TomNicholas/xgcm_boundary_conditions.ipynb

## xgcm_boundary_conditions.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "946cee33-5838-469f-9323-d7cfa867990d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import dask.array as dsa\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "611807f3-abd7-4049-ae4f-256c6d82ead3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 20)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ny, Nx = (30, 20)\n",
    "data_in = np.random.rand(Ny, Nx)\n",
    "data_in.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9e074262-e780-4604-b41e-8e394ffc849b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 21)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dummy pad function\n",
    "# works lazily with dask input\n",
    "\n",
    "def pad(a_in):\n",
    "    pad_width = (a_in.ndim - 1) * ((0, 0),) + ((1, 0),)\n",
    "    return np.pad(a_in, pad_width, mode='wrap')\n",
    "           \n",
    "pad(data_in).shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "821defdc-b013-44fa-b31e-4b5d88e9d9e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 21)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(30, 20)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def diff(a_in):\n",
    "    print(f\"Calling diff on array of shape {a_in.shape}\")\n",
    "    return a_in[..., 1:] - a_in[..., :-1]\n",
    "\n",
    "expected_result = diff(pad(data_in))\n",
    "expected_result.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc13b6bd-582b-4311-88bc-a893664bdb7e",
   "metadata": {},
   "source": [
    "## Case 1: All Numpy Data\n",
    "\n",
    "Note I'm using _function composition_ here. I think this is an important concept.\n",
    "Whenever possible, we want to compose the boundary handling with the actual operation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "430e3477-b337-489b-9f2e-21a81e3d97d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 21)\n"
     ]
    }
   ],
   "source": [
    "da_in = xr.DataArray(data_in, dims=('y', 'x'))\n",
    "\n",
    "da_out = xr.apply_ufunc(\n",
    "    lambda a_in: diff(pad(a_in)),\n",
    "    da_in,\n",
    "    input_core_dims=['x'],\n",
    "    output_core_dims=['x'],\n",
    "    vectorize=False\n",
    ")\n",
    "\n",
    "np.testing.assert_equal(da_out.values, expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63c2f0c9-3b00-4519-8ea4-daf0db15fce9",
   "metadata": {},
   "source": [
    "## Case 2: Chunked in the y dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "22462996-55dd-4782-91b8-04b5ba6170c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.56 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (10, 20) </td></tr>\n",
       "    <tr><th> Count </th><td> 3 Tasks </td><td> 3 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"40\" x2=\"80\" y2=\"40\" />\n",
       "  <line x1=\"0\" y1=\"80\" x2=\"80\" y2=\"80\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<xarray-<this-array>, shape=(30, 20), dtype=float64, chunksize=(10, 20), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_chunk_y = da_in.chunk({'y': 10})\n",
    "da_chunk_y.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a28c8434-1762-4001-aa08-423499afa5c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.56 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (10, 20) </td></tr>\n",
       "    <tr><th> Count </th><td> 12 Tasks </td><td> 3 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"40\" x2=\"80\" y2=\"40\" />\n",
       "  <line x1=\"0\" y1=\"80\" x2=\"80\" y2=\"80\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<transpose, shape=(30, 20), dtype=float64, chunksize=(10, 20), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_out_chunk_y = xr.apply_ufunc(\n",
    "    lambda a_in: diff(pad(a_in)),\n",
    "    da_chunk_y,\n",
    "    dask=\"parallelized\",\n",
    "    input_core_dims=['x'],\n",
    "    output_core_dims=['x'],\n",
    "    output_dtypes=[da_in.dtype]\n",
    ")\n",
    "da_out_chunk_y.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e19ca4af-fd84-4f77-8fe2-a0ad06bca416",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_out_chunk_y.data.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7aff77e2-141a-485e-98d9-73389263c29a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (10, 21)\n",
      "Calling diff on array of shape (10, 21)Calling diff on array of shape (10, 21)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "np.testing.assert_equal(da_out_chunk_y.values, expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fdc82f0-0a50-4b66-9689-4c4d5e4c770d",
   "metadata": {},
   "source": [
    "Note that this exact same `apply_ufunc` works just as well with numpy data, subsuming case 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e08095b8-9b21-4e9b-8e6e-484801901c9d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 21)\n"
     ]
    }
   ],
   "source": [
    "da_out = xr.apply_ufunc(\n",
    "    lambda a_in: diff(pad(a_in)),\n",
    "    da_in,\n",
    "    dask=\"parallelized\",\n",
    "    input_core_dims=['x'],\n",
    "    output_core_dims=['x'],\n",
    "    output_dtypes=[da_in.dtype]\n",
    ")\n",
    "\n",
    "np.testing.assert_equal(da_out.values, expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b43de31-8f32-439d-94ab-03856a0fc2d1",
   "metadata": {},
   "source": [
    "## Case 3: Chunked in the x dimension\n",
    "\n",
    "This is harder because we have to apply the boundary condition separately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "daa1efef-3470-498d-b380-4be4cee49afe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 4 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<xarray-<this-array>, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_chunk_x = da_in.chunk({'x': 5})\n",
    "da_chunk_x.data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c99e193f-1e90-4834-877a-2d4b0e86ea25",
   "metadata": {},
   "source": [
    "It's important that we define our own padding function, rather than rely on `map_overlap`, because we will eventually have to implement global boundary conditions not supported by dask.array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5835baca-faee-4d3f-ae7a-89cedfc7b781",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.92 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 21) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 10 Tasks </td><td> 5 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"134\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"84\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"4\" y1=\"0\" x2=\"4\" y2=\"120\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"120\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"120\" />\n",
       "  <line x1=\"64\" y1=\"0\" x2=\"64\" y2=\"120\" />\n",
       "  <line x1=\"84\" y1=\"0\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 84.0,0.0 84.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"42.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >21</text>\n",
       "  <text x=\"104.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,104.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<concatenate, shape=(30, 21), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_padded = pad(da_chunk_x.data)\n",
    "data_padded"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55369224-d7e1-4502-9c5c-00aca8a8a4fa",
   "metadata": {},
   "source": [
    "Now we have a lonely lengh-1 chunk. This is not good.\n",
    "We probably want to merge it back with its parent before calling map-blocks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "828d82a9-9fa1-4769-9f2c-8d3e50b8542e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.92 kiB </td> <td> 1.41 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 21) </td> <td> (30, 6) </td></tr>\n",
       "    <tr><th> Count </th><td> 14 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"134\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"84\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"120\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"120\" />\n",
       "  <line x1=\"64\" y1=\"0\" x2=\"64\" y2=\"120\" />\n",
       "  <line x1=\"84\" y1=\"0\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 84.0,0.0 84.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"42.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >21</text>\n",
       "  <text x=\"104.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,104.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<rechunk-merge, shape=(30, 21), dtype=float64, chunksize=(30, 6), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO: think about how to generalize this\n",
    "data_padded_rechunked = data_padded.rechunk((-1, (6, 5, 5, 5)))\n",
    "data_padded_rechunked"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b2eca6c7-63b6-46b0-812d-573f5934459b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((30,), (6, 5, 5, 5))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_padded_rechunked.chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a2627279-c485-4ad2-9546-868ab19566bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_padded_rechunked.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f3bb361-8e81-4fd3-97a1-0e2601ec4580",
   "metadata": {},
   "source": [
    "This is the best graph we can hope for at this stage.\n",
    "\n",
    "Now we can map overlap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8dbcec2d-bb3a-4cef-a4f9-da3c8e98ba0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.92 kiB </td> <td> 1.41 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 21) </td> <td> (30, 6) </td></tr>\n",
       "    <tr><th> Count </th><td> 32 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"134\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"84\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"120\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"120\" />\n",
       "  <line x1=\"64\" y1=\"0\" x2=\"64\" y2=\"120\" />\n",
       "  <line x1=\"84\" y1=\"0\" x2=\"84\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 84.0,0.0 84.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"42.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >21</text>\n",
       "  <text x=\"104.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,104.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<diff, shape=(30, 21), dtype=float64, chunksize=(30, 6), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_diffed = dsa.map_overlap(\n",
    "    diff,\n",
    "    data_padded_rechunked,\n",
    "    depth={1: (1, 0)},\n",
    "    boundary='none',\n",
    "    trim=False,\n",
    "    meta=np.array([], dtype=data_padded_rechunked.dtype),\n",
    ")\n",
    "data_diffed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ba65378-eaba-493f-b1ff-7cfae4035e41",
   "metadata": {},
   "source": [
    "Here dask _thinks_ that the output shape is `(30, 21)`. But if we compute it, we see that we get the right shape `(30, 20)`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ea135105-2531-486a-bb71-709ca6ff49b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 6)Calling diff on array of shape (30, 6)\n",
      "\n",
      "Calling diff on array of shape (30, 6)\n",
      "Calling diff on array of shape (30, 6)\n"
     ]
    }
   ],
   "source": [
    "np.testing.assert_equal(data_diffed.compute(), expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48551aa9-a709-41b9-8b5e-5f6b26d21a1e",
   "metadata": {},
   "source": [
    "The logging tells us that each mapped operation is a getting an array of the same size.\n",
    "However, for the first block, the \"extra\" part is not an overlap region but explicitly part of the array.\n",
    "\n",
    "To get around this, we need to manually specify the chunks in map_overlap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "70d7a042-7f86-4165-a85e-bb0f60d01058",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((30,), (6, 5, 5, 5))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_padded_rechunked.chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cb98bf4b-c2b5-4b9d-b899-1e65cc471f30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((30,), (5, 5, 5, 5))"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orig_chunks = data_padded_rechunked.chunks\n",
    "core_dim_chunks = orig_chunks[-1]\n",
    "true_core_dim_chunks = ((core_dim_chunks[0]-1,) + core_dim_chunks[1:],)\n",
    "true_chunks = orig_chunks[:-1] + true_core_dim_chunks\n",
    "\n",
    "true_chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aecd6bc0-4853-47bd-99c6-bb3982a5cc64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 32 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_diffed = dsa.map_overlap(\n",
    "    diff,\n",
    "    data_padded_rechunked,\n",
    "    depth={1: (1, 0)},\n",
    "    boundary='none',\n",
    "    trim=False,\n",
    "    meta=np.array([], dtype=data_padded_rechunked.dtype),\n",
    "    chunks=true_chunks\n",
    ")\n",
    "data_diffed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "52fc5e24-1581-498c-8693-5b4dec18f1d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_diffed.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cdf1b854-4d60-4a13-b6b1-49b796ffc379",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 6)\n",
      "Calling diff on array of shape (30, 6)Calling diff on array of shape (30, 6)Calling diff on array of shape (30, 6)\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "np.testing.assert_equal(data_diffed.compute(), expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc830f05-333f-417d-afe7-7c197ffd47e2",
   "metadata": {},
   "source": [
    "🎉🎉🎉 It worked!\n",
    "\n",
    "Making this work at the Xarray level involves a few more complications.\n",
    "\n",
    "The function composition is a bit more involved. Generalizing this will take work.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "744eea17-6e3c-4c14-b4e7-4155059e72a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compose_boundary_and_operation(boundary_fn, operation_fn):\n",
    "    def composed_function(da_in):\n",
    "        data_padded = boundary_fn(da_in)\n",
    "        padded_chunks = data_padded.chunks\n",
    "        non_core_dim_chunks = padded_chunks[:-1]\n",
    "        core_dim_chunks = padded_chunks[-1]\n",
    "        # need to generalize to more boundary conditions\n",
    "        rechunked_core_dim_chunks = (core_dim_chunks[0] + core_dim_chunks[1],) + core_dim_chunks[2:]\n",
    "        core_dim_axis = len(padded_chunks) - 1\n",
    "        data_padded_rechunked = data_padded.rechunk({core_dim_axis: rechunked_core_dim_chunks}) \n",
    "        core_dim_chunks = rechunked_core_dim_chunks\n",
    "        true_core_dim_chunks = ((core_dim_chunks[0]-1,) + core_dim_chunks[1:],)\n",
    "        true_chunks = non_core_dim_chunks + true_core_dim_chunks\n",
    "        return dsa.map_overlap(\n",
    "            operation_fn,\n",
    "            data_padded_rechunked,\n",
    "            depth={1: (1, 0)},\n",
    "            boundary='none',\n",
    "            trim=False,\n",
    "            meta=np.array([], dtype=data_padded_rechunked.dtype),\n",
    "            chunks=true_chunks,\n",
    "        )\n",
    "    return composed_function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "96bde340-b6aa-41f4-a2de-619b33018cbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 32 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "dask.array<diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compose_boundary_and_operation(pad, diff)(da_chunk_x.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c06d1ac7-ecce-430e-8395-f2a29e687d51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --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.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;\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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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.DataArray (y: 30, x: 20)&gt;\n",
       "dask.array&lt;diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray&gt;\n",
       "Dimensions without coordinates: y, x</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span>y</span>: 30</li><li><span>x</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e3e66ce3-fa35-4996-9332-b5ca4e98dbc9' class='xr-array-in' type='checkbox' checked><label for='section-e3e66ce3-fa35-4996-9332-b5ca4e98dbc9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(30, 5), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 32 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-72536c3a-d3b9-44db-8e1d-5fdbd39d2957' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-72536c3a-d3b9-44db-8e1d-5fdbd39d2957' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-7473c8ad-01ec-43dc-a898-3ecaba84ba8f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7473c8ad-01ec-43dc-a898-3ecaba84ba8f' 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.DataArray (y: 30, x: 20)>\n",
       "dask.array<diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>\n",
       "Dimensions without coordinates: y, x"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_out_chunk_y = xr.apply_ufunc(\n",
    "    compose_boundary_and_operation(pad, diff),\n",
    "    da_chunk_x,\n",
    "    dask=\"allowed\",\n",
    "    input_core_dims=['x'],\n",
    "    output_core_dims=['x'],\n",
    "    output_dtypes=[da_in.dtype]\n",
    ")\n",
    "da_out_chunk_y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "403529e3-aae2-4622-a9a9-7df6766142a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 6)\n",
      "Calling diff on array of shape (30, 6)\n",
      "Calling diff on array of shape (30, 6)Calling diff on array of shape (30, 6)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "np.testing.assert_equal(da_out_chunk_y.values, expected_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fe649d9-2780-46c7-8061-1f2d76315c51",
   "metadata": {},
   "source": [
    "## Attempt to copy Case 3 using `xgcm.apply_grid_ufunc`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9a70d73-0228-4ec5-ab53-a4446f86f199",
   "metadata": {},
   "source": [
    "We need to mock up a `Grid` object to use first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "50c8bf6b-fe62-4131-9584-deb4af093f6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xgcm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7554ccc1-33b8-40eb-ae87-bb64c6b052e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_c = xr.DataArray(name='x_c', data=np.arange(20) + 0.5, dims=['x_c'])\n",
    "x_g = xr.DataArray(name='x_g', data=np.arange(20), dims=['x_g'])\n",
    "y_c = xr.DataArray(name='y_c', data=np.arange(30) + 0.5, dims=['y_c'])\n",
    "y_g = xr.DataArray(name='y_g', data=np.arange(30), dims=['y_g'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5c60335f-06c9-41b5-95b7-003b8c9551ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --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.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;\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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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;\n",
       "Dimensions:  (x_c: 20, x_g: 20, y_c: 30, y_g: 30, time: 10)\n",
       "Coordinates:\n",
       "  * x_c      (x_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 15.5 16.5 17.5 18.5 19.5\n",
       "  * x_g      (x_g) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5\n",
       "  * y_g      (y_g) int64 0 1 2 3 4 5 6 7 8 9 ... 20 21 22 23 24 25 26 27 28 29\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 9\n",
       "Data variables:\n",
       "    *empty*</pre><div class='xr-wrap' hidden><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-885cddb8-0c8b-470a-a24c-72690917d5e0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-885cddb8-0c8b-470a-a24c-72690917d5e0' 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_c</span>: 20</li><li><span class='xr-has-index'>x_g</span>: 20</li><li><span class='xr-has-index'>y_c</span>: 30</li><li><span class='xr-has-index'>y_g</span>: 30</li><li><span class='xr-has-index'>time</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ccac8d28-419b-487c-aad7-0f336a6e8986' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ccac8d28-419b-487c-aad7-0f336a6e8986' class='xr-section-summary' >Coordinates: <span>(5)</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_c</span></div><div class='xr-var-dims'>(x_c)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 ... 17.5 18.5 19.5</div><input id='attrs-ef504355-6556-43ca-bb5a-1d486f43a2c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef504355-6556-43ca-bb5a-1d486f43a2c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a6a058-4a65-44f1-ad2f-d59833fbaabe' class='xr-var-data-in' type='checkbox'><label for='data-a3a6a058-4a65-44f1-ad2f-d59833fbaabe' 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,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5,\n",
       "       12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_g</span></div><div class='xr-var-dims'>(x_g)</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-0b975d90-7a40-427e-974b-aec3eae313d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b975d90-7a40-427e-974b-aec3eae313d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85e12c98-8e4d-43ca-96a6-13b22de60c30' class='xr-var-data-in' type='checkbox'><label for='data-85e12c98-8e4d-43ca-96a6-13b22de60c30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_c</span></div><div class='xr-var-dims'>(y_c)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 ... 27.5 28.5 29.5</div><input id='attrs-c49883c0-87a2-48ae-b9ee-7874ca87fe4e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c49883c0-87a2-48ae-b9ee-7874ca87fe4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc8d82be-d1d5-4b69-8050-f839d36bd830' class='xr-var-data-in' type='checkbox'><label for='data-cc8d82be-d1d5-4b69-8050-f839d36bd830' 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,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5,\n",
       "       12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5, 22.5, 23.5,\n",
       "       24.5, 25.5, 26.5, 27.5, 28.5, 29.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_g</span></div><div class='xr-var-dims'>(y_g)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-a05454fa-e443-4469-be0d-c143ad6b6dfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a05454fa-e443-4469-be0d-c143ad6b6dfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bca9f988-2cbf-4088-8aa6-1f69a5145fea' class='xr-var-data-in' type='checkbox'><label for='data-bca9f988-2cbf-4088-8aa6-1f69a5145fea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</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'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9</div><input id='attrs-8b19c5f7-807c-4589-bd99-56b92bbed181' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8b19c5f7-807c-4589-bd99-56b92bbed181' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd141e47-8bca-4491-b866-acb5366dab0a' class='xr-var-data-in' type='checkbox'><label for='data-dd141e47-8bca-4491-b866-acb5366dab0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6effb4ec-2c9c-4a02-a9f5-2d440d77d5ad' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6effb4ec-2c9c-4a02-a9f5-2d440d77d5ad' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2115d884-79c6-4ed3-9982-ad0962c2681f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2115d884-79c6-4ed3-9982-ad0962c2681f' 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>\n",
       "Dimensions:  (x_c: 20, x_g: 20, y_c: 30, y_g: 30, time: 10)\n",
       "Coordinates:\n",
       "  * x_c      (x_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 15.5 16.5 17.5 18.5 19.5\n",
       "  * x_g      (x_g) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5\n",
       "  * y_g      (y_g) int64 0 1 2 3 4 5 6 7 8 9 ... 20 21 22 23 24 25 26 27 28 29\n",
       "  * time     (time) int64 0 1 2 3 4 5 6 7 8 9\n",
       "Data variables:\n",
       "    *empty*"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_test = xr.Dataset(coords={'x_c': x_c,\n",
    "                             'x_g': x_g,\n",
    "                             'y_c': y_c,\n",
    "                             'y_g': y_g,\n",
    "                             'time': np.arange(10)})\n",
    "ds_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fe5f7896-bb3b-4a83-b32a-3cec9af50742",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xgcm.Grid>\n",
       "X Axis (periodic, boundary=None):\n",
       "  * center   x_c --> left\n",
       "  * left     x_g --> center\n",
       "Y Axis (periodic, boundary=None):\n",
       "  * center   y_c --> left\n",
       "  * left     y_g --> center"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_test = xgcm.Grid(ds_test, coords={'X': {'center': 'x_c', 'left': 'x_g'}, 'Y': {'center': 'y_c', 'left': 'y_g'}})\n",
    "grid_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "688370be-7511-4934-88d6-013d72ad0df4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --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.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;\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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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.DataArray (y_c: 30, x_c: 20)&gt;\n",
       "dask.array&lt;xarray-&lt;this-array&gt;, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * x_c      (x_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 15.5 16.5 17.5 18.5 19.5\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y_c</span>: 30</li><li><span class='xr-has-index'>x_c</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8b037b92-a3ca-4c28-80fd-f422a525ef33' class='xr-array-in' type='checkbox' checked><label for='section-8b037b92-a3ca-4c28-80fd-f422a525ef33' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(30, 5), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 4 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-0bdc27a4-ee13-4acf-91fb-8035eb1ef7a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0bdc27a4-ee13-4acf-91fb-8035eb1ef7a3' 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_c</span></div><div class='xr-var-dims'>(x_c)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 ... 17.5 18.5 19.5</div><input id='attrs-6e252f43-9868-419e-9ed7-01e1081c4861' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e252f43-9868-419e-9ed7-01e1081c4861' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-187761b7-1ead-4932-ba8e-b0c4ec17a5ea' class='xr-var-data-in' type='checkbox'><label for='data-187761b7-1ead-4932-ba8e-b0c4ec17a5ea' 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,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5,\n",
       "       12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_c</span></div><div class='xr-var-dims'>(y_c)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 ... 27.5 28.5 29.5</div><input id='attrs-7991e725-b39f-475e-bbc6-d56bc39e619f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7991e725-b39f-475e-bbc6-d56bc39e619f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81089724-b6b3-483f-8ef6-1398d891582e' class='xr-var-data-in' type='checkbox'><label for='data-81089724-b6b3-483f-8ef6-1398d891582e' 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,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5,\n",
       "       12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5, 22.5, 23.5,\n",
       "       24.5, 25.5, 26.5, 27.5, 28.5, 29.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b66b843a-6bd2-4562-a71d-b9f510d4cb39' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b66b843a-6bd2-4562-a71d-b9f510d4cb39' 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.DataArray (y_c: 30, x_c: 20)>\n",
       "dask.array<xarray-<this-array>, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * x_c      (x_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 15.5 16.5 17.5 18.5 19.5\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da_chunk_x_c = da_chunk_x.rename(x='x_c', y='y_c').assign_coords({'x_c': x_c, 'y_c': y_c})\n",
    "da_chunk_x_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1145efea-fd8e-4b9b-904b-6c9a78dd6233",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n",
      "600\n",
      "((30,), (5, 5, 5, 5))\n",
      "{'X': (1, 0)}\n",
      "630\n",
      "((30,), (1, 5, 5, 5, 5))\n",
      "{'y_c': (30,), 'x_c': (5, 5, 5, 5)}\n",
      "{'x_c': (1, 0)}\n",
      "{'x_c': (6, 5, 5, 5)}\n",
      "((30,), (5, 5, 5, 5))\n",
      "{1: (1, 0)}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --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.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;\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-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",
       "  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",
       "  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-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-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",
       "  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.DataArray (y_c: 30, x_g: 20)&gt;\n",
       "dask.array&lt;diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5\n",
       "  * x_g      (x_g) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y_c</span>: 30</li><li><span class='xr-has-index'>x_g</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5dac7f18-8766-4742-b935-48c5ad847290' class='xr-array-in' type='checkbox' checked><label for='section-5dac7f18-8766-4742-b935-48c5ad847290' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(30, 5), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.69 kiB </td> <td> 1.17 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (30, 20) </td> <td> (30, 5) </td></tr>\n",
       "    <tr><th> Count </th><td> 32 Tasks </td><td> 4 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"130\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"80\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"20\" y1=\"0\" x2=\"20\" y2=\"120\" />\n",
       "  <line x1=\"40\" y1=\"0\" x2=\"40\" y2=\"120\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 80.0,0.0 80.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"40.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >20</text>\n",
       "  <text x=\"100.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,100.000000,60.000000)\">30</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-9d5c1dc2-c208-4654-a28c-d13e8c22ee7d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d5c1dc2-c208-4654-a28c-d13e8c22ee7d' 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'>y_c</span></div><div class='xr-var-dims'>(y_c)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 3.5 ... 27.5 28.5 29.5</div><input id='attrs-f474c1c6-2bcb-4be0-94c5-c1d7b91fa95a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f474c1c6-2bcb-4be0-94c5-c1d7b91fa95a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8d621cd-e862-4836-b00b-057a34598167' class='xr-var-data-in' type='checkbox'><label for='data-e8d621cd-e862-4836-b00b-057a34598167' 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,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5,\n",
       "       12.5, 13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5, 20.5, 21.5, 22.5, 23.5,\n",
       "       24.5, 25.5, 26.5, 27.5, 28.5, 29.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_g</span></div><div class='xr-var-dims'>(x_g)</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-ef47fd13-8973-4a26-a663-b8e89f08233e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef47fd13-8973-4a26-a663-b8e89f08233e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f65a937b-f4ca-4499-9197-faf0aaf4f5da' class='xr-var-data-in' type='checkbox'><label for='data-f65a937b-f4ca-4499-9197-faf0aaf4f5da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb9d8af9-0ba0-4c82-aba5-2287f387fdd7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cb9d8af9-0ba0-4c82-aba5-2287f387fdd7' 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.DataArray (y_c: 30, x_g: 20)>\n",
       "dask.array<diff, shape=(30, 20), dtype=float64, chunksize=(30, 5), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * y_c      (y_c) float64 0.5 1.5 2.5 3.5 4.5 5.5 ... 25.5 26.5 27.5 28.5 29.5\n",
       "  * x_g      (x_g) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_diffed = xgcm.apply_as_grid_ufunc(\n",
    "    diff,\n",
    "    da_chunk_x_c,\n",
    "    axis=[(\"X\",)],\n",
    "    grid=grid_test,\n",
    "    signature=\"(X:center)->(X:left)\",\n",
    "    boundary_width={\"X\": (1, 0)},\n",
    "    # boundary='none',\n",
    "    dask=\"allowed\",\n",
    "    map_overlap=True,\n",
    ")\n",
    "data_diffed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "71fa42c5-7c40-43ff-816d-be9e88076fc5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_diffed.data.visualize(optimize_graph=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9ecbf9be-60c8-498a-a5b1-3650a29765bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calling diff on array of shape (30, 6)Calling diff on array of shape (30, 6)\n",
      "\n",
      "Calling diff on array of shape (30, 6)\n",
      "Calling diff on array of shape (30, 6)\n"
     ]
    }
   ],
   "source": [
    "np.testing.assert_equal(data_diffed.values, expected_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb77efac-3b9e-4088-a2a9-fb5d566e5553",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}