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   "id": "86a5df32-2d0e-4de1-a7c1-5dff2d96d39e",
   "metadata": {},
   "source": [
    "### How to access Strax data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af3ab6b7-9d20-47aa-9e5c-fb096a5b6853",
   "metadata": {},
   "source": [
    "Start with a conda environment {conda env:2022.11.1}\n",
    "Data is scattered in stor0, stor1 and stor2, most of the new data downloaded should be in stor2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01caea8b-f022-44d1-8a05-d42f2dcb030d",
   "metadata": {},
   "source": [
    "There might be an error when you import some of the following modules, you can ignore that."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c589d1a-41b3-4853-aaff-db112ca146cd",
   "metadata": {},
   "source": [
    "NOTE: Cutax does not come with the environments provided, you will have to downloaded an appropriate version of cutax (if you even need to use cutax/want to use it) at https://github.com/XENONnT/cutax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01aed115-c586-41a3-84b8-d988b1a0b51a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import strax \n",
    "import straxen \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cutax # download cutax version 1.13.0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3a2c4b5-924b-4ebe-9d94-ccd9ea9cdc9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_id = '049047' #"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c88bfbc2-c108-45fa-9778-dc67b709e783",
   "metadata": {},
   "source": [
    "You can set the environment to either use cutax or straxen, the functionality will be the same. The main difference is that cutax allows you to use data cuts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4156373e-f0a3-4fa4-a6ae-e02ea6e50120",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Cutax\n",
    "st = cutax.contexts.xenonnt_offline(cmt_version = 'global_v9',\n",
    "                                    _raw_path = '/stor2/data/raw_recrods', \n",
    "                                    _processed_path = '/stor2/data/processed_data', \n",
    "                                    output_folder = '/stor2/data/processed_data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34cb5b29-dcb9-4fac-887c-5f80c6a6cac7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For Straxen\n",
    "st = straxen.contexts.xenonnt(xedocs_version = 'global_v10',\n",
    "                                    _raw_paths = '/stor2/data/raw_recrods', \n",
    "                                    _processed_paths = '/stor2/data/processed_data', \n",
    "                                    output_folder = '/stor2/data/processed_data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28b19e98-5e0d-4b5d-98fb-2f23c004cf71",
   "metadata": {},
   "outputs": [],
   "source": [
    "st.is_stored(run_id, 'raw_records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4bcbdff3-0c69-4c7d-8e4b-2c7fb653025d",
   "metadata": {},
   "outputs": [],
   "source": [
    "rn_peaks = st.get_array(run_id, 'peaks') # get peak level data! this might take a while if the data has not been generated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95f38754-8823-43e7-890b-ae5c192571e2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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