Improve type inference in simple functions (#304)

* add tests

* fix real, imag and conj

* fix isinf and isnan

* bump patch version

Project.toml

@@ -1,7 +1,7 @@
 name = "TaylorSeries"
 uuid = "6aa5eb33-94cf-58f4-a9d0-e4b2c4fc25ea"
 repo = "https://github.com/JuliaDiff/TaylorSeries.jl.git"
-version = "0.12.1"
+version = "0.12.2"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

src/other_functions.jl

@@ -10,15 +10,15 @@ for T in (:Taylor1, :HomogeneousPolynomial, :TaylorN)
 
     ## real, imag, conj and ctranspose ##
     for f in (:real, :imag, :conj)
-        @eval ($f)(a::$T) = $T(($f).(a.coeffs), a.order)
+        @eval ($f)(a::$T) = $T($f(a.coeffs), a.order)
     end
 
     @eval adjoint(a::$T) = conj(a)
 
     ## isinf and isnan ##
-    @eval isinf(a::$T) = any( isinf.(a.coeffs) )
+    @eval isinf(a::$T) = any(isinf, a.coeffs)
 
-    @eval isnan(a::$T) = any( isnan.(a.coeffs) )
+    @eval isnan(a::$T) = any(isnan, a.coeffs)
 end
 
 

test/manyvariables.jl

@@ -114,9 +114,14 @@ using LinearAlgebra
     @test xH == convert(HomogeneousPolynomial{Float64},xH)
     @test HomogeneousPolynomial(xH) == xH
     @test HomogeneousPolynomial(0,0)  == 0
+    @test (@inferred conj(xH)) == (@inferred adjoint(xH))
+    @test (@inferred real(xH)) == xH
     xT = TaylorN(xH, 17)
     yT = TaylorN(Int, 2, order=17)
+    @test (@inferred conj(xT)) == (@inferred adjoint(xT))
+    @test (@inferred real(xT)) == (xT)
     zeroT = zero( TaylorN([xH],1) )
+    @test (@inferred imag(xT)) == (zeroT)
     @test zeroT.coeffs == zeros(HomogeneousPolynomial{Int}, 1)
     @test size(xH) == (2,)
     @test firstindex(xH) == 1
@@ -376,8 +381,8 @@ using LinearAlgebra
     @test (1+xT)^(3//2) == ((1+xT)^0.5)^3
     @test real(xH) == xH
     @test imag(xH) == zero(xH)
-    @test conj(im*yH) == (im*yH)'
-    @test conj(im*yT) == (im*yT)'
+    @test (@inferred conj(im*yH)) == (@inferred adjoint(im*yH))
+    @test (@inferred conj(im*yT)) == (@inferred adjoint(im*yT))
     @test real( exp(1im * xT)) == cos(xT)
     @test getcoeff(convert(TaylorN{Rational{Int}},cos(xT)),(4,0)) ==
         1//factorial(4)

test/mixtures.jl

@@ -100,8 +100,8 @@ using LinearAlgebra
     end
     @test string(t1N*t1N) ==
         "  1.0 x₁² + 𝒪(‖x‖³) + ( 2.0 x₁ + 𝒪(‖x‖³)) t + ( 1.0 + 𝒪(‖x‖³)) t² + ( 2.0 x₂² + 𝒪(‖x‖³)) t³ + 𝒪(t⁴)"
-    @test !isnan(tN1)
-    @test !isinf(tN1)
+    @test !(@inferred isnan(tN1))
+    @test !(@inferred isinf(tN1))
 
     @test mod(tN1+1,1.0) == 0+tN1
     @test mod(tN1-1.125,2) == 0.875+tN1
@@ -185,10 +185,10 @@ using LinearAlgebra
     @test typeof(xx) == Taylor1{TaylorN{Float64}}
     @test eltype(xx) == Taylor1{TaylorN{Float64}}
     @test TS.numtype(xx) == TaylorN{Float64}
-    @test !isnan(xx)
-    @test !isnan(δx)
-    @test !isinf(xx)
-    @test !isinf(δx)
+    @test !(@inferred isnan(xx))
+    @test !(@inferred isnan(δx))
+    @test !(@inferred isinf(xx))
+    @test !(@inferred isinf(δx))
     @test +xx == xx
     @test -xx == 0 - xx
     @test xx/1.0 == 1.0*xx
@@ -297,8 +297,8 @@ using LinearAlgebra
     @test P ≈ P
     Q = deepcopy(P)
     Q[2][2] = Taylor1([NaN, Inf])
-    @test isnan(Q)
-    @test isinf(Q)
+    @test (@inferred isnan(Q))
+    @test (@inferred isinf(Q))
     @test !isfinite(Q)
     Q[2][2] = P[2][2]+sqrt(eps())/2
     @test isapprox(P, Q, rtol=1.0)

test/onevariable.jl

@@ -148,8 +148,8 @@ Base.iszero(::SymbNumber) = false
     @test TaylorSeries.findlast(zt) == -1
     @test iszero(zero(t))
     @test !iszero(one(t))
-    @test isinf(Taylor1([typemax(1.0)]))
-    @test isnan(Taylor1([typemax(1.0), NaN]))
+    @test @inferred isinf(Taylor1([typemax(1.0)]))
+    @test @inferred isnan(Taylor1([typemax(1.0), NaN]))
 
     @test constant_term(2.0) == 2.0
     @test constant_term(t) == 0