interval-array.ipynb

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   "source": [
    "# IntervalIndex experiment"
   ]
  },
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     "text": [
      "numpy : 1.26.4\n",
      "xarray: 2024.5.0\n",
      "pandas: 2.2.2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "\n",
    "%watermark -iv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "153621a6-27fd-4635-a27b-390526fdf188",
   "metadata": {},
   "source": [
    "## Example data"
   ]
  },
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   "id": "22c5360e-5ff0-44b3-b3b0-dcf739097f43",
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    "tags": []
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 376B\n",
       "Dimensions:      (time: 5, x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 32B 1 2 3 4\n",
       "    x_bounds     (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "    time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 160B 0 1 2 3 4 5 6 7 ... 13 14 15 16 17 18 19</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-2193a172-6bcc-456c-9867-74b506167eef' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2193a172-6bcc-456c-9867-74b506167eef' 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'>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 4</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c0d95a9e-138e-474d-9dcb-46ec885f4c53' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c0d95a9e-138e-474d-9dcb-46ec885f4c53' class='xr-section-summary' >Coordinates: <span>(4)</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'>1 2 3 4</div><input id='attrs-5fada95c-d2e4-4ce5-809d-0d86d7d49f23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fada95c-d2e4-4ce5-809d-0d86d7d49f23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d111b15e-daaf-479c-97a0-590ff06a0bf7' class='xr-var-data-in' type='checkbox'><label for='data-d111b15e-daaf-479c-97a0-590ff06a0bf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>x_bounds</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x_bounds</span></div><div class='xr-var-dims'>(bnds, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5</div><input id='attrs-38b4311c-b29c-43d3-b5e0-c091476645c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38b4311c-b29c-43d3-b5e0-c091476645c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-913fe9d4-e38d-4015-9c32-a6ed0a8fc03d' class='xr-var-data-in' type='checkbox'><label for='data-913fe9d4-e38d-4015-9c32-a6ed0a8fc03d' 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([[0.5, 1.5, 2.5, 3.5],\n",
       "       [1.5, 2.5, 3.5, 4.5]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2001-01-01 ... 2001-01-05</div><input id='attrs-482a0736-53c8-4a8c-a4f7-43f7944efae4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-482a0736-53c8-4a8c-a4f7-43f7944efae4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcca73e9-7676-4bd8-bc0b-cc84af4845b7' class='xr-var-data-in' type='checkbox'><label for='data-bcca73e9-7676-4bd8-bc0b-cc84af4845b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-01-01T00:00:00.000000000&#x27;, &#x27;2001-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-03T00:00:00.000000000&#x27;, &#x27;2001-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-05T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(bnds, time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-12-31T12:00:00 ... 2001-01-...</div><input id='attrs-ffa9ba08-c94e-4c08-90d6-36b88d613aca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ffa9ba08-c94e-4c08-90d6-36b88d613aca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-853a15df-a538-4f3d-b690-899556ad5b7a' class='xr-var-data-in' type='checkbox'><label for='data-853a15df-a538-4f3d-b690-899556ad5b7a' 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([[&#x27;2000-12-31T12:00:00.000000000&#x27;, &#x27;2001-01-01T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-02T12:00:00.000000000&#x27;, &#x27;2001-01-03T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-04T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2001-01-01T12:00:00.000000000&#x27;, &#x27;2001-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-03T12:00:00.000000000&#x27;, &#x27;2001-01-04T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-05T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-15d31429-525c-421a-a911-a30ced7239a9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-15d31429-525c-421a-a911-a30ced7239a9' class='xr-section-summary' >Data variables: <span>(1)</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>data</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 14 15 16 17 18 19</div><input id='attrs-8a863e80-c46c-4b05-b09b-b66de66b1981' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a863e80-c46c-4b05-b09b-b66de66b1981' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef052eb3-a4c7-4490-b9f2-704b1e06166b' class='xr-var-data-in' type='checkbox'><label for='data-ef052eb3-a4c7-4490-b9f2-704b1e06166b' 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],\n",
       "       [ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11],\n",
       "       [12, 13, 14, 15],\n",
       "       [16, 17, 18, 19]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de5d40e4-e0d9-4698-a388-0c877cc370b5' class='xr-section-summary-in' type='checkbox'  ><label for='section-de5d40e4-e0d9-4698-a388-0c877cc370b5' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-da4eec7e-98be-479a-a605-51bf882d19d6' class='xr-index-data-in' type='checkbox'/><label for='index-da4eec7e-98be-479a-a605-51bf882d19d6' 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([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-29656d96-4933-4bd7-92dc-5037775a6a68' class='xr-index-data-in' type='checkbox'/><label for='index-29656d96-4933-4bd7-92dc-5037775a6a68' 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(DatetimeIndex([&#x27;2001-01-01&#x27;, &#x27;2001-01-02&#x27;, &#x27;2001-01-03&#x27;, &#x27;2001-01-04&#x27;,\n",
       "               &#x27;2001-01-05&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dfa3434e-0923-4aab-93a9-f296d98d46d6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dfa3434e-0923-4aab-93a9-f296d98d46d6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 376B\n",
       "Dimensions:      (time: 5, x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 32B 1 2 3 4\n",
       "    x_bounds     (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "    time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 160B 0 1 2 3 4 5 6 7 ... 13 14 15 16 17 18 19"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "left = np.arange(0.5, 3.6, 1)\n",
    "right = np.arange(1.5, 4.6, 1)\n",
    "bounds = np.stack([left, right])\n",
    "\n",
    "ds = xr.Dataset(\n",
    "    {\"data\": ((\"time\", \"x\"), np.arange(20).reshape(5, 4))},\n",
    "    coords={\"x\": (\"x\", [1, 2, 3, 4], {\"bounds\": \"x_bounds\"}), \"x_bounds\": ((\"bnds\", \"x\"), bounds)},\n",
    ")\n",
    "tindex = pd.date_range(\"2001-01-01\", \"2001-01-05\", freq=\"D\")\n",
    "left = tindex - pd.DateOffset(hours=12)\n",
    "right = tindex + pd.DateOffset(hours=12)\n",
    "tbounds = np.stack([left, right])\n",
    "ds.coords[\"time\"] = (\"time\", tindex, {\"bounds\": \"time_bounds\"})\n",
    "ds.coords[\"time_bounds\"] = ((\"bnds\", \"time\"), tbounds)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bc53e69-0664-4e60-9a89-102dcc8e75b1",
   "metadata": {},
   "source": [
    "## Approach 1. Dropping bounds variable"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6810a79e-0906-4206-a289-47397784b9cb",
   "metadata": {},
   "source": [
    "### From [benbovy](https://github.com/pydata/xarray/discussions/7041#discussioncomment-4936891)\n",
    "\n",
    "I think one of the best approaches would be to have a custom Xarray IntervalIndex that only supports a unique 1-d coordinate.\n",
    "\n",
    "That said, an extension array adaptor like the one at the end of @dcherian's notebook would be nice to have. As another example, geopandas uses extension arrays for the geometry columns so this could be useful for other cases like martinfleis/xvec.\n",
    "\n",
    "Perhaps something like this could work for IntervalIndex:\n",
    "\n",
    "1. Expose a custom xarray.indexes.IntervalIndex that wraps a pd.IntervalIndex\n",
    "    - Like for PandasIndex, its corresponding 1-d coordinate wraps the pandas index in a xarray.core.indexing.PandasIndexingAdapter\n",
    "    - It could actually be implemented as a subclass of PandasIndex?\n",
    "2. How to use set_xindex?\n",
    "    - obj.set_xindex(\"x\", IntervalIndex) where \"x\" is a 1-d coordinate (if it wraps an pd.arrays.IntervalArray or a pd.IntervalIndex just reuse it, otherwise create a new pandas interval index with default bounds).\n",
    "    - obj.set_xindex(\"x\", IntervalIndex, use_bounds_coord=\"x_bounds\") where use_bounds_coord is an option specific to the Xarray IntervalIndex. In this case the \"x_bounds\" coordinate remains unindexed, it could be manually removed after creating the index.\n",
    "2. Getting back the bounds coordinate, e.g., with something like obj.assign(x_bounds=obj.xindexes[\"x\"].get_bounds_coord())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d82258d1-afad-49a7-bef5-6a205862bcc0",
   "metadata": {},
   "source": [
    "#### TODO\n",
    "\n",
    "1. pd.IntervalIndex cannot support alternative \"central\" values. We'll need a more involved approach to do that.\n",
    "2. We'll need a \"decoding\" function to break this in to two variables prior to writing to disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1d257b30-685b-4510-9a6b-9e7f55d8ac66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.arrays.interval.IntervalArray"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.arrays.IntervalArray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "0b247925-d61c-4e2a-8692-d62648d73fdc",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       ".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: 376B\n",
       "Dimensions:      (time: 5, x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 32B 1 2 3 4\n",
       "  * x_bounds     (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 160B 0 1 2 3 4 5 6 7 ... 13 14 15 16 17 18 19</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-5b99ea17-0b68-4d02-babb-9f6cb4ada4ba' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5b99ea17-0b68-4d02-babb-9f6cb4ada4ba' 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'>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 4</li><li><span class='xr-has-index'>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-87bd118e-1db3-4dad-93fd-b0ca8ed250da' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87bd118e-1db3-4dad-93fd-b0ca8ed250da' class='xr-section-summary' >Coordinates: <span>(4)</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'>1 2 3 4</div><input id='attrs-b0d453e5-7489-41f4-a556-5198309c26ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d453e5-7489-41f4-a556-5198309c26ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2638f141-f9a4-46ec-91a8-908ff3a91880' class='xr-var-data-in' type='checkbox'><label for='data-2638f141-f9a4-46ec-91a8-908ff3a91880' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>x_bounds</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_bounds</span></div><div class='xr-var-dims'>(bnds, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5</div><input id='attrs-118dc615-4ccb-46d1-90a0-bef07aff6383' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-118dc615-4ccb-46d1-90a0-bef07aff6383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62fe7ba3-f810-413c-a32f-116578d6e0e7' class='xr-var-data-in' type='checkbox'><label for='data-62fe7ba3-f810-413c-a32f-116578d6e0e7' 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([[0.5, 1.5, 2.5, 3.5],\n",
       "       [1.5, 2.5, 3.5, 4.5]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2001-01-01 ... 2001-01-05</div><input id='attrs-390ab196-47ba-4b09-a797-82ddc07e1aa2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390ab196-47ba-4b09-a797-82ddc07e1aa2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-132f8dfb-7177-4a49-a392-9c7a932df4ee' class='xr-var-data-in' type='checkbox'><label for='data-132f8dfb-7177-4a49-a392-9c7a932df4ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-01-01T00:00:00.000000000&#x27;, &#x27;2001-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-03T00:00:00.000000000&#x27;, &#x27;2001-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-05T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_bounds</span></div><div class='xr-var-dims'>(bnds, time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-12-31T12:00:00 ... 2001-01-...</div><input id='attrs-98eb4878-53d2-499a-9b15-34ab29414b63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98eb4878-53d2-499a-9b15-34ab29414b63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e41380b3-ee01-4a25-b520-61183be9f962' class='xr-var-data-in' type='checkbox'><label for='data-e41380b3-ee01-4a25-b520-61183be9f962' 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([[&#x27;2000-12-31T12:00:00.000000000&#x27;, &#x27;2001-01-01T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-02T12:00:00.000000000&#x27;, &#x27;2001-01-03T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-04T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2001-01-01T12:00:00.000000000&#x27;, &#x27;2001-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-03T12:00:00.000000000&#x27;, &#x27;2001-01-04T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-05T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-afaa68e4-3d48-4796-be64-f5614d56a259' class='xr-section-summary-in' type='checkbox'  checked><label for='section-afaa68e4-3d48-4796-be64-f5614d56a259' class='xr-section-summary' >Data variables: <span>(1)</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>data</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 14 15 16 17 18 19</div><input id='attrs-aed2a5ab-4496-4076-8f0b-e19f95a9cbae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aed2a5ab-4496-4076-8f0b-e19f95a9cbae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64c76c05-eafb-4ea7-8959-5d2eb356b7c7' class='xr-var-data-in' type='checkbox'><label for='data-64c76c05-eafb-4ea7-8959-5d2eb356b7c7' 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],\n",
       "       [ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11],\n",
       "       [12, 13, 14, 15],\n",
       "       [16, 17, 18, 19]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d57935d-6740-44a7-a9d4-bb7d217d32fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-4d57935d-6740-44a7-a9d4-bb7d217d32fc' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x<br>x_bounds</div></div><div class='xr-index-preview'>XarrayIntervalIndex</div><div></div><input id='index-e4fc49d6-669b-43b3-9949-9e7bdd064c21' class='xr-index-data-in' type='checkbox'/><label for='index-e4fc49d6-669b-43b3-9949-9e7bdd064c21' 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>XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype=&#x27;interval[float64, right]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time<br>time_bounds</div></div><div class='xr-index-preview'>XarrayIntervalIndex</div><div></div><input id='index-206cad30-0fe5-4c63-bfd8-99e8b77a950f' class='xr-index-data-in' type='checkbox'/><label for='index-206cad30-0fe5-4c63-bfd8-99e8b77a950f' 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>XarrayIntervalIndex([(2000-12-31 12:00:00, 2001-01-01 12:00:00],\n",
       "               (2001-01-01 12:00:00, 2001-01-02 12:00:00],\n",
       "               (2001-01-02 12:00:00, 2001-01-03 12:00:00],\n",
       "               (2001-01-03 12:00:00, 2001-01-04 12:00:00],\n",
       "               (2001-01-04 12:00:00, 2001-01-05 12:00:00]],\n",
       "              dtype=&#x27;interval[datetime64[ns], right]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab33f385-535b-49b9-9157-5a63cb997b2d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ab33f385-535b-49b9-9157-5a63cb997b2d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 376B\n",
       "Dimensions:      (time: 5, x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 32B 1 2 3 4\n",
       "  * x_bounds     (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 160B 0 1 2 3 4 5 6 7 ... 13 14 15 16 17 18 19"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xarray import Variable\n",
    "from xarray.indexes import Index, PandasIndex\n",
    "\n",
    "\n",
    "class XarrayIntervalIndex(PandasIndex):\n",
    "    def __init__(self, index, dim, coord_dtype):\n",
    "        assert isinstance(index, pd.IntervalIndex)\n",
    "\n",
    "        # for PandasIndex\n",
    "        self.index = index\n",
    "        self.dim = dim\n",
    "        self.coord_dtype = coord_dtype\n",
    "\n",
    "    @classmethod\n",
    "    def from_variables(cls, variables, options):\n",
    "        items = iter(variables.items())\n",
    "        dim, centers = next(items)\n",
    "        bounds_var_name, bounds = next(items)\n",
    "        assert centers.ndim == 1\n",
    "        assert bounds.ndim == 2\n",
    "        \n",
    "        assert isinstance(bounds, (xr.DataArray, xr.Variable))\n",
    "\n",
    "        (axis,) = bounds.get_axis_num(set(bounds.dims) - {dim})\n",
    "        left, right = np.split(bounds.data, 2, axis=axis)\n",
    "        index = pd.IntervalIndex.from_arrays(left.squeeze(), right.squeeze())\n",
    "        coord_dtype = bounds.dtype\n",
    "\n",
    "        return cls(index, dim, coord_dtype)\n",
    "\n",
    "    #def create_variables(self, variables):\n",
    "    #    from xarray.core.indexing import PandasIndexingAdapter\n",
    "         #   newvars = {\"x_bounds\": xr.Variable(self.dim, self.index.array)}\n",
    "    #    return newvars\n",
    "\n",
    "    def __repr__(self):\n",
    "        string = f\"Xarray{self.index!r}\"\n",
    "        return string\n",
    "\n",
    "    def to_pandas_index(self):\n",
    "        return self.index\n",
    "\n",
    "    @property\n",
    "    def mid(self):\n",
    "        return PandasIndex(self.dim, self.dim, self.coord_dtype)\n",
    "\n",
    "    @property\n",
    "    def left(self):\n",
    "        return PandasIndex(self.index.left, self.dim, self.coord_dtype)\n",
    "\n",
    "    @property\n",
    "    def right(self):\n",
    "        return PandasIndex(self.index.right, self.dim, self.coord_dtype)\n",
    "\n",
    "\n",
    "ds1 = (\n",
    "    ds.drop_indexes([\"x\", \"time\"])\n",
    "    .set_xindex([\"x\", \"x_bounds\"], XarrayIntervalIndex)\n",
    "    .set_xindex([\"time\", \"time_bounds\"], XarrayIntervalIndex)\n",
    "    #.drop_vars(\"x_bounds\")\n",
    ")\n",
    "ds1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "99046f3a-f07b-44ff-a1a9-7f2b862d186c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  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: 184B\n",
       "Dimensions:      (time: 5, x: 1, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 8B 1\n",
       "  * x_bounds     (bnds, x) float64 16B 0.5 1.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 40B 0 4 8 12 16</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-f8f1614d-3ae7-4db8-8f63-c667505defd3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f8f1614d-3ae7-4db8-8f63-c667505defd3' 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'>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 1</li><li><span class='xr-has-index'>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-182b4b6a-5355-4f70-a88c-190aedb4362a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-182b4b6a-5355-4f70-a88c-190aedb4362a' class='xr-section-summary' >Coordinates: <span>(4)</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'>1</div><input id='attrs-85d039bb-f378-427e-89a3-01f63220ac52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85d039bb-f378-427e-89a3-01f63220ac52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-405091bb-bac5-46da-a433-d5d6b1634ffa' class='xr-var-data-in' type='checkbox'><label for='data-405091bb-bac5-46da-a433-d5d6b1634ffa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>x_bounds</dd></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_bounds</span></div><div class='xr-var-dims'>(bnds, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5</div><input id='attrs-04493847-da9f-447d-b0c1-e0af2b2d819b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04493847-da9f-447d-b0c1-e0af2b2d819b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41178042-0d83-4310-a750-1b91ba023c17' class='xr-var-data-in' type='checkbox'><label for='data-41178042-0d83-4310-a750-1b91ba023c17' 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([[0.5],\n",
       "       [1.5]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2001-01-01 ... 2001-01-05</div><input id='attrs-d3febf67-d2d4-4e41-b61d-aeb80080605e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3febf67-d2d4-4e41-b61d-aeb80080605e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd4d95ca-3e7f-4018-a849-9be3bea72408' class='xr-var-data-in' type='checkbox'><label for='data-dd4d95ca-3e7f-4018-a849-9be3bea72408' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-01-01T00:00:00.000000000&#x27;, &#x27;2001-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-03T00:00:00.000000000&#x27;, &#x27;2001-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-05T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_bounds</span></div><div class='xr-var-dims'>(bnds, time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-12-31T12:00:00 ... 2001-01-...</div><input id='attrs-d8bcb8c3-76d9-4dc7-8e06-0fdabe8f9392' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8bcb8c3-76d9-4dc7-8e06-0fdabe8f9392' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8acd92a4-47e2-43ea-aaa4-b85edd6082b9' class='xr-var-data-in' type='checkbox'><label for='data-8acd92a4-47e2-43ea-aaa4-b85edd6082b9' 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([[&#x27;2000-12-31T12:00:00.000000000&#x27;, &#x27;2001-01-01T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-02T12:00:00.000000000&#x27;, &#x27;2001-01-03T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-04T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2001-01-01T12:00:00.000000000&#x27;, &#x27;2001-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-03T12:00:00.000000000&#x27;, &#x27;2001-01-04T12:00:00.000000000&#x27;,\n",
       "        &#x27;2001-01-05T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-34c10b24-6354-487c-88f5-880ca1a97c32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-34c10b24-6354-487c-88f5-880ca1a97c32' class='xr-section-summary' >Data variables: <span>(1)</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>data</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 4 8 12 16</div><input id='attrs-a06d78f0-97ad-46fc-827c-e960286449ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a06d78f0-97ad-46fc-827c-e960286449ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8325b6c-b7ce-4b57-bf94-2c38fc6d514f' class='xr-var-data-in' type='checkbox'><label for='data-a8325b6c-b7ce-4b57-bf94-2c38fc6d514f' 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],\n",
       "       [ 4],\n",
       "       [ 8],\n",
       "       [12],\n",
       "       [16]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b4ed31d-59eb-4bee-9be1-1d7561366cac' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b4ed31d-59eb-4bee-9be1-1d7561366cac' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x<br>x_bounds</div></div><div class='xr-index-preview'>XarrayIntervalIndex</div><div></div><input id='index-a0d27fae-60ea-4f41-980d-ad7db04baf62' class='xr-index-data-in' type='checkbox'/><label for='index-a0d27fae-60ea-4f41-980d-ad7db04baf62' 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>XarrayIntervalIndex([(0.5, 1.5]], dtype=&#x27;interval[float64, right]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time<br>time_bounds</div></div><div class='xr-index-preview'>XarrayIntervalIndex</div><div></div><input id='index-8670cb3a-7606-4f46-b21a-1000eef1bf40' class='xr-index-data-in' type='checkbox'/><label for='index-8670cb3a-7606-4f46-b21a-1000eef1bf40' 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>XarrayIntervalIndex([(2000-12-31 12:00:00, 2001-01-01 12:00:00],\n",
       "               (2001-01-01 12:00:00, 2001-01-02 12:00:00],\n",
       "               (2001-01-02 12:00:00, 2001-01-03 12:00:00],\n",
       "               (2001-01-03 12:00:00, 2001-01-04 12:00:00],\n",
       "               (2001-01-04 12:00:00, 2001-01-05 12:00:00]],\n",
       "              dtype=&#x27;interval[datetime64[ns], right]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ac467f0d-4d1a-4cf1-87d2-44c44fdf7b78' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ac467f0d-4d1a-4cf1-87d2-44c44fdf7b78' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 184B\n",
       "Dimensions:      (time: 5, x: 1, bnds: 2)\n",
       "Coordinates:\n",
       "  * x            (x) int64 8B 1\n",
       "  * x_bounds     (bnds, x) float64 16B 0.5 1.5\n",
       "  * time         (time) datetime64[ns] 40B 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (bnds, time) datetime64[ns] 80B 2000-12-31T12:00:00 ... 2001...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data         (time, x) int64 40B 0 4 8 12 16"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds1.sel(x=[1.1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d54457-e207-4d8d-87fc-fa999bbd2790",
   "metadata": {},
   "source": [
    "## Approach 2. Create new PandasIntervalIndex\n",
    "\n",
    "instead of using `PandasIndex` wrapping `pd.IntervalIndex`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "3b30a525-4bea-41e6-a1ef-72be103d819d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BoundsArray([[0.5, 1.5, 2.5, 3.5],\n",
       "       [1.5, 2.5, 3.5, 4.5]])"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class BoundsArrayWrapper:\n",
    "    def __init__(self, array: np.ndarray, axis: int):\n",
    "        assert bounds.ndim == 2\n",
    "        assert bounds.shape[axis] == 2\n",
    "        self.axis = axis\n",
    "        self.array = array\n",
    "\n",
    "    def __array__(self):\n",
    "        return self.array\n",
    "\n",
    "    def get_duck_array(self):\n",
    "        return self.array\n",
    "\n",
    "    def values(self):\n",
    "        return self.array\n",
    "\n",
    "    @property\n",
    "    def shape(self):\n",
    "        return shape\n",
    "\n",
    "    @property\n",
    "    def ndim(self):\n",
    "        return self.array.ndim - 1\n",
    "\n",
    "    @property\n",
    "    def shape(self):\n",
    "        return tuple(s for ax, s in enumerate(self.array.shape) if ax != self.axis)\n",
    "\n",
    "    @property\n",
    "    def data(self):\n",
    "        raise\n",
    "        return self.array\n",
    "\n",
    "    @property\n",
    "    def dtype(self):\n",
    "        return self.array.dtype\n",
    "\n",
    "    def __array_ufunc__(self, *args, **kwargs):\n",
    "        return self.array.__array_ufunc__(*args, **kwargs)\n",
    "\n",
    "    def __array_function__(self, func, types, args, kwargs):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def __repr__(self):\n",
    "        return f\"BoundsArray{repr(self.array)[5:]}\"\n",
    "\n",
    "    def __getitem__(self, key):\n",
    "        print(key)\n",
    "        if len(key) != 2 or key[1] != ...:\n",
    "            raise\n",
    "        if isinstance(key, tuple):\n",
    "            label, ell = key\n",
    "            if ell != Ellipsis:\n",
    "                ell, label = label, ell\n",
    "        else:\n",
    "            label = key\n",
    "\n",
    "        newkey = [label, label]\n",
    "        newkey[self.axis] = Ellipsis\n",
    "\n",
    "        # normalize key depending on axis\n",
    "        return type(self)(self.array[tuple(newkey)], axis=self.axis)\n",
    "\n",
    "\n",
    "@xr.register_dataarray_accessor(\"bounds\")\n",
    "class BoundsAccessor:\n",
    "    def __init__(self, da):\n",
    "        self.da = da\n",
    "\n",
    "    def wrap(self):\n",
    "        return\n",
    "\n",
    "\n",
    "wrapped = BoundsArrayWrapper(bounds, 0)\n",
    "wrapped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "dcd27fb3-e5dd-413f-9f9d-007bd7b29f0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "([1, 1], Ellipsis)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BoundsArray([[1.5, 1.5],\n",
       "       [2.5, 2.5]])"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wrapped[([1, 1], ...)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "4c52e667-afd4-4bce-b8d2-9c1b603f862c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:      (time: 5, x: 4)\n",
      "Coordinates:\n",
      "  * x            (x) int64 1 2 3 4\n",
      "    x_bounds     (x) float64 BoundsArray([[0.5, 1.5, 2.5, 3.5],        [1.5, ...\n",
      "  * time         (time) datetime64[ns] 2001-01-01 2001-01-02 ... 2001-01-05\n",
      "    time_bounds  (time) datetime64[ns] BoundsArray([['2000-12-31T12:00:00.000...\n",
      "Data variables:\n",
      "    data         (time, x) int64 0 1 2 3 4 5 6 7 8 ... 12 13 14 15 16 17 18 19\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (time: 5, x: 4)\n",
       "Coordinates:\n",
       "  * x            (x) float64 1.0 2.0 3.0 4.0\n",
       "  * x_bounds     (x) float64 BoundsArray([[0.5, 1.5, 2.5, 3.5],        [1.5, ...\n",
       "  * time         (time) datetime64[ns] 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (time) datetime64[ns] BoundsArray([[&#x27;2000-12-31T12:00:00.000...\n",
       "Data variables:\n",
       "    data         (time, x) int64 0 1 2 3 4 5 6 7 8 ... 12 13 14 15 16 17 18 19</pre>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (time: 5, x: 4)\n",
       "Coordinates:\n",
       "  * x            (x) float64 1.0 2.0 3.0 4.0\n",
       "  * x_bounds     (x) float64 BoundsArray([[0.5, 1.5, 2.5, 3.5],        [1.5, ...\n",
       "  * time         (time) datetime64[ns] 2001-01-01 2001-01-02 ... 2001-01-05\n",
       "  * time_bounds  (time) datetime64[ns] BoundsArray([['2000-12-31T12:00:00.000...\n",
       "Data variables:\n",
       "    data         (time, x) int64 0 1 2 3 4 5 6 7 8 ... 12 13 14 15 16 17 18 19"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xarray.core.indexes import Index, PandasIndex\n",
    "from xarray.core.indexing import merge_sel_results\n",
    "from xarray.core.variable import Variable\n",
    "\n",
    "\n",
    "class XarrayIntervalIndex(PandasIndex):\n",
    "    # based off Benoit's RasterIndex in\n",
    "    # https://hackmd.io/Zxw_zCa7Rbynx_iJu6Y3LA?view\n",
    "\n",
    "    def __init__(self, index, dim, coord_dtype):\n",
    "        # TODO: hardcoded variable names\n",
    "\n",
    "        assert isinstance(index, pd.IntervalIndex)\n",
    "\n",
    "        # for PandasIndex\n",
    "        self.index = index\n",
    "        self.dim = dim\n",
    "        self.coord_dtype = coord_dtype\n",
    "\n",
    "    @classmethod\n",
    "    def from_variables(cls, variables, options):\n",
    "        assert len(variables) == 2\n",
    "\n",
    "        for k, v in variables.items():\n",
    "            if isinstance(v.data, BoundsArrayWrapper):\n",
    "                bounds_name, bounds = k, v\n",
    "            elif v.ndim == 1:\n",
    "                dim, other = k, v\n",
    "\n",
    "        axis = bounds.data.axis\n",
    "        other_axis = 1 if axis == 0 else 1\n",
    "        left, right = np.split(bounds.data.array, 2, axis=axis)\n",
    "        bounds = bounds.data\n",
    "        index = pd.IntervalIndex.from_arrays(left.squeeze(), right.squeeze())\n",
    "\n",
    "        coord_dtype = bounds.array.dtype\n",
    "\n",
    "        return cls(index, dim, coord_dtype)\n",
    "\n",
    "    def create_variables(self, variables):\n",
    "        bounds_array = BoundsArrayWrapper(np.stack([self.index.left, self.index.right]), axis=0)\n",
    "        bounds = Variable(dims=self.dim, data=bounds_array)\n",
    "        mid = Variable(dims=self.dim, data=self.index.mid)\n",
    "\n",
    "        newvars = {}\n",
    "        for k, v in variables.items():\n",
    "            if isinstance(v.data, BoundsArrayWrapper):\n",
    "                newvars[k] = bounds\n",
    "            else:\n",
    "                newvars[k] = mid\n",
    "        return newvars\n",
    "\n",
    "    def __repr__(self):\n",
    "        string = f\"Xarray{self.index!r}\"\n",
    "        return string\n",
    "\n",
    "    def to_pandas_index(self):\n",
    "        return self.index\n",
    "\n",
    "    @property\n",
    "    def mid(self):\n",
    "        return PandasIndex(self.index.right, self.dim, self.coord_dtype)\n",
    "\n",
    "    @property\n",
    "    def left(self):\n",
    "        return PandasIndex(self.index.right, self.dim, self.coord_dtype)\n",
    "\n",
    "    @property\n",
    "    def right(self):\n",
    "        return PandasIndex(self.index.right, self.dim, self.coord_dtype)\n",
    "\n",
    "\n",
    "ds = xr.Dataset(\n",
    "    {\"data\": ((\"time\", \"x\"), np.arange(20).reshape(5, 4))},\n",
    "    coords={\"x\": [1, 2, 3, 4], \"x_bounds\": ((\"bnds\", \"x\"), bounds)},\n",
    ")\n",
    "tindex = pd.date_range(\"2001-01-01\", \"2001-01-05\", freq=\"D\")\n",
    "left = tindex - pd.DateOffset(hours=12)\n",
    "right = tindex + pd.DateOffset(hours=12)\n",
    "tbounds = np.stack([left, right])\n",
    "ds.coords[\"time\"] = (\"time\", tindex)\n",
    "ds.coords[\"time_bounds\"] = (\"time\", BoundsArrayWrapper(tbounds, axis=0))\n",
    "wrapped = BoundsArrayWrapper(ds.x_bounds.data, axis=ds.x_bounds.get_axis_num(\"bnds\"))\n",
    "ds.update({\"x_bounds\": (\"x\", wrapped)})\n",
    "print(ds)\n",
    "\n",
    "newds = ds.drop_indexes(\"x\").set_xindex(\n",
    "    (\"x\", \"x_bounds\"),\n",
    "    XarrayIntervalIndex,\n",
    ")\n",
    "newds = newds.drop_indexes(\"time\").set_xindex(\n",
    "    (\"time\", \"time_bounds\"),\n",
    "    XarrayIntervalIndex,\n",
    ")\n",
    "newds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "39ddafe8-5296-4b39-9ff8-011c5779588b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Indexes:\n",
       "    x            XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5]], dtype='interval[float64, right]')\n",
       "    x_bounds     XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5]], dtype='interval[float64, right]')\n",
       "    time         XarrayIntervalIndex([(2001-01-02 12:00:00, 2001-01-03 12:00:00]], dtype='interval[datetime64[ns], right]')\n",
       "    time_bounds  XarrayIntervalIndex([(2001-01-02 12:00:00, 2001-01-03 12:00:00]], dtype='interval[datetime64[ns], right]')"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newds.sel(x=[1.1, 2.4], time=[\"2001-01-02 13:00\"]).xindexes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dcb8cba-f7af-4a0d-a5b2-c64b11cc6e3c",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Approach 3. PandasMetaIndex style approach"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "040271fb-39e3-4fe3-88d5-dbabcd6a173d",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Splitting into 2 arrays\n",
    "\n",
    "doesn't work with `set_xindex` which does not expect changes in variables in vs variables out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "083074dd-7513-480f-9064-bf108613132c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) int64 1 2 3 4\n",
       "    x_bounds  (bnds, x) float64 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 1 2 3 4</pre>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) int64 1 2 3 4\n",
       "    x_bounds  (bnds, x) float64 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 1 2 3 4"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "left = np.arange(0.5, 3.6, 1)\n",
    "right = np.arange(1.5, 4.6, 1)\n",
    "bounds = np.stack([left, right])\n",
    "bounds.shape\n",
    "\n",
    "ds = xr.Dataset(\n",
    "    {\"data\": (\"x\", [1, 2, 3, 4])},\n",
    "    coords={\"x\": [1, 2, 3, 4], \"x_bounds\": ((\"bnds\", \"x\"), bounds)},\n",
    ")\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3a0e6a01-ed5f-4815-b30f-da14d2f6788a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([[0, 1), [1, 2), [2, 3)], dtype='object', name='x')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iidx = pd.IntervalIndex.from_arrays([0, 1, 2], [1, 2, 3], closed=\"left\")\n",
    "\n",
    "ds = xr.Dataset(coords={\"x\": iidx.values})\n",
    "\n",
    "actual = pd.IntervalIndex(ds.x.variable.data)\n",
    "\n",
    "assert actual.equals(iidx)\n",
    "ds.indexes[\"x\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d0f5473f-1df1-468d-9da2-6a34104a9b51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IntervalIndex([[0, 1), [1, 2), [2, 3)], dtype='interval[int64, left]')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iidx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1670c264-caa1-4963-9f3e-b9b8af3ad152",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "in from_variables\n",
      "init\n",
      "in create_vars\n",
      "{'x': <xarray.Variable (x: 4)>\n",
      "array([1, 2, 3, 4]), 'x_bounds': <xarray.Variable (bnds: 2, x: 4)>\n",
      "array([[0.5, 1.5, 2.5, 3.5],\n",
      "       [1.5, 2.5, 3.5, 4.5]])}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) int64 1 2 3 4\n",
       "  * x_bounds  (bnds, x) float64 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 1 2 3 4\n",
       "Indexes:\n",
       "    x         XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype=&#x27;interval[float64, right]&#x27;)\n",
       "    x_bounds  XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype=&#x27;interval[float64, right]&#x27;)</pre>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) int64 1 2 3 4\n",
       "  * x_bounds  (bnds, x) float64 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 1 2 3 4\n",
       "Indexes:\n",
       "    x         XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype='interval[float64, right]')\n",
       "    x_bounds  XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype='interval[float64, right]')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xarray.core.indexes import PandasIndex\n",
    "\n",
    "\n",
    "class XarrayIntervalIndex(Index):\n",
    "    # based off Benoit's RasterIndex in\n",
    "    # https://hackmd.io/Zxw_zCa7Rbynx_iJu6Y3LA?view\n",
    "\n",
    "    def __init__(self, variables):\n",
    "        print(\"init\")\n",
    "\n",
    "        assert len(variables) == 2\n",
    "        self._variables = variables\n",
    "\n",
    "        for k, v in variables.items():\n",
    "            if v.ndim == 2:\n",
    "                self._bounds_name, bounds = k, v\n",
    "            elif v.ndim == 1:\n",
    "                dim, other = k, v\n",
    "\n",
    "        bounds = bounds.transpose(..., dim)\n",
    "        left, right = bounds.data.tolist()\n",
    "        self._index = pd.IntervalIndex.from_arrays(left, right)\n",
    "        self._dim = dim\n",
    "        self._bounds_dim = (set(bounds.dims) - set(dim)).pop()\n",
    "\n",
    "    @classmethod\n",
    "    def from_variables(cls, variables, options):\n",
    "        print(\"in from_variables\")\n",
    "        assert len(variables) == 2\n",
    "        return cls(variables)\n",
    "\n",
    "    # TODO: variables=None?\n",
    "    # set_xindex tries to pass variables; this seems like a bug\n",
    "    def create_variables(self, variables=None):\n",
    "        print(\"in create_vars\")\n",
    "        print(variables)\n",
    "        variables = {\n",
    "            f\"{self._dim}{edge}\": Variable(dims=(self._dim,), data=getattr(self._index, edge))\n",
    "            for suffix, edge in [(\"left\", \"left\"), (\"right\", \"right\"), (\"\", \"mid\")]\n",
    "        }\n",
    "        return variables\n",
    "\n",
    "    # TODO: see notes about IndexSelResult\n",
    "    #    The latter is a small class that stores positional indexers (indices)\n",
    "    #    and that could also store new variables, new indexes,\n",
    "    #    names of variables or indexes to drop,\n",
    "    #    names of dimensions to rename, etc.\n",
    "    def sel(self, labels, **kwargs):\n",
    "        # sel needs to only handle keys in labels\n",
    "        # since it delegates to isel.\n",
    "        # we handle all entries in ._indexes there\n",
    "        results = self.index.sel({k: labels[k]}, **kwargs)\n",
    "        return merge_sel_results(results)\n",
    "\n",
    "    def isel(self, indexers):\n",
    "        # TODO: check dim names in indexes\n",
    "        results = {}\n",
    "        for k, index in self._indexes.items():\n",
    "            if k in indexers:\n",
    "                # again possible KDTree / friends here.\n",
    "                results[k] = index.isel({k: indexers[k]})\n",
    "            else:\n",
    "                results[k] = index\n",
    "        return type(self)(results)\n",
    "\n",
    "    def __repr__(self):\n",
    "        string = f\"Xarray{self._index!r}\"\n",
    "        return string\n",
    "\n",
    "\n",
    "newds = ds.drop_indexes(\"x\").set_xindex(\n",
    "    (\"x\", \"x_bounds\"),\n",
    "    XarrayIntervalIndex,\n",
    ")\n",
    "newds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8845d16d-7354-4f99-86fa-105183e6d1f1",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Preserving 2D bounds variable\n",
    "\n",
    "Doesn't work because it isn't propagated with DataArray selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "723d582e-aab3-4ac1-8275-2bfee380f361",
   "metadata": {},
   "outputs": [],
   "source": [
    "left = np.arange(0.5, 3.6, 1)\n",
    "right = np.arange(1.5, 4.6, 1)\n",
    "bounds = np.stack([left, right])\n",
    "bounds.shape\n",
    "\n",
    "ds = xr.Dataset(\n",
    "    {\"data\": (\"x\", [1, 2, 3, 4])},\n",
    "    coords={\"x\": [1, 2, 3, 4], \"x_bounds\": ((\"bnds\", \"x\"), bounds)},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "28504419-d4b7-4e7f-a34b-6eca23b4b7b8",
   "metadata": {},
   "outputs": [
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       ".xr-attrs dd {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 128B\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) float64 32B 1.0 2.0 3.0 4.0\n",
       "  * x_bounds  (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 32B 1 2 3 4\n",
       "Indexes:\n",
       "  ┌ x         XarrayIntervalIndex\n",
       "  └ x_bounds</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-668605a1-ef24-4725-9eff-bf51e6b410a3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-668605a1-ef24-4725-9eff-bf51e6b410a3' 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>: 4</li><li><span class='xr-has-index'>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a1ec46d5-b505-4bd4-b72b-1aad2baf646d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a1ec46d5-b505-4bd4-b72b-1aad2baf646d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0</div><input id='attrs-253d3e2b-56fe-4073-a11e-8ab6504590aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-253d3e2b-56fe-4073-a11e-8ab6504590aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08e8fbff-b004-4d9c-b7ff-874bd87c57a7' class='xr-var-data-in' type='checkbox'><label for='data-08e8fbff-b004-4d9c-b7ff-874bd87c57a7' 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([1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_bounds</span></div><div class='xr-var-dims'>(bnds, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5</div><input id='attrs-c66ca83c-ea1f-49fd-a8c6-8559062717df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c66ca83c-ea1f-49fd-a8c6-8559062717df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-249c7627-425e-45c0-82c3-3f6a7ebcfbfd' class='xr-var-data-in' type='checkbox'><label for='data-249c7627-425e-45c0-82c3-3f6a7ebcfbfd' 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([[0.5, 1.5, 2.5, 3.5],\n",
       "       [1.5, 2.5, 3.5, 4.5]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-66cff959-e70d-4ca0-b64b-46ce339c499a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-66cff959-e70d-4ca0-b64b-46ce339c499a' class='xr-section-summary' >Data variables: <span>(1)</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>data</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-53c18e71-822d-4e1a-8bf0-5560ba6327a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53c18e71-822d-4e1a-8bf0-5560ba6327a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f45223ec-b10c-466a-9511-839e913c1242' class='xr-var-data-in' type='checkbox'><label for='data-f45223ec-b10c-466a-9511-839e913c1242' 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([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-91c00938-1547-4bb1-9ed6-7bd1e5e7ba00' class='xr-section-summary-in' type='checkbox'  ><label for='section-91c00938-1547-4bb1-9ed6-7bd1e5e7ba00' class='xr-section-summary' >Indexes: <span>(1)</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<br>x_bounds</div></div><div class='xr-index-preview'>XarrayIntervalIndex</div><div></div><input id='index-f018407f-93bf-4e6e-aa39-309b21c3f5eb' class='xr-index-data-in' type='checkbox'/><label for='index-f018407f-93bf-4e6e-aa39-309b21c3f5eb' 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>XarrayIntervalIndex([(0.5, 1.5], (1.5, 2.5], (2.5, 3.5], (3.5, 4.5]], dtype=&#x27;interval[float64, right]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d4fdafa2-7b2b-43ab-a168-1043484825c0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4fdafa2-7b2b-43ab-a168-1043484825c0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 128B\n",
       "Dimensions:   (x: 4, bnds: 2)\n",
       "Coordinates:\n",
       "  * x         (x) float64 32B 1.0 2.0 3.0 4.0\n",
       "  * x_bounds  (bnds, x) float64 64B 0.5 1.5 2.5 3.5 1.5 2.5 3.5 4.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    data      (x) int64 32B 1 2 3 4\n",
       "Indexes:\n",
       "  ┌ x         XarrayIntervalIndex\n",
       "  └ x_bounds"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from xarray.core.indexes import Index, PandasIndex\n",
    "\n",
    "\n",
    "class XarrayIntervalIndex(Index):\n",
    "    # based off Benoit's RasterIndex in\n",
    "    # https://hackmd.io/Zxw_zCa7Rbynx_iJu6Y3LA?view\n",
    "\n",
    "    def __init__(self, variables):\n",
    "        # TODO: hardcoded variable names\n",
    "\n",
    "        assert len(variables) == 2\n",
    "        self._variables = variables\n",
    "\n",
    "        for k, v in variables.items():\n",
    "            if v.ndim == 2:\n",
    "                self._bounds_name, bounds = k, v\n",
    "            elif v.ndim == 1:\n",
    "                dim, other = k, v\n",
    "\n",
    "        bounds = bounds.transpose(..., dim)\n",
    "        left, right = bounds.data.tolist()\n",
    "        self._index = pd.IntervalIndex.from_arrays(left, right)\n",
    "        self._dim = dim\n",
    "        self._bounds_dim = (set(bounds.dims) - set(dim)).pop()\n",
    "\n",
    "    @classmethod\n",
    "    def from_variables(cls, variables, options):\n",
    "        assert len(variables) == 2\n",
    "        return cls(variables)\n",
    "\n",
    "    # TODO: variables=None?\n",
    "    # set_xindex tries to pass variables; this seems like a bug\n",
    "    def create_variables(self, variables=None):\n",
    "        idx_variables = {}\n",
    "\n",
    "        bounds = Variable(\n",
    "            dims=(self._bounds_dim, self._dim),\n",
    "            data=np.stack([self._index.left, self._index.right], axis=0),\n",
    "        )\n",
    "        mid = Variable(dims=(self._dim,), data=self._index.mid)\n",
    "        return {self._dim: mid, self._bounds_name: bounds}\n",
    "\n",
    "    # TODO: see notes about IndexSelResult\n",
    "    #    The latter is a small class that stores positional indexers (indices)\n",
    "    #    and that could also store new variables, new indexes,\n",
    "    #    names of variables or indexes to drop,\n",
    "    #    names of dimensions to rename, etc.\n",
    "    def sel(self, labels, **kwargs):\n",
    "        # sel needs to only handle keys in labels\n",
    "        # since it delegates to isel.\n",
    "        # we handle all entries in ._indexes there\n",
    "        results = self.index.sel({k: labels[k]}, **kwargs)\n",
    "        return merge_sel_results(results)\n",
    "\n",
    "    def isel(self, indexers):\n",
    "        # TODO: check dim names in indexes\n",
    "        results = {}\n",
    "        for k, index in self._indexes.items():\n",
    "            if k in indexers:\n",
    "                # again possible KDTree / friends here.\n",
    "                results[k] = index.isel({k: indexers[k]})\n",
    "            else:\n",
    "                results[k] = index\n",
    "        return type(self)(results)\n",
    "\n",
    "    def __repr__(self):\n",
    "        string = f\"Xarray{self._index!r}\"\n",
    "        return string\n",
    "\n",
    "\n",
    "newds = ds.drop_indexes(\"x\").set_xindex(\n",
    "    (\"x\", \"x_bounds\"),\n",
    "    XarrayIntervalIndex,\n",
    ")\n",
    "newds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30fc7a4f-7f2a-48b1-8aae-1666e13f34d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "newds.sel(x=1.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d65d45ee-df08-435c-8a5c-826a1a8e9cac",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Approach 4. Extension Array Adaptor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bc2479c3-5850-49ba-a69e-9bebbe5d05ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True 1 3 interval[int64, right] (3,)\n"
     ]
    }
   ],
   "source": [
    "intarray = pd.arrays.IntervalArray.from_arrays([0, 1, 2], [1, 2, 3])\n",
    "\n",
    "print(\n",
    "    isinstance(intarray, pd.api.extensions.ExtensionArray),\n",
    "    intarray.ndim,\n",
    "    intarray.size,\n",
    "    intarray.dtype,\n",
    "    intarray.shape,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b0d44444-4d06-4dfa-9282-e275649dd376",
   "metadata": {},
   "outputs": [
    {
     "ename": "RuntimeError",
     "evalue": "No active exception to reraise",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[16], line 86\u001b[0m\n\u001b[1;32m     81\u001b[0m         coords[dim] \u001b[38;5;241m=\u001b[39m coords[dim]\u001b[38;5;241m.\u001b[39mcopy(data\u001b[38;5;241m=\u001b[39mindexes[dim]\u001b[38;5;241m.\u001b[39mindex)\n\u001b[1;32m     83\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_obj\u001b[38;5;241m.\u001b[39m_replace(var, coords\u001b[38;5;241m=\u001b[39mcoords, indexes\u001b[38;5;241m=\u001b[39mindexes)\n\u001b[0;32m---> 86\u001b[0m da \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDataArray\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     87\u001b[0m \u001b[43m    \u001b[49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mintarray\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     88\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdims\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     89\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcoords\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mExtensionArrayAdaptor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mintarray\u001b[49m\u001b[43m)\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     90\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m     91\u001b[0m da\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/dataarray.py:455\u001b[0m, in \u001b[0;36mDataArray.__init__\u001b[0;34m(self, data, coords, dims, name, attrs, indexes, fastpath)\u001b[0m\n\u001b[1;32m    453\u001b[0m data \u001b[38;5;241m=\u001b[39m _check_data_shape(data, coords, dims)\n\u001b[1;32m    454\u001b[0m data \u001b[38;5;241m=\u001b[39m as_compatible_data(data)\n\u001b[0;32m--> 455\u001b[0m coords, dims \u001b[38;5;241m=\u001b[39m \u001b[43m_infer_coords_and_dims\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcoords\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdims\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    456\u001b[0m variable \u001b[38;5;241m=\u001b[39m Variable(dims, data, attrs, fastpath\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    458\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(coords, Coordinates):\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/dataarray.py:187\u001b[0m, in \u001b[0;36m_infer_coords_and_dims\u001b[0;34m(shape, coords, dims)\u001b[0m\n\u001b[1;32m    185\u001b[0m         new_coords[k] \u001b[38;5;241m=\u001b[39m as_variable(v, name\u001b[38;5;241m=\u001b[39mk, auto_convert\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m    186\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m new_coords[k]\u001b[38;5;241m.\u001b[39mdims \u001b[38;5;241m==\u001b[39m (k,):\n\u001b[0;32m--> 187\u001b[0m             new_coords[k] \u001b[38;5;241m=\u001b[39m \u001b[43mnew_coords\u001b[49m\u001b[43m[\u001b[49m\u001b[43mk\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_index_variable\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    188\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m coords \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    189\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m dim, coord \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(dims_tuple, coords):\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/variable.py:556\u001b[0m, in \u001b[0;36mVariable.to_index_variable\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    554\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mto_index_variable\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m IndexVariable:\n\u001b[1;32m    555\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return this variable as an xarray.IndexVariable\"\"\"\u001b[39;00m\n\u001b[0;32m--> 556\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mIndexVariable\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    557\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dims\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_data\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_attrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_encoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfastpath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\n\u001b[1;32m    558\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/variable.py:2629\u001b[0m, in \u001b[0;36mIndexVariable.__init__\u001b[0;34m(self, dims, data, attrs, encoding, fastpath)\u001b[0m\n\u001b[1;32m   2627\u001b[0m \u001b[38;5;66;03m# Unlike in Variable, always eagerly load values into memory\u001b[39;00m\n\u001b[1;32m   2628\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_data, PandasIndexingAdapter):\n\u001b[0;32m-> 2629\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_data \u001b[38;5;241m=\u001b[39m \u001b[43mPandasIndexingAdapter\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_data\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/indexing.py:1659\u001b[0m, in \u001b[0;36mPandasIndexingAdapter.__init__\u001b[0;34m(self, array, dtype)\u001b[0m\n\u001b[1;32m   1656\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, array: pd\u001b[38;5;241m.\u001b[39mIndex, dtype: DTypeLike \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m   1657\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mxarray\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mindexes\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m safe_cast_to_index\n\u001b[0;32m-> 1659\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39marray \u001b[38;5;241m=\u001b[39m \u001b[43msafe_cast_to_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43marray\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1661\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m dtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   1662\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dtype \u001b[38;5;241m=\u001b[39m get_valid_numpy_dtype(array)\n",
      "File \u001b[0;32m~/miniforge3/envs/xarray-release/lib/python3.11/site-packages/xarray/core/indexes.py:469\u001b[0m, in \u001b[0;36msafe_cast_to_index\u001b[0;34m(array)\u001b[0m\n\u001b[1;32m    459\u001b[0m             emit_user_level_warning(\n\u001b[1;32m    460\u001b[0m                 (\n\u001b[1;32m    461\u001b[0m                     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`pandas.Index` does not support the `float16` dtype.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    465\u001b[0m                 category\u001b[38;5;241m=\u001b[39m\u001b[38;5;167;01mDeprecationWarning\u001b[39;00m,\n\u001b[1;32m    466\u001b[0m             )\n\u001b[1;32m    467\u001b[0m             kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfloat64\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 469\u001b[0m     index \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mIndex(np\u001b[38;5;241m.\u001b[39masarray(array), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    471\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _maybe_cast_to_cftimeindex(index)\n",
      "Cell \u001b[0;32mIn[16], line 11\u001b[0m, in \u001b[0;36mExtensionArrayAdaptor.__array__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__array__\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m---> 11\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: No active exception to reraise"
     ]
    }
   ],
   "source": [
    "from xarray.core.indexes import PandasIndex\n",
    "from xarray.core.indexing import ExplicitlyIndexed, PandasIndexingAdapter\n",
    "from xarray.core.utils import NdimSizeLenMixin\n",
    "\n",
    "\n",
    "class ExtensionArrayAdaptor(NdimSizeLenMixin, ExplicitlyIndexed):\n",
    "    def __init__(self, array):\n",
    "        self.array = array\n",
    "\n",
    "    def __array__(self):\n",
    "        raise\n",
    "\n",
    "    def get_duck_array(self):\n",
    "        return self\n",
    "\n",
    "    def values(self):\n",
    "        raise\n",
    "\n",
    "    @property\n",
    "    def shape(self):\n",
    "        return self.array.shape\n",
    "\n",
    "    @property\n",
    "    def data(self):\n",
    "        return self.array\n",
    "\n",
    "    @property\n",
    "    def dtype(self):\n",
    "        return self.array.dtype\n",
    "\n",
    "    def __array_ufunc__(self, *args, **kwargs):\n",
    "        return self.array.__array_ufunc__(*args, **kwargs)\n",
    "\n",
    "    def __array_function__(self, func, types, args, kwargs):\n",
    "        raise NotImplementedError\n",
    "\n",
    "    def __repr__(self):\n",
    "        return f\"ExtensionArrayAdaptor({self.array!r})\"\n",
    "\n",
    "\n",
    "@xr.register_dataarray_accessor(\"interval\")\n",
    "class IntervalAccessor:\n",
    "    def __init__(self, obj):\n",
    "        assert isinstance(obj, xr.DataArray)\n",
    "        self._variable = obj._variable.to_base_variable()\n",
    "        assert isinstance(self._variable._data, PandasIndexingAdapter)\n",
    "        array = self._variable._data.array.array\n",
    "        assert isinstance(array, pd.arrays.IntervalArray)\n",
    "\n",
    "        self._obj = obj\n",
    "        self._array = array\n",
    "\n",
    "    def _get_property_var(self, prop):\n",
    "        vals = getattr(self._array, prop)\n",
    "        return self._variable.copy(data=np.array(vals))\n",
    "\n",
    "    def _wrap_property(self, prop):\n",
    "        return self._obj._replace(self._get_property_var(prop))\n",
    "\n",
    "    @property\n",
    "    def mid(self):\n",
    "        return self._wrap_property(\"mid\")\n",
    "\n",
    "    @property\n",
    "    def left(self):\n",
    "        return self._wrap_property(\"left\")\n",
    "\n",
    "    @property\n",
    "    def right(self):\n",
    "        return self._wrap_property(\"right\")\n",
    "\n",
    "    def to(self, loc):\n",
    "        assert loc in [\"left\", \"mid\", \"right\"]\n",
    "        var = self._get_property_var(loc)\n",
    "        dim = self._obj.name\n",
    "\n",
    "        coords = self._obj._coords.copy()\n",
    "        indexes = self._obj._indexes.copy()\n",
    "\n",
    "        indexes[dim] = PandasIndex(var._data, dim=dim)\n",
    "        coords[dim] = coords[dim].copy(data=indexes[dim].index)\n",
    "\n",
    "        return self._obj._replace(var, coords=coords, indexes=indexes)\n",
    "\n",
    "\n",
    "da = xr.DataArray(\n",
    "    np.arange(len(intarray)),\n",
    "    dims=\"x\",\n",
    "    coords={\"x\": ExtensionArrayAdaptor(intarray)},\n",
    ")\n",
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "612060e9-25cd-4f84-8dba-ee22e00bcc4c",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'xarray.core.pycompat'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mxarray\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpycompat\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m is_duck_array\n\u001b[1;32m      3\u001b[0m a \u001b[38;5;241m=\u001b[39m ExtensionArrayAdaptor(intarray)\n\u001b[1;32m      4\u001b[0m is_duck_array(a)\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'xarray.core.pycompat'"
     ]
    }
   ],
   "source": [
    "from xarray.core.pycompat import is_duck_array\n",
    "\n",
    "a = ExtensionArrayAdaptor(intarray)\n",
    "is_duck_array(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e68b90ed-1a38-4039-a6d0-3fd439bca53d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PandasIndex(IntervalIndex([(0, 1], (1, 2], (2, 3]], dtype='interval[int64, right]', name='x'))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da._indexes[\"x\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d81b0001-104c-4cef-b5fe-faaacf687b14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray (x: 3)&gt;\n",
       "array([0, 1, 2])\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]</pre>"
      ],
      "text/plain": [
       "<xarray.DataArray (x: 3)>\n",
       "array([0, 1, 2])\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f04519ea-0adc-40cd-8c8a-f5c13880f1e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray &#x27;x&#x27; (x: 3)&gt;\n",
       "array([0.5, 1.5, 2.5])\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]</pre>"
      ],
      "text/plain": [
       "<xarray.DataArray 'x' (x: 3)>\n",
       "array([0.5, 1.5, 2.5])\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da.x.interval.mid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "aa39a88d-57bf-4acf-8c59-f0c4c923a7e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray &#x27;x&#x27; (x: 3)&gt;\n",
       "array([Interval(0, 1, closed=&#x27;right&#x27;), Interval(1, 2, closed=&#x27;right&#x27;),\n",
       "       Interval(2, 3, closed=&#x27;right&#x27;)], dtype=object)\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]</pre>"
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      "text/plain": [
       "<xarray.DataArray 'x' (x: 3)>\n",
       "array([Interval(0, 1, closed='right'), Interval(1, 2, closed='right'),\n",
       "       Interval(2, 3, closed='right')], dtype=object)\n",
       "Coordinates:\n",
       "  * x        (x) object (0, 1] (1, 2] (2, 3]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f6924f77-b655-4e73-abd2-64c72afb7c59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtensionArrayAdaptor(<IntervalArray>\n",
       "[(0, 1], (1, 2], (2, 3]]\n",
       "Length: 3, dtype: interval[int64, right])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v = xr.Variable(\"x\", ExtensionArrayAdaptor(intarray))\n",
    "v._data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "02d5dfec-54f1-417b-9b3f-03c2884c7a8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PandasIndexingAdapter(array=IntervalIndex([(0, 1], (1, 2], (2, 3]], dtype='interval[int64, right]'), dtype=dtype('O'))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v = xr.IndexVariable(\"x\", ExtensionArrayAdaptor(intarray))\n",
    "v._data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "da778339-5cb2-4d27-8188-2b00456b9302",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.Variable ()&gt;\n",
       "array(Interval(0, 1, closed=&#x27;right&#x27;), dtype=object)</pre>"
      ],
      "text/plain": [
       "<xarray.Variable ()>\n",
       "array(Interval(0, 1, closed='right'), dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v.isel(x=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9ed37d66-ec27-470b-a7f0-1a67d7c7ecf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.IndexVariable &#x27;x&#x27; (x: 3)&gt;\n",
       "array([Interval(0, 1, closed=&#x27;right&#x27;), Interval(1, 2, closed=&#x27;right&#x27;),\n",
       "       Interval(2, 3, closed=&#x27;right&#x27;)], dtype=object)</pre>"
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       "array([Interval(0, 1, closed='right'), Interval(1, 2, closed='right'),\n",
       "       Interval(2, 3, closed='right')], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.IndexVariable(\"x\", ExtensionArrayAdaptor(intarray))"
   ]
  }
 ],
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