Intelegentny_Pszczelarz/.venv/Lib/site-packages/scipy/optimize/tests/test__root.py

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2023-06-19 00:49:18 +02:00
"""
Unit tests for optimization routines from _root.py.
"""
from numpy.testing import assert_
from pytest import raises as assert_raises
import numpy as np
from scipy.optimize import root
class TestRoot:
def test_tol_parameter(self):
# Check that the minimize() tol= argument does something
def func(z):
x, y = z
return np.array([x**3 - 1, y**3 - 1])
def dfunc(z):
x, y = z
return np.array([[3*x**2, 0], [0, 3*y**2]])
for method in ['hybr', 'lm', 'broyden1', 'broyden2', 'anderson',
'diagbroyden', 'krylov']:
if method in ('linearmixing', 'excitingmixing'):
# doesn't converge
continue
if method in ('hybr', 'lm'):
jac = dfunc
else:
jac = None
sol1 = root(func, [1.1,1.1], jac=jac, tol=1e-4, method=method)
sol2 = root(func, [1.1,1.1], jac=jac, tol=0.5, method=method)
msg = "%s: %s vs. %s" % (method, func(sol1.x), func(sol2.x))
assert_(sol1.success, msg)
assert_(sol2.success, msg)
assert_(abs(func(sol1.x)).max() < abs(func(sol2.x)).max(),
msg)
def test_tol_norm(self):
def norm(x):
return abs(x[0])
for method in ['excitingmixing',
'diagbroyden',
'linearmixing',
'anderson',
'broyden1',
'broyden2',
'krylov']:
root(np.zeros_like, np.zeros(2), method=method,
options={"tol_norm": norm})
def test_minimize_scalar_coerce_args_param(self):
# github issue #3503
def func(z, f=1):
x, y = z
return np.array([x**3 - 1, y**3 - f])
root(func, [1.1, 1.1], args=1.5)
def test_f_size(self):
# gh8320
# check that decreasing the size of the returned array raises an error
# and doesn't segfault
class fun:
def __init__(self):
self.count = 0
def __call__(self, x):
self.count += 1
if not (self.count % 5):
ret = x[0] + 0.5 * (x[0] - x[1]) ** 3 - 1.0
else:
ret = ([x[0] + 0.5 * (x[0] - x[1]) ** 3 - 1.0,
0.5 * (x[1] - x[0]) ** 3 + x[1]])
return ret
F = fun()
with assert_raises(ValueError):
root(F, [0.1, 0.0], method='lm')