Merge pull request #89 from JuliaAlgebra/0.7

Update package for 0.7 only

Author: saschatimme

.travis.yml

@@ -3,10 +3,17 @@ language: julia
 os:
   - linux
 julia:
-  - 0.6
+  - 0.7
+  - 1.0
   - nightly
+
+matrix:
+ allow_failures:
+ - julia: nightly
+
 notifications:
   email: false
+
 after_success:
   # push coverage results to Coveralls
   - julia -e 'cd(Pkg.dir("MultivariatePolynomials")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'

REQUIRE

@@ -1,2 +1 @@
-julia 0.6
-Compat 0.61
+julia 0.7

appveyor.yml

@@ -1,14 +1,17 @@
 environment:
   matrix:
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.6/julia-0.6-latest-win32.exe"
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.6/julia-0.6-latest-win64.exe"
-    - JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x86/julia-latest-win32.exe"
-    - JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x64/julia-latest-win64.exe"
+  - julia_version: 0.7
+  - julia_version: latest
 
+platform:
+  - x86 # 32-bit
+  - x64 # 64-bit
+
+## uncomment the following lines to allow failures on nightly julia
+## (tests will run but not make your overall status red)
 matrix:
  allow_failures:
-   - JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x86/julia-latest-win32.exe"
-   - JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x64/julia-latest-win64.exe"
+ - julia_version: latest
 
 branches:
   only:
@@ -22,22 +25,12 @@ notifications:
     on_build_status_changed: false
 
 install:
-  - ps: "[System.Net.ServicePointManager]::SecurityProtocol = [System.Net.SecurityProtocolType]::Tls12"
-# Download most recent Julia Windows binary
-  - ps: (new-object net.webclient).DownloadFile(
-        $env:JULIA_URL,
-        "C:\projects\julia-binary.exe")
-# Run installer silently, output to C:\projects\julia
-  - C:\projects\julia-binary.exe /S /D=C:\projects\julia
+  - ps: iex ((new-object net.webclient).DownloadString("https://raw.githubusercontent.com/JuliaCI/Appveyor.jl/version-1/bin/install.ps1"))
 
 build_script:
-# Need to convert from shallow to complete for Pkg.clone to work
-  - IF EXIST .git\shallow (git fetch --unshallow)
-  - C:\projects\julia\bin\julia -e "versioninfo();
-      Pkg.clone(pwd(), \"MultivariatePolynomials\");
-      Pkg.clone(\"https://github.com/blegat/DynamicPolynomials.jl\");
-      Pkg.clone(\"https://github.com/rdeits/TypedPolynomials.jl\");
-      Pkg.build(\"MultivariatePolynomials\")"
+  - echo "%JL_BUILD_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_BUILD_SCRIPT%"
 
 test_script:
-  - C:\projects\julia\bin\julia -e "Pkg.test(\"MultivariatePolynomials\")"
+  - echo "%JL_TEST_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_TEST_SCRIPT%"

src/MultivariatePolynomials.jl

@@ -1,22 +1,6 @@
-__precompile__()
-
 module MultivariatePolynomials
 
-#using DocStringExtensions
-
-using Compat
-import Compat.LinearAlgebra
-
-# The ' operator lowers to `transpose()` in v0.6 and to
-# `adjoint()` in v0.7+.
-# TOOD: remove this switch when dropping v0.6 support
-@static if VERSION <= v"0.7.0-DEV.3351"
-    import Base: transpose
-    const adjoint_operator = transpose
-else
-    import Compat.LinearAlgebra: adjoint
-    const adjoint_operator = adjoint
-end
+import LinearAlgebra
 
 export AbstractPolynomialLike, AbstractTermLike, AbstractMonomialLike
 """

src/det.jl

@@ -1,7 +1,7 @@
-function Compat.LinearAlgebra.det(M::Matrix{<:AbstractPolynomialLike})
+function LinearAlgebra.det(M::Matrix{<:AbstractPolynomialLike})
     m = size(M)[1]
     if m > 2
-        return sum((-1)^(i-1) * M[i,1] *  det(M[1:end .!= i, 2:end]) for i in 1:m)
+        return sum((-1)^(i-1) * M[i,1] * LinearAlgebra.det(M[1:end .!= i, 2:end]) for i in 1:m)
     else
         return M[1,1] * M[2,2] - M[2,1] * M[1,2]
     end

src/differentiation.jl

@@ -63,7 +63,7 @@ differentiate(p::ARPL, m::AbstractMonomial) = differentiate(p, variable(m))
 # so we just set `R` to `Any`
 function (_differentiate_recursive(p, x, deg::Int, ::Type{R})::R) where {R}
     if deg < 0
-        throw(DomainError())
+        throw(DomainError(deg, "degree is negative"))
     elseif deg == 0
         return p
     else

src/hash.jl

@@ -31,6 +31,6 @@ function Base.hash(p::AbstractPolynomial, u::UInt)
     if iszero(p)
         hash(0, u)
     else
-        reduce((u, t) -> hash(t, u), u, terms(p))
+        reduce((u, t) -> hash(t, u), terms(p); init=u)
     end
 end

src/operators.jl

@@ -99,14 +99,14 @@ for op in [:+, :-]
     end
 end
 
-adjoint_operator(v::AbstractVariable) = v
-adjoint_operator(m::AbstractMonomial) = m
-adjoint_operator(t::T) where {T <: AbstractTerm} = adjoint_operator(coefficient(t)) * monomial(t)
-adjoint_operator(p::AbstractPolynomialLike) = polynomial(map(adjoint_operator, terms(p)))
-
-Compat.LinearAlgebra.dot(p1::AbstractPolynomialLike, p2::AbstractPolynomialLike) = p1' * p2
-Compat.LinearAlgebra.dot(x, p::AbstractPolynomialLike) = x' * p
-Compat.LinearAlgebra.dot(p::AbstractPolynomialLike, x) = p' * x
+LinearAlgebra.adjoint(v::AbstractVariable) = v
+LinearAlgebra.adjoint(m::AbstractMonomial) = m
+LinearAlgebra.adjoint(t::T) where {T <: AbstractTerm} = LinearAlgebra.adjoint(coefficient(t)) * monomial(t)
+LinearAlgebra.adjoint(p::AbstractPolynomialLike) = polynomial(map(LinearAlgebra.adjoint, terms(p)))
+
+LinearAlgebra.dot(p1::AbstractPolynomialLike, p2::AbstractPolynomialLike) = p1' * p2
+LinearAlgebra.dot(x, p::AbstractPolynomialLike) = x' * p
+LinearAlgebra.dot(p::AbstractPolynomialLike, x) = p' * x
 
 # Amazingly, this works! Thanks, StaticArrays.jl!
 """

src/polynomial.jl

@@ -4,7 +4,7 @@ export mindegree, maxdegree, extdegree
 export leadingterm, leadingcoefficient, leadingmonomial
 export removeleadingterm, removemonomials, monic
 
-Compat.LinearAlgebra.norm(p::AbstractPolynomialLike, r::Int=2) = norm(coefficients(p), r)
+LinearAlgebra.norm(p::AbstractPolynomialLike, r::Int=2) = LinearAlgebra.norm(coefficients(p), r)
 
 changecoefficienttype(::Type{TT}, ::Type{T}) where {TT<:AbstractTermLike, T} = termtype(TT, T)
 changecoefficienttype(::Type{PT}, ::Type{T}) where {PT<:AbstractPolynomial, T} = polynomialtype(PT, T)
@@ -54,7 +54,7 @@ polynomial(ts::AbstractVector{<:AbstractTerm}, s::SortedUniqState) = polynomial(
 polynomial(a::AbstractVector, x::AbstractVector, s::ListState=MessyState()) = polynomial([α * m for (α, m) in zip(a, x)], s)
 polynomial(f::Function, mv::AbstractVector{<:AbstractMonomialLike}) = polynomial([f(i) * mv[i] for i in 1:length(mv)])
 function polynomial(Q::AbstractMatrix, mv::AbstractVector)
-    dot(mv, Q * mv)
+    LinearAlgebra.dot(mv, Q * mv)
 end
 function polynomial(Q::AbstractMatrix, mv::AbstractVector, ::Type{T}) where T
     polynomial(polynomial(Q, mv), T)
@@ -368,8 +368,10 @@ function mapcoefficientsnz(f::Function, p::AbstractPolynomialLike)
 end
 mapcoefficientsnz(f::Function, t::AbstractTermLike) = f(coefficient(t)) * monomial(t)
 
-Base.round(t::AbstractTermLike, args...) = round(coefficient(t), args...) * monomial(t)
-function Base.round(p::AbstractPolynomialLike, args...)
+Base.round(t::AbstractTermLike; args...) = round(coefficient(t); args...) * monomial(t)
+function Base.round(p::AbstractPolynomialLike; args...)
     # round(0.1) is zero so we cannot use SortedUniqState
-    polynomial(round.(terms(p), args...), SortedState())
+    polynomial(round.(terms(p); args...), SortedState())
 end
+
+Base.broadcastable(p::AbstractPolynomialLike) = Ref(p)

test/REQUIRE

@@ -1,2 +1,2 @@
 BenchmarkTools
-TypedPolynomials
+DynamicPolynomials 0.1