# NumPy 1.22.0 Release Notes¶

## Deprecations¶

the misspelled keyword argument

`delimitor`

of`numpy.ma.mrecords.fromtextfile()`

has been changed into`delimiter`

, using it will emit a deprecation warning.(gh-19921)

### Passing boolean `kth`

values to (arg-)partition has been deprecated¶

`partition`

and `argpartition`

would previously accept boolean
values for the `kth`

parameter, which would subsequently be converted into
integers. This behavior has now been deprecated.

(gh-20000)

## Expired deprecations¶

Using the strings

`"Bytes0"`

,`"Datetime64"`

,`"Str0"`

,`"Uint32"`

, and`"Uint64"`

as a dtype will now raise a`TypeError`

.(gh-19539)

### Expired deprecations for `loads`

, `ndfromtxt`

, and `mafromtxt`

in npyio¶

`numpy.loads`

was deprecated in v1.15, with the recommendation that users
use `pickle.loads`

instead.
`ndfromtxt`

and `mafromtxt`

were both deprecated in v1.17 - users should
use `numpy.genfromtxt`

instead with the appropriate value for the
`usemask`

parameter.

(gh-19615)

## Compatibility notes¶

### Distutils forces strict floating point model on clang¶

NumPy now sets the `-ftrapping-math`

option on clang to enforce correct
floating point error handling for universal functions.
Clang defaults to non-IEEE and C99 conform behaviour otherwise.
This change (using the equivalent but newer `-ffp-exception-behavior=strict`

)
was attempted in NumPy 1.21, but was effectively never used.

(gh-19479)

## C API changes¶

### Masked inner-loops cannot be customized anymore¶

The masked inner-loop selector is now never used. A warning will be given in the unlikely event that it was customized.

We do not expect that any code uses this. If you do use it, you must unset the selector on newer NumPy version. Please also contact the NumPy developers, we do anticipate providing a new, more specific, mechanism.

The customization was part of a never-implemented feature to allow for faster masked operations.

(gh-19259)

## New Features¶

### Implementation of the NEP 47 (adopting the array API standard)¶

An initial implementation of NEP 47 (adoption the array API standard) has
been added as `numpy.array_api`

. The implementation is experimental and will
issue a UserWarning on import, as the array API standard is still in draft state.
`numpy.array_api`

is a conforming implementation of the array API standard,
which is also minimal, meaning that only those functions and behaviors that
are required by the standard are implemented (see the NEP for more info).
Libraries wishing to make use of the array API standard are encouraged to use
`numpy.array_api`

to check that they are only using functionality that is
guaranteed to be present in standard conforming implementations.

(gh-18585)

### Generate C/C++ API reference documentation from comments blocks is now possible¶

This feature depends on Doxygen in the generation process and on Breathe to integrate it with Sphinx.

(gh-18884)

### Assign the platform-specific `c_intp`

precision via a mypy plugin¶

The mypy plugin, introduced in numpy/numpy#17843, has again been expanded:
the plugin now is now responsible for setting the platform-specific precision
of `numpy.ctypeslib.c_intp`

, the latter being used as data type for various
`numpy.ndarray.ctypes`

attributes.

Without the plugin, aforementioned type will default to `ctypes.c_int64`

.

To enable the plugin, one must add it to their mypy configuration file:

```
[mypy]
plugins = numpy.typing.mypy_plugin
```

(gh-19062)

`keepdims`

optional argument added to `numpy.argmin`

, `numpy.argmax`

¶

`keepdims`

argument is added to `numpy.argmin`

, `numpy.argmax`

.
If set to `True`

, the axes which are reduced are left in the result as dimensions with size one.
The resulting array has the same number of dimensions and will broadcast with the
input array.

(gh-19211)

### The `ndim`

and `axis`

attributes have been added to `numpy.AxisError`

¶

The `ndim`

and `axis`

parameters are now also stored as attributes
within each `numpy.AxisError`

instance.

(gh-19459)

### Preliminary support for *windows/arm64* target¶

`numpy`

added support for windows/arm64 target. Please note
`OpenBLAS`

support is not yet available for windows/arm64 target.

(gh-19513)

### Added support for LoongArch¶

LoongArch is a new instruction set, numpy compilation failure on LoongArch architecture, so add the commit.

(gh-19527)

### A `.clang-format`

file has been added¶

Clang-format is a C/C++ code formatter, together with the added
`.clang-format`

file, it produces code close enough to the NumPy
C_STYLE_GUIDE for general use. Clang-format version 12+ is required
due to the use of several new features, it is available in
Fedora 34 and Ubuntu Focal among other distributions.

(gh-19754)

`is_integer`

is now available to `numpy.floating`

and `numpy.integer`

¶

Based on its counterpart in *float* and *int*, the numpy floating point and
integer types now support *is_integer*. Returns `True`

if the
number is finite with integral value, and `False`

otherwise.

```
>>> np.float32(-2.0).is_integer()
True
>>> np.float64(3.2).is_integer()
False
>>> np.int32(-2).is_integer()
True
```

(gh-19803)

### Symbolic parser for Fortran dimension specifications¶

A new symbolic parser has been added to f2py in order to correctly parse dimension specifications. The parser is the basis for future improvements and provides compatibility with Draft Fortran 202x.

(gh-19805)

`ndarray`

, `dtype`

and `number`

are now runtime-subscriptable¶

Mimicking **PEP 585**, the `ndarray`

, `dtype`

and `number`

classes are now subscriptable for python 3.9 and later.
Consequently, expressions that were previously only allowed in .pyi stub files
or with the help of `from __future__ import annotations`

are now also legal
during runtime.

```
>>> import numpy as np
>>> from typing import Any
>>> np.ndarray[Any, np.dtype[np.float64]]
numpy.ndarray[typing.Any, numpy.dtype[numpy.float64]]
```

(gh-19879)

## Improvements¶

*ctypeslib.load_library* can now take any path-like object¶

All parameters in the can now take any path-like object.
This includes the likes of strings, bytes and objects implementing the
`__fspath__`

protocol.

(gh-17530)

### Add `smallest_normal`

and `smallest_subnormal`

attributes to *finfo*¶

The attributes `smallest_normal`

and `smallest_subnormal`

are available as
an extension of *finfo* class for any floating-point data type. To use these
new attributes, write `np.finfo(np.float64).smallest_normal`

or
`np.finfo(np.float64).smallest_subnormal`

.

(gh-18536)

`numpy.linalg.qr`

accepts stacked matrices as inputs¶

`numpy.linalg.qr`

is able to produce results for stacked matrices as inputs.
Moreover, the implementation of QR decomposition has been shifted to C
from Python.

(gh-19151)

`numpy.fromregex`

now accepts `os.PathLike`

implementations¶

`numpy.fromregex`

now accepts objects implementing the `__fspath__`

protocol, *e.g.* `pathlib.Path`

.

(gh-19680)

### Missing parameters have been added to the `nan<x>`

functions¶

A number of the `nan<x>`

functions previously lacked parameters that were
present in their `<x>`

-based counterpart, *e.g.* the `where`

parameter was
present in `mean`

but absent from `nanmean`

.

The following parameters have now been added to the `nan<x>`

functions:

nanmin:

`initial`

&`where`

nanmax:

`initial`

&`where`

nanargmin:

`keepdims`

&`out`

nanargmax:

`keepdims`

&`out`

nansum:

`initial`

&`where`

nanprod:

`initial`

&`where`

nanmean:

`where`

nanvar:

`where`

nanstd:

`where`

(gh-20027)

## Performance improvements and changes¶

### Vectorize umath module using AVX-512¶

By leveraging Intel Short Vector Math Library (SVML), 18 umath functions
(`exp2`

, `log2`

, `log10`

, `expm1`

, `log1p`

, `cbrt`

, `sin`

,
`cos`

, `tan`

, `arcsin`

, `arccos`

, `arctan`

, `sinh`

, `cosh`

,
`tanh`

, `arcsinh`

, `arccosh`

, `arctanh`

) are vectorized using AVX-512
instruction set for both single and double precision implementations. This
change is currently enabled only for Linux users and on processors with
AVX-512 instruction set. It provides an average speed up of 32x and 14x for
single and double precision functions respectively.

(gh-19478)

## Changes¶

### Removed floor division support for complex types¶

Floor division of complex types will now result in a *TypeError*

```
>>> a = np.arange(10) + 1j* np.arange(10)
>>> a // 1
TypeError: ufunc 'floor_divide' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
```

(gh-19135)

`numpy.vectorize`

functions now produce the same output class as the base function¶

When a function that respects `numpy.ndarray`

subclasses is vectorized using
`numpy.vectorize`

, the vectorized function will now be subclass-safe
also for cases that a signature is given (i.e., when creating a `gufunc`

):
the output class will be the same as that returned by the first call to
the underlying function.

(gh-19356)

### OpenBLAS v0.3.17¶

Update the OpenBLAS used in testing and in wheels to v0.3.17

(gh-19462)

### Python 3.7 is no longer supported¶

Python support has been dropped. This is rather strict, there are changes that require Python >=3.8.

(gh-19665)

### str/repr of complex dtypes now include space after punctuation¶

The repr of `np.dtype({"names": ["a"], "formats": [int], "offsets": [2]})`

is
now `dtype({'names': ['a'], 'formats': ['<i8'], 'offsets': [2], 'itemsize': 10})`

,
whereas spaces where previously omitted after colons and between fields.

The old behavior can be restored via `np.set_printoptions(legacy="1.21")`

.

(gh-19687)

### Corrected `advance`

in `PCG64DSXM`

and `PCG64`

¶

Fixed a bug in the `advance`

method of `PCG64DSXM`

and `PCG64`

. The bug only
affects results when the step was larger than \(2^{64}\) on platforms
that do not support 128-bit integers(e.g., Windows and 32-bit Linux).

(gh-20049)