"""
[n]Rotaxane
===========
"""
import numpy as np
from ..topology_graph import NullOptimizer, TopologyGraph
from .vertices import AxleVertex, CycleVertex
[docs]class NRotaxane(TopologyGraph):
"""
Represents [n]rotaxane topology graphs.
Axle and cycle building blocks do not require functional groups.
This class assumes one axle with (n-1) macrocycles threaded on it.
The macrocycles are spaced evenly along the axle in repeating
patterns. The threaded macrocycles can be described analogously
to monomers in linear polymers, in terms of a repeating unit,
except that no bonds are formed between them.
Examples
--------
*Construction*
.. testcode:: construction
import stk
cycle = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='[Br]CC[Br]',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='A',
num_repeating_units=5,
),
)
axle = stk.ConstructedMolecule(
topology_graph=stk.polymer.Linear(
building_blocks=(
stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]),
stk.BuildingBlock('BrCNCBr', [stk.BromoFactory()]),
),
repeating_unit='AB',
num_repeating_units=7,
)
)
rotaxane = stk.ConstructedMolecule(
topology_graph=stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle),
),
repeating_unit='A',
num_repeating_units=3,
),
)
.. moldoc::
import moldoc.molecule as molecule
import stk
cycle = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='[Br]CC[Br]',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='A',
num_repeating_units=5,
),
)
axle = stk.ConstructedMolecule(
topology_graph=stk.polymer.Linear(
building_blocks=(
stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]),
stk.BuildingBlock('BrCNCBr', [stk.BromoFactory()]),
),
repeating_unit='AB',
num_repeating_units=7,
)
)
rotaxane = stk.ConstructedMolecule(
topology_graph=stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle),
),
repeating_unit='A',
num_repeating_units=3,
),
)
moldoc_display_molecule = molecule.Molecule(
atoms=(
molecule.Atom(
atomic_number=atom.get_atomic_number(),
position=position,
) for atom, position in zip(
rotaxane.get_atoms(),
rotaxane.get_position_matrix(),
)
),
bonds=(
molecule.Bond(
atom1_id=bond.get_atom1().get_id(),
atom2_id=bond.get_atom2().get_id(),
order=bond.get_order(),
) for bond in rotaxane.get_bonds()
),
)
*Suggested Optimization*
For :class:`.NRotaxane` topologies, there is no need to use an
optimizer, so stick with :class:`.NullOptimizer`. However, it is
recommended that all building blocks be optimized prior to
construction.
*Defining the Orientation of Each Building Block*
The `orientations` parameter allows the direction of each cycle
along the axle to be flipped
.. testcode:: defining-the-orientation-of-each-building-block
import stk
cycle1 = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='BrCCBr',
functional_groups=[stk.BromoFactory()],
),
stk.BuildingBlock(
smiles='BrCNCBr',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='AB',
num_repeating_units=5,
optimizer=stk.MCHammer(),
),
)
cycle2 = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='BrCCCBr',
functional_groups=[stk.BromoFactory()],
),
stk.BuildingBlock(
smiles='BrCCNCBr',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='AB',
num_repeating_units=5,
optimizer=stk.MCHammer(),
),
)
axle = stk.ConstructedMolecule(
topology_graph=stk.polymer.Linear(
building_blocks=(
stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]),
),
repeating_unit='A',
num_repeating_units=2,
),
)
rotaxane1 = stk.ConstructedMolecule(
topology_graph=stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
),
repeating_unit='AB',
num_repeating_units=3,
orientations=(1., 0.5),
),
)
In the above example, ``cycle1`` is guaranteed to be flipped,
``cycle2`` has a 50% chance of being flipped, each time it is
placed on a node.
Note that whether a building block will be flipped or not
is decided during the initialization of :class:`.NRotaxane`
.. testcode:: defining-the-orientation-of-each-building-block
# graph1 will always construct the same [n]rotaxane.
graph1 = stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
),
repeating_unit='AB',
num_repeating_units=5,
orientations=(0.65, 0.45),
)
# rotaxane2 and rotaxane3 are guaranteed to be the same as they
# used the same topology graph.
rotaxane2 = stk.ConstructedMolecule(graph1)
rotaxane3 = stk.ConstructedMolecule(graph1)
# graph2 may lead to a different [n]rotaxane, despite
# being initialized with the same parameters.
graph2 = stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
),
repeating_unit='AB',
num_repeating_units=5,
orientations=(0.65, 0.45)
)
# rotaxane4 and rotaxane5 are guaranteed to be the same because
# they used the same topology graph. However, they may be
# different to rotaxane2 and rotaxane3.
rotaxane4 = stk.ConstructedMolecule(graph2)
rotaxane5 = stk.ConstructedMolecule(graph2)
The `random_seed` parameter can be used to get reproducible results
.. testcode:: defining-the-orientation-of-each-building-block
# rotaxane6 and rotaxane7 are guaranteed to be the same,
# because graph3 and graph4 used the same random seed.
graph3 = stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
),
repeating_unit='AB',
num_repeating_units=5,
orientations=(0.65, 0.45),
random_seed=4,
)
rotaxane6 = stk.ConstructedMolecule(graph3)
graph4 = stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
),
repeating_unit='AB',
num_repeating_units=5,
orientations=(0.65, 0.45),
random_seed=4,
)
rotaxane7 = stk.ConstructedMolecule(graph4)
*Using Numbers to Define the Repeating Unit*
The repeating unit can also be specified through the indices of
the building blocks
.. testcode:: using-numbers-to-define-the-repeating-unit
import stk
cycle1 = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='BrCCBr',
functional_groups=[stk.BromoFactory()],
),
stk.BuildingBlock(
smiles='BrCNCBr',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='AB',
num_repeating_units=5,
optimizer=stk.MCHammer(),
),
)
cycle2 = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='BrCCCBr',
functional_groups=[stk.BromoFactory()],
),
stk.BuildingBlock(
smiles='BrCCNCBr',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='AB',
num_repeating_units=5,
optimizer=stk.MCHammer(),
),
)
cycle3 = stk.ConstructedMolecule(
topology_graph=stk.macrocycle.Macrocycle(
building_blocks=(
stk.BuildingBlock(
smiles='BrCCNNCBr',
functional_groups=[stk.BromoFactory()],
),
stk.BuildingBlock(
smiles='BrCCNNNCBr',
functional_groups=[stk.BromoFactory()],
),
),
repeating_unit='AB',
num_repeating_units=5,
optimizer=stk.MCHammer(),
),
)
axle = stk.ConstructedMolecule(
topology_graph=stk.polymer.Linear(
building_blocks=(
stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]),
),
repeating_unit='A',
num_repeating_units=2,
),
)
# r1 and r2 are different ways to write the same thing.
r1 = stk.ConstructedMolecule(
topology_graph=stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
stk.BuildingBlock.init_from_molecule(cycle3),
),
repeating_unit='ACB',
num_repeating_units=3,
),
)
r2 = stk.ConstructedMolecule(
topology_graph=stk.rotaxane.NRotaxane(
axle=stk.BuildingBlock.init_from_molecule(axle),
cycles=(
stk.BuildingBlock.init_from_molecule(cycle1),
stk.BuildingBlock.init_from_molecule(cycle2),
stk.BuildingBlock.init_from_molecule(cycle3),
),
repeating_unit=(0, 2, 1),
num_repeating_units=3,
),
)
"""
[docs] def __init__(
self,
axle,
cycles,
repeating_unit,
num_repeating_units,
orientations=None,
random_seed=None,
num_processes=1,
optimizer=NullOptimizer(),
):
"""
Initialize a :class:`NRotaxane` instance.
Parameters
----------
axle : :class:`.BuildingBlock`
The axle of the rotaxane.
cycles : :class:`tuple` of :class:`.BuildingBlock`
The cycles threaded onto the `axle`.
repeating_unit : :class:`str` or :class:`tuple` of :class:`int`
A string specifying the repeating unit of the `cycles`.
For example, ``'AB'`` or ``'ABB'``. The first cycle in
`cycles` is ``'A'`` and so on.
The repeating unit can also be specified by the indices of
`cycles`, for example ``'ABB'`` can be
written as ``(0, 1, 1)``.
num_repeating_units : :class:`int`
The number of repeating units threaded along the axle.
orientations : :class:`tuple` of :class:`float`, optional
For each character in the repeating unit, a value
between ``0`` and ``1`` (both inclusive) must be given in
a :class:`tuple`. It indicates the probability that each
cycle will have its orientation along the axle
flipped. If ``0`` then the cycle is guaranteed not to
flip. If ``1`` it is guaranteed to flip. This allows the
user to create head-to-head or head-to-tail chains, as well
as chain with a preference for head-to-head or head-to-tail
if a number between ``0`` and ``1`` is chosen. If
``None``, then defaults to ``0`` in every case.
It is also possible to supply an orientation for every
cycle vertex in the final topology graph. In this case, the
length of `orientations` must be equal to
``len(repeating_unit)*num_repeating_units``.
random_seed : :class:`int`, optional
The random seed to use when choosing random orientations.
num_processes : :class:`int`, optional
The number of parallel processes to create during
:meth:`construct`.
optimizer : :class:`.Optimizer`, optional
Used to optimize the structure of the constructed
molecule.
Raises
------
:class:`ValueError`
If the length of `orientations` is not equal in length to
`repeating_unit` or to the total number of vertices.
"""
if orientations is None:
orientations = tuple(
0. for i in range(len(repeating_unit))
)
if len(orientations) == len(repeating_unit):
orientations = orientations*num_repeating_units
chain_length = len(repeating_unit)*num_repeating_units
if len(orientations) != chain_length:
raise ValueError(
'The length of orientations must match either '
'the length of repeating_unit or the '
'total number of vertices.'
)
generator = np.random.RandomState(random_seed)
self._repeating_unit = self._normalize_repeating_unit(
repeating_unit=repeating_unit,
)
self._num_repeating_units = num_repeating_units
vertices = [AxleVertex(0, [0, 0, 0])]
distance = 1 / (chain_length+1)
choices = [True, False]
for vertex_id, flip_chance in enumerate(orientations, 1):
vertices.append(
CycleVertex(
id=vertex_id,
position=[vertex_id*distance-0.5, 0, 0],
flip=generator.choice(
choices,
p=[flip_chance, 1-flip_chance],
)
)
)
# Save the chosen orientations for __repr__.
self._orientations = tuple(
int(vertex.get_flip()) for vertex in vertices[1:]
)
super().__init__(
building_block_vertices=self._get_building_block_vertices(
axle=axle,
cycles=cycles,
vertices=vertices,
),
edges=(),
reaction_factory=None,
construction_stages=(),
num_processes=num_processes,
optimizer=optimizer,
edge_groups=None,
)
[docs] def clone(self):
clone = super().clone()
clone._repeating_unit = self._repeating_unit
clone._num_repeating_units = self._num_repeating_units
clone._orientations = self._orientations
return clone
@staticmethod
def _normalize_repeating_unit(repeating_unit):
if isinstance(repeating_unit, tuple):
return repeating_unit
base = ord('A')
return tuple(ord(letter)-base for letter in repeating_unit)
def _get_building_block_vertices(self, axle, cycles, vertices):
threads = self._repeating_unit*self._num_repeating_units
building_block_vertices = {}
building_block_vertices[axle] = vertices[0:1]
for cycle_index, vertex in zip(threads, vertices[1:]):
bb = cycles[cycle_index]
building_block_vertices[bb] = (
building_block_vertices.get(bb, [])
)
building_block_vertices[bb].append(vertex)
return building_block_vertices
def _run_reactions(self, state):
return state
def _get_scale(self, building_block_vertices):
axle = next(iter(building_block_vertices))
return 0.8*axle.get_maximum_diameter()
def __repr__(self):
return (
f'rotaxane.NRotaxane('
f'{self._repeating_unit!r}, '
f'{self._num_repeating_units}, '
f'{self._orientations!r}'
f')'
)