Changelog¶

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased ¶

In arange, the array type can be deduced from its arguments if no bit- specifiers are given.
Added optional parameter for bias in array creation functions that were missing it.
Added APyFloatArray.from_bits to create floating-point arrays from bit patterns.
It is now possible to assign parts of arrays as APyFixedArray.__setitem__ and APyFloatArray.__setitem__ has been added.
fx and fp functions to create fixed-point and floating-point objects of correct type (scalar or array) depending on argument.
fn utility function to easily evaluate functions with APy-classes and get a result with the same format.
New complex-valued data types:
- APyCFixed, a scalar fixed-point complex type.
- APyCFixedArray, an array fixed-point complex type.
APyFloatArray.convolve now supports accumulator contexts.
VHDL code generation for ROMs.
It is possible to perform arithmetic with Numpy arrays, automatically converting the Numpy array to an APyArray.
from_float now accepts APyTypes scalars.
Wheels for Python 3.13.

APyTypes contexts now supports multi-threading.
Incorrect fixed-point quantization in RND_INF and RND_MIN_INF when source has multiple of 64 bits.
Incorrect fixed-point rounding in APyFixedArray.from_array on Windows.
Incorrect LaTeX-representation of negative fixed-point scalars.
Incorrect casting of large integers in APyFixedArray.from_*.

Mini-GMP is no longer used. Instead, a local multi-precision integer library written in C++ is used.
Support for Python 3.9.

Memory-access bug in APyFloatArray.cumsum.
Bug where APyFixedArray multiplicative methods could give wrong result for multi-limb products if the right-hand side have longer word-length than the left-hand side.
Memory leak in nanobind wrapper library.
Correct subnormal conversions between APyFixed(Array) and float.
Improved arange. It now handles quantization accurately and does not allow infinity and NaN as inputs.

Added methods next_up() and next_down() for floating-point scalars.
Broadcasting support as NumPy.
- APyFixedArray.broadcast_to()
- APyFloatArray.broadcast_to()
- Automatic broadcasting on array arithmetic
Support arithmetic between APyTypes classes and Python’s built-in floats and ints.
Support for automatic stub generation added.
Docstrings are made compatible with doctest, which is run in the CI.
Linting using ruff is added to pre-commit and CI.
Array manipulation and mathematical functions added:
- squeeze()
- reshape()
- flatten() / ravel()
- convolve()
- sum()
- cumsum()
- nansum()
- nancumsum()
- prod()
- cumprod()
- nanprod()
- nancumprod()
- moveaxis()
- swapaxis()
- expand_dims()
- max()
- min()
- nanmax()
- nanmin()
Array creation functions added:
- arange()
- eye()
- identity()
- ones()
- ones_like()
- zeros()
- zeros_like()
- full()
- full_like()
Added to_bits() to array types.
Significantly improved indexing of arrays.
Added support for higher dimensions (ndim > 2) in transpose().

Smaller fixes in quantization for floating-point scalar multiplication.
Fix in floating-point cast-method when result became subnormal.
Fix bug in APyFixedArray.__truediv__() where program crashes on long-limb zero denominators.
Fix bug where single-dimensional tuple representations missed out on a comma.
Fix bug in comparison between floating-point infinity and fixed-point numbers.
Start uploading source distributions of APyTypes to PyPI on releases.
Fixed bug where APyFixedArray.from_array() initialized the wrong stored value from floating-point values that are too small for its representation. (#487)
No longer consider zero a subnormal number.