Skip to main content

JAX + Units

Project description

JAX + Units

Built with JAX and Pint!

This module provides an interface between JAX and Pint to allow JAX to support operations with units. The propagation of units happens at trace time, so jitted functions should see no runtime cost. This library is experimental so expect some sharp edges.

For example:

>>> import jax
>>> import jax.numpy as jnp
>>> import jpu
>>>
>>> u = jpu.UnitRegistry()
>>>
>>> @jax.jit
... def add_two_lengths(a, b):
...     return a + b
...
>>> add_two_lengths(3 * u.m, jnp.array([4.5, 1.2, 3.9]) * u.cm)
<Quantity([3.045 3.012 3.039], 'meter')>

Installation

To install, use pip:

python -m pip install jpu

The only dependencies are jax and pint, and these will also be installed, if not already in your environment. Take a look at the JAX docs for more information about installing JAX on different systems.

Usage

Here is a slightly more complete example:

>>> import jax
>>> import numpy as np
>>> from jpu import UnitRegistry, numpy as jnpu
>>>
>>> u = UnitRegistry()
>>>
>>> @jax.jit
... def projectile_motion(v_init, theta, time, g=u.standard_gravity):
...     """Compute the motion of a projectile with support for units"""
...     x = v_init * time * jnpu.cos(theta)
...     y = v_init * time * jnpu.sin(theta) - 0.5 * g * jnpu.square(time)
...     return x.to(u.m), y.to(u.m)
...
>>> x, y = projectile_motion(
...     5.0 * u.km / u.h, 60 * u.deg, np.linspace(0, 1, 50) * u.s
... )

Technical details & limitations

The most significant limitation of this library is the fact that users must use jpu.numpy functions when interacting with "quantities" with units instead of the jax.numpy interface. This is because JAX does not (yet?) provide a general interface for dispatching of ufuncs on custom array classes. I have played around with the undocumented __jax_array__ interface, but it's not really flexible enough, and it isn't currently compatible with Pytree objects.

So far, only a subset of the numpy/jax.numpy interface is implemented. Pull requests adding broader support (including submodules) would be welcome!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jpu-0.0.4rc1.tar.gz (19.0 kB view details)

Uploaded Source

Built Distribution

jpu-0.0.4rc1-py3-none-any.whl (16.0 kB view details)

Uploaded Python 3

File details

Details for the file jpu-0.0.4rc1.tar.gz.

File metadata

  • Download URL: jpu-0.0.4rc1.tar.gz
  • Upload date:
  • Size: 19.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.4

File hashes

Hashes for jpu-0.0.4rc1.tar.gz
Algorithm Hash digest
SHA256 aadd0dad4f487c01177313130fe45b81ce6e452c8a9e30dec9199abc2ee56891
MD5 0f941aaa1d5c6c8f3e11feca4767ff95
BLAKE2b-256 e190024d53a92c0e5b095edd40c2ac8c542b2fa3971ae62aae5770b6e035d5ee

See more details on using hashes here.

File details

Details for the file jpu-0.0.4rc1-py3-none-any.whl.

File metadata

  • Download URL: jpu-0.0.4rc1-py3-none-any.whl
  • Upload date:
  • Size: 16.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.4

File hashes

Hashes for jpu-0.0.4rc1-py3-none-any.whl
Algorithm Hash digest
SHA256 1329c8c02e84ae738641148c7349df37a95b68ba7d7f386e494b6fa6a7561b0d
MD5 4699adb68d98f61b64168cb445fc1826
BLAKE2b-256 2f3fcf590dc410d9732fa0430313ed18e9e6786c13fa31ae1ec46dfd23331de8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page