examples/boulder_watershed_viewer_demo.ipynb

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    "## Boulder Watershed Demo\n",
    "\n",
    "Process ATL03 data from the Boulder Watershed region and produce a photon count dataset.\n",
    "\n",
    "### What is demonstrated\n",
    "\n",
    "* The `icesat2.atl03vp` API is used to perform a SlideRule parallel processing request of the Boulder Watershed region\n",
    "* The `matplotlib` and `geopandas` packages are used to plot the data returned by SlideRule\n",
    "\n",
    "### Points of interest\n",
    "\n",
    "This is a simple notebook showing how a region of interest can be processed by SlideRule and the results analyzed using pandas DataFrames and Matplotlib."
   ]
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   "source": [
    "import logging\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "from sliderule import icesat2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SlideRule Configuration"
   ]
  },
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    "tags": []
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   "source": [
    "# Configure ICESat-2 API\n",
    "icesat2.init(\"slideruleearth.io\")\n",
    "# Configure Region of Interest\n",
    "region = [ {\"lon\":-105.82971551223244, \"lat\": 39.81983728534918},\n",
    "           {\"lon\":-105.30742121965137, \"lat\": 39.81983728534918},\n",
    "           {\"lon\":-105.30742121965137, \"lat\": 40.164048017973755},\n",
    "           {\"lon\":-105.82971551223244, \"lat\": 40.164048017973755},\n",
    "           {\"lon\":-105.82971551223244, \"lat\": 39.81983728534918} ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Execute ATL03 Viewer Algorithm using SlideRule"
   ]
  },
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    "tags": []
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    "%%time\n",
    "\n",
    "# Build ATL03 Viewer Request\n",
    "parms = {\n",
    "    \"poly\": region,\n",
    "    \"track\": 1\n",
    "}\n",
    "\n",
    "# Request ATL03 Viewer Data\n",
    "gdf = icesat2.atl03vp(parms)\n",
    "\n",
    "# Display Statistics\n",
    "print(\"Reference Ground Tracks: {}\".format(gdf[\"rgt\"].unique()))\n",
    "print(\"Cycles: {}\".format(gdf[\"cycle\"].unique()))\n",
    "print(\"Received {} segments\".format(len(gdf)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "tags": []
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   "outputs": [],
   "source": [
    "# Calculate Extent\n",
    "lons = [p[\"lon\"] for p in region]\n",
    "lats = [p[\"lat\"] for p in region]\n",
    "lon_margin = (max(lons) - min(lons)) * 0.1\n",
    "lat_margin = (max(lats) - min(lats)) * 0.1\n",
    "\n",
    "# Create Plot\n",
    "fig,(ax1) = plt.subplots(num=None, ncols=1, figsize=(12, 6))\n",
    "box_lon = [e[\"lon\"] for e in region]\n",
    "box_lat = [e[\"lat\"] for e in region]\n",
    "\n",
    "# Plot SlideRule Ground Tracks\n",
    "ax1.set_title(\"SlideRule Zoomed Ground Tracks\")\n",
    "gdf.plot(ax=ax1, column=gdf[\"segment_ph_cnt\"], cmap='winter_r', s=1.0, zorder=3)\n",
    "ax1.plot(box_lon, box_lat, linewidth=1.5, color='r', zorder=2)\n",
    "ax1.set_xlim(min(lons) - lon_margin, max(lons) + lon_margin)\n",
    "ax1.set_ylim(min(lats) - lat_margin, max(lats) + lat_margin)\n",
    "ax1.set_aspect('equal', adjustable='box')\n",
    "\n",
    "# Show Plot\n",
    "plt.tight_layout()"
   ]
  }
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