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Improve types #101

Merged
merged 5 commits into from
Oct 2, 2019
Merged

Improve types #101

merged 5 commits into from
Oct 2, 2019

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guilhermebodin
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@codecov-io
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codecov-io commented Oct 2, 2019

Codecov Report

Merging #101 into master will not change coverage.
The diff coverage is 100%.

Impacted file tree graph

@@           Coverage Diff           @@
##           master     #101   +/-   ##
=======================================
  Coverage   95.69%   95.69%           
=======================================
  Files          13       13           
  Lines         488      488           
=======================================
  Hits          467      467           
  Misses         21       21
Impacted Files Coverage Δ
src/prints.jl 100% <ø> (ø) ⬆️
src/forecast.jl 100% <ø> (ø) ⬆️
src/utils.jl 95.34% <ø> (ø) ⬆️
src/structures.jl 100% <100%> (ø) ⬆️
src/kalman.jl 96.49% <100%> (ø) ⬆️
src/random_seeds_lbfgs.jl 100% <100%> (ø) ⬆️
src/StateSpaceModels.jl 83.33% <100%> (ø) ⬆️
src/univariate_kalman.jl 83.33% <100%> (ø) ⬆️
src/diagnostics.jl 100% <100%> (ø) ⬆️
src/models.jl 100% <100%> (ø) ⬆️
... and 3 more

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sqrtQ[findall(isequal(1), sqrtQ)] = psi[(unknownsH+1):Int(unknownsH + (r/p)*(p*(p + 1)/2))]

# Obtain full matrices
H = gram(sqrtH)
Q = gram(sqrtQ)

return H, Q
return T.(H), T.(Q)
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This is probably affecting performance as we're doing a cast in every estimation step, perhaps there's a better way?

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hmm true, I think it does not make much difference but let us check it

@raphaelsaavedra
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We might want to benchmark this PR to see how much these changes have affected performance

@guilhermebodin
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Some quick benchmarking showed me that the code has the same performace. We could study how MOI did for benchmarking performance in their testset

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3 participants