70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
|
"""
|
||
|
|
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(object):
|
||
|
|
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_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(object):
|
||
|
|
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')
|