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- """
- Unit tests for optimization routines from _root.py.
- """
- from __future__ import division, print_function, absolute_import
- 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):
- sol = root(F, [0.1, 0.0], method='lm')
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