Welcome to :mod:`arraycontext`'s documentation!

GPU arrays? Deferred-evaluation arrays? Just plain numpy arrays? You'd like your code to work with all of them? No problem! Comes with pre-made array context implementations for:

• :mod:`numpy`
• :mod:`pyopencl`
• :mod:`jax.numpy`
• :mod:`pytato` (for lazy/deferred evaluation)
• Debugging
• Profiling

:mod:`arraycontext` started life as an array abstraction for use with the :mod:`meshmode` unstrucuted discretization package.

Design Guidelines

Here are some of the guidelines we aim to follow in :mod:`arraycontext`. There exist numerous other, related efforts, such as the Python array API standard. These points may aid in clarifying and differentiating our objectives.

• The array context is about exposing the common subset of operations available in immutable and mutable arrays. As a result, the interface does not seek to support interfaces that provide, enable, or are typically used only with in-place mutation.

  For example: The equivalents of :func:`numpy.empty` were deprecated and will eventually be removed.

• Each array context offers a specific subset of of :mod:`numpy` under :attr:`arraycontext.ArrayContext.np`. Functions under this namespace must be unconditionally :mod:`numpy`-compatible, that is, they may not offer an interface beyond what numpy offers. Functions that are incompatible, for example by supporting tag metadata (cf. :meth:`arraycontext.ArrayContext.einsum`) should live under the :class:`~arraycontext.ArrayContext` directly.

• Similarly, we strive to minimize redundancy between attributes of :class:`~arraycontext.ArrayContext` and :attr:`arraycontext.ArrayContext.np`.

  For example: ArrayContext.empty_like was deprecated.

• Array containers are data structures that may contain arrays. See :mod:`arraycontext.container`. We strive to support these, where sensible, in :class:`~arraycontext.ArrayContext` and :attr:`arraycontext.ArrayContext.np`.

Contents

Indices and tables

• :ref:`genindex`
• :ref:`modindex`
• :ref:`search`