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staticstate.py
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staticstate.py
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"""
The StaticState class and supporting functionality.
"""
#***************************************************************************************************
# Copyright 2015, 2019 National Technology & Engineering Solutions of Sandia, LLC (NTESS).
# Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights
# in this software.
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0 or in the LICENSE file in the root pyGSTi directory.
#***************************************************************************************************
import numpy as _np
from pygsti.modelmembers.states.densestate import DenseState as _DenseState
from pygsti.modelmembers.errorgencontainer import NoErrorGeneratorInterface as _NoErrorGeneratorInterface
class StaticState(_DenseState, _NoErrorGeneratorInterface):
"""
A state vector that is completely fixed, or "static" (i.e. that posesses no parameters).
Parameters
----------
vec : array_like or State
a 1D numpy array representing the state. The
shape of this array sets the dimension of the state.
basis : Basis or str
The basis that `vec` is in.
evotype : Evotype or str, optional
The evolution type. The special value `"default"` is equivalent
to specifying the value of `pygsti.evotypes.Evotype.default_evotype`.
state_space : StateSpace, optional
The state space for this operation. If `None` a default state space
with the appropriate number of qubits is used.
"""
def __init__(self, vec, basis=None, evotype="default", state_space=None):
_DenseState.__init__(self, vec, basis, evotype, state_space)
def _is_similar(self, other, rtol, atol):
""" Returns True if `other` model member (which it guaranteed to be the same type as self) has
the same local structure, i.e., not considering parameter values or submembers """
# static objects must also test their values in is_similar, since these aren't parameters.
return (super()._is_similar(other, rtol, atol)
and _np.allclose(self.to_dense(), other.to_dense(), rtol=rtol, atol=atol))