Inzynierka/Lib/site-packages/scipy/integrate/tests/test__quad_vec.py
2023-06-02 12:51:02 +02:00

205 lines
6.1 KiB
Python

import pytest
import numpy as np
from numpy.testing import assert_allclose
from scipy.integrate import quad_vec
from multiprocessing.dummy import Pool
quadrature_params = pytest.mark.parametrize(
'quadrature', [None, "gk15", "gk21", "trapezoid"])
@quadrature_params
def test_quad_vec_simple(quadrature):
n = np.arange(10)
f = lambda x: x**n
for epsabs in [0.1, 1e-3, 1e-6]:
if quadrature == 'trapezoid' and epsabs < 1e-4:
# slow: skip
continue
kwargs = dict(epsabs=epsabs, quadrature=quadrature)
exact = 2**(n+1)/(n + 1)
res, err = quad_vec(f, 0, 2, norm='max', **kwargs)
assert_allclose(res, exact, rtol=0, atol=epsabs)
res, err = quad_vec(f, 0, 2, norm='2', **kwargs)
assert np.linalg.norm(res - exact) < epsabs
res, err = quad_vec(f, 0, 2, norm='max', points=(0.5, 1.0), **kwargs)
assert_allclose(res, exact, rtol=0, atol=epsabs)
res, err, *rest = quad_vec(f, 0, 2, norm='max',
epsrel=1e-8,
full_output=True,
limit=10000,
**kwargs)
assert_allclose(res, exact, rtol=0, atol=epsabs)
@quadrature_params
def test_quad_vec_simple_inf(quadrature):
f = lambda x: 1 / (1 + np.float64(x)**2)
for epsabs in [0.1, 1e-3, 1e-6]:
if quadrature == 'trapezoid' and epsabs < 1e-4:
# slow: skip
continue
kwargs = dict(norm='max', epsabs=epsabs, quadrature=quadrature)
res, err = quad_vec(f, 0, np.inf, **kwargs)
assert_allclose(res, np.pi/2, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, 0, -np.inf, **kwargs)
assert_allclose(res, -np.pi/2, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, -np.inf, 0, **kwargs)
assert_allclose(res, np.pi/2, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, np.inf, 0, **kwargs)
assert_allclose(res, -np.pi/2, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, -np.inf, np.inf, **kwargs)
assert_allclose(res, np.pi, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, np.inf, -np.inf, **kwargs)
assert_allclose(res, -np.pi, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, np.inf, np.inf, **kwargs)
assert_allclose(res, 0, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, -np.inf, -np.inf, **kwargs)
assert_allclose(res, 0, rtol=0, atol=max(epsabs, err))
res, err = quad_vec(f, 0, np.inf, points=(1.0, 2.0), **kwargs)
assert_allclose(res, np.pi/2, rtol=0, atol=max(epsabs, err))
f = lambda x: np.sin(x + 2) / (1 + x**2)
exact = np.pi / np.e * np.sin(2)
epsabs = 1e-5
res, err, info = quad_vec(f, -np.inf, np.inf, limit=1000, norm='max', epsabs=epsabs,
quadrature=quadrature, full_output=True)
assert info.status == 1
assert_allclose(res, exact, rtol=0, atol=max(epsabs, 1.5 * err))
def test_quad_vec_args():
f = lambda x, a: x * (x + a) * np.arange(3)
a = 2
exact = np.array([0, 4/3, 8/3])
res, err = quad_vec(f, 0, 1, args=(a,))
assert_allclose(res, exact, rtol=0, atol=1e-4)
def _lorenzian(x):
return 1 / (1 + x**2)
def test_quad_vec_pool():
f = _lorenzian
res, err = quad_vec(f, -np.inf, np.inf, norm='max', epsabs=1e-4, workers=4)
assert_allclose(res, np.pi, rtol=0, atol=1e-4)
with Pool(10) as pool:
f = lambda x: 1 / (1 + x**2)
res, err = quad_vec(f, -np.inf, np.inf, norm='max', epsabs=1e-4, workers=pool.map)
assert_allclose(res, np.pi, rtol=0, atol=1e-4)
def _func_with_args(x, a):
return x * (x + a) * np.arange(3)
@pytest.mark.parametrize('extra_args', [2, (2,)])
@pytest.mark.parametrize('workers', [1, 10])
def test_quad_vec_pool_args(extra_args, workers):
f = _func_with_args
exact = np.array([0, 4/3, 8/3])
res, err = quad_vec(f, 0, 1, args=extra_args, workers=workers)
assert_allclose(res, exact, rtol=0, atol=1e-4)
with Pool(workers) as pool:
res, err = quad_vec(f, 0, 1, args=extra_args, workers=pool.map)
assert_allclose(res, exact, rtol=0, atol=1e-4)
@quadrature_params
def test_num_eval(quadrature):
def f(x):
count[0] += 1
return x**5
count = [0]
res = quad_vec(f, 0, 1, norm='max', full_output=True, quadrature=quadrature)
assert res[2].neval == count[0]
def test_info():
def f(x):
return np.ones((3, 2, 1))
res, err, info = quad_vec(f, 0, 1, norm='max', full_output=True)
assert info.success == True
assert info.status == 0
assert info.message == 'Target precision reached.'
assert info.neval > 0
assert info.intervals.shape[1] == 2
assert info.integrals.shape == (info.intervals.shape[0], 3, 2, 1)
assert info.errors.shape == (info.intervals.shape[0],)
def test_nan_inf():
def f_nan(x):
return np.nan
def f_inf(x):
return np.inf if x < 0.1 else 1/x
res, err, info = quad_vec(f_nan, 0, 1, full_output=True)
assert info.status == 3
res, err, info = quad_vec(f_inf, 0, 1, full_output=True)
assert info.status == 3
@pytest.mark.parametrize('a,b', [(0, 1), (0, np.inf), (np.inf, 0),
(-np.inf, np.inf), (np.inf, -np.inf)])
def test_points(a, b):
# Check that initial interval splitting is done according to
# `points`, by checking that consecutive sets of 15 point (for
# gk15) function evaluations lie between `points`
points = (0, 0.25, 0.5, 0.75, 1.0)
points += tuple(-x for x in points)
quadrature_points = 15
interval_sets = []
count = 0
def f(x):
nonlocal count
if count % quadrature_points == 0:
interval_sets.append(set())
count += 1
interval_sets[-1].add(float(x))
return 0.0
quad_vec(f, a, b, points=points, quadrature='gk15', limit=0)
# Check that all point sets lie in a single `points` interval
for p in interval_sets:
j = np.searchsorted(sorted(points), tuple(p))
assert np.all(j == j[0])