From 748eab0fcb998472a70bb52d60904ee71a7e74cf Mon Sep 17 00:00:00 2001 From: dcherian Date: Mon, 26 Jun 2023 11:59:06 -0600 Subject: [PATCH] Small edits --- advanced/apply_ufunc/example-interp.ipynb | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/advanced/apply_ufunc/example-interp.ipynb b/advanced/apply_ufunc/example-interp.ipynb index 410db120..dd8a5cd1 100644 --- a/advanced/apply_ufunc/example-interp.ipynb +++ b/advanced/apply_ufunc/example-interp.ipynb @@ -17,7 +17,7 @@ "tags": [] }, "source": [ - "This example will illustrate how to conveniently apply an unvectorized function `func` to xarray objects using `apply_ufunc`. `func` expects 1D numpy arrays and returns a 1D numpy array. Our goal is to coveniently apply this function along a dimension of xarray objects that may or may not wrap dask arrays with a signature.\n", + "This example will illustrate how to conveniently apply an unvectorized function `func` to xarray objects using `apply_ufunc`. `func` expects 1D numpy arrays and returns a 1D numpy array. Our goal is to conveniently apply this function along a dimension of xarray objects that may or may not wrap dask arrays with a signature.\n", "\n", "We will illustrate this using [`np.interp`](https://numpy.org/doc/stable/reference/generated/numpy.interp.html): \n", "\n", @@ -43,6 +43,8 @@ "1. Automatically parallelization with dask arrays using `dask=\"parallelized\"`\n", "1. High-performance vectorization with numba and `vectorize=False`.\n", "\n", + "It puts together all the concepts covered earlier.\n", + "\n", "\n", "```{tip}\n", "We'll reduce the length of error messages using in this tutorial using `%xmode minimal` See the [ipython documentation](https://ipython.readthedocs.io/en/stable/interactive/magics.html#magic-xmode) for details.\n",