modified: CHANGELOG.md

	modified:   Project.toml
	modified:   src/AutomationLabsSystems.jl
	modified:   src/main/main_systems.jl
	deleted:    src/sub/design_models.jl
	modified:   src/types/types.jl
	modified:   test/system_evaluation_test.jl

CHANGELOG.md

@@ -1,5 +1,12 @@
 # AutomationLabsSystems Changelog
 
+## v0.1.8
+
+* Remove dependencies AutomationLabsIdentification, MLJ, MLJMultivariateStatsInterface.
+* Remove design_models.jl.
+* Add type models for removing the AutomationLabsIdentification dependency.
+* proceed_system_model_evaluation types modifications.
+
 ## v0.1.7
 
 * Add dict for return for _extract_model_from_machine functions.

Project.toml

@@ -1,33 +1,30 @@
 name = "AutomationLabsSystems"
 uuid = "6d3dfdf0-e107-48c6-a6ff-eced1a5a9334"
 authors = ["Pierre BLAUD <pierre.blaud@ikmail.com> and contributors"]
-version = "0.1.7"
+version = "0.1.8"
 
 [deps]
-AutomationLabsIdentification = "48ff5a6f-d08b-4053-9585-6a9e3e078386"
 ControlSystems = "a6e380b2-a6ca-5380-bf3e-84a91bcd477e"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LazySets = "b4f0291d-fe17-52bc-9479-3d1a343d9043"
-MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
-MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
 MathematicalSystems = "d14a8603-c872-5ed3-9ece-53e0e82e39da"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 
 [compat]
-AutomationLabsIdentification = "0.2"
 ControlSystems = "1.6"
 Flux = "0.13"
 ForwardDiff = "0.10"
 LazySets = "2"
-MLJ = "0.19"
-MLJMultivariateStatsInterface = "0.5"
 MathematicalSystems = "0.13"
 NNlib = "0.8"
 julia = "1"
 
 [extras]
+AutomationLabsIdentification = "48ff5a6f-d08b-4053-9585-6a9e3e078386"
+MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
+MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test"]
+test = ["Test", "AutomationLabsIdentification", "MLJ", "MLJMultivariateStatsInterface"]

src/AutomationLabsSystems.jl

@@ -9,15 +9,13 @@
 module AutomationLabsSystems
 
 import MathematicalSystems
-import AutomationLabsIdentification
-import MLJ
-import MLJMultivariateStatsInterface
 import LazySets
 import Flux
 import ForwardDiff
 import NNlib
 import ControlSystems
 
+# Export methods
 export proceed_system
 export proceed_system_linearization
 
@@ -26,7 +24,6 @@ export proceed_system_model_evaluation
 
 # Load files
 include("types/types.jl")
-include("sub/design_models.jl")
 include("sub/design_systems.jl")
 include("main/main_systems.jl")
 

src/main/main_systems.jl

@@ -202,44 +202,57 @@ function proceed_system_model_evaluation(
     sublayers_name = collect(keys(system.f))
 
     if sublayers_name[1] == :fnn_input
-        model_type = AutomationLabsIdentification.Fnn()
+        #model_type = AutomationLabsIdentification.Fnn()
+        model_type = Fnn()
 
     elseif sublayers_name[1] == :icnn_input
-        model_type = AutomationLabsIdentification.Icnn()
+        #model_type = AutomationLabsIdentification.Icnn()
+        model_type = Icnn()
+
 
     elseif sublayers_name[1] == :resnet_input
-        model_type = AutomationLabsIdentification.ResNet()
+       #model_type = AutomationLabsIdentification.ResNet()
+        model_type = ResNet()
 
     elseif sublayers_name[1] == :polynet_input
-        model_type = AutomationLabsIdentification.PolyNet()
+        #model_type = AutomationLabsIdentification.PolyNet()
+        model_type = PolyNet()
 
     elseif sublayers_name[1] == :densenet_input
-        model_type = AutomationLabsIdentification.DenseNet()
+        #model_type = AutomationLabsIdentification.DenseNet()
+        model_type = DenseNet()
 
     elseif sublayers_name[1] == :rbf_input
-        model_type = AutomationLabsIdentification.Rbf()
+        #model_type = AutomationLabsIdentification.Rbf()
+        model_type = Rbf()
 
     elseif sublayers_name[1] == :neuralode_inner
-        model_type = AutomationLabsIdentification.NeuralODE()
+        #model_type = AutomationLabsIdentification.NeuralODE()
+        model_type = NeuralODE()
 
     elseif sublayers_name[1] == :rknn1_identity
-        model_type = AutomationLabsIdentification.Rknn1()
+        #model_type = AutomationLabsIdentification.Rknn1()
+        model_type = Rknn1()
 
     elseif sublayers_name[1] == :rknn2_identity
-        model_type = AutomationLabsIdentification.Rknn2()
+        #model_type = AutomationLabsIdentification.Rknn2()
+        model_type = Rknn2()
 
     elseif sublayers_name[1] == :rknn4_identity
-        model_type = AutomationLabsIdentification.Rknn4()
+        #model_type = AutomationLabsIdentification.Rknn4()
+        model_type = Rknn4()
 
     elseif sublayers_name[1] == :rnn_input
-        model_type = AutomationLabsIdentification.Rnn()
+        #model_type = AutomationLabsIdentification.Rnn()
+        model_type = Rnn()
 
     elseif sublayers_name[1] == :lstm_input
-        model_type = AutomationLabsIdentification.Lstm()
+        #model_type = AutomationLabsIdentification.Lstm()
+        model_type = Lstm()
 
     elseif sublayers_name[1] == :gru_input
-        model_type = AutomationLabsIdentification.Gru()
-
+        #model_type = AutomationLabsIdentification.Gru()
+        model_type = Gru()
     end
 
     return model_type

src/types/types.jl

@@ -71,3 +71,88 @@ struct DiscreteNonLinearModel <: AbstractModel
     nbr_state::Int
     nbr_input::Int
 end
+
+#This is a type reformulation to avoid AutomationLabsIdentification types deps
+"""
+    Fnn
+An feedforward neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Fnn <: AbstractModel end
+
+"""
+    Rbf
+An radial basis neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Rbf <: AbstractModel end
+
+"""
+    Icnn
+An input convex neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Icnn <: AbstractModel end
+
+"""
+    ResNet
+An residual layer network architecture type for dynamical system identification problem [ref].
+"""
+struct ResNet <: AbstractModel end
+
+"""
+    PolyNet
+An poly-inception network architecture type for dynamical system identification problem [ref].
+"""
+struct PolyNet <: AbstractModel end
+
+"""
+    DenseNet
+An densely connected network architecture type for dynamical system identification problem [ref].
+"""
+struct DenseNet <: AbstractModel end
+
+"""
+NeuralODE
+An neural neural network ODE architecture type for dynamical system identification problem [ref].
+"""
+struct NeuralODE <: AbstractModel end
+
+"""
+    Rknn1
+A runge-kutta neural neural network 1 architecture type for dynamical system identification problem [ref].
+"""
+struct Rknn1 <: AbstractModel end
+
+"""
+    Rknn2
+A runge-kutta neural neural network 2 architecture type for dynamical system identification problem [ref].
+"""
+struct Rknn2 <: AbstractModel end
+
+"""
+    Rknn4
+A runge-kutta neural neural network 4 architecture type for dynamical system identification problem [ref].
+"""
+struct Rknn4 <: AbstractModel end
+
+"""
+    linear
+An linear (Wv --> Ax + Bu) architecture type for dynamical system identification problem [ref].
+"""
+struct Linear <: AbstractModel end
+
+"""
+    Rnn
+A recurrent neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Rnn <: AbstractModel end
+
+"""
+    lstm
+A long short-term memory recurrent neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Lstm <: AbstractModel end
+
+"""
+    gru
+A gated recurrent unit recurrent neural network architecture type for dynamical system identification problem [ref].
+"""
+struct Gru <: AbstractModel end