def setUp(self):
avail_funcs = ['3h-camel', 'beale', 'mc-cormick', 'rosenbrock']
# Instancing the available functions to test optimizer
self.funcs = {}
for fun_id in avail_funcs:
self.funcs[fun_id] = CFunction.create(fun_id)
def test_2D(self):
"""Plot of a 2D example."""
grid_limits = [(-4, 4), (-4, 4)]
A = CArray.eye(2, 2)
b = CArray.zeros(2).T
circle = CFunction.create('quadratic', A, b, 0)
self._test_2D(circle, grid_limits, levels=[16])
def _quadratic_fun(d):
"""Creates a quadratic function in d dimensions."""
def _quadratic_fun_min(A, b):
from scipy import linalg
min_x_scipy = linalg.solve((2 * A).tondarray(),
-b.tondarray(),
sym_pos=True)
return CArray(min_x_scipy).ravel()
A = CArray.eye(d, d)
b = CArray.ones((d, 1)) * 2
discr_fun = CFunction.create('quadratic', A, b, c=0)
min_x = _quadratic_fun_min(A, b)
min_val = discr_fun.fun(min_x)
discr_fun.global_min = lambda: min_val
discr_fun.global_min_x = lambda: min_x
return discr_fun
def setUp(self):
self.fun = CFunction.create('mc-cormick')
def setUp(self):
self.fun = CFunction.create('rosenbrock')
def setUp(self):
self.fun = CFunction.create('3h-camel')
def setUp(self):
self.fun = CFunction.create('beale')
def setUp(self):
A = CArray.eye(2, 2)
b = CArray.zeros((2, 1))
c = 0
self.fun = CFunction.create('quadratic', A, b, c)
def setUp(self):
self.test_funcs = dict()
# Instancing the available functions to test optimizer
self.test_funcs['3h-camel'] = {
'fun': CFunction.create('3h-camel'),
'x0': CArray([1, 1]),
'grid_limits': [(-2, 2), (-2, 2)],
'vmin': 0,
'vmax': 5
}
self.test_funcs['beale'] = {
'fun': CFunction.create('beale'),
'x0': CArray([0, 0]),
'grid_limits': [(-1, 4.5), (-1, 1.5)],
'vmin': 0,
'vmax': 1
}
self.test_funcs['mc-cormick'] = {
'fun': CFunction.create('mc-cormick'),
'x0': CArray([0, 1]),
'grid_limits': [(-2, 3), (-3, 1)],
'vmin': -2,
'vmax': 2
}
self.test_funcs['rosenbrock'] = {
'fun': CFunction.create('rosenbrock'),
'x0': CArray([-1, -1]),
'grid_limits': [(-2.1, 1.1), (-2.1, 1.1)],
'vmin': 0,
'vmax': 10
}
quad = self._quadratic_fun(2)
self.test_funcs['quad-2'] = {
'fun': quad,
'x0': CArray([4, -4]),
'grid_limits': [(-5, 5), (-5, 5)],
'vmin': None,
'vmax': None
}
n = 100
quad = self._quadratic_fun(n)
self.test_funcs['quad-100-sparse'] = {
'fun': quad,
'x0': CArray.zeros((n, ), dtype=int).tosparse(dtype=int),
}
n = 2
poly = self._create_poly(d=n)
self.test_funcs['poly-2'] = {
'fun': poly,
'x0': CArray.ones((n, )) * 2,
'vmin': -10,
'vmax': 5,
'grid_limits': [(-1, 1), (-1, 1)]
}
n = 100
# x0 is a sparse CArray and the solution is a zero vector
poly = self._create_poly(d=n)
self.test_funcs['poly-100-int'] = {
'fun': poly,
'x0': CArray.ones((n, ), dtype=int) * 2
}
n = 100
poly = self._create_poly(d=n)
self.test_funcs['poly-100-int-sparse'] = {
'fun': poly,
'x0': CArray.ones((n, ), dtype=int).tosparse(dtype=int) * 2
}
