def _call(self, x, out):
xim = x[:functional.N]
xi = xim[i]
ret = functional.alpha[i] * (
functional.forward.adjoint *
(functional.forward -
ConstantOperator(functional.data[i])))(xi)
out.assign(ret)
def translation_prox_factory(step_size):
"""Create proximal for the translation with a given step_size.
Parameters
----------
step_size : positive `float`
Step size parameter
Returns
-------
proximal : `Operator`
The proximal operator of ``s * F( . - y)`` where ``s`` is the
step size
"""
return (ConstantOperator(y) + prox_factory(step_size) *
(IdentityOperator(y.space) - ConstantOperator(y)))
def gradient(self):
"""Gradient operator of the functional."""
return self.functional.gradient + ConstantOperator(self.linear_term)
def gradient(self):
"""Gradient operator of the functional."""
return (self.functional.gradient +
(2 * self.quadratic_coeff) * IdentityOperator(self.domain) +
ConstantOperator(self.linear_term))