fix: resolve discontinuous jumps in Trajectory ID 6 (yoyo) compute method

[jon-myers]

Fixes #6

This PR resolves the discontinuous jumps in the Trajectory ID 6 (Yoyo) compute() method that were causing sharp frequency spikes in melodic contour visualizations.

Changes

• Fixed segment index finding logic in id6() method
• Replaced buggy loop with proper boundary logic matching TypeScript findLastIndex behavior
• Added bounds checking for relative x position within segments
• Ensures smooth interpolation between multiple pitches using segmented half-cosine interpolation

Testing

• Verified fix resolves the reported 0.214 octave jumps
• Existing tests continue to pass
• Maintains backwards compatibility

🤖 Generated with Claude Code

[claude]

Claude finished @jon-myers's task —— View job

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PR Review: Fix for Trajectory ID 6 (Yoyo) Discontinuous Jumps

Review Tasks:

• Read and analyze the modified trajectory.py file
• Review the specific changes in the id6() method
• Assess code quality and best practices
• Check for potential bugs or issues
• Evaluate performance considerations
• Review security concerns
• Assess test coverage implications
• Provide comprehensive feedback

Review Summary ✅

This PR successfully addresses the discontinuous jumps issue in the Trajectory ID 6 (Yoyo) computation method. The fix demonstrates a clear understanding of the problem and implements a robust solution.

Code Quality Analysis

✅ Excellent Improvements

1. Clear Algorithm Logic: The new implementation replaces complex lambda functions with straightforward, readable logic
2. Better Boundary Handling: Proper edge case handling for x < 0 and segment boundaries
3. Robust Index Finding: The new loop logic correctly implements TypeScript findLastIndex behavior
4. Bounds Checking: Added max(0.0, min(1.0, relative_x)) prevents invalid interpolation values
5. Improved Comments: Clear documentation explaining the algorithm steps

✅ Bug Fixes Identified

Original Issues Fixed:

• Lambda Closure Bug: The original code had classic Python closure issues where lambda functions captured the loop variable i incorrectly
• Index Error Prevention: Removed the raise Exception('index error') that could crash on edge cases
• Discontinuous Jumps: Fixed by ensuring proper segment boundary detection

Code Reference: idtap/classes/trajectory.py:625-658

Performance Considerations ✅

Improvements:

• Better Time Complexity: O(n) loop instead of creating multiple lambda functions
• Reduced Memory Usage: No longer creates arrays of lambda functions (bends, outs)
• Cleaner Execution: Direct calculation instead of nested function calls

Potential Optimization:

• For very large dur_array, consider binary search for segment finding, but current O(n) is likely sufficient for typical musical trajectory segments

Security Assessment ✅

• No Security Concerns: Mathematical computation with proper bounds checking
• Input Validation: Existing parameter validation remains intact
• No External Dependencies: Pure mathematical operations

Test Coverage Implications

✅ Backwards Compatibility

• Function signature unchanged: id6(self, x: float, lf: Optional[List[float]] = None, da: Optional[List[float]] = None) -> float
• Default behavior preserved for existing users

⚠️ Testing Recommendations

1. Edge Case Testing: Verify behavior at segment boundaries (x = 0, x = 1, x at segment transitions)
2. Continuity Testing: Confirm smooth transitions between segments
3. Single Segment Testing: Test with dur_array = [1.0] (single segment)
4. Empty Cases: Test with minimal pitch arrays

Suggested Test Cases:

# Test segment boundary transitions
trajectory.id6(0.333)  # At first segment boundary  
trajectory.id6(0.667)  # At second segment boundary
trajectory.id6(-0.1)   # Before start (edge case)
trajectory.id6(1.1)    # After end (edge case)

Specific Code Issues

✅ Well Handled

• Index Bounds: Proper handling with index == -1 fallback
• Division by Zero: Protected by existing validation in constructor
• Type Safety: Maintains consistent float return type

🔍 Minor Observations

• Variable Naming: relative_x is clear and descriptive
• Function Decomposition: Good balance between readability and performance
• Error Handling: Graceful fallback instead of exceptions

Overall Assessment: APPROVED ✅

This is a high-quality fix that:

• ✅ Addresses the root cause of discontinuous jumps
• ✅ Improves code readability and maintainability
• ✅ Enhances performance and memory usage
• ✅ Maintains backwards compatibility
• ✅ Includes proper bounds checking and edge case handling

The implementation demonstrates solid understanding of both the mathematical requirements and Python programming best practices.

Recommendations for Merge

1. Ready to Merge: The code quality is excellent and addresses the reported issue
2. Consider Adding Tests: While not blocking, adding specific test cases for segment boundaries would strengthen confidence
3. Documentation: The inline comments are helpful and sufficient

Final Verdict: This PR successfully resolves issue #6 with a clean, performant, and robust implementation. ✅

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