DataCoordinate

class lsst.daf.butler.DataCoordinate

Bases: lsst.daf.butler.NamedKeyMapping

Data ID dictionary.

An immutable data ID dictionary that guarantees that its key-value pairs identify at least all required dimensions in a DimensionGraph.

DataCoordinate itself is an ABC, but provides staticmethod factory functions for private concrete implementations that should be sufficient for most purposes. standardize is the most flexible and safe of these; the others (makeEmpty, fromRequiredValues, and fromFullValues) are more specialized and perform little or no checking of inputs.

Notes

Like any data ID class, DataCoordinate behaves like a dictionary, but with some subtleties:

• Both Dimension instances and str names thereof may be used as keys in lookup operations, but iteration (and keys) will yield Dimension instances. The names property can be used to obtain the corresponding str names.
• Lookups for implied dimensions (those in self.graph.implied) are supported if and only if hasFull returns True, and are never included in iteration or keys. The full property may be used to obtain a mapping whose keys do include implied dimensions.
• Equality comparison with other mappings is supported, but it always considers only required dimensions (as well as requiring both operands to identify the same dimensions). This is not quite consistent with the way mappings usually work - normally differing keys imply unequal mappings - but it makes sense in this context because data IDs with the same values for required dimensions but different values for implied dimensions represent a serious problem with the data that DataCoordinate cannot generally recognize on its own, and a data ID that knows implied dimension values should still be able to compare as equal to one that does not. This is of course not the way comparisons between simple dict data IDs work, and hence using a DataCoordinate instance for at least one operand in any data ID comparison is strongly recommended.

Attributes Summary

full	Return mapping for all dimensions in self.graph.
graph	Dimensions identified by this data ID (DimensionGraph).
names	Names of the required dimensions identified by this data ID.
records	Return the records.
region	Spatial region associated with this data ID.
timespan	Temporal interval associated with this data ID.
universe	Universe that defines all known compatible dimensions.

Methods Summary

byName()	Return a Mapping with names as keys and the self values.
expanded(records, …)	Return a DataCoordinate that holds the given records.
fromFullValues(graph, values, str, None], …])	Construct a DataCoordinate from all dimension values.
fromRequiredValues(graph, values, str, …)	Construct a DataCoordinate from required dimension values.
from_json(json_str, universe, registry)	Convert from JSON to a pydantic model.
from_simple(simple, universe, registry)	Construct a new object from the simplified form.
get(k[,d])
hasFull()	Whether this data ID contains implied and required values.
hasRecords()	Whether this data ID contains records.
items()
keys()
makeEmpty(universe)	Return an empty DataCoordinate.
pack(name, *, returnMaxBits)	Pack this data ID into an integer.
standardize(mapping, DataIdValue]] = None, …)	Standardize the supplied dataId.
subset(graph)	Return a DataCoordinate whose graph is a subset of self.graph.
to_json(minimal)	Convert this class to JSON assuming that the to_simple() returns a pydantic model.
to_simple(minimal)	Convert this class to a simple python type.
union(other)	Combine two data IDs.
values()

Attributes Documentation

full

Return mapping for all dimensions in self.graph.

The mapping includes key-value pairs for all dimensions in self.graph, including implied (NamedKeyMapping).

Accessing this attribute if hasFull returns False is a logic error that may raise an exception of unspecified type either immediately or when implied keys are accessed via the returned mapping, depending on the implementation and whether assertions are enabled.

graph

Dimensions identified by this data ID (DimensionGraph).

Note that values are only required to be present for dimensions in self.graph.required; all others may be retrieved (from a Registry) given these.

names

Names of the required dimensions identified by this data ID.

They are returned in the same order as keys (collections.abc.Set [ str ]).

records

Return the records.

Returns a mapping that contains DimensionRecord objects for all elements identified by this data ID (NamedKeyMapping).

The values of this mapping may be None if and only if there is no record for that element with these dimensions in the database (which means some foreign key field must have a NULL value).

Accessing this attribute if hasRecords returns False is a logic error that may raise an exception of unspecified type either immediately or when the returned mapping is used, depending on the implementation and whether assertions are enabled.

region

Spatial region associated with this data ID.

(lsst.sphgeom.Region or None).

This is None if and only if self.graph.spatial is empty.

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

timespan

Temporal interval associated with this data ID.

(Timespan or None).

This is None if and only if self.graph.timespan is empty.

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

universe

Universe that defines all known compatible dimensions.

The univers will be compatible with this coordinate (DimensionUniverse).

Methods Documentation

byName() → Dict[str, V_co]

Return a Mapping with names as keys and the self values.

Returns:

dictionary : dict

A dictionary with the same values (and iteration order) as self, with str names as keys. This is always a new object, not a view.

expanded(records: Union[lsst.daf.butler.core.named.NamedKeyMapping[lsst.daf.butler.core.dimensions._elements.DimensionElement, Optional[lsst.daf.butler.core.dimensions._records.DimensionRecord, None]], Mapping[str, Optional[lsst.daf.butler.core.dimensions._records.DimensionRecord, None]]]) → lsst.daf.butler.core.dimensions._coordinate.DataCoordinate

Return a DataCoordinate that holds the given records.

Guarantees that hasRecords returns True.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use Registry.expandDataId instead.

Parameters:

records : Mapping [ str, DimensionRecord or None ]

A NamedKeyMapping with DimensionElement keys or a regular Mapping with str (DimensionElement name) keys and DimensionRecord values. Keys must cover all elements in self.graph.elements. Values may be None, but only to reflect actual NULL values in the database, not just records that have not been fetched.

static fromFullValues(graph: lsst.daf.butler.core.dimensions._graph.DimensionGraph, values: Tuple[Union[int, str, None], ...]) → lsst.daf.butler.core.dimensions._coordinate.DataCoordinate

Construct a DataCoordinate from all dimension values.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use standardize instead.

Parameters:

graph : DimensionGraph

Dimensions this data ID will identify.

values : tuple [ int or str ]

Tuple of primary key values corresponding to itertools.chain(graph.required, graph.implied), in that order. Note that this is _not_ the same order as graph.dimensions, though these contain the same elements.

Returns:

dataId : DataCoordinate

A data ID object that identifies the given dimensions. dataId.hasFull() will return True if and only if graph.implied is empty, and dataId.hasRecords() will never return True.

static fromRequiredValues(graph: lsst.daf.butler.core.dimensions._graph.DimensionGraph, values: Tuple[Union[int, str, None], ...]) → lsst.daf.butler.core.dimensions._coordinate.DataCoordinate

Construct a DataCoordinate from required dimension values.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use standardize instead.

Parameters:

graph : DimensionGraph

Dimensions this data ID will identify.

values : tuple [ int or str ]

Tuple of primary key values corresponding to graph.required, in that order.

Returns:

dataId : DataCoordinate

A data ID object that identifies the given dimensions. dataId.hasFull() will return True if and only if graph.implied is empty, and dataId.hasRecords() will never return True.

classmethod from_json(json_str: str, universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → SupportsSimple

Convert from JSON to a pydantic model.

classmethod from_simple(simple: SerializedDataCoordinate, universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → DataCoordinate

Construct a new object from the simplified form.

The data is assumed to be of the form returned from the to_simple method.

Parameters:

simple : dict of [str, Any]

The dict returned by to_simple().

universe : DimensionUniverse

The special graph of all known dimensions.

registry : lsst.daf.butler.Registry, optional

Registry from which a universe can be extracted. Can be None if universe is provided explicitly.

Returns:

dataId : DataCoordinate

Newly-constructed object.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.

hasFull() → bool

Whether this data ID contains implied and required values.

Returns:

state : bool

If True, __getitem__, get, and __contains__ (but not keys!) will act as though the mapping includes key-value pairs for implied dimensions, and the full property may be used. If False, these operations only include key-value pairs for required dimensions, and accessing full is an error. Always True if there are no implied dimensions.

hasRecords() → bool

Whether this data ID contains records.

These are the records for all of the dimension elements it identifies.

Returns:

state : bool

If True, the following attributes may be accessed:

• records
• region
• timespan
• pack

If False, accessing any of these is considered a logic error.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

static makeEmpty(universe: DimensionUniverse) → DataCoordinate

Return an empty DataCoordinate.

It identifies the null set of dimensions.

Parameters:

universe : DimensionUniverse

Universe to which this null dimension set belongs.

Returns:

dataId : DataCoordinate

A data ID object that identifies no dimensions. hasFull and hasRecords are guaranteed to return True, because both full and records are just empty mappings.

pack(name: str, *, returnMaxBits: bool = False) → Union[Tuple[int, int], int]

Pack this data ID into an integer.

Parameters:

name : str

Name of the DimensionPacker algorithm (as defined in the dimension configuration).

returnMaxBits : bool, optional

If True (False is default), return the maximum number of nonzero bits in the returned integer across all data IDs.

Returns:

packed : int

Integer ID. This ID is unique only across data IDs that have the same values for the packer’s “fixed” dimensions.

maxBits : int, optional

Maximum number of nonzero bits in packed. Not returned unless returnMaxBits is True.

Notes

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

static standardize(mapping: Optional[NameLookupMapping[Dimension, DataIdValue]] = None, *, graph: Optional[DimensionGraph] = None, universe: Optional[DimensionUniverse] = None, defaults: Optional[DataCoordinate] = None, **kwargs) → DataCoordinate

Standardize the supplied dataId.

Adapts an arbitrary mapping and/or additional arguments into a true DataCoordinate, or augment an existing one.

Parameters:

mapping : Mapping, optional

An informal data ID that maps dimensions or dimension names to their primary key values (may also be a true DataCoordinate).

graph : DimensionGraph

The dimensions to be identified by the new DataCoordinate. If not provided, will be inferred from the keys of mapping and **kwargs, and universe must be provided unless mapping is already a DataCoordinate.

universe : DimensionUniverse

All known dimensions and their relationships; used to expand and validate dependencies when graph is not provided.

defaults : DataCoordinate, optional

Default dimension key-value pairs to use when needed. These are never used to infer graph, and are ignored if a different value is provided for the same key in mapping or **kwargs`.

**kwargs

Additional keyword arguments are treated like additional key-value pairs in mapping.

Returns:

coordinate : DataCoordinate

A validated DataCoordinate instance.

Raises:

TypeError

Raised if the set of optional arguments provided is not supported.

KeyError

Raised if a key-value pair for a required dimension is missing.

subset(graph: lsst.daf.butler.core.dimensions._graph.DimensionGraph) → lsst.daf.butler.core.dimensions._coordinate.DataCoordinate

Return a DataCoordinate whose graph is a subset of self.graph.

Parameters:

graph : DimensionGraph

The dimensions identified by the returned DataCoordinate.

Returns:

coordinate : DataCoordinate

A DataCoordinate instance that identifies only the given dimensions. May be self if graph == self.graph.

Raises:

KeyError

Raised if the primary key value for one or more required dimensions is unknown. This may happen if graph.issubset(self.graph) is False, or even if graph.issubset(self.graph) is True, if self.hasFull() is False and graph.required.issubset(self.graph.required) is False. As an example of the latter case, consider trying to go from a data ID with dimensions {instrument, physical_filter, band} to just {instrument, band}; band is implied by physical_filter and hence would have no value in the original data ID if self.hasFull() is False.

Notes

If hasFull and hasRecords return True on self, they will return True (respectively) on the returned DataCoordinate as well. The converse does not hold.

to_json(minimal: bool = False) → str

Convert this class to JSON assuming that the to_simple() returns a pydantic model.

to_simple(minimal: bool = False) → lsst.daf.butler.core.dimensions._coordinate.SerializedDataCoordinate

Convert this class to a simple python type.

This is suitable for serialization.

Parameters:

minimal : bool, optional

Use minimal serialization. If set the records will not be attached.

Returns:

simple : SerializedDataCoordinate

The object converted to simple form.

union(other: lsst.daf.butler.core.dimensions._coordinate.DataCoordinate) → lsst.daf.butler.core.dimensions._coordinate.DataCoordinate

Combine two data IDs.

Yields a new one that identifies all dimensions that either of them identify.

Parameters:

other : DataCoordinate

Data ID to combine with self.

Returns:

unioned : DataCoordinate

A DataCoordinate instance that satisfies unioned.graph == self.graph.union(other.graph). Will preserve hasFull and hasRecords whenever possible.

Notes

No checking for consistency is performed on values for keys that self and other have in common, and which value is included in the returned data ID is not specified.

values() → an object providing a view on D's values