quadax is a library for numerical quadrature and integration using JAX.
vmap-able, jit-able, differentiable in both forward and reverse mode.
Pluggable adjoint methods controlling how derivatives are computed.
Scalar or vector valued integrands.
Finite or infinite domains with discontinuities or singularities within the domain of integration.
Globally adaptive Gauss-Kronrod and Clenshaw-Curtis quadrature for smooth integrands (similar to scipy.integrate.quad)
Adaptive tanh-sinh quadrature for singular or near singular integrands.
Quadrature from sampled values using trapezoidal and Simpsons methods.
Coming soon:
N-D quadrature (cubature)
QMC methods
Integration with weight functions
Sparse grids (maybe, need to play with data structures and JAX)
Installation
quadax is installable with pip:
pip install quadaxUsage
import jax.numpy as jnp
import numpy as np
from quadax import quadgk
fun = lambda t: t * jnp.log(1 + t)
epsabs = epsrel = 1e-5 # by default jax uses 32 bit, higher accuracy requires going to 64 bit
a, b = 0, 1
y, info = quadgk(fun, [a, b], epsabs=epsabs, epsrel=epsrel)
assert info.err < max(epsabs, epsrel*abs(y))
np.testing.assert_allclose(y, 1/4, rtol=epsrel, atol=epsabs)For full details of various options see the API documentation
1 maintainer
Metadata
1 maintainer
Release files for quadax 0.3.0
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|---|---|---|---|---|
| quadax-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 279.0 kB
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