Question 1

How to choose the best quadrature scheme in quadpy for a triangle?

Accepted Answer

Use quadpy.t2.get_good_scheme(degree) to automatically select a suitable scheme based on the desired polynomial degree. For fine-grained control, inspect available schemes with commands like quadpy info t2 or browse quadpy.t2.schemes to compare properties like point counts and weights.

Question 2

Quadpy vs SciPy integrate: which is better for high-dimensional integrals?

Accepted Answer

Quadpy excels with its extensive collection of schemes for n-dimensional domains like n-spheres and n-cubes, offering higher precision and flexibility for complex geometries. SciPy's integrate is simpler for common 1D/2D cases but lacks quadpy's depth for specialized high-dimensional integration.

Question 3

How to integrate a complex-valued function over a sphere using quadpy?

Accepted Answer

Define your function to return complex values and use a scheme from quadpy.u3, such as u3.get_good_scheme(), with the integrate method. Quadpy natively handles complex integrands, as shown in the support for complex-, vector-, and matrix-valued functions in the README examples.

Question 4

Does quadpy support adaptive integration for oscillatory functions?

Accepted Answer

Yes, quadpy includes adaptive quadrature techniques, but it's documented as an advanced topic in the wiki. For oscillatory functions, you may need to combine adaptive features with specific schemes or tune parameters carefully, as it's not as straightforward as fixed schemes.

Question 5

What are the performance implications of using quadpy for batch simulations?

Accepted Answer

Quadpy's vectorized integrate() method allows efficient batch processing over multiple domains, reducing overhead. However, scheme initialization and selection can add latency, so pre-computing schemes and ensuring function vectorization is key for optimal performance in large-scale runs.

Question 6

How to install quadpy and handle any license issues?

Accepted Answer

Install via pip install quadpy, but check the README link for license requirements, which may involve additional steps. Dependencies are primarily NumPy, but verify compatibility, as the license aspect could introduce barriers compared to fully open-source libraries.

quadpy

What is quadpy?

Overview

Use Cases

Best For

Related Projects

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions