Create wrapper for square-root Kalman filter #97
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| ) | ||
| μ, Σ = GaussianDistributions.pair(state) | ||
| H, c, R = calc_params(model.obs, iter; kwargs...) | ||
| !all(c .== 0) && error("SKRF doesn't current support non-zero c") |
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| !all(c .== 0) && error("SKRF doesn't current support non-zero c") | |
| c != zero(μ) && error("SKRF doesn't current support non-zero c") |
I doubt this gets us any speed up, but should guarantee type stability in 99% of cases.
| ) | ||
| μ, Σ = GaussianDistributions.pair(state) | ||
| A, b, Q = calc_params(model.dyn, iter; kwargs...) | ||
| !all(b .== 0) && error("SKRF doesn't current support non-zero b") |
There was a problem hiding this comment.
Suggested change
| !all(b .== 0) && error("SKRF doesn't current support non-zero b") | |
| b != zero(μ) && error("SKRF doesn't current support non-zero b") |
same as before
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| # @test isa(srkf_state.μ, SVector) | ||
| # @test isa(srkf_state.Σ.mat, SMatrix) |
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what's up with the unit testing?
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This PR adds a wrapper for KalmanFilters.jl's square-root Kalman filter and corresponding unit tests. Solves #5
It's works fine for regular arrays but when static arrays are inputted, the outputs become regular arrays. This is an upstream issue that I'll create a PR for.