Add trace_analysis_script/tests/test_core.py

trace_analysis_script/tests/test_core.py

@@ -0,0 +1,51 @@
+import json
+import math
+import tempfile
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from trace_analysis_script import core
+
+def _create_sample_trace_file(tmp_path: Path) -> Path:
+    data = {
+        'time': np.arange(0, 1, 0.01),
+        'signal': np.sin(2 * np.pi * 5 * np.arange(0, 1, 0.01)) * 0.5 + 0.5
+    }
+    df = pd.DataFrame(data)
+    file_path = tmp_path / 'sample_trace.csv'
+    df.to_csv(file_path, index=False)
+    return file_path
+
+def test_analyze_trace_returns_dict_with_expected_keys(tmp_path):
+    trace_file = _create_sample_trace_file(tmp_path)
+    result = core.analyze_trace(str(trace_file))
+
+    assert isinstance(result, dict)
+    expected_keys = {'peak_amplitude', 'median_bandpower', 'crosscorr_with_clockevents'}
+    assert set(result.keys()) == expected_keys
+
+    for key in expected_keys:
+        assert isinstance(result[key], (float, int))
+
+
+def test_peak_amplitude_value_is_reasonable(tmp_path):
+    trace_file = _create_sample_trace_file(tmp_path)
+    result = core.analyze_trace(str(trace_file))
+    assert 0.4 <= result['peak_amplitude'] <= 0.6
+
+
+def test_crosscorr_with_clockevents_is_numeric(tmp_path):
+    trace_file = _create_sample_trace_file(tmp_path)
+    result = core.analyze_trace(str(trace_file))
+    val = result['crosscorr_with_clockevents']
+    assert isinstance(val, (float, int))
+    assert -1.0 <= val <= 1.0
+
+
+def test_handles_invalid_input_file_gracefully(tmp_path):
+    invalid_path = tmp_path / 'nonexistent.csv'
+    with pytest.raises((FileNotFoundError, ValueError)):
+        _ = core.analyze_trace(str(invalid_path))