Add lookupvar and evaluate methods for Pair with tests

src/calculus.jl

@@ -131,8 +131,7 @@ function derivative(a::HomogeneousPolynomial, r::Int)
 
     return HomogeneousPolynomial{T}(coeffs, a.order-1)
 end
-derivative(a::HomogeneousPolynomial, s::Symbol) =
-    derivative(a, findfirst(get_variable_symbols(), s))
+derivative(a::HomogeneousPolynomial, s::Symbol) = derivative(a, lookupvar(s))
 
 """
     derivative(a, [r=1])
@@ -149,8 +148,7 @@ function derivative(a::TaylorN, r=1::Int)
     end
     return TaylorN{T}( coeffs, a.order )
 end
-derivative(a::TaylorN, s::Symbol) =
-    derivative(a, findfirst(get_variable_symbols(), s))
+derivative(a::TaylorN, s::Symbol) = derivative(a, lookupvar(s))
 
 ## Gradient, jacobian and hessian
 """
@@ -318,8 +316,7 @@ function integrate(a::HomogeneousPolynomial, r::Int)
 
     return HomogeneousPolynomial{T}(coeffs, a.order+1)
 end
-integrate(a::HomogeneousPolynomial, s::Symbol) =
-    integrate(a, findfirst(get_variable_symbols(), s))
+integrate(a::HomogeneousPolynomial, s::Symbol) = integrate(a, lookupvar(s))
 
 
 """
@@ -352,9 +349,6 @@ end
 integrate(a::TaylorN, r::Int, x0::NumberNotSeries) =
     integrate(a,r,TaylorN(HomogeneousPolynomial([convert(eltype(a),x0)], 0)))
 
-integrate(a::TaylorN, s::Symbol) =
-    integrate(a, findfirst(get_variable_symbols(), s))
-integrate(a::TaylorN, s::Symbol, x0::TaylorN) =
-    integrate(a, findfirst(get_variable_symbols(), s), x0)
-integrate(a::TaylorN, s::Symbol, x0::NumberNotSeries) =
-    integrate(a, findfirst(get_variable_symbols(), s), x0)
+integrate(a::TaylorN, s::Symbol) = integrate(a, lookupvar(s))
+integrate(a::TaylorN, s::Symbol, x0::TaylorN) = integrate(a, lookupvar(s), x0)
+integrate(a::TaylorN, s::Symbol, x0::NumberNotSeries) = integrate(a, lookupvar(s), x0)

src/evaluate.jl

@@ -332,10 +332,12 @@ end
 function evaluate(a::TaylorN{T}, s::Symbol, val::S) where
         {T<:Number, S<:NumberNotSeriesN}
     vars = get_variables()
-    ind = findfirst(get_variable_symbols(), s)
+    ind = lookupvar(s)
     vars[ind] = val
     evaluate(a, vars)
 end
+evaluate(a::TaylorN{T}, x::Pair{Symbol,S}) where {T<:Number, S<:NumberNotSeriesN} =
+    evaluate(p, first(x), last(x))
 
 evaluate(a::TaylorN{T}) where {T<:Number} = a[0][1]
 
@@ -378,6 +380,7 @@ evaluate(A::SubArray{TaylorN{T},2}) where {T<:Number} = evaluate.(A)
 (p::TaylorN)(x) = evaluate(p, x)
 (p::TaylorN)() = evaluate(p)
 (p::TaylorN)(s::Symbol, x) = evaluate(p, s, x)
+(p::TaylorN)(x::Pair) = evaluate(p, first(x), last(x))
 
 #function-like behavior for Vector{TaylorN}
 (p::Array{TaylorN{T},1})(x) where {T<:Number} = evaluate(p, x)

src/parameters.jl

@@ -31,11 +31,12 @@ ParamsTaylorN(order, num_vars, variable_names) = ParamsTaylorN(order, num_vars,
 const _params_TaylorN_ = ParamsTaylorN(6, 2, ["x₁", "x₂"])
 
 
-## Utilities to get the maximum order and number of variables
+## Utilities to get the maximum order, number of variables, their names and symbols
 get_order() = _params_TaylorN_.order
 get_numvars() = _params_TaylorN_.num_vars
 get_variable_names() = _params_TaylorN_.variable_names
 get_variable_symbols() = _params_TaylorN_.variable_symbols
+lookupvar(s::Symbol) = findfirst(_params_TaylorN_.variable_symbols, s)
 
 function set_variable_names(varnames::Vector{T}) where {T<:AbstractString}
     _params_TaylorN_.variable_names = varnames

test/manyvariables.jl

@@ -44,6 +44,8 @@ end
     @test TaylorSeries._params_TaylorN_.variable_names == ["x","y"]
     @test TaylorSeries._params_TaylorN_.variable_symbols == [:x, :y]
     @test get_variable_symbols() == [:x, :y]
+    @test TaylorSeries.lookupvar(:x) == 1
+    @test TaylorSeries.lookupvar(:α) == 0
     @test TaylorSeries.get_variable_names() == ["x", "y"]
     @test x == HomogeneousPolynomial(Float64, 1)
     @test x == HomogeneousPolynomial(1)
@@ -140,8 +142,8 @@ end
     @test (rem(1+xT,1.0))[0] == 0
     @test abs(1-xT)  == 1-xT
     @test abs(-1-xT)  == 1+xT
-    @test derivative(yH,1) == derivative(xH,:x₂)
-    @test derivative(mod2pi(2pi+yT^3),2) == derivative(yT^3,:x₂)
+    @test derivative(yH,1) == derivative(xH, :x₂)
+    @test derivative(mod2pi(2pi+yT^3),2) == derivative(yT^3, :x₂)
     @test derivative(yT) == zeroT
     @test -xT/3im == im*xT/3
     @test (xH/3im)' == im*xH/3
@@ -157,7 +159,7 @@ end
     vr = rand(2)
     @test hp(vr) == evaluate(hp, vr)
 
-    @test integrate(yH,1) == integrate(xH,:x₂)
+    @test integrate(yH,1) == integrate(xH, :x₂)
     p = (xT-yT)^6
     @test integrate(derivative(p, 1), 1, yT^6) == p
     @test integrate(derivative(p, :x₁), :x₁, yT^6) == p
@@ -290,13 +292,14 @@ end
     @test evaluate(exy) == 1
     @test evaluate(exy,[0.1im,0.01im]) == exp(0.11im)
     @test isapprox(evaluate(exy, [1,1]), eeuler^2)
-    @test exy(:x₁, 1) ≈ exp(1+yT)
+    @test exy(:x₁, 0.0) == exp(yT)
     txy = tan(xT+yT)
     @test getcoeff(txy,[8,7]) == 929569/99225
     ptxy = xT + yT + (1/3)*( xT^3 + yT^3 ) + xT^2*yT + xT*yT^2
     @test getindex(tan(TaylorN(1)+TaylorN(2)),0:4) == ptxy.coeffs[1:5]
-    @test evaluate(xH*yH,[1.0,2.0]) == 2.0
+    @test evaluate(xH*yH, [1.0,2.0]) == 2.0
     @test ptxy(:x₁, -1.0) == -1 + yT + (-1.0+yT^3)/3 + yT - yT^2
+    @test ptxy(:x₁ => -1.0) == -1 + yT + (-1.0+yT^3)/3 + yT - yT^2
     v = zeros(Int, 2)
     @test evaluate!([xT, yT], ones(Int, 2), v) == nothing
     @test v == ones(2)