The FixedCombinations constraint enforces that the combinations between a set of columns are fixed. That is, no other permutations or shuffling is allowed other than what's already observed in the data.
Parameters
(required) column_names: A list of two or more columns whose combinations are fixed. The SDV will not further shuffle the data between these column names.
Example
Define your constraint using the parameters and then add it to a synthesizer.
my_constraint ={'constraint_class':'FixedCombinations','table_name':'locations',# for multi table synthesizers'constraint_parameters':{'column_names': ['city','country']}}my_synthesizer.add_constraints(constraints=[ my_constraint])
FAQs
Why can't I apply this constraint to a single column?
This constraint ensures that the synthetic data only contains combinations that exist in the real data. If there is only one column, there are no combinations.
The SDV already guarantees that the synthetic data contains the same categorical values as the real data for a single column.
The synthetic data has the same combination multiple times. Is this intended?
Yes. This constraint prevents the SDV from creating additional permutations between columns. But the same permutations are allowed to appear multiple times.
For example, it will prevent the SDV from inventing new city, country pairs, but a valid pair such as Boston, USA may appear more than once.
What happens to null values?
This constraint will consider a null value as part of a combination. For example if a null in one column always appears next to a True value in another column, the constraint will learn that.
If you would to only fix the combinations of the null values (and allow synthesizer to continue creating new permutations of the non-null values), please used the FixedNullCombinations constraint instead.
