BUG: issues with hash-function for Float64HashTable (GH21866) #21904

realead · 2018-07-13T22:09:40Z

The following issues

hash(0.0) != hash(-0.0)
hash(x) != hash(y) for different x,y which are nans

are solved by setting:

hash(-0.0):=hash(0.0)
hash(x):=hash(np.nan) for every x which is nan

closes Issues with hash-function for float64 version of klib's hash-map #21866
tests added / passed
passes git diff upstream/master -u -- "*.py" | flake8 --diff
whatsnew entry

jbrockmendel · 2018-07-14T03:49:47Z

Test failure appears unrelated. Can you push again to re-run it?

codecov · 2018-07-14T05:16:44Z

Codecov Report

Merging #21904 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master   #21904   +/-   ##
=======================================
  Coverage   91.99%   91.99%           
=======================================
  Files         167      167           
  Lines       50578    50578           
=======================================
  Hits        46530    46530           
  Misses       4048     4048

Flag	Coverage Δ
#multiple	`90.4% <ø> (ø)`	⬆️
#single	`42.17% <ø> (ø)`	⬆️

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jreback · 2018-07-14T14:11:42Z

can you run an asv and report any anomalies

jreback

does this have any user level visible effects?
can you add a whatsnew note (0.24.0), depending on your answer above either API changes or other Enhancements section.

realead · 2018-07-14T14:57:05Z

@jbrockmendel No, it was a problem in the one of the added test cases: somewhat naively 16GB memory were reserved (but not committed!), yet obviously different operating systems with different resources reacts differently to such a request.

It is a little bit strange, that the testing just died and didn't recover from that...

I removed these silly tests and now it looks better (at least it is clear, what goes wrong).

jreback · 2018-07-14T14:58:19Z

pandas/_libs/src/klib/khash_python.h

-#define kh_float64_hash_func(key) (khint32_t)((asint64(key))>>33^(asint64(key))^(asint64(key))<<11)
+
+// correct for all inputs but not -0.0 and NaNs
+#define kh_float64_hash_func_0_NAN(key) (khint32_t)((asint64(key))>>33^(asint64(key))^(asint64(key))<<11)


can you add a blank between cases

@jreback Sorry for the silly question: Do you expect me to add a new commit with the improvements to the branch and you will fixup it when merging or should I amend the current commit?

generally push new commits.

needs to add a whatsnew in any event

realead · 2018-07-15T20:24:18Z

pandas/_libs/src/klib/khash_python.h

+
+// correct for all
+#define kh_float64_hash_func(key) ((key) != (key) ?                       \
+                                   kh_float64_hash_func_NAN(Py_NAN) :     \


Not sure about Py_NAN:

Must the case of Py_NO_NAN be taken into account?

There is PANDAS_NAN, but here Py_NAN didn't require additional includes.

PS: NAN from math.h isn't defined for some plattforms.

jreback · 2018-07-16T10:32:28Z

doc/source/whatsnew/v0.24.0.txt

 - Invalid construction of ``IntervalDtype`` will now always raise a ``TypeError`` rather than a ``ValueError`` if the subdtype is invalid (:issue:`21185`)
 - Trying to reindex a ``DataFrame`` with a non unique ``MultiIndex`` now raises a ``ValueError`` instead of an ``Exception`` (:issue:`21770`)
-
+- :class:`Float64HashTable` handles zeros/signed zeros and all flavors of NaNs consistently: it is no longer possible to have both, zero and signed-zero, as keys at the same time in a table, also there can be at most one NaN-key in a table (:issue:`21866`)


this is not public, my question below was whether this has a public change?

It fixes the bug #21866, i.e. produces right results for some esoteric corner cases. This change of behavior can be observed by the end-user, but is this then a public change worth mentioning?

#21866 (comment)

is this the public case? you can list this, but just make it related to the effect on .unique()

also add a test w.r.t. unique

jreback · 2018-07-17T00:53:58Z

doc/source/whatsnew/v0.24.0.txt

 - :meth:`Series.nlargest`, :meth:`Series.nsmallest`, :meth:`DataFrame.nlargest`, and :meth:`DataFrame.nsmallest` now accept the value ``"all"`` for the ``keep`` argument. This keeps all ties for the nth largest/smallest value (:issue:`16818`)
 - :class:`IntervalIndex` has gained the :meth:`~IntervalIndex.set_closed` method to change the existing ``closed`` value (:issue:`21670`)
 - :func:`~DataFrame.to_csv` and :func:`~DataFrame.to_json` now support ``compression='infer'`` to infer compression based on filename (:issue:`15008`)
+- :class:`Float64HashTable` handles zeros/signed zeros and all flavors of NaNs consistently: it is no longer possible to have both, zero and signed-zero, as keys at the same time in a table, also there can be at most one NaN-key in a table (:issue:`21866`)


right, can you reword to just focus on .unique()

jreback

doc comments. rebase & ping on green.

jreback · 2018-07-20T12:56:16Z

pandas/tests/test_algos.py

        tm.assert_numpy_array_equal(result, expected, strict_nan=True)

+    def test_signed_zero(self):
+        a = np.array([-0.0, 0.0])


can you add the issue number here as a comment (and on test below)

jreback · 2018-07-20T12:57:11Z

doc/source/whatsnew/v0.24.0.txt

 - :meth:`Series.nlargest`, :meth:`Series.nsmallest`, :meth:`DataFrame.nlargest`, and :meth:`DataFrame.nsmallest` now accept the value ``"all"`` for the ``keep`` argument. This keeps all ties for the nth largest/smallest value (:issue:`16818`)
 - :class:`IntervalIndex` has gained the :meth:`~IntervalIndex.set_closed` method to change the existing ``closed`` value (:issue:`21670`)
 - :func:`~DataFrame.to_csv` and :func:`~DataFrame.to_json` now support ``compression='infer'`` to infer compression based on filename (:issue:`15008`)
+- :func:`unique` handles signed zeros consistently: it is no longer possible to have both, 0.0 and -0.0, in the same resulting array (:issue:`21866`)


move to bug fix / Numeric section.

The following issues 1) hash(0.0) != hash(-0.0) 2) hash(x) != hash(y) for different x,y which are nans are solved by setting: 1) hash(-0.0):=hash(0.0) 2) hash(x):=hash(np.nan) for every x which is nan

realead · 2018-07-21T17:22:24Z

@jreback Done.

jreback · 2018-07-25T10:36:25Z

@jbrockmendel any comments? if ok pls merge.

jbrockmendel · 2018-07-25T19:13:24Z

@realead good job catching a subtle bug. Thanks for taking point on this.

it is more or less the clean-up after PR pandas-dev#21904 and PR pandas-dev#22207, the underlying hash-map handles all cases correctly out-of-the box and thus no special handling is needed.

…-dev#21904) * BUG: issues with hash-function for Float64HashTable (GH21866) The following issues 1) hash(0.0) != hash(-0.0) 2) hash(x) != hash(y) for different x,y which are nans are solved by setting: 1) hash(-0.0):=hash(0.0) 2) hash(x):=hash(np.nan) for every x which is nan * add the id of the issue to tests

realead force-pushed the hash_for_float64_GH21866 branch from 0d7fe27 to 2cec96e Compare July 14, 2018 05:16

realead force-pushed the hash_for_float64_GH21866 branch from 2cec96e to 94b7087 Compare July 14, 2018 13:41

jreback requested changes Jul 14, 2018

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jreback added the Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff label Jul 14, 2018

jreback reviewed Jul 14, 2018

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realead commented Jul 15, 2018

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jreback requested changes Jul 16, 2018

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realead force-pushed the hash_for_float64_GH21866 branch from 4bf5983 to 0f77145 Compare July 16, 2018 18:42

jreback reviewed Jul 17, 2018

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jreback requested changes Jul 20, 2018

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jreback added this to the 0.24.0 milestone Jul 20, 2018

realead added 2 commits July 21, 2018 08:45

BUG: issues with hash-function for Float64HashTable (GH21866)

7f12a1d

The following issues 1) hash(0.0) != hash(-0.0) 2) hash(x) != hash(y) for different x,y which are nans are solved by setting: 1) hash(-0.0):=hash(0.0) 2) hash(x):=hash(np.nan) for every x which is nan

add the id of the issue to tests

124b095

realead force-pushed the hash_for_float64_GH21866 branch from 11131c9 to 124b095 Compare July 21, 2018 06:46

jreback approved these changes Jul 25, 2018

View reviewed changes

jbrockmendel merged commit 2c7c797 into pandas-dev:master Jul 25, 2018

realead deleted the hash_for_float64_GH21866 branch August 9, 2018 19:34

realead mentioned this pull request Aug 12, 2018

BUG: don't mangle NaN-float-values and pd.NaT (GH 22295) #22296

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BUG: issues with hash-function for Float64HashTable (GH21866) #21904

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realead commented Jul 21, 2018

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realead commented Jul 13, 2018 •

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