updated to Reduce v0.4.0 and added tests

.travis.yml

@@ -13,9 +13,9 @@ git:
 
 ## uncomment the following lines to allow failures on nightly julia
 ## (tests will run but not make your overall status red)
-#matrix:
-#  allow_failures:
-#  - julia: nightly
+matrix:
+  allow_failures:
+  - julia: nightly
 
 ## uncomment and modify the following lines to manually install system packages
 #addons:

README.md

@@ -7,9 +7,10 @@
 **LINALG: Linear algebra package**
 *A selection of functions that are useful in the world of linear algebra*
 
-[![Build Status](https://travis-ci.org/chakravala/ReduceLinAlg.jl.svg?branch=master)](https://travis-ci.org/chakravala/ReduceLinAlg.jl)
-[![Coverage Status](https://coveralls.io/repos/chakravala/ReduceLinAlg.jl/badge.svg?branch=master&service=github)](https://coveralls.io/github/chakravala/ReduceLinAlg.jl?branch=master)
-[![codecov.io](http://codecov.io/github/chakravala/ReduceLinAlg.jl/coverage.svg?branch=master)](http://codecov.io/github/chakravala/ReduceLinAlg.jl?branch=master)
+[![Build Status](https://travis-ci.org/JuliaReducePkg/ReduceLinAlg.jl.svg?branch=master)](https://travis-ci.org/JuliaReducePkg/ReduceLinAlg.jl)
+[![Build status](https://ci.appveyor.com/api/projects/status/e239kk217a0lb92w?svg=true)](https://ci.appveyor.com/project/chakravala/reducelinalg-jl)
+[![Coverage Status](https://coveralls.io/repos/JuliaReducePkg/ReduceLinAlg.jl/badge.svg?branch=master&service=github)](https://coveralls.io/github/JuliaReducePkg/ReduceLinAlg.jl?branch=master)
+[![codecov.io](http://codecov.io/github/JuliaReducePkg/ReduceLinAlg.jl/coverage.svg?branch=master)](http://codecov.io/github/JuliaReducePkg/ReduceLinAlg.jl?branch=master)
 [![Join the chat at gitter](https://badges.gitter.im/Reduce-jl/Lobby.svg)](https://gitter.im/Reduce-jl/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 
 Upstream REDUCE package by Matt Rebbeck.

appveyor.yml

@@ -7,10 +7,10 @@ environment:
 
 ## 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"
+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"
 
 branches:
   only:

src/ReduceLinAlg.jl

@@ -59,14 +59,17 @@ end
 const MatExpr = Union{Array{Any,2},Array{Expr,2},Array{Symbol,2},Expr,Symbol}
 
 band_matrix(r::Union{Vector,RowVector,Expr,Symbol},v::Integer) = band_matrix(list(r),v) |> parse
+band_matrix(r::T,v::Integer) where T <: Tuple = band_matrix(RExpr(r),v) |> parse
 block_matrix(r::Integer,c::Integer,s::VectorAny) = block_matrix(RExpr(r),RExpr(c),list(s)) |> parse
+block_matrix(r::Integer,c::Integer,s::T) where T <: Tuple = block_matrix(RExpr(r),RExpr(c),RExpr(s)) |> parse
 
-char_matrix(r::Reduce.MatExpr,v::Any) = mat(char_matrix(list(r),RExpr(v)) |> parse,r)
-char_poly(r::Reduce.MatExpr,v::Any) = mat(char_matrix(list(r),RExpr(v)) |> parse,r)
+char_matrix(r::MatExpr,v::Any) = mat(char_matrix(list(r),RExpr(v)) |> parse,r)
+char_poly(r::MatExpr,v::Any) = mat(char_matrix(list(r),RExpr(v)) |> parse,r)
 
 extend(a::MatExpr,r::Integer,c::Integer,s) = mat(extend(RExpr(a),r,c,RExpr(s)) |> parse,a)
 
 hessian(r::Reduce.ExprSymbol,l::T) where T <: VectorAny  = hessian(r,list(l))
+hessian(r::Reduce.ExprSymbol,l::T) where T <: Tuple  = hessian(r,RExpr(l))
 
 @doc """
     hessian(expr,var_list::Vector)
@@ -82,6 +85,11 @@ function mat_jacobian(r::T,v::S) where T <: VectorAny where S <: VectorAny
     mat_jacobian(list(r),list(v)) |> parse
 end
 
+function mat_jacobian(r::T,v::S) where T <: Tuple where S <: Tuple
+    mat_jacobian(RExpr(r),RExpr(v)) |> parse
+end
+
+
 @doc """
     mat_jacobian(expr_list::Vector,var_list::Vector)
 
@@ -90,9 +98,9 @@ Computes the Jacobian matrix of `expr_list` with respect to `var_list`.
 This is a matrix whose (i,j)th entry is `df(expr_list[i],var_list[j])`. The matrix is n×m where n is the number of variables and m is the number of expressions.
 """ mat_jacobian
 
-jacobian = mat_jacobian
+export jacobian
 
-jordan_block(r::Any,s::Integer) = jordan_block(RExpr(r),s) |> parse
+jacobian = mat_jacobian
 
 @doc """
     jordan_block(expr,square_size::Integer)
@@ -106,14 +114,19 @@ kronecker_product(a::MatExpr,b::MatExpr) = mat(kronecker(RExpr(a),RExpr(b)) |> p
 
 cholesky(r::Array{T,2}) where T <: Number = cholesky(RExpr(r)) |> parse |> mat
 coeff_matrix(r::VectorAny) = coeff_matrix(list(r)) |> parse
+coeff_matrix(r::T) where T <: Tuple = coeff_matrix(RExpr(r)) |> parse
 diagonal(r::VectorAny) = diagonal(list(r)) |> parse
+diagonal(r::T) where T <: Tuple = diagonal(RExpr(r)) |> parse
 gram_schmidt(r::Vector{<:Vector}) = gram_schmidt(list(r)) |> parse
+gram_schmidt(r::T) where T <: Tuple = gram_schmidt(RExpr(r)) |> parse
 gram_schmidt(r::Matrix) = gram_schmidt(list(r)) |> parse
 hermitian_tp(r::MatExpr) = mat(hermitian_tp(RExpr(r)) |> parse, r)
 symmetricp(r::MatExpr) = mat(symmetricp(RExpr(r)) |> parse, r)
 toeplitz(r::VectorAny) = toeplitz(list(r)) |> parse
+toeplitz(r::T) where T <: Tuple = toeplitz(RExpr(r)) |> parse
 triang_adjoint(r::MatExpr) = mat(triang_adjoint(RExpr(r)) |> parse, r)
 vandermonde(r::VectorAny) = vandermonde(list(r)) |> parse
+vandermonde(r::T) where T <: Tuple = vandermonde(RExpr(r)) |> parse
 
 function __init__()
     load_package(:linalg)

test/runtests.jl

@@ -2,4 +2,6 @@ using ReduceLinAlg
 using Base.Test
 
 # write your own tests here
-@test 1 == 2
+@test mat_jacobian((:x,),(:x,)) == mat_jacobian([:x],[:x])
+@test hessian(:x,(:x,)) == hessian(:x,[:x])
+@test jordan_block(:x,1) == jordan_block(Reduce.RExpr("x"),Reduce.RExpr("1")) |> parse