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   "source": [
    "## Precomputed: regridding numpy arrays"
   ]
  },
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   "source": [
    "This example shows how to interpolate numpy arrays using the :ref:`precomputed <precomputed-regrid-array>` backend. "
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   "source": [
    "from earthkit.regrid.array import regrid\n",
    "import numpy as np"
   ]
  },
  {
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   "source": [
    "First, we generate random data matching the size of an O32 octahedral reduced Gaussian grid."
   ]
  },
  {
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   "source": [
    "values = np.random.random(5248)"
   ]
  },
  {
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   "source": [
    "Interpolate the array onto a 1x1 degree global regular latitude-longitude grid using :ref:`regrid() <precomputed-regrid-array>`. The input and output grids are defined by a :ref:`gridspec <gridspec>`. Both the input and the output values are numpy arrays."
   ]
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "((181, 360), {'grid': [1, 1]})"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "res, res_grid = regrid(values, in_grid={\"grid\": \"O32\"}, out_grid={\"grid\": [1,1]}, backend=\"precomputed\") \n",
    "res.shape, res_grid"
   ]
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    ":ref:`regrid() <precomputed-regrid-array>` returns a tuple with the regridded array and the resulting gridspec."
   ]
  },
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   "execution_count": null,
   "id": "3b00a3f6-5ce3-4175-8776-8c0331f82130",
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