Cannot fit twice if I add constraints: ValueError: There are non-numerical values in your data.

[npatki]

Environment Details

• SDV version: SDV 1.0 (in progress)
• Python version: 3.8
• Operating System: Linux (Colab Notebook)

Error Description

If I apply constraints to HMASynthesizer, then I am unable to call fit more than once. I get a ValueError every time I try to fit a second time.

Steps to reproduce

Observe that the first fit call succeeds but the second one fails.

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

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

synthesizer = HMASynthesizer(metadata)

fixed_location_combinations = {
    'constraint_class': 'FixedCombinations',
    'table_name': 'hotels',
    'constraint_parameters': {
        'column_names': ['city', 'state']
    } 
}

synthesizer.add_constraints([fixed_location_combinations])

synthesizer.fit(real_data)
print('FITTING 1: DONE')

synthesizer.fit(real_data)
print('FITTING 2: DONE')

Stack Trace

FITTING 1: DONE
/usr/local/lib/python3.8/dist-packages/rdt/hyper_transformer.py:400: UserWarning: For this change to take effect, please refit your data using 'fit' or 'fit_transform'.
  warnings.warn(self._REFIT_MESSAGE)
/usr/local/lib/python3.8/dist-packages/sdv/single_table/base.py:398: UserWarning: This model has already been fitted. To use the new preprocessed data, please refit the model using 'fit' or 'fit_processed_data'.
  warnings.warn(
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-10-3b08a927e949>](https://localhost:8080/#) in <module>
     21 synthesizer.fit(real_data)
     22 print('FITTING 1: DONE')
---> 23 synthesizer.fit(real_data)
     24 print('FITTING 2: DONE')

8 frames
[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/base.py](https://localhost:8080/#) in fit(self, data)
    324         self._fitted = False
    325         processed_data = self.preprocess(data)
--> 326         self.fit_processed_data(processed_data)
    327 
    328     def reset_sampling(self):

[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/base.py](https://localhost:8080/#) in fit_processed_data(self, processed_data)
    309                 Dictionary mapping each table name to a preprocessed ``pandas.DataFrame``.
    310         """
--> 311         self._fit(processed_data)
    312         self._fitted = True
    313         self._fitted_date = datetime.datetime.today().strftime('%Y-%m-%d')

[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/hma.py](https://localhost:8080/#) in _fit(self, processed_data)
    207         for table_name in processed_data:
    208             if not parent_map.get(table_name):
--> 209                 self._model_table(table_name, processed_data)
    210 
    211         LOGGER.info('Modeling Complete')

[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/hma.py](https://localhost:8080/#) in _model_table(self, table_name, tables)
    180         self._table_sizes[table_name] = len(table)
    181 
--> 182         table = self._extend_table(table, tables, table_name)
    183         keys = self._pop_foreign_keys(table, table_name)
    184         self._clear_nans(table)

[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/hma.py](https://localhost:8080/#) in _extend_table(self, table, tables, table_name)
    117         for child_name in self.metadata._get_child_map()[table_name]:
    118             if child_name not in self._modeled_tables:
--> 119                 child_table = self._model_table(child_name, tables)
    120             else:
    121                 child_table = tables[child_name]

[/usr/local/lib/python3.8/dist-packages/sdv/multi_table/hma.py](https://localhost:8080/#) in _model_table(self, table_name, tables)
    186                     table_name, table.shape)
    187 
--> 188         self._table_synthesizers[table_name].fit_processed_data(table)
    189 
    190         for name, values in keys.items():

[/usr/local/lib/python3.8/dist-packages/sdv/single_table/base.py](https://localhost:8080/#) in fit_processed_data(self, processed_data)
    419                 The transformed data used to fit the model to.
    420         """
--> 421         self._fit(processed_data)
    422         self._fitted = True
    423         self._fitted_date = datetime.datetime.today().strftime('%Y-%m-%d')

[/usr/local/lib/python3.8/dist-packages/sdv/single_table/copulas.py](https://localhost:8080/#) in _fit(self, processed_data)
    130         with warnings.catch_warnings():
    131             warnings.filterwarnings('ignore', module='scipy')
--> 132             self._model.fit(processed_data)
    133 
    134     def _warn_for_update_transformers(self, column_name_to_transformer):

[/usr/local/lib/python3.8/dist-packages/copulas/__init__.py](https://localhost:8080/#) in decorated(self, X, *args, **kwargs)
    251 
    252         if not (np.issubdtype(W.dtype, np.floating) or np.issubdtype(W.dtype, np.integer)):
--> 253             raise ValueError('There are non-numerical values in your data.')
    254 
    255         if np.isnan(W).any().any():

ValueError: There are non-numerical values in your data.