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# 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.

(gh-14527) (gh-14518)