From 9bdb256e3c826274e64ae25b01bd52ee817d4b64 Mon Sep 17 00:00:00 2001
From: Fredrik Bagge Carlsson <cont-frb@ulund.org>
Date: Sat, 5 Sep 2015 14:23:20 +0200
Subject: [PATCH] Added tests for ar arx and fixed bug in ar arx LS_reg
---
src/SystemIdentification.jl | 9 +++------
src/armax.jl | 12 ++++++------
test/tests.jl | 13 ++++++++++++-
3 files changed, 21 insertions(+), 13 deletions(-)
diff --git a/src/SystemIdentification.jl b/src/SystemIdentification.jl
index 8d47ab1..0374b49 100644
--- a/src/SystemIdentification.jl
+++ b/src/SystemIdentification.jl
@@ -32,12 +32,10 @@ typealias PolynomMatrix{T} Union(Array{Polynom{T},1},Polynom{T}, T)
"""
`a::Vector{Float64}`: The polynomial coeffs A(z) (not including the first 1)\n
`na::Int`\n
-`λ::Float64`\n
"""
type AR <: LinearModel
a::Polynom
na::Int
- λ::Float64
end
"""
@@ -45,14 +43,12 @@ end
`b::VecOrMat{Float64}`: The polynomial coeffs B(z)\n
`na::Int`\n
`nb::Vector{Int}`\n
-`λ::Float64`\n
"""
type ARX <: LinearModel
a::Polynom
b::PolynomMatrix
na::Int
nb::Polynom{Int}
- λ::Float64
end
type RBFARX <: Network
@@ -74,9 +70,10 @@ type FitResult
error::VecOrMat{Float64}
fit::FitStatistics
method::Symbol
- function FitResult(y,yh,d::Int,method::Symbol)
+ λ::Float64
+ function FitResult(y,yh,d::Int,method::Symbol, λ = 0)
error = y-yh
- new(error, FitStatistics(y,yh, d),method)
+ new(error, FitStatistics(y,yh, d),method, λ)
end
end
diff --git a/src/armax.jl b/src/armax.jl
index cb23ca1..36477a7 100644
--- a/src/armax.jl
+++ b/src/armax.jl
@@ -5,12 +5,12 @@ function ar(y::Vector{Float64}, na; λ = 0)
if λ == 0
w = A\y_train
else
- w = (A'A + λeye(size(A,2)))\A'y_train
+ w = (A'A + λ*eye(size(A,2)))\A'y_train
end
prediction = A*w
error = y_train - prediction
- model = AR(w,na,λ)
- result = FitResult(y_train,prediction,na, λ>0?(:LS_reg) :(:LS))
+ model = AR(w,na)
+ result = FitResult(y_train,prediction,na, λ>0?(:LS_reg) :(:LS),λ)
return model, result
end
ar(iddata::IdData, na; λ = 0, doplot=false) = ar(iddata.y, na; λ = 0)
@@ -22,7 +22,7 @@ function arx(y::Vector{Float64}, u::VecOrMat{Float64}, na, nb; λ = 0, doplot=fa
if λ == 0
w = A\y_train
else
- w = (A'A + λeye(size(A,2)))\A'y_train
+ w = (A'A + λ*eye(size(A,2)))\A'y_train
end
prediction = A*w
error = y_train - prediction
@@ -35,8 +35,8 @@ function arx(y::Vector{Float64}, u::VecOrMat{Float64}, na, nb; λ = 0, doplot=fa
push!(b,w[si:si+nb[i]-1])
si += nb[i]
end
- model = ARX(w[1:na],b,na,nb,λ)
- result = FitResult(y_train,prediction,na, λ>0?(:LS_reg) :(:LS))
+ model = ARX(w[1:na],b,na,nb)
+ result = FitResult(y_train,prediction,na, λ>0?(:LS_reg) :(:LS), λ)
return model, result
end
arx(iddata::IdData, na, nb; λ = 0) = arx(iddata.y, iddata.u, na, nb; λ = 0)
diff --git a/test/tests.jl b/test/tests.jl
index 34f3102..323ed66 100644
--- a/test/tests.jl
+++ b/test/tests.jl
@@ -60,6 +60,12 @@ function run_tests()
@tassert fit.FIT ≈ 100.0
@tassert isapprox(fit.RMS, 0.0, atol=1e-10)
@tassert result.method == :LS
+ @tassert model.na == 2
+ @tassert result.λ == 0
+ model, result = ar(collect(1:5.0),2,λ = 1)
+ @tassert result.method == :LS_reg
+ @tassert result.λ == 1
+
end
@test "ARX " begin
@@ -68,10 +74,15 @@ function run_tests()
@tassert isa(model,ARX)
@tassert isa(result,FitResult)
@tassert isa(fit,FitStatistics)
- @tassert model.a ≈ [2;-1]
@tassert fit.FIT ≈ 100.0
@tassert isapprox(fit.RMS, 0.0, atol=1e-10)
@tassert result.method == :LS
+ @tassert model.nb == 1
+ @tassert model.na == 1
+ @tassert result.λ == 0
+ model, result = arx(collect(1:5.0),collect(1:5.0),1,1,λ = 1)
+ @tassert result.method == :LS_reg
+ @tassert result.λ == 1
end
end
--
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