Constraint adherence metric

sdmetrics/multi_table/__init__.py

@@ -32,6 +32,7 @@
 from sdmetrics.multi_table.statistical.cardinality_statistic_similarity import (
     CardinalityStatisticSimilarity,
 )
+from sdmetrics.multi_table.statistical.constraint_adherence import ConstraintAdherence
 
 __all__ = [
     'detection',
@@ -59,4 +60,5 @@
     'TVComplement',
     'RangeCoverage',
     'NewRowSynthesis',
+    'ConstraintAdherence',
 ]

sdmetrics/multi_table/statistical/__init__.py

@@ -6,5 +6,6 @@
 from sdmetrics.multi_table.statistical.cardinality_statistic_similarity import (
     CardinalityStatisticSimilarity,
 )
+from sdmetrics.multi_table.statistical.constraint_adherence import ConstraintAdherence
 
-__all__ = ['CardinalityShapeSimilarity', 'CardinalityStatisticSimilarity']
+__all__ = ['CardinalityShapeSimilarity', 'CardinalityStatisticSimilarity', 'ConstraintAdherence']

sdmetrics/multi_table/statistical/constraint_adherence.py

@@ -0,0 +1,79 @@
+"""Constraint Adherence metric."""
+
+import logging
+import warnings
+
+import numpy as np
+import pandas as pd
+
+from sdmetrics.goal import Goal
+from sdmetrics.multi_table.base import MultiTableMetric
+from sdmetrics.multi_table.statistical.constraints.base import BaseConstraint
+from sdmetrics.multi_table.statistical.constraints.error import ConstraintNotApplicableError
+
+LOGGER = logging.getLogger(__name__)
+
+
+class ConstraintAdherence(MultiTableMetric):
+    """Constraint Adherence metric.
+
+    Compute the fraction of data points in the synthetic data that
+    follow the specified constraint.
+
+    Attributes:
+        name (str):
+            Name to use when reports about this metric are printed.
+        goal (sdmetrics.goal.Goal):
+            The goal of this metric.
+        min_value (float):
+            Minimum value that this metric can take.
+        max_value (float):
+            Maximum value that this metric can take.
+    """
+
+    name = 'ConstraintAdherence'
+    goal = Goal.MAXIMIZE
+    min_value = 0.0
+    max_value = 1.0
+
+    @classmethod
+    def compute(cls, real_data, synthetic_data, metadata, constraint):
+        """Compute the percentage of rows that adhere to the constraint.
+
+        Args:
+            real_data (dict[str, pandas.DataFrame]):
+                The tables from the real dataset, passed as a dictionary of
+                table names and pandas.DataFrames.
+            synthetic_data (dict[str, pandas.DataFrame]):
+                The tables from the synthetic dataset, passed as a dictionary of
+                table names and pandas.DataFrames.
+            metadata (dict):
+                Multi-table metadata dict.
+            constraint (dict):
+                A dictionary that defines the type of constraint and its parameters.
+
+        Returns:
+            float:
+                The proportion of data points in the synthetic data that match
+                the specified constraint format.
+        """
+        constraint = BaseConstraint.load_constraint_from_dict(constraint)
+
+        try:
+            constraint.fit(real_data, metadata)
+            real_score = constraint.get_score(real_data, metadata)
+        except ConstraintNotApplicableError as error:
+            LOGGER.warning(f'Unable to check the constraint against the real data: {error}')
+            real_score = np.nan
+
+        if not pd.isna(real_score) and real_score < 1.0:
+            warnings.warn(
+                f"The real data does not adhere to the '{constraint.__class__.__name__}' "
+                f'constraint ({round(real_score * 100, 2)}% of the rows are valid). '
+            )
+
+        try:
+            return constraint.get_score(synthetic_data, metadata)
+        except ConstraintNotApplicableError as error:
+            LOGGER.warning(f'Unable to check the constraint against the synthetic data: {error}')
+            return np.nan

sdmetrics/multi_table/statistical/constraints/__init__.py

@@ -0,0 +1,55 @@
+"""Constraints."""
+
+from sdmetrics.multi_table.statistical.constraints.base import BaseConstraint
+from sdmetrics.multi_table.statistical.constraints.carry_over_columns import CarryOverColumns
+from sdmetrics.multi_table.statistical.constraints.column_formula import ColumnFormula
+from sdmetrics.multi_table.statistical.constraints.denormalized_table import (
+    DenormalizedTable,
+)
+from sdmetrics.multi_table.statistical.constraints.chained_inequality import ChainedInequality
+from sdmetrics.multi_table.statistical.constraints.inequality import Inequality
+from sdmetrics.multi_table.statistical.constraints.fixed_combinations import FixedCombinations
+from sdmetrics.multi_table.statistical.constraints.fixed_increments import FixedIncrements
+from sdmetrics.multi_table.statistical.constraints.fixed_null_combinations import (
+    FixedNullCombinations,
+)
+from sdmetrics.multi_table.statistical.constraints.foreign_to_foreign_key import (
+    ForeignToForeignKey,
+)
+from sdmetrics.multi_table.statistical.constraints.foreign_to_primary_key_subset import (
+    ForeignToPrimaryKeySubset,
+)
+from sdmetrics.multi_table.statistical.constraints.mixed_scales import MixedScales
+from sdmetrics.multi_table.statistical.constraints.polymorphic_relationship import (
+    PolymorphicRelationship,
+)
+from sdmetrics.multi_table.statistical.constraints.primary_to_primary_key_subset import (
+    PrimaryToPrimaryKeySubset,
+)
+from sdmetrics.multi_table.statistical.constraints.reference_table import ReferenceTable
+from sdmetrics.multi_table.statistical.constraints.one_hot_encoding import OneHotEncoding
+from sdmetrics.multi_table.statistical.constraints.range import Range
+from sdmetrics.multi_table.statistical.constraints.referential_hierarchy import (
+    SelfReferentialHierarchy,
+)
+
+__all__ = (
+    BaseConstraint,
+    CarryOverColumns,
+    ColumnFormula,
+    DenormalizedTable,
+    ChainedInequality,
+    Inequality,
+    FixedIncrements,
+    FixedCombinations,
+    FixedNullCombinations,
+    ForeignToForeignKey,
+    ForeignToPrimaryKeySubset,
+    MixedScales,
+    PolymorphicRelationship,
+    PrimaryToPrimaryKeySubset,
+    ReferenceTable,
+    OneHotEncoding,
+    Range,
+    SelfReferentialHierarchy,
+)