fix #161

src/arx.jl

@@ -110,7 +110,7 @@ end
 
 function arx(ds::AbstractVector{<:AbstractIdData}, na, nb; inputdelay = ones(Int, size(nb)), λ = 0, estimator = \)
     allequal(sampletime(d) for d in ds) || throw(ArgumentError("All data sets must have the same sample time"))
-    yA = getARXregressor.(ds, na, nb; inputdelay)
+    yA = [getARXregressor(d, na, nb; inputdelay) for d in ds]
     y_train = reduce(vcat, first.(yA))
     A = reduce(vcat, last.(yA))
     w = ls(A, y_train, λ, estimator) |> vec

src/subspace2.jl

@@ -233,6 +233,7 @@ function subspaceid(
     t0 = max(s1,s2)+1
     s = s1*p + s2*m
     N = t - r + 1 - t0
+    verbose && @info "Estimating with r = $r, s1 = $s1, s2 = $s2, stability constraint = $stable, zeroD = $zeroD, focus = $focus, scaleU = $scaleU"
 
     @views @inbounds function hankel(u::AbstractArray, t0, r)
         d = size(u, 2)

test/test_arx.jl

@@ -160,3 +160,20 @@ Gest = arx(d, na, nb, inputdelay = inputdelay)
 
 Gests = arx(d, na, nb, inputdelay = inputdelay, stochastic = true)
 @test compareTFs(G1, Gests)
+
+## Multiple data sets
+Gest = arx([d, d], na, nb; inputdelay)
+
+# From https://github.com/baggepinnen/ControlSystemIdentification.jl/issues/161
+N  = 20000    # Number of time steps
+t  = 1:N
+Δt = 1        # Sample time
+u  = randn(2, N) # A random control input
+G  = ssrand(1, size(u, 1), size(u, 1); Ts=Δt)
+y  = lsim(G, u, t)[1][:]
+d  = iddata(y, u, Δt)
+na = 2
+nb = [3, 3]
+
+Gest = arx([d, d], na, nb, inputdelay=[0,0])  
+@test freqresptest(G, Gest, 0.0001)