compat bump for BifurcationKit v0.1.5

Author: gszep

Project.toml

@@ -1,7 +1,7 @@
 name = "BifurcationInference"
 uuid = "7fe238d6-d31e-4646-aa16-9d8429fd6da8"
 authors = ["gszep <gregory.szep@gmail.com>"]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
@@ -17,7 +17,7 @@ SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 
 [compat]
-BifurcationKit = "0.1"
+BifurcationKit = "0.1.5"
 Flux = "0.12"
 ForwardDiff = "0.10"
 InvertedIndices = "1"

src/BifurcationInference.jl

@@ -108,8 +108,6 @@ module BifurcationInference
 					try
 						iterator = ContIterable( f, J, u, parameters, (@lens _.p), hyperparameters, linsolver, verbosity=verbosity)
 						for state ∈ iterator
-
-							computeEigenvalues!(iterator,state)
 							push!(branch,state)
 						end
 

test/runtests.jl

@@ -30,4 +30,17 @@ error_tolerance = 0.05
 			@test acos(x'y/(norm(x)*norm(y)))/π < error_tolerance
 		end
 	end
+end
+
+using Flux: Optimise
+@testset "Gradients" begin
+include("applied/two-state.jl")
+
+	parameters = ( θ=SizedVector{5}(0.5,0.5,0.5470,2.0,7.5), p=minimum(X.parameter) )
+	trajectory = train!( F, parameters, X;  iter=100, optimiser=Optimise.ADAM(0.01) )
+
+	steady_states = deflationContinuation(F,X.roots,(p=minimum(X.parameter),θ=trajectory[end]),getParameters(X))
+	bifurcations = unique([ s.z for branch ∈ steady_states for s ∈ branch if s.bif ], atol=3*step(X.parameter) )
+
+	@test length(bifurcations) == 2
 end