Reuse solver residual in calibrator#231
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The block update_gradient methods previously hand-coded the residual r = E*ydot + F*y + c, duplicating the residual the solver already assembles in SparseSystem::update_residual (r = -C - E*ydot - F*y). Reuse the solver residual during calibration and have update_gradient assemble only the Jacobian of the residual with respect to the parameters. The Jacobian signs are flipped to match the solver's sign convention; the overall sign cancels in the LM normal equations, so the optimization is unchanged. - LevenbergMarquardtOptimizer now sets the model parameters to the current alpha, assembles E/F once, and computes the residual per observation via update_solution + update_residual. - calibrate registers the parameters with the model so the solver's assembly can read their values. - Blocks without calibration parameters (e.g. a normal junction) are skipped in the Jacobian loop, so Junction::update_gradient is removed. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
…ndeleev-a7e408 # Conflicts: # src/model/Junction.h # src/optimize/LevenbergMarquardtOptimizer.cpp # src/optimize/calibrate.cpp
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Current situation
Closes #153.
Release Notes
The calibrator reuses the code from the solver to calculate the residual, which previously needed to be reimplemented for each block. This makes the code more straightforward and makes calibrating new blocks easier.
Documentation
No change in functionality
Testing
Should work as before
Code of Conduct & Contributing Guidelines