omop.ObservationPeriod¶
- class omop.ObservationPeriod¶
Bases:
Record
,CanCurate
,TracksRun
,TracksUpdates
Records which define spans of time during which two conditions are expected to hold.
Clinical Events that happened to the Person are recorded in the Event tables, and
absense of records indicate such Events did not occur during this span of time.
Simple fields¶
- observation_period_id: int¶
A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.
- observation_period_start_date: datetime¶
A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.
- observation_period_end_date: datetime¶
A wrapper for a deferred-loading field. When the value is read from this object the first time, the query is executed.
- created_at: datetime¶
Time of creation of record.
- updated_at: datetime¶
Time of last update to record.
Relational fields¶
- created_by: User¶
Creator of record.
- run: Run | None¶
Last run that created or updated the record.
- person: Person¶
Accessor to the related object on the forward side of a many-to-one or one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example:
class Child(Model): parent = ForeignKey(Parent, related_name='children')
Child.parent
is aForwardManyToOneDescriptor
instance.
- period_type_concept: Concept¶
Accessor to the related object on the forward side of a many-to-one or one-to-one (via ForwardOneToOneDescriptor subclass) relation.
In the example:
class Child(Model): parent = ForeignKey(Parent, related_name='children')
Child.parent
is aForwardManyToOneDescriptor
instance.
Class methods¶
- classmethod df(include=None, features=False, limit=100)¶
Convert to
pd.DataFrame
.By default, shows all direct fields, except
updated_at
.Use arguments
include
orfeature
to include other data.- Parameters:
include (
str
|list
[str
] |None
, default:None
) – Related fields to include as columns. Takes strings of form"ulabels__name"
,"cell_types__name"
, etc. or a list of such strings.features (
bool
|list
[str
], default:False
) – IfTrue
, map all features of theFeature
registry onto the resultingDataFrame
. Only available forArtifact
.limit (
int
, default:100
) – Maximum number of rows to display from a Pandas DataFrame. Defaults to 100 to reduce database load.
- Return type:
DataFrame
Examples
Include the name of the creator in the
DataFrame
:>>> ln.ULabel.df(include="created_by__name"])
Include display of features for
Artifact
:>>> df = ln.Artifact.df(features=True) >>> ln.view(df) # visualize with type annotations
Only include select features:
>>> df = ln.Artifact.df(features=["cell_type_by_expert", "cell_type_by_model"])
- classmethod filter(*queries, **expressions)¶
Query records.
- Parameters:
queries – One or multiple
Q
objects.expressions – Fields and values passed as Django query expressions.
- Return type:
QuerySet
- Returns:
A
QuerySet
.
See also
Guide: Query & search registries
Django documentation: Queries
Examples
>>> ln.ULabel(name="my label").save() >>> ln.ULabel.filter(name__startswith="my").df()
- classmethod from_values(values, field=None, create=False, organism=None, source=None, mute=False)¶
Bulk create validated records by parsing values for an identifier such as a name or an id).
- Parameters:
values (
List
[str
] |Series
|array
) – A list of values for an identifier, e.g.["name1", "name2"]
.field (
str
|DeferredAttribute
|None
, default:None
) – ARecord
field to look up, e.g.,bt.CellMarker.name
.create (
bool
, default:False
) – Whether to create records if they don’t exist.organism (
Record
|str
|None
, default:None
) – Abionty.Organism
name or record.source (
Record
|None
, default:None
) – Abionty.Source
record to validate against to create records for.mute (
bool
, default:False
) – Whether to mute logging.
- Return type:
- Returns:
A list of validated records. For bionty registries. Also returns knowledge-coupled records.
Notes
For more info, see tutorial: Manage biological registries.
Examples
Bulk create from non-validated values will log warnings & returns empty list:
>>> ulabels = ln.ULabel.from_values(["benchmark", "prediction", "test"], field="name") >>> assert len(ulabels) == 0
Bulk create records from validated values returns the corresponding existing records:
>>> ln.save([ln.ULabel(name=name) for name in ["benchmark", "prediction", "test"]]) >>> ulabels = ln.ULabel.from_values(["benchmark", "prediction", "test"], field="name") >>> assert len(ulabels) == 3
Bulk create records from public reference:
>>> import bionty as bt >>> records = bt.CellType.from_values(["T cell", "B cell"], field="name") >>> records
- classmethod get(idlike=None, **expressions)¶
Get a single record.
- Parameters:
idlike (
int
|str
|None
, default:None
) – Either a uid stub, uid or an integer id.expressions – Fields and values passed as Django query expressions.
- Return type:
- Returns:
A record.
- Raises:
lamindb.core.exceptions.DoesNotExist – In case no matching record is found.
See also
Guide: Query & search registries
Django documentation: Queries
Examples
>>> ulabel = ln.ULabel.get("FvtpPJLJ") >>> ulabel = ln.ULabel.get(name="my-label")
- classmethod inspect(values, field=None, *, mute=False, organism=None, source=None)¶
Inspect if values are mappable to a field.
Being mappable means that an exact match exists.
- Parameters:
values (
List
[str
] |Series
|array
) – Values that will be checked against the field.field (
str
|DeferredAttribute
|None
, default:None
) – The field of values. Examples are'ontology_id'
to map against the source ID or'name'
to map against the ontologies field names.mute (
bool
, default:False
) – Whether to mute logging.organism (
Record
|str
|None
, default:None
) – An Organism name or record.source (
Record
|None
, default:None
) – Abionty.Source
record that specifies the version to inspect against.
- Return type:
See also
Examples
>>> import bionty as bt >>> bt.settings.organism = "human" >>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol")) >>> gene_symbols = ["A1CF", "A1BG", "FANCD1", "FANCD20"] >>> result = bt.Gene.inspect(gene_symbols, field=bt.Gene.symbol) >>> result.validated ['A1CF', 'A1BG'] >>> result.non_validated ['FANCD1', 'FANCD20']
- classmethod lookup(field=None, return_field=None)¶
Return an auto-complete object for a field.
- Parameters:
field (
str
|DeferredAttribute
|None
, default:None
) – The field to look up the values for. Defaults to first string field.return_field (
str
|DeferredAttribute
|None
, default:None
) – The field to return. IfNone
, returns the whole record.
- Return type:
NamedTuple
- Returns:
A
NamedTuple
of lookup information of the field values with a dictionary converter.
See also
Examples
>>> import bionty as bt >>> bt.settings.organism = "human" >>> bt.Gene.from_source(symbol="ADGB-DT").save() >>> lookup = bt.Gene.lookup() >>> lookup.adgb_dt >>> lookup_dict = lookup.dict() >>> lookup_dict['ADGB-DT'] >>> lookup_by_ensembl_id = bt.Gene.lookup(field="ensembl_gene_id") >>> genes.ensg00000002745 >>> lookup_return_symbols = bt.Gene.lookup(field="ensembl_gene_id", return_field="symbol")
- classmethod search(string, *, field=None, limit=20, case_sensitive=False)¶
Search.
- Parameters:
string (
str
) – The input string to match against the field ontology values.field (
str
|DeferredAttribute
|None
, default:None
) – The field or fields to search. Search all string fields by default.limit (
int
|None
, default:20
) – Maximum amount of top results to return.case_sensitive (
bool
, default:False
) – Whether the match is case sensitive.
- Return type:
QuerySet
- Returns:
A sorted
DataFrame
of search results with a score in columnscore
. Ifreturn_queryset
isTrue
.QuerySet
.
Examples
>>> ulabels = ln.ULabel.from_values(["ULabel1", "ULabel2", "ULabel3"], field="name") >>> ln.save(ulabels) >>> ln.ULabel.search("ULabel2")
- classmethod standardize(values, field=None, *, return_field=None, return_mapper=False, case_sensitive=False, mute=False, public_aware=True, keep='first', synonyms_field='synonyms', organism=None, source=None)¶
Maps input synonyms to standardized names.
- Parameters:
values (
List
[str
] |Series
|array
) – Identifiers that will be standardized.field (
str
|DeferredAttribute
|None
, default:None
) – The field representing the standardized names.return_field (
str
|None
, default:None
) – The field to return. Defaults to field.return_mapper (
bool
, default:False
) – IfTrue
, returns{input_value: standardized_name}
.case_sensitive (
bool
, default:False
) – Whether the mapping is case sensitive.mute (
bool
, default:False
) – Whether to mute logging.public_aware (
bool
, default:True
) – Whether to standardize from Bionty reference. Defaults toTrue
for Bionty registries.keep (
Literal
['first'
,'last'
,False
], default:'first'
) –- When a synonym maps to multiple names, determines which duplicates to mark as
pd.DataFrame.duplicated
: "first"
: returns the first mapped standardized name"last"
: returns the last mapped standardized nameFalse
: returns all mapped standardized name.
When
keep
isFalse
, the returned list of standardized names will contain nested lists in case of duplicates.When a field is converted into return_field, keep marks which matches to keep when multiple return_field values map to the same field value.
- When a synonym maps to multiple names, determines which duplicates to mark as
synonyms_field (
str
, default:'synonyms'
) – A field containing the concatenated synonyms.organism (
Record
|str
|None
, default:None
) – An Organism name or record.source (
Record
|None
, default:None
) – Abionty.Source
record that specifies the version to validate against.
- Return type:
list
[str
] |dict
[str
,str
]- Returns:
If
return_mapper
isFalse
– a list of standardized names. Otherwise, a dictionary of mapped values with mappable synonyms as keys and standardized names as values.
See also
add_synonym()
Add synonyms.
remove_synonym()
Remove synonyms.
Examples
>>> import bionty as bt >>> bt.settings.organism = "human" >>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol")) >>> gene_synonyms = ["A1CF", "A1BG", "FANCD1", "FANCD20"] >>> standardized_names = bt.Gene.standardize(gene_synonyms) >>> standardized_names ['A1CF', 'A1BG', 'BRCA2', 'FANCD20']
- classmethod using(instance)¶
Use a non-default LaminDB instance.
- Parameters:
instance (
str
|None
) – An instance identifier of form “account_handle/instance_name”.- Return type:
QuerySet
Examples
>>> ln.ULabel.using("account_handle/instance_name").search("ULabel7", field="name") uid score name ULabel7 g7Hk9b2v 100.0 ULabel5 t4Jm6s0q 75.0 ULabel6 r2Xw8p1z 75.0
- classmethod validate(values, field=None, *, mute=False, organism=None, source=None)¶
Validate values against existing values of a string field.
Note this is strict validation, only asserts exact matches.
- Parameters:
values (
List
[str
] |Series
|array
) – Values that will be validated against the field.field (
str
|DeferredAttribute
|None
, default:None
) – The field of values. Examples are'ontology_id'
to map against the source ID or'name'
to map against the ontologies field names.mute (
bool
, default:False
) – Whether to mute logging.organism (
Record
|str
|None
, default:None
) – An Organism name or record.source (
Record
|None
, default:None
) – Abionty.Source
record that specifies the version to validate against.
- Return type:
ndarray
- Returns:
A vector of booleans indicating if an element is validated.
See also
Examples
>>> import bionty as bt >>> bt.settings.organism = "human" >>> ln.save(bt.Gene.from_values(["A1CF", "A1BG", "BRCA2"], field="symbol")) >>> gene_symbols = ["A1CF", "A1BG", "FANCD1", "FANCD20"] >>> bt.Gene.validate(gene_symbols, field=bt.Gene.symbol) array([ True, True, False, False])
Methods¶
- add_synonym(synonym, force=False, save=None)¶
Add synonyms to a record.
- Parameters:
synonym (
str
|List
[str
] |Series
|array
) – The synonyms to add to the record.force (
bool
, default:False
) – Whether to add synonyms even if they are already synonyms of other records.save (
bool
|None
, default:None
) – Whether to save the record to the database.
See also
remove_synonym()
Remove synonyms.
Examples
>>> import bionty as bt >>> bt.CellType.from_source(name="T cell").save() >>> lookup = bt.CellType.lookup() >>> record = lookup.t_cell >>> record.synonyms 'T-cell|T lymphocyte|T-lymphocyte' >>> record.add_synonym("T cells") >>> record.synonyms 'T cells|T-cell|T-lymphocyte|T lymphocyte'
- delete()¶
Delete.
- Return type:
None
- remove_synonym(synonym)¶
Remove synonyms from a record.
- Parameters:
synonym (
str
|List
[str
] |Series
|array
) – The synonym values to remove.
See also
add_synonym()
Add synonyms
Examples
>>> import bionty as bt >>> bt.CellType.from_source(name="T cell").save() >>> lookup = bt.CellType.lookup() >>> record = lookup.t_cell >>> record.synonyms 'T-cell|T lymphocyte|T-lymphocyte' >>> record.remove_synonym("T-cell") 'T lymphocyte|T-lymphocyte'
- set_abbr(value)¶
Set value for abbr field and add to synonyms.
- Parameters:
value (
str
) – A value for an abbreviation.
See also
Examples
>>> import bionty as bt >>> bt.ExperimentalFactor.from_source(name="single-cell RNA sequencing").save() >>> scrna = bt.ExperimentalFactor.get(name="single-cell RNA sequencing") >>> scrna.abbr None >>> scrna.synonyms 'single-cell RNA-seq|single-cell transcriptome sequencing|scRNA-seq|single cell RNA sequencing' >>> scrna.set_abbr("scRNA") >>> scrna.abbr 'scRNA' >>> scrna.synonyms 'scRNA|single-cell RNA-seq|single cell RNA sequencing|single-cell transcriptome sequencing|scRNA-seq' >>> scrna.save()