ModelingToolkit.jl
ModelingToolkit.jl copied to clipboard
SciML
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and...
Using the `idxs` keyword on solutions to index many symbols will crash Julia completely (terminates Julia and underlying terminal process before any stacktrace or segfault display for me). Maybe related...
If i try to get a numerical solution to this ODE system i don't get the correct result. ```julia # This code is inspired by the one found as an...
MWE: ```julia julia> @variables t F(t)[1:2] = [0.0, 0.0] julia> @parameters m = 1.0 julia> collect(F ./ m) ``` Error: ``` ERROR: MethodError: no method matching /(::Term{Real, Base.ImmutableDict{DataType, Any}}, ::Base.RefValue{Sym{Real,...
Take a look at this slightly modified code from the tutorial: ```julia using ModelingToolkit, Plots, DifferentialEquations @variables t @connector function Pin(;name) sts = @variables v(t)=1.0 i(t)=1.0 [connect = Flow] ODESystem(Equation[],...
This is something that came up as I was looking at adding events into other system types. Maybe this isn't an easy fix, or desired, but right now when new...
Hi, The input/output causality specifiers do not seem to work properly. Or it is rather an equation system simplification issue given the time when the error occurs. The following test...
Hi, If `r=0.0`, the following model does not actually have any states, but `states(ss)` reports it has one, `capacitor.vc`. No wonder since `structural_simplify` analyzes only the system structure, doesn't it?...
The following code used to run in MTK a couple of versions ago, but have since been broken. It recently started producing a new error: > Observed variables depends on...
I am trying to pass in a vector of parameters in a system of ODEs. This will be especially useful when trying to integrate neural networks with MTK models. I...
I am trying to introduce directionality in an event trigger (i.e. only fire as either up or downpass). IIUC [this](https://diffeq.sciml.ai/stable/features/callback_functions/#SciMLBase.ContinuousCallback) correctly it should be possible in principle with `affect_neg!=nothing` in...