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   "source": [
    "<div style=\"text-align:center\"><h1>AWAKE ANALYSIS TOOLS Tutorial</h1></div>\n",
    "<div style=\"text-align:center\"><h2><i>Set of Analysis sub-routines packed for performing analysis of data discovered by AWAKE</i></h2></div>\n",
    "<div style=\"text-align:center\"><i>https://gitlab.cern.ch/AWAKE/AWAKE_ANALYSIS_TOOLS</i></div>\n",
    "<hr style=\"border-top-width: 4px; border-top-color: #34609b;\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook demonstrates accessing the AWAKE CSV compressed database and visualizing the extracted datasets  \n",
    "***Author: Aman Singh Thakur***  \n",
    "***Contact: Spencer Jake Gessner / Prasanth Kothuri***  \n",
    "  \n",
    "To run this notebook we used the following configuration:\n",
    "* *Software stack*: LCG_96 Python3\n",
    "* *Platform*: centos8-gcct\n",
    "\n",
    "This is developed in the context of CERN-HSF Google Summer Of Code \n",
    "<img align=\"left\" src=\"https://developers.google.com/open-source/gsoc/resources/downloads/GSoC-logo-horizontal-200.png\" alt=\"Italian Trulli\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "''' Replace this line with your local AWAKE_ANALYSIS_TOOLS directory '''\n",
    "os.environ['AAT'] = '/eos/user/a/amthakur/SWAN_projects/AWAKE_ANALYSIS_TOOLS/'\n",
    "sys.path.append(os.environ['AAT']+'ntupling/')\n",
    "sys.path.append(os.environ['AAT']+'utilities/')\n",
    "sys.path.append(os.environ['AAT']+'analyses/')\n",
    "\n",
    "''' Imports from AWAKE_ANALYSIS_TOOLS '''\n",
    "import cutParser\n",
    "from bunchRotationStatus import bunchRotationStatus\n",
    "import returnGoodData as rgd\n",
    "from returnPlasmaDensity import returnPlasmaDensity\n",
    "import frame_analysis as fa\n",
    "from custom_cmap import custom_cmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we specify the data we want to load with an external file.<br/> \n",
    "Alternatively, we can generate this file from within the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_file = 'input_delay_scan.txt'\n",
    "input_path = os.environ['AAT']+'/examples/'\n",
    "InputParsed=cutParser.inputParser(input_path+input_file)\n",
    "file_list, file_bool = InputParsed()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_path = '/AwakeEventData/XMPP-STREAK/StreakImage/streakImageData'\n",
    "image_data = rgd.returnGoodData(image_path,file_list)\n",
    "\n",
    "window_path = '/AwakeEventData/XMPP-STREAK/StreakImage/streakImageTimeRange'\n",
    "window_data = rgd.returnGoodData(window_path,file_list)\n",
    "\n",
    "sps_bucket_path = '/AwakeEventData/VTUAwake2Fc/NormalModeAcq/b_offline'\n",
    "sps_bucket_data = rgd.returnGoodData(sps_bucket_path,file_list)\n",
    "\n",
    "sps_degree_path = '/AwakeEventData/AWAKEInjPhaseShifter/PhaseReadback/phaseACurrentValue'\n",
    "sps_degree_data = rgd.returnGoodData(sps_degree_path,file_list)"
   ]
  }
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