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author | Peter Andreas Entschev <peter@entschev.com> | 2019-08-14 10:08:34 +0200 |
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committer | Peter Andreas Entschev <peter@entschev.com> | 2019-08-14 10:08:34 +0200 |
commit | 5195c1bcb91ed9ac337407257d82a78b56be1665 (patch) | |
tree | fce31c454f4ea53a25c6b29245587019c6559278 /doc/neps | |
parent | b2785d85e5bd1f594067f4f918d2afaa774ef583 (diff) | |
download | numpy-5195c1bcb91ed9ac337407257d82a78b56be1665.tar.gz |
Fix NEP-30 usage example
Diffstat (limited to 'doc/neps')
-rw-r--r-- | doc/neps/nep-0030-duck-array-protocol.rst | 14 |
1 files changed, 6 insertions, 8 deletions
diff --git a/doc/neps/nep-0030-duck-array-protocol.rst b/doc/neps/nep-0030-duck-array-protocol.rst index c8faebe29..07c4275a1 100644 --- a/doc/neps/nep-0030-duck-array-protocol.rst +++ b/doc/neps/nep-0030-duck-array-protocol.rst @@ -107,10 +107,10 @@ An example of how the ``__duckarray__`` protocol could be used to write a ``stack`` function based on ``concatenate``, and its produced outcome, can be seen below. The example here was chosen not only to demonstrate the usage of the ``duckarray`` function, but also to demonstrate its dependency on the NumPy -API, demonstrated by checks on the array's ``ndim`` and ``shape`` attributes. -Note that the example is merely a simplified version of NumPy's actualy -implementation of ``stack``, and it is assumed that Dask has implemented the -``__duckarray__`` method. +API, demonstrated by checks on the array's ``shape`` attribute. Note that the +example is merely a simplified version of NumPy's actualy implementation of +``stack`` working on the first axis, and it is assumed that Dask has implemented +the ``__duckarray__`` method. .. code:: python @@ -121,10 +121,8 @@ implementation of ``stack``, and it is assumed that Dask has implemented the if len(shapes) != 1: raise ValueError('all input arrays must have the same shape') - result_ndim = arrays[0].ndim + 1 - - expanded_arrays = [arr for arr in arrays] - return np.concatenate(expanded_arrays) + expanded_arrays = [arr[np.newaxis, ...] for arr in arrays] + return np.concatenate(expanded_arrays, axis=0) dask_arr = dask.array.arange(10) np_arr = np.arange(10) |