Add basic pytest suite

tests/conftest.py

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+import os
+import sys
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))

tests/test_create_input.py

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+import pandas as pd
+import pytest
+
+from src.create_input import conv_filename_to_condition, validate_inputs
+
+
+def test_conv_filename_to_condition_match():
+    pattern = r"(?P<noise>[^_]+)_(?P<level>\d+)\.wav"
+    result = conv_filename_to_condition("white_10.wav", pattern)
+    assert list(result.items()) == [("level", "10"), ("noise", "white")]
+
+
+def test_conv_filename_to_condition_no_match():
+    pattern = r"(?P<noise>[^_]+)_(?P<level>\d+)\.wav"
+    result = conv_filename_to_condition("unexpected.wav", pattern)
+    assert result == {"Unknown": "NoCondition"}
+
+
+def test_validate_inputs_acr_minimal():
+    cfg = {"number_of_gold_clips_per_session": "0"}
+    df = pd.DataFrame(columns=[
+        "rating_clips", "math", "pair_a", "pair_b", "trapping_clips", "trapping_ans"
+    ])
+    validate_inputs(cfg, df, "acr")
+
+
+def test_validate_inputs_missing_column():
+    cfg = {"number_of_gold_clips_per_session": "0"}
+    df = pd.DataFrame(columns=[
+        "rating_clips", "math", "pair_a", "trapping_clips", "trapping_ans"
+    ])
+    with pytest.raises(AssertionError):
+        validate_inputs(cfg, df, "acr")

tests/test_result_parser.py

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+from src.result_parser import outliers_modified_z_score, outliers_z_score
+
+
+def test_outliers_modified_z_score_removes_outlier():
+    data = [1, 1, 1, 100]
+    assert outliers_modified_z_score(data) == [1, 1, 1]
+
+
+def test_outliers_z_score_threshold_high():
+    data = [10, 10, 10, 1000]
+    # With default threshold 3.29 the outlier is not removed
+    assert outliers_z_score(data) == data