the dynamics.
These class implement functions for getting the dynamics generators for
the combined (drift + ctrls) dynamics with the approriate operator applied
Note the methods in these classes were inspired by:
DYNAMO - Dynamic Framework for Quantum Optimal Control
See Machnes et.al., arXiv.1011.4874
"""
import os
import numpy as np
import scipy.linalg as la
from six import string_types
# QuTiP logging
import qutip.logging as logging
logger = logging.get_logger()
# QuTiP control modules
import qutip.control.errors as errors
import qutip.control.tslotcomp as tslotcomp
import qutip.control.fidcomp as fidcomp
import qutip.control.propcomp as propcomp
import qutip.control.symplectic as sympl
class Dynamics:
"""
This is a base class only. See subclass descriptions and choose an
appropriate one for the application.
Note that initialize_controls must be called before any of the methods
can be used.
The baseclass Optimizer implements the function wrappers to the
fidelity error, gradient, and iteration callback functions.
These are called from the within the SciPy optimisation functions.
The subclasses implement the algorithm specific pulse optimisation function.
"""
import os
import numpy as np
import timeit
import scipy.optimize as spopt
import copy
import collections
# QuTiP
from qutip import Qobj
import qutip.logging as logging
logger = logging.get_logger()
# QuTiP control modules
import qutip.control.optimresult as optimresult
import qutip.control.termcond as termcond
import qutip.control.errors as errors
import qutip.control.dynamics as dynamics
import qutip.control.pulsegen as pulsegen
class Optimizer:
"""
Base class for all control pulse optimisers. This class should not be
instantiated, use its subclasses
This class implements the fidelity, gradient and interation callback
functions.
All subclass objects must be initialised with a