NumPy 1.18.0 Release Notes#
In addition to the usual bug fixes, this NumPy release cleans up and documents the new random C-API, expires a large number of old deprecations, and improves the appearance of the documentation. The Python versions supported are 3.5-3.8. This is the last NumPy release series that will support Python 3.5.
Downstream developers should use Cython >= 0.29.14 for Python 3.8 support and OpenBLAS >= 3.7 to avoid problems on the Skylake architecture.
Highlights#
The C-API for
numpy.random
has been defined and documented.Basic infrastructure for linking with 64 bit BLAS and LAPACK libraries.
Many documentation improvements.
New functions#
Multivariate hypergeometric distribution added to numpy.random
#
The method multivariate_hypergeometric
has been added to the class
numpy.random.Generator
. This method generates random variates from
the multivariate hypergeometric probability distribution.
(gh-13794)
Deprecations#
np.fromfile
and np.fromstring
will error on bad data#
In future numpy releases, the functions np.fromfile
and np.fromstring
will throw an error when parsing bad data.
This will now give a DeprecationWarning
where previously partial or
even invalid data was silently returned. This deprecation also affects
the C defined functions PyArray_FromString
and PyArray_FromFile
(gh-13605)
Deprecate non-scalar arrays as fill values in ma.fill_value
#
Setting a MaskedArray.fill_value
to a non-scalar array is deprecated
since the logic to broadcast the fill value to the array is fragile,
especially when slicing.
(gh-13698)
Deprecate PyArray_As1D
, PyArray_As2D
#
PyArray_As1D
, PyArray_As2D
are deprecated, use
PyArray_AsCArray
instead
(gh-14036)
Deprecate np.alen
#
np.alen
was deprecated. Use len
instead.
(gh-14181)
Deprecate the financial functions#
In accordance with
NEP-32,
the financial functions fv
ipmt
, irr
, mirr
, nper
,
npv
, pmt
, ppmt
, pv
and rate
are deprecated, and will be
removed from NumPy 1.20.The replacement for these functions is the Python package
numpy-financial.
(gh-14720)
The axis
argument to numpy.ma.mask_cols
and numpy.ma.mask_row
is deprecated#
This argument was always ignored. (gh-14996)
Expired deprecations#
PyArray_As1D
andPyArray_As2D
have been removed in favor ofPyArray_AsCArray
(gh-14036)np.rank
has been removed. This was deprecated in NumPy 1.10 and has been replaced bynp.ndim
. (gh-14039)The deprecation of
expand_dims
out-of-range axes in 1.13.0 has expired. (gh-14051)PyArray_FromDimsAndDataAndDescr
andPyArray_FromDims
have been removed (they will always raise an error). UsePyArray_NewFromDescr
andPyArray_SimpleNew
instead. (gh-14100)numeric.loads
,numeric.load
,np.ma.dump
,np.ma.dumps
,np.ma.load
,np.ma.loads
are removed, usepickle
methods instead (gh-14256)arrayprint.FloatFormat
,arrayprint.LongFloatFormat
has been removed, useFloatingFormat
insteadarrayprint.ComplexFormat
,arrayprint.LongComplexFormat
has been removed, useComplexFloatingFormat
insteadarrayprint.StructureFormat
has been removed, useStructureVoidFormat
instead (gh-14259)np.testing.rand
has been removed. This was deprecated in NumPy 1.11 and has been replaced bynp.random.rand
. (gh-14325)Class
SafeEval
innumpy/lib/utils.py
has been removed. This was deprecated in NumPy 1.10. Usenp.safe_eval
instead. (gh-14335)Remove deprecated support for boolean and empty condition lists in
np.select
(gh-14583)Array order only accepts ‘C’, ‘F’, ‘A’, and ‘K’. More permissive options were deprecated in NumPy 1.11. (gh-14596)
np.linspace parameter
num
must be an integer. Deprecated in NumPy 1.12. (gh-14620)UFuncs with multiple outputs must use a tuple for the
out
kwarg. This finishes a deprecation started in NumPy 1.10. (gh-14682)
The files numpy/testing/decorators.py
, numpy/testing/noseclasses.py
and numpy/testing/nosetester.py
have been removed. They were never
meant to be public (all relevant objects are present in the
numpy.testing
namespace), and importing them has given a deprecation
warning since NumPy 1.15.0
(gh-14567)
Compatibility notes#
numpy.lib.recfunctions.drop_fields
can no longer return None#
If drop_fields
is used to drop all fields, previously the array would
be completely discarded and None returned. Now it returns an array of the
same shape as the input, but with no fields. The old behavior can be retained
with:
dropped_arr = drop_fields(arr, ['a', 'b'])
if dropped_arr.dtype.names == ():
dropped_arr = None
converting the empty recarray to None (gh-14510)
numpy.argmin/argmax/min/max
returns NaT
if it exists in array#
numpy.argmin
, numpy.argmax
, numpy.min
, and numpy.max
will return
NaT
if it exists in the array.
(gh-14717)
np.can_cast(np.uint64, np.timedelta64, casting='safe')
is now False
#
Previously this was True
- however, this was inconsistent with uint64
not being safely castable to int64
, and resulting in strange type
resolution.
If this impacts your code, cast uint64
to int64
first.
(gh-14718)
Changed random variate stream from numpy.random.Generator.integers
#
There was a bug in numpy.random.Generator.integers
that caused biased
sampling of 8 and 16 bit integer types. Fixing that bug has changed the
output stream from what it was in previous releases.
(gh-14777)
Add more ufunc loops for datetime64
, timedelta64
#
np.datetime('NaT')
should behave more like float('Nan')
. Add needed
infrastructure so np.isinf(a)
and np.isnan(a)
will run on
datetime64
and timedelta64
dtypes. Also added specific loops for
numpy.fmin
and numpy.fmax
that mask NaT
. This may require
adjustment to user- facing code. Specifically, code that either disallowed the
calls to numpy.isinf
or numpy.isnan
or checked that they raised an
exception will require adaptation, and code that mistakenly called
numpy.fmax
and numpy.fmin
instead of numpy.maximum
or
numpy.minimum
respectively will require adjustment. This also affects
numpy.nanmax
and numpy.nanmin
.
(gh-14841)
Moved modules in numpy.random
#
As part of the API cleanup, the submodules in numpy.random
bit_generator
, philox
, pcg64
, sfc64, ``common
, generator
,
and bounded_integers
were moved to _bit_generator
, _philox
,
_pcg64
, _sfc64, ``_common
, _generator
, and _bounded_integers
respectively to indicate that they are not part of the public interface.
(gh-14608)
C API changes#
PyDataType_ISUNSIZED(descr)
now returns False for structured datatypes#
Previously this returned True for any datatype of itemsize 0, but now this
returns false for the non-flexible datatype with itemsize 0, np.dtype([])
.
(gh-14393)
New Features#
Add our own *.pxd
cython import file#
Added a numpy/__init__.pxd
file. It will be used for cimport numpy
(gh-12284)
A tuple of axes can now be input to expand_dims
#
The numpy.expand_dims
axis
keyword can now accept a tuple of
axes. Previously, axis
was required to be an integer.
(gh-14051)
Support for 64-bit OpenBLAS#
Added support for 64-bit (ILP64) OpenBLAS. See site.cfg.example
for details.
(gh-15012)
Add --f2cmap
option to F2PY#
Allow specifying a file to load Fortran-to-C type map customizations from. (gh-15113)
Improvements#
Different C numeric types of the same size have unique names#
On any given platform, two of np.intc
, np.int_
, and np.longlong
would previously appear indistinguishable through their repr
, despite
their corresponding dtype
having different properties.
A similar problem existed for the unsigned counterparts to these types, and on
some platforms for np.double
and np.longdouble
These types now always print with a unique __name__
.
(gh-10151)
argwhere
now produces a consistent result on 0d arrays#
On N-d arrays, numpy.argwhere
now always produces an array of shape
(n_non_zero, arr.ndim)
, even when arr.ndim == 0
. Previously, the
last axis would have a dimension of 1 in this case.
(gh-13610)
Add axis
argument for random.permutation
and random.shuffle
#
Previously the random.permutation
and random.shuffle
functions
can only shuffle an array along the first axis; they now have a
new argument axis
which allows shuffle along a specified axis.
(gh-13829)
method
keyword argument for np.random.multivariate_normal
#
A method
keyword argument is now available for
np.random.multivariate_normal
with possible values
{'svd', 'eigh', 'cholesky'}
. To use it, write
np.random.multivariate_normal(..., method=<method>)
.
(gh-14197)
Add complex number support for numpy.fromstring
#
Now numpy.fromstring
can read complex numbers.
(gh-14227)
numpy.unique
has consistent axes order when axis
is not None#
Using moveaxis
instead of swapaxes
in numpy.unique
, so that the ordering of axes
except the axis in arguments will not be broken.
(gh-14255)
numpy.matmul
with boolean output now converts to boolean values#
Calling numpy.matmul
where the output is a boolean array would fill the array
with uint8 equivalents of the result, rather than 0/1. Now it forces the output
to 0 or 1 (NPY_TRUE
or NPY_FALSE
).
(gh-14464)
numpy.random.randint
produced incorrect value when the range was 2**32
#
The implementation introduced in 1.17.0 had an incorrect check when
determining whether to use the 32-bit path or the full 64-bit
path that incorrectly redirected random integer generation with a high - low
range of 2**32
to the 64-bit generator.
(gh-14501)
Add complex number support for numpy.fromfile
#
Now numpy.fromfile
can read complex numbers.
(gh-14730)
std=c99
added if compiler is named gcc
#
GCC before version 5 requires the -std=c99
command line argument. Newer
compilers automatically turn on C99 mode. The compiler setup code will
automatically add the code if the compiler name has gcc
in it.
(gh-14771)
Changes#
NaT
now sorts to the end of arrays#
NaT
is now effectively treated as the largest integer for sorting
purposes, so that it sorts to the end of arrays. This change is for consistency
with NaN
sorting behavior.
(gh-12658)
(gh-15068)
Incorrect threshold
in np.set_printoptions
raises TypeError
or ValueError
#
Previously an incorrect threshold
raised ValueError
; it now raises TypeError
for non-numeric types and ValueError
for nan
values.
(gh-13899)
Warn when saving a dtype with metadata#
A UserWarning
will be emitted when saving an array via numpy.save
with
metadata
. Saving such an array may not preserve metadata, and if metadata
is preserved, loading it will cause a ValueError
. This shortcoming in save
and load will be addressed in a future release.
(gh-14142)
numpy.distutils
append behavior changed for LDFLAGS and similar#
numpy.distutils
has always overridden rather than appended to LDFLAGS
and
other similar such environment variables for compiling Fortran extensions. Now
the default behavior has changed to appending - which is the expected behavior
in most situations. To preserve the old (overwriting) behavior, set the
NPY_DISTUTILS_APPEND_FLAGS
environment variable to 0. This applies to:
LDFLAGS
, F77FLAGS
, F90FLAGS
, FREEFLAGS
, FOPT
, FDEBUG
,
and FFLAGS
. NumPy 1.16 and 1.17 gave build warnings in situations where this
change in behavior would have affected the compile flags used.
(gh-14248)
Remove numpy.random.entropy
without a deprecation#
numpy.random.entropy
was added to the numpy.random
namespace in 1.17.0.
It was meant to be a private c-extension module, but was exposed as public.
It has been replaced by numpy.random.SeedSequence
so the module was
completely removed.
(gh-14498)
Add options to quiet build configuration and build with -Werror
#
Added two new configuration options. During the build_src
subcommand, as
part of configuring NumPy, the files _numpyconfig.h
and config.h
are
created by probing support for various runtime functions and routines.
Previously, the very verbose compiler output during this stage clouded more
important information. By default the output is silenced. Running
runtests.py --debug-info
will add --verbose-cfg
to the build_src
subcommand,which will restore the previous behaviour.
Adding CFLAGS=-Werror
to turn warnings into errors would trigger errors
during the configuration. Now runtests.py --warn-error
will add
--warn-error
to the build
subcommand, which will percolate to the
build_ext
and build_lib
subcommands. This will add the compiler flag
to those stages and turn compiler warnings into errors while actually building
NumPy itself, avoiding the build_src
subcommand compiler calls.