Biochar-Toilet/test_dryness_monitor.py at main · PubInv/Biochar-Toilet · GitHub

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import unittest
from dryness_monitor import DrynessMonitor

class TestDrynessMonitor(unittest.TestCase):
    def test_initial_state(self):
        monitor = DrynessMonitor()
        self.assertFalse(monitor.is_dry(), "Should not be dry initially without data")

    def test_wet_state(self):
        # Wet state: Both T and P rise (simulating heating water in closed vessel)
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # Add data points where both T and P increase
        # T increases 1 deg/sec, P increases 0.5 unit/sec
        # This should result in is_dry() == False because P rate (0.5) > max_pressure_rate (0.1)
        for i in range(5):
            monitor.add_reading(temperature=100 + i*1.0, pressure=10 + i*0.5, timestamp=i)

        self.assertFalse(monitor.is_dry(), "Should not be dry when pressure is rising significantly")

    def test_dry_state(self):
        # Dry state: T rises, P stays relatively constant
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # Add data points where T increases but P is stable
        # T increases 1 deg/sec, P increases 0.05 unit/sec
        # This should result in is_dry() == True because:
        # T rate (1.0) > min_temp_rate (0.5) AND P rate (0.05) < max_pressure_rate (0.1)
        for i in range(5):
            monitor.add_reading(temperature=150 + i*1.0, pressure=20 + i*0.05, timestamp=i)

        self.assertTrue(monitor.is_dry(), "Should be dry when temp rises and pressure is stable")

    def test_cooling_or_steady_temp(self):
        # Temp not rising enough or cooling
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # T decreases 1 deg/sec (cooling), P stable
        for i in range(5):
            monitor.add_reading(temperature=100 - i*1.0, pressure=10, timestamp=i)

        self.assertFalse(monitor.is_dry(), "Should not be dry if temp is cooling")

        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # T increases 0.1 deg/sec (below threshold), P stable
        for i in range(5):
            monitor.add_reading(temperature=100 + i*0.1, pressure=10, timestamp=i)

        self.assertFalse(monitor.is_dry(), "Should not be dry if temp is not rising fast enough")

    def test_pressure_drop(self):
        # Pressure dropping (maybe leak or cooling), Temp rising
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # T increases 1.0 deg/sec, P decreases
        for i in range(5):
            monitor.add_reading(temperature=100 + i*1.0, pressure=10 - i*0.1, timestamp=i)

        # P rate is negative, which is < max_pressure_rate. T rate is high. Should be dry (or at least satisfy condition).
        # In physical reality, P dropping while T rising might mean valve open or leak, effectively "dry" wrt steam generation pressure build-up.
        self.assertTrue(monitor.is_dry(), "Should be dry if pressure is dropping while temp rises")

    def test_noisy_high_frequency_data(self):
        # Simulating high frequency data (e.g., millisecond updates) where time_diff might be 0 or very small
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # Test adding readings with the exact same timestamp (simulating very fast reads that get truncated or batch processed)
        for i in range(5):
            monitor.add_reading(temperature=100 + i, pressure=10, timestamp=1.0)

        # The monitor should safely return False instead of raising DivisionByZero error
        self.assertFalse(monitor.is_dry(), "Should handle 0 time difference safely by returning False")

        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # Now simulate actual high-frequency noisy data
        import random
        random.seed(42) # For reproducibility

        # Temperature is generally rising 1 deg/sec, but with noise
        # Pressure is generally stable at 10, but with noise
        for i in range(100):
            # 10ms intervals
            t = i * 0.01
            # Temp rises 1 deg/sec on average, +/- 0.5 noise
            temp = 100 + (t * 1.0) + (random.random() - 0.5)
            # Pressure is stable, +/- 0.5 noise
            pressure = 10 + (random.random() - 0.5)
            monitor.add_reading(temperature=temp, pressure=pressure, timestamp=t)

        # Due to the small history_len=10 (0.1 seconds of data at 10ms intervals),
        # the noise (+/- 0.5) completely overwhelms the signal (0.1 temp rise over 0.1s).
        # The current implementation calculates rate just using the first and last point in the history window.
        # It's highly likely to fail or be erratic. We will just assert that it doesn't crash,
        # but document this limitation. To make it pass consistently, we would need a larger history window
        # or a filtering algorithm. For now, we just test that it runs.
        monitor.is_dry()

    def test_low_moisture_sample(self):
        # Simulating low-moisture samples (e.g., bread charring) where pressure does not rise significantly initially
        # This highlights a flaw in the basic algorithm where low initial moisture could trigger a false positive
        monitor = DrynessMonitor(min_temp_rate=0.5, max_pressure_rate=0.1)

        # Simulating heating a low-moisture sample (temp rises, pressure stays close to 0)
        # Even though the sample might not be completely dry, it hasn't generated enough steam
        # to cross any "wetness" pressure threshold
        for i in range(5):
            monitor.add_reading(temperature=100 + i*1.0, pressure=0 + i*0.01, timestamp=i)

        # The algorithm is likely to wrongly assert it is 'dry' immediately because the pressure change is so low
        # We write this test to document the current algorithm's behavior (which might need to be fixed later)
        # and to ensure any future improvements handle this edge case.
        # Currently, it WILL return True (dry).
        self.assertTrue(monitor.is_dry(), "Currently returns true immediately for low-moisture samples (algorithm limitation)")

if __name__ == '__main__':
    unittest.main()