8000 BUG: Fix unique handling of nan entries. by ftrojan · Pull Request #18070 · numpy/numpy · GitHub
[go: up one dir, main page]
Skip to content

BUG: Fix unique handling of nan entries. #18070

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 11 commits into from
Feb 12, 2021
Merged

BUG: Fix unique handling of nan entries. #18070

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
11 commits
Select commit Hold shift + click to select a range
9563e40
benchmark bench_lib.Unique added
Dec 25, 2020
56d84b4
extended test_unique_1d
Dec 25, 2020
321f27e
modify _unique1d
Dec 25, 2020
8f2d3e8
extend test with return_index, return_inverse and return_counts param…
Dec 25, 2020
19af656
documentation updated
Dec 25, 2020
8e59b8b
Update numpy/lib/arraysetops.py
ftrojan Dec 26, 2020
00d663e
full coverage of nan types
ftrojan Dec 26, 2020
4cb1ac9
added tests for the datetime like dtypes
Dec 26, 2020
37a2ba6
nan as vector of length 1
Dec 26, 2020
8b294c5
use aux[-1] as nan, ..versionchanged, release note
Dec 28, 2020
f2a99c6
for complex arrays all NaN values are considered equivalent
Dec 28, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
use aux[-1] as nan, ..versionchanged, release note
  • Loading branch information
filip_trojan authored and filip_trojan committed Dec 28, 2020
commit 8b294c576fc67559767db6cce7da3b57844a9cc2
6 changes: 6 additions & 0 deletions doc/release/upcoming_changes/18070.improvement.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
``np.unique`` now returns single ``NaN``
----------------------------------------
When ``np.unique`` operated on an array with multiple ``NaN`` entries,
its return included a ``NaN`` for each entry that was ``NaN`` in the original array.
This is now improved such that the returned array contains just one ``NaN`` as the
last element.
11 changes: 6 additions & 5 deletions numpy/lib/arraysetops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -207,8 +207,11 @@ def unique(ar, return_index=False, return_inverse=False,
effect that we end up with a 1-D array of structured types that can be
treated in the same way as any other 1-D array. The result is that the
flattened subarrays are sorted in lexicographic order starting with the
first element. If nan values are in the input array, a single nan is put
to the end of the sorted unique values.
first element.

.. versionchanged: NumPy 1.21
If nan values are in the input array, a single nan is put
to the end of the sorted unique values.

Examples
--------
Expand Down Expand Up @@ -326,9 +329,7 @@ def _unique1d(ar, return_index=False, return_inverse=False,
mask = np.empty(aux.shape, dtype=np.bool_)
mask[:1] = True
if aux.shape[0] > 0 and aux.dtype.kind in "cfmM" and np.isnan(aux[-1]):
# Ensure that `NaT` is used for time-like dtypes
nan = np.array(np.nan).astype(aux.dtype)
aux_firstnan = np.searchsorted(aux, nan, side='left')
aux_firstnan = np.searchsorted(aux, aux[-1], side='left')
mask[1:aux_firstnan] = (aux[1:aux_firstnan] != aux[:aux_firstnan - 1])
mask[aux_firstnan] = True
mask[aux_firstnan + 1:] = False
Expand Down
0