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Test master #928

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d2728e0
Test master
ChrisRackauckas Mar 6, 2025
4771c69
Update BPINN_tests.jl
ChrisRackauckas Mar 6, 2025
4c18b29
Update BPINN_PDE_tests.jl
ChrisRackauckas Mar 6, 2025
59f261e
Update pino_ode.md
ChrisRackauckas Mar 8, 2025
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -17,6 +17,7 @@ compared with classical methods.

## Installation


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[JuliaFormatter] reported by reviewdog 🐶

Suggested change

Assuming that you already have Julia correctly installed, it suffices to install NeuralPDE.jl in the standard way, that is, by typing `] add NeuralPDE`. Note:
to exit the Pkg REPL-mode, just press <kbd>Backspace</kbd> or <kbd>Ctrl</kbd> + <kbd>C</kbd>.

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4 changes: 2 additions & 2 deletions docs/src/tutorials/pino_ode.md
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Expand Up @@ -21,11 +21,11 @@ u0 = 1.0
prob = ODEProblem(equation, u0, tspan)

# Set the number of parameters for the ODE
number_of_parameter = 3
number_of_parameters = 3
# Define the DeepONet architecture for the PINO
deeponet = NeuralOperators.DeepONet(
Chain(
Dense(number_of_parameter => 10, Lux.tanh_fast), Dense(10 => 10, Lux.tanh_fast), Dense(10 => 10)),
Dense(number_of_parameters => 10, Lux.tanh_fast), Dense(10 => 10, Lux.tanh_fast), Dense(10 => 10)),
Chain(Dense(1 => 10, Lux.tanh_fast), Dense(10 => 10, Lux.tanh_fast),
Dense(10 => 10, Lux.tanh_fast)))

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2 changes: 1 addition & 1 deletion test/BPINN_PDE_tests.jl
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Expand Up @@ -30,7 +30,7 @@
u_predict = pmean(sol1.ensemblesol[1])

# absol tests
@test mean(abs, u_predict .- u_real) < 5e-2
@test mean(abs, u_predict .- u_real) < 7e-2
end

@testitem "BPINN PDE II: 1D ODE" tags=[:pdebpinn] begin
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4 changes: 2 additions & 2 deletions test/BPINN_tests.jl
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Expand Up @@ -44,8 +44,8 @@
meanscurve = prob.u0 .+ (t .- prob.tspan[1]) .* luxmean

# --------------------- ahmc_bayesian_pinn_ode() call
@test mean(abs.(x̂ .- meanscurve)) < 0.05
@test mean(abs.(physsol1 .- meanscurve)) < 0.005
@test mean(abs.(x̂ .- meanscurve)) < 0.06
@test mean(abs.(physsol1 .- meanscurve)) < 0.006

#--------------------- solve() call
@test mean(abs.(x̂1 .- pmean(sol1lux.ensemblesol[1]))) < 0.025
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