2025-08-15 08:24:01 +02:00
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---
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id: "implement-lfm-kernel-core"
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title: "Implement core LFM kernel functionality"
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status: "Proposed"
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priority: "High"
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created: "2025-08-15"
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last_updated: "2025-08-15"
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owner: "Neil Lawrence"
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2025-08-15 08:27:09 +02:00
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github_issue: ""
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dependencies: "design-modern-lfm-kernel"
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2025-08-15 08:24:01 +02:00
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tags:
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- lfm
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- kernel
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- implementation
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- core
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---
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# Implement core LFM kernel functionality
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## Description
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Implement the core LFM kernel class with basic functionality including kernel computation, parameter handling, and gradient computation.
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## Background
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- Design phase completed with modern LFM kernel architecture
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- Need to implement the core kernel computation methods
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- Should follow the mathematical foundations from the papers and MATLAB implementation
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## Implementation Tasks
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- [ ] Create `GPy.kern.LFM` class inheriting from appropriate base class
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- [ ] Implement parameter handling for mass, damper, spring, sensitivity, delay
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- [ ] Implement `K()` method for kernel matrix computation
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- [ ] Implement `Kdiag()` method for diagonal computation
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- [ ] Add parameter constraints and transformations
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- [ ] Implement basic gradient computation
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- [ ] Add support for different base kernels for latent functions
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## Core Methods to Implement
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- [ ] `__init__()` - Parameter initialization and validation
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- [ ] `K(X, X2=None)` - Kernel matrix computation
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- [ ] `Kdiag(X)` - Diagonal computation
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- [ ] `update_gradients_full()` - Gradient computation
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- [ ] `update_gradients_diag()` - Diagonal gradient computation
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- [ ] `parameters_changed()` - Parameter update handling
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## Acceptance Criteria
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- [ ] Core LFM kernel class implemented and functional
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- [ ] Basic kernel computation working correctly
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- [ ] Parameter handling and constraints implemented
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- [ ] Gradient computation implemented
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- [ ] Unit tests passing for core functionality
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- [ ] Integration with GPy's parameterization system
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## Implementation Notes
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- Follow the mathematical structure from the MATLAB implementation
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- Use GPy's parameterization system for constraints
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- Implement efficient computation methods
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- Ensure proper handling of edge cases and numerical stability
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- Add comprehensive docstrings and documentation
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## Related
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- CIP: 0001 (LFM kernel implementation)
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- Backlog: design-modern-lfm-kernel
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- Papers: Álvarez et al. (2009, 2012)
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