{
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   "cell_type": "markdown",
   "id": "fe5f8c50-64ec-4f30-929d-fd457b8a2ec1",
   "metadata": {},
   "source": [
    "# Cubes Visualization with Lexcube"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "fee89449-12da-494c-bb02-684bf14cad01",
   "metadata": {},
   "source": [
    "This tutorial shows how to visualize different cubes using Lexcube:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6b60e78-9e6c-40d8-bbea-dccc66376347",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cubo\n",
    "import lexcube"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b75eaf5f-db3c-4c0b-a57e-4c0e930e3201",
   "metadata": {},
   "source": [
    "If you are in Google Colab you have to run the following cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a250d0c-b500-4cb3-9cf1-b63327789e26",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from google.colab import output\n",
    "# output.enable_custom_widget_manager()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c782f3e-9afa-4463-9d08-39acab77da92",
   "metadata": {},
   "source": [
    "## Sentinel-2\n",
    "\n",
    "An example over crop fields in Colombia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ead0866-3b85-4b04-97c0-b38742df9b80",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/net/home/dmontero/.conda/envs/cube/lib/python3.11/site-packages/stackstac/prepare.py:408: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
      "  times = pd.to_datetime(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d0fb535457894a53a80e3f64cf865024",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Cube3DWidget(api_metadata={'/api': {'status': 'ok', 'api_version': 5}, '/api/datasets': [{'id': 'default', 'sh…"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s2 = cubo.create(\n",
    "    lat=4.31,\n",
    "    lon=-76.2,\n",
    "    collection=\"sentinel-2-l2a\",\n",
    "    bands=[\"B02\",\"B03\",\"B04\"],\n",
    "    start_date=\"2019-01-01\",\n",
    "    end_date=\"2021-12-31\",\n",
    "    edge_size=64,\n",
    "    resolution=10,\n",
    "    query={\"eo:cloud_cover\": {\"lt\": 40}}\n",
    ")\n",
    "\n",
    "ws2 = lexcube.Cube3DWidget(s2.sel(band=\"B04\"), cmap=\"viridis\", vmin=0, vmax=2000)\n",
    "ws2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c4a1f25-7002-4dbf-bf6e-d9bbe3874b43",
   "metadata": {},
   "source": [
    "## Sentinel-1\n",
    "\n",
    "A C-band cube over the Panama Canal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6ac0c7bf-7a46-4fd6-911b-c629625222f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/net/home/dmontero/.conda/envs/cube/lib/python3.11/site-packages/stackstac/prepare.py:408: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
      "  times = pd.to_datetime(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "70cc3db0f13c4c3cbd90e6d9767379e4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Cube3DWidget(api_metadata={'/api': {'status': 'ok', 'api_version': 5}, '/api/datasets': [{'id': 'default', 'sh…"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1 = cubo.create(\n",
    "    lat=8.93548,\n",
    "    lon=-79.56005,\n",
    "    collection=\"sentinel-1-rtc\",\n",
    "    bands=[\"vv\",\"vh\"],\n",
    "    start_date=\"2021-01-01\",\n",
    "    end_date=\"2021-12-31\",\n",
    "    edge_size=256,\n",
    "    resolution=10,\n",
    ")\n",
    "\n",
    "ws1 = lexcube.Cube3DWidget(s1.sel(band=\"vv\"), cmap=\"Greys_r\", vmin=0, vmax=0.6)\n",
    "ws1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "489fe636-b6a2-4882-8165-e4457d86aa7c",
   "metadata": {},
   "source": [
    "## MODIS Gross Primary Productivity (GPP)\n",
    "\n",
    "GPP over the Hainich National Park in Germany."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cfc12730-c388-42d4-9db1-b182027ba15a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/net/home/dmontero/.conda/envs/cube/lib/python3.11/site-packages/stackstac/prepare.py:408: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
      "  times = pd.to_datetime(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f2d762d0d98440d8b9cf8dce35b01e8b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Cube3DWidget(api_metadata={'/api': {'status': 'ok', 'api_version': 5}, '/api/datasets': [{'id': 'default', 'sh…"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpp = cubo.create(\n",
    "    lat=51.0825008,\n",
    "    lon=10.437455,\n",
    "    collection=\"modis-17A2H-061\",\n",
    "    bands=[\"Gpp_500m\"], \n",
    "    start_date=\"2022-01-01\", \n",
    "    end_date=\"2022-12-31\",\n",
    "    edge_size=64, \n",
    "    resolution=500,\n",
    ").where(lambda x: x[\"platform\"] == \"terra\",drop=True)\n",
    "\n",
    "wgpp = lexcube.Cube3DWidget(gpp.sel(band=\"Gpp_500m\"), cmap=\"YlGn\", vmin=0, vmax=0.1)\n",
    "wgpp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09c87326-d55c-45c1-ac18-5ca576b6a2c3",
   "metadata": {},
   "source": [
    "## MODIS Land Surface Temperature (LST)\n",
    "\n",
    "LST over Budapest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bac80211-b8de-426e-b9f7-87d9d040c633",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/net/home/dmontero/.conda/envs/cube/lib/python3.11/site-packages/stackstac/prepare.py:408: UserWarning: The argument 'infer_datetime_format' is deprecated and will be removed in a future version. A strict version of it is now the default, see https://pandas.pydata.org/pdeps/0004-consistent-to-datetime-parsing.html. You can safely remove this argument.\n",
      "  times = pd.to_datetime(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9edd9a7db6b346d48cd2bff345fc3872",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Cube3DWidget(api_metadata={'/api': {'status': 'ok', 'api_version': 5}, '/api/datasets': [{'id': 'default', 'sh…"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lst = cubo.create(\n",
    "    lat=47.49744,\n",
    "    lon=19.048363,\n",
    "    collection=\"modis-11A2-061\",\n",
    "    bands=[\"LST_Day_1km\"], \n",
    "    start_date=\"2022-01-01\", \n",
    "    end_date=\"2022-12-31\",\n",
    "    edge_size=128, \n",
    "    resolution=500,\n",
    ").where(lambda x: x[\"platform\"] == \"terra\",drop=True)\n",
    "\n",
    "wlst = lexcube.Cube3DWidget(lst.sel(band=\"LST_Day_1km\"), cmap=\"inferno\", vmin=270, vmax=310)\n",
    "wlst"
   ]
  }
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