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   "source": [
    "## Example 4: Sweep Scan loading\n",
    "This is an example showcasing the loading of a kinetic energy sweep scan\n",
    "\n",
    "The individual images are loaded, and summed onto the grid of data that overlap on all images"
   ]
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    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from specsscan import SpecsScan\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib widget"
   ]
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    "Here, a SpecsScan class instance is created as per the configuration provided in [config.yaml](../tests/data/config.yaml). Crop parameters are set by an additional config dictionary."
   ]
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    "config = {\"spa_params\": {\n",
    "    'ek_range_min': 0.07597844332538357,\n",
    "    'ek_range_max': 0.8965456312395133,\n",
    "    'ang_range_min': 0.16732026143790849,\n",
    "    'ang_range_max': 0.8449673202614381,\n",
    "    \"angle_offset_px\":13,\n",
    "    \"rotation_angle\": 2,\n",
    "    \"crop\":True,\n",
    "}}\n",
    "sps = SpecsScan(config=config, user_config=\"../src/specsscan/config/example_config_FHI.yaml\")\n",
    "path = \"../tests/data/\" # Path to the test data set"
   ]
  },
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   "source": [
    "The load_scan method performs the merging of the images and returns the scan as an xarray"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res_xarray = sps.load_scan(\n",
    "    scan=6455, # Scan number for an example sweep scan\n",
    "    path=path,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure()\n",
    "res_xarray.plot()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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