Coverage for python/lsst/daf/butler/core/dimensions/graph.py : 20%

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1# This file is part of daf_butler.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <http://www.gnu.org/licenses/>.
22from __future__ import annotations
24__all__ = ["DimensionGraph"]
26import itertools
27from typing import (
28 Any,
29 Dict,
30 Iterable,
31 Iterator,
32 KeysView,
33 Optional,
34 Set,
35 Tuple,
36 TYPE_CHECKING,
37 Union,
38)
40from ..named import NamedValueSet
41from ..utils import immutable
43if TYPE_CHECKING: # Imports needed only for type annotations; may be circular. 43 ↛ 44line 43 didn't jump to line 44, because the condition on line 43 was never true
44 from .universe import DimensionUniverse
45 from .elements import DimensionElement, Dimension
48@immutable
49class DimensionGraph:
50 """An immutable, dependency-complete collection of dimensions.
52 `DimensionGraph` behaves in many respects like a set of `Dimension`
53 instances that maintains several special subsets and supersets of
54 related `DimensionElement` instances. It does not fully implement the
55 `collections.abc.Set` interface, as its automatic expansion of dependencies
56 would make set difference and XOR operations behave surprisingly.
58 It also provides dict-like lookup of `DimensionElement` instances from
59 their names.
61 Parameters
62 ----------
63 universe : `DimensionUniverse`
64 The special graph of all known dimensions of which this graph will be
65 a subset.
66 dimensions : iterable of `Dimension`, optional
67 An iterable of `Dimension` instances that must be included in the
68 graph. All (recursive) dependencies of these dimensions will also
69 be included. At most one of ``dimensions`` and ``names`` must be
70 provided.
71 names : iterable of `str`, optional
72 An iterable of the names of dimensiosn that must be included in the
73 graph. All (recursive) dependencies of these dimensions will also
74 be included. At most one of ``dimensions`` and ``names`` must be
75 provided.
76 conform : `bool`, optional
77 If `True` (default), expand to include dependencies. `False` should
78 only be used for callers that can guarantee that other arguments are
79 already correctly expanded, and is primarily for internal use.
81 Notes
82 -----
83 `DimensionGraph` should be used instead of other collections in any context
84 where a collection of dimensions is required and a `DimensionUniverse` is
85 available.
87 While `DimensionUniverse` inherits from `DimensionGraph`, it should
88 otherwise not be used as a base class.
89 """
91 def __new__(cls, universe: DimensionUniverse,
92 dimensions: Optional[Iterable[Dimension]] = None,
93 names: Optional[Iterable[str]] = None,
94 conform: bool = True) -> DimensionGraph:
95 conformedNames: Set[str]
96 if names is None:
97 if dimensions is None:
98 conformedNames = set()
99 else:
100 try:
101 # Optimize for NamedValueSet/NamedKeyDict, though that's
102 # not required.
103 conformedNames = set(dimensions.names) # type: ignore
104 except AttributeError:
105 conformedNames = set(d.name for d in dimensions)
106 else:
107 if dimensions is not None:
108 raise TypeError("Only one of 'dimensions' and 'names' may be provided.")
109 conformedNames = set(names)
110 if conform:
111 # Expand given dimensions to include all dependencies.
112 for name in tuple(conformedNames): # iterate over a temporary copy so we can modify the original
113 conformedNames.update(universe[name]._related.dependencies)
114 # Look in the cache of existing graphs, with the expanded set of names.
115 cacheKey = frozenset(conformedNames)
116 self = universe._cache.get(cacheKey, None)
117 if self is not None:
118 return self
119 # This is apparently a new graph. Create it, and add it to the cache.
120 self = super().__new__(cls)
121 universe._cache[cacheKey] = self
122 self.universe = universe
123 # Reorder dimensions by iterating over the universe (which is
124 # ordered already) and extracting the ones in the set.
125 self.dimensions = NamedValueSet(d for d in universe.dimensions if d.name in conformedNames)
126 # Make a set that includes both the dimensions and any
127 # DimensionElements whose dependencies are in self.dimensions.
128 self.elements = NamedValueSet(e for e in universe.elements
129 if e._shouldBeInGraph(self.dimensions.names))
130 self._finish()
131 return self
133 def _finish(self) -> None:
134 """Complete construction of the graph.
136 This is intended for internal use by `DimensionGraph` and
137 `DimensionUniverse` only.
138 """
139 # Freeze the sets the constructor is responsible for populating.
140 self.dimensions.freeze()
141 self.elements.freeze()
143 # Split dependencies up into "required" and "implied" subsets.
144 # Note that a dimension may be required in one graph and implied in
145 # another.
146 self.required = NamedValueSet()
147 self.implied = NamedValueSet()
148 for i1, dim1 in enumerate(self.dimensions):
149 for i2, dim2 in enumerate(self.dimensions):
150 if dim1.name in dim2._related.implied:
151 self.implied.add(dim1)
152 break
153 else:
154 # If no other dimension implies dim1, it's required.
155 self.required.add(dim1)
156 self.required.freeze()
157 self.implied.freeze()
159 # Compute sets of spatial and temporal elements.
160 # This contain the values of the `.spatial` and `.temporal` attributes
161 # of all elements, unless those attributes are not in the graph.
162 # In that case, the element whose attribute is not in the graph is
163 # added instead. This ensures that these sets contain the
164 # most-specific spatial and temporal elements, not the summary elements
165 # that aggregate them, unless the summaries are all that we have.
166 self.spatial = NamedValueSet()
167 self.temporal = NamedValueSet()
168 for element in self.elements:
169 if element.spatial is not None:
170 if element.spatial in self.elements:
171 self.spatial.add(element.spatial)
172 else:
173 self.spatial.add(element)
174 if element.temporal is not None:
175 if element.temporal in self.elements:
176 self.temporal.add(element.temporal)
177 else:
178 self.temporal.add(element)
179 self.spatial.freeze()
180 self.temporal.freeze()
182 # Build mappings from dimension to index; this is really for
183 # DataCoordinate, but we put it in DimensionGraph because many
184 # (many!) DataCoordinates will share the same DimensionGraph, and
185 # we want them to be lightweight. The order here is what's convenient
186 # for DataCoordinate: all required dimensions before all implied
187 # dimensions.
188 self._dataCoordinateIndices: Dict[str, int] = {
189 name: i for i, name in enumerate(itertools.chain(self.required.names, self.implied.names))
190 }
191 # Same for element to index. These are used for topological-sort
192 # comparison operators in DimensionElement itself.
193 self._elementIndices: Dict[str, int] = {
194 name: i for i, name in enumerate(self.elements.names)
195 }
196 # Same for dimension to index, sorted topologically across required
197 # and implied. This is used for encode/decode.
198 self._dimensionIndices: Dict[str, int] = {
199 name: i for i, name in enumerate(self.dimensions.names)
200 }
202 def __getnewargs__(self) -> tuple:
203 return (self.universe, None, tuple(self.dimensions.names), False)
205 @property
206 def names(self) -> KeysView[str]:
207 """A set of the names of all dimensions in the graph (`KeysView`).
208 """
209 return self.dimensions.names
211 def __iter__(self) -> Iterator[Dimension]:
212 """Iterate over all dimensions in the graph (and true `Dimension`
213 instances only).
214 """
215 return iter(self.dimensions)
217 def __len__(self) -> int:
218 """Return the number of dimensions in the graph (and true `Dimension`
219 instances only).
220 """
221 return len(self.dimensions)
223 def __contains__(self, element: Union[str, DimensionElement]) -> bool:
224 """Return `True` if the given element or element name is in the graph.
226 This test covers all `DimensionElement` instances in ``self.elements``,
227 not just true `Dimension` instances).
228 """
229 return element in self.elements
231 def __getitem__(self, name: str) -> DimensionElement:
232 """Return the element with the given name.
234 This lookup covers all `DimensionElement` instances in
235 ``self.elements``, not just true `Dimension` instances).
236 """
237 return self.elements[name]
239 def get(self, name: str, default: Any = None) -> DimensionElement:
240 """Return the element with the given name.
242 This lookup covers all `DimensionElement` instances in
243 ``self.elements``, not just true `Dimension` instances).
244 """
245 return self.elements.get(name, default)
247 def __str__(self) -> str:
248 return str(self.dimensions)
250 def __repr__(self) -> str:
251 return f"DimensionGraph({str(self)})"
253 @classmethod
254 def decode(cls, encoded: bytes, *, universe: DimensionUniverse) -> DimensionGraph:
255 """Construct a `DimensionGraph` from its encoded representation.
257 Parameters
258 ----------
259 encoded : `bytes`
260 Byte string produced by `DimensionGraph.encode`.
261 universe : `DimensionUniverse`
262 Universe the new graph is a part of. Must have the same dimensions
263 as the original universe.
265 Returns
266 -------
267 graph : `DimensionGraph`
268 A new (or possibly cached) `DimensionGraph` instance matching the
269 given encoding.
270 """
271 dimensions = []
272 mask = int.from_bytes(encoded, "big")
273 for dimension in universe.dimensions:
274 index = universe._dimensionIndices[dimension.name]
275 if mask & (1 << index):
276 dimensions.append(dimension)
277 return cls(universe, dimensions=dimensions, conform=False)
279 def encode(self) -> bytes:
280 """Encode a `DimensionGraph` into a byte string.
282 Returns
283 -------
284 encoded : `bytes`
285 Encoded representation of the graph. Length is guaranteed to be
286 equal to `DimensionUniverse.getEncodeLength`.
287 """
288 mask = 0
289 for dimension in self.dimensions:
290 index = self.universe._dimensionIndices[dimension.name]
291 mask |= (1 << index)
292 return mask.to_bytes(self.universe.getEncodeLength(), byteorder="big")
294 def isdisjoint(self, other: DimensionGraph) -> bool:
295 """Test whether the intersection of two graphs is empty.
297 Returns `True` if either operand is the empty.
298 """
299 return self.dimensions.isdisjoint(other.dimensions)
301 def issubset(self, other: DimensionGraph) -> bool:
302 """Test whether all dimensions in ``self`` are also in ``other``.
304 Returns `True` if ``self`` is empty.
305 """
306 return self.dimensions.issubset(other.dimensions)
308 def issuperset(self, other: DimensionGraph) -> bool:
309 """Test whether all dimensions in ``other`` are also in ``self``.
311 Returns `True` if ``other`` is empty.
312 """
313 return self.dimensions.issuperset(other.dimensions)
315 def __eq__(self, other: Any) -> bool:
316 """Test whether ``self`` and ``other`` have exactly the same dimensions
317 and elements.
318 """
319 if isinstance(other, DimensionGraph):
320 return self.dimensions == other.dimensions
321 else:
322 return False
324 def __hash__(self) -> int:
325 return hash(tuple(self.dimensions.names))
327 def __le__(self, other: DimensionGraph) -> bool:
328 """Test whether ``self`` is a subset of ``other``.
329 """
330 return self.dimensions <= other.dimensions
332 def __ge__(self, other: DimensionGraph) -> bool:
333 """Test whether ``self`` is a superset of ``other``.
334 """
335 return self.dimensions >= other.dimensions
337 def __lt__(self, other: DimensionGraph) -> bool:
338 """Test whether ``self`` is a strict subset of ``other``.
339 """
340 return self.dimensions < other.dimensions
342 def __gt__(self, other: DimensionGraph) -> bool:
343 """Test whether ``self`` is a strict superset of ``other``.
344 """
345 return self.dimensions > other.dimensions
347 def union(self, *others: DimensionGraph) -> DimensionGraph:
348 """Construct a new graph containing all dimensions in any of the
349 operands.
351 The elements of the returned graph may exceed the naive union of
352 their elements, as some `DimensionElement` instances are included
353 in graphs whenever multiple dimensions are present, and those
354 dependency dimensions could have been provided by different operands.
355 """
356 names = set(self.names).union(*[other.names for other in others])
357 return DimensionGraph(self.universe, names=names)
359 def intersection(self, *others: DimensionGraph) -> DimensionGraph:
360 """Construct a new graph containing only dimensions in all of the
361 operands.
362 """
363 names = set(self.names).intersection(*[other.names for other in others])
364 return DimensionGraph(self.universe, names=names)
366 def __or__(self, other: DimensionGraph) -> DimensionGraph:
367 """Construct a new graph containing all dimensions in any of the
368 operands.
370 See `union`.
371 """
372 return self.union(other)
374 def __and__(self, other: DimensionGraph) -> DimensionGraph:
375 """Construct a new graph containing only dimensions in all of the
376 operands.
377 """
378 return self.intersection(other)
380 @property
381 def primaryKeyTraversalOrder(self) -> Tuple[DimensionElement, ...]:
382 """Return a tuple of all elements in an order allows records to be
383 found given their primary keys, starting from only the primary keys of
384 required dimensions (`tuple` [ `DimensionRecord` ]).
386 Unlike the table definition/topological order (which is what
387 DimensionUniverse.sorted gives you), when dimension A implies
388 dimension B, dimension A appears first.
389 """
390 order = getattr(self, "_primaryKeyTraversalOrder", None)
391 if order is None:
392 done: Set[str] = set()
393 order = []
395 def addToOrder(element: DimensionElement) -> None:
396 if element.name in done:
397 return
398 predecessors = set(element.required.names)
399 predecessors.discard(element.name)
400 if not done.issuperset(predecessors):
401 return
402 order.append(element)
403 done.add(element.name)
404 for other in element.implied:
405 addToOrder(other)
407 while not done.issuperset(self.required):
408 for dimension in self.required:
409 addToOrder(dimension)
411 order.extend(element for element in self.elements if element.name not in done)
412 order = tuple(order)
413 self._primaryKeyTraversalOrder = order
414 return order
416 # Class attributes below are shadowed by instance attributes, and are
417 # present just to hold the docstrings for those instance attributes.
419 universe: DimensionUniverse
420 """The set of all known dimensions, of which this graph is a subset
421 (`DimensionUniverse`).
422 """
424 dimensions: NamedValueSet[Dimension]
425 """A true `~collections.abc.Set` of all true `Dimension` instances in the
426 graph (`NamedValueSet` of `Dimension`).
428 This is the set used for iteration, ``len()``, and most set-like operations
429 on `DimensionGraph` itself.
430 """
432 elements: NamedValueSet[DimensionElement]
433 """A true `~collections.abc.Set` of all `DimensionElement` instances in the
434 graph; a superset of `dimensions` (`NamedValueSet` of `DimensionElement`).
436 This is the set used for dict-like lookups, including the ``in`` operator,
437 on `DimensionGraph` itself.
438 """
440 required: NamedValueSet[Dimension]
441 """The subset of `dimensions` whose elments must be directly identified via
442 their primary keys in a data ID in order to identify the rest of the
443 elements in the graph (`NamedValueSet` of `Dimension`).
444 """
446 implied: NamedValueSet[Dimension]
447 """The subset of `dimensions` whose elements need not be directly
448 identified via their primary keys in a data ID (`NamedValueSet` of
449 `Dimension`).
450 """
452 spatial: NamedValueSet[DimensionElement]
453 """Elements that are associated with independent spatial regions
454 (`NamedValueSet` of `DimensionElement`).
455 """
457 temporal: NamedValueSet[DimensionElement]
458 """Elements that are associated with independent spatial regions
459 (`NamedValueSet` of `DimensionElement`).
460 """