zonca/websky_sources_high_flux_catalog.ipynb

## websky_sources_high_flux_catalog.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0ed31a46-d481-4958-af82-3889e2f6b80a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import h5py\n",
    "import numpy as np\n",
    "import healpy as hp\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8e35f4b9-bc39-49e9-af61-67464526f4d9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/global/cfs/cdirs/sobs/www/users/Radio_WebSky/matched_catalogs_2\n"
     ]
    }
   ],
   "source": [
    "cd /global/cfs/cdirs/sobs/www/users/Radio_WebSky/matched_catalogs_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "031d3e3d-b9d0-4c73-80bb-bbd804a825fe",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "catalog_100.0.h5  catalog_232.0.h5  catalog_353.0.h5  catalog_643.0.h5\r\n",
      "catalog_111.0.h5  catalog_24.5.h5   catalog_375.0.h5  catalog_67.8.h5\r\n",
      "catalog_129.0.h5  catalog_256.0.h5  catalog_409.0.h5  catalog_70.0.h5\r\n",
      "catalog_143.0.h5  catalog_27.3.h5   catalog_41.7.h5   catalog_729.0.h5\r\n",
      "catalog_153.0.h5  catalog_275.0.h5  catalog_44.0.h5   catalog_73.7.h5\r\n",
      "catalog_164.0.h5  catalog_294.0.h5  catalog_467.0.h5  catalog_79.6.h5\r\n",
      "catalog_18.7.h5   catalog_30.0.h5   catalog_47.4.h5   catalog_817.0.h5\r\n",
      "catalog_189.0.h5  catalog_306.0.h5  catalog_525.0.h5  catalog_857.0.h5\r\n",
      "catalog_21.6.h5   catalog_314.0.h5  catalog_545.0.h5  catalog_90.2.h5\r\n",
      "catalog_210.0.h5  catalog_340.0.h5  catalog_584.0.h5  catalog_906.0.h5\r\n",
      "catalog_217.0.h5  catalog_35.9.h5   catalog_63.9.h5\r\n"
     ]
    }
   ],
   "source": [
    "%ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ba71f7d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "freqs = [\n",
    "    \"18.7\",\n",
    "    \"24.5\",\n",
    "    \"44.0\",\n",
    "    \"70.0\",\n",
    "    \"100.0\",\n",
    "    \"143.0\",\n",
    "    \"217.0\",\n",
    "    \"353.0\",\n",
    "    \"545.0\",\n",
    "    \"643.0\",\n",
    "    \"729.0\",\n",
    "    \"857.0\",\n",
    "    \"906.0\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d0653ac2-3d67-4480-849d-bcca2727a143",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "cat = h5py.File(\"catalog_100.0.h5\", \"r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80b4c835",
   "metadata": {},
   "source": [
    "There are no metadata in the file, I guess fluxes are in `Jy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5f8de1f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "cutoff_flux = .1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1ad4445f",
   "metadata": {},
   "outputs": [],
   "source": [
    "high_flux_sources_mask = cat[\"flux\"][:] > cutoff_flux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e916cd08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2587"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(high_flux_sources_mask).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4483e313",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0009181691064907792"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "high_flux_sources_mask.mean() * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "06739d8b-fc8a-46d8-a430-c905f89fb37c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flux [3.24291534e-07 3.16862867e-07 3.17171157e-07]\n",
      "phi [3.22861886 3.22861886 3.22861886]\n",
      "polarized flux [1.42910628e-09 1.99535624e-08 2.29563857e-09]\n",
      "theta [1.64009452 1.64009452 1.64009452]\n"
     ]
    }
   ],
   "source": [
    "for k, v in cat.items():\n",
    "    print(k, v[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "306159e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "(all_indices,) = np.nonzero(high_flux_sources_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1b7ed1da-8a08-47a0-a513-538bfec1dd9b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2587"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "06ee9c0f-c6d6-4f86-ba98-5ec295e18f0b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "all_indices = np.array(sorted(all_indices))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "886dbbaf-8890-449c-bab4-2f7eba722d31",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b918e34e-b782-480b-8067-c3c31df9c436",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "columns = [\"theta\", \"phi\", \"flux\", \"polarized flux\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0851b3a4-7214-4182-9afb-c21768fd96e4",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "flux = xr.DataArray(\n",
    "    data=np.zeros((len(all_indices), len(freqs)), dtype=np.float64),\n",
    "    coords={\"index\": all_indices, \"freq\": list(map(float, freqs))},\n",
    "    name=\"flux\",\n",
    ")\n",
    "fluxnorm = flux.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "394e8f66-d9e7-446e-af75-6940184da4a7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "polarized_flux = flux.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6dedf80b-4d9c-4a8b-b028-ca99f5f1393e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18.7\n",
      "24.5\n",
      "44.0\n",
      "70.0\n",
      "100.0\n",
      "143.0\n",
      "217.0\n",
      "353.0\n",
      "545.0\n",
      "643.0\n",
      "729.0\n",
      "857.0\n",
      "906.0\n"
     ]
    }
   ],
   "source": [
    "sources_xr = xr.Dataset(\n",
    "    {\"flux\": flux, \"polarized_flux\": polarized_flux, \"fluxnorm\": fluxnorm}\n",
    ")\n",
    "for freq in freqs:\n",
    "    print(freq)\n",
    "    cat = h5py.File(f\"catalog_{freq}.h5\", \"r\")\n",
    "    for column in [\"flux\", \"polarized_flux\"]:\n",
    "        sources_xr[column].loc[dict(index=all_indices, freq=float(freq))] = cat[\n",
    "            column.replace(\"_\", \" \")\n",
    "        ][high_flux_sources_mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8f1fa80e-f674-40c1-bb9d-901503650240",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sources_xr = sources_xr.sortby(sources_xr.flux.loc[dict(freq=float(freqs[0]))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "074fa7ac-7aae-4513-af86-cbe2a24082b1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sources_xr.coords[\"index\"] = np.arange(len(sources_xr.coords[\"index\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e38b940b-9b60-4162-bb0f-392dcea5563f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for s in range(len(all_indices)):\n",
    "    sources_xr[\"fluxnorm\"].loc[dict(index=s)] = sources_xr[\"flux\"].loc[\n",
    "        dict(index=s)\n",
    "    ] / sources_xr[\"flux\"].loc[dict(index=s)].sel(freq=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8728e619-1716-4894-9ecb-94ba384a2266",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'fluxnorm' (freq: 13)>\n",
      "array([30.40802202, 17.91860293,  6.28537366,  2.15768438,  1.        ,\n",
      "        0.52485817,  0.28947277,  0.14876815,  0.08212189,  0.06549698,\n",
      "        0.0551598 ,  0.0442103 ,  0.04097164])\n",
      "Coordinates:\n",
      "  * freq     (freq) float64 18.7 24.5 44.0 70.0 ... 643.0 729.0 857.0 906.0\n",
      "    index    int64 2586 <xarray.DataArray 'flux' (freq: 13)>\n",
      "array([1118.93920898,  659.35980225,  231.28604126,   79.39739227,\n",
      "         36.79750061,   19.31346893,   10.65187454,    5.47429609,\n",
      "          3.02188039,    2.41012502,    2.02974296,    1.62682843,\n",
      "          1.50765407])\n",
      "Coordinates:\n",
      "  * freq     (freq) float64 18.7 24.5 44.0 70.0 ... 643.0 729.0 857.0 906.0\n",
      "    index    int64 2586\n"
     ]
    }
   ],
   "source": [
    "print(sources_xr[\"fluxnorm\"].loc[dict(index=s)], sources_xr[\"flux\"].loc[dict(index=s)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e6f77665-62a3-45d5-b1cd-73f19e4ba279",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f6d11c58100>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sources_xr.fluxnorm.plot(vmin=0, vmax=100)\n",
    "plt.figure()\n",
    "sources_xr.flux.plot(vmin=0, vmax=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "41cd2b38-0caf-41ae-a8f5-871d205238c3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sources_xr[\"logpolycoefflux\"] = xr.DataArray(\n",
    "    np.zeros((len(all_indices), 5), dtype=np.float64),\n",
    "    dims=[\"index\", \"power\"],\n",
    "    coords={\"power\": np.arange(5)},\n",
    ")\n",
    "sources_xr[\"logpolycoefnorm\"] = sources_xr[\"logpolycoefflux\"].copy()\n",
    "sources_xr[\"logpolycoefpolflux\"] = sources_xr[\"logpolycoefflux\"].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6dbd89aa-fe34-401f-8d9d-43330c8057c9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from scipy.optimize import curve_fit\n",
    "\n",
    "\n",
    "def model(freq, a, b, c, d, e):\n",
    "    log_freq = np.log(freq)\n",
    "    return a + b * log_freq + c * log_freq**2 + d * log_freq**3 + e * log_freq**4\n",
    "\n",
    "\n",
    "for s in range(len(all_indices)):\n",
    "    sources_xr[\"logpolycoefflux\"].loc[dict(index=s)], cov = curve_fit(\n",
    "        model, sources_xr.coords[\"freq\"], sources_xr.flux.sel(index=s)\n",
    "    )\n",
    "    sources_xr[\"logpolycoefpolflux\"].loc[dict(index=s)], cov = curve_fit(\n",
    "        model, sources_xr.coords[\"freq\"], sources_xr.polarized_flux.sel(index=s)\n",
    "    )\n",
    "    sources_xr[\"logpolycoefnorm\"].loc[dict(index=s)], cov = curve_fit(\n",
    "        model, sources_xr.coords[\"freq\"], sources_xr.fluxnorm.sel(index=s)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fbfa997a-54f3-43ab-bfbe-6b1ae107a368",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for s in range(len(all_indices)):\n",
    "    plt.figure()\n",
    "    sources_xr.flux.sel(index=s).plot(marker=\"o\", linestyle=\"none\")  # , xscale=\"log\")\n",
    "    sources_xr.fluxnorm.sel(index=s).plot(\n",
    "        marker=\"o\", linestyle=\"none\"\n",
    "    )  # , xscale=\"log\")\n",
    "\n",
    "    plt.loglog(\n",
    "        sources_xr.coords[\"freq\"],\n",
    "        model(sources_xr.coords[\"freq\"], *sources_xr.logpolycoefflux.sel(index=s)),\n",
    "    )\n",
    "    plt.loglog(\n",
    "        sources_xr.coords[\"freq\"],\n",
    "        model(sources_xr.coords[\"freq\"], *sources_xr.logpolycoefnorm.sel(index=s)),\n",
    "    )\n",
    "    plt.grid()\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "31df666c-4e49-40f1-b884-9e3eec1da294",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<xarray.DataArray 'logpolycoefflux' ()>\n",
       " array(-17557.80288493),\n",
       " <xarray.DataArray 'logpolycoefflux' ()>\n",
       " array(23993.59927165))"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sources_xr.logpolycoefflux.min(), sources_xr.logpolycoefflux.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "43f02e70-7a7e-408d-851e-17d4f6356f5e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f6d1173c340>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "plt.subplot(121)\n",
    "sources_xr.logpolycoefflux.plot(vmax=50, vmin=-50)\n",
    "plt.subplot(122)\n",
    "sources_xr.logpolycoefnorm.plot(vmax=50, vmin=-50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a8be3926-00e6-4a14-a66a-060424b6d405",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "\n",
    "for power in range(5):\n",
    "    plt.subplot(231 + power)\n",
    "\n",
    "    np.fabs(sources_xr.logpolycoefflux.loc[dict(power=power)]).plot.hist(\n",
    "        bins=np.logspace(-0, 4, 20), density=False, lw=3, label=\"fluxes\"\n",
    "    )\n",
    "\n",
    "    np.fabs(sources_xr.logpolycoefnorm.loc[dict(power=power)]).plot.hist(\n",
    "        bins=np.logspace(-0, 4, 20),\n",
    "        density=False,\n",
    "        histtype=\"step\",\n",
    "        lw=2,\n",
    "        label=\"normalized fluxes\",\n",
    "        linestyle=\"--\",\n",
    "    )\n",
    "    plt.grid()\n",
    "    plt.title(f\"Power {power}\")\n",
    "    plt.legend()\n",
    "    plt.xscale(\"log\")\n",
    "    plt.xlabel(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a77ffa7b-6e77-4187-b84f-89c9e2b7da23",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:             (freq: 13, index: 2587, power: 5)\n",
       "Coordinates:\n",
       "  * freq                (freq) float64 18.7 24.5 44.0 70.0 ... 729.0 857.0 906.0\n",
       "  * index               (index) int64 0 1 2 3 4 5 ... 2582 2583 2584 2585 2586\n",
       "  * power               (power) int64 0 1 2 3 4\n",
       "Data variables:\n",
       "    flux                (index, freq) float64 0.009533 0.01227 ... 1.627 1.508\n",
       "    polarized_flux      (index, freq) float64 0.000209 0.0004197 ... 0.4463\n",
       "    fluxnorm            (index, freq) float64 0.04609 0.05934 ... 0.04097\n",
       "    logpolycoefflux     (index, power) float64 7.21 -6.782 ... -580.4 26.14\n",
       "    logpolycoefnorm     (index, power) float64 34.86 -32.79 ... -15.77 0.7105\n",
       "    logpolycoefpolflux  (index, power) float64 -3.959 3.659 ... 40.85 -1.996</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a45aabe4-6dff-4276-a631-69aa35cad11e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a45aabe4-6dff-4276-a631-69aa35cad11e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>freq</span>: 13</li><li><span class='xr-has-index'>index</span>: 2587</li><li><span class='xr-has-index'>power</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fd615667-49be-4403-b4f9-28d0ea8b019d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fd615667-49be-4403-b4f9-28d0ea8b019d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>freq</span></div><div class='xr-var-dims'>(freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.7 24.5 44.0 ... 857.0 906.0</div><input id='attrs-c0ca6221-5ca6-4a0e-b962-19f56a666bb4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0ca6221-5ca6-4a0e-b962-19f56a666bb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8870f22c-1e2e-4b89-a956-df5febcc9f00' class='xr-var-data-in' type='checkbox'><label for='data-8870f22c-1e2e-4b89-a956-df5febcc9f00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 18.7,  24.5,  44. ,  70. , 100. , 143. , 217. , 353. , 545. , 643. ,\n",
       "       729. , 857. , 906. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 2583 2584 2585 2586</div><input id='attrs-b98d7be1-da27-42fb-8204-af0372e727e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b98d7be1-da27-42fb-8204-af0372e727e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68995b13-7f2c-44a6-a3b9-6c44f7f40a2c' class='xr-var-data-in' type='checkbox'><label for='data-68995b13-7f2c-44a6-a3b9-6c44f7f40a2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 2584, 2585, 2586])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>power</span></div><div class='xr-var-dims'>(power)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-0254ddf5-49bf-4a49-a622-33e9b12c4181' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0254ddf5-49bf-4a49-a622-33e9b12c4181' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f01f5932-c1fc-48bd-8b30-c26c407017a4' class='xr-var-data-in' type='checkbox'><label for='data-f01f5932-c1fc-48bd-8b30-c26c407017a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5274959a-6731-43d0-8f56-081455f719e4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5274959a-6731-43d0-8f56-081455f719e4' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>flux</span></div><div class='xr-var-dims'>(index, freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.009533 0.01227 ... 1.627 1.508</div><input id='attrs-2c704d22-2c78-4727-b613-ede1b8202053' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c704d22-2c78-4727-b613-ede1b8202053' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d34add2-4122-4ae0-bc2a-886d0085fa07' class='xr-var-data-in' type='checkbox'><label for='data-7d34add2-4122-4ae0-bc2a-886d0085fa07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[9.53296665e-03, 1.22731710e-02, 3.52343917e-02, ...,\n",
       "        1.65953088e+00, 1.95570362e+00, 2.06929731e+00],\n",
       "       [1.26502942e-02, 1.54346246e-02, 3.83479334e-02, ...,\n",
       "        1.00082076e+00, 1.14858925e+00, 1.20428038e+00],\n",
       "       [1.54469153e-02, 1.79893449e-02, 3.94336283e-02, ...,\n",
       "        6.16975665e-01, 6.91993356e-01, 7.19839036e-01],\n",
       "       ...,\n",
       "       [6.54059143e+01, 4.68565788e+01, 2.77972107e+01, ...,\n",
       "        2.08714557e+00, 1.84204388e+00, 1.76460385e+00],\n",
       "       [1.33397018e+02, 1.02788383e+02, 7.41813278e+01, ...,\n",
       "        1.24044895e+01, 1.13484068e+01, 1.10064850e+01],\n",
       "       [1.11893921e+03, 6.59359802e+02, 2.31286041e+02, ...,\n",
       "        2.02974296e+00, 1.62682843e+00, 1.50765407e+00]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>polarized_flux</span></div><div class='xr-var-dims'>(index, freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.000209 0.0004197 ... 0.4463</div><input id='attrs-af97a2b4-29f5-4f31-9c57-4e7a5cee2c64' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af97a2b4-29f5-4f31-9c57-4e7a5cee2c64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07e9eb82-be0e-4af8-bcff-50ddef3ec92c' class='xr-var-data-in' type='checkbox'><label for='data-07e9eb82-be0e-4af8-bcff-50ddef3ec92c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[2.09032238e-04, 4.19746910e-04, 8.50656244e-04, ...,\n",
       "        2.80669611e-02, 4.83805351e-02, 1.06494231e-02],\n",
       "       [4.54504247e-04, 1.50887718e-05, 1.15917868e-03, ...,\n",
       "        6.64930139e-03, 1.56093715e-02, 1.58509389e-01],\n",
       "       [2.47256685e-04, 7.32700719e-05, 8.71646043e-04, ...,\n",
       "        3.88313900e-03, 1.35359634e-02, 2.01009363e-02],\n",
       "       ...,\n",
       "       [1.22437552e-01, 1.49131942e+00, 8.76178622e-01, ...,\n",
       "        4.46697995e-02, 8.82707760e-02, 1.81531653e-01],\n",
       "       [2.65626907e+00, 2.97604179e+00, 2.06295834e+01, ...,\n",
       "        6.23656869e-01, 1.55271769e-01, 4.41605270e-01],\n",
       "       [1.88864768e+00, 8.98794460e+00, 1.72133484e+01, ...,\n",
       "        4.70941141e-02, 7.98787270e-03, 4.46305782e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fluxnorm</span></div><div class='xr-var-dims'>(index, freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04609 0.05934 ... 0.04421 0.04097</div><input id='attrs-5570c41e-d585-4d63-9fdf-b250c2711663' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5570c41e-d585-4d63-9fdf-b250c2711663' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a6dd688-a0eb-4933-a9ac-d6e03bcdf2af' class='xr-var-data-in' type='checkbox'><label for='data-9a6dd688-a0eb-4933-a9ac-d6e03bcdf2af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.04609111,  0.05933977,  0.17035539, ...,  8.02369561,\n",
       "         9.45566649, 10.00488269],\n",
       "       [ 0.07201749,  0.08786854,  0.21831285, ...,  5.69762198,\n",
       "         6.53886057,  6.85590732],\n",
       "       [ 0.10602616,  0.12347715,  0.27066867, ...,  4.23486223,\n",
       "         4.74977652,  4.94090662],\n",
       "       ...,\n",
       "       [ 6.00171432,  4.29960812,  2.55070079, ...,  0.19151864,\n",
       "         0.16902785,  0.16192187],\n",
       "       [ 3.27655575,  2.52473311,  1.82207413, ...,  0.30468448,\n",
       "         0.27874452,  0.27034608],\n",
       "       [30.40802202, 17.91860293,  6.28537366, ...,  0.0551598 ,\n",
       "         0.0442103 ,  0.04097164]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.21 -6.782 2.351 ... -580.4 26.14</div><input id='attrs-322b3436-31da-4630-b97e-5e2fd27279bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-322b3436-31da-4630-b97e-5e2fd27279bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d967ce9-761c-493a-ab79-72c97696d1fe' class='xr-var-data-in' type='checkbox'><label for='data-5d967ce9-761c-493a-ab79-72c97696d1fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 7.21009379e+00, -6.78216434e+00,  2.35140055e+00,\n",
       "        -3.61168594e-01,  2.14158216e-02],\n",
       "       [ 4.11706083e+00, -3.78195493e+00,  1.26968227e+00,\n",
       "        -1.87266210e-01,  1.07418896e-02],\n",
       "       [ 2.70419720e+00, -2.44622907e+00,  8.01376309e-01,\n",
       "        -1.13598951e-01,  6.22500143e-03],\n",
       "       ...,\n",
       "       [ 6.65702855e+02, -4.19460501e+02,  1.01946013e+02,\n",
       "        -1.12183430e+01,  4.68620629e-01],\n",
       "       [ 8.72594549e+02, -4.93835884e+02,  1.13773940e+02,\n",
       "        -1.23353675e+01,  5.21350605e-01],\n",
       "       [ 2.39935993e+04, -1.75578029e+04,  4.80132734e+03,\n",
       "        -5.80425328e+02,  2.61441573e+01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefnorm</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.86 -32.79 ... -15.77 0.7105</div><input id='attrs-be252194-ba3a-4758-b420-123d90918c98' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be252194-ba3a-4758-b420-123d90918c98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f10ca78e-ac32-4e85-91a2-e1b2eec0acf8' class='xr-var-data-in' type='checkbox'><label for='data-f10ca78e-ac32-4e85-91a2-e1b2eec0acf8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.48601644e+01, -3.27911662e+01,  1.13688153e+01,\n",
       "        -1.74621867e+00,  1.03543647e-01],\n",
       "       [ 2.34381718e+01, -2.15304364e+01,  7.22822353e+00,\n",
       "        -1.06609521e+00,  6.11529406e-02],\n",
       "       [ 1.85613460e+01, -1.67906780e+01,  5.50056893e+00,\n",
       "        -7.79732139e-01,  4.27278049e-02],\n",
       "       ...,\n",
       "       [ 6.10856484e+01, -3.84901877e+01,  9.35469022e+00,\n",
       "        -1.02940934e+00,  4.30012444e-02],\n",
       "       [ 2.14329706e+01, -1.21297440e+01,  2.79454319e+00,\n",
       "        -3.02983633e-01,  1.28054869e-02],\n",
       "       [ 6.52043826e+02, -4.77146226e+02,  1.30479588e+02,\n",
       "        -1.57734812e+01,  7.10486424e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefpolflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.959 3.659 ... 40.85 -1.996</div><input id='attrs-bf4c99ae-7f76-4758-802e-bcd5c3500d4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf4c99ae-7f76-4758-802e-bcd5c3500d4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94933e81-6877-46b3-a241-b080709ae44f' class='xr-var-data-in' type='checkbox'><label for='data-94933e81-6877-46b3-a241-b080709ae44f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-3.95903957e+00,  3.65860103e+00, -1.23167717e+00,\n",
       "         1.79032180e-01, -9.46426232e-03],\n",
       "       [ 4.97689942e+00, -4.64639813e+00,  1.58118244e+00,\n",
       "        -2.32581602e-01,  1.24985185e-02],\n",
       "       [ 7.17239802e-01, -6.77859626e-01,  2.30615836e-01,\n",
       "        -3.33932585e-02,  1.75182088e-03],\n",
       "       ...,\n",
       "       [-8.51219132e+01,  7.45685716e+01, -2.33713634e+01,\n",
       "         3.14195869e+00, -1.53946001e-01],\n",
       "       [-1.01911300e+03,  8.77738494e+02, -2.71679313e+02,\n",
       "         3.61777219e+01, -1.75996613e+00],\n",
       "       [-1.12741047e+03,  9.78764313e+02, -3.05045263e+02,\n",
       "         4.08467575e+01, -1.99578923e+00]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95ddb3b3-fd83-4a92-baed-43ce7195ac1d' class='xr-section-summary-in' type='checkbox'  ><label for='section-95ddb3b3-fd83-4a92-baed-43ce7195ac1d' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c5e2aceb-a67c-4f42-a38b-e58860580265' class='xr-index-data-in' type='checkbox'/><label for='index-c5e2aceb-a67c-4f42-a38b-e58860580265' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 18.7,  24.5,  44.0,  70.0, 100.0, 143.0, 217.0, 353.0, 545.0, 643.0,\n",
       "       729.0, 857.0, 906.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;freq&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>index</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d3a55722-877d-4d6d-a493-27032148fdea' class='xr-index-data-in' type='checkbox'/><label for='index-d3a55722-877d-4d6d-a493-27032148fdea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "       ...\n",
       "       2577, 2578, 2579, 2580, 2581, 2582, 2583, 2584, 2585, 2586],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;index&#x27;, length=2587))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>power</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-47ba653a-bd8c-4339-9c26-7a607a9512e5' class='xr-index-data-in' type='checkbox'/><label for='index-47ba653a-bd8c-4339-9c26-7a607a9512e5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;power&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-42a8b35b-5138-414d-8351-f089d43661d3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-42a8b35b-5138-414d-8351-f089d43661d3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (freq: 13, index: 2587, power: 5)\n",
       "Coordinates:\n",
       "  * freq                (freq) float64 18.7 24.5 44.0 70.0 ... 729.0 857.0 906.0\n",
       "  * index               (index) int64 0 1 2 3 4 5 ... 2582 2583 2584 2585 2586\n",
       "  * power               (power) int64 0 1 2 3 4\n",
       "Data variables:\n",
       "    flux                (index, freq) float64 0.009533 0.01227 ... 1.627 1.508\n",
       "    polarized_flux      (index, freq) float64 0.000209 0.0004197 ... 0.4463\n",
       "    fluxnorm            (index, freq) float64 0.04609 0.05934 ... 0.04097\n",
       "    logpolycoefflux     (index, power) float64 7.21 -6.782 ... -580.4 26.14\n",
       "    logpolycoefnorm     (index, power) float64 34.86 -32.79 ... -15.77 0.7105\n",
       "    logpolycoefpolflux  (index, power) float64 -3.959 3.659 ... 40.85 -1.996"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sources_xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "70a01735",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_catalog = sources_xr[[\"logpolycoefflux\",\"logpolycoefpolflux\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "45961c76",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_catalog[\"index\"] = all_indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ed6fd91a",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_catalog.logpolycoefflux.attrs[\"units\"] = \"Jy\"\n",
    "output_catalog.logpolycoefpolflux.attrs[\"units\"] = \"Jy\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5ea9a33b",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "  display: inline-block;\n",
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       "\n",
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       "\n",
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       ".xr-var-attrs,\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  stroke-width: 0;\n",
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       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:             (index: 2587, power: 5)\n",
       "Coordinates:\n",
       "  * index               (index) int64 4149281 6364699 ... 281707775 281749853\n",
       "  * power               (power) int64 0 1 2 3 4\n",
       "Data variables:\n",
       "    logpolycoefflux     (index, power) float64 7.21 -6.782 ... -580.4 26.14\n",
       "    logpolycoefpolflux  (index, power) float64 -3.959 3.659 ... 40.85 -1.996</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8af55d47-bcbb-48b8-a600-f88d4bf4f08c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8af55d47-bcbb-48b8-a600-f88d4bf4f08c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>index</span>: 2587</li><li><span class='xr-has-index'>power</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a0dd42d2-6b38-49f1-98fb-b1fb1c04c670' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a0dd42d2-6b38-49f1-98fb-b1fb1c04c670' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4149281 6364699 ... 281749853</div><input id='attrs-00947963-b1e6-4d64-954f-f89bfef7d9af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00947963-b1e6-4d64-954f-f89bfef7d9af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e35a2d8-7bd6-4562-8c5c-c9705a41c54b' class='xr-var-data-in' type='checkbox'><label for='data-8e35a2d8-7bd6-4562-8c5c-c9705a41c54b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  4149281,   6364699,   9532007, ..., 281704976, 281707775, 281749853])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>power</span></div><div class='xr-var-dims'>(power)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-d0b328e5-e491-4328-b7e0-0f8ae5357c73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0b328e5-e491-4328-b7e0-0f8ae5357c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ac3d2f2-1705-4a2d-89df-531b21a1ddce' class='xr-var-data-in' type='checkbox'><label for='data-9ac3d2f2-1705-4a2d-89df-531b21a1ddce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7fc20fe5-ba78-4858-abdd-c005608ed79e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7fc20fe5-ba78-4858-abdd-c005608ed79e' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.21 -6.782 2.351 ... -580.4 26.14</div><input id='attrs-68f5a4e0-92e6-4176-b30d-8c70b8fb6d90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68f5a4e0-92e6-4176-b30d-8c70b8fb6d90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0865a3cb-91c2-4f1a-aeac-57d9bb93f926' class='xr-var-data-in' type='checkbox'><label for='data-0865a3cb-91c2-4f1a-aeac-57d9bb93f926' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>array([[ 7.21009379e+00, -6.78216434e+00,  2.35140055e+00,\n",
       "        -3.61168594e-01,  2.14158216e-02],\n",
       "       [ 4.11706083e+00, -3.78195493e+00,  1.26968227e+00,\n",
       "        -1.87266210e-01,  1.07418896e-02],\n",
       "       [ 2.70419720e+00, -2.44622907e+00,  8.01376309e-01,\n",
       "        -1.13598951e-01,  6.22500143e-03],\n",
       "       ...,\n",
       "       [ 6.65702855e+02, -4.19460501e+02,  1.01946013e+02,\n",
       "        -1.12183430e+01,  4.68620629e-01],\n",
       "       [ 8.72594549e+02, -4.93835884e+02,  1.13773940e+02,\n",
       "        -1.23353675e+01,  5.21350605e-01],\n",
       "       [ 2.39935993e+04, -1.75578029e+04,  4.80132734e+03,\n",
       "        -5.80425328e+02,  2.61441573e+01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>logpolycoefpolflux</span></div><div class='xr-var-dims'>(index, power)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.959 3.659 ... 40.85 -1.996</div><input id='attrs-c2a7ab58-57cd-49a8-b15e-8f0d38ad3620' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2a7ab58-57cd-49a8-b15e-8f0d38ad3620' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315f0aba-8549-4e36-bb56-95722b011fab' class='xr-var-data-in' type='checkbox'><label for='data-315f0aba-8549-4e36-bb56-95722b011fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Jy</dd></dl></div><div class='xr-var-data'><pre>array([[-3.95903957e+00,  3.65860103e+00, -1.23167717e+00,\n",
       "         1.79032180e-01, -9.46426232e-03],\n",
       "       [ 4.97689942e+00, -4.64639813e+00,  1.58118244e+00,\n",
       "        -2.32581602e-01,  1.24985185e-02],\n",
       "       [ 7.17239802e-01, -6.77859626e-01,  2.30615836e-01,\n",
       "        -3.33932585e-02,  1.75182088e-03],\n",
       "       ...,\n",
       "       [-8.51219132e+01,  7.45685716e+01, -2.33713634e+01,\n",
       "         3.14195869e+00, -1.53946001e-01],\n",
       "       [-1.01911300e+03,  8.77738494e+02, -2.71679313e+02,\n",
       "         3.61777219e+01, -1.75996613e+00],\n",
       "       [-1.12741047e+03,  9.78764313e+02, -3.05045263e+02,\n",
       "         4.08467575e+01, -1.99578923e+00]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc4db450-c6d6-464d-9075-53a894421c73' class='xr-section-summary-in' type='checkbox'  ><label for='section-cc4db450-c6d6-464d-9075-53a894421c73' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>index</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c46b2b46-2399-493d-9cae-50974cf017b3' class='xr-index-data-in' type='checkbox'/><label for='index-c46b2b46-2399-493d-9cae-50974cf017b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  4149281,   6364699,   9532007,  13064907,  14325531,  21636411,\n",
       "        21860320,  25717653,  25721926,  25729793,\n",
       "       ...\n",
       "       281569233, 281572464, 281626298, 281633199, 281669277, 281670629,\n",
       "       281701280, 281704976, 281707775, 281749853],\n",
       "      dtype=&#x27;int64&#x27;, name=&#x27;index&#x27;, length=2587))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>power</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7881666e-f9f9-4d2e-be9e-747f846b5b35' class='xr-index-data-in' type='checkbox'/><label for='index-7881666e-f9f9-4d2e-be9e-747f846b5b35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;power&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-64d3a52b-8175-4b23-b737-f2099ae349e4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-64d3a52b-8175-4b23-b737-f2099ae349e4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:             (index: 2587, power: 5)\n",
       "Coordinates:\n",
       "  * index               (index) int64 4149281 6364699 ... 281707775 281749853\n",
       "  * power               (power) int64 0 1 2 3 4\n",
       "Data variables:\n",
       "    logpolycoefflux     (index, power) float64 7.21 -6.782 ... -580.4 26.14\n",
       "    logpolycoefpolflux  (index, power) float64 -3.959 3.659 ... 40.85 -1.996"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c63ccaec",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_filename = \"websky_high_flux_catalog.h5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a4d323e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_catalog.to_netcdf(output_filename, format=\"NETCDF4\") # requires netcdf4 package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "75634cd0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-rw-rw---- 1 zonca sobs 231K Jun 18 13:35 websky_high_flux_catalog.h5\r\n"
     ]
    }
   ],
   "source": [
    "%ls -lah $output_filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "21904125",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "72f8f94f",
   "metadata": {},
   "outputs": [
    {
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       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",