Merge branch 'master' of github.com:JuliaLang/julia

base/docs/Docs.jl

@@ -187,7 +187,8 @@ catdoc(xs...) = vcat(xs...)
 # Type Documentation
 
 isdoc(x) = isexpr(x, :string, AbstractString) ||
-    (isexpr(x, :macrocall) && endswith(string(x.args[1]), "_str"))
+    (isexpr(x, :macrocall) && x.args[1] == symbol("@doc_str")) ||
+    (isexpr(x, :call) && x.args[1] == Expr(:., Base.Markdown, QuoteNode(:doc_str)))
 
 dict_expr(d) = :(Dict($([:($(Expr(:quote, f)) => $d) for (f, d) in d]...)))
 

base/docs/helpdb.jl

@@ -10692,7 +10692,7 @@ Store values from array `X` within some subset of `A` as specified by `inds`.
 
     setindex!(collection, value, key...)
 
-Store the given value at the given key or index within a collection. The syntax `a[i,j,...] = x` is converted by the compiler to `setindex!(a, x, i, j, ...)`.
+Store the given value at the given key or index within a collection. The syntax `a[i,j,...] = x` is converted by the compiler to `(setindex!(a, x, i, j, ...); x)`.
 """
 setindex!
 

base/linalg/lu.jl

@@ -210,6 +210,7 @@ function logdet{T<:Complex,S}(A::LU{T,S})
 end
 
 inv!{T<:BlasFloat,S<:StridedMatrix}(A::LU{T,S}) = @assertnonsingular LAPACK.getri!(A.factors, A.ipiv) A.info
+inv{T<:BlasFloat,S<:StridedMatrix}(A::LU{T,S}) = inv!(LU(copy(A.factors), copy(A.ipiv), copy(A.info)))
 
 cond{T<:BlasFloat,S<:StridedMatrix}(A::LU{T,S}, p::Number) = inv(LAPACK.gecon!(p == 1 ? '1' : 'I', A.factors, norm((A[:L]*A[:U])[A[:p],:], p)))
 cond(A::LU, p::Number) = norm(A[:L]*A[:U],p)*norm(inv(A),p)

base/markdown/Markdown.jl

@@ -50,8 +50,10 @@ macro md_str(s, t...)
     mdexpr(s, t...)
 end
 
+doc_str(md, file, mod) = (md.meta[:path] = file; md.meta[:module] = mod; md)
+
 macro doc_str(s, t...)
-    docexpr(s, t...)
+    :(doc_str($(mdexpr(s, t...)), @__FILE__, current_module()))
 end
 
 function Base.display(d::Base.REPL.REPLDisplay, md::Vector{MD})

test/docs.jl

@@ -95,6 +95,15 @@ t(::Int, ::Any)
 "t-3"
 t{S <: Integer}(::S)
 
+"FieldDocs"
+type FieldDocs
+    "one"
+    one
+    doc"two"
+    two
+    three
+end
+
 end
 
 import Base.Docs: meta
@@ -157,6 +166,11 @@ end
 @test @doc(DocsTest.t(::Int, ::Any)) == doc"t-2"
 @test @doc(DocsTest.t{S <: Integer}(::S)) == doc"t-3"
 
+let fields = meta(DocsTest)[DocsTest.FieldDocs].fields
+    @test haskey(fields, :one) && fields[:one] == doc"one"
+    @test haskey(fields, :two) && fields[:two] == doc"two"
+end
+
 # issue 11993
 # Check if we are documenting the expansion of the macro
 macro m1_11993()

test/linalg/lu.jl

@@ -3,6 +3,7 @@
 debug = false
 
 using Base.Test
+import Base.LinAlg.BlasInt, Base.LinAlg.BlasFloat
 
 n = 10
 
@@ -32,6 +33,11 @@ for eltya in (Float32, Float64, Complex64, Complex128, BigFloat, Int)
     d = eltya == Int ? Tridiagonal(rand(1:7, n-1), rand(1:7, n), rand(1:7, n-1)) : convert(Tridiagonal{eltya}, eltya <: Complex ? Tridiagonal(complex(dlreal, dlimg), complex(dreal, dimg), complex(dureal, duimg)) : Tridiagonal(dlreal, dreal, dureal))
     ε = εa = eps(abs(float(one(eltya))))
 
+    if eltya <: BlasFloat
+        num = rand(eltya)
+        @test lu(num) == (one(eltya),num,1)
+        @test_approx_eq full(lufact(num)) eltya[num]
+    end
     for eltyb in (Float32, Float64, Complex64, Complex128, Int)
         b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex(breal, bimg) : breal)
         c = eltyb == Int ? rand(1:5, n) : convert(Vector{eltyb}, eltyb <: Complex ? complex(creal, cimg) : creal)
@@ -41,7 +47,10 @@ for eltya in (Float32, Float64, Complex64, Complex128, BigFloat, Int)
 debug && println("(Automatic) Square LU decomposition")
         κ     = cond(a,1)
         lua   = factorize(a)
+        @test_throws KeyError lua[:Z]
         l,u,p = lua[:L], lua[:U], lua[:p]
+        ll,ul,pl = lu(a)
+        @test_approx_eq ll * ul a[pl,:]
         @test_approx_eq l*u a[p,:]
         @test_approx_eq (l*u)[invperm(p),:] a
         @test_approx_eq a * inv(lua) eye(n)
@@ -50,15 +59,21 @@ debug && println("(Automatic) Square LU decomposition")
         @test norm(a'*(lua'\a') - a', 1) < ε*κ*n^2
         @test norm(a*(lua\c) - c, 1) < ε*κ*n # c is a vector
         @test norm(a'*(lua'\c) - c, 1) < ε*κ*n # c is a vector
+        @test_approx_eq full(lua) a
         if eltya <: Real && eltyb <: Real
             @test norm(a.'*(lua.'\b) - b,1) < ε*κ*n*2 # Two because the right hand side has two columns
             @test norm(a.'*(lua.'\c) - c,1) < ε*κ*n
         end
-        @test_approx_eq full(lua) a
+        if eltya <: BlasFloat && eltyb <: BlasFloat
+            e = rand(eltyb,n,n)
+            @test norm(e/lua - e/a,1) < ε*κ*n^2
+        end
 
 debug && println("Tridiagonal LU")
         κd    = cond(full(d),1)
         lud   = lufact(d)
+        @test lufact(lud) == lud
+        @test_throws KeyError lud[:Z]
         @test_approx_eq lud[:L]*lud[:U] lud[:P]*full(d)
         @test_approx_eq lud[:L]*lud[:U] full(d)[lud[:p],:]
         @test_approx_eq full(lud) d
@@ -71,6 +86,23 @@ debug && println("Tridiagonal LU")
         end
         f = zeros(eltyb, n+1)
         @test_throws DimensionMismatch lud\f
+        @test_throws DimensionMismatch lud.'\f
+        @test_throws DimensionMismatch lud'\f
+
+        if eltya <: BlasFloat && eltyb <: BlasFloat
+            e = rand(eltyb,n,n)
+            @test norm(e/lud - e/d,1) < ε*κ*n^2
+            @test norm((lud.'\e') - full(d.')\e',1) < ε*κd*n^2
+            #test singular
+            du = rand(eltya,n-1)
+            dl = rand(eltya,n-1)
+            dd = rand(eltya,n)
+            dd[1] = zero(eltya)
+            du[1] = zero(eltya)
+            dl[1] = zero(eltya)
+            zT = Tridiagonal(dl,dd,du)
+            @test lufact(zT).info == 1
+        end
 
 debug && println("Thin LU")
         lua   = @inferred lufact(a[:,1:n1])

test/linalg/svd.jl

@@ -44,8 +44,11 @@ debug && println("Generalized svd")
     @test_approx_eq gsvd[:V]*gsvd[:D2]*gsvd[:R]*gsvd[:Q]' a_svd
     @test_approx_eq usv[:Vt]' usv[:V]
     @test_throws KeyError usv[:Z]
+    @test_throws KeyError gsvd[:Z]
+    @test_approx_eq gsvd[:vals] svdvals(a,a_svd)
     α = eltya == Int ? -1 : rand(eltya)
     β = svdfact(α)
     @test β[:S] == [abs(α)]
     @test svdvals(α) == abs(α)
+
 end