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