Macrocycle¶

class
Macrocycle
(building_blocks, repeating_unit, num_repeating_units, orientations=None, random_seed=None, reaction_factory=GenericReactionFactory(), num_processes=1, optimizer=<stk.molecular.topology_graphs.topology_graph.optimizers.null.NullOptimizer object>)[source]¶ Bases:
stk.molecular.topology_graphs.topology_graph.topology_graph.topology_graph.TopologyGraph
Represents a macrocycle topology graph.
Building blocks with two functional groups are required for this topology.
Examples
Construction
This topology graph essentially makes a polymer chain and joins the ends, hence the constructor parameters allows you to specify the chain
import stk macrocycle = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=( stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]), stk.BuildingBlock('BrCNCBr', [stk.BromoFactory()]), ), repeating_unit='AB', num_repeating_units=5, ), )
Suggested Optimization
For
Macrocycle
topologies, it is recommended to use theMCHammer
optimizer.import stk macrocycle = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=( stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]), stk.BuildingBlock('BrCNCBr', [stk.BromoFactory()]), ), repeating_unit='AB', num_repeating_units=5, optimizer=stk.MCHammer(), ), )
Defining the Orientation of Each Building Block
The orientations parameter allows the direction of each building block along to the chain to be flipped
import stk bb1 = stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]) bb2 = stk.BuildingBlock('BrCOCCBr', [stk.BromoFactory()]) c1 = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=5, orientations=(1, 0.5), ), )
In the above example,
bb1
is guaranteed to be flipped,bb2
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
Macrocycle
# cycle will always construct the same macrocycle. cycle = stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=5, orientations=(0.65, 0.45), ) # c2 and c3 are guaranteed to be the same as they used the same # topology graph. c2 = stk.ConstructedMolecule(cycle) c3 = stk.ConstructedMolecule(cycle) # cycle2 may lead to a different polymer than chain, despite # being initialized with the same parameters. cycle2 = stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=5, orientations=(0.65, 0.45) ) # c4 and c5 are guaranteed to be the same because they used # the same topology graph. However, they may be different to # c2 and c3. c4 = stk.ConstructedMolecule(cycle2) c5 = stk.ConstructedMolecule(cycle2)
The random_seed parameter can be used to get reproducible results
# c6 and c7 are guaranteed to be the same, because cycle3 and # cycle4 used the same random seed. cycle3 = stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=5, orientations=(0.65, 0.45), random_seed=4, ) c6 = stk.ConstructedMolecule(cycle3) cycle4 = stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=5, orientations=(0.65, 0.45), random_seed=4, ) c7 = stk.ConstructedMolecule(cycle4)
Using Numbers to Define the Repeating Unit
The repeating unit can also be specified through the indices of the building blocks
import stk bb1 = stk.BuildingBlock('BrCCBr', [stk.BromoFactory()]) bb2 = stk.BuildingBlock('BrCNCBr', [stk.BromoFactory()]) bb3 = stk.BuildingBlock('BrCNNCBr', [stk.BromoFactory()]) # c1 and c2 are different ways to write the same thing. c1 = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2, bb3), repeating_unit='ACB', num_repeating_units=3 ) ) c2 = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=(bb1, bb2, bb3), repeating_unit=(0, 2, 1), num_repeating_units=3, ) )
Methods
clone
()Return a clone.
Construct a
ConstructedMolecule
.Yield the building blocks.
get_num_building_block
(building_block)Get the number of times building_block is present.
with_building_blocks
(building_block_map)Return a clone holding different building blocks.

__init__
(building_blocks, repeating_unit, num_repeating_units, orientations=None, random_seed=None, reaction_factory=GenericReactionFactory(), num_processes=1, optimizer=<stk.molecular.topology_graphs.topology_graph.optimizers.null.NullOptimizer object>)[source]¶ Initialize a
Macrocycle
instance. Parameters
building_blocks (
tuple
ofBuildingBlock
) – The building blocks of the macrocycle.repeating_unit (
str
ortuple
ofint
) –A string specifying the repeating unit of the macrocycle. For example,
'AB'
or'ABB'
. The first building block passed to building_blocks is'A'
and so on.The repeating unit can also be specified by the indices of building_blocks, for example
'ABB'
can be written as(0, 1, 1)
.num_repeating_units (
int
) – The number of repeating units which are used to make the macrocycle.orientations (
tuple
offloat
, optional) –For each character in the repeating unit, a value between
0
and1
(both inclusive) must be given in atuple
. It indicates the probability that each monomer will have its orientation along the chain flipped. If0
then the monomer is guaranteed not to flip. If1
it is guaranteed to flip. This allows the user to create headtohead or headtotail chains, as well as chain with a preference for headtohead or headtotail if a number between0
and1
is chosen. IfNone
, then0
is picked in every case.It is also possible to supply an orientation for every 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 (
int
, optional) – The random seed to use when choosing random orientations.num_processes (
int
, optional) – The number of parallel processes to create duringconstruct()
.optimizer (
Optimizer
, optional) – Used to optimize the structure of the constructed molecule.
 Raises
ValueError – If the length of orientations is not equal in length to repeating_unit or to the total number of vertices.

clone
()[source]¶ Return a clone.
 Returns
The clone. Has the same type as the original topology graph.
 Return type

construct
()¶ Construct a
ConstructedMolecule
. Returns
The data describing the
ConstructedMolecule
. Return type

get_building_blocks
()¶ Yield the building blocks.
Building blocks are yielded in an order based on their position in the topology graph. For two equivalent topology graphs, but with different building blocks, equivalently positioned building blocks will be yielded at the same time.
 Yields
BuildingBlock
– A building block of the topology graph.

get_num_building_block
(building_block)¶ Get the number of times building_block is present.
 Parameters
building_block (
BuildingBlock
) – The building block whose frequency in the topology graph is desired. Returns
The number of times building_block is present in the topology graph.
 Return type

with_building_blocks
(building_block_map)¶ Return a clone holding different building blocks.
 Parameters
building_block_map (
dict
) – Maps a building block in the current topology graph to the building block which should replace it in the clone. If a building block should be not replaced in the clone, it can be omitted from the map. Returns
The clone. Has the same type as the original topology graph.
 Return type
