gerlero/fronts.jl

Nonlinear diffusion problems in Julia

Fronts, at the speed of Julia ⚡️

This is the (fully native) Julia version of our numerical package for nonlinear diffusion problems, also available as a Python library.

julia> using Fronts

julia> D(u) = u^4
D (generic function with 1 method)

julia> eq = DiffusionEquation(D)
∂u/∂t = ∂(D(u)*∂u/∂r)/∂r

julia> prob = DirichletProblem(eq, i=0.1, b=1)
⎧ ∂u/∂t = ∂(D(u)*∂u/∂r)/∂r, r>0,t>0
⎨ u(r,0) = 0.1, r>0
⎩ u(0,t) = 1.0, t>0

julia> u = solve(prob)
Solution u after 10 iterations
retcode: Success
ub = 1.0
du/do|b = -0.28388671875000004
ui = 0.10006060603081587

julia> u(0.25, 2) # Evaluate the solution anywhere and at any time
0.9440546607878473

julia> d_dr(u, 0.25, 2) # Obtain derivatives
-0.25038534184881966

julia> flux(u, 0.25, 2) # Obtain the flux
0.19888290889257723

   

fronts.jl's Issues

Function transform not exported

The transform function is documented but not exported.

Doc page missing from index

A page is currently missing from the table of contents on the docs homepage.

Slow precompilation in Julia 1.5

The precompilation step when importing the package for the first time is taking very long (about 15-30 minutes) in Julia 1.5.4.

This was not a problem before and it also does not occur with Julia 1.6.2, where the precompilation step happens when the package is installed and as expected it is much faster.

The issue can be observed in the execution times of CI jobs (compare https://github.com/gerlero/Fronts.jl/runs/2777286953 and https://github.com/gerlero/Fronts.jl/runs/3174472477). I was also able to reproduce this behavior locally.

Brooks and Corey default argument inconsistency.

D.brookscorey l parameter should default to 1 (as docs indicate) but it currently defaults to 0.5.

TagBot trigger issue

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Plot recipe fails with MethodError

As in examples/exact.jl.
SciML/OrdinaryDiffEq.jl#1584

Failing CI tests

https://github.com/gerlero/Fronts.jl/actions/runs/3498668705/jobs/5859328096

Function monotonicity not exported

The monotonicity function is documented but by mistake it is not being exported.