Numerical integration, quadrature for various domains

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for nschloe from gravatar.com nschloe

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Other/Proprietary License
  • Author: Nico Schlömer
  • Tags mathematics, physics, engineering, quadrature, cubature, integration, numerical integration
  • Requires: Python >=3.8
Classifiers

Project description

quadpy

Your one-stop shop for numerical integration in Python.

PyPi Version PyPI pyversions GitHub stars PyPi downloads

Discord awesome

More than 1500 numerical integration schemes for line segments, circles, disks, triangles, quadrilaterals, spheres, balls, tetrahedra, hexahedra, wedges, pyramids, n-spheres, n-balls, n-cubes, n-simplices, the 1D half-space with weight functions exp(-r), the 2D space with weight functions exp(-r), the 3D space with weight functions exp(-r), the nD space with weight functions exp(-r), the 1D space with weight functions exp(-r2), the 2D space with weight functions exp(-r2), the 3D space with weight functions exp(-r2), and the nD space with weight functions exp(-r2), for fast integration of real-, complex-, and vector-valued functions.

Installation

Install quadpy from PyPI with

pip install quadpy

See here on how to get a license.

Using quadpy

Quadpy provides integration schemes for many different 1D, 2D, even nD domains.

To start off easy: If you'd numerically integrate any function over any given 1D interval, do

import numpy as np
import quadpy


def f(x):
    return np.sin(x) - x


val, err = quadpy.quad(f, 0.0, 6.0)

This is like scipy with the addition that quadpy handles complex-, vector-, matrix-valued integrands, and "intervals" in spaces of arbitrary dimension.

To integrate over a triangle, do

import numpy as np
import quadpy


def f(x):
    return np.sin(x[0]) * np.sin(x[1])


triangle = np.array([[0.0, 0.0], [1.0, 0.0], [0.7, 0.5]])

# get a "good" scheme of degree 10
scheme = quadpy.t2.get_good_scheme(10)
val = scheme.integrate(f, triangle)

Most domains have get_good_scheme(degree). If you would like to use a particular scheme, you can pick one from the dictionary quadpy.t2.schemes.

All schemes have

scheme.points
scheme.weights
scheme.degree
scheme.source
scheme.test_tolerance

scheme.show()
scheme.integrate(
    # ...
)

and many have

scheme.points_symbolic
scheme.weights_symbolic

You can explore schemes on the command line with, e.g.,

quadpy info s2 rabinowitz_richter_3

<quadrature scheme for S2>
  name:                 Rabinowitz-Richter 2
  source:               Perfectly Symmetric Two-Dimensional Integration Formulas with Minimal Numbers of Points
                        Philip Rabinowitz, Nira Richter
                        Mathematics of Computation, vol. 23, no. 108, pp. 765-779, 1969
                        https://doi.org/10.1090/S0025-5718-1969-0258281-4
  degree:               9
  num points/weights:   21
  max/min weight ratio: 7.632e+01
  test tolerance:       9.417e-15
  point position:       outside
  all weights positive: True

Also try quadpy show!

quadpy is fully vectorized, so if you like to compute the integral of a function on many domains at once, you can provide them all in one integrate() call, e.g.,

# shape (3, 5, 2), i.e., (corners, num_triangles, xy_coords)
triangles = np.stack(
    [
        [[0.0, 0.0], [1.0, 0.0], [0.0, 1.0]],
        [[1.2, 0.6], [1.3, 0.7], [1.4, 0.8]],
        [[26.0, 31.0], [24.0, 27.0], [33.0, 28]],
        [[0.1, 0.3], [0.4, 0.4], [0.7, 0.1]],
        [[8.6, 6.0], [9.4, 5.6], [7.5, 7.4]],
    ],
    axis=-2,
)

The same goes for functions with vectorized output, e.g.,

def f(x):
    return [np.sin(x[0]), np.sin(x[1])]

More examples under test/examples_test.py.

Read more about the dimensionality of the input/output arrays in the wiki.

Advanced topics:

Schemes

Line segment (C1)

  • Chebyshev-Gauss (type 1 and 2, arbitrary degree)
  • Clenshaw-Curtis (arbitrary degree)
  • Fejér (type 1 and 2, arbitrary degree)
  • Gauss-Jacobi (arbitrary degree)
  • Gauss-Legendre (arbitrary degree)
  • Gauss-Lobatto (arbitrary degree)
  • Gauss-Kronrod (arbitrary degree)
  • Gauss-Patterson (9 nested schemes up to degree 767)
  • Gauss-Radau (arbitrary degree)
  • Newton-Cotes (open and closed, arbitrary degree)

See here for how to generate Gauss formulas for your own weight functions.

Example:

import numpy as np
import quadpy

scheme = quadpy.c1.gauss_patterson(5)
scheme.show()
val = scheme.integrate(lambda x: np.exp(x), [0.0, 1.0])

1D half-space with weight function exp(-r) (E1r)

Example:

import quadpy

scheme = quadpy.e1r.gauss_laguerre(5, alpha=0)
scheme.show()
val = scheme.integrate(lambda x: x**2)

1D space with weight function exp(-r2) (E1r2)

  • Gauss-Hermite (arbitrary degree)
  • Genz-Keister (1996, 8 nested schemes up to degree 67)

Example:

import quadpy

scheme = quadpy.e1r2.gauss_hermite(5)
scheme.show()
val = scheme.integrate(lambda x: x**2)

Circle (U2)

  • Krylov (1959, arbitrary degree)

Example:

import numpy as np
import quadpy

scheme = quadpy.u2.get_good_scheme(7)
scheme.show()
val = scheme.integrate(lambda x: np.exp(x[0]), [0.0, 0.0], 1.0)

Triangle (T2)

Apart from the classical centroid, vertex, and seven-point schemes we have

Example:

import numpy as np
import quadpy

scheme = quadpy.t2.get_good_scheme(12)
scheme.show()
val = scheme.integrate(lambda x: np.exp(x[0]), [[0.0, 0.0], [1.0, 0.0], [0.5, 0.7]])

Disk (S2)

  • Radon (1948, degree 5)
  • Peirce (1956, 3 schemes up to degree 11)
  • Peirce (1957, arbitrary degree)
  • Albrecht-Collatz (1958, degree 3)
  • Hammer-Stroud (1958, 8 schemes up to degree 15)
  • Albrecht (1960, 8 schemes up to degree 17)
  • Mysovskih (1964, 3 schemes up to degree 15)
  • Rabinowitz-Richter (1969, 6 schemes up to degree 15)
  • Lether (1971, arbitrary degree)
  • Piessens-Haegemans (1975, 1 scheme of degree 9)
  • Haegemans-Piessens (1977, degree 9)
  • Cools-Haegemans (1985, 4 schemes up to degree 13)
  • Wissmann-Becker (1986, 3 schemes up to degree 8)
  • Kim-Song (1997, 15 schemes up to degree 17)
  • Cools-Kim (2000, 3 schemes up to degree 21)
  • Luo-Meng (2007, 6 schemes up to degree 17)
  • Takaki-Forbes-Rolland (2022, 19 schemes up to degree 77)
  • all schemes from the n-ball

Example:

import numpy as np
import quadpy

scheme = quadpy.s2.get_good_scheme(6)
scheme.show()
val = scheme.integrate(lambda x: np.exp(x[0]), [0.0, 0.0], 1.0)

Quadrilateral (C2)

Example:

import numpy as np
import quadpy

scheme = quadpy.c2.get_good_scheme(7)
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    [[[0.0, 0.0], [1.0, 0.0]], [[0.0, 1.0], [1.0, 1.0]]],
)

The points are specified in an array of shape (2, 2, ...) such that arr[0][0] is the lower left corner, arr[1][1] the upper right. If your c2 has its sides aligned with the coordinate axes, you can use the convenience function

quadpy.c2.rectangle_points([x0, x1], [y0, y1])

to generate the array.

2D space with weight function exp(-r) (E2r)

Example:

import quadpy

scheme = quadpy.e2r.get_good_scheme(5)
scheme.show()
val = scheme.integrate(lambda x: x[0] ** 2)

2D space with weight function exp(-r2) (E2r2)

Example:

import quadpy

scheme = quadpy.e2r2.get_good_scheme(3)
scheme.show()
val = scheme.integrate(lambda x: x[0] ** 2)

Sphere (U3)

Example:

import numpy as np
import quadpy

scheme = quadpy.u3.get_good_scheme(19)
# scheme.show()
val = scheme.integrate(lambda x: np.exp(x[0]), [0.0, 0.0, 0.0], 1.0)

Integration on the sphere can also be done for functions defined in spherical coordinates:

import numpy as np
import quadpy


def f(theta_phi):
    theta, phi = theta_phi
    return np.sin(phi) ** 2 * np.sin(theta)


scheme = quadpy.u3.get_good_scheme(19)
val = scheme.integrate_spherical(f)

Ball (S3)

Example:

import numpy as np
import quadpy

scheme = quadpy.s3.get_good_scheme(4)
# scheme.show()
val = scheme.integrate(lambda x: np.exp(x[0]), [0.0, 0.0, 0.0], 1.0)

Tetrahedron (T3)

Example:

import numpy as np
import quadpy

scheme = quadpy.t3.get_good_scheme(5)
# scheme.show()
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.5, 0.7, 0.0], [0.3, 0.9, 1.0]],
)

Hexahedron (C3)

Example:

import numpy as np
import quadpy

scheme = quadpy.c3.product(quadpy.c1.newton_cotes_closed(3))
# scheme.show()
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    quadpy.c3.cube_points([0.0, 1.0], [-0.3, 0.4], [1.0, 2.1]),
)

Pyramid (P3)

  • Felippa (2004, 9 schemes up to degree 5)

Example:

import numpy as np
import quadpy

scheme = quadpy.p3.felippa_5()

val = scheme.integrate(
    lambda x: np.exp(x[0]),
    [
        [0.0, 0.0, 0.0],
        [1.0, 0.0, 0.0],
        [0.5, 0.7, 0.0],
        [0.3, 0.9, 0.0],
        [0.0, 0.1, 1.0],
    ],
)

Wedge (W3)

Example:

import numpy as np
import quadpy

scheme = quadpy.w3.felippa_3()
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    [
        [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.5, 0.7, 0.0]],
        [[0.0, 0.0, 1.0], [1.0, 0.0, 1.0], [0.5, 0.7, 1.0]],
    ],
)

3D space with weight function exp(-r) (E3r)

Example:

import quadpy

scheme = quadpy.e3r.get_good_scheme(5)
# scheme.show()
val = scheme.integrate(lambda x: x[0] ** 2)

3D space with weight function exp(-r2) (E3r2)

Example:

import quadpy

scheme = quadpy.e3r2.get_good_scheme(6)
# scheme.show()
val = scheme.integrate(lambda x: x[0] ** 2)

n-Simplex (Tn)

Example:

import numpy as np
import quadpy

dim = 4
scheme = quadpy.tn.grundmann_moeller(dim, 3)
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    np.array(
        [
            [0.0, 0.0, 0.0, 0.0],
            [1.0, 2.0, 0.0, 0.0],
            [0.0, 1.0, 0.0, 0.0],
            [0.0, 3.0, 1.0, 0.0],
            [0.0, 0.0, 4.0, 1.0],
        ]
    ),
)

n-Sphere (Un)

Example:

import numpy as np
import quadpy

dim = 4
scheme = quadpy.un.dobrodeev_1978(dim)
val = scheme.integrate(lambda x: np.exp(x[0]), np.zeros(dim), 1.0)

n-Ball (Sn)

Example:

import numpy as np
import quadpy

dim = 4
scheme = quadpy.sn.dobrodeev_1970(dim)
val = scheme.integrate(lambda x: np.exp(x[0]), np.zeros(dim), 1.0)

n-Cube (Cn)

Example:

import numpy as np
import quadpy

dim = 4
scheme = quadpy.cn.stroud_cn_3_3(dim)
val = scheme.integrate(
    lambda x: np.exp(x[0]),
    quadpy.cn.ncube_points([0.0, 1.0], [0.1, 0.9], [-1.0, 1.0], [-1.0, -0.5]),
)

nD space with weight function exp(-r) (Enr)

Example:

import quadpy

dim = 4
scheme = quadpy.enr.stroud_enr_5_4(dim)
val = scheme.integrate(lambda x: x[0] ** 2)

nD space with weight function exp(-r2) (Enr2)

Example:

import quadpy

dim = 4
scheme = quadpy.enr2.stroud_enr2_5_2(dim)
val = scheme.integrate(lambda x: x[0] ** 2)

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for nschloe from gravatar.com nschloe

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Other/Proprietary License
  • Author: Nico Schlömer
  • Tags mathematics, physics, engineering, quadrature, cubature, integration, numerical integration
  • Requires: Python >=3.8
Classifiers

Release history Release notifications | RSS feed

This version

0.17.21

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

quadpy-0.17.21-py3-none-any.whl (3.0 MB view details)

Uploaded Python 3

File details

Details for the file quadpy-0.17.21-py3-none-any.whl.

File metadata

  • Download URL: quadpy-0.17.21-py3-none-any.whl
  • Upload date:
  • Size: 3.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.4

File hashes

Hashes for quadpy-0.17.21-py3-none-any.whl
Algorithm Hash digest
SHA256 ea74599bc28b5f62e3b24d8cb4eb43d7fa600132106e121099177c02ab248194
MD5 eca77eec33591d1e9531a70145607845
BLAKE2b-256 42c9d647dc440adf9cfea0fd5c92b37258d9fef34b8e9bb421083ca47ee2ada9

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