From ef825d98c7b14401c449bba4a7b42b5ca5483dcb Mon Sep 17 00:00:00 2001
From: Felipe Alex Hofmann <fealho@gmail.com>
Date: Fri, 22 Nov 2024 09:59:38 -0800
Subject: [PATCH] Improve warning handling for non-positive values when
`apply_log = True` for `InterRowMSAS` (#671)
---
.../statistical/inter_row_msas.py | 99 +++++++++++--------
.../statistical/test_inter_row_msas.py | 25 +++++
2 files changed, 84 insertions(+), 40 deletions(-)
diff --git a/sdmetrics/column_pairs/statistical/inter_row_msas.py b/sdmetrics/column_pairs/statistical/inter_row_msas.py
index eea77f06..200b58fa 100644
--- a/sdmetrics/column_pairs/statistical/inter_row_msas.py
+++ b/sdmetrics/column_pairs/statistical/inter_row_msas.py
@@ -29,7 +29,61 @@ class InterRowMSAS:
max_value = 1.0
@staticmethod
- def compute(real_data, synthetic_data, n_rows_diff=1, apply_log=False):
+ def _validate_inputs(real_data, synthetic_data, n_rows_diff, apply_log):
+ for data in [real_data, synthetic_data]:
+ if (
+ not isinstance(data, tuple)
+ or len(data) != 2
+ or (not (isinstance(data[0], pd.Series) and isinstance(data[1], pd.Series)))
+ ):
+ raise ValueError('The data must be a tuple of two pandas series.')
+
+ if not isinstance(n_rows_diff, int) or n_rows_diff < 1:
+ raise ValueError("'n_rows_diff' must be an integer greater than zero.")
+
+ if not isinstance(apply_log, bool):
+ raise ValueError("'apply_log' must be a boolean.")
+
+ @staticmethod
+ def _apply_log(real_values, synthetic_values, apply_log):
+ if apply_log:
+ num_invalid = sum(x <= 0 for x in pd.concat((real_values, synthetic_values)))
+ if num_invalid:
+ warnings.warn(
+ f'There are {num_invalid} non-positive values in your data, which cannot be '
+ "used with log. Consider changing 'apply_log' to False for a better result."
+ )
+ with warnings.catch_warnings():
+ warnings.filterwarnings('ignore', message='.*encountered in log')
+ real_values = np.log(real_values)
+ synthetic_values = np.log(synthetic_values)
+
+ return real_values, synthetic_values
+
+ @staticmethod
+ def _calculate_differences(keys, values, n_rows_diff, data_name):
+ grouped = values.groupby(keys)
+ group_sizes = grouped.size()
+
+ num_invalid_groups = len(group_sizes[group_sizes <= n_rows_diff])
+ if num_invalid_groups > 0:
+ warnings.warn(
+ f"n_rows_diff '{n_rows_diff}' is greater than the "
+ f'size of {num_invalid_groups} sequence keys in {data_name}.'
+ )
+
+ def diff_func(group):
+ if len(group) <= n_rows_diff:
+ return np.nan
+ group = group.to_numpy()
+ return np.mean(group[n_rows_diff:] - group[:-n_rows_diff])
+
+ with warnings.catch_warnings():
+ warnings.filterwarnings('ignore', message='invalid value encountered in.*')
+ return grouped.apply(diff_func)
+
+ @classmethod
+ def compute(cls, real_data, synthetic_data, n_rows_diff=1, apply_log=False):
"""Compute this metric.
This metric compares the inter-row differences of sequences in the real data
@@ -58,48 +112,13 @@ def compute(real_data, synthetic_data, n_rows_diff=1, apply_log=False):
float:
The similarity score between the real and synthetic data distributions.
"""
- for data in [real_data, synthetic_data]:
- if (
- not isinstance(data, tuple)
- or len(data) != 2
- or (not (isinstance(data[0], pd.Series) and isinstance(data[1], pd.Series)))
- ):
- raise ValueError('The data must be a tuple of two pandas series.')
-
- if not isinstance(n_rows_diff, int) or n_rows_diff < 1:
- raise ValueError("'n_rows_diff' must be an integer greater than zero.")
-
- if not isinstance(apply_log, bool):
- raise ValueError("'apply_log' must be a boolean.")
-
+ cls._validate_inputs(real_data, synthetic_data, n_rows_diff, apply_log)
real_keys, real_values = real_data
synthetic_keys, synthetic_values = synthetic_data
+ real_values, synthetic_values = cls._apply_log(real_values, synthetic_values, apply_log)
- if apply_log:
- real_values = np.log(real_values)
- synthetic_values = np.log(synthetic_values)
-
- def calculate_differences(keys, values, n_rows_diff, data_name):
- group_sizes = values.groupby(keys).size()
- num_invalid_groups = group_sizes[group_sizes <= n_rows_diff].count()
- if num_invalid_groups > 0:
- warnings.warn(
- f"n_rows_diff '{n_rows_diff}' is greater than the "
- f'size of {num_invalid_groups} sequence keys in {data_name}.'
- )
-
- differences = values.groupby(keys).apply(
- lambda group: np.mean(
- group.to_numpy()[n_rows_diff:] - group.to_numpy()[:-n_rows_diff]
- )
- if len(group) > n_rows_diff
- else np.nan
- )
-
- return pd.Series(differences)
-
- real_diff = calculate_differences(real_keys, real_values, n_rows_diff, 'real_data')
- synthetic_diff = calculate_differences(
+ real_diff = cls._calculate_differences(real_keys, real_values, n_rows_diff, 'real_data')
+ synthetic_diff = cls._calculate_differences(
synthetic_keys, synthetic_values, n_rows_diff, 'synthetic_data'
)
diff --git a/tests/unit/column_pairs/statistical/test_inter_row_msas.py b/tests/unit/column_pairs/statistical/test_inter_row_msas.py
index 9a3552db..a88e375f 100644
--- a/tests/unit/column_pairs/statistical/test_inter_row_msas.py
+++ b/tests/unit/column_pairs/statistical/test_inter_row_msas.py
@@ -71,6 +71,31 @@ def test_compute_with_log(self):
# Assert
assert score == 1
+ def test_compute_with_log_warning(self):
+ """Test it warns when negative values are present and apply_log is True."""
+ # Setup
+ real_keys = pd.Series(['id1', 'id1', 'id1', 'id2', 'id2', 'id2'])
+ real_values = pd.Series([1, 1.4, 4, -1, 16, -10])
+ synthetic_keys = pd.Series(['id1', 'id1', 'id1', 'id2', 'id2', 'id2'])
+ synthetic_values = pd.Series([1, 2, -4, 8, 16, 30])
+
+ # Run
+ with pytest.warns(UserWarning) as warning_info:
+ score = InterRowMSAS.compute(
+ real_data=(real_keys, real_values),
+ synthetic_data=(synthetic_keys, synthetic_values),
+ apply_log=True,
+ )
+
+ # Assert
+ expected_message = (
+ 'There are 3 non-positive values in your data, which cannot be used with log. '
+ "Consider changing 'apply_log' to False for a better result."
+ )
+ assert len(warning_info) == 1
+ assert str(warning_info[0].message) == expected_message
+ assert score == 0
+
def test_compute_different_n_rows_diff(self):
"""Test it with different n_rows_diff."""
# Setup