{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import requests\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shot_no = 46831 # to be replaced by the actual discharge number"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plasma life time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plasma_start = float(requests.get(f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/PlasmaDetection/Results/t_plasma_start').text)\n",
    "plasma_end = float(requests.get(f'http://golem.fjfi.cvut.cz/shots/{shot_no}/Diagnostics/PlasmaDetection/Results/t_plasma_end').text)\n",
    "\n",
    "\n",
    "print ('Plasma start =', round(plasma_start, 3), 'ms')\n",
    "print ('Plasma end =', round(plasma_end, 3), 'ms')\n",
    "\n",
    "# convert to s\n",
    "plasma_start*=1e-3\n",
    "plasma_end*=1e-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.load('DAS_raw_data_dir/dataHiRes.npz')\n",
    "df = pd.DataFrame({ name : data[name] for name in ['time', 'ch1', 'ch2']}, index='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plasma = df[plasma_start:plasma_end]\n",
    "df_plasma.plot.scatter(x = 'ch1', y = 'ch2')\n",
    "plt.savefig('icon-fig.png')"
   ]
  }
 ],
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