# 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`

and`PyArray_As2D`

have been removed in favor of`PyArray_AsCArray`

(gh-14036)`np.rank`

has been removed. This was deprecated in NumPy 1.10 and has been replaced by`np.ndim`

. (gh-14039)The deprecation of

`expand_dims`

out-of-range axes in 1.13.0 has expired. (gh-14051)`PyArray_FromDimsAndDataAndDescr`

and`PyArray_FromDims`

have been removed (they will always raise an error). Use`PyArray_NewFromDescr`

and`PyArray_SimpleNew`

instead. (gh-14100)`numeric.loads`

,`numeric.load`

,`np.ma.dump`

,`np.ma.dumps`

,`np.ma.load`

,`np.ma.loads`

are removed, use`pickle`

methods instead (gh-14256)`arrayprint.FloatFormat`

,`arrayprint.LongFloatFormat`

has been removed, use`FloatingFormat`

instead`arrayprint.ComplexFormat`

,`arrayprint.LongComplexFormat`

has been removed, use`ComplexFloatingFormat`

instead`arrayprint.StructureFormat`

has been removed, use`StructureVoidFormat`

instead (gh-14259)`np.testing.rand`

has been removed. This was deprecated in NumPy 1.11 and has been replaced by`np.random.rand`

. (gh-14325)Class

`SafeEval`

in`numpy/lib/utils.py`

has been removed. This was deprecated in NumPy 1.10. Use`np.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.