# PRD: Enhanced Hysteresis Integration Tests with Threshold Assertions

This PRD builds upon the basic hysteresis integration test (GPM-061) by adding more sophisticated assertions to verify specific threshold crossing behaviors. This will improve confidence in the correctness of the hysteresis downscaling logic.

### GPM-062: Add Assertion for Upscaling Threshold Crossing
**Goal:** Verify that the downscaled value upscales when the original data crosses the upper threshold.
**Acceptance Criteria:**
- Given a mock data stream that starts below the upper threshold, the downscaled value remains unchanged.
- When the mock data stream crosses the upper threshold, the downscaled value immediately upscales to the original data value.
- The test should pass with configurable upper threshold values.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:** Add assertion for downscaling threshold crossing.

### GPM-063: Add Assertion for Downscaling Threshold Crossing
**Goal:** Verify that the downscaled value downscales when the original data crosses the lower threshold.
**Acceptance Criteria:**
- Given a mock data stream that starts above the lower threshold, the downscaled value remains unchanged.
- When the mock data stream crosses the lower threshold, the downscaled value immediately downscales to the original data value.
- The test should pass with configurable lower threshold values.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:** Add assertions for multiple threshold crossings (both up and down).

### GPM-064: Test Multiple Threshold Crossings
**Goal:** Verify that the downscaling/upscaling behavior functions correctly with multiple crossings of both upper and lower thresholds.
**Acceptance Criteria:**
- Given a mock data stream that crosses the upper and lower thresholds multiple times in a defined sequence, the downscaled value accurately reflects the expected hysteresis behavior at each crossing.
- The test should pass with different sequences of threshold crossings.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:** Implement negative tests to verify behavior when thresholds are invalid.

### GPM-065: Add Negative Tests for Invalid Thresholds
**Goal:** Verify that the system handles invalid threshold configurations gracefully (e.g., upper threshold less than lower threshold).
**Acceptance Criteria:**
- If the upper threshold is less than the lower threshold, the system should raise an appropriate exception or log an error message.
- The system should not crash or produce unexpected behavior with invalid threshold configurations.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:**  Add tests for edge cases around the threshold values (e.g., data exactly equal to the threshold).

### GPM-066: Add Tests for Edge Cases: Data Equals Threshold
**Goal:** Verify the system's behavior when the incoming data is exactly equal to either the upper or lower threshold.
**Acceptance Criteria:**
- If the current data value is exactly equal to the upper threshold, and the downscaled value is below, the downscaled value should upscale.
- If the current data value is exactly equal to the lower threshold, and the downscaled value is above, the downscaled value should downscale.
- If the current data value is equal to a threshold and no change is needed (e.g., already upscaled and data = upper threshold), no change should occur.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:** Add tests with noisy data near the thresholds.

### GPM-067: Add Tests with Noisy Data Near Thresholds
**Goal:** Verify the system's behavior with noisy data fluctuating around the upper and lower thresholds.
**Acceptance Criteria:**
- Given a mock data stream with noise that causes frequent small crossings of the thresholds, the downscaled value should exhibit stable behavior and avoid oscillating rapidly.
- The degree of noise should be configurable in the test.
**Files:** `tests/integration/test_hysteresis.py`
**Spawns:** Investigate performance implications of hysteresis downscaling.

### GPM-068: Performance Test Hysteresis Downscaling
**Goal:** Measure the performance of the hysteresis downscaling logic under various data rates and threshold configurations.
**Acceptance Criteria:**
- The downscaling process should not introduce significant latency or consume excessive resources (CPU, memory) under realistic data rates.
- Performance metrics should be collected and reported for different threshold configurations.
**Files:** `tests/performance/test_hysteresis_performance.py`, `docs/performance_report.md`
**Spawns:** Create a utility function for generating mock data streams.
