# Path: openpathsampling/ops_logging.py
# def initialization_logging(logger, obj, entries):
#     # this works with either a list of attributes of a dictionary of
#     # variable name : attribute value
#     try:
#         entries.keys()
#         working_dict = entries
#     except AttributeError:
#         working_dict = {}
#         for entry in entries:
#             working_dict[entry] = obj.__dict__[entry]
# 
#     logger.info("Initializing <%s> (%s)",
#                 str(hex(id(obj))), str(obj.__class__.__name__))
#     for entry in working_dict.keys():
#         logger.info("Parameter: %s : %s", str(entry), str(working_dict[entry]))
# 
# Path: openpathsampling/deprecations.py
# def deprecate(deprecation):
#     """Decorator to deprecate a class/method
# 
#     Note
#     ----
#         Properties can be particularly challenging. First, you must put the
#         @property decorator outside (above) the @deprecate decorator.
#         Second, this does not (yet) change the docstrings of properties.
#         However, it will raise a warning when the property is used.
#     """
#     def decorator(dep_obj):
#         dep_obj.__new_docstring = update_docstring(dep_obj, deprecation)
#         wrap_class = isclass(dep_obj)
#         to_wrap = dep_obj.__init__ if wrap_class else dep_obj
# 
#         @wraps(to_wrap)
#         def wrapper(*args, **kwargs):
#             deprecation.warn()
#             return to_wrap(*args, **kwargs)
# 
#         if wrap_class:
#             dep_obj.__init__ = wrapper
#             return dep_obj
#         else:
#             return wrapper
#     return decorator
# 
# def has_deprecations(cls):
#     """Decorator to ensure that docstrings get updated for wrapped class"""
#     for obj in [cls] + list(vars(cls).values()):
#         if callable(obj) and hasattr(obj, '__new_docstring'):
#             try:
#                 obj.__doc__ = obj.__new_docstring
#             except AttributeError:
#                 # probably Python 2; we can't update docstring in Py2
#                 # see https://github.com/Chilipp/docrep/pull/9 and related
#                 pass
#             del obj.__new_docstring
#     return cls
# 
# Path: openpathsampling/deprecations.py
# SAMPLE_DETAILS = Deprecation(
#     problem="SampleDetails will be removed in {OPS} {version}.",
#     remedy="Use generic Details class instead.",
#     remove_version=(2, 0),
#     deprecated_in=(0, 9, 3)
# )
# 
# MOVE_DETAILS = Deprecation(
#     problem="MoveDetails will be removed in {OPS} {version}.",
#     remedy="Use generic Details class instead.",
#     remove_version=(2, 0),
#     deprecated_in=(0, 9, 3)
# )
# 
# NEW_SNAPSHOT_KWARG_SELECTOR = Deprecation(
#     problem=("'new_snapshot' should be a supported keyword in "
#              "selector.probability_ratio(); If snapshot has been copied or "
#              "modified we can't reliably find it in trial_trajectory. This "
#              "keyword must be supported in the expected signature: "
#              "(old_snapshot, old_trajectory, new_snapshot, new_trajectory) "
#              "in {OPS} {version}. "),
#     remedy=("kwarg 'new_snapshot' must to be supported, implement it as "
#             "new_snapshot=old_snapshot if new_traj is not used to calculate "
#             "the weight of old_snapshot"),
#     remove_version=(2, 0),
#     deprecated_in=(1, 6, 0)
# )


import abc
import logging
import numpy as np
import random
import openpathsampling as paths
from openpathsampling.netcdfplus import StorableNamedObject, StorableObject
from openpathsampling.pathmover_inout import InOutSet, InOut
from openpathsampling.rng import default_rng
from .ops_logging import initialization_logging
from .treelogic import TreeMixin
from openpathsampling.deprecations import deprecate, has_deprecations
from openpathsampling.deprecations import (SAMPLE_DETAILS, MOVE_DETAILS,
                                           NEW_SNAPSHOT_KWARG_SELECTOR)
from future.utils import with_metaclass
    def __str__(self):
        # primarily for debugging/interactive use
        mystr = ""
        for key in self.__dict__.keys():
            obj = self.__dict__[key]
            if key in self._print_nothing_keys:
                pass  # do nothing!
            elif any([isinstance(obj, tt) for tt in self._print_repr_types]):
                mystr += str(key) + " = " + repr(obj) + '\n'
            else:
                mystr += str(key) + " = " + str(self.__dict__[key]) + '\n'
        return mystr


@has_deprecations
@deprecate(MOVE_DETAILS)
class MoveDetails(Details):
    """Details of the move as applied to a given replica

    Specific move types may have add several other attributes for each
    MoveDetails object. For example, shooting moves will also include
    information about the shooting point selection, etc.
    """

    def __init__(self, **kwargs):
        super(MoveDetails, self).__init__(**kwargs)


# leave this for potential backwards compatibility
@has_deprecations

# Path: openpathsampling/ops_logging.py
# def initialization_logging(logger, obj, entries):
#     # this works with either a list of attributes of a dictionary of
#     # variable name : attribute value
#     try:
#         entries.keys()
#         working_dict = entries
#     except AttributeError:
#         working_dict = {}
#         for entry in entries:
#             working_dict[entry] = obj.__dict__[entry]
# 
#     logger.info("Initializing <%s> (%s)",
#                 str(hex(id(obj))), str(obj.__class__.__name__))
#     for entry in working_dict.keys():
#         logger.info("Parameter: %s : %s", str(entry), str(working_dict[entry]))
# 
# Path: openpathsampling/deprecations.py
# def deprecate(deprecation):
#     """Decorator to deprecate a class/method
# 
#     Note
#     ----
#         Properties can be particularly challenging. First, you must put the
#         @property decorator outside (above) the @deprecate decorator.
#         Second, this does not (yet) change the docstrings of properties.
#         However, it will raise a warning when the property is used.
#     """
#     def decorator(dep_obj):
#         dep_obj.__new_docstring = update_docstring(dep_obj, deprecation)
#         wrap_class = isclass(dep_obj)
#         to_wrap = dep_obj.__init__ if wrap_class else dep_obj
# 
#         @wraps(to_wrap)
#         def wrapper(*args, **kwargs):
#             deprecation.warn()
#             return to_wrap(*args, **kwargs)
# 
#         if wrap_class:
#             dep_obj.__init__ = wrapper
#             return dep_obj
#         else:
#             return wrapper
#     return decorator
# 
# def has_deprecations(cls):
#     """Decorator to ensure that docstrings get updated for wrapped class"""
#     for obj in [cls] + list(vars(cls).values()):
#         if callable(obj) and hasattr(obj, '__new_docstring'):
#             try:
#                 obj.__doc__ = obj.__new_docstring
#             except AttributeError:
#                 # probably Python 2; we can't update docstring in Py2
#                 # see https://github.com/Chilipp/docrep/pull/9 and related
#                 pass
#             del obj.__new_docstring
#     return cls
# 
# Path: openpathsampling/deprecations.py
# SAMPLE_DETAILS = Deprecation(
#     problem="SampleDetails will be removed in {OPS} {version}.",
#     remedy="Use generic Details class instead.",
#     remove_version=(2, 0),
#     deprecated_in=(0, 9, 3)
# )
# 
# MOVE_DETAILS = Deprecation(
#     problem="MoveDetails will be removed in {OPS} {version}.",
#     remedy="Use generic Details class instead.",
#     remove_version=(2, 0),
#     deprecated_in=(0, 9, 3)
# )
# 
# NEW_SNAPSHOT_KWARG_SELECTOR = Deprecation(
#     problem=("'new_snapshot' should be a supported keyword in "
#              "selector.probability_ratio(); If snapshot has been copied or "
#              "modified we can't reliably find it in trial_trajectory. This "
#              "keyword must be supported in the expected signature: "
#              "(old_snapshot, old_trajectory, new_snapshot, new_trajectory) "
#              "in {OPS} {version}. "),
#     remedy=("kwarg 'new_snapshot' must to be supported, implement it as "
#             "new_snapshot=old_snapshot if new_traj is not used to calculate "
#             "the weight of old_snapshot"),
#     remove_version=(2, 0),
#     deprecated_in=(1, 6, 0)
# )


# Path: openpathsampling/pathmover.py
import abc
import logging
import numpy as np
import random
import openpathsampling as paths
from openpathsampling.netcdfplus import StorableNamedObject, StorableObject
from openpathsampling.pathmover_inout import InOutSet, InOut
from openpathsampling.rng import default_rng
from .ops_logging import initialization_logging
from .treelogic import TreeMixin
from openpathsampling.deprecations import deprecate, has_deprecations
from openpathsampling.deprecations import (SAMPLE_DETAILS, MOVE_DETAILS,
                                           NEW_SNAPSHOT_KWARG_SELECTOR)
from future.utils import with_metaclass

    def __str__(self):
        # primarily for debugging/interactive use
        mystr = ""
        for key in self.__dict__.keys():
            obj = self.__dict__[key]
            if key in self._print_nothing_keys:
                pass  # do nothing!
            elif any([isinstance(obj, tt) for tt in self._print_repr_types]):
                mystr += str(key) + " = " + repr(obj) + '\n'
            else:
                mystr += str(key) + " = " + str(self.__dict__[key]) + '\n'
        return mystr


@has_deprecations
@deprecate(MOVE_DETAILS)
class MoveDetails(Details):
    """Details of the move as applied to a given replica

    Specific move types may have add several other attributes for each
    MoveDetails object. For example, shooting moves will also include
    information about the shooting point selection, etc.
    """

    def __init__(self, **kwargs):
        super(MoveDetails, self).__init__(**kwargs)


# leave this for potential backwards compatibility
@has_deprecations

@deprecate(SAMPLE_DETAILS)