# pylint: disable=too-many-lines
"""Find allowed transitions between an initial and final state."""
import logging
from collections import abc, defaultdict
from copy import copy, deepcopy
from enum import Enum, auto
from itertools import zip_longest
from multiprocessing import Pool
from typing import (
TYPE_CHECKING,
Any,
Collection,
DefaultDict,
Dict,
Iterable,
Iterator,
List,
Mapping,
Optional,
Sequence,
Set,
Tuple,
Type,
Union,
overload,
)
import attrs
from attrs import define, field, frozen
from attrs.validators import instance_of
from tqdm.auto import tqdm
from qrules._implementers import implement_pretty_repr
from ._system_control import (
GammaCheck,
InteractionDeterminator,
LeptonCheck,
create_edge_properties,
create_interaction_properties,
create_node_properties,
create_particle,
filter_interaction_types,
remove_duplicate_solutions,
)
from .combinatorics import (
InitialFacts,
StateDefinition,
create_initial_facts,
match_external_edges,
)
from .particle import (
Particle,
ParticleCollection,
ParticleWithSpin,
_to_float,
load_pdg,
)
from .quantum_numbers import (
EdgeQuantumNumber,
EdgeQuantumNumbers,
InteractionProperties,
NodeQuantumNumber,
NodeQuantumNumbers,
)
from .settings import (
InteractionType,
NumberOfThreads,
create_interaction_settings,
)
from .solving import (
CSPSolver,
EdgeSettings,
GraphEdgePropertyMap,
GraphElementProperties,
GraphSettings,
NodeSettings,
QNProblemSet,
QNResult,
)
from .topology import (
FrozenDict,
StateTransitionGraph,
Topology,
create_isobar_topologies,
create_n_body_topology,
)
if TYPE_CHECKING:
try:
from IPython.lib.pretty import PrettyPrinter
except ImportError:
PrettyPrinter = Any
[docs]class SolvingMode(Enum):
"""Types of modes for solving."""
FAST = auto()
"""Find "likeliest" solutions only."""
FULL = auto()
"""Find all possible solutions."""
[docs]@implement_pretty_repr
@define(on_setattr=attrs.setters.frozen)
class ExecutionInfo:
not_executed_node_rules: Dict[int, Set[str]] = field(
factory=lambda: defaultdict(set)
)
violated_node_rules: Dict[int, Set[str]] = field(
factory=lambda: defaultdict(set)
)
not_executed_edge_rules: Dict[int, Set[str]] = field(
factory=lambda: defaultdict(set)
)
violated_edge_rules: Dict[int, Set[str]] = field(
factory=lambda: defaultdict(set)
)
[docs] def extend(
self, other_result: "ExecutionInfo", intersect_violations: bool = False
) -> None:
for key, rules in other_result.not_executed_node_rules.items():
self.not_executed_node_rules[key].update(rules)
for key, rules in other_result.not_executed_edge_rules.items():
self.not_executed_edge_rules[key].update(rules)
for key, rules2 in other_result.violated_node_rules.items():
if intersect_violations:
self.violated_node_rules[key] &= rules2
else:
self.violated_node_rules[key].update(rules2)
for key, rules2 in other_result.violated_edge_rules.items():
if intersect_violations:
self.violated_edge_rules[key] &= rules2
else:
self.violated_edge_rules[key].update(rules2)
[docs] def clear(self) -> None:
self.not_executed_node_rules.clear()
self.violated_node_rules.clear()
self.not_executed_edge_rules.clear()
self.violated_edge_rules.clear()
@frozen
class _SolutionContainer:
"""Defines a result of a `.ProblemSet`."""
solutions: List[StateTransitionGraph[ParticleWithSpin]] = field(
factory=list
)
execution_info: ExecutionInfo = field(default=ExecutionInfo())
def __attrs_post_init__(self) -> None:
if self.solutions and (
self.execution_info.violated_node_rules
or self.execution_info.violated_edge_rules
):
raise ValueError(
f"Invalid {self.__class__.__name__}! Found"
f" {len(self.solutions)} solutions, but also violated rules.",
self.execution_info.violated_node_rules,
self.execution_info.violated_edge_rules,
)
def extend(
self, other: "_SolutionContainer", intersect_violations: bool = False
) -> None:
if self.solutions or other.solutions:
self.solutions.extend(other.solutions)
self.execution_info.clear()
else:
self.execution_info.extend(
other.execution_info, intersect_violations
)
[docs]@implement_pretty_repr
@define
class ProblemSet:
"""Particle reaction problem set, defined as a graph like data structure.
Args:
topology: `.Topology` that contains the structure of the reaction.
initial_facts: `~.InitialFacts` that contain the info of initial and
final state in connection with the topology.
solving_settings: Solving related settings such as the conservation
rules and the quantum number domains.
"""
topology: Topology
initial_facts: InitialFacts
solving_settings: GraphSettings
[docs] def to_qn_problem_set(self) -> QNProblemSet:
node_props = {
k: create_node_properties(v)
for k, v in self.initial_facts.node_props.items()
}
edge_props = {
k: create_edge_properties(v[0], v[1])
for k, v in self.initial_facts.edge_props.items()
}
return QNProblemSet(
topology=self.topology,
initial_facts=GraphElementProperties(
node_props=node_props, edge_props=edge_props
),
solving_settings=self.solving_settings,
)
def _group_by_strength(
problem_sets: List[ProblemSet],
) -> Dict[float, List[ProblemSet]]:
def calculate_strength(
node_interaction_settings: Dict[int, NodeSettings]
) -> float:
strength = 1.0
for int_setting in node_interaction_settings.values():
strength *= int_setting.interaction_strength
return strength
strength_sorted_problem_sets: Dict[float, List[ProblemSet]] = defaultdict(
list
)
for problem_set in problem_sets:
strength = calculate_strength(
problem_set.solving_settings.node_settings
)
strength_sorted_problem_sets[strength].append(problem_set)
return strength_sorted_problem_sets
[docs]class StateTransitionManager: # pylint: disable=too-many-instance-attributes
"""Main handler for decay topologies.
.. seealso:: :doc:`/usage/reaction` and `.generate_transitions`
"""
def __init__( # pylint: disable=too-many-arguments, too-many-branches, too-many-locals
self,
initial_state: Sequence[StateDefinition],
final_state: Sequence[StateDefinition],
particle_db: Optional[ParticleCollection] = None,
allowed_intermediate_particles: Optional[List[str]] = None,
interaction_type_settings: Dict[
InteractionType, Tuple[EdgeSettings, NodeSettings]
] = None,
formalism: str = "helicity",
topology_building: str = "isobar",
solving_mode: SolvingMode = SolvingMode.FAST,
reload_pdg: bool = False,
mass_conservation_factor: Optional[float] = 3.0,
max_angular_momentum: int = 1,
max_spin_magnitude: float = 2.0,
number_of_threads: Optional[int] = None,
) -> None:
if number_of_threads is not None:
NumberOfThreads.set(number_of_threads)
self.__number_of_threads = NumberOfThreads.get()
if interaction_type_settings is None:
interaction_type_settings = {}
allowed_formalisms = [
"helicity",
"canonical-helicity",
"canonical",
]
if formalism not in allowed_formalisms:
raise NotImplementedError(
f'Formalism "{formalism}" not implemented.'
f" Use one of {allowed_formalisms} instead."
)
self.__formalism = str(formalism)
self.__particles = ParticleCollection()
if particle_db is not None:
self.__particles = particle_db
self.reaction_mode = str(solving_mode)
self.initial_state = initial_state
self.final_state = final_state
self.interaction_type_settings = interaction_type_settings
self.interaction_determinators: List[InteractionDeterminator] = [
LeptonCheck(),
GammaCheck(),
]
self.final_state_groupings: Optional[List[List[List[str]]]] = None
self.allowed_interaction_types: List[InteractionType] = [
InteractionType.STRONG,
InteractionType.EM,
InteractionType.WEAK,
]
self.filter_remove_qns: Set[Type[NodeQuantumNumber]] = set()
self.filter_ignore_qns: Set[Type[NodeQuantumNumber]] = set()
if formalism == "helicity":
self.filter_remove_qns = {
NodeQuantumNumbers.l_magnitude,
NodeQuantumNumbers.l_projection,
NodeQuantumNumbers.s_magnitude,
NodeQuantumNumbers.s_projection,
}
if "helicity" in formalism:
self.filter_ignore_qns = {NodeQuantumNumbers.parity_prefactor}
use_nbody_topology = False
topology_building = topology_building.lower()
if topology_building == "isobar":
self.topologies: Tuple[Topology, ...] = create_isobar_topologies(
len(final_state)
)
"""`.Topology` instances over which the STM propagates quantum numbers."""
elif "n-body" in topology_building or "nbody" in topology_building:
self.topologies = (
create_n_body_topology(len(initial_state), len(final_state)),
)
use_nbody_topology = True
# turn off mass conservation, in case more than one initial state
# particle is present
if len(initial_state) > 1:
mass_conservation_factor = None
if reload_pdg or len(self.__particles) == 0:
self.__particles = load_pdg()
if not self.interaction_type_settings:
self.interaction_type_settings = create_interaction_settings(
formalism,
particle_db=self.__particles,
nbody_topology=use_nbody_topology,
mass_conservation_factor=mass_conservation_factor,
max_angular_momentum=max_angular_momentum,
max_spin_magnitude=max_spin_magnitude,
)
self.__user_allowed_intermediate_particles = (
allowed_intermediate_particles
)
self.__allowed_intermediate_particles: List[GraphEdgePropertyMap] = []
if allowed_intermediate_particles is not None:
self.set_allowed_intermediate_particles(
allowed_intermediate_particles
)
else:
self.__allowed_intermediate_particles = [
create_edge_properties(x) for x in self.__particles
]
[docs] def set_allowed_intermediate_particles(
self, particle_names: List[str]
) -> None:
self.__allowed_intermediate_particles = []
for particle_name in particle_names:
matches = self.__particles.filter(
lambda p: particle_name # pylint: disable=cell-var-from-loop
in p.name
)
if len(matches) == 0:
raise LookupError(
"Could not find any matches for allowed intermediate"
f' particle "{particle_name}"'
)
self.__allowed_intermediate_particles += [
create_edge_properties(x) for x in matches
]
@property
def formalism(self) -> str:
return self.__formalism
[docs] def add_final_state_grouping(
self, fs_group: Union[List[str], List[List[str]]]
) -> None:
if not isinstance(fs_group, list):
raise ValueError(
"The final state grouping has to be of type list."
)
if len(fs_group) > 0:
if self.final_state_groupings is None:
self.final_state_groupings = []
nested_list = _safe_wrap_list(fs_group)
self.final_state_groupings.append(nested_list)
[docs] def set_allowed_interaction_types(
self, allowed_interaction_types: Iterable[InteractionType]
) -> None:
# verify order
for allowed_types in allowed_interaction_types:
if not isinstance(allowed_types, InteractionType):
raise TypeError(
"allowed interaction types must be of type"
"[InteractionType]"
)
if allowed_types not in self.interaction_type_settings:
logging.info(self.interaction_type_settings.keys())
raise ValueError(
f"interaction {allowed_types} not found in settings"
)
self.allowed_interaction_types = list(allowed_interaction_types)
[docs] def create_problem_sets(self) -> Dict[float, List[ProblemSet]]:
problem_sets = []
for topology in self.topologies:
for initial_facts in create_initial_facts(
topology=topology,
particle_db=self.__particles,
initial_state=self.initial_state,
final_state=self.final_state,
final_state_groupings=self.final_state_groupings,
):
problem_sets.extend(
[
ProblemSet(
topology=topology,
initial_facts=initial_facts,
solving_settings=x,
)
for x in self.__determine_graph_settings(
topology, initial_facts
)
]
)
# create groups of settings ordered by "probability"
return _group_by_strength(problem_sets)
def __determine_graph_settings(
self, topology: Topology, initial_facts: InitialFacts
) -> List[GraphSettings]:
# pylint: disable=too-many-locals
def create_intermediate_edge_qn_domains() -> Dict:
# if a list of intermediate states is given by user,
# built a domain based on these states
if self.__user_allowed_intermediate_particles:
intermediate_edge_domains: Dict[
Type[EdgeQuantumNumber], Set
] = defaultdict(set)
intermediate_edge_domains[
EdgeQuantumNumbers.spin_projection
].update(
self.interaction_type_settings[InteractionType.WEAK][
0
].qn_domains[EdgeQuantumNumbers.spin_projection]
)
for particle_props in self.__allowed_intermediate_particles:
for edge_qn, qn_value in particle_props.items():
intermediate_edge_domains[edge_qn].add(qn_value)
return {
k: list(v)
for k, v in intermediate_edge_domains.items()
if k is not EdgeQuantumNumbers.pid
and k is not EdgeQuantumNumbers.mass
and k is not EdgeQuantumNumbers.width
}
return self.interaction_type_settings[InteractionType.WEAK][
0
].qn_domains
intermediate_state_edges = topology.intermediate_edge_ids
int_edge_domains = create_intermediate_edge_qn_domains()
def create_edge_settings(edge_id: int) -> EdgeSettings:
settings = copy(
self.interaction_type_settings[InteractionType.WEAK][0]
)
if edge_id in intermediate_state_edges:
settings.qn_domains = int_edge_domains
else:
settings.qn_domains = {}
return settings
final_state_edges = topology.outgoing_edge_ids
initial_state_edges = topology.incoming_edge_ids
graph_settings: List[GraphSettings] = [
GraphSettings(
edge_settings={
edge_id: create_edge_settings(edge_id)
for edge_id in topology.edges
},
node_settings={},
)
]
for node_id in topology.nodes:
interaction_types: List[InteractionType] = []
out_edge_ids = topology.get_edge_ids_outgoing_from_node(node_id)
in_edge_ids = topology.get_edge_ids_outgoing_from_node(node_id)
in_edge_props = [
initial_facts.edge_props[edge_id]
for edge_id in [
x for x in in_edge_ids if x in initial_state_edges
]
]
out_edge_props = [
initial_facts.edge_props[edge_id]
for edge_id in [
x for x in out_edge_ids if x in final_state_edges
]
]
node_props = InteractionProperties()
if node_id in initial_facts.node_props:
node_props = initial_facts.node_props[node_id]
for int_det in self.interaction_determinators:
determined_interactions = int_det.check(
in_edge_props, out_edge_props, node_props
)
if interaction_types:
interaction_types = list(
set(determined_interactions) & set(interaction_types)
)
else:
interaction_types = determined_interactions
interaction_types = filter_interaction_types(
interaction_types, self.allowed_interaction_types
)
logging.debug(
"using %s interaction order for node: %s",
str(interaction_types),
str(node_id),
)
temp_graph_settings: List[GraphSettings] = graph_settings
graph_settings = []
for temp_setting in temp_graph_settings:
for int_type in interaction_types:
updated_setting = deepcopy(temp_setting)
updated_setting.node_settings[node_id] = deepcopy(
self.interaction_type_settings[int_type][1]
)
graph_settings.append(updated_setting)
return graph_settings
[docs] def find_solutions( # pylint: disable=too-many-branches
self,
problem_sets: Dict[float, List[ProblemSet]],
) -> "ReactionInfo":
# pylint: disable=too-many-locals
"""Check for solutions for a specific set of interaction settings."""
results: Dict[float, _SolutionContainer] = {}
logging.info(
"Number of interaction settings groups being processed: %d",
len(problem_sets),
)
total = sum(map(len, problem_sets.values()))
progress_bar = tqdm(
total=total,
desc="Propagating quantum numbers",
disable=logging.getLogger().level > logging.WARNING,
)
for strength, problems in sorted(problem_sets.items(), reverse=True):
logging.info(
"processing interaction settings group with "
f"strength {strength}",
)
logging.info(f"{len(problems)} entries in this group")
logging.info(f"running with {self.__number_of_threads} threads...")
qn_problems = [x.to_qn_problem_set() for x in problems]
# Because of pickling problems of Generic classes (in this case
# StateTransitionGraph), multithreaded code has to work with
# QNProblemSet's and QNResult's. So the appropriate conversions
# have to be done before and after
temp_qn_results: List[Tuple[QNProblemSet, QNResult]] = []
if self.__number_of_threads > 1:
with Pool(self.__number_of_threads) as pool:
for qn_result in pool.imap_unordered(
self._solve, qn_problems, 1
):
temp_qn_results.append(qn_result)
progress_bar.update()
else:
for problem in qn_problems:
temp_qn_results.append(self._solve(problem))
progress_bar.update()
for temp_qn_result in temp_qn_results:
temp_result = self.__convert_result(
temp_qn_result[0].topology,
temp_qn_result[1],
)
if strength not in results:
results[strength] = temp_result
else:
results[strength].extend(temp_result, True)
if (
results[strength].solutions
and self.reaction_mode == SolvingMode.FAST
):
break
progress_bar.close()
for key, result in results.items():
logging.info(
f"number of solutions for strength ({key}) "
f"after qn solving: {len(result.solutions)}",
)
final_result = _SolutionContainer()
for temp_result in results.values():
final_result.extend(temp_result)
# remove duplicate solutions, which only differ in the interaction qns
final_solutions = remove_duplicate_solutions(
final_result.solutions,
self.filter_remove_qns,
self.filter_ignore_qns,
)
if (
final_result.execution_info.violated_edge_rules
or final_result.execution_info.violated_node_rules
):
execution_info = final_result.execution_info
violated_rules: Set[str] = set()
for rules in execution_info.violated_edge_rules.values():
violated_rules |= rules
for rules in execution_info.violated_node_rules.values():
violated_rules |= rules
if violated_rules:
raise RuntimeError(
"There were violated conservation rules: "
+ ", ".join(violated_rules)
)
if (
final_result.execution_info.not_executed_edge_rules
or final_result.execution_info.not_executed_node_rules
):
not_executed_rules: Set[str] = set()
for rules in execution_info.not_executed_edge_rules.values():
not_executed_rules |= rules
for rules in execution_info.not_executed_node_rules.values():
not_executed_rules |= rules
raise RuntimeWarning(
"There are conservation rules that were not executed: "
+ ", ".join(not_executed_rules)
)
if not final_solutions:
raise ValueError("No solutions were found")
match_external_edges(final_solutions)
final_solutions = [
_match_final_state_ids(graph, self.final_state)
for graph in final_solutions
]
return ReactionInfo.from_graphs(final_solutions, self.formalism)
def _solve(
self, qn_problem_set: QNProblemSet
) -> Tuple[QNProblemSet, QNResult]:
solver = CSPSolver(self.__allowed_intermediate_particles)
return (qn_problem_set, solver.find_solutions(qn_problem_set))
def __convert_result(
self, topology: Topology, qn_result: QNResult
) -> _SolutionContainer:
"""Converts a `.QNResult` with a `.Topology` into `.ReactionInfo`.
The ParticleCollection is used to retrieve a particle instance
reference to lower the memory footprint.
"""
solutions = []
for solution in qn_result.solutions:
graph = StateTransitionGraph[ParticleWithSpin](
topology=topology,
node_props={
i: create_interaction_properties(x)
for i, x in solution.node_quantum_numbers.items()
},
edge_props={
i: create_particle(x, self.__particles)
for i, x in solution.edge_quantum_numbers.items()
},
)
solutions.append(graph)
return _SolutionContainer(
solutions,
ExecutionInfo(
violated_edge_rules=qn_result.violated_edge_rules,
violated_node_rules=qn_result.violated_node_rules,
not_executed_node_rules=qn_result.not_executed_node_rules,
not_executed_edge_rules=qn_result.not_executed_edge_rules,
),
)
def _safe_wrap_list(
nested_list: Union[List[str], List[List[str]]]
) -> List[List[str]]:
if all(map(lambda i: isinstance(i, list), nested_list)):
return nested_list # type: ignore[return-value]
if all(map(lambda i: isinstance(i, str), nested_list)):
return [nested_list] # type: ignore[list-item]
raise TypeError(
f"Input final state grouping {nested_list} is not a list of lists of"
" strings"
)
def _match_final_state_ids(
graph: StateTransitionGraph[ParticleWithSpin],
state_definition: Sequence[StateDefinition],
) -> StateTransitionGraph[ParticleWithSpin]:
"""Temporary fix to https://github.com/ComPWA/qrules/issues/143."""
particle_names = _strip_spin(state_definition)
name_to_id = {name: i for i, name in enumerate(particle_names)}
id_remapping = {
name_to_id[graph.get_edge_props(i)[0].name]: i
for i in graph.topology.outgoing_edge_ids
}
new_topology = graph.topology.relabel_edges(id_remapping)
return StateTransitionGraph(
new_topology,
edge_props={
i: graph.get_edge_props(id_remapping.get(i, i))
for i in graph.topology.edges
},
node_props={i: graph.get_node_props(i) for i in graph.topology.nodes},
)
def _strip_spin(state_definition: Sequence[StateDefinition]) -> List[str]:
particle_names = []
for state in state_definition:
if isinstance(state, str):
particle_names.append(state)
else:
particle_names.append(state[0])
return particle_names
[docs]@implement_pretty_repr
@frozen(order=True)
class State:
particle: Particle = field(validator=instance_of(Particle))
spin_projection: float = field(converter=_to_float)
[docs]@implement_pretty_repr
@frozen(order=True)
class StateTransition:
"""Frozen instance of a `.StateTransitionGraph` of a particle with spin."""
topology: Topology = field(validator=instance_of(Topology))
states: FrozenDict[int, State] = field(converter=FrozenDict)
interactions: FrozenDict[int, InteractionProperties] = field(
converter=FrozenDict
)
def __attrs_post_init__(self) -> None:
_assert_defined(self.topology.edges, self.states)
_assert_defined(self.topology.nodes, self.interactions)
[docs] @staticmethod
def from_graph(
graph: StateTransitionGraph[ParticleWithSpin],
) -> "StateTransition":
return StateTransition(
topology=graph.topology,
states=FrozenDict(
{
i: State(*graph.get_edge_props(i))
for i in graph.topology.edges
}
),
interactions=FrozenDict(
{i: graph.get_node_props(i) for i in graph.topology.nodes}
),
)
[docs] def to_graph(self) -> StateTransitionGraph[ParticleWithSpin]:
return StateTransitionGraph[ParticleWithSpin](
topology=self.topology,
edge_props={
i: (state.particle, state.spin_projection)
for i, state in self.states.items()
},
node_props=self.interactions,
)
@property
def initial_states(self) -> Dict[int, State]:
return self.filter_states(self.topology.incoming_edge_ids)
@property
def final_states(self) -> Dict[int, State]:
return self.filter_states(self.topology.outgoing_edge_ids)
@property
def intermediate_states(self) -> Dict[int, State]:
return self.filter_states(self.topology.intermediate_edge_ids)
[docs] def filter_states(self, edge_ids: Iterable[int]) -> Dict[int, State]:
return {i: self.states[i] for i in edge_ids}
@property
def particles(self) -> Dict[int, Particle]:
return {i: edge_prop.particle for i, edge_prop in self.states.items()}
def _assert_defined(items: Collection, properties: Mapping) -> None:
existing = set(items)
defined = set(properties)
if existing & defined != existing:
raise ValueError(
"Some items have no property assigned to them."
f" Available items: {existing}, items with property: {defined}"
)
def _to_sorted_tuple(
iterable: Iterable[StateTransition],
) -> Tuple[StateTransition, ...]:
if not all(map(lambda t: isinstance(t, StateTransition), iterable)):
raise TypeError(
f"Not all instances are of type {StateTransition.__name__}"
)
return tuple(sorted(iterable))
[docs]@frozen
class StateTransitionCollection(abc.Sequence):
"""`.StateTransition` instances with the same `.Topology` and edge IDs."""
transitions: Tuple[StateTransition, ...] = field(
converter=_to_sorted_tuple
)
topology: Topology = field(init=False, repr=False)
initial_state: FrozenDict[int, Particle] = field(init=False, repr=False)
final_state: FrozenDict[int, Particle] = field(init=False, repr=False)
def __attrs_post_init__(self) -> None:
if not any(self.transitions):
ValueError(f"At least one {StateTransition.__name__} required")
some_transition = next(iter(self.transitions))
topology = some_transition.topology
if not all(map(lambda t: t.topology == topology, self.transitions)):
raise TypeError(
f"Not all {StateTransition.__name__} items have the same"
f" underlying topology. Expecting: {topology}"
)
object.__setattr__(self, "topology", topology)
object.__setattr__(
self,
"initial_state",
FrozenDict(
{
i: s.particle
for i, s in some_transition.states.items()
if i in some_transition.topology.incoming_edge_ids
}
),
)
object.__setattr__(
self,
"final_state",
FrozenDict(
{
i: s.particle
for i, s in some_transition.states.items()
if i in some_transition.topology.outgoing_edge_ids
}
),
)
def _repr_pretty_(self, p: "PrettyPrinter", cycle: bool) -> None:
class_name = type(self).__name__
if cycle:
p.text(f"{class_name}(...)")
else:
with p.group(indent=2, open=f"{class_name}(transitions=("):
for transition in self:
p.breakable()
p.pretty(transition)
p.text(",")
p.breakable()
p.text("))")
def __contains__(self, item: object) -> bool:
return item in self.transitions
@overload
def __getitem__(self, idx: int) -> StateTransition:
...
@overload
def __getitem__(self, idx: slice) -> Tuple[StateTransition]:
...
[docs] def __getitem__(self, idx: Any) -> Any:
return self.transitions[idx]
def __iter__(self) -> Iterator[StateTransition]:
return iter(self.transitions)
def __len__(self) -> int:
return len(self.transitions)
[docs] @staticmethod
def from_graphs(
graphs: Iterable[StateTransitionGraph[ParticleWithSpin]],
) -> "StateTransitionCollection":
transitions = [StateTransition.from_graph(g) for g in graphs]
return StateTransitionCollection(transitions)
[docs] def to_graphs(self) -> List[StateTransitionGraph[ParticleWithSpin]]:
return [transition.to_graph() for transition in sorted(self)]
[docs] def get_intermediate_particles(self) -> ParticleCollection:
"""Extract the particle names of the intermediate states."""
intermediate_states = ParticleCollection()
for transition in self.transitions:
for state in transition.intermediate_states.values():
if state.particle not in intermediate_states:
intermediate_states.add(state.particle)
return intermediate_states
def _to_tuple(
iterable: Iterable[StateTransitionCollection],
) -> Tuple[StateTransitionCollection, ...]:
if not all(
map(lambda t: isinstance(t, StateTransitionCollection), iterable)
):
raise TypeError(
"Not all instances are of type"
f" {StateTransitionCollection.__name__}"
)
return tuple(iterable)
[docs]@frozen(eq=False, hash=True)
class ReactionInfo:
"""`StateTransitionCollection` instances, grouped by `.Topology`."""
transition_groups: Tuple[StateTransitionCollection, ...] = field(
converter=_to_tuple
)
transitions: Tuple[StateTransition, ...] = field(
init=False, repr=False, eq=False
)
initial_state: FrozenDict[int, Particle] = field(init=False, repr=False)
final_state: FrozenDict[int, Particle] = field(init=False, repr=False)
formalism: str = field(validator=instance_of(str))
def __attrs_post_init__(self) -> None:
if len(self.transition_groups) == 0:
ValueError(
f"At least one {StateTransitionCollection.__name__} required"
)
transitions: List[StateTransition] = []
for grouping in self.transition_groups:
transitions.extend(sorted(grouping))
first_grouping = self.transition_groups[0]
object.__setattr__(self, "transitions", tuple(transitions))
object.__setattr__(self, "final_state", first_grouping.final_state)
object.__setattr__(self, "initial_state", first_grouping.initial_state)
def __eq__(self, other: object) -> bool:
if isinstance(other, ReactionInfo):
for own_grouping, other_grouping in zip_longest(
self.transition_groups, other.transition_groups
):
if own_grouping != other_grouping:
return False
return True
raise NotImplementedError(
f"Cannot compare {self.__class__.__name__} with "
f" {other.__class__.__name__}"
)
def _repr_pretty_(self, p: "PrettyPrinter", cycle: bool) -> None:
class_name = type(self).__name__
if cycle:
p.text(f"{class_name}(...)")
else:
with p.group(indent=2, open=f"{class_name}("):
p.breakable()
p.text("transition_groups=")
with p.group(indent=2, open="("):
for transition_grouping in self.transition_groups:
p.breakable()
p.pretty(transition_grouping)
p.text(",")
p.breakable()
p.text("),")
p.breakable()
p.text("formalism=")
p.pretty(self.formalism)
p.text(",")
p.breakable()
p.text(")")
[docs] def get_intermediate_particles(self) -> ParticleCollection:
"""Extract the names of the intermediate state particles."""
return ParticleCollection(
set().union(
*[
grouping.get_intermediate_particles()
for grouping in self.transition_groups
]
)
)
[docs] @staticmethod
def from_graphs(
graphs: Iterable[StateTransitionGraph[ParticleWithSpin]],
formalism: str,
) -> "ReactionInfo":
transition_mapping: DefaultDict[
Topology, List[StateTransition]
] = defaultdict(list)
for graph in graphs:
transition_mapping[graph.topology].append(
StateTransition.from_graph(graph)
)
transition_groups = tuple(
StateTransitionCollection(transitions)
for transitions in transition_mapping.values()
)
return ReactionInfo(transition_groups, formalism)
[docs] def to_graphs(self) -> List[StateTransitionGraph[ParticleWithSpin]]:
graphs: List[StateTransitionGraph[ParticleWithSpin]] = []
for grouping in self.transition_groups:
graphs.extend(grouping.to_graphs())
return graphs
