＊ ChainedInequality

＊SDV Enterprise Feature. This feature is only available for licensed, enterprise users. For more information, visit our page to Compare SDV Features.

The ChainedInequality constraint enforces a chain of inequality relationships between any number of columns. For every row, the value in these columns must follow a strict ordering system.

Constraint API

Create a ChainedInequality constraint.

Parameters:

• (required) column_names: A list of strings that represent the column names. They should appear in ascending order (lowest to highest). Only numerical and datetime columns are allowed.

• strict_boundaries: Whether a column must be strictly greater than previous one

  • (default) True: The value in the higher column must be strictly greater than the lower one

  • False: The value in the higher column must be greater than or equal to the value of the lower one

• table_name: A string with the name of the table to apply this to. Required if you have a multi-table dataset.

from sdv.cag import ChainedInequality

my_constraint = ChainedInequality(
    column_names=['purchase_date', 'start_date', 'end_date', 'expiration_date']
)   

Usage

Apply the constraint to any SDV synthesizer. Then fit and sample as usual.

synthesizer = GaussianCopulaSynthesizer(metadata)
synthesizer.add_constraints([my_constraint])

synthesizer.fit(data)
synthetic_data = synthesizer.sample()

For more information about using predefined constraints, please see the Constraint-Augmented Generation tutorial.