# Release Notes¶

These are the major changes made in each release. For details of the changes see the commit log at https://github.com/pydata/bottleneck

## Bottleneck 1.4.0¶

*Release date: in development*

### Bug Fixes¶

### Contributors¶

### Bug Fixes¶

Explicitly declare numpy version dependency in

`pyproject.toml`

for Python 3.8, fixing certain cases where`pip install`

would fail. Thanks to`@goggle`

,`@astrofrog`

, and`@0xb0b`

for reporting. (#277)

### Contributors¶

A total of 1 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Christopher Whelan

#### Bottleneck 1.3.1¶

*Release date: 2019-11-18*

### Bug Fixes¶

Fix memory leak in

`bottleneck.nanmedian()`

with the default argument of`axis=None`

. Thanks to`@jsmodic`

for reporting! (#276, #278)Add regression test for memory leak case (#279)

### Contributors¶

A total of 1 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Christopher Whelan

#### Bottleneck 1.3.0¶

*Release date: 2019-11-12*

### Project Updates¶

Bottleneck has a new maintainer, Christopher Whelan (

`@qwhelan`

on GitHub).Documentation now hosted at https://bottleneck.readthedocs.io

1.3.x will be the last release to support Python 2.7

Bottleneck now supports and is tested against Python 3.7 and 3.8. (#211, #268)

The

`LICENSE`

file has been restructured to only include the license for the Bottleneck project to aid license audit tools. There has been no change to the licensing of Bottleneck.Licenses for other projects incorporated by Bottleneck are now reproduced in full in separate files in the

`LICENSES/`

directory (eg,`LICENSES/NUMPY_LICENSE`

)All licenses have been updated. Notably, setuptools is now MIT licensed and no longer under the ambiguous dual PSF/Zope license.

Bottleneck now uses

**PEP 518**for specifying build dependencies, with per Python version specifications (#247)

### Enhancements¶

Remove

`numpydoc`

package from Bottleneck source distribution`bottleneck.slow.reduce.nansum()`

and`bottleneck.slow.reduce.ss()`

now longer coerce output to have the same dtype as inputTest (tox, travis, appveyor) against latest

`numpy`

(in conda)Performance benchmarking also available via

`asv`

`versioneer`

now used for versioning (#213)Test suite now uses

`pytest`

as`nose`

is deprecated (#222)`python setup.py build_ext --inplace`

is now incremental (#224)`python setup.py clean`

now cleans all artifacts (#226)Compiler feature support now identified by testing rather than hardcoding (#227)

The

`BN_OPT_3`

macro allows selective use of`-O3`

at the function level (#223)Contributors are now automatically cited in the release notes (#244)

### Performance¶

Speed up

`bottleneck.reduce.anynan()`

and`bottleneck.reduce.allnan()`

by 2x via`BN_OPT_3`

(#223)All functions covered by

`asv`

benchmarks`bottleneck.nonreduce.replace()`

speedup of 4x via more explicit typing (#239)`bottleneck.reduce.median()`

up to 2x faster for Fortran-ordered arrays (#248)

### Bug Fixes¶

Documentation fails to build on Python 3 (#170)

`bottleneck.benchmark.bench()`

crashes on python 3.6.3, numpy 1.13.3 (#175)`bottleneck.nonreduce_axis.push()`

raises when`n=None`

is explicitly passed (#178)`bottleneck.reduce.nansum()`

wrong output when`a = np.ones((2, 2))[..., np.newaxis]`

same issue of other reduce functions (#183)Silenced FutureWarning from NumPy in the slow version of move functions (#194)

Installing bottleneck onto a system that does not already have Numpy (#195)

Memory leaked when input was not a NumPy array (#201)

Tautological comparison in

`bottleneck.move.move_rank()`

removed (#207, #212)

### Cleanup¶

### Contributors¶

A total of 9 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Ales Erjavec +

Christoph Gohlke

Christopher Whelan +

Daniel Hakimi +

Ghislain Antony Vaillant +

Keith Goodman

Stephan Hoyer

Thomas Robitaille +

kwgoodman

#### Bottleneck 1.2.1¶

*Release date: 2017-05-15*

This release adds support for NumPy’s relaxed strides checking and fixes a few bugs.

**Bug Fixes**

Installing bottleneck when two versions of NumPy are present (#156)

Compiling on Ubuntu 14.04 inside a Windows 7 WMware (#157)

Occasional segmentation fault in

`bn.nanargmin()`

,`nanargmax()`

,`median()`

, and`nanmedian()`

when all of the following conditions are met: axis is None, input array is 2d or greater, and input array is not C contiguous. (#159)Reducing np.array([2**31], dtype=np.int64) overflows on Windows (#163)

**Contributors**

A total of 1 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Keith Goodman

#### Bottleneck 1.2.0¶

*Release date: 2016-10-20*

This release is a complete rewrite of Bottleneck.

**Port to C**

Bottleneck is now written in C

Cython is no longer a dependency

Source tarball size reduced by 80%

Build time reduced by 66%

Install size reduced by 45%

**Redesign**

Besides porting to C, much of bottleneck has been redesigned to be simpler and faster. For example, bottleneck now uses its own N-dimensional array iterators, reducing function call overhead.

**New features**

The new function bench_detailed runs a detailed performance benchmark on a single bottleneck function.

Bottleneck can be installed on systems that do not yet have NumPy installed. Previously that only worked on some systems.

**Beware**

Functions partsort and argpartsort have been renamed to partition and argpartition to match NumPy. Additionally the meaning of the input arguments have changed:

`bn.partsort(a, n)()`

is now equivalent to`bn.partition(a, kth=n-1)()`

. Similarly for bn.argpartition.The keyword for array input has been changed from arr to a in all functions. It now matches NumPy.

**Thanks**

Moritz E. Beber: continuous integration with AppVeyor

Christoph Gohlke: Windows compatibility

Jennifer Olsen: comments and suggestions

A special thanks to the Cython developers. The quickest way to appreciate their work is to remove Cython from your project. It is not easy.

**Contributors**

A total of 3 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Keith Goodman

Moritz E. Beber +

kwgoodman

#### Bottleneck 1.1.0¶

*Release date: 2016-06-22*

This release makes Bottleneck more robust, releases GIL, adds new functions.

**More Robust**

`bn.move_median()`

can now handle NaNs and min_count parameter`bn.move_std()`

is slower but numerically more stableBottleneck no longer crashes on byte-swapped input arrays

**Faster**

All Bottleneck functions release the GIL

median is faster if the input array contains NaN

move_median is faster for input arrays that contain lots of NaNs

No speed penalty for median, nanmedian, nanargmin, nanargmax for Fortran ordered input arrays when axis is None

Function call overhead cut in half for reduction along all axes (axis=None) if the input array satisfies at least one of the following properties: 1d, C contiguous, F contiguous

Reduction along all axes (axis=None) is more than twice as fast for long, narrow input arrays such as a (1000000, 2) C contiguous array and a (2, 1000000) F contiguous array

**New Functions**

move_var

move_argmin

move_argmax

move_rank

push

**Beware**

`bn.median()`

now returns NaN for a slice that contains one or more NaNsInstead of using the distutils default, the ‘-O2’ C compiler flag is forced

`bn.move_std()`

output changed when mean is large compared to standard deviationFixed: Non-accelerated moving window functions used min_count incorrectly

`bn.move_median()`

is a bit slower for float input arrays that do not contain NaN

**Thanks**

Alphabeticaly by last name

Alessandro Amici worked on setup.py

Pietro Battiston modernized bottleneck installation

Moritz E. Beber set up continuous integration with Travis CI

Jaime Frio improved the numerical stability of move_std

Christoph Gohlke revived Windows compatibility

Jennifer Olsen added NaN support to move_median

**Contributors**

A total of 10 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Alessandro Amici +

Christoph Gohlke

Jaime Fernandez +

Jenn Olsen +

Keith Goodman

Midnighter +

Pietro Battiston +

jaimefrio +

jennolsen84 +

kwgoodman

#### Bottleneck 1.0.0¶

*Release date: 2015-02-06*

This release is a complete rewrite of Bottleneck.

**Faster**

“python setup.py build” is 18.7 times faster

Function-call overhead cut in half—a big speed up for small input arrays

Arbitrary ndim input arrays accelerated; previously only 1d, 2d, and 3d

bn.nanrankdata is twice as fast for float input arrays

bn.move_max, bn.move_min are faster for int input arrays

No speed penalty for reducing along all axes when input is Fortran ordered

**Smaller**

Compiled binaries 14.1 times smaller

Source tarball 4.7 times smaller

9.8 times less C code

4.3 times less Cython code

3.7 times less Python code

**Beware**

Requires numpy 1.9.1

Single API, e.g.: bn.nansum instead of bn.nansum and nansum_2d_float64_axis0

On 64-bit systems bn.nansum(int32) returns int32 instead of int64

bn.nansum now returns 0 for all NaN slices (as does numpy 1.9.1)

Reducing over all axes returns, e.g., 6.0; previously np.float64(6.0)

bn.ss() now has default axis=None instead of axis=0

bn.nn() is no longer in bottleneck

**min_count**

Previous releases had moving window function pairs: move_sum, move_nansum

This release only has half of the pairs: move_sum

Instead a new input parameter, min_count, has been added

min_count=None same as old move_sum; min_count=1 same as old move_nansum

If # non-NaN values in window < min_count, then NaN assigned to the window

Exception: move_median does not take min_count as input

**Bug Fixes**

Can now install bottleneck with pip even if numpy is not already installed

bn.move_max, bn.move_min now return float32 for float32 input

**Contributors**

A total of 4 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Keith Goodman

Lev Givon +

Stephan Hoyer

kwgoodman

#### Bottleneck 0.8.0¶

*Release date: 2014-01-21*

This version of Bottleneck requires NumPy 1.8.

**Breaks from 0.7.0**

This version of Bottleneck requires NumPy 1.8

nanargmin and nanargmax behave like the corresponding functions in NumPy 1.8

**Bug fixes**

nanargmax/nanargmin wrong for redundant max/min values in 1d int arrays

**Contributors**

A total of 4 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Christoph Gohlke +

Keith Goodman

Stephan Hoyer +

kwgoodman

#### Bottleneck 0.7.0¶

*Release date: 2013-09-10*

**Enhancements**

bn.rankdata() is twice as fast (with input a = np.random.rand(1000000))

C files now included in github repo; cython not needed to try latest

C files are now generated with Cython 0.19.1 instead of 0.16

Test bottleneck across multiple python/numpy versions using tox

Source tarball size cut in half

**Bug fixes**

move_std, move_nanstd return inappropriate NaNs (sqrt of negative #) (#50)

make test fails on some computers (#52)

scipy optional yet some unit tests depend on scipy (#57)

nanstd([1.0], ddof=1) and nanvar([1.0], ddof=1) crash (#60)

**Contributors**

A total of 5 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Jens Hedegaard Nielsen +

John Benediktsson +

Keith Goodman

jmcloughlin +

kwgoodman

#### Bottleneck 0.6.0¶

*Release date: 2012-06-04*

Thanks to Dougal Sutherland, Bottleneck now runs on Python 3.2.

**New functions**

replace(arr, old, new), e.g, replace(arr, np.nan, 0)

nn(arr, arr0, axis) nearest neighbor and its index of 1d arr0 in 2d arr

anynan(arr, axis) faster alternative to np.isnan(arr).any(axis)

allnan(arr, axis) faster alternative to np.isnan(arr).all(axis)

**Enhancements**

Python 3.2 support (may work on earlier versions of Python 3)

C files are now generated with Cython 0.16 instead of 0.14.1

Upgrade numpydoc from 0.3.1 to 0.4 to support Sphinx 1.0.1

**Breaks from 0.5.0**

Support for Python 2.5 dropped

Default axis for benchmark suite is now axis=1 (was 0)

**Bug fixes**

Confusing error message in partsort and argpartsort (#31)

Update path in MANIFEST.in (#32)

Wrong output for very large (2**31) input arrays (#35)

**Contributors**

A total of 4 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.

Ben Root +

Dougal Sutherland +

Keith Goodman

kwgoodman +

#### Bottleneck 0.5.0¶

*Release date: 2011-06-13*

The fifth release of bottleneck adds four new functions, comes in a single source distribution instead of separate 32 and 64 bit versions, and contains bug fixes.

J. David Lee wrote the C-code implementation of the double heap moving window median.

**New functions**

move_median(), moving window median

partsort(), partial sort

argpartsort()

ss(), sum of squares, faster version of scipy.stats.ss

**Changes**

Single source distribution instead of separate 32 and 64 bit versions

nanmax and nanmin now follow Numpy 1.6 (not 1.5.1) when input is all NaN

**Bug fixes**

#### Bottleneck 0.4.3¶

*Release date: 2011-03-17*

This is a bug fix release.

**Bug fixes**

median and nanmedian modified (partial sort) input array (#11)

nanmedian wrong when odd number of elements with all but last a NaN (#12)

**Enhancement**

Lazy import of SciPy (rarely used) speeds Bottleneck import 3x

#### Bottleneck 0.4.2¶

*Release date: 2011-03-08*

This is a bug fix release.

Same bug fixed in Bottleneck 0.4.1 for nanstd() was fixed for nanvar() in this release. Thanks again to Christoph Gohlke for finding the bug.

#### Bottleneck 0.4.1¶

*Release date: 2011-03-08*

This is a bug fix release.

The low-level functions nanstd_3d_int32_axis1 and nanstd_3d_int64_axis1, called by bottleneck.nanstd(), wrote beyond the memory owned by the output array if arr.shape[1] == 0 and arr.shape[0] > arr.shape[2], where arr is the input array.

Thanks to Christoph Gohlke for finding an example to demonstrate the bug.

#### Bottleneck 0.4.0¶

*Release date: 2011-03-08*

The fourth release of Bottleneck contains new functions and bug fixes. Separate source code distributions are now made for 32 bit and 64 bit operating systems.

**New functions**

rankdata()

nanrankdata()

**Enhancements**

Optionally specify the shapes of the arrays used in benchmark

Can specify which input arrays to fill with one-third NaNs in benchmark

**Breaks from 0.3.0**

Removed group_nanmean() function

Bump dependency from NumPy 1.4.1 to NumPy 1.5.1

C files are now generated with Cython 0.14.1 instead of 0.13

**Bug fixes**

#### Bottleneck 0.3.0¶

*Release date: 2010-01-19*

The third release of Bottleneck is twice as fast for small input arrays and contains 10 new functions.

**Faster**

All functions are faster (less overhead in selector functions)

**New functions**

nansum()

move_sum()

move_nansum()

move_mean()

move_std()

move_nanstd()

move_min()

move_nanmin()

move_max()

move_nanmax()

**Enhancements**

You can now specify the dtype and axis to use in the benchmark timings

Improved documentation and more unit tests

**Breaks from 0.2.0**

Moving window functions now default to axis=-1 instead of axis=0

Low-level moving window selector functions no longer take window as input

**Bug fix**

int input array resulted in call to slow, non-cython version of move_nanmean

#### Bottleneck 0.2.0¶

*Release date: 2010-12-27*

The second release of Bottleneck is faster, contains more functions, and supports more dtypes.

**Faster**

All functions faster (less overhead) when output is not a scalar

Faster nanmean() for 2d, 3d arrays containing NaNs when axis is not None

**New functions**

nanargmin()

nanargmax()

nanmedian()

**Enhancements**

Added support for float32

Fallback to slower, non-Cython functions for unaccelerated ndim/dtype

Scipy is no longer a dependency

Added support for older versions of NumPy (1.4.1)

All functions are now templated for dtype and axis

Added a sandbox for prototyping of new Bottleneck functions

Rewrote benchmarking code

#### Bottleneck 0.1.0¶

*Release date: 2010-12-10*

Initial release. The three categories of Bottleneck functions:

Faster replacement for NumPy and SciPy functions

Moving window functions

Group functions that bin calculations by like-labeled elements