03_EMIT_Interactive_Points.ipynb

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    "import csv\n",
    "\n",
    "import holoviews as hv\n",
    "import hvplot.xarray  # noqa: F401\n",
    "import numpy as np\n",
    "from fsspec.implementations.http import HTTPFileSystem\n",
    "\n",
    "from emit_tools import emit_xarray\n",
    "from utils import get_earthdata_token, get_rgb_dataset, load_emit_granule"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interactive Visualisation of Specra at Points\n",
    "\n",
    "This notebook allows the interactive querying of points in a scene to extract a plot\n",
    "of the specra at those points.\n",
    "\n",
    "## First load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%%time\n",
    "# Loading data can take around 3-4 minutes on a 100 Mbps connection\n",
    "\n",
    "# See README.md for instructions on how to get an Earthdata token\n",
    "token = get_earthdata_token()\n",
    "\n",
    "# Refer to the README.md for instructions on how to find different granule IDs\n",
    "granule = \"EMIT_L2A_RFL_001_20230316T045211_2307503_006\" # Canberra\n",
    "\n",
    "ds = load_emit_granule(granule, token)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "tags": []
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   "source": [
    "# Clean up empty bands.\n",
    "ds = ds.fillna(np.nan).where(ds.reflectance!=-0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "tags": []
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   "source": [
    "%%capture --no-stdout\n",
    "# Create an RGB dataset for rendering\n",
    "\n",
    "# Select wavelengths to be displayed\n",
    "r = 2100\n",
    "g = 950\n",
    "b = 490\n",
    "\n",
    "# Select brightness - range between 0-1, higher values 'brighten' the whole scene\n",
    "brightness = 0.4\n",
    "\n",
    "## End configuration area ##\n",
    "\n",
    "# Get data structured for rendering\n",
    "ds_rgb = get_rgb_dataset(ds, [r, g, b], brightness)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the plots\n",
    "\n",
    "In the plot below, select the \"Point Draw Tool\" from the control panel\n",
    "and digitise points. You can add up to 20 points. You can delete a point\n",
    "by clicking it and pressing the backspace/delete key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
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   "source": [
    "from holoviews import opts\n",
    "from holoviews.plotting.links import DataLink\n",
    "\n",
    "POINT_LIMIT = 20\n",
    "color_cycle = hv.Cycle('Category20')\n",
    "colors = [color_cycle[i] for i in range(5)]\n",
    "\n",
    "# RGB image/map\n",
    "map = ds_rgb.hvplot.rgb(\n",
    "    x=\"longitude\", y=\"latitude\", bands=\"bands\", aspect=\"equal\", frame_width=600\n",
    ")\n",
    "\n",
    "# Set up a holoviews points array to enable plotting of the clicked points\n",
    "xmid = ds.longitude.values[int(len(ds.longitude) / 2)]\n",
    "ymid = ds.latitude.values[int(len(ds.latitude) / 2)]\n",
    "\n",
    "first_point = ([xmid], [ymid], [0])\n",
    "points = hv.Points(first_point, vdims='id')\n",
    "points_stream = hv.streams.PointDraw(\n",
    "    data=points.columns(),\n",
    "    source=points,\n",
    "    drag=True,\n",
    "    num_objects=POINT_LIMIT,\n",
    "    styles={'fill_color': color_cycle.values[0:POINT_LIMIT], 'line_color': 'gray'}\n",
    ")\n",
    "\n",
    "clickxy = hv.streams.Tap(source=map, x=147.5, y=-42.7)\n",
    "\n",
    "# Function to build spectral plot of clicked location to show on hover stream plot\n",
    "def click_spectra(data):\n",
    "    coordinates = []\n",
    "    if data is None or not any(len(d) for d in data.values()):\n",
    "        coordinates.append(clicked_points[0][0], clicked_points[1][0])\n",
    "    else:\n",
    "        coordinates = [c for c in zip(data['x'], data['y'])]\n",
    "    \n",
    "    plots = []\n",
    "    for i, coords in enumerate(coordinates):\n",
    "        x, y = coords\n",
    "        data = ds.sel(longitude=x, latitude=y, method=\"nearest\")\n",
    "        plots.append(\n",
    "            data.hvplot.line(\n",
    "                y=\"reflectance\",\n",
    "                x=\"wavelengths\",\n",
    "                color=color_cycle,\n",
    "                label=f\"{i}\"\n",
    "            )\n",
    "        )\n",
    "        points_stream.data[\"id\"][i] = i\n",
    "    return hv.Overlay(plots)\n",
    "\n",
    "# Define the Dynamic Maps\n",
    "click_dmap = hv.DynamicMap(click_spectra, streams=[points_stream])\n",
    "# label_dmap = hv.DynamicMap(update_labels, streams=[points_stream])\n",
    "\n",
    "# Plot the Map and Dynamic Map side by side\n",
    "hv.Layout(map * points + click_dmap).cols(1).opts(\n",
    "    opts.Points(active_tools=['point_draw'], size=10, tools=['hover'], color='white', line_color='gray'),\n",
    "    opts.Labels(xoffset=0.01, yoffset=0.01, bgcolor='gray', text_color='black'),\n",
    "    opts.Overlay(show_legend=False, show_title=False, frame_width=600)\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write out points to a CSV on disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "data = points_stream.data\n",
    "wavelengths = ds.wavelengths.values\n",
    "\n",
    "rows = [[\"id\", \"x\", \"y\"] + [str(i) for i in wavelengths]]\n",
    "\n",
    "for p in zip(data['x'], data['y'], data['id']):\n",
    "    x, y, i = p\n",
    "    spectra = ds.sel(longitude=x, latitude=y, method=\"nearest\").reflectance.values\n",
    "    row = [i, x, y] + list(spectra)\n",
    "    rows.append(row)\n",
    "    \n",
    "len(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "with open('data.csv', 'w', newline='') as f:\n",
    "    writer = csv.writer(f)\n",
    "    writer.writerows(rows)"
   ]
  }
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