flashquad 0.1.0

A user-friendly Python numerical integration library with GPU acceleration

FlashQuad

A user-friendly Python numerical integration library with GPU acceleration.

Installation

We recommend using uv:

uv add flashquad
uv sync

or directly install:

uv pip install flashquad

Quick start

import numpy as np
from flashquad import FlashQuad

fq = FlashQuad(backend="numpy")

result = fq.simpson(
    func=lambda x, y: np.sin(x) * np.cos(y),
    intervals=[[0, np.pi], [0, np.pi]],
    num_points=[101, 101],
)

Switch to GPU by changing the backend (we recommend using CuPy for minimal setup):

fq = FlashQuad(backend="cupy")

Batch thousands of parameter sets in a single GPU call:

import cupy as cp
from flashquad import FlashQuad

fq = FlashQuad(backend="cupy")
params = cp.linspace(0.1, 10.0, 5000).reshape(-1, 1)  # 5000 parameter sets

results = fq.simpson(
    func=lambda x, a: cp.exp(-a * x**2),
    intervals=[[0, 5]],
    num_points=[201],
    params=params,
)

Methods

Method	Call
Trapezoidal	fq.trapz(...)
Simpson's 1/3	fq.simpson(...)
Boole's	fq.booles(...)
Gauss-Legendre	fq.gauss(...)
Monte Carlo	fq.mc(...)
Adaptive Monte Carlo	fq.adpmc(...)

Backends

NumPy, PyTorch, CuPy, and JAX.

License

MIT