diff --git "a/make_multipic_conv_train.ipynb" "b/make_multipic_conv_train.ipynb"
new file mode 100644--- /dev/null
+++ "b/make_multipic_conv_train.ipynb"
@@ -0,0 +1,3244 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0dd2c5d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "import geopandas as gpd\n",
+    "from shapely.geometry import box\n",
+    "import rioxarray as rxr # Make sure you have rioxarray installed (pip install rioxarray)\n",
+    "import numpy as np\n",
+    "import ibis\n",
+    "import pandas as pd\n",
+    "from rasterio.enums import Resampling\n",
+    "from pathlib import Path\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "ibis.options.interactive = True"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7cc89208-69c2-455b-97c3-1e2d470d326c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10.5.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import ibis\n",
+    "print(ibis.__version__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d615f835",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<duckdb.duckdb.DuckDBPyConnection at 0x23e780de930>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "con = ibis.duckdb.connect()\n",
+    "con.raw_sql('INSTALL spatial;')\n",
+    "con.raw_sql('LOAD spatial;')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "700cf1f9",
+   "metadata": {},
+   "source": [
+    "- The .rio accessor: https://corteva.github.io/rioxarray/html/rioxarray.html#rioxarray-rio-accessors\n",
+    "\n",
+    "- Affine( pixel_width, 0, top_left_x_coord,\n",
+    "          0, -pixel_height, top_left_y_coord)\n",
+    "\n",
+    "- Rasterio Affine Docs (https://affine.readthedocs.io/en/latest/)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "cf514138",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Variable with lowest resolution: temp\n",
+      "target resolution:(2605.1644663456045, -2605.1644663456045)\n",
+      "target shape:(1768, 2123)\n",
+      "target crs:EPSG:3031\n",
+      "target bounds:(-2732000.0, -2233000.0, 2800025.0, 2373000.0)\n",
+      "Resampling images to the same format...\n",
+      "Done\n"
+     ]
+    }
+   ],
+   "source": [
+    "from rasterio.transform import from_origin\n",
+    "\n",
+    "filenamez = Path.cwd().parent / 'antarctica_bedmachine_v3_7' / 'BedMachineAntarctica-v3.nc'\n",
+    "sat_imz = rxr.open_rasterio(filenamez)\n",
+    "\n",
+    "filenamesmb = Path.cwd().parent / 'antarctica_mass_balance' / 'smb_antarctica_mean_1979_2021_RACMO23p2_gf.nc'\n",
+    "sat_imsmb = rxr.open_rasterio(filenamesmb)\n",
+    "\n",
+    "filenamev = Path.cwd().parent / 'antarctica_ice_velocity' / 'antarctic_ice_vel_phase_map_v01-001.nc'\n",
+    "sat_imv = rxr.open_rasterio(filenamev)\n",
+    "\n",
+    "filenamet2m = Path.cwd().parent / 'antarctica_temperature' / 'era5land_era5.nc'\n",
+    "sat_imt2m = rxr.open_rasterio(filenamet2m)\n",
+    "\n",
+    "# Pre-process t2m map since it uses a different projection and is a map over the entire world and not just antartica.\n",
+    "sat_imt2m = sat_imt2m.squeeze()\n",
+    "sat_imt2m = sat_imt2m.sel(y=sat_imt2m.y < -60)\n",
+    "sat_imt2m = sat_imt2m.rio.reproject(\"EPSG:3031\",resampling=Resampling.bilinear)\n",
+    "\n",
+    "\n",
+    "res_dict = {\n",
+    "    'VX': sat_imv['VX'].rio.resolution(),\n",
+    "    'VY': sat_imv['VY'].rio.resolution(),\n",
+    "    'surface': sat_imz['surface'].rio.resolution(),\n",
+    "    'smb': sat_imsmb.rio.resolution(),\n",
+    "    'temp': sat_imt2m.rio.resolution()\n",
+    "}\n",
+    "\n",
+    "sat_im_dict = {\n",
+    "    'VX': sat_imv['VX'],\n",
+    "    'VY': sat_imv['VY'],\n",
+    "    'surface': sat_imz['surface'],\n",
+    "    'smb': sat_imsmb,\n",
+    "    'temp': sat_imt2m\n",
+    "}\n",
+    "\n",
+    "# Compute pixel areas (abs values), store in new dict\n",
+    "area_dict = {k: abs(v[0]) * abs(v[1]) for k, v in res_dict.items()}\n",
+    "\n",
+    "# Get the key with the lowest pixel area (lowest resolution)\n",
+    "highest_res_key = max(area_dict, key=area_dict.get)\n",
+    "\n",
+    "print(\"Variable with lowest resolution:\", highest_res_key)\n",
+    "\n",
+    "from rasterio.coords import BoundingBox\n",
+    "\n",
+    "# Get bounds of all rasters\n",
+    "bounds_list = [\n",
+    "    sat_imz.rio.bounds(),\n",
+    "    sat_imsmb.rio.bounds(),\n",
+    "    sat_imv['VX'].rio.bounds(),\n",
+    "    sat_imv['VY'].rio.bounds(),\n",
+    "    sat_imt2m.rio.bounds()\n",
+    "]\n",
+    "\n",
+    "# Compute intersection bounds\n",
+    "minx = max(b[0] for b in bounds_list)\n",
+    "miny = max(b[1] for b in bounds_list)\n",
+    "maxx = min(b[2] for b in bounds_list)\n",
+    "maxy = min(b[3] for b in bounds_list)\n",
+    "\n",
+    "target_res = sat_im_dict[highest_res_key].rio.resolution()\n",
+    "target_crs = 'EPSG:3031'\n",
+    "target_bounds = (minx, miny, maxx, maxy)\n",
+    "\n",
+    "# Example: Define your shared top-left corner and resolution\n",
+    "left, top = minx, maxy  # top-left corner (notice it's from sat_imv)\n",
+    "xres, yres = abs(target_res[0]), abs(target_res[1])\n",
+    "\n",
+    "# Make the transform\n",
+    "transform = from_origin(left, top, xres, yres)\n",
+    "\n",
+    "# Use this fixed transform + shape\n",
+    "target_shape = (\n",
+    "    int((target_bounds[3] - target_bounds[1]) / yres),\n",
+    "    int((target_bounds[2] - target_bounds[0]) / xres)\n",
+    ")\n",
+    "print('target resolution:' + str(target_res))\n",
+    "print('target shape:' + str(target_shape))\n",
+    "print('target crs:' + str(target_crs))\n",
+    "print('target bounds:' + str(target_bounds))\n",
+    "\n",
+    "# Now reproject using this transform + shape instead of dst_bounds\n",
+    "def resample_to_target(src_dataarray, transform, shape, target_crs, resampling=Resampling.bilinear):\n",
+    "    return src_dataarray.rio.reproject(\n",
+    "        dst_crs=target_crs,\n",
+    "        transform=transform,\n",
+    "        shape=shape,\n",
+    "        resolution=None,\n",
+    "        resampling=resampling,\n",
+    "        nodata=src_dataarray.rio.nodata or None\n",
+    "    )\n",
+    "\n",
+    "print('Resampling images to the same format...')\n",
+    "# Resample every picture to the same an preserving as much information as possible with Resampling.cubic instead of .bilinear\n",
+    "sat_imvx  = resample_to_target(sat_imv['VX'], transform, target_shape, target_crs)\n",
+    "sat_imvy  = resample_to_target(sat_imv['VY'], transform, target_shape, target_crs)\n",
+    "sat_imz   = resample_to_target(sat_imz['surface'], transform, target_shape, target_crs)\n",
+    "sat_imsmb = resample_to_target(sat_imsmb, transform, target_shape, target_crs)\n",
+    "sat_imt2m = resample_to_target(sat_imt2m, transform, target_shape, target_crs).fillna(271).expand_dims(dim=\"band\")\n",
+    "print('Done')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "efb1c26c-7fe4-4a0c-9c6e-0aa1bdbadb98",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sat_imv = (sat_imvx**2 + sat_imvy**2)**0.5 #A much more interesting graph to look at so maybe it works better for CNN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "471dfdd9-f924-44c4-80bb-8c1652b2e0f8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "✅ All rasters have identical resolution, transform, bounds, and shape.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pprint import pprint\n",
+    "\n",
+    "# Dictionary of resampled rasters\n",
+    "resampled_images = {\n",
+    "    \"v\": sat_imv,\n",
+    "    \"surface\": sat_imz,\n",
+    "    \"smb\": sat_imsmb,\n",
+    "    \"temp\": sat_imt2m,\n",
+    "}\n",
+    "\n",
+    "# Initialize reference from the first raster\n",
+    "first_key = next(iter(resampled_images))\n",
+    "ref_res = resampled_images[first_key].rio.resolution()\n",
+    "ref_transform = resampled_images[first_key].rio.transform()\n",
+    "ref_bounds = resampled_images[first_key].rio.bounds()\n",
+    "ref_shape = resampled_images[first_key].shape\n",
+    "\n",
+    "# Track inconsistencies\n",
+    "inconsistencies = {\n",
+    "    \"resolution\": [],\n",
+    "    \"transform\": [],\n",
+    "    \"bounds\": [],\n",
+    "    \"shape\": [],\n",
+    "}\n",
+    "\n",
+    "# Compare each raster\n",
+    "for name, img in resampled_images.items():\n",
+    "    res = img.rio.resolution()\n",
+    "    tr = img.rio.transform()\n",
+    "    bounds = img.rio.bounds()\n",
+    "    shape = img.shape\n",
+    "\n",
+    "    if res != ref_res:\n",
+    "        inconsistencies[\"resolution\"].append((name, res))\n",
+    "    if tr != ref_transform:\n",
+    "        inconsistencies[\"transform\"].append((name, tr))\n",
+    "    if bounds != ref_bounds:\n",
+    "        inconsistencies[\"bounds\"].append((name, bounds))\n",
+    "    if shape != ref_shape:\n",
+    "        inconsistencies[\"shape\"].append((name, shape))\n",
+    "\n",
+    "# Report findings\n",
+    "if not any(inconsistencies.values()):\n",
+    "    print(\"✅ All rasters have identical resolution, transform, bounds, and shape.\")\n",
+    "else:\n",
+    "    print(\"❌ Inconsistencies found:\")\n",
+    "    pprint(inconsistencies)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "3ac4d327-47e2-429e-a99c-69df29d4ba9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1, 1768, 2123)\n",
+      "(1768, 2123)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ref_shape)\n",
+    "print(sat_imt2m.rio.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "876d8393-5611-4611-a54d-5b0b1c85b08f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "(function(root) {\n",
+       "  function now() {\n",
+       "    return new Date();\n",
+       "  }\n",
+       "\n",
+       "  const force = true;\n",
+       "  const py_version = '3.7.3'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
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+       "  const Bokeh = root.Bokeh;\n",
+       "\n",
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+       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
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+       "\n",
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+       "      root._bokeh_is_loading = css_urls.length + 0;\n",
+       "    } else {\n",
+       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
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+       "        existing_stylesheets.push(link.href)\n",
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+       "    }\n",
+       "    for (let i = 0; i < css_urls.length; i++) {\n",
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+       "      const escaped = encodeURI(url)\n",
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+       "        continue;\n",
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+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }    var existing_scripts = []\n",
+       "    const scripts = document.getElementsByTagName('script')\n",
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+       "        existing_scripts.push(script.src)\n",
+       "      }\n",
+       "    }\n",
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+       "          on_load();\n",
+       "        }\n",
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+       "      }\n",
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+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
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+       "      }\n",
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+       "      }\n",
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+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    if (!js_urls.length && !js_modules.length) {\n",
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+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  const js_urls = [\"https://cdn.holoviz.org/panel/1.7.0/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.7.3.min.js\", \"https://cdn.holoviz.org/panel/1.7.0/dist/panel.min.js\"];\n",
+       "  const js_modules = [];\n",
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+       "      Bokeh.set_log_level(\"info\");\n",
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+       "function(Bokeh) {} // ensure no trailing comma for IE\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (let i = 0; i < inline_js.length; i++) {\n",
+       "        try {\n",
+       "          inline_js[i].call(root, root.Bokeh);\n",
+       "        } catch(e) {\n",
+       "          if (!reloading) {\n",
+       "            throw e;\n",
+       "          }\n",
+       "        }\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "        var NewBokeh = root.Bokeh;\n",
+       "        if (Bokeh.versions === undefined) {\n",
+       "          Bokeh.versions = new Map();\n",
+       "        }\n",
+       "        if (NewBokeh.version !== Bokeh.version) {\n",
+       "          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "        }\n",
+       "        root.Bokeh = Bokeh;\n",
+       "      }\n",
+       "    } else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    }\n",
+       "    root._bokeh_is_initializing = false\n",
+       "  }\n",
+       "\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      // If the timeout and bokeh was not successfully loaded we reset\n",
+       "      // everything and try loading again\n",
+       "      root._bokeh_timeout = Date.now() + 5000;\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      root._bokeh_is_loading = 0\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
+       "      if (!reloading && !bokeh_loaded) {\n",
+       "        if (root.Bokeh) {\n",
+       "          root.Bokeh = undefined;\n",
+       "        }\n",
+       "        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "        run_inline_js();\n",
+       "      });\n",
+       "    }\n",
+       "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
+       "}(window));"
+      ],
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.7.3'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.7.0/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.7.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.7.3.min.js\", \"https://cdn.holoviz.org/panel/1.7.0/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
+       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
+       "}\n",
+       "\n",
+       "\n",
+       "    function JupyterCommManager() {\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        comm_manager.register_target(comm_id, function(comm) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        });\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        });\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
+       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "          function processIteratorResult(result) {\n",
+       "            var message = result.value;\n",
+       "            console.log(message)\n",
+       "            var content = {data: message.data, comm_id};\n",
+       "            var buffers = []\n",
+       "            for (var buffer of message.buffers || []) {\n",
+       "              buffers.push(new DataView(buffer))\n",
+       "            }\n",
+       "            var metadata = message.metadata || {};\n",
+       "            var msg = {content, buffers, metadata}\n",
+       "            msg_handler(msg);\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "          return messages.next().then(processIteratorResult);\n",
+       "        })\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (comm_id in window.PyViz.comms) {\n",
+       "        return window.PyViz.comms[comm_id];\n",
+       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
+       "        if (msg_handler) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        }\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
+       "        comm.open();\n",
+       "        if (msg_handler) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        }\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
+       "        comm_promise.then((comm) => {\n",
+       "          window.PyViz.comms[comm_id] = comm;\n",
+       "          if (msg_handler) {\n",
+       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "            function processIteratorResult(result) {\n",
+       "              var message = result.value;\n",
+       "              var content = {data: message.data};\n",
+       "              var metadata = message.metadata || {comm_id};\n",
+       "              var msg = {content, metadata}\n",
+       "              msg_handler(msg);\n",
+       "              return messages.next().then(processIteratorResult);\n",
+       "            }\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "        })\n",
+       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
+       "          return comm_promise.then((comm) => {\n",
+       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
+       "          });\n",
+       "        };\n",
+       "        var comm = {\n",
+       "          send: sendClosure\n",
+       "        };\n",
+       "      }\n",
+       "      window.PyViz.comms[comm_id] = comm;\n",
+       "      return comm;\n",
+       "    }\n",
+       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
+       "    \n",
+       "\n",
+       "\n",
+       "var JS_MIME_TYPE = 'application/javascript';\n",
+       "var HTML_MIME_TYPE = 'text/html';\n",
+       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
+       "var CLASS_NAME = 'output';\n",
+       "\n",
+       "/**\n",
+       " * Render data to the DOM node\n",
+       " */\n",
+       "function render(props, node) {\n",
+       "  var div = document.createElement(\"div\");\n",
+       "  var script = document.createElement(\"script\");\n",
+       "  node.appendChild(div);\n",
+       "  node.appendChild(script);\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when a new output is added\n",
+       " */\n",
+       "function handle_add_output(event, handle) {\n",
+       "  var output_area = handle.output_area;\n",
+       "  var output = handle.output;\n",
+       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "    return\n",
+       "  }\n",
+       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "  if (id !== undefined) {\n",
+       "    var nchildren = toinsert.length;\n",
+       "    var html_node = toinsert[nchildren-1].children[0];\n",
+       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var scripts = [];\n",
+       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
+       "    for (var i in nodelist) {\n",
+       "      if (nodelist.hasOwnProperty(i)) {\n",
+       "        scripts.push(nodelist[i])\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    scripts.forEach( function (oldScript) {\n",
+       "      var newScript = document.createElement(\"script\");\n",
+       "      var attrs = [];\n",
+       "      var nodemap = oldScript.attributes;\n",
+       "      for (var j in nodemap) {\n",
+       "        if (nodemap.hasOwnProperty(j)) {\n",
+       "          attrs.push(nodemap[j])\n",
+       "        }\n",
+       "      }\n",
+       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
+       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
+       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
+       "    });\n",
+       "    if (JS_MIME_TYPE in output.data) {\n",
+       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
+       "    }\n",
+       "    output_area._hv_plot_id = id;\n",
+       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
+       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
+       "    } else {\n",
+       "      window.PyViz.plot_index[id] = null;\n",
+       "    }\n",
+       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "    var bk_div = document.createElement(\"div\");\n",
+       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var script_attrs = bk_div.children[0].attributes;\n",
+       "    for (var i = 0; i < script_attrs.length; i++) {\n",
+       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "    }\n",
+       "    // store reference to server id on output_area\n",
+       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when an output is cleared or removed\n",
+       " */\n",
+       "function handle_clear_output(event, handle) {\n",
+       "  var id = handle.cell.output_area._hv_plot_id;\n",
+       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
+       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
+       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
+       "  if (server_id !== null) {\n",
+       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
+       "    return;\n",
+       "  } else if (comm !== null) {\n",
+       "    comm.send({event_type: 'delete', 'id': id});\n",
+       "  }\n",
+       "  delete PyViz.plot_index[id];\n",
+       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
+       "    var doc = window.Bokeh.index[id].model.document\n",
+       "    doc.clear();\n",
+       "    const i = window.Bokeh.documents.indexOf(doc);\n",
+       "    if (i > -1) {\n",
+       "      window.Bokeh.documents.splice(i, 1);\n",
+       "    }\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle kernel restart event\n",
+       " */\n",
+       "function handle_kernel_cleanup(event, handle) {\n",
+       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
+       "  window.PyViz.plot_index = {}\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle update_display_data messages\n",
+       " */\n",
+       "function handle_update_output(event, handle) {\n",
+       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
+       "  handle_add_output(event, handle)\n",
+       "}\n",
+       "\n",
+       "function register_renderer(events, OutputArea) {\n",
+       "  function append_mime(data, metadata, element) {\n",
+       "    // create a DOM node to render to\n",
+       "    var toinsert = this.create_output_subarea(\n",
+       "    metadata,\n",
+       "    CLASS_NAME,\n",
+       "    EXEC_MIME_TYPE\n",
+       "    );\n",
+       "    this.keyboard_manager.register_events(toinsert);\n",
+       "    // Render to node\n",
+       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "    render(props, toinsert[0]);\n",
+       "    element.append(toinsert);\n",
+       "    return toinsert\n",
+       "  }\n",
+       "\n",
+       "  events.on('output_added.OutputArea', handle_add_output);\n",
+       "  events.on('output_updated.OutputArea', handle_update_output);\n",
+       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
+       "  events.on('delete.Cell', handle_clear_output);\n",
+       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
+       "\n",
+       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "    safe: true,\n",
+       "    index: 0\n",
+       "  });\n",
+       "}\n",
+       "\n",
+       "if (window.Jupyter !== undefined) {\n",
+       "  try {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  } catch(err) {\n",
+       "  }\n",
+       "}\n"
+      ],
+      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='610afc7f-781a-4159-9ff8-d88066c8f99d'>\n",
+       "  <div id=\"f973f936-38fa-4447-b7a7-088b6ec8505d\" data-root-id=\"610afc7f-781a-4159-9ff8-d88066c8f99d\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"52d6e854-a508-4322-be41-183b991c9f4a\":{\"version\":\"3.7.3\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"610afc7f-781a-4159-9ff8-d88066c8f99d\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"b479484d-f716-45a4-89e5-e5d21e66bc33\",\"attributes\":{\"plot_id\":\"610afc7f-781a-4159-9ff8-d88066c8f99d\",\"comm_id\":\"3bf2510e48c34b42995b321e027506cb\",\"client_comm_id\":\"b55bc3c311a14841b0d3d00135c451b6\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
+       "  var render_items = [{\"docid\":\"52d6e854-a508-4322-be41-183b991c9f4a\",\"roots\":{\"610afc7f-781a-4159-9ff8-d88066c8f99d\":\"f973f936-38fa-4447-b7a7-088b6ec8505d\"},\"root_ids\":[\"610afc7f-781a-4159-9ff8-d88066c8f99d\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "610afc7f-781a-4159-9ff8-d88066c8f99d"
+      }
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "(function(root) {\n",
+       "  function now() {\n",
+       "    return new Date();\n",
+       "  }\n",
+       "\n",
+       "  const force = false;\n",
+       "  const py_version = '3.7.3'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
+       "  const reloading = true;\n",
+       "  const Bokeh = root.Bokeh;\n",
+       "\n",
+       "  // Set a timeout for this load but only if we are not already initializing\n",
+       "  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n",
+       "    root._bokeh_timeout = Date.now() + 5000;\n",
+       "    root._bokeh_failed_load = false;\n",
+       "  }\n",
+       "\n",
+       "  function run_callbacks() {\n",
+       "    try {\n",
+       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
+       "        if (callback != null)\n",
+       "          callback();\n",
+       "      });\n",
+       "    } finally {\n",
+       "      delete root._bokeh_onload_callbacks;\n",
+       "    }\n",
+       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
+       "  }\n",
+       "\n",
+       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
+       "    if (css_urls == null) css_urls = [];\n",
+       "    if (js_urls == null) js_urls = [];\n",
+       "    if (js_modules == null) js_modules = [];\n",
+       "    if (js_exports == null) js_exports = {};\n",
+       "\n",
+       "    root._bokeh_onload_callbacks.push(callback);\n",
+       "\n",
+       "    if (root._bokeh_is_loading > 0) {\n",
+       "      // Don't load bokeh if it is still initializing\n",
+       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
+       "      return null;\n",
+       "    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
+       "      // There is nothing to load\n",
+       "      run_callbacks();\n",
+       "      return null;\n",
+       "    }\n",
+       "\n",
+       "    function on_load() {\n",
+       "      root._bokeh_is_loading--;\n",
+       "      if (root._bokeh_is_loading === 0) {\n",
+       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
+       "        run_callbacks()\n",
+       "      }\n",
+       "    }\n",
+       "    window._bokeh_on_load = on_load\n",
+       "\n",
+       "    function on_error(e) {\n",
+       "      const src_el = e.srcElement\n",
+       "      console.error(\"failed to load \" + (src_el.href || src_el.src));\n",
+       "    }\n",
+       "\n",
+       "    const skip = [];\n",
+       "    if (window.requirejs) {\n",
+       "      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n",
+       "      root._bokeh_is_loading = css_urls.length + 0;\n",
+       "    } else {\n",
+       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
+       "    }\n",
+       "\n",
+       "    const existing_stylesheets = []\n",
+       "    const links = document.getElementsByTagName('link')\n",
+       "    for (let i = 0; i < links.length; i++) {\n",
+       "      const link = links[i]\n",
+       "      if (link.href != null) {\n",
+       "        existing_stylesheets.push(link.href)\n",
+       "      }\n",
+       "    }\n",
+       "    for (let i = 0; i < css_urls.length; i++) {\n",
+       "      const url = css_urls[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (existing_stylesheets.indexOf(escaped) !== -1) {\n",
+       "        on_load()\n",
+       "        continue;\n",
+       "      }\n",
+       "      const element = document.createElement(\"link\");\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }    var existing_scripts = []\n",
+       "    const scripts = document.getElementsByTagName('script')\n",
+       "    for (let i = 0; i < scripts.length; i++) {\n",
+       "      var script = scripts[i]\n",
+       "      if (script.src != null) {\n",
+       "        existing_scripts.push(script.src)\n",
+       "      }\n",
+       "    }\n",
+       "    for (let i = 0; i < js_urls.length; i++) {\n",
+       "      const url = js_urls[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      const element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (let i = 0; i < js_modules.length; i++) {\n",
+       "      const url = js_modules[i];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    for (const name in js_exports) {\n",
+       "      const url = js_exports[name];\n",
+       "      const escaped = encodeURI(url)\n",
+       "      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n",
+       "        if (!window.requirejs) {\n",
+       "          on_load();\n",
+       "        }\n",
+       "        continue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "    if (!js_urls.length && !js_modules.length) {\n",
+       "      on_load()\n",
+       "    }\n",
+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  const js_urls = [\"https://cdn.holoviz.org/panel/1.7.0/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n",
+       "  const js_modules = [];\n",
+       "  const js_exports = {};\n",
+       "  const css_urls = [];\n",
+       "  const inline_js = [    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "function(Bokeh) {} // ensure no trailing comma for IE\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
+       "      for (let i = 0; i < inline_js.length; i++) {\n",
+       "        try {\n",
+       "          inline_js[i].call(root, root.Bokeh);\n",
+       "        } catch(e) {\n",
+       "          if (!reloading) {\n",
+       "            throw e;\n",
+       "          }\n",
+       "        }\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "        var NewBokeh = root.Bokeh;\n",
+       "        if (Bokeh.versions === undefined) {\n",
+       "          Bokeh.versions = new Map();\n",
+       "        }\n",
+       "        if (NewBokeh.version !== Bokeh.version) {\n",
+       "          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "        }\n",
+       "        root.Bokeh = Bokeh;\n",
+       "      }\n",
+       "    } else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    }\n",
+       "    root._bokeh_is_initializing = false\n",
+       "  }\n",
+       "\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      // If the timeout and bokeh was not successfully loaded we reset\n",
+       "      // everything and try loading again\n",
+       "      root._bokeh_timeout = Date.now() + 5000;\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      root._bokeh_is_loading = 0\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n",
+       "      if (!reloading && !bokeh_loaded) {\n",
+       "        if (root.Bokeh) {\n",
+       "          root.Bokeh = undefined;\n",
+       "        }\n",
+       "        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "        run_inline_js();\n",
+       "      });\n",
+       "    }\n",
+       "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
+       "}(window));"
+      ],
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = false;\n  const py_version = '3.7.3'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = true;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.7.0/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "\n",
+       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
+       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
+       "}\n",
+       "\n",
+       "\n",
+       "    function JupyterCommManager() {\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        comm_manager.register_target(comm_id, function(comm) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        });\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        });\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
+       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "          function processIteratorResult(result) {\n",
+       "            var message = result.value;\n",
+       "            console.log(message)\n",
+       "            var content = {data: message.data, comm_id};\n",
+       "            var buffers = []\n",
+       "            for (var buffer of message.buffers || []) {\n",
+       "              buffers.push(new DataView(buffer))\n",
+       "            }\n",
+       "            var metadata = message.metadata || {};\n",
+       "            var msg = {content, buffers, metadata}\n",
+       "            msg_handler(msg);\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "          return messages.next().then(processIteratorResult);\n",
+       "        })\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
+       "      if (comm_id in window.PyViz.comms) {\n",
+       "        return window.PyViz.comms[comm_id];\n",
+       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
+       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
+       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
+       "        if (msg_handler) {\n",
+       "          comm.on_msg(msg_handler);\n",
+       "        }\n",
+       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
+       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
+       "        comm.open();\n",
+       "        if (msg_handler) {\n",
+       "          comm.onMsg = msg_handler;\n",
+       "        }\n",
+       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
+       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
+       "        comm_promise.then((comm) => {\n",
+       "          window.PyViz.comms[comm_id] = comm;\n",
+       "          if (msg_handler) {\n",
+       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
+       "            function processIteratorResult(result) {\n",
+       "              var message = result.value;\n",
+       "              var content = {data: message.data};\n",
+       "              var metadata = message.metadata || {comm_id};\n",
+       "              var msg = {content, metadata}\n",
+       "              msg_handler(msg);\n",
+       "              return messages.next().then(processIteratorResult);\n",
+       "            }\n",
+       "            return messages.next().then(processIteratorResult);\n",
+       "          }\n",
+       "        })\n",
+       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
+       "          return comm_promise.then((comm) => {\n",
+       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
+       "          });\n",
+       "        };\n",
+       "        var comm = {\n",
+       "          send: sendClosure\n",
+       "        };\n",
+       "      }\n",
+       "      window.PyViz.comms[comm_id] = comm;\n",
+       "      return comm;\n",
+       "    }\n",
+       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
+       "    \n",
+       "\n",
+       "\n",
+       "var JS_MIME_TYPE = 'application/javascript';\n",
+       "var HTML_MIME_TYPE = 'text/html';\n",
+       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
+       "var CLASS_NAME = 'output';\n",
+       "\n",
+       "/**\n",
+       " * Render data to the DOM node\n",
+       " */\n",
+       "function render(props, node) {\n",
+       "  var div = document.createElement(\"div\");\n",
+       "  var script = document.createElement(\"script\");\n",
+       "  node.appendChild(div);\n",
+       "  node.appendChild(script);\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when a new output is added\n",
+       " */\n",
+       "function handle_add_output(event, handle) {\n",
+       "  var output_area = handle.output_area;\n",
+       "  var output = handle.output;\n",
+       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
+       "    return\n",
+       "  }\n",
+       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "  if (id !== undefined) {\n",
+       "    var nchildren = toinsert.length;\n",
+       "    var html_node = toinsert[nchildren-1].children[0];\n",
+       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var scripts = [];\n",
+       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
+       "    for (var i in nodelist) {\n",
+       "      if (nodelist.hasOwnProperty(i)) {\n",
+       "        scripts.push(nodelist[i])\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    scripts.forEach( function (oldScript) {\n",
+       "      var newScript = document.createElement(\"script\");\n",
+       "      var attrs = [];\n",
+       "      var nodemap = oldScript.attributes;\n",
+       "      for (var j in nodemap) {\n",
+       "        if (nodemap.hasOwnProperty(j)) {\n",
+       "          attrs.push(nodemap[j])\n",
+       "        }\n",
+       "      }\n",
+       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
+       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
+       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
+       "    });\n",
+       "    if (JS_MIME_TYPE in output.data) {\n",
+       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
+       "    }\n",
+       "    output_area._hv_plot_id = id;\n",
+       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
+       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
+       "    } else {\n",
+       "      window.PyViz.plot_index[id] = null;\n",
+       "    }\n",
+       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "    var bk_div = document.createElement(\"div\");\n",
+       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "    var script_attrs = bk_div.children[0].attributes;\n",
+       "    for (var i = 0; i < script_attrs.length; i++) {\n",
+       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "    }\n",
+       "    // store reference to server id on output_area\n",
+       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle when an output is cleared or removed\n",
+       " */\n",
+       "function handle_clear_output(event, handle) {\n",
+       "  var id = handle.cell.output_area._hv_plot_id;\n",
+       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
+       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
+       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
+       "  if (server_id !== null) {\n",
+       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
+       "    return;\n",
+       "  } else if (comm !== null) {\n",
+       "    comm.send({event_type: 'delete', 'id': id});\n",
+       "  }\n",
+       "  delete PyViz.plot_index[id];\n",
+       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
+       "    var doc = window.Bokeh.index[id].model.document\n",
+       "    doc.clear();\n",
+       "    const i = window.Bokeh.documents.indexOf(doc);\n",
+       "    if (i > -1) {\n",
+       "      window.Bokeh.documents.splice(i, 1);\n",
+       "    }\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle kernel restart event\n",
+       " */\n",
+       "function handle_kernel_cleanup(event, handle) {\n",
+       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
+       "  window.PyViz.plot_index = {}\n",
+       "}\n",
+       "\n",
+       "/**\n",
+       " * Handle update_display_data messages\n",
+       " */\n",
+       "function handle_update_output(event, handle) {\n",
+       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
+       "  handle_add_output(event, handle)\n",
+       "}\n",
+       "\n",
+       "function register_renderer(events, OutputArea) {\n",
+       "  function append_mime(data, metadata, element) {\n",
+       "    // create a DOM node to render to\n",
+       "    var toinsert = this.create_output_subarea(\n",
+       "    metadata,\n",
+       "    CLASS_NAME,\n",
+       "    EXEC_MIME_TYPE\n",
+       "    );\n",
+       "    this.keyboard_manager.register_events(toinsert);\n",
+       "    // Render to node\n",
+       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "    render(props, toinsert[0]);\n",
+       "    element.append(toinsert);\n",
+       "    return toinsert\n",
+       "  }\n",
+       "\n",
+       "  events.on('output_added.OutputArea', handle_add_output);\n",
+       "  events.on('output_updated.OutputArea', handle_update_output);\n",
+       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
+       "  events.on('delete.Cell', handle_clear_output);\n",
+       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
+       "\n",
+       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "    safe: true,\n",
+       "    index: 0\n",
+       "  });\n",
+       "}\n",
+       "\n",
+       "if (window.Jupyter !== undefined) {\n",
+       "  try {\n",
+       "    var events = require('base/js/events');\n",
+       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  } catch(err) {\n",
+       "  }\n",
+       "}\n"
+      ],
+      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Launching server at http://localhost:55003\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<panel.io.server.Server at 0x23e668041a0>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import rioxarray\n",
+    "import hvplot.xarray\n",
+    "import panel as pn\n",
+    "\n",
+    "pn.extension()\n",
+    "\n",
+    "def view():\n",
+    "    return sat_imv.hvplot.image(\n",
+    "        x='x', y='y',\n",
+    "        rasterize=True, # Datashader aggregates data to fit the screen resolution\n",
+    "        dynamic=True, # plot will dynamically update\n",
+    "    ).opts(\n",
+    "        cmap='turbo',\n",
+    "        width=700,\n",
+    "        height=700,\n",
+    "    )\n",
+    "\n",
+    "# displayed the raster in the browser\n",
+    "pn.serve(view, title=\"tab_title\", show=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7cc14869",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab = con.read_parquet(Path.cwd().parent / 'finalprojectdata' / 'grid_300km_30M.parquet')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "c532b9e3-a0c9-434b-845f-dcafb26aa6c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/25 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f68386a8e62c49ecaa76615ee433bc72",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  4%|▍         | 1/25 [00:10<04:22, 10.92s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cd2199c1a47e492989bed2f3f254d557",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  8%|▊         | 2/25 [00:24<04:47, 12.51s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "071593744471488e95574b7a455e4b69",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 12%|█▏        | 3/25 [00:37<04:39, 12.73s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "05b90613c5ab45fcb333505d0cfd2b5e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 16%|█▌        | 4/25 [00:51<04:34, 13.09s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1fbf6d9268864e6fa4bcdc3ddbc55aea",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 20%|██        | 5/25 [01:04<04:26, 13.33s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "45f9862fe6e6438680aa5516ea482b0b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 24%|██▍       | 6/25 [01:18<04:16, 13.49s/it]"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4de01748a8264fc2bc954646d9a58f53",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+      ]
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+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 96%|█████████▌| 24/25 [05:10<00:10, 10.78s/it]"
+     ]
+    },
+    {
+     "data": {
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+      },
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+       "FloatProgress(value=0.0, layout=Layout(width='auto'), style=ProgressStyle(bar_color='black'))"
+      ]
+     },
+     "metadata": {},
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+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 25/25 [05:15<00:00, 12.63s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Stratified sampling in 'THICK' bins using ibis to conserve memory\n",
+    "num_points = 300_000\n",
+    "n_bins = 25  # Adjust for smoothness\n",
+    "\n",
+    "# Compute bin edges\n",
+    "thick_min = tab.THICK.min().execute()\n",
+    "thick_max = tab.THICK.max().execute()\n",
+    "bin_edges = np.linspace(thick_min, thick_max, n_bins + 1)\n",
+    "\n",
+    "samples_per_bin = num_points // n_bins\n",
+    "sampled_tables = []\n",
+    "sampled_frames = []\n",
+    "\n",
+    "for b in tqdm(range(n_bins), leave=True):\n",
+    "    lower = bin_edges[b]\n",
+    "    upper = bin_edges[b+1]\n",
+    "    bin_rows = tab.filter((tab.THICK >= lower) & (tab.THICK < upper))\n",
+    "    bin_count = bin_rows.count().execute()\n",
+    "    n = min(samples_per_bin, bin_count)\n",
+    "    if n > 0:\n",
+    "        sampled = bin_rows.sample(n / bin_count)\n",
+    "        df = sampled.to_pandas()\n",
+    "        sampled_frames.append(df)\n",
+    "\n",
+    "gdf = pd.concat(sampled_frames, ignore_index=True)\n",
+    "gdf.crs = \"EPSG:3031\"\n",
+    "gdf_sindex = gdf.sindex"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "ae2f315d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ssdKjci2v5ZKTk83rwjkQlJ38aLNIQD3dhXq6S7jXM5zXDbiUicBUysGdcmrVG2ZC+Mw0dd3ChQtNGj/d17HFFysue3bv4uAKESH9zEmdLEIefPBBx68lFzAAwKsDLdjfQ6TL10C6pmPRAPbKlSt9wWodcae5z/v27WvuN23aVE6dOiWbNm2Shg0bmsdWrVplRidp/nK7zDPPPGNGFdqBBh1dWLt2bZPWxS6jnzNgwADf52sZfTzYdQEAAED+Bv98AUDLyjL4Hh/9+4CCCt1elJQ0y1f+xLLJJmjPgRUiQUbqmWy38ewwwhwA4OWBFuzvwQ0cB9LPnDkje/fu9d3XST23bNlicpzrF0ED288995zUqlXLBLNHjhwplStXlk6dOpnydevWlTZt2kivXr3k1VdfNcHy/v37m8k/tZzq1q2byVX+6KOPypAhQ2THjh0yffp0mTp1qu9zn3jiCWnRooVMnjxZ2rdvL4sWLZKNGzfKa6+9Zp6PiorKdV0AAAAQ2uB7rJl0PV1iK9QI6io9wFUnmAAA8Gg/CHgykK7B6ltvvdV3384p3r17d5k3b54MHjxYzp49K7179zYjz2+++WZZvny5xMfH+14zf/58Ezxv1aqVSV3SpUsXmTFjhu/5hIQEM8Fnv379zKh1zaE0atQo8562Zs2ayYIFC2TEiBEyfPhwEyxfunSp1K9f31cmmHUBAACANzjN5emWPJ5O6u0k5zcAAADgJY4D6S1bthTL+v0y3KzoSPCxY8eaJTs6el2D4Dm57rrrJDExMccy9957r1kuZV0AAADgfnnJ5emGPJ55zWEKAIBXMYkmgJDkSAcAAADckMvTLXk8ndabPN4AAC87ePCgXFOvPpNoAsgSgXQAAAB4hldzeQZbb/J4AwC87MSJE0yiCSBbBNIBAAAAAACASzjx7mSeEVLBAJGJQDoAAAAAAACQB+lnTuokffLggw8G/RpSwQCRiUA6AAAAXD8RmJNRYoDX7NmzR0qUKCFbt26VIkWK5FiWUZQAECgj9YyIZXluHhbAiwikAwAAIOKC6LXr1HU8EVheOA3AE2REJI6i7NWrlyxcuFCaN28uycnJOb6GUZQAkDWvzsMCeAmBdAAAAEQUHcHldCKw5J82yunEfxToZdqKICMicRRl6TaPm/sVur0oKWlWtuUZRQkAALyMQDoAAABcP/JLA4AFeZm2/RkEGRGJYkpfaW5jK9QQKz2qsFcHAAAgLBFIBwAA8KBgU5Z4Pbc4l2kDAEIxlwepwQAg/BFIBwAA8JC8piwBAAAFN5cHqcEAIPwRSAcAAPAQpylLnOYWvxSMkgcAeHEuD1KDAUBkIJAOAADgQcGmLHGaWzwvGCUPAHAj0oMBgLsQSAcAAEChCudR8gAAIPLldjVbRkaGud2zZ0+I1ghAJCKQDgAAgLAQTqPk3TJ5HWlwAABeFuxVb8WKFZOFCxdKr169QrZuACIPgXQAAAAgAhw8eFCuqVff0eR1ALzryy+/lIkTJ8qmTZvk8OHDsmTJEunUqZPvecuyZPTo0fL666/LqVOn5KabbpJXXnlFatWq5SuTlJQkjz/+uHz00UdSpEgR6dKli0yfPl1KlCjhK7Nt2zbp16+ffPvtt1KuXDlTfvDgwQHrsnjxYhk5cqTs37/fvP9LL70k7dq1C1FLwMuCveotPjrK3JZsdp8kr5wXwjUEEEkIpAMAAAAR4MSJE44mr1OkwQG86+zZs3L99dfLI488Ip07d77o+QkTJsiMGTPkrbfekurVq5tA95133inff/+9xMfHmzIPPPCACcJ//vnncuHCBenZs6f07t1bFixYYJ7/9ddf5Y477pDWrVvLq6++Ktu3bzefV6pUKVNOrVu3Trp27Srjx4+Xu+66y7xWA/rfffed1K9fP8StAq/K7aq32KKWjl+X6JLlxctyupLNTn+zdevWS0qB4+RqudTUVImLi3P0/mXLlmXSXhQYAukAAACASyev83IaHMDr2rZta5as6Gj0adOmyYgRI6Rjx47msbffflsqVKggS5culfvvv98Eu5YvX25Gmjdq1MiUmTlzphlJPmnSJKlcubLMnz9fzp8/L3PmzJHY2FipV6+ebNmyRaZMmeILpOsI9jZt2sigQYPM/XHjxpnA/KxZs0zwHUBkpMCx0980b95ckpOTC+QzLhJVRMT6PYAfrPhixWXP7l0E01EgCKQDAADHnn32WRkzZkzAY7Vr15bdu3eb/6ekpMjAgQNl0aJFZiSJjnB7+eWXzQG6f67nvn37yurVq80l4t27dzej1aKj/3/3ZM2aNfLUU0/Jzp07pUqVKuaAv0ePHiGsKVCwI60YNQWgMOzbt0+OHDliRpLbEhISpEmTJrJ+/XoTSNdbHVluB9GVltcULxs2bJB77rnHlNGgmgbRbdrna+qWkydPyhVXXGHKaF/uT8towD47uu+gi01HvisdFa+Lzf6//2PhQEfuatBR04X8PtI5Z1HRUaa8vi6/65LXNnJah7zUw+lnpMUUdbxOwb4mrsjvz8UX4GeEqp3ysk5pGclSLD5eSrd5XGJKX5llmbj/S39T9eGX5NTe7+TXde84W6cgPsNf8v7N5jOCLa8uJB2SpOUz5dixY1KpUiUJtXD9TQo3F8KsnZysB4F0AACQJzrq7IsvvvDd9w+AP/nkk/Lxxx+bnKh6YN6/f39zWfnatWvN8+np6dK+fXupWLGiueRbLxt/+OGHJSYmRl544QXfQb6W6dOnjxnxtnLlSnnsscfMTrEegAPhJi8jrRg1BaAwaBBd+Z/gtu/bz+lt+fKBaS60ry9dunRAGU0Lk/k97Oc0kK63OX1OVvTEeuYT9mrFihVSvHjxix7XEe7hRkfu/i49iNLVRDoslEOHDpmlIOSljZzVIW/1cPQZjZuJdG/mbJ0cvmZytyYi3RzW2/F6FXA75WWdAsrn7KW2us9SVeTxTpewTsGo5vcZDl7TvVmBfpeCEY6/SeEoXNrp3Lng5x8ikA4AAPJED6Y1EJ7Z6dOn5c033zQ5UG+77Tbz2Ny5c6Vu3bry9ddfy4033mgOhDUHqwbi9WC6QYMG5lLvIUOGmNHuOrJNL/fWg/PJkyeb99DXf/XVVzJ16tQcA+nBjmILxYiKcBppFaryub3GHvFl34bDOuXbZzgcaRXsqCl72wrJiLQwbNu8rFN0TFHf6DkrTNYpnD/DHmXo/70M9ajZSOP1+he0YcOGBYxi175cr0zTfOwlS5YM+DtoIOb22283J+PDheaQ1pH6Fbq9KLEVauRa/vzRn+TogqFmgljNa5+f8tpGTuuQl3o4/YyzuxJNv+lknYJ9jf7+jWuUIQMXbJB/fzStQD4jVO2Ul3UKprzdRiM3FpGknV8V2N8ir+X921YnUdarZYNRpkwZueqqqyQ/hOtvUri5EGbtZB8vBoNAOgAAyJMffvjB5EfVCcmaNm1qRo/pqNpNmzaZnSP/y8Xr1KljntPLuzWQrrfXXnttwAg1DY5rqhdN43LDDTeYMv7vYZcZMGBAjuvldBRbQY+oCLeRVgVePsjX6IFYuK1T/n5G/o+a0is3QjsiLUw+I0/r1MRv1Fy4rFO4f0am72UhjZpFaNgnwo8ePRpwIk/v68ltu4ye6POXlpYmSUlJvtfrrb7Gn30/tzJZnYy36eSCWU0wqAGXrIIu2T1eWDT9jeaQTkmzxEr//URVTlLTLFNeX1dQ9XDaRk7rkJd6OP2MlAvpjtfJ6WtC8RkF3U55WScn5VMzosL2b3HuVJIkp6QU+tWB4fabFK5iwqSdnKxDtJtzps6ePVsmTpxoLhnTs3w6MUrjxo3zu8oAAHiO5lCdN2+e6eM1uKd9/y233CI7duww/a6OKNe8qjldLp7VZd72czmV0REDulOtoyIvZRRbKEZUhNNIq1CVz+01/qOZ9EAsHNapsD4j2FFTOvpXv2dnzpyRXr16RXy9Q7FO6XvXmcvzh3x6QKwy1cNincL5MzTfrZ508P9ehnrUbKTR3/4PPvhAIpVe8aWBbE2bZgfOtb/U3Od6LK70JPmpU6fMCfKGDRuax1atWmV+k3Q/wC7zzDPPmPaw+0DtE/U3TdO62GX0c/xPhGsZfRx5p3GT48eP51pO/172Pomm6iGVGNwsI/WMzqYsZe4aaCZnD2ZS9hPLJpvvEt8NFNqI9HDImfrOO++Yg2i9LFw7eZ2RXJ/bs2fPRXneAACAM23btvX9/7rrrjN9bbVq1eTdd9/NNsAdKk5HsV3qQat9gKqpanTEkD/d7wi3UVDhMjJLg3Wp//dcuKxTqD8j2FFT+p3SkegaRHdDvUOxTmkX0n2j/sJlncL5M7SdMn8vC2vULPKPnnzbu3ev774eR2/ZssXkONeAkQa2n3vuOalVq5YJrI8cOdJcadapUydfSrU2bdqY3x49rtZguR6/60SkWk5169bNnEx/9NFHTXo2PaE+ffp0k4bN9sQTT0iLFi1MqjY9jtdBdRs3bpTXXnutEFrFHXR/pHadupKSnHteX7sP0RP7lkSFZF6OYCfddjI5N+CEBtHjKtYs7NWAC0W7NWfqlClTTIffs2dPc19fowH8OXPmyNChQ0OeU9U+yA42T2Ok5h8Mt5l3Cwr1dBfq6S6RUs9wXz+ndPT51VdfbQ7YdWT2+fPnzSg2/1Hp/pdx6+0333yTp0vBdVR5YQTrszto9T9A1QATkN+jpjTftSrZ7D5JXjkvhGsIIJJpsPrWW2/13bev1tIrvvWqssGDB8vZs2eld+/eps+++eabZfny5SZlm00HrmnwvFWrVuYESpcuXWTGjBm+53VwnB7D9+vXz4xaL1u2rIwaNcq8p61Zs2YmBqBXkQ8fPtwE7pcuXSr169cPWVu4jZ7U1/2RYEbd2n2Izt9xaMmEAh15m5dJtwFAvB5IL+ycqXrwrp+ll3bbtNPX1+hrCzOnatB5GiM8/2C4zLxb0Kinu1BPdwn3ejqZGTxSRr39+OOP8tBDD5kDaR2pqFeM6QG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+      "text/plain": [
+       "<Figure size 1500x1000 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gdf.hist(bins=30, figsize=(15, 10), edgecolor='black')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81ed8655-c62e-4dc9-a464-8aa727fe95db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(\"gdf CRS:\", gdf.crs)\n",
+    "print(\"sat_imv CRS:\", sat_imt2m.rio.crs)\n",
+    "\n",
+    "from shapely.geometry import box\n",
+    "\n",
+    "raster_bounds = sat_imt2m.rio.bounds()\n",
+    "raster_bbox = box(*raster_bounds)\n",
+    "\n",
+    "# Check how many points are inside\n",
+    "inside_mask = gdf.geometry.within(raster_bbox)\n",
+    "print(f\"{inside_mask.sum()} out of {len(gdf)} geometries fall inside raster extent.\")\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(8, 8))\n",
+    "gdf.plot(ax=ax, color='red', markersize=1, label='gdf points')\n",
+    "sat_imt2m.sel(band=1).plot.imshow(ax=ax, alpha=0.4, cmap='gray')\n",
+    "plt.legend()\n",
+    "plt.title(\"Check Alignment: gdf vs. sat_imv\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ca10fb08-c04d-45d5-9c3e-208bff5f4f31",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.patches import Rectangle\n",
+    "from shapely.geometry import box\n",
+    "\n",
+    "# Choose a sample point from gdf\n",
+    "sample_idx = 0  # change this index to explore other patches\n",
+    "geom = gdf.geometry.iloc[sample_idx]\n",
+    "\n",
+    "# Get transform and patch info\n",
+    "transform = sat_imz.rio.transform()\n",
+    "inv_transform = ~transform\n",
+    "size = 27\n",
+    "half = size // 2\n",
+    "\n",
+    "# Get pixel coords\n",
+    "x, y = geom.x, geom.y\n",
+    "col, row = inv_transform * (x, y)\n",
+    "col, row = int(np.floor(col)), int(np.floor(row))\n",
+    "\n",
+    "# Get bounds of patch (in pixel space)\n",
+    "x_start = col - half\n",
+    "y_start = row - half\n",
+    "\n",
+    "# Convert patch pixel bounds to real-world coords\n",
+    "x_min, y_max = transform * (x_start, y_start)\n",
+    "x_max, y_min = transform * (x_start + size, y_start + size)\n",
+    "\n",
+    "# Create a bounding box polygon\n",
+    "patch_bounds = box(x_min, y_min, x_max, y_max)\n",
+    "\n",
+    "# Plot raster and overlay patch\n",
+    "fig, ax = plt.subplots(figsize=(10, 8))\n",
+    "\n",
+    "sat_imt2m.plot(ax=ax, cmap='terrain')\n",
+    "ax.plot(x, y, 'r.', label=\"Sample Center\")\n",
+    "patch_rect = Rectangle((x_min, y_min), x_max - x_min, y_max - y_min,\n",
+    "                       edgecolor='red', facecolor='none', linewidth=1, label=\"27x27 patch\")\n",
+    "ax.add_patch(patch_rect)\n",
+    "\n",
+    "ax.legend()\n",
+    "ax.set_title(\"Patch Location on Surface Raster\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "8cd3bb9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from collections import defaultdict\n",
+    "from shapely.geometry import Point\n",
+    "from math import floor\n",
+    "\n",
+    "size = 27\n",
+    "half = size // 2\n",
+    "\n",
+    "transformz = sat_imz.rio.transform() #We have made it so that the transform is the same for all pictures.\n",
+    "inverse_transformz = ~transformz\n",
+    "\n",
+    "scalar_feats = ['THICK', 'vx', 'vy', 'v', 'smb', 'z', 's', 'temp', 'ith_bm', 'gridCellId']\n",
+    "\n",
+    "# Step 1: Map gdf points to pixel coordinates\n",
+    "#gdf['pixel_row'], gdf['pixel_col'] = zip(*gdf.geometry.apply(lambda geom: map(lambda v: int(floor(v)), inverse_transformz * (geom.x, geom.y))))\n",
+    "\n",
+    "cols, rows = [],[]\n",
+    "for geom in gdf.geometry:\n",
+    "    x, y = geom.x, geom.y\n",
+    "    col, row = inverse_transformz * (x, y)\n",
+    "    cols.append(int(np.floor(col)))\n",
+    "    rows.append(int(np.floor(row)))\n",
+    "    \n",
+    "gdf['pixel_row'], gdf['pixel_col'] = rows, cols\n",
+    "\n",
+    "# Step 2: Group by pixel (row, col) and average\n",
+    "grouped = gdf.groupby(['pixel_row', 'pixel_col'])\n",
+    "aggregated_data = grouped[scalar_feats].mean().reset_index()\n",
+    "\n",
+    "# Step 3: Extract image patches at each unique (row, col)\n",
+    "imagesz = []\n",
+    "imagesv = []\n",
+    "imagessmb = []\n",
+    "imagest2m = []\n",
+    "\n",
+    "new_scalar_data = defaultdict(list)\n",
+    "center_xs = []\n",
+    "center_ys = []\n",
+    "\n",
+    "def patching(row_pixel,col_pixel,sat,image_name):\n",
+    "    patch = sat.isel(\n",
+    "            y=slice(row_pixel - half, row_pixel + half + 1),\n",
+    "            x=slice(col_pixel - half, col_pixel + half + 1)\n",
+    "        )\n",
+    "\n",
+    "    image = xr.DataArray(\n",
+    "            patch[0].values,\n",
+    "            coords={\"x\": np.arange(size), \"y\": np.arange(size)},\n",
+    "            dims=(\"x\", \"y\"),\n",
+    "            name=image_name\n",
+    "        )\n",
+    "    return image\n",
+    "\n",
+    "for _, row in tqdm(aggregated_data.iterrows()):\n",
+    "    row_pix = int(row['pixel_row'])\n",
+    "    col_pix = int(row['pixel_col'])\n",
+    "\n",
+    "    # Skip if patch would go out of bounds in any of the images\n",
+    "    if (row_pix - half < 0 or row_pix + half + 1 > sat_imz.sizes['y'] or\n",
+    "        col_pix - half < 0 or col_pix + half + 1 > sat_imz.sizes['x'] or \n",
+    "        row_pix - half < 0 or row_pix + half + 1 > sat_imv.sizes['y'] or\n",
+    "        col_pix - half < 0 or col_pix + half + 1 > sat_imv.sizes['x']):\n",
+    "        continue\n",
+    "\n",
+    "    imagez = patching(row_pix, col_pix, sat_imz, \"z_image\")\n",
+    "    imagev = patching(row_pix, col_pix, sat_imv, \"v_image\")\n",
+    "    imagesmb = patching(row_pix, col_pix, sat_imsmb, \"smb_image\")\n",
+    "    imaget2m = patching(row_pix, col_pix, sat_imt2m, \"temp_image\")\n",
+    "\n",
+    "    imagesz.append(imagez)\n",
+    "    imagesv.append(imagev)\n",
+    "    imagessmb.append(imagesmb)\n",
+    "    imagest2m.append(imaget2m)\n",
+    "\n",
+    "    for feat in scalar_feats:\n",
+    "        new_scalar_data[feat].append(row[feat])\n",
+    "\n",
+    "    # Get center pixel world coordinates\n",
+    "    x_center, y_center = transformz * (col_pix + 0.5, row_pix + 0.5)\n",
+    "    center_xs.append(x_center)\n",
+    "    center_ys.append(y_center)\n",
+    "\n",
+    "# Step 4: Build xarray dataset\n",
+    "sample_ids = np.arange(len(imagesz)) #We use the same ids of course\n",
+    "all_imagesz_da = xr.concat(imagesz, dim=\"sample\")\n",
+    "all_imagesz_da[\"sample\"] = sample_ids\n",
+    "\n",
+    "all_imagesv_da = xr.concat(imagesv, dim=\"sample\")\n",
+    "all_imagesv_da[\"sample\"] = sample_ids\n",
+    "\n",
+    "all_imagessmb_da = xr.concat(imagessmb, dim=\"sample\")\n",
+    "all_imagessmb_da[\"sample\"] = sample_ids\n",
+    "\n",
+    "all_imagest2m_da = xr.concat(imagest2m, dim=\"sample\")\n",
+    "all_imagest2m_da[\"sample\"] = sample_ids\n",
+    "\n",
+    "scalars_ds = xr.Dataset({\n",
+    "    feat: xr.DataArray(np.array(new_scalar_data[feat]), coords={'sample': sample_ids}, dims=('sample',))\n",
+    "    for feat in scalar_feats if feat != \"THICK\"\n",
+    "})\n",
+    "labels_da = xr.DataArray(np.array(new_scalar_data[\"THICK\"]), coords={\"sample\": sample_ids}, dims=(\"sample\",), name=\"label\")\n",
+    "\n",
+    "# Add X, Y world coordinates\n",
+    "x_coords_da = xr.DataArray(np.array(center_xs), coords={'sample': sample_ids}, dims=('sample',), name='x')\n",
+    "y_coords_da = xr.DataArray(np.array(center_ys), coords={'sample': sample_ids}, dims=('sample',), name='y')\n",
+    "\n",
+    "# Final dataset\n",
+    "training_data_ds = xr.Dataset(\n",
+    "    {\n",
+    "        \"z_images\": all_imagesz_da,\n",
+    "        \"v_images\": all_imagesv_da,\n",
+    "        \"smb_images\": all_imagessmb_da,\n",
+    "        \"temp_images\": all_imagest2m_da,\n",
+    "        \"labels\": labels_da,\n",
+    "        \"EAST\": x_coords_da,\n",
+    "        \"NORTH\": y_coords_da\n",
+    "    },\n",
+    "    coords={\"sample\": sample_ids},\n",
+    "    attrs={'description': 'CNN data with averaged scalar features and one image per pixel.'}\n",
+    ").merge(scalars_ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "26daaf37-1ded-4397-809a-528f9b6acc9c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Group and count how many gdf rows fall into each pixel\n",
+    "point_counts = gdf.groupby(['pixel_row', 'pixel_col']).size()\n",
+    "\n",
+    "# Plot histogram\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "plt.hist(point_counts.values, bins=range(1, point_counts.max()+2), edgecolor='black')\n",
+    "plt.xlabel(\"Number of gdf rows per pixel\")\n",
+    "plt.ylabel(\"Number of pixels\")\n",
+    "plt.yscale('log')\n",
+    "plt.title(\"Distribution of gdf rows per raster pixel\")\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "86565850-2861-4e08-9531-de6dfac08085",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from matplotlib.colors import LogNorm\n",
+    "\n",
+    "# Setup\n",
+    "size = 27\n",
+    "half = size // 2\n",
+    "transform = sat_imz.rio.transform()\n",
+    "inv_transform = ~transform\n",
+    "\n",
+    "ny, nx = sat_imsmb.sizes['y'], sat_imsmb.sizes['x']\n",
+    "zero_patch_coords = []\n",
+    "\n",
+    "# Loop through all sample points\n",
+    "for geom in gdf.geometry:\n",
+    "    x, y = geom.x, geom.y\n",
+    "    col, row = inv_transform * (x, y)\n",
+    "    col, row = int(np.floor(col)), int(np.floor(row))\n",
+    "\n",
+    "    # Bounds check\n",
+    "    if (\n",
+    "        (row - half >= 0) and (row + half + 1 < ny) and\n",
+    "        (col - half >= 0) and (col + half + 1 < nx)\n",
+    "    ):\n",
+    "        patch = sat_imsmb.isel(\n",
+    "            y=slice(row - half, row + half + 1),\n",
+    "            x=slice(col - half, col + half + 1)\n",
+    "        ).values\n",
+    "\n",
+    "        # Check if patch is entirely zero\n",
+    "        if np.all(patch == 0):\n",
+    "            zero_patch_coords.append((x, y))\n",
+    "\n",
+    "# Convert to arrays\n",
+    "zero_x, zero_y = zip(*zero_patch_coords) if zero_patch_coords else ([], [])\n",
+    "print(len(zero_patch_coords))\n",
+    "# Plot\n",
+    "fig, ax = plt.subplots(figsize=(10, 8))\n",
+    "sat_imsmb.sel(band=1).plot.imshow(ax=ax, cmap='gray', alpha=0.4)\n",
+    "\n",
+    "# Overlay zero-patch points\n",
+    "ax.scatter(zero_x, zero_y, marker='.', color='red', s=10, label=\"Zero Patches\")\n",
+    "\n",
+    "ax.set_title(\"Patches with All-Zero Values\")\n",
+    "ax.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "81a25ec3-a5df-4156-b600-f48f51b49d0f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "# Extract the image patches\n",
+    "x_coords, y_coords = training_data_ds['EAST'].values, training_data_ds['NORTH'].values\n",
+    "images = training_data_ds['smb_images'].values\n",
+    "values = training_data_ds['smb'].values\n",
+    "is_all_zero = np.all(images == 0, axis=(1, 2))\n",
+    "\n",
+    "# Get corresponding coordinates\n",
+    "zero_x = x_coords[is_all_zero]\n",
+    "zero_y = y_coords[is_all_zero]\n",
+    "print(values[is_all_zero])\n",
+    "\n",
+    "x_center, y_center = transformz * (aggregated_data['pixel_col'].values, aggregated_data['pixel_row'])\n",
+    "\n",
+    "# Plot\n",
+    "fig, ax = plt.subplots(figsize=(10, 8))\n",
+    "sat_imv.sel(band=1).plot.imshow(ax=ax, cmap='gray', alpha=0.4)\n",
+    "ax.scatter(x_coords, y_coords, color='green', s=1, label=\"Datapoints\")\n",
+    "\n",
+    "ax.scatter(x_center, y_center, color='green', s=1, label=\"Datapoints\")\n",
+    "gdf.plot(ax=ax, color='blue', markersize=0.5, label='gdf points', alpha=0.5)\n",
+    "ax.scatter(zero_x, zero_y, color='red', s=1, label=\"Zero Patches\")\n",
+    "ax.set_title(\"All-Zero Patches from `training_data_ds`\")\n",
+    "ax.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "ff009162-896f-4ca5-a44c-ee53e4cc0231",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compute basic stats over all samples\n",
+    "min_vals = training_data_ds['smb_images'].min(dim=['x', 'y'])\n",
+    "max_vals = training_data_ds['smb_images'].max(dim=['x', 'y'])\n",
+    "mean_vals = training_data_ds['smb_images'].mean(dim=['x', 'y'])\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.figure(figsize=(12, 4))\n",
+    "\n",
+    "plt.subplot(1, 3, 1)\n",
+    "plt.hist(min_vals.values, bins=50, color='blue', edgecolor='black')\n",
+    "plt.title(\"Min value per image\")\n",
+    "\n",
+    "plt.subplot(1, 3, 2)\n",
+    "plt.hist(max_vals.values, bins=50, color='green', edgecolor='black')\n",
+    "plt.title(\"Max value per image\")\n",
+    "\n",
+    "plt.subplot(1, 3, 3)\n",
+    "plt.hist(mean_vals.values, bins=50, color='red', edgecolor='black')\n",
+    "plt.title(\"Mean value per image\")\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "3e45d006-5da3-4cc5-9fe0-bcb91cba9e7b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Extract image means\n",
+    "image_means = training_data_ds['v_images'].mean(dim=('x', 'y')).values\n",
+    "scalars = training_data_ds['v'].values\n",
+    "\n",
+    "# Compute difference\n",
+    "diff = scalars - image_means\n",
+    "\n",
+    "# Correlation\n",
+    "correlation = np.corrcoef(scalars, image_means)[0, 1]\n",
+    "\n",
+    "# Plot comparison\n",
+    "plt.figure(figsize=(14, 5))\n",
+    "\n",
+    "# Scatter plot\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.scatter(np.array(scalars), np.array(image_means), s=5, alpha=0.1)\n",
+    "plt.plot([min(scalars),max(scalars)],[min(scalars),max(scalars)], color='r', ls='--',alpha=0.5)\n",
+    "plt.xlabel(\"Scalar\")\n",
+    "plt.ylabel(\"Image (mean of patch)\")\n",
+    "plt.title(f\"Scalar vs Image Mean (r = {correlation:.3f})\")\n",
+    "plt.grid(True)\n",
+    "\n",
+    "# Histogram of differences\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.hist(np.array(diff)/max(scalars), bins=50, color='purple', alpha=0.7)\n",
+    "plt.axvline(np.mean(diff)/max(scalars), color='red', linestyle='--', label=f\"Mean diff = {np.mean(diff):.2f}\")\n",
+    "plt.xlabel(\"Scalar - Image mean %\")\n",
+    "plt.ylabel(\"Frequency\")\n",
+    "plt.title(\"Difference Histogram\")\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "c0812faa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "training_data_ds.to_netcdf(Path.cwd().parent / 'finalprojectdata' / 'conv_train_allimages.nc')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bdb4d03a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_import = xr.open_dataset(Path.cwd().parent / 'finalprojectdata' / 'conv_train_2.nc') "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "6bf789a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
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+       "  --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",
+       "html[data-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 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\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:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\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; Size: 2GB\n",
+       "Dimensions:      (x: 27, y: 27, sample: 148505)\n",
+       "Coordinates:\n",
+       "  * x            (x) int64 216B 0 1 2 3 4 5 6 7 8 ... 18 19 20 21 22 23 24 25 26\n",
+       "  * y            (y) int64 216B 0 1 2 3 4 5 6 7 8 ... 18 19 20 21 22 23 24 25 26\n",
+       "  * sample       (sample) int64 1MB 0 1 2 3 4 ... 148501 148502 148503 148504\n",
+       "Data variables: (12/16)\n",
+       "    z_images     (sample, x, y) float32 433MB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    v_images     (sample, x, y) float32 433MB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    smb_images   (sample, x, y) float32 433MB nan nan nan nan ... nan nan nan\n",
+       "    temp_images  (sample, x, y) float64 866MB 262.8 262.8 262.7 ... 260.7 260.7\n",
+       "    labels       (sample) float64 1MB 281.2 214.0 273.9 ... 239.0 373.9 235.9\n",
+       "    EAST         (sample) float64 1MB -1.091e+04 2.12e+03 ... 1.078e+06\n",
+       "    ...           ...\n",
+       "    smb          (sample) float64 1MB 428.9 434.6 434.9 ... 376.1 465.3 459.6\n",
+       "    z            (sample) float64 1MB 25.95 22.24 26.59 ... 13.47 29.86 25.5\n",
+       "    s            (sample) float64 1MB 0.0007497 0.001448 ... 0.01696 0.005734\n",
+       "    temp         (sample) float64 1MB 260.8 260.7 259.4 ... 257.2 259.6 260.0\n",
+       "    ith_bm       (sample) float64 1MB 240.9 206.2 247.0 ... 129.4 282.5 241.8\n",
+       "    gridCellId   (sample) float64 1MB 260.0 260.0 260.0 260.0 ... 11.0 11.0 11.0\n",
+       "Attributes:\n",
+       "    description:  CNN data with averaged scalar features and one image per pi...</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-2a823332-18af-465f-93f8-a18ec60ca59d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2a823332-18af-465f-93f8-a18ec60ca59d' 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'>x</span>: 27</li><li><span class='xr-has-index'>y</span>: 27</li><li><span class='xr-has-index'>sample</span>: 148505</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4be1634b-438a-416c-ae43-1c9fe70324b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4be1634b-438a-416c-ae43-1c9fe70324b7' 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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 21 22 23 24 25 26</div><input id='attrs-31feb8ee-9a8c-4d44-bc6a-c148bf40ef9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-31feb8ee-9a8c-4d44-bc6a-c148bf40ef9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9044722a-c18a-4737-8844-acb469a07eec' class='xr-var-data-in' type='checkbox'><label for='data-9044722a-c18a-4737-8844-acb469a07eec' 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,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+       "       18, 19, 20, 21, 22, 23, 24, 25, 26])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 21 22 23 24 25 26</div><input id='attrs-9e32e690-badf-4692-86ac-9d68c0315d28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e32e690-badf-4692-86ac-9d68c0315d28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83a4493e-e7b4-4876-a4ba-2726b7c11509' class='xr-var-data-in' type='checkbox'><label for='data-83a4493e-e7b4-4876-a4ba-2726b7c11509' 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,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+       "       18, 19, 20, 21, 22, 23, 24, 25, 26])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sample</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 148502 148503 148504</div><input id='attrs-b2219a17-9c37-49b3-ab48-9c7b7fc6f4cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2219a17-9c37-49b3-ab48-9c7b7fc6f4cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-259f0745-64b0-4112-92fd-69a069fa7c6d' class='xr-var-data-in' type='checkbox'><label for='data-259f0745-64b0-4112-92fd-69a069fa7c6d' 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, ..., 148502, 148503, 148504])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8a7b5785-16e5-4ad3-8c18-b27c8c2168d3' class='xr-section-summary-in' type='checkbox'  ><label for='section-8a7b5785-16e5-4ad3-8c18-b27c8c2168d3' class='xr-section-summary' >Data variables: <span>(16)</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>z_images</span></div><div class='xr-var-dims'>(sample, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-68cab557-b267-4d0f-a61a-520ac7669cfe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68cab557-b267-4d0f-a61a-520ac7669cfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97fb255a-23b4-4aa5-9a1b-c3e5187cd0b2' class='xr-var-data-in' type='checkbox'><label for='data-97fb255a-23b4-4aa5-9a1b-c3e5187cd0b2' 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([[[0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        ...,\n",
+       "        [1.7082745e+01, 1.7705540e+01, 1.7536556e+01, ...,\n",
+       "         8.0005679e-04, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [1.8374014e+01, 2.3346291e+01, 2.1388363e+01, ...,\n",
+       "         0.0000000e+00, 8.0602950e-01, 5.2883997e+00],\n",
+       "        [2.4387648e+01, 2.4661743e+01, 2.3212154e+01, ...,\n",
+       "         1.8431128e+00, 9.8002462e+00, 2.0601597e+01]],\n",
+       "\n",
+       "       [[0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "...\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00]],\n",
+       "\n",
+       "       [[4.0468723e+01, 3.6838036e+01, 3.5055271e+01, ...,\n",
+       "         3.0266846e+01, 3.1639317e+01, 2.8394480e+01],\n",
+       "        [3.5715626e+01, 3.6469788e+01, 3.6568867e+01, ...,\n",
+       "         2.7259031e+01, 3.0618822e+01, 2.8830671e+01],\n",
+       "        [4.3182484e+01, 3.5919415e+01, 3.5038136e+01, ...,\n",
+       "         2.7449829e+01, 3.1176653e+01, 2.0521715e+01],\n",
+       "        ...,\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00],\n",
+       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
+       "         0.0000000e+00, 0.0000000e+00, 0.0000000e+00]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_images</span></div><div class='xr-var-dims'>(sample, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-f589906c-7e89-42aa-9b69-f50732fc5d53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f589906c-7e89-42aa-9b69-f50732fc5d53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f386704-9ef3-4f8c-9a4d-b3a6c399eb87' class='xr-var-data-in' type='checkbox'><label for='data-7f386704-9ef3-4f8c-9a4d-b3a6c399eb87' 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.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        ...,\n",
+       "        [711.9202  , 709.30005 , 710.2961  , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [707.53784 , 705.143   , 706.2532  , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [703.4031  , 700.8299  , 701.00946 , ...,   0.      ,\n",
+       "         501.75317 , 552.7642  ]],\n",
+       "\n",
+       "       [[  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "...\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ]],\n",
+       "\n",
+       "       [[102.35082 ,  99.48862 , 141.2029  , ..., 794.79626 ,\n",
+       "         803.1036  , 807.56976 ],\n",
+       "        [126.39434 , 127.91764 , 147.22377 , ..., 798.14557 ,\n",
+       "         805.9463  , 816.6959  ],\n",
+       "        [146.98853 , 146.81374 , 157.671   , ..., 795.9662  ,\n",
+       "         809.0107  , 818.1636  ],\n",
+       "        ...,\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ],\n",
+       "        [  0.      ,   0.      ,   0.      , ...,   0.      ,\n",
+       "           0.      ,   0.      ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smb_images</span></div><div class='xr-var-dims'>(sample, x, y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d32a580e-c478-4166-9106-5bc637edb5bf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d32a580e-c478-4166-9106-5bc637edb5bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-528011e5-cbb7-4ae3-a035-0e1afcb77df7' class='xr-var-data-in' type='checkbox'><label for='data-528011e5-cbb7-4ae3-a035-0e1afcb77df7' 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([[[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        ...,\n",
+       "        [367.2912 , 373.71365, 378.51422, ..., 432.50476, 432.7109 ,\n",
+       "         437.77533],\n",
+       "        [367.2939 , 374.876  , 378.83206, ..., 426.24203, 426.90213,\n",
+       "         430.26694],\n",
+       "        [369.83798, 375.0514 , 377.66675, ..., 420.37274, 423.25293,\n",
+       "         426.12405]],\n",
+       "\n",
+       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "...\n",
+       "        [452.8358 , 446.50705, 438.98804, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [452.78   , 446.46274, 438.93445, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]],\n",
+       "\n",
+       "       [[333.13358, 352.89426, 372.032  , ..., 601.9798 , 606.85254,\n",
+       "         611.4539 ],\n",
+       "        [325.66968, 344.48892, 363.15698, ..., 599.9885 , 604.8607 ,\n",
+       "         609.4582 ],\n",
+       "        [327.39072, 343.3884 , 359.97427, ..., 598.2151 , 603.0016 ,\n",
+       "         607.35516],\n",
+       "        ...,\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_images</span></div><div class='xr-var-dims'>(sample, x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>262.8 262.8 262.7 ... 260.7 260.7</div><input id='attrs-1f7ab923-2fde-44e2-b0bd-1f2d514fda1a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f7ab923-2fde-44e2-b0bd-1f2d514fda1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bedc545d-2c0d-45f0-ba74-f812945650a9' class='xr-var-data-in' type='checkbox'><label for='data-bedc545d-2c0d-45f0-ba74-f812945650a9' 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([[[262.78265722, 262.75042753, 262.71456836, ..., 262.40669152,\n",
+       "         262.42937522, 262.45190995],\n",
+       "        [262.74693509, 262.70985341, 262.66883915, ..., 262.35904372,\n",
+       "         262.38634473, 262.41302505],\n",
+       "        [262.67453265, 262.63223238, 262.58602818, ..., 262.29908009,\n",
+       "         262.33099831, 262.36144258],\n",
+       "        ...,\n",
+       "        [259.52561481, 259.4061473 , 259.27419429, ..., 259.71121091,\n",
+       "         259.65322231, 259.67096003],\n",
+       "        [259.3633298 , 259.24675628, 259.11789858, ..., 259.48986604,\n",
+       "         259.37984938, 259.38385847],\n",
+       "        [259.20113564, 259.08730548, 258.96164712, ..., 259.25932299,\n",
+       "         259.11328635, 259.10714251]],\n",
+       "\n",
+       "       [[262.54571026, 262.50585499, 262.47317404, ..., 262.48661758,\n",
+       "         262.49811972, 262.50115317],\n",
+       "        [262.45274626, 262.41105522, 262.37698114, ..., 262.44108401,\n",
+       "         262.45343167, 262.45684642],\n",
+       "        [262.35982184, 262.31629051, 262.2807523 , ..., 262.39557535,\n",
+       "         262.40876111, 262.41254273],\n",
+       "...\n",
+       "        [258.79714558, 258.89609344, 259.02207177, ..., 260.63389731,\n",
+       "         260.62818032, 260.62326715],\n",
+       "        [258.96653289, 259.05452842, 259.1648991 , ..., 260.65715595,\n",
+       "         260.65017766, 260.64423013],\n",
+       "        [259.13563523, 259.21752496, 259.31424585, ..., 260.67843231,\n",
+       "         260.66927468, 260.66267945]],\n",
+       "\n",
+       "       [[256.28619791, 256.44072339, 256.58792577, ..., 258.67485239,\n",
+       "         258.75207758, 258.82206993],\n",
+       "        [256.4154199 , 256.60184685, 256.76832921, ..., 258.89923666,\n",
+       "         258.97844192, 259.04438661],\n",
+       "        [256.55735557, 256.76174418, 256.94204838, ..., 259.11433064,\n",
+       "         259.18214973, 259.22873559],\n",
+       "        ...,\n",
+       "        [259.37555022, 259.4533405 , 259.53168042, ..., 260.68759326,\n",
+       "         260.68101966, 260.67631438],\n",
+       "        [259.5006654 , 259.55195587, 259.6128603 , ..., 260.70519777,\n",
+       "         260.69816352, 260.6935474 ],\n",
+       "        [259.59494503, 259.64319897, 259.69932183, ..., 260.72204324,\n",
+       "         260.71456166, 260.70920057]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>labels</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>281.2 214.0 273.9 ... 373.9 235.9</div><input id='attrs-adb968e4-e34d-4fbd-a3a3-5eceec485748' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adb968e4-e34d-4fbd-a3a3-5eceec485748' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0fd25d7-cf86-4124-94f7-52dcc65f73d6' class='xr-var-data-in' type='checkbox'><label for='data-b0fd25d7-cf86-4124-94f7-52dcc65f73d6' 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([281.2 , 214.  , 273.9 , ..., 239.04, 373.94, 235.87])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EAST</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.091e+04 2.12e+03 ... 1.078e+06</div><input id='attrs-0fa14e83-6850-4ed1-92d4-3c8188a59987' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0fa14e83-6850-4ed1-92d4-3c8188a59987' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a4a8fa5-5fa5-4e68-9b9e-4ccb5043f292' class='xr-var-data-in' type='checkbox'><label for='data-0a4a8fa5-5fa5-4e68-9b9e-4ccb5043f292' 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([ -10905.71490202,    2120.10742971,  -21326.3727674 , ...,\n",
+       "       1044185.89396795, 1075447.8675641 , 1078053.03203045])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NORTH</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.228e+06 2.226e+06 ... -2.127e+06</div><input id='attrs-47120b7b-3daa-4230-976a-323f71e14dc0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-47120b7b-3daa-4230-976a-323f71e14dc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be96fb2a-e323-43ef-94cc-23c0484d4b26' class='xr-var-data-in' type='checkbox'><label for='data-be96fb2a-e323-43ef-94cc-23c0484d4b26' 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([ 2228413.37211782,  2225808.20765147,  2212782.38531975, ...,\n",
+       "       -2114395.7932803 , -2119606.12221299, -2127421.61561203])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vx</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-162.0 -153.3 ... 332.8 336.6</div><input id='attrs-6ce82322-b690-4ee1-964d-66362ce79953' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ce82322-b690-4ee1-964d-66362ce79953' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc5f302-030e-4827-9b5b-b15531991dd7' class='xr-var-data-in' type='checkbox'><label for='data-2cc5f302-030e-4827-9b5b-b15531991dd7' 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([-161.99590496, -153.30288312, -162.76223021, ...,   62.74567784,\n",
+       "        332.8383528 ,  336.56345018])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vy</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>746.4 761.1 726.3 ... -628.4 -637.6</div><input id='attrs-03ad6f85-d1b8-4178-9037-b4c0dae4eaa6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-03ad6f85-d1b8-4178-9037-b4c0dae4eaa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f07beea7-cff5-4cca-b79e-de9f2ab71520' class='xr-var-data-in' type='checkbox'><label for='data-f07beea7-cff5-4cca-b79e-de9f2ab71520' 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([ 746.39772057,  761.14367243,  726.28250995, ...,  -58.39111938,\n",
+       "       -628.43012854, -637.56648753])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>763.8 776.4 744.3 ... 711.1 720.9</div><input id='attrs-a85d6cae-a388-4608-840f-681a996fd285' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a85d6cae-a388-4608-840f-681a996fd285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3854120-8b00-4b91-8a9c-440342a01923' class='xr-var-data-in' type='checkbox'><label for='data-d3854120-8b00-4b91-8a9c-440342a01923' 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([763.77498683, 776.42865999, 744.29686808, ...,  85.71197646,\n",
+       "       711.1299428 , 720.94797456])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smb</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>428.9 434.6 434.9 ... 465.3 459.6</div><input id='attrs-4e990579-9e67-44b1-9232-4c24e74a4eb3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e990579-9e67-44b1-9232-4c24e74a4eb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e1eb006-9d9b-4c96-8e4b-cee6dfe30e74' class='xr-var-data-in' type='checkbox'><label for='data-5e1eb006-9d9b-4c96-8e4b-cee6dfe30e74' 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([428.87433598, 434.55229646, 434.93751893, ..., 376.06726179,\n",
+       "       465.34065605, 459.56618505])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.95 22.24 26.59 ... 29.86 25.5</div><input id='attrs-9b17cc9d-5517-4c0c-98ec-6f252b654677' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b17cc9d-5517-4c0c-98ec-6f252b654677' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64700c0a-6fd9-499f-ac50-c0cc7af76110' class='xr-var-data-in' type='checkbox'><label for='data-64700c0a-6fd9-499f-ac50-c0cc7af76110' 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([25.95130967, 22.23970848, 26.59351251, ..., 13.47093109,\n",
+       "       29.86251046, 25.50161153])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>s</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0007497 0.001448 ... 0.005734</div><input id='attrs-5c14f7d2-9ad2-464c-b9c6-7eab523698e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c14f7d2-9ad2-464c-b9c6-7eab523698e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26f29923-f335-4fc9-b96a-80d0982ea1a8' class='xr-var-data-in' type='checkbox'><label for='data-26f29923-f335-4fc9-b96a-80d0982ea1a8' 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([0.00074971, 0.00144761, 0.00374135, ..., 0.00629617, 0.01696483,\n",
+       "       0.00573413])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>260.8 260.7 259.4 ... 259.6 260.0</div><input id='attrs-16588226-0c57-4668-8931-82956ee5d7f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16588226-0c57-4668-8931-82956ee5d7f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07bd2435-59ce-40a0-b379-5abb0a840638' class='xr-var-data-in' type='checkbox'><label for='data-07bd2435-59ce-40a0-b379-5abb0a840638' 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([260.77134628, 260.65433532, 259.4486686 , ..., 257.23016897,\n",
+       "       259.59469537, 259.96645018])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ith_bm</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>240.9 206.2 247.0 ... 282.5 241.8</div><input id='attrs-7590de9f-841d-45e8-b527-1f73dd918eec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7590de9f-841d-45e8-b527-1f73dd918eec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-897c118f-d612-47f0-9b05-807a9aca69df' class='xr-var-data-in' type='checkbox'><label for='data-897c118f-d612-47f0-9b05-807a9aca69df' 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([240.8875826 , 206.21611391, 246.97271624, ..., 129.41278019,\n",
+       "       282.51973245, 241.79668549])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gridCellId</span></div><div class='xr-var-dims'>(sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>260.0 260.0 260.0 ... 11.0 11.0</div><input id='attrs-5dc9ea95-e21b-42bd-948b-9803d6a1d0e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5dc9ea95-e21b-42bd-948b-9803d6a1d0e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78c25d8f-de96-463f-953a-834670eb7e55' class='xr-var-data-in' type='checkbox'><label for='data-78c25d8f-de96-463f-953a-834670eb7e55' 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([260., 260., 260., ...,  11.,  11.,  11.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4da8771a-5254-411a-916d-49e245159793' class='xr-section-summary-in' type='checkbox'  ><label for='section-4da8771a-5254-411a-916d-49e245159793' 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>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4bb0a1c1-b058-4c75-8ae8-2daa47bb639e' class='xr-index-data-in' type='checkbox'/><label for='index-4bb0a1c1-b058-4c75-8ae8-2daa47bb639e' 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, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+       "       18, 19, 20, 21, 22, 23, 24, 25, 26],\n",
+       "      dtype=&#x27;int64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-18f268d4-2071-42f7-911e-7b323475afa1' class='xr-index-data-in' type='checkbox'/><label for='index-18f268d4-2071-42f7-911e-7b323475afa1' 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, 10, 11, 12, 13, 14, 15, 16, 17,\n",
+       "       18, 19, 20, 21, 22, 23, 24, 25, 26],\n",
+       "      dtype=&#x27;int64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>sample</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-965791e8-9c16-4223-872d-3cb8b82b6e8e' class='xr-index-data-in' type='checkbox'/><label for='index-965791e8-9c16-4223-872d-3cb8b82b6e8e' 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,\n",
+       "            9,\n",
+       "       ...\n",
+       "       148495, 148496, 148497, 148498, 148499, 148500, 148501, 148502, 148503,\n",
+       "       148504],\n",
+       "      dtype=&#x27;int64&#x27;, name=&#x27;sample&#x27;, length=148505))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-94f0bf51-09e9-470a-9fcf-109e8fc46325' class='xr-section-summary-in' type='checkbox'  checked><label for='section-94f0bf51-09e9-470a-9fcf-109e8fc46325' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>CNN data with averaged scalar features and one image per pixel.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:      (x: 27, y: 27, sample: 148505)\n",
+       "Coordinates:\n",
+       "  * x            (x) int64 216B 0 1 2 3 4 5 6 7 8 ... 18 19 20 21 22 23 24 25 26\n",
+       "  * y            (y) int64 216B 0 1 2 3 4 5 6 7 8 ... 18 19 20 21 22 23 24 25 26\n",
+       "  * sample       (sample) int64 1MB 0 1 2 3 4 ... 148501 148502 148503 148504\n",
+       "Data variables: (12/16)\n",
+       "    z_images     (sample, x, y) float32 433MB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    v_images     (sample, x, y) float32 433MB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
+       "    smb_images   (sample, x, y) float32 433MB nan nan nan nan ... nan nan nan\n",
+       "    temp_images  (sample, x, y) float64 866MB 262.8 262.8 262.7 ... 260.7 260.7\n",
+       "    labels       (sample) float64 1MB 281.2 214.0 273.9 ... 239.0 373.9 235.9\n",
+       "    EAST         (sample) float64 1MB -1.091e+04 2.12e+03 ... 1.078e+06\n",
+       "    ...           ...\n",
+       "    smb          (sample) float64 1MB 428.9 434.6 434.9 ... 376.1 465.3 459.6\n",
+       "    z            (sample) float64 1MB 25.95 22.24 26.59 ... 13.47 29.86 25.5\n",
+       "    s            (sample) float64 1MB 0.0007497 0.001448 ... 0.01696 0.005734\n",
+       "    temp         (sample) float64 1MB 260.8 260.7 259.4 ... 257.2 259.6 260.0\n",
+       "    ith_bm       (sample) float64 1MB 240.9 206.2 247.0 ... 129.4 282.5 241.8\n",
+       "    gridCellId   (sample) float64 1MB 260.0 260.0 260.0 260.0 ... 11.0 11.0 11.0\n",
+       "Attributes:\n",
+       "    description:  CNN data with averaged scalar features and one image per pi..."
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "training_data_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a1e044e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p = gdf.iloc[0].geometry\n",
+    "\n",
+    "transform = sat_im.rio.transform()\n",
+    "\n",
+    "col, row = ~transform * (p.x, p.y)\n",
+    "\n",
+    "col, row = int(np.floor(col)), int(np.floor(row))\n",
+    "\n",
+    "print(p.x, p.y)\n",
+    "\n",
+    "print(sat_im.surface[0][row][col].x, sat_im.surface[0][row][col].y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9ac2f290",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import inspect\n",
+    "\n",
+    "source_file_path = inspect.getsourcefile(type(sat_im.surface.rio.transform()))\n",
+    "print(f\"\\nSource file path for Affine class: {source_file_path}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "appmlenv",
+   "language": "python",
+   "name": "appmlenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}