Check and supply a more descriptive error when trying to use 'gaussian_kde' with HMA

[npatki]

Problem Description

The HMASynthesizer is not compatible with the 'gaussian_kde' distribution. The HMA algorithm is only designed to work with parametric distributions (distributions must have pre-defined parameters and a predetermined number of them).

Even though we know this incompatibility exists, the HMASynthesizer is still allowing you to apply the 'gaussian_kde' distribution in the set_table_parameters function without complaining. Then it is erroring on fit with a KeyError that makes it every hard to understand what's happening (see #1602).

Expected behavior

If I try to apply the gaussian_kde for an HMA distribution, the set_table_parameters method should produce a clear error with guidance about what to do next.

from sdv.multi_table import HMASynthesizer
from sdv.datasets.demo import download_demo

data, metadata = download_demo(
    modality='multi_table',
    dataset_name='fake_hotels'
)

synthesizer = HMASynthesizer(metadata)
synthesizer.set_table_parameters(
    table_name='guests',
    table_parameters={
        'default_distribution': 'gaussian_kde',
        'numerical_distributions': {
            'checkin_date': 'uniform',
            'checkout_date': 'gaussian_kde'
        }
    }
)

synthesizer.fit(data)

SynthesizerInputError: The 'gaussian_kde' is not compatible with the HMA algorithm. Please choose a different distribution such as 'beta' or 'truncnorm'. Or try a different algorithm such as HSA.

Additional context

Note that the error should trigger for either case below:

• I try to set default distribution to 'gaussian_kde'
• I try to set any individual column to 'gaussian_kde' using the numerical_distributions parameter