\n",
    "fileid.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
