Remove stale dependencies (#432)

* remove stale dependencies

* don't need OrdinaryDiffEqTsit5 either

Project.toml

@@ -10,55 +10,31 @@ ChainRules = "082447d4-558c-5d27-93f4-14fc19e9eca2"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
-DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
-DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
-DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 ExponentialUtilities = "d4d017d3-3776-5f7e-afef-a10c40355c18"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
-Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
 GraphDynamics = "bcd5d0fe-e6b7-4ef1-9848-780c183c7f4c"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
-HypothesisTests = "09f84164-cd44-5f33-b23f-e6b0d136a0d5"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
-JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
-MAT = "23992714-dd62-5051-b70f-ba57cb901cac"
-MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2"
-MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
 MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 ModelingToolkitStandardLibrary = "16a59e39-deab-5bd0-87e4-056b12336739"
 MuladdMacro = "46d2c3a1-f734-5fdb-9937-b9b9aeba4221"
-NaNStatistics = "b946abbf-3ea7-4610-9019-9858bfdeaf2d"
-Optim = "429524aa-4258-5aef-a3af-852621145aeb"
-Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
-OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
-OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Peaks = "18e31ff7-3703-566c-8e60-38913d67486b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
-Requires = "ae029012-a4dd-5104-9daa-d747884805df"
-SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
-Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
-SignalAnalysis = "df1fea92-c066-49dd-8b36-eace3378ea47"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
-SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
-StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StochasticDiffEq = "789caeaf-c7a9-5a7d-9973-96adeb23e2a0"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 ToeplitzMatrices = "c751599d-da0a-543b-9d20-d0a503d91d24"
-Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
-Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [weakdeps]
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
@@ -72,42 +48,26 @@ CairoMakie = "0.11"
 Combinatorics = "1"
 DSP = "0.7"
 DataFrames = "1.3"
-DiffEqBase = "6"
 DifferentialEquations = "7"
 Distributions = "0.25.102"
 ExponentialUtilities = "1"
 Flux = "0.14"
 ForwardDiff = "0.10"
-Glob = "1"
-Graphs = "1"
 GraphDynamics = "0.1.2"
-HypothesisTests = "0.11"
+Graphs = "1"
 Interpolations = "0.14, 0.15"
-JLD2 = "0.4"
-MAT = "0.10"
-MLJ = "0.20"
 MetaGraphs = "0.7"
 ModelingToolkit = "9.34"
 ModelingToolkitStandardLibrary = "2"
 MuladdMacro = "0.2"
-NaNStatistics = "0.6"
-Optim = "1"
-Optimization = "3"
-OptimizationOptimJL = "0.2"
-OptimizationOptimisers = "0.2"
-OrderedCollections = "1.4"
-OrdinaryDiffEq = "6"
+OrderedCollections = "1.6.3"
 RecursiveArrayTools = "2, 3"
 Reexport = "1.0"
 SafeTestsets = "0.1"
-SignalAnalysis = "0.6"
-StaticArrays = "1.0"
-StatsBase = "0.34"
-StochasticDiffEq = "6"
 ToeplitzMatrices = "0.8"
 Tracker = "0.2"
 Turing = "0.29"
-julia = "1.8"
+julia = "1.10"
 
 [extras]
 CPUSummary = "2a0fbf3d-bb9c-48f3-b0a9-814d99fd7ab9"
@@ -133,4 +93,4 @@ Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
 Turing = "fce5fe82-541a-59a6-adf8-730c64b5f9a0"
 
 [targets]
-test = ["DifferentialEquations", "LinearAlgebra", "ForwardDiff", "Distributions", "Flux", "Random", "SparseArrays", "Optim", "Optimization", "OptimizationOptimJL", "OptimizationOptimisers", "OrdinaryDiffEq", "StochasticDiffEq", "SafeTestsets", "Turing", "Test", "Tracker"]
+test = ["DifferentialEquations", "LinearAlgebra", "ForwardDiff", "Distributions", "Flux", "Random", "SparseArrays", "MAT", "Optim", "Optimization", "OptimizationOptimJL", "OptimizationOptimisers", "OrdinaryDiffEq", "StochasticDiffEq", "SafeTestsets", "Turing", "Test", "Tracker"]

src/GraphDynamicsInterop/GraphDynamicsInterop.jl

@@ -99,14 +99,6 @@ using ModelingToolkit:
     ODESystem,
     getdefault
 
-using StaticArrays:
-    StaticArrays,
-    StaticArray,
-    SMatrix,
-    MMatrix,
-    SVector,
-    MVector
-
 using ModelingToolkit:
     get_ps,
     get_noiseeqs,

src/Neuroblox.jl

@@ -1,9 +1,5 @@
 module Neuroblox
 
-if !isdefined(Base, :get_extension)
-    using Requires
-end
-
 using Reexport
 @reexport using ModelingToolkit
 const t = ModelingToolkit.t_nounits
@@ -22,22 +18,20 @@ ForwardDiff.can_dual(::Type{Complex{Float64}}) = true
 using ChainRules: _eigen_norm_phase_fwd!
 
 using LinearAlgebra
-using MKL
 using ToeplitzMatrices: Toeplitz
 using ExponentialUtilities: exponential!
 
 using DSP, Statistics
-using OrdinaryDiffEq
-using DifferentialEquations
+
 using Interpolations
 using Random
 using OrderedCollections
-using DelayDiffEq
 
 using StatsBase: sample
 using Distributions
 
-using SciMLBase: AbstractSolution
+using SciMLBase: SciMLBase, AbstractSolution, solve, remake
+
 
 using ModelingToolkit: get_namespace, get_systems, isparameter,
                     renamespace, namespace_equation, namespace_parameters, namespace_expr,
@@ -46,10 +40,8 @@ import ModelingToolkit: inputs, nameof, outputs, getdescription
 
 using Symbolics: @register_symbolic, getdefaultval
 
-using DelimitedFiles: readdlm
 using CSV: read
 using DataFrames
-using JLD2
 
 using Peaks: argmaxima, peakproms!, peakheights!, findmaxima
 using SparseArrays
@@ -216,14 +208,9 @@ function __init__()
     #if Preferences.@load_preference("PrintLicense", true)
         print_license()
     #end
-
-    @static if !isdefined(Base, :get_extension)
-        @require Makie="ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a" begin
-            include("../ext/MakieExtension.jl")
-        end
-    end
 end
 
+
 export JansenRitSPM12, next_generation, qif_neuron, if_neuron, hh_neuron_excitatory, 
     hh_neuron_inhibitory, van_der_pol, Generic2dOscillator
 export HHNeuronExciBlox, HHNeuronInhibBlox, IFNeuron, LIFNeuron, QIFNeuron, IzhikevichNeuron, LIFExciNeuron, LIFInhNeuron,