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| author | Stefan van der Walt <stefanv@berkeley.edu> | 2018-07-25 11:26:12 -0700 |
|---|---|---|
| committer | Stefan van der Walt <stefanv@berkeley.edu> | 2018-07-25 11:26:12 -0700 |
| commit | 47904579abb339ca380bf36c4cc72ebfbd0d0643 (patch) | |
| tree | 5567f6e30b2bf178fc4de395e8dbd7648f46dd99 /doc/neps | |
| parent | 67e7414910c6ea90940f767e037cebe10bb4d86d (diff) | |
| download | numpy-47904579abb339ca380bf36c4cc72ebfbd0d0643.tar.gz | |
Clarify comment on scalar conversion inconsistency.
Diffstat (limited to 'doc/neps')
| -rw-r--r-- | doc/neps/roadmap.rst | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/doc/neps/roadmap.rst b/doc/neps/roadmap.rst index c9c1976c9..1cd522463 100644 --- a/doc/neps/roadmap.rst +++ b/doc/neps/roadmap.rst @@ -103,8 +103,10 @@ Numpy has both scalars and zero-dimensional arrays. - The current implementation adds a large maintenance burden -- can we remove scalars and/or simplify it internally? -- Zero dimensional arrays get converted into scalars by most NumPy functions. - Can this be fixed? +- Zero dimensional arrays get converted into scalars by most NumPy + functions (i.e., output of `np.sin(x)` depends on whether `x` is + zero-dimensional or not). This inconsistency should be addressed, + so that one could, e.g., write sane type annotations. .. _`NEP 19`: https://www.numpy.org/neps/nep-0019-rng-policy.html .. _`NEP 22`: http://www.numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html |