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Add Bhattacharyya distance data drift method #123

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Merged
merged 1 commit into from
Jan 26, 2023
Merged

Add Bhattacharyya distance data drift method #123

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2 changes: 2 additions & 0 deletions frouros/data_drift/batch/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
"""Data drift batch detection methods init."""

from .distance_based import (
Bhattacharyya,
EMD,
Hellinger,
HistogramIntersection,
Expand All @@ -17,6 +18,7 @@
)

__all__ = [
"Bhattacharyya",
"ChiSquareTest",
"CVMTest",
"EMD",
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2 changes: 2 additions & 0 deletions frouros/data_drift/batch/distance_based/__init__.py
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@@ -1,5 +1,6 @@
"""Data drift batch distance based detection methods' init."""

from .bhattacharyya import Bhattacharyya
from .emd import EMD
from .hellinger import Hellinger
from .histogram_intersection import HistogramIntersection
Expand All @@ -9,6 +10,7 @@
from .mmd import MMD

__all__ = [
"Bhattacharyya",
"EMD",
"Hellinger",
"HistogramIntersection",
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27 changes: 27 additions & 0 deletions frouros/data_drift/batch/distance_based/bhattacharyya.py
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@@ -0,0 +1,27 @@
"""Bhattacharyya distance module."""

import numpy as np # type: ignore

from frouros.data_drift.batch.distance_based.base import (
DistanceBinsBasedBase,
)


class Bhattacharyya(DistanceBinsBasedBase):
"""Bhattacharyya algorithm class."""

def _distance_measure_bins(
self,
X_ref_: np.ndarray, # noqa: N803
X: np.ndarray, # noqa: N803
) -> float:
distance = self._bhattacharyya(
X_ref_=X_ref_,
X=X,
)
return distance

@staticmethod
def _bhattacharyya(X_ref_: np.ndarray, X: np.ndarray) -> float: # noqa: N803
distance = 1 - np.sum(np.sqrt(X_ref_ * X))
return distance
5 changes: 3 additions & 2 deletions frouros/tests/test_data_drift.py
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Expand Up @@ -7,6 +7,7 @@

from frouros.data_drift.batch.base import DataDriftBatchBase
from frouros.data_drift.batch.distance_based import (
Bhattacharyya,
EMD,
Hellinger,
HistogramIntersection,
Expand Down Expand Up @@ -86,7 +87,7 @@ def test_batch_distance_based_univariate(

@pytest.mark.parametrize(
"detector, expected_distance",
[(PSI(), 468.79410784), (Hellinger(), 0.77137797)],
[(PSI(), 468.79410784), (Hellinger(), 0.77137797), (Bhattacharyya(), 0.59502397)],
)
def test_batch_distance_bins_based_univariate_different_distribution(
univariate_distribution_p: Tuple[float, float],
Expand Down Expand Up @@ -120,7 +121,7 @@ def test_batch_distance_bins_based_univariate_different_distribution(

@pytest.mark.parametrize(
"detector, expected_distance",
[(PSI(), 0.01840072), (Hellinger(), 0.04792538)],
[(PSI(), 0.01840072), (Hellinger(), 0.04792538), (Bhattacharyya(), 0.00229684)],
)
def test_batch_distance_bins_based_univariate_same_distribution(
univariate_distribution_p: Tuple[float, float],
Expand Down