tests xai consistency

Author: ahinterl94-th

test/test_xai_consistency.py

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+import numpy as np
+from spotpython.utils.metrics import calculate_xai_consistency
+
+
+def test_xai_consistency():
+    # Mock data for testing
+
+    dl_attr_test_sum = [1, 2, 3, 4, 5]
+    row_sum_dl = np.sum(dl_attr_test_sum, axis=0)
+    if row_sum_dl == 0:
+        row_sum_dl += 1e-10
+    scaled_attribution_dl = dl_attr_test_sum / row_sum_dl
+
+    ig_attr_test_sum = [1, 2, 3, 4, 5]
+    row_sum_ig = np.sum(ig_attr_test_sum, axis=0)
+    if row_sum_ig == 0:
+        row_sum_ig += 1e-10
+    scaled_attribution_ig = ig_attr_test_sum / row_sum_ig
+
+    attributions = [scaled_attribution_dl, scaled_attribution_ig]
+    result = calculate_xai_consistency(attributions)
+    print("XAI Consistency Result:")
+    print(result)
+
+    # Assert that the result is 1
+    assert abs(result - 1) < 1e-10
+
+
+def test_xai_consistency_negative():
+    # Mock data for testing negative consistency
+
+    dl_attr_test_sum = [1, 2, 3, 4, 5]
+    row_sum_dl = np.sum(dl_attr_test_sum, axis=0)
+    if row_sum_dl == 0:
+        row_sum_dl += 1e-10
+    scaled_attribution_dl = dl_attr_test_sum / row_sum_dl
+
+    ig_attr_test_sum = [-1, -2, -3, -4, -5]
+    row_sum_ig = np.sum(np.abs(ig_attr_test_sum), axis=0)
+    if row_sum_ig == 0:
+        row_sum_ig += 1e-10
+    scaled_attribution_ig = ig_attr_test_sum / row_sum_ig
+
+    attributions = [scaled_attribution_dl, scaled_attribution_ig]
+    result = calculate_xai_consistency(attributions)
+    print("XAI Consistency Result (Negative):")
+    print(result)
+
+    # Assert that the result is -1
+    assert abs(result + 1) < 1e-10