Clean up repo to run on 0.5 (#14)

* Clean up repo to run on 0.5

* Forgot some Compat

* Forgot to modify the runtests path

* Fixed reshaping issue

* Introduce dependency on StatsBase for maxad

* Okay, not just for maxad

* 0.4 doesn't like array dims as tuples I guess

* Add status badges to the readme

.travis.yml

@@ -1,17 +1,17 @@
-language: cpp
-compiler:
-  - clang
+# Documentation: http://docs.travis-ci.com/user/languages/julia/
+language: julia
+os:
+  - linux
+julia:
+  - 0.3
+  - 0.4
+  - 0.5
+  - nightly
 notifications:
   email: false
-env:
-  matrix: 
-    - JULIAVERSION="juliareleases" 
-    - JULIAVERSION="julianightlies" 
-before_install:
-  - sudo add-apt-repository ppa:staticfloat/julia-deps -y
-  - sudo add-apt-repository ppa:staticfloat/${JULIAVERSION} -y
-  - sudo apt-get update -qq -y
-  - sudo apt-get install libpcre3-dev julia -y
-script:
-  - julia -e 'Pkg.init(); run(`ln -s $(pwd()) $(Pkg.dir("NMF"))`); Pkg.pin("NMF"); Pkg.resolve()'
-  - julia ./runtests.jl
+# 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("NMF"); Pkg.test("NMF"; coverage=true)'
+after_success:
+  - julia -e 'cd(Pkg.dir("NMF")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())';

README.md

@@ -3,8 +3,10 @@
 A Julia package for non-negative matrix factorization (NMF).
 
 [![Build Status](https://travis-ci.org/JuliaStats/NMF.jl.svg?branch=master)](https://travis-ci.org/JuliaStats/NMF.jl)
-[![NMF](http://pkg.julialang.org/badges/NMF_0.3.svg)](http://pkg.julialang.org/?pkg=NMF&ver=0.3)
-[![NMF](http://pkg.julialang.org/badges/NMF_0.4.svg)](http://pkg.julialang.org/?pkg=NMF&ver=0.4)
+[![Coverage Status](https://coveralls.io/repos/github/JuliaStats/NMF.jl/badge.svg?branch=master)](https://coveralls.io/github/JuliaStats/NMF.jl?branch=master)
+[![NMF](http://pkg.julialang.org/badges/NMF_0.3.svg)](http://pkg.julialang.org/?pkg=NMF)
+[![NMF](http://pkg.julialang.org/badges/NMF_0.4.svg)](http://pkg.julialang.org/?pkg=NMF)
+[![NMF](http://pkg.julialang.org/badges/NMF_0.5.svg)](http://pkg.julialang.org/?pkg=NMF)
 
 ---------------------------
 

REQUIRE

@@ -1,3 +1,3 @@
-julia 0.3-
-MLBase 0.3-
-ArrayViews 0.4.8-
+julia 0.3
+Compat 0.8.0
+StatsBase

src/NMF.jl

@@ -1,19 +1,20 @@
 module NMF
+    using Compat
+    using StatsBase
 
-    using ArrayViews
-    using MLBase
+    import Compat: view
     import Base: sum!
 
     export nnmf
 
     include("common.jl")
     include("utils.jl")
-    
+
     include("initialization.jl")
     include("multupd.jl")
     include("projals.jl")
     include("alspgrad.jl")
-    
+
     include("interf.jl")
 
 end # module

src/alspgrad.jl

@@ -8,7 +8,7 @@
 
 function projgradnorm(g, x)
     T = eltype(g)
-    v = convert(T, 0.0)
+    v = zero(T)
     @inbounds for i = 1:length(g)
         gi = g[i]
         if gi < zero(T) || x[i] > zero(T)
@@ -22,18 +22,18 @@ end
 # all elements of A becoming zero
 # The new value of A would be A = A - α*G
 function maxstep(G, A)
-    T = typeof(one(eltype(A))/one(eltype(G)))
+    T = typeof(one(eltype(A)) / one(eltype(G)))
     αmax = zero(T)
     for i = 1:length(G)
         g = G[i]
         if g >= 0
-            αmax = max(αmax, A[i]/g)
+            αmax = max(αmax, A[i] / g)
         else
             αmax = convert(T, Inf)
             break
         end
     end
-    αmax
+    return αmax
 end
 
 ## sub-routines for updating H
@@ -49,13 +49,13 @@ immutable ALSGradUpdH_State{T}
 
     function ALSGradUpdH_State(X, W, H)
         k, n = size(H)
-        new(Array(T, k, n),
-            Array(T, k, n),
-            Array(T, k, n),
-            Array(T, k, n),
-            Array(T, k, k),
-            Array(T, k, n),
-            Array(T, k, n))
+        @compat new(Array{T,2}(k, n),
+                    Array{T,2}(k, n),
+                    Array{T,2}(k, n),
+                    Array{T,2}(k, n),
+                    Array{T,2}(k, k),
+                    Array{T,2}(k, n),
+                    Array{T,2}(k, n))
     end
 end
 ALSGradUpdH_State{T}(X, W::VecOrMat{T}, H::VecOrMat{T}) = ALSGradUpdH_State{T}(X, W, H)
@@ -77,8 +77,8 @@ function alspgrad_updateh!{T}(X,
 
     s = ALSGradUpdH_State(X, W, H)
     set_w!(s, X, W)
-    _alspgrad_updateh!(X, W, H, s, 
-                       maxiter, traceiter, tolg, 
+    _alspgrad_updateh!(X, W, H, s,
+                       maxiter, traceiter, tolg,
                        beta, sigma, verbose)
 end
 
@@ -103,8 +103,8 @@ function _alspgrad_updateh!(X,                      # size (p, n)
     T = eltype(H)
 
     # banner
-    if verbose       
-        @printf("%5s    %12s    %12s    %12s    %8s    %12s\n", 
+    if verbose
+        @printf("%5s    %12s    %12s    %12s    %8s    %12s\n",
             "Iter", "objv", "objv.change", "1st-ord", "alpha", "back-tracks")
         WH = W * H
         objv = sqL2dist(X, WH)
@@ -115,7 +115,7 @@ function _alspgrad_updateh!(X,                      # size (p, n)
     t = 0
     converged = false
     to_decr = true
-    α = one(T)/one(eltype(G))
+    α = one(T) / one(eltype(G))
     while !converged && t < maxiter
         t += 1
 
@@ -152,7 +152,7 @@ function _alspgrad_updateh!(X,                      # size (p, n)
                 dv1 = BLAS.dot(G, D)  # <G, D>
                 A_mul_B!(WtWD, WtW, D)
                 dv2 = BLAS.dot(WtWD, D)  # <D, WtW * D>
-                
+
                 # back-track
                 suff_decr = ((1 - σ) * dv1 + convert(T, 0.5) * dv2) < 0
 
@@ -189,7 +189,7 @@ function _alspgrad_updateh!(X,                      # size (p, n)
             A_mul_B!(WH, W, H)
             preobjv = objv
             objv = sqL2dist(X, WH)
-            @printf("%5d    %12.5e    %12.5e    %12.5e    %8.4f    %12d\n", 
+            @printf("%5d    %12.5e    %12.5e    %12.5e    %8.4f    %12d\n",
                 t, objv, objv - preobjv, pgnrm, α, it)
         end
     end
@@ -210,13 +210,13 @@ immutable ALSGradUpdW_State{T}
 
     function ALSGradUpdW_State(X, W, H)
         p, k = size(W)
-        new(Array(T, p, k),
-            Array(T, p, k),
-            Array(T, p, k),
-            Array(T, p, k),
-            Array(T, k, k),
-            Array(T, p, k),
-            Array(T, p, k))
+        @compat new(Array{T,2}(p, k),
+                    Array{T,2}(p, k),
+                    Array{T,2}(p, k),
+                    Array{T,2}(p, k),
+                    Array{T,2}(k, k),
+                    Array{T,2}(p, k),
+                    Array{T,2}(p, k))
     end
 end
 ALSGradUpdW_State{T}(X, W::VecOrMat{T}, H::VecOrMat{T}) = ALSGradUpdW_State{T}(X, W, H)
@@ -239,8 +239,8 @@ function alspgrad_updatew!{T}(X,
 
     s = ALSGradUpdW_State(X, W, H)
     set_h!(s, X, H)
-    _alspgrad_updatew!(X, W, H, s, 
-                       maxiter, traceiter, tolg, 
+    _alspgrad_updatew!(X, W, H, s,
+                       maxiter, traceiter, tolg,
                        beta, sigma, verbose)
 end
 
@@ -265,8 +265,8 @@ function _alspgrad_updatew!(X,                      # size (p, n)
     T = eltype(W)
 
     # banner
-    if verbose       
-        @printf("%5s    %12s    %12s    %12s    %8s    %12s\n", 
+    if verbose
+        @printf("%5s    %12s    %12s    %12s    %8s    %12s\n",
             "Iter", "objv", "objv.change", "1st-ord", "alpha", "back-tracks")
         WH = W * H
         objv = sqL2dist(X, WH)
@@ -277,7 +277,7 @@ function _alspgrad_updatew!(X,                      # size (p, n)
     t = 0
     converged = false
     to_decr = true
-    α = one(T)/one(eltype(G))
+    α = one(T) / one(eltype(G))
     while !converged && t < maxiter
         t += 1
 
@@ -314,7 +314,7 @@ function _alspgrad_updatew!(X,                      # size (p, n)
                 dv1 = BLAS.dot(G, D)  # <G, D>
                 A_mul_B!(DHHt, D, HHt)
                 dv2 = BLAS.dot(DHHt, D)  # <D * HHt, D>
-                
+
                 # back-track
                 suff_decr = ((1 - σ) * dv1 + convert(T, 0.5) * dv2) < 0
 
@@ -351,7 +351,7 @@ function _alspgrad_updatew!(X,                      # size (p, n)
             A_mul_B!(WH, W, H)
             preobjv = objv
             objv = sqL2dist(X, WH)
-            @printf("%5d    %12.5e    %12.5e    %12.5e    %8.4f    %12d\n", 
+            @printf("%5d    %12.5e    %12.5e    %12.5e    %8.4f    %12d\n",
                 t, objv, objv - preobjv, pgnrm, α, it)
         end
     end
@@ -368,7 +368,7 @@ type ALSPGrad{T}
     tolg::T     # tolerance of grad norm in sub-routine
     verbose::Bool     # whether to show procedural information (main)
 
-    function ALSPGrad(;maxiter::Integer=100, 
+    function ALSPGrad(;maxiter::Integer=100,
                        maxsubiter::Integer=200,
                        tol::Real=cbrt(eps(T)),
                        tolg::Real=eps(T)^(1/4),
@@ -387,7 +387,7 @@ immutable ALSPGradUpd{T} <: NMFUpdater{T}
 end
 
 solve!(alg::ALSPGrad, X, W, H) =
-    nmf_skeleton!(ALSPGradUpd(alg.maxsubiter, alg.tolg), 
+    nmf_skeleton!(ALSPGradUpd(alg.maxsubiter, alg.tolg),
                   X, W, H, alg.maxiter, alg.verbose, alg.tol)
 
 
@@ -397,8 +397,8 @@ immutable ALSPGradUpd_State{T}
     uwstate::ALSGradUpdW_State
 
     ALSPGradUpd_State(X, W, H) =
-        new(W * H, 
-            ALSGradUpdH_State(X, W, H), 
+        new(W * H,
+            ALSGradUpdH_State(X, W, H),
             ALSGradUpdW_State(X, W, H))
 end
 
@@ -410,15 +410,15 @@ function update_wh!(upd::ALSPGradUpd, s::ALSPGradUpd_State, X, W, H)
 
     # update H
     set_w!(s.uhstate, X, W)
-    _alspgrad_updateh!(X, W, H, s.uhstate, 
+    _alspgrad_updateh!(X, W, H, s.uhstate,
         upd.maxsubiter, 20, upd.tolg, convert(T, 0.2), convert(T, 0.01), false)
 
     # update W
     set_h!(s.uwstate, X, H)
-    _alspgrad_updatew!(X, W, H, s.uwstate, 
+    _alspgrad_updatew!(X, W, H, s.uwstate,
         upd.maxsubiter, 20, upd.tolg, convert(T, 0.2), convert(T, 0.01), false)
 
     # update WH
-    A_mul_B!(s.WH, W, H) 
+    A_mul_B!(s.WH, W, H)
 end
 

src/common.jl

@@ -2,9 +2,7 @@
 
 # tools to check size
 
-function nmf_checksize(X,
-                       W::AbstractMatrix, 
-                       H::AbstractMatrix)
+function nmf_checksize(X, W::AbstractMatrix, H::AbstractMatrix)
 
     p = size(X, 1)
     n = size(X, 2)
@@ -13,6 +11,7 @@ function nmf_checksize(X,
     if !(size(W,1) == p && size(H) == (k, n))
         throw(DimensionMismatch("Dimensions of X, W, and H are inconsistent."))
     end
+
     return (p, n, k)
 end
 
@@ -26,11 +25,10 @@ immutable Result{T}
     converged::Bool
     objvalue::T
 
-    function Result(W::Matrix{T}, H::Matrix{T},
-                       niters::Int, converged::Bool, objv)
-
-        size(W, 2) == size(H, 1) || 
+    function Result(W::Matrix{T}, H::Matrix{T}, niters::Int, converged::Bool, objv)
+        if size(W, 2) != size(H, 1)
             throw(DimensionMismatch("Inner dimensions of W and H mismatch."))
+        end
         new(W, H, niters, converged, objv)
     end
 end
@@ -46,8 +44,8 @@ function nmf_skeleton!{T}(updater::NMFUpdater{T},
 
     # init
     state = prepare_state(updater, X, W, H)
-    preW = Array(T, size(W))
-    preH = Array(T, size(H))
+    preW = @compat Array{T,2}(size(W)...)
+    preH = @compat Array{T,2}(size(H)...)
     if verbose
         objv = evaluate_objv(updater, state, X, W, H)
         @printf("%-5s     %-13s    %-13s    %-13s\n", "Iter", "objv", "objv.change", "(W & H).change")
@@ -75,7 +73,7 @@ function nmf_skeleton!{T}(updater::NMFUpdater{T},
         if verbose
             preobjv = objv
             objv = evaluate_objv(updater, state, X, W, H)
-            @printf("%5d    %13.6e    %13.6e    %13.6e\n", 
+            @printf("%5d    %13.6e    %13.6e    %13.6e\n",
                 t, objv, objv - preobjv, dev)
         end
     end
@@ -85,5 +83,3 @@ function nmf_skeleton!{T}(updater::NMFUpdater{T},
     end
     return Result{T}(W, H, t, converged, objv)
 end
-
-