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added: new KalmanCovariance struct to handle covariance sparsity efficiently#216

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franckgaga merged 11 commits into
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cov_sparsity
Jun 14, 2025
Merged

added: new KalmanCovariance struct to handle covariance sparsity efficiently#216
franckgaga merged 11 commits into
mainfrom
cov_sparsity

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@franckgaga

@franckgaga franckgaga commented Jun 12, 2025

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Similarly to #202 for the objective function weights in MPCs, a new KalmanCovariance parametric struct is created. First, it avoid duplicate code in the constructor of the Kalman filters. Second, two new parameters are introduced to preserve special types like Diagonal{NT, Vector{NT}}. It will also preserves other special types like SparseMatrixCSC. The performance advantages will be mainly visible for the MovingHorizontEstimator with nonlinear plant models, since the objective is computed with e.g. dot(V̂, invR̂_Nk, V̂) and the operation is faster when invR̂_Nk is a Diagonal matrix.

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codecov-commenter commented Jun 13, 2025

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Codecov Report

❌ Patch coverage is 95.27027% with 7 lines in your changes missing coverage. Please review.
✅ Project coverage is 98.61%. Comparing base (336eaf3) to head (73e36ce).
⚠️ Report is 752 commits behind head on main.

Files with missing lines Patch % Lines
src/estimator/construct.jl 83.72% 7 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #216      +/-   ##
==========================================
- Coverage   98.70%   98.61%   -0.09%     
==========================================
  Files          26       26              
  Lines        4308     4327      +19     
==========================================
+ Hits         4252     4267      +15     
- Misses         56       60       +4     

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@franckgaga franckgaga merged commit e7c8c89 into main Jun 14, 2025
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@franckgaga franckgaga deleted the cov_sparsity branch June 14, 2025 00:41
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2 participants