Merge pull request #23 from kescobo/julia07fixes

Move to julia 0.7

.travis.yml

@@ -3,8 +3,9 @@ language: julia
 os:
   - linux
   - osx
+  - windows
 julia:
-  - 0.6
+  - 0.7
   - nightly
 notifications:
   email: false
@@ -16,6 +17,7 @@ git:
 matrix:
  allow_failures:
  - julia: nightly
+ - os: windows
 
 ## uncomment and modify the following lines to manually install system packages
 #addons:

NEWS.md

@@ -0,0 +1,14 @@
+# News for Microbiome.jl
+
+## v0.3.0
+
+Major changes:
+- Dropped support for julia-0.6, moved on to julia-0.7
+- Moved Plotting and BioBakery utilities out to separate packages to reduce dependencies
+    - These two new packages will be released shortly
+- I'm keeping DataFrames dependency for now, though I'd like to move to IterableTables soonish (though constructors might be more sense in EcoBase)
+
+## Older versions
+
+I didn't have NEWS.md until v0.3. I doubt anyone cares, but I kinda tried to
+keep track in release notes.

REQUIRE

@@ -1,12 +1,7 @@
-julia 0.6
-SpatialEcology 0.3
+julia 0.7-alpha
+SpatialEcology 0.4
+StatsBase
 Reexport
-RecipesBase
-StatPlots
 Distances
 DataFrames
 Clustering
-Colors
-CSVFiles
-FileIO
-MicroLogging

docs/src/abundances.md

@@ -51,6 +51,8 @@ featurenames(abund2)
 
 ## Plotting
 
+**NOTE: The following functions are not currently working - I've moved them to a new package to simplify dependencies. I'm leaving the docs for now as a reference - see `Microbiome.jl` versions 0.2.1 and below for working versions**
+
 Some convenience plotting types are available using [`RecipesBase`](https://github.com/juliaplots/recipesbase.jl) and
 [StatPlots](https://github.com/juliaplots/StatPlots.jl)
 

docs/src/distances.md

@@ -31,6 +31,8 @@ variance(p, [1,2])
 
 ## Plotting
 
+**NOTE: The following functions are not currently working - I've moved them to a new package to simplify dependencies. I'm leaving the docs for now as a reference - see `Microbiome.jl` versions 0.2.1 and below for working versions**
+
 Some convenience plotting types are available using [`RecipesBase`](https://github.com/juliaplots/recipesbase.jl).
 
 ```@repl 2

src/Microbiome.jl

@@ -33,40 +33,24 @@ export
     optimalorder,
     optimalorder!,
     ginisimpson,
-    shannon,
-    ## plotting
-    hclustplot,
-    annotationbar,
-    ## utils
-    metaphlan_import,
-    panphlan_calcs,
-    bysample,
-    taxfilter,
-    taxfilter!,
-    qvalue!
+    shannon
 
 using Reexport
 @reexport using SpatialEcology
 @reexport using Distances
 
-using RecipesBase
-using StatPlots
+using LinearAlgebra
+using Statistics
 using StatsBase
 using DataFrames
-using FileIO
-using CSVFiles
-using MicroLogging
+using Clustering
 
-import SpatialEcology.@forward_func
-import Clustering: Hclust, hclust
+import SpatialEcology: @forward_func
 import Base: getindex, setindex, length
 
 include("ecotranslations.jl")
 include("abundances.jl")
 include("distances.jl")
 include("leafordering.jl")
-include("plotting.jl")
-include("biobakery_utils.jl")
-
 
 end  # module Microbiome

src/abundances.jl

@@ -1,14 +1,15 @@
 # Methods for absolute and relative abundances
 
 abundancetable(df::DataFrame) = ComMatrix(
-    Matrix{Float64}(df[2:end]),
-    string.(df[1]),
-    String.(names(df[2:end])))
+    convert(Matrix{Float64}, df[2:end]),
+        string.(df[1]),
+        string.(names(df[2:end]))
+    )
 
 abundancetable(table::AbstractArray{T,2},
-    site = ["sample_$x" for x in indices(table, 2)],
-    species = ["feature_$x" for x in indices(table, 1)]) where T<:Real =
-    ComMatrix(Float64.(table), species, site)
+    site = ["sample_$x" for x in axes(table, 2)],
+    species = ["feature_$x" for x in axes(table, 1)]
+    ) where T<:Real = ComMatrix(Float64.(table), species, site)
 
 
 """
@@ -28,7 +29,7 @@ function filterabund(abun::AbstractComMatrix, n::Int=minimum(10, nfeatures(abun)
 
     remainder = [sum(occurrences(abun)[srt[n+1:end], i]) for i in 1:size(abun, 2)]'
     newabun = vcat(newabun, remainder)
-    newrows = cat(1, featurenames(abun)[srt[1:n]], ["other"])
+    newrows = cat(featurenames(abun)[srt[1:n]], ["other"], dims=1)
 
     return abundancetable(newabun, samplenames(abun), newrows)
 end

src/distances.jl

@@ -34,7 +34,7 @@ function getdm(t::AbstractArray, distance::PreMetric)
 end
 
 function getdm(df::DataFrame, distance::PreMetric)
-    dm = pairwise(distance, Matrix(df[2:end]))
+    dm = pairwise(distance, convert(Matrix, df[2:end]))
     for i in eachindex(dm); if isnan(dm[i]); dm[i] = 1; end; end
     return DistanceMatrix(
             dm,
@@ -59,7 +59,7 @@ function getrowdm(arr::AbstractArray, distance::PreMetric)
 end
 
 function getrowdm(df::DataFrame, distance::PreMetric)
-    m = Matrix(df[2:end])'
+    m = convert(Matrix, df[2:end])'
     return DistanceMatrix(
             pairwise(distance, m),
             Vector(df[:,1]),
@@ -88,10 +88,10 @@ function pcoa(D::DistanceMatrix; correct_neg::Bool=false)
 end
 
 function sortedeig(M::Array{Float64,2})
-    f = eigfact(M)
+    f = eigen(M, scale=true, permute=true)
     v = real.(f.values)
     p = sortperm(v, rev = true)
-    return LinAlg.Eigen(v[p], real.(f.vectors[:,p]))
+    return LinearAlgebra.Eigen(v[p], real.(f.vectors[:,p]))
 end
 
 

src/leafordering.jl

@@ -86,5 +86,5 @@ For 2 multi-leaf branches, determine if one or two flips is required
 4 = flip both
 """
 function flip2(u::Int, m::Int, k::Int, w::Int, dm::Array{Float64,2})
-    indmin([dm[m,k], dm[u,k], dm[m,w], dm[u,w]])
+    argmin([dm[m,k], dm[u,k], dm[m,w], dm[u,w]])
 end