Update to Julia 1.0

.travis.yml

@@ -1,28 +1,27 @@
-# Documentation: http://docs.travis-ci.com/user/languages/julia/
 language: julia
 
+sudo: required
+
+services:
+  - docker
+
 os:
   - linux
   - osx
 
 julia:
-  - 0.5
-  - 0.6
+  - 0.7
+  - 1.0
   - nightly
 
-matrix:
-  allow_failures:
-    - julia: 0.5
-
+# matrix:
+#   allow_failures:
+#     - julia: nightly
 
 notifications:
   email: false
 
-# uncomment the following lines to override the default test script
-#script:
-#  - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-#  - julia -e 'Pkg.clone(pwd()); Pkg.build("ConstraintPropagation"); Pkg.test("ConstraintPropagation"; coverage=true)'
-
 after_success:
-  - julia -e 'Pkg.add("Documenter")'
+  - julia -e 'using Pkg; Pkg.add("Documenter")'
   - julia -e 'cd(Pkg.dir("IntervalConstraintProgramming")); include(joinpath("docs", "make.jl"))'
+  - julia -e 'cd(Pkg.dir("IntervalConstraintProgramming")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder()); Codecov.submit(process_folder())'

REQUIRE

@@ -1,6 +1,5 @@
-julia 0.6 0.7
-IntervalArithmetic 0.9 0.14
-IntervalRootFinding 0.2 0.3
-IntervalContractors 0.2 0.3
-MacroTools 0.3
-
+julia 0.7
+IntervalArithmetic 0.15
+IntervalRootFinding 0.4
+IntervalContractors 0.3
+MacroTools 0.4

appveyor.yml

@@ -1,9 +1,18 @@
 environment:
   matrix:
-  - JULIAVERSION: "julialang/bin/winnt/x86/0.4/julia-0.4-latest-win32.exe"
-  - JULIAVERSION: "julialang/bin/winnt/x64/0.4/julia-0.4-latest-win64.exe"
-  - JULIAVERSION: "julianightlies/bin/winnt/x86/julia-latest-win32.exe"
-  - JULIAVERSION: "julianightlies/bin/winnt/x64/julia-latest-win64.exe"
+  - julia_version: 0.7
+  - julia_version: 1
+  - julia_version: nightly
+
+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_version: nightly
 
 branches:
   only:
@@ -17,18 +26,18 @@ notifications:
     on_build_status_changed: false
 
 install:
-# Download most recent Julia Windows binary
-  - ps: (new-object net.webclient).DownloadFile(
-        $("http://s3.amazonaws.com/"+$env:JULIAVERSION),
-        "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(), \"ConstraintPropagation\"); Pkg.build(\"ConstraintPropagation\")"
+  - echo "%JL_BUILD_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_BUILD_SCRIPT%"
 
 test_script:
-  - C:\projects\julia\bin\julia --check-bounds=yes -e "Pkg.test(\"ConstraintPropagation\")"
+  - echo "%JL_TEST_SCRIPT%"
+  - C:\julia\bin\julia -e "%JL_TEST_SCRIPT%"
+
+# # Uncomment to support code coverage upload. Should only be enabled for packages
+# # which would have coverage gaps without running on Windows
+# on_success:
+#   - echo "%JL_CODECOV_SCRIPT%"
+#   - C:\julia\bin\julia -e "%JL_CODECOV_SCRIPT%"

src/ast.jl

@@ -1,7 +1,6 @@
 const symbol_numbers = Dict{Symbol, Int}()
 
-
-doc"""Return a new, unique symbol like _z3_"""
+"""Return a new, unique symbol like _z3_"""
 function make_symbol(s::Symbol)  # default is :z
 
     i = get(symbol_numbers, s, 0)
@@ -17,7 +16,7 @@ end
 make_symbol(c::Char) = make_symbol(Symbol(c))
 
 let current_symbol = 'a'
-    function make_symbol()
+    global function make_symbol()
         current_sym = current_symbol
 
         if current_sym < 'z'
@@ -36,7 +35,7 @@ function make_symbols(n::Integer)
 end
 
 # The following function is not used
-doc"""Check if a symbol like `:a` has been uniqued to `:_a_1_`"""
+"""Check if a symbol like `:a` has been uniqued to `:_a_1_`"""
 function isuniqued(s::Symbol)
     ss = string(s)
     contains(ss, "_") && isdigit(ss[end-1])
@@ -46,21 +45,21 @@ end
 
 # Combine Assignment and FunctionAssignment ?
 
-immutable Assignment
+struct Assignment
     lhs
     op
     args
 end
 
-immutable FunctionAssignment
+struct FunctionAssignment
     f  # function name
     args  # input arguments
     return_arguments
     intermediate  # tuple of intermediate variables
 end
 
 # Close to single assignment form
-type FlatAST
+mutable struct FlatAST
     top  # topmost variable(s)
     input_variables::Set{Symbol}
     intermediate::Vector{Symbol}  # generated vars
@@ -103,7 +102,7 @@ function flatten(ex)
 end
 
 
-doc"""`flatten!` recursively converts a Julia expression into a "flat" (one-dimensional)
+"""`flatten!` recursively converts a Julia expression into a "flat" (one-dimensional)
 structure, stored in a FlatAST object. This is close to SSA (single-assignment form,
 https://en.wikipedia.org/wiki/Static_single_assignment_form).
 

src/code_generation.jl

@@ -1,7 +1,7 @@
-doc"""
+"""
 A generated function, with the code that generated it
 """
-immutable GeneratedFunction{F}
+struct GeneratedFunction{F}
     f::F
     code::Expr
 end
@@ -10,7 +10,7 @@ end
 
 # GeneratedFunction(code::Expr) = GeneratedFunction(eval(code), code)
 
-(f::GeneratedFunction{F}){F}(x...) = f.f(x...)
+(f::GeneratedFunction{F})(x...) where {F} = f.f(x...)
 
 
 function make_tuple(args)
@@ -179,7 +179,7 @@ function forward_backward(flatAST::FlatAST)
 end
 
 
-doc"""
+"""
 Generate code for an anonymous function with given
 input arguments, output arguments, and code block.
 """

src/contractor.jl

@@ -1,9 +1,9 @@
 
-doc"""
-`Contractor` represents a `Contractor` from $\mathbb{R}^N$ to $\mathbb{R}^N$.
+"""
+`Contractor` represents a `Contractor` from ``\\mathbb{R}^N`` to ``\\mathbb{R}^N``.
 Nout is the output dimension of the forward part.
 """
-immutable Contractor{N, Nout, F1<:Function, F2<:Function}
+struct Contractor{N, Nout, F1<:Function, F2<:Function}
     variables::Vector{Symbol}  # input variables
     forward::GeneratedFunction{F1}
     backward::GeneratedFunction{F2}
@@ -32,7 +32,7 @@ function Contractor(variables::Vector{Symbol}, top, forward, backward, expressio
     Contractor{N, Nout, typeof(forward.f), typeof(backward.f)}(variables, forward, backward, expression)
 end
 
-function Base.show{N,Nout,F1,F2}(io::IO, C::Contractor{N,Nout,F1,F2})
+function Base.show(io::IO, C::Contractor{N,Nout,F1,F2}) where {N,Nout,F1,F2}
     println(io, "Contractor in $(N) dimensions:")
     println(io, "  - forward pass contracts to $(Nout) dimensions")
     println(io, "  - variables: $(C.variables)")
@@ -41,8 +41,8 @@ end
 
 
 
-function (C::Contractor{N,Nout,F1,F2}){N,Nout,F1,F2,T}(
-    A::IntervalBox{Nout,T}, X::IntervalBox{N,T})
+function (C::Contractor{N,Nout,F1,F2})(
+    A::IntervalBox{Nout,T}, X::IntervalBox{N,T}) where {N,Nout,F1,F2,T}
 
     output, intermediate = C.forward(X)
 
@@ -67,7 +67,8 @@ function (C::Contractor{N,Nout,F1,F2}){N,Nout,F1,F2,T}(
 end
 
 # allow 1D contractors to take Interval instead of IntervalBox for simplicty:
-(C::Contractor{N,1,F1,F2}){N,F1,F2,T}(A::Interval{T}, X::IntervalBox{N,T}) = C(IntervalBox(A), X)
+
+(C::Contractor{N,1,F1,F2})(A::Interval{T}, X::IntervalBox{N,T}) where {N,F1,F2,T} = C(IntervalBox(A), X)
 
 function make_contractor(expr::Expr)
     # println("Entering Contractor(ex) with ex=$ex")
@@ -109,7 +110,7 @@ function make_contractor(expr::Expr)
 end
 
 
-doc"""Usage:
+"""Usage:
 ```
 C = @contractor(x^2 + y^2)
 A = -∞..1  # the constraint interval

src/functions.jl

@@ -1,10 +1,10 @@
 
 
-doc"""
+"""
 A `ConstraintFunction` contains the created forward and backward
 code
 """
-type ConstraintFunction{F <: Function, G <: Function}
+mutable struct ConstraintFunction{F <: Function, G <: Function}
     input::Vector{Symbol}  # input arguments for forward function
     output::Vector{Symbol} # output arguments for forward function
     forward::F
@@ -14,15 +14,15 @@ type ConstraintFunction{F <: Function, G <: Function}
     expression::Expr
 end
 
-function Base.show{F,G}(io::IO, f::ConstraintFunction{F,G})
+function Base.show(io::IO, f::ConstraintFunction{F,G}) where {F,G}
     println(io, "ConstraintFunction:")
     println(io, "  - input arguments: $(f.input)")
     println(io, "  - output arguments: $(f.output)")
     print(io, "  - expression: $(MacroTools.striplines(f.expression))")
 end
 
 
-immutable FunctionArguments
+struct FunctionArguments
     input
     return_arguments
     intermediate
@@ -33,12 +33,11 @@ end
 const registered_functions = Dict{Symbol, FunctionArguments}()
 
 
-@doc """
-`@function` registers a function to be used in forwards and backwards mode.
-
-Example: `@function f(x, y) = x^2 + y^2`
-"""  # this docstring does not work!
-
+# """
+# `@function` registers a function to be used in forwards and backwards mode.
+#
+# Example: `@function f(x, y) = x^2 + y^2`
+# """  # this docstring does not work!
 @eval macro ($(:function))(ex)   # workaround to define macro @function
 
     (f, args, code) = match_function(ex)

src/paving.jl

@@ -1,14 +1,14 @@
-typealias SubPaving{N,T} Vector{IntervalBox{N,T}}
+const SubPaving{N,T} = Vector{IntervalBox{N,T}}
 
-type Paving{N,T}
+struct Paving{N,T}
     separator::Separator   # parametrize!
     inner::SubPaving{N,T}
     boundary::SubPaving{N,T}
     ϵ::Float64
 end
 
 
-function setdiff{N,T}(x::IntervalBox{N,T}, subpaving::SubPaving{N,T})
+function setdiff(x::IntervalBox{N,T}, subpaving::SubPaving{N,T}) where {N,T}
     working = [x]
     new_working = IntervalBox{N,T}[]
 
@@ -37,16 +37,16 @@ function setdiff{N,T}(x::IntervalBox{N,T}, subpaving::SubPaving{N,T})
 
 end
 
-setdiff{N,T}(X::SubPaving{N,T}, Y::SubPaving{N,T}) = vcat([setdiff(x, Y) for x in X]...)
+setdiff(X::SubPaving{N,T}, Y::SubPaving{N,T}) where {N,T} = vcat([setdiff(x, Y) for x in X]...)
 
-function setdiff{N,T}(x::IntervalBox{N,T}, paving::Paving{N,T})
+function setdiff(x::IntervalBox{N,T}, paving::Paving{N,T}) where {N,T}
     Y = setdiff(x, paving.inner)
     Z = setdiff(Y, paving.boundary)
     return Z
 end
 
 
-function show{N,T}(io::IO, p::Paving{N,T})
+function show(io::IO, p::Paving{N,T}) where {N,T}
     print(io, """Paving:
                  - tolerance ϵ = $(p.ϵ)
                  - inner approx. of length $(length(p.inner))