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[skip-ci] minor updates
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xarray/core/computation.py

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@@ -1036,8 +1036,7 @@ def apply_ufunc(
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Most of NumPy's builtin functions already broadcast their inputs
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appropriately for use in ``apply_ufunc``. You may find helper functions such as
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:py:func:`numpy.broadcast_arrays` helpful in writing your function. ``apply_ufunc`` also
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works well with :py:func:`numba.vectorize` and :py:func:`numba.guvectorize`. Further explanation with
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examples are provided in the xarray documentation [3]_.
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works well with :py:func:`numba.vectorize` and :py:func:`numba.guvectorize`.
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See Also
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--------
@@ -1047,12 +1046,12 @@ def apply_ufunc(
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dask.array.apply_gufunc
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xarray.map_blocks
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:ref:`dask.automatic-parallelization`
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User guide describing :py:func:`apply_ufunc` and :py:func:`map_blocks`.
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References
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----------
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.. [1] http://docs.scipy.org/doc/numpy/reference/ufuncs.html
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.. [2] http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html
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.. [3] http://xarray.pydata.org/en/stable/computation.html#wrapping-custom-computation
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"""
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from .dataarray import DataArray
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from .groupby import GroupBy

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