Improve Parsing with Symbolics

.gitignore

@@ -8,4 +8,4 @@ Manifest.toml
 docs/build/*
 scratch
 scratch/*
-.DS_store
+.DS_store

Project.toml

@@ -27,6 +27,7 @@ MonteCarloMeasurements = "0987c9cc-fe09-11e8-30f0-b96dd679fdca"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
+PDEBase = "a7812802-0625-4b9e-961c-d332478797e5"
 QuasiMonteCarlo = "8a4e6c94-4038-4cdc-81c3-7e6ffdb2a71b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
@@ -77,6 +78,7 @@ Reexport = "1.0"
 RuntimeGeneratedFunctions = "0.5"
 SafeTestsets = "0.1"
 SciMLBase = "2"
+PDEBase = "0.1.7"
 Statistics = "1"
 StochasticDiffEq = "6.13"
 SymbolicUtils = "1"

src/NeuralPDE.jl

@@ -17,35 +17,44 @@ using QuasiMonteCarlo: LatinHypercubeSample
 import QuasiMonteCarlo
 using RuntimeGeneratedFunctions
 using SciMLBase
+using PDEBase
+using PDEBase: cardinalize_eqs!, get_depvars, get_indvars, differential_order
 using Statistics
 using ArrayInterface
 import Optim
-using Symbolics: wrap, unwrap, arguments, operation
+using DomainSets
+using Symbolics
+using Symbolics: wrap, unwrap, arguments, operation, symtype, @arrayop, Arr
 using SymbolicUtils
 using AdvancedHMC, LogDensityProblems, LinearAlgebra, Functors, MCMCChains
-using MonteCarloMeasurements: Particles
-using ModelingToolkit: value, nameof, toexpr, build_expr, expand_derivatives, Interval, infimum, supremum
-import DomainSets
-using DomainSets: Domain, ClosedInterval, AbstractInterval, leftendpoint, rightendpoint, ProductDomain
-using SciMLBase: @add_kwonly, parameterless_type
-using UnPack: @unpack
+using MonteCarloMeasurements
+using SymbolicUtils.Code
+using SymbolicUtils: Prewalk, Postwalk, Chain
+import ModelingToolkit: value, nameof, toexpr, build_expr, expand_derivatives
+import DomainSets: Domain, ClosedInterval
+import ModelingToolkit: Interval, infimum, supremum #,Ball
+import SciMLBase: @add_kwonly, parameterless_type
+import UnPack: @unpack
 import ChainRulesCore, Lux, ComponentArrays
-using ChainRulesCore: @non_differentiable
+import ChainRulesCore: @non_differentiable, @ignore_derivatives
 
 RuntimeGeneratedFunctions.init(@__MODULE__)
 
-abstract type AbstractPINN end
+abstract type AbstractPINN <: SciMLBase.AbstractDiscretization end
 
 abstract type AbstractTrainingStrategy end
+abstract type AbstractGridfreeStrategy <: AbstractTrainingStrategy end
 
 include("pinn_types.jl")
+include("eq_data.jl")
 include("symbolic_utilities.jl")
 include("training_strategies.jl")
 include("adaptive_losses.jl")
 include("ode_solve.jl")
 # include("rode_solve.jl")
 include("dae_solve.jl")
 include("transform_inf_integral.jl")
+include("loss_function_generation.jl")
 include("discretize.jl")
 include("neural_adapter.jl")
 include("advancedHMC_MCMC.jl")