Awesome

Unxt is unitful quantities and calculations in JAX, built on Equinox and Quax.

Unxt supports JAX's compelling features:

• JIT compilation (jit)
• vectorization (vmap, etc.)
• auto-differentiation (grad, jacobian, hessian)
• GPU/TPU/multi-host acceleration

And best of all, unxt doesn't force you to use special unit-compatible re-exports of JAX libraries. You can use unxt with existing JAX code, and with quax's simple decorator, JAX will work with unxt.Quantity.

Installation

pip install unxt

uv add unxt

pip install git+https://https://github.com/GalacticDynamics/unxt.git

cd /path/to/parent
git clone https://https://github.com/GalacticDynamics/unxt.git
cd unxt
pip install -e .  # editable mode

Documentation

Quick example

import unxt as u

x = u.Quantity(jnp.arange(1, 5, dtype=float), "km")
print(x)
# Quantity['length'](Array([1., 2., 3., 4.], dtype=float64), unit='km')

The constituent value and unit are accessible as attributes:

print(x.value)
# Array([1., 2., 3., 4.], dtype=float64)

print(x.unit)
# Unit("m")

Quantity objects obey the rules of unitful arithmetic.

# Addition / Subtraction
print(x + x)
# Quantity['length'](Array([2., 4., 6., 8.], dtype=float64), unit='km')

# Multiplication / Division
print(2 * x)
# Quantity['length'](Array([2., 4., 6., 8.], dtype=float64), unit='km')

y = u.Quantity(jnp.arange(4, 8, dtype=float), "yr")

print(x / y)
# Quantity['speed'](Array([0.25      , 0.4       , 0.5       , 0.57142857], dtype=float64), unit='km / yr')

# Exponentiation
print(x**2)
# Quantity['area'](Array([0., 1., 4., 9.], dtype=float64), unit='km2')

# Unit checking on operations
try:
    x + y
except Exception as e:
    print(e)
# 'yr' (time) and 'km' (length) are not convertible

Quantities can be converted to different units:

print(u.uconvert("m", x))  # via function
# Quantity['length'](Array([1000., 2000., 3000., 4000.], dtype=float64), unit='m')

print(x.uconvert("m"))  # via method
# Quantity['length'](Array([1000., 2000., 3000., 4000.], dtype=float64), unit='m')

Since Quantity is parametric, it can do runtime dimension checking!

LengthQuantity = u.Quantity["length"]
print(LengthQuantity(2, "km"))
# Quantity['length'](Array(2, dtype=int64, weak_type=True), unit='km')

try:
    LengthQuantity(2, "s")
except ValueError as e:
    print(e)
# Physical type mismatch.

unxt is built on quax, which enables custom array-ish objects in JAX. For convenience we use the quaxed library, which is just a quax.quaxify wrapper around jax to avoid boilerplate code.

[!NOTE]

Using quaxed is optional. You can directly use quaxify, and even apply it to the top-level function instead of individual functions.

from quaxed import grad, vmap
import quaxed.numpy as jnp

print(jnp.square(x))
# Quantity['area'](Array([ 1.,  4.,  9., 16.], dtype=float64), unit='km2')

print(qnp.power(x, 3))
# Quantity['volume'](Array([ 1.,  8., 27., 64.], dtype=float64), unit='km3')

print(vmap(grad(lambda x: x**3))(x))
# Quantity['area'](Array([ 3., 12., 27., 48.], dtype=float64), unit='km2')

See the documentation for more examples and details of JIT and AD

Citation

If you found this library to be useful and want to support the development and maintenance of lower-level code libraries for the scientific community, please consider citing this work.

Development

We welcome contributions!