Represent statespace metadata with dataclasses

pymc_extras/statespace/core/properties.py

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+from __future__ import annotations
+
+import warnings
+
+from collections.abc import Iterator
+from copy import deepcopy
+from dataclasses import dataclass, fields
+from typing import TYPE_CHECKING, Generic, Self, TypeVar
+
+from pymc_extras.statespace.core import PyMCStateSpace
+from pymc_extras.statespace.utils.constants import (
+    ALL_STATE_AUX_DIM,
+    ALL_STATE_DIM,
+    OBS_STATE_AUX_DIM,
+    OBS_STATE_DIM,
+    SHOCK_AUX_DIM,
+    SHOCK_DIM,
+)
+
+if TYPE_CHECKING:
+    from pymc_extras.statespace.models.structural.core import Component
+
+
+@dataclass(frozen=True)
+class Property:
+    def __str__(self) -> str:
+        return "\n".join(f"{f.name}: {getattr(self, f.name)}" for f in fields(self))
+
+
+T = TypeVar("T", bound=Property)
+
+
+@dataclass(frozen=True)
+class Info(Generic[T]):
+    items: tuple[T, ...]
+    key_field: str = "name"
+    _index: dict[str, T] | None = None
+
+    def __post_init__(self):
+        index = {}
+        missing_attr = []
+        for item in self.items:
+            if not hasattr(item, self.key_field):
+                missing_attr.append(item)
+                continue
+            key = getattr(item, self.key_field)
+            # if key in index:
+            #     raise ValueError(f"Duplicate {self.key_field} '{key}' detected.") # This needs to be possible for shared states
+            index[key] = item
+        if missing_attr:
+            raise AttributeError(f"Items missing attribute '{self.key_field}': {missing_attr}")
+        object.__setattr__(self, "_index", index)
+
+    def _key(self, item: T) -> str:
+        return getattr(item, self.key_field)
+
+    def get(self, key: str, default=None) -> T | None:
+        return self._index.get(key, default)
+
+    def __getitem__(self, key: str) -> T:
+        try:
+            return self._index[key]
+        except KeyError as e:
+            available = ", ".join(self._index.keys())
+            raise KeyError(f"No {self.key_field} '{key}'. Available: [{available}]") from e
+
+    def __contains__(self, key: object) -> bool:
+        return key in self._index
+
+    def __iter__(self) -> Iterator[T]:
+        return iter(self.items)
+
+    def __len__(self) -> int:
+        return len(self.items)
+
+    def __str__(self) -> str:
+        return f"{self.key_field}s: {list(self._index.keys())}"
+
+    def add(self, new_item: T):
+        return type(self)([*self.items, new_item])
+
+    def merge(self, other: Self, allow_duplicates: bool = False) -> Self:
+        if not isinstance(other, type(self)):
+            raise TypeError(f"Cannot merge {type(other).__name__} with {type(self).__name__}")
+
+        overlapping = set(self.names) & set(other.names)
+        if overlapping and not allow_duplicates:
+            raise ValueError(f"Duplicate names found: {overlapping}")
+
+        return type(self)(list(self.items) + list(other.items))
+
+    @property
+    def names(self) -> tuple[str, ...]:
+        return tuple(self._index.keys())
+
+    def copy(self) -> Info[T]:
+        return deepcopy(self)
+
+
+@dataclass(frozen=True)
+class Parameter(Property):
+    name: str
+    shape: tuple[int, ...]
+    dims: tuple[str, ...]
+    constraints: str | None = None
+
+
+@dataclass(frozen=True)
+class ParameterInfo(Info[Parameter]):
+    def __init__(self, parameters: list[Parameter]):
+        super().__init__(items=tuple(parameters), key_field="name")
+
+
+@dataclass(frozen=True)
+class Data(Property):
+    name: str
+    shape: tuple[int, ...]
+    dims: tuple[str, ...]
+    is_exogenous: bool
+
+
+@dataclass(frozen=True)
+class DataInfo(Info[Data]):
+    def __init__(self, data: list[Data]):
+        super().__init__(items=tuple(data), key_field="name")
+
+    @property
+    def needs_exogenous_data(self) -> bool:
+        return any(d.is_exogenous for d in self.items)
+
+    @property
+    def exogenous_names(self) -> tuple[str, ...]:
+        return tuple(d.name for d in self.items if d.is_exogenous)
+
+    def __str__(self) -> str:
+        return f"data: {[d.name for d in self.items]}\nneeds exogenous data: {self.needs_exogenous_data}"
+
+
+@dataclass(frozen=True)
+class Coord(Property):
+    dimension: str
+    labels: tuple[str, ...]
+
+
+@dataclass(frozen=True)
+class CoordInfo(Info[Coord]):
+    def __init__(self, coords: list[Coord]):
+        super().__init__(items=tuple(coords), key_field="dimension")
+
+    def __str__(self) -> str:
+        base = "coordinates:"
+        for coord in self.items:
+            coord_str = str(coord)
+            indented = "\n".join("  " + line for line in coord_str.splitlines())
+            base += "\n" + indented + "\n"
+        return base
+
+    @classmethod
+    def default_coords_from_model(
+        cls, model: PyMCStateSpace | Component
+    ) -> (
+        Self
+    ):  # TODO: Need to figure out how to include Component type was causing circular import issues
+        states = tuple(model.state_names)
+        obs_states = tuple(model.observed_states)
+        shocks = tuple(model.shock_names)
+
+        dim_to_labels = (
+            (ALL_STATE_DIM, states),
+            (ALL_STATE_AUX_DIM, states),
+            (OBS_STATE_DIM, obs_states),
+            (OBS_STATE_AUX_DIM, obs_states),
+            (SHOCK_DIM, shocks),
+            (SHOCK_AUX_DIM, shocks),
+        )
+
+        coords = [Coord(dimension=dim, labels=labels) for dim, labels in dim_to_labels]
+        return cls(coords)
+
+    def to_dict(self):
+        return {coord.dimension: coord.labels for coord in self.items if len(coord.labels) > 0}
+
+
+@dataclass(frozen=True)
+class State(Property):
+    name: str
+    observed: bool
+    shared: bool
+
+
+@dataclass(frozen=True)
+class StateInfo(Info[State]):
+    def __init__(self, states: list[State]):
+        super().__init__(items=tuple(states), key_field="name")
+
+    def __str__(self) -> str:
+        return (
+            f"states: {[s.name for s in self.items]}\nobserved: {[s.observed for s in self.items]}"
+        )
+
+    @property
+    def observed_states(self) -> tuple[State, ...]:  # Is this needed??
+        return tuple(s for s in self.items if s.observed)
+
+    @property
+    def observed_state_names(self) -> tuple[State, ...]:
+        return tuple(s.name for s in self.items if s.observed)
+
+    @property
+    def unobserved_state_names(self) -> tuple[State, ...]:
+        return tuple(s.name for s in self.items if not s.observed)
+
+    def merge(self, other: StateInfo, allow_duplicates: bool = False) -> StateInfo:
+        """Combine states from two StateInfo objects."""
+        if not isinstance(other, StateInfo):
+            raise TypeError(f"Cannot merge {type(other).__name__} with StateInfo")
+
+        overlapping = set(self.names) & set(other.names)
+        if overlapping and not allow_duplicates:
+            # This is necessary for shared states
+            warnings.warn(
+                f"Duplicate state names found: {overlapping}. Merge will ONLY retain unique states",
+                UserWarning,
+            )
+            return StateInfo(
+                states=list(self.items)
+                + [item for item in other.items if item.name not in overlapping]
+            )
+
+        return StateInfo(states=list(self.items) + list(other.items))
+
+
+@dataclass(frozen=True)
+class Shock(Property):
+    name: str
+
+
+@dataclass(frozen=True)
+class ShockInfo(Info[Shock]):
+    def __init__(self, shocks: list[Shock]):
+        super().__init__(items=tuple(shocks), key_field="name")