Catalyst.jl
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SciML
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
Since the latter is more likely to be updated as things change in MTK.
I am new to Julia, so maybe I am overseeing an important point here. I am trying to fit parameters to multiple experiments. Fitting it to one set of experimental...
https://github.com/SciML/Catalyst.jl/pull/1070 disabled StructuralIdentifiability tests and added a warning in the docs about it having issues. Once they are resolved we should reenable the tests.
`BifurcationProblem` does not support symbolic indexing and as a result, MTK (somewhat hackily) just removes `sys.index_cache` in the `BifurcationProblem` constructor to force `split = false` behavior. However, with `complete` now...
```julia rn1 = @reaction_network rn_observed begin @variables X1(t) @observables X2(t) ~ X1(t) k, A --> 0 end ``` when expanded gives ```julia :(Catalyst.complete(begin var"#7616#t" = Catalyst.default_t() begin var"#7617###1945" = begin...
Since tests are now passing and I am not that familiar with the code, I haven't updated any spatial related codes to remove scalarization of parameters in https://github.com/SciML/Catalyst.jl/pull/1052. This should...
```julia ┌ Warning: Initialization system is overdetermined. 1 equations for 0 unknowns. Initialization will default to using least squares. To suppress this warning pass warn_initialize_determined = false. To make this...
We should drop our test dependencies on OrdinaryDiffEq and switch to the slimmer packages for solvers we actually use there (mainly Tsit5 I think). This should help reduce build times...
See failures and comments in https://github.com/SciML/Catalyst.jl/pull/1048
It seems like some users, especially anyone with a longer model, may prefer to have the DSL require all species, parameters, and variables to be pre-declared (to help with catching...