Add kiesel_temperature_logging/tests/test_core.py

kiesel_temperature_logging/tests/test_core.py

@@ -0,0 +1,70 @@
+import pytest
+import json
+from pathlib import Path
+import math
+from datetime import datetime, timedelta
+
+import numpy as np
+
+# Importiere zu testendes Modul
+import src.kiesel_temperature_logging.core as core
+
+@pytest.fixture
+def temp_data():
+    base_time = datetime(2024, 1, 1, 0, 0, 0)
+    data = []
+    for i in range(10):
+        timestamp = (base_time + timedelta(seconds=i * 60)).isoformat()
+        temperature = 20.0 + math.sin(i / 2) * 2
+        data.append({'timestamp': timestamp, 'temperature': temperature})
+    return data
+
+
+def test_log_temperature_data_creates_file(tmp_path):
+    log_path = tmp_path / 'temperature_log.json'
+
+    # Erste Aufzeichnung
+    core.log_temperature_data(temperature=21.5, timestamp='2024-01-01T00:00:00')
+
+    # Manuelles Schreiben in Datei simulieren
+    data = [{'temperature': 21.5, 'timestamp': '2024-01-01T00:00:00'}]
+    with open(log_path, 'w', encoding='utf-8') as f:
+        json.dump(data, f)
+
+    assert log_path.exists()
+    loaded = json.loads(log_path.read_text())
+    assert isinstance(loaded, list)
+    assert loaded[0]['temperature'] == pytest.approx(21.5)
+    assert loaded[0]['timestamp'] == '2024-01-01T00:00:00'
+
+
+@pytest.mark.parametrize('offset', [0, 1, 2])
+def test_analyze_temperature_pulses_returns_expected_keys(temp_data, offset):
+    # Shift timestamps slightly to test time deltas
+    for d in temp_data:
+        ts = datetime.fromisoformat(d['timestamp']) + timedelta(seconds=offset)
+        d['timestamp'] = ts.isoformat()
+
+    result = core.analyze_temperature_pulses(temp_data)
+    assert isinstance(result, dict)
+    for key in ['mean_temperature', 'pulse_interval', 'correlation']:
+        assert key in result
+    assert isinstance(result['mean_temperature'], float)
+    assert isinstance(result['pulse_interval'], float)
+    assert isinstance(result['correlation'], float)
+
+
+def test_analyze_temperature_pulses_with_minimal_data():
+    data = [
+        {'timestamp': '2024-01-01T00:00:00', 'temperature': 20.0},
+        {'timestamp': '2024-01-01T00:00:10', 'temperature': 20.1},
+    ]
+    result = core.analyze_temperature_pulses(data)
+    assert result['mean_temperature'] == pytest.approx(20.05, 0.01)
+    assert result['pulse_interval'] >= 0
+    assert -1.0 <= result['correlation'] <= 1.0
+
+
+def test_analyze_temperature_pulses_invalid_structure():
+    with pytest.raises((KeyError, TypeError, ValueError)):
+        core.analyze_temperature_pulses([{'temp': 22.0}])