adam_to_metadata()

Convert an ADaM dataset template to a MetadataImport object.

Usage

adam_to_metadata(
    dataset,
    study_id=None,
)

The ADaM dataset templates (see get_adam_dataset()) have their own classes, ADaMDatasetTemplate and ADaMVariableSpec. The adam_to_metadata() function converts a template to a MetadataImport, the same object that import_metadata() returns for a metadata file. That gives the template the methods of a MetadataImport, such as to_schema() and get_variable(), and lets it be exported with export_metadata().

Each variable in the template becomes a VariableMetadata with the same name, label, required flag, maximum length and controlled terminology name. The variable’s core designation ("Req", "Cond" or "Perm") goes in cdisc_role, and its expected source (such as "SDTM.DM") goes in adam_derivation. ADaM’s "Num" type becomes the "Float64" dtype and "Char" becomes "String", so numeric dates such as TRTSDT (which ADaM stores as numbers of days) are "Float64". The source version is "IG 1.1". Calling import_metadata(format="cdisc_adam", dataset=...) gives the same result.

Parameters

dataset: str: The name of the ADaM dataset template: "ADSL", "BDS", "ADAE" or "ADTTE". This is case-insensitive.
study_id: str | None = None: A study identifier to record in the metadata’s study_id. The default is None.

Returns

MetadataImport: The metadata for the dataset, with source_format="cdisc_adam".

Raises

KeyError: If there is no template with that name.

Examples

Let’s convert the template for the subject-level analysis dataset, ADSL:

import pointblank as pb

adsl_meta = pb.adam_to_metadata("ADSL", study_id="STUDY01")

print(adsl_meta.dataset_label)
print(len(adsl_meta.variables), "variables")

Subject Level Analysis Dataset
30 variables

Each variable keeps what the template says about it, with the ADaM core designation in cdisc_role:

for name in ["USUBJID", "TRT01P", "SAFFL", "TRTSDT"]:
    var = adsl_meta.get_variable(name)
    print(f"{name:8}{var.dtype:8}{var.cdisc_role:5}{var.adam_derivation}")

USUBJID String  Req  SDTM.DM
TRT01P  String  Req  None
SAFFL   String  Cond None
TRTSDT  Float64 Cond Derived from SDTM.EX

USUBJID and TRT01P are required, while SAFFL (the safety population flag) and TRTSDT (the treatment start date) are conditionally required. USUBJID comes from the SDTM Demographics (DM) domain and TRTSDT is derived from Exposure (EX). Only the required variables get required=True, so the conditional ones don’t get the null checks that to_validate() adds for required variables.

Parameters

Returns

Raises

Examples

See Also