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Utilise AbstractGPs.TestUtils #206

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Jul 22, 2021
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Utilise AbstractGPs.TestUtils #206

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36 changes: 2 additions & 34 deletions test/gaussian_process_probabilistic_programme.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -82,40 +82,8 @@
GPPPInput(:f1, randn(4)),
),
]

atol=1e-9
rtol=1e-9

m = mean(f, x0)
@test m isa AbstractVector{<:Real}
@test length(m) == length(x0)

@assert length(x0) ≠ length(x1)

# Check that unary cov is consistent with binary cov and conforms to the API
K_x0 = cov(f, x0)
@test K_x0 isa AbstractMatrix{<:Real}
@test size(K_x0) == (length(x0), length(x0))
@test K_x0 ≈ cov(f, x0, x0) atol=atol rtol=rtol
@test minimum(eigvals(K_x0)) > -atol
@test K_x0 ≈ K_x0' atol=atol rtol=rtol

# Check that single-process binary cov is consistent with single-process binary-cov
K_x0_x1 = cov(f, x0, x1)
@test K_x0_x1 isa AbstractMatrix{<:Real}
@test size(K_x0_x1) == (length(x0), length(x1))

# Check that single-process binary var is consistent.
K_x0_x0_diag = var(f, x0, x0)
@test K_x0_x0_diag isa AbstractVector{<:Real}
@test length(K_x0_x0_diag) == length(x0)
@test K_x0_x0_diag ≈ diag(cov(f, x0, x0)) atol=atol rtol=rtol

# Check that unary var conforms to the API and is consistent with unary cov
K_x0_diag = var(f, x0)
@test K_x0_diag isa AbstractVector{<:Real}
@test length(K_x0_diag) == length(x0)
@test K_x0_diag ≈ diag(cov(f, x0)) atol=atol rtol=rtol
rng = MersenneTwister(123456)
AbstractGPs.TestUtils.test_internal_abstractgps_interface(rng, f, x0, x1)
end

@timedtestset "gppp macro" begin
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5 changes: 1 addition & 4 deletions test/gp/gp.jl
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Expand Up @@ -11,10 +11,7 @@

@test mean(f, x) == AbstractGPs._map(m, x)
@test cov(f, x) == kernelmatrix(k, x)
@test var(f, x) == diag(cov(f, x))
@test cov(f, x, x) == kernelmatrix(k, x, x)
@test cov(f, x, x′) == kernelmatrix(k, x, x′)
@test cov(f, x, x′) ≈ cov(f, x′, x)'
AbstractGPs.TestUtils.test_internal_abstractgps_interface(rng, f, x, x′)
end

# Test the creation of indepenent GPs.
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