adjustments for DSP breakage (#352)

Project.toml

@@ -2,7 +2,7 @@ name = "Polynomials"
 uuid = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
 license = "MIT"
 author = "JuliaMath"
-version = "2.0.13"
+version = "2.0.14"
 
 [deps]
 Intervals = "d8418881-c3e1-53bb-8760-2df7ec849ed5"

src/polynomials/LaurentPolynomial.jl

@@ -132,6 +132,12 @@ function Base.convert(P::Type{<:Polynomial}, q::LaurentPolynomial)
     P([q[i] for i  in 0:n], indeterminate(q))
 end
 
+# need to add p.m[], so abstract.jl method isn't sufficent
+# XXX unlike abstract.jl, this uses Y variable in conversion; no error
+# Used in DSP.jl
+function Base.convert(::Type{LaurentPolynomial{S,Y}}, p::LaurentPolynomial{T,X}) where {T,X,S,Y}
+    LaurentPolynomial{S,Y}(p.coeffs, p.m[])
+end
 
 # work around for non-applicable convert(::Type{<:P}, p::P{T,X}) in abstract.jl
 struct OffsetCoeffs{V}
@@ -451,6 +457,13 @@ function Base.:*(p1::P, p2::P) where {T,X,P<:LaurentPolynomial{T,X}}
     return p
 end
 
+function scalar_mult(p::LaurentPolynomial{T,X}, c::Number) where {T,X}
+    LaurentPolynomial(p.coeffs .* c, p.m[], X)
+end
+function scalar_mult(c::Number, p::LaurentPolynomial{T,X}) where {T,X}
+    LaurentPolynomial(c .* p.coeffs, p.m[], X)
+end
+
 ##
 ## roots
 ##

src/polynomials/Poly.jl

@@ -63,7 +63,7 @@ Base.one(::Type{P}) where {P <: Poly} = Poly{_eltype(P), Polynomials.indetermina
 Base.one(::Type{P},var::Polynomials.SymbolLike) where {P <: Poly} = Poly(ones(_eltype(P),1), var)
 Polynomials.variable(::Type{P}) where {P <: Poly} = Poly{_eltype(P), Polynomials.indeterminate(P)}([0,1])
 Polynomials.variable(::Type{P},var::Polynomials.SymbolLike) where {P <: Poly} = Poly(_eltype(P)[0,1], var)
-function Polynomials.basis(P::Type{<:Poly}, k::Int, _var::Polynomials.SymbolLike=:x; var=_var) 
+function Polynomials.basis(P::Type{<:Poly}, k::Int, _var::Polynomials.SymbolLike=:x; var=_var)
     zs = zeros(Int, k+1)
     zs[end] = 1
     Polynomials.constructorof(P){_eltype(P), Symbol(var)}(zs)

test/StandardBasis.jl

@@ -428,6 +428,12 @@ end
         @test p*q ==ᵟ P(im*[1,2,3])
     end
 
+    # Laurent polynomials and scalar operations
+    cs = [1,2,3,4]
+    p = LaurentPolynomial(cs, -3)
+    @test p*3 == LaurentPolynomial(cs .* 3, -3)
+    @test 3*p == LaurentPolynomial(3 .* cs, -3)
+
     # LaurentPolynomial has an inverse for monomials
     x = variable(LaurentPolynomial)
     @test Polynomials.isconstant(x * inv(x))