J[:, 1] = self.x * np.exp(p[1] * self.x)
return J
def cubic_soft_l1(z):
rho = np.empty((3, z.size))
t = 1 + z
rho[0] = 3 * (t**(1 / 3) - 1)
rho[1] = t**(-2 / 3)
rho[2] = -2 / 3 * t**(-5 / 3)
return rho
LOSSES = list(IMPLEMENTED_LOSSES.keys()) + [cubic_soft_l1]
class BaseMixin(object):
def test_basic(self):
# Test that the basic calling sequence works.
res = least_squares(fun_trivial, 2., method=self.method)
assert_allclose(res.x, 0, atol=1e-4)
assert_allclose(res.fun, fun_trivial(res.x))
def test_args_kwargs(self):
# Test that args and kwargs are passed correctly to the functions.
a = 3.0
for jac in ['2-point', '3-point', 'cs', jac_trivial]:
with suppress_warnings() as sup:
sup.filter(
J[:, 1] = self.x * np.exp(p[1] * self.x)
return J
def cubic_soft_l1(z):
rho = np.empty((3, z.size))
t = 1 + z
rho[0] = 3 * (t**(1/3) - 1)
rho[1] = t ** (-2/3)
rho[2] = -2/3 * t**(-5/3)
return rho
LOSSES = list(IMPLEMENTED_LOSSES.keys()) + [cubic_soft_l1]
class BaseMixin(object):
def test_basic(self):
# Test that the basic calling sequence works.
res = least_squares(fun_trivial, 2., method=self.method)
assert_allclose(res.x, 0, atol=1e-4)
assert_allclose(res.fun, fun_trivial(res.x))
def test_args_kwargs(self):
# Test that args and kwargs are passed correctly to the functions.
a = 3.0
for jac in ['2-point', '3-point', 'cs', jac_trivial]:
with suppress_warnings() as sup:
sup.filter(UserWarning,