Experiment with factor gradients in solve #1825
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dehann
reviewed
May 26, 2024
| meas = cfm.meas | ||
| points = map(idx->p[idx], cfm.varOrderIdxs) | ||
| return cfm.sqrt_iΣ * cfm(meas, points...) | ||
| end | ||
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| function (cfm::CalcFactorResidual)(p::ArrayPartition) | ||
| points = map(idx->p.x[idx], cfm.varOrderIdxs) | ||
| return cfm.sqrt_iΣ * cfm(cfm.meas, points...) |
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Post AMP 41, we should look at consolidating this with the kernel evaluations done in AMP. Specifically this Malahanobis distance part. The reasoning is that we need to build belief trees on each clique and then be able to evaluation, which is exactly the same requirement as what this code here is doing.
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Draft PR not to lose possible value