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Fix 291 #294

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Fix 291 #294

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b677bad
add test for NaN with repeated vector input
hv10 Nov 22, 2024
629b108
relax test requirement
hv10 Nov 22, 2024
b2ddaf3
fix "Encountering NaN when fitting Vectors with CCIPCA" #291
hv10 Nov 22, 2024
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4 changes: 2 additions & 2 deletions src/stats/pca.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -100,12 +100,12 @@ function _fit!(o::CCIPCA, x::AbstractVector{<:Real})
@inbounds for i in 1:outdim(o)
if i == n
o.lambda[i] = norm(o.xi)
o.U[:, i] = o.xi / o.lambda[i]
o.U[:, i] = o.xi / (o.lambda[i]+OnlineStats.ϵ)
break
end
o.v = (1-f) * o.lambda[i] * o.U[:, i] + f * dot(o.U[:, i], o.xi) * o.xi
o.lambda[i] = norm(o.v)
o.U[:, i] = o.v/o.lambda[i]
o.U[:, i] = o.v/(o.lambda[i]+OnlineStats.ϵ)
o.xi = o.xi .- (dot(o.U[:, i], o.xi) * o.U[:, i])
end
o.n = n
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12 changes: 11 additions & 1 deletion test/test_ccipca.jl
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Expand Up @@ -17,7 +17,7 @@
# first vector added goes straight into the projection matrix:
u1 = rand(4)
fit!(o, u1)
@test o[1] == u1/norm(u1)
@test isapprox(o[1], u1/norm(u1); atol=1e-6)
@test o[2] == zeros(Float64, 4)

# We can get eigen-values individually or in array:
Expand Down Expand Up @@ -177,3 +177,13 @@ end
end
end
end

@testset "Is CCIPCA resistant against accidental misuse?" begin
o = CCIPCA(2, 4)
u1 = rand(4)
# if we repeatedly fit with the same vector
# we should not fail by having an eigenval of NaN
fit!(o, u1)
fit!(o, u1)
@test !any(isnan.(OnlineStats.eigenvalues(o)))
end