Merge pull request #639 from JuliaControl/typestab

type stability fixes and tests

Author: baggepinnen

src/types/SisoTfTypes/SisoRational.jl

@@ -1,8 +1,8 @@
 ## User should just use TransferFunction
 struct SisoRational{T} <: SisoTf{T}
-    num::Polynomial{T}
-    den::Polynomial{T}
-    function SisoRational{T}(num::Polynomial{T}, den::Polynomial{T}) where T <: Number
+    num::Polynomial{T, :x}
+    den::Polynomial{T, :x}
+    function SisoRational{T}(num::Polynomial{T, S}, den::Polynomial{T, S}) where {T <: Number, S}
         if isequal(den, zero(den))
             error("Cannot create SisoRational with zero denominator")
         elseif isequal(num, zero(num))
@@ -14,12 +14,12 @@ struct SisoRational{T} <: SisoTf{T}
 end
 function SisoRational(num::Polynomial{T1}, den::Polynomial{T2}) where T1 <: Number where T2 <: Number
     T = promote_type(T1,T2)
-    SisoRational{T}(Polynomial{T}(num.coeffs), Polynomial{T}(den.coeffs))
+    SisoRational{T}(Polynomial{T, :x}(num.coeffs), Polynomial{T, :x}(den.coeffs))
 end
-SisoRational{T}(num::Polynomial, den::Polynomial) where T = SisoRational{T}(convert(Polynomial{T}, num), convert(Polynomial{T}, den))
+SisoRational{T}(num::Polynomial, den::Polynomial) where T = SisoRational{T}(convert(Polynomial{T, :x}, num), convert(Polynomial{T, :x}, den))
 
 function SisoRational{T}(num::AbstractVector, den::AbstractVector) where T <: Number # NOTE: Typearguemnts on the parameters?
-    SisoRational{T}(Polynomial{T}(reverse(num)), Polynomial{T}(reverse(den)))
+    SisoRational{T}(Polynomial{T, :x}(reverse(num)), Polynomial{T, :x}(reverse(den)))
 end
 function SisoRational(num::AbstractVector{T1}, den::AbstractVector{T2}) where T1 <: Number where T2 <: Number
     T = promote_type(T1,T2)
@@ -126,7 +126,7 @@ end
 #.-(f::SisoRational, n::Number) = -(t, n)
 #.-(n::Number, f::SisoRational) = -(n, t)
 
--(f::SisoRational) = SisoRational(-f.num, f.den)
+-(f::SisoRational) = SisoRational((-f.num)::typeof(f.num), f.den) # typeassert due to https://github.com/JuliaMath/Polynomials.jl/issues/395 and can be removed once that is closed
 
 # We overload this method to circumvent the Base methods use of promote_op(matprod,...)
 function (*)(A::AbstractMatrix{<:SisoRational}, B::AbstractMatrix{<:SisoRational})

src/types/StateSpace.jl

@@ -261,9 +261,9 @@ function *(sys1::ST, sys2::ST) where {ST <: AbstractStateSpace}
     #Note: sys1*sys2 = y <- sys1 <- sys2 <- u
     if xor(issiso(sys1), issiso(sys2))
         if issiso(sys1)
-            sys1 = append(fill(sys1, sys2.ny)...)
+            sys1 = append(fill(sys1, sys2.ny)...)::ST
         else
-            sys2 = append(fill(sys2, sys1.nu)...)
+            sys2 = append(fill(sys2, sys1.nu)...)::ST
         end
     elseif sys1.nu != sys2.ny
         error("sys1*sys2: sys1 must have same number of inputs as sys2 has outputs")

src/types/TransferFunction.jl

@@ -180,11 +180,12 @@ end
 ## DIVISION ##
 function /(n::Number, G::TransferFunction)
     if issiso(G)
-        matrix = reshape([n/G.matrix[1,1]], 1, 1)
+        entry = n/G.matrix[1,1]
+        matrix = fill(entry, 1, 1)
+        return TransferFunction(matrix, G.timeevol)
     else
         error("MIMO TransferFunction inversion isn't implemented yet")
     end
-    return TransferFunction(matrix, G.timeevol)
 end
 /(G::TransferFunction, n::Number) = G*(1/n)
 /(G1::TransferFunction, G2::TransferFunction) = G1*(1/G2)

test/test_statespace.jl

@@ -55,10 +55,14 @@
         @test C_222 + 1 == SS([-5 -3; 2 -9],[1 0; 0 2],[1 0; 0 1],[1 1; 1 1])
         @test D_111 + D_111 == SS([-0.5 0; 0 -0.5],[2; 2],[3 3],[0], 0.005)
 
+        @inferred C_111 + C_111
+
         @test C_111 + false == C_111
         @test false + C_111 == C_111
         @test 1.0*C_111 + false == C_111
 
+        @inferred C_111 + false
+
         @test C_222 + 1.5 == 1.0C_222 + 1.5 # C_222 has eltype Int
         @test 1.5 + C_222 == 1.0C_222 + 1.5
 
@@ -80,6 +84,9 @@
         @test minreal(C_111*C_222_d - C_222_d*C_111, atol=1e-3) == ss(0*I(2)) # scalar times MIMO
         @test C_111*C_222 == ss([-5 0 2 0; 0 -5 0 2; 0 0 -5 -3; 0 0 2 -9], [0 0; 0 0; 1 0; 0 2], [3 0 0 0; 0 3 0 0], 0)
 
+        @inferred C_111 * C_221
+        @inferred C_111 * I(2)
+
         # Division
         @test 1/C_222_d == SS([-6 -3; 2 -11],[1 0; 0 2],[-1 0; -0 -1],[1 -0; 0 1])
         @test C_221/C_222_d == SS([-5 -3 -1 0; 2 -9 -0 -2; 0 0 -6 -3;
@@ -90,6 +97,9 @@
         fsys = ss(1,1,1,0)/3 # Int becomes FLoat after division
         @test fsys.B[]*fsys.C[] == 1/3
 
+        @inferred 1/C_222_d
+        @inferred C_221/C_222_d
+
         # Indexing
         @test size(C_222) == (2, 2)
         @test size(C_212) == (2, 1)

test/test_transferfunction.jl

@@ -4,6 +4,9 @@
 # {type}_{dims}
 # type: C: Continuous, D: Discrete
 # dims: "npnuny" (np = # poles)
+s = tf("s")
+@inferred 1.0/s
+@inferred 1/s
 
 # CONTINUOUS
 C_111 = tf([1, 2], [1, 5])
@@ -32,6 +35,9 @@ z = tf("z", 0.005)
 @test C_022 == tf([4 0;0 4])
 @test D_022 == tf([4 0;0 4], 0.005)
 
+@inferred tf([4 0;0 4])
+@inferred tf([4 0;0 4], 0.005)
+
 # Test equality
 @test tf([1,2], [2,3,4]) == tf(2*[1,2], 2*[2,3,4])
 @test tf([1.0], [2.0,3.0]) == tf(π*[1.0], π*[2.0,3.0])
@@ -62,12 +68,14 @@ z = tf("z", 0.005)
 @test C_222 + 1 == tf(vecarray(2, 2, [2,10,18], [1,9,17], [2,10,18], [1,9,17]),
   vecarray(2, 2, [1,8,15], [1,8,15], [1,8,15], [1,8,15]))
 @test D_111 + D_111 == tf([2,3,-2], [1,-1,0.25], 0.005)
+@inferred C_111 + C_111
 
 # Subtraction
 @test C_111 - C_211 == tf([0,3,18,15], [1,13,55,75])
 @test 1 - C_222 == tf(vecarray(2, 2, [0,6,12], [1,7,13], [0,6,12], [1,7,13]), vecarray(2, 2, [1,8,15], [1,8,15], [1,8,15], [1,8,15]))
 # We are not doing enough to identify zero numerator here
 @test_broken D_111 - D_211 - tf([0,0.3,-2.55,1.2], [1,-0.7,-0.05,0.075], 0.005) == tf([0.0], [1], 0.005)
+@inferred C_111 - C_211
 
 # Multiplication
 @test C_111 * C_221 == tf(vecarray(1, 2, [1,4,7,6], [0,1,4,4]),
@@ -80,6 +88,7 @@ z = tf("z", 0.005)
 @test_broken D_111 * D_221 - tf(vecarray(1, 2, [1,4,7,6], [0,1,4,4]),
   vecarray(1, 2, [1,-0.7,-0.05,0.075], [1.0,-0.7,-0.05,0.075]), 0.005) ==
 tf(vecarray(1, 2, [0], [0]), vecarray(1, 2, [1], [1]), 0.005)
+@inferred C_111 * C_221
 
 @test tf(1) .* C_222 == C_222
 @test tf(1) .* I(2) == tf(I(2))
@@ -89,6 +98,9 @@ tf(vecarray(1, 2, [0], [0]), vecarray(1, 2, [1], [1]), 0.005)
 @test C_212/C_111 == tf(vecarray(2, 1, [1,7,13,15], [0,1,7,10]),
   vecarray(2, 1, [1,10,31,30], [1,10,31,30]))
 @test 1/D_111 == tf([1.0,-0.5], [1.0,2.0], 0.005)
+@inferred 1/C_111
+@inferred C_212/C_111
+@inferred 1/D_111
 
 # Indexing
 @test size(C_222) == (2, 2)