Merge 3899ef7 into db62811

.travis.yml

@@ -17,14 +17,22 @@ matrix:
 notifications:
   email: false
 
-script:
-  - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-  - julia -e 'Pkg.clone(pwd())'
-  - julia -e 'Pkg.test("BioSimulator", coverage=true)'
+#script: # the default script is equivalent to the following
+#  - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
+#  - julia -e 'Pkg.clone(pwd()); Pkg.build("Example"); Pkg.test("Example"; coverage=true)';
 
 after_success:
-  - julia -e 'cd(Pkg.dir("BioSimulator")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
-  - julia -e 'cd(Pkg.dir("BioSimulator")); Pkg.add("Coverage"); using Coverage; Codecov.submit(Codecov.process_folder())'
-  - julia -e 'Pkg.add("Plots"); Pkg.add("GR")'
-  - julia -e 'Pkg.add("Documenter"); Pkg.add("JSON")'
-  - julia -e 'cd(Pkg.dir("BioSimulator")); include(joinpath("docs", "make.jl"))'
+  - julia -e 'if VERSION >= v"0.7.0-" using Pkg end; cd(Pkg.dir("BioSimulator")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())';
+  - julia -e 'if VERSION >= v"0.7.0-" using Pkg end; cd(Pkg.dir("BioSimulator")); Pkg.add("Coverage"); using Coverage; Codecov.submit(Codecov.process_folder())';
+
+jobs:
+  include:
+    - stage: "Documentation"
+      julia: 1.0
+      os: linux
+      script:
+        - julia -e 'using Pkg; Pkg.add("Documenter"); Pkg.add("TikzPictures"); Pkg.add("Plots")'
+        - julia --project=docs/ -e 'using Pkg; Pkg.instantiate();
+                                    Pkg.develop(PackageSpec(path=pwd()))'
+        - julia --project=docs/ docs/make.jl
+      after_success: skip

appveyor.yml

@@ -1,17 +1,20 @@
 environment:
   matrix:
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.7/julia-0.7-latest-win32.exe"
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.7/julia-0.7-latest-win64.exe"
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.7/julia-1.0-latest-win32.exe"
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.7/julia-1.0-latest-win64.exe"
-    - 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"
+  - 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_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.7/julia-1.0-latest-win32.exe"
-    - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.7/julia-1.0-latest-win64.exe"
-    - 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"
+   allow_failures:
+   - julia_version: 1
+   - julia_version: nightly
+
 branches:
   only:
     - master
@@ -24,20 +27,18 @@ notifications:
     on_build_status_changed: false
 
 install:
-  - ps: "[System.Net.ServicePointManager]::SecurityProtocol = [System.Net.SecurityProtocolType]::Tls12"
-# Download most recent Julia Windows binary
-  - ps: (new-object net.webclient).DownloadFile(
-        $env:JULIA_URL,
-        "C:\projects\julia-binary.exe")
-  - set PATH=C:\Miniconda3;C:\Miniconda3\Scripts;%PATH%
-# 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(), \"BioSimulator\"); Pkg.build(\"BioSimulator\")"
+  - 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(\"BioSimulator\")"
+  - 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%"

docs/make.jl

@@ -6,7 +6,7 @@ ENV["PLOTS_TEST"] = "true"
 
 makedocs(
   doctest  = false,
-  format   = :html,
+  format   = Documenter.HTML(),
   modules  = [BioSimulator],
   clean    = true,
   sitename = "BioSimulator.jl",
@@ -22,7 +22,6 @@ makedocs(
 deploydocs(
   repo   = "github.com/alanderos91/BioSimulator.jl.git",
   target = "build",
-  julia  = "0.6",
   deps   = nothing,
   make   = nothing
 )

docs/src/man/examples.md

@@ -4,15 +4,15 @@ The following examples illustrate BioSimulator.jl's interface and features.
 Each code block assumes BioSimulator.jl and Plots.jl are loaded; that is, `using BioSimulator, Plots`.
 
 ```@setup kendall
-using BioSimulator, Plots
+using BioSimulator, Plots, TikzPictures
 gr(fmt = :png, dpi = 300)
 ```
 ```@setup mmek
-using BioSimulator, Plots
+using BioSimulator, Plots, TikzPictures
 gr(fmt = :png, dpi = 300)
 ```
 ```@setup gene
-using BioSimulator, Plots
+using BioSimulator, Plots, TikzPictures
 gr(fmt = :png, dpi = 300)
 ```
 ```@setup brusselator_cascade
@@ -41,7 +41,7 @@ model <= Reaction("immigration", 0.5, "0 --> X")
 # Petri net; the "scale = 2" argument is optional and can be omitted
 # it is used to pass additional options for the underlying Tikz document
 fig = visualize(model, "scale = 2")
-nothing #hide
+TikzPictures.save(SVG("kendall_petri.svg"), fig) # hide
 ```
 ![](kendall_petri.svg)
 
@@ -88,7 +88,7 @@ model <= Reaction("Conversion", 0.1, "SE --> P + E")
 
 # Petri net
 fig = visualize(model)
-nothing #hide
+TikzPictures.save(SVG("mmek_petri.svg"), fig) # hide
 ```
 ![](mmek_petri.svg)
 
@@ -175,7 +175,7 @@ model = autoreg()
 
 # Petri net
 fig = visualize(model)
-nothing # hide
+TikzPictures.save(SVG("gene_petri.svg"), fig) # hide
 ```
 ![](gene_petri.svg)
 

src/BioSimulator.jl

@@ -4,13 +4,14 @@ __precompile__()
 
 using DataStructures
 using RecipesBase
-
-import TikzGraphs
+using SparseArrays
 using LightGraphs: DiGraph, add_edge!
+using Random
 
+import TikzGraphs
 import StatsFuns.RFunctions: poisrand
-
 import DataFrames: DataFrame
+import Statistics: mean, std
 
 import Base: (<=),
              (>=),

src/algorithm/odm.jl

@@ -106,7 +106,7 @@ end
     r.scaled_rates[i] = k[i]
     r.dependencies[i] = g[i]
     for j in eachindex(g[i])
-      r.dependencies[i][j] = findfirst(ix, g[i][j])
+      r.dependencies[i][j] = something(findfirst(isequal(g[i][j]), ix), 0)
     end
   end
 

src/algorithm/otl.jl

@@ -31,7 +31,7 @@ mutable struct OTL <: TauLeapMethod
   # end
   function OTL(end_time, ϵ, δ, β, stats_tracked)
     new(end_time, ϵ, δ, β,
-    0.0, Matrix{Float64}(0,0), Int[],
+    0.0, Matrix{Float64}(undef,0,0), Int[],
     stats_tracked,
     Dict{Symbol,Int}(
       :negative_excursions => 0,

src/backend/pvec.jl

@@ -24,13 +24,13 @@ Base.eltype(x::PVec{T}) where T = T
 
 ##### PVec interface #####
 intensity(x::PVec) = x.intensity
-isstable{T}(x::PVec{T})  = (x.error_bound <= eps(T) * x.intensity)
+isstable(x::PVec{T}) where T  = (x.error_bound <= eps(T) * x.intensity)
 
-@fastmath function update_errorbound!{T}(x::PVec{T}, xi::T, i::Integer)
+@fastmath function update_errorbound!(x::PVec{T}, xi::T, i::Integer) where T
   x.error_bound = x.error_bound + eps(T) * (x.intensity + x[i] + xi)
 end
 
-@fastmath function update_intensity!{T}(x::PVec{T}, xi::T, i::Integer)
+@fastmath function update_intensity!(x::PVec{T}, xi::T, i::Integer) where T
   # if x.intensity - x[i] + xi < 0
   #   error("""
   #   Intensity update failed!

src/backend/util.jl

@@ -60,15 +60,15 @@ function make_dependency_graph!(dg, reactions_dict)
   return dg
 end
 
-function make_species_vector(dict::Associative{Symbol,Species})
-  X0     = Array{Int}(length(dict))
-  id     = Array{Symbol}(length(dict))
+function make_species_vector(dict::AbstractDict{Symbol,Species})
+  X0     = zeros(Int, length(dict))
+  id     = Array{Symbol}(undef, length(dict))
   id2ind = Dict{Symbol,Int}()
 
   i = 1
   for (key, s) in dict
     X0[i] = s.population
-    id[i] = s.id
+    id[i] = Symbol(s.id)
     id2ind[key] = i
     i = i + 1
   end

src/interface/reaction.jl

@@ -62,7 +62,7 @@ function print_participants(io, participants)
   end
 end
 
-parse_reaction(formula::String) = parse_reaction(parse(formula))
+parse_reaction(formula::String) = parse_reaction(Meta.parse(formula))
 
 function parse_reaction(ex::Expr)
   reactants = OrderedDict{Symbol,Int}()

src/interface/simulate.jl

@@ -57,10 +57,10 @@ end
 
 function build_output(::Val{:fixed}, nspecies, epochs, ntrials, tfinal)
   n = epochs + 1
-  tdata = collect(linspace(0.0, tfinal, n))
+  tdata = collect(range(0.0, stop = tfinal, length = n))
   output = RegularEnsemble(ntrials, nspecies, epochs)
   for i in eachindex(output)
-    @inbounds copy!(output[i].tdata, tdata)
+    @inbounds copyto!(output[i].tdata, tdata)
   end
   return output
 end
@@ -100,7 +100,7 @@ end
 function simulate_chunk!(output, Xt, X0, algorithm, reactions, trial_set)
   a = propensities(reactions)
   for trial in trial_set
-    copy!(Xt, X0)
+    copyto!(Xt, X0)
     reset!(algorithm, Xt, reactions)
 
     xw = output[trial]

src/output/average_path.jl

@@ -12,7 +12,7 @@ function AveragePath(xw :: RegularEnsemble{T1,T2}) where {T1,T2}
   trials = length(xw)
 
   xmean = mean(xw[k].xdata for k in 1:trials)
-  temp = std([xw[k].xdata[i, j] for i in 1:d, j in 1:n, k in 1:trials], 3)
+  temp = std([xw[k].xdata[i, j] for i in 1:d, j in 1:n, k in 1:trials], dims=3)
   xstd = reshape(temp, n, d)
 
   return AveragePath{T1}(tdata, xmean, xstd)

src/output/petrinet.jl

@@ -55,11 +55,11 @@ function petri_net(model :: Network)
   end
 
   species_nodes  = collect(1:s)
-  species_labels = map(string, keys(species))
+  species_labels = [string(v) for v in keys(species)]
   species_styles = Dict( i => "draw, rounded corners, fill=blue!10, font=\\large" for i in species_nodes )
 
   reaction_nodes = collect(s+1:s+r)
-  reaction_labels = map(string, keys(reactions))
+  reaction_labels = [string(v) for v in keys(reactions)]
   reaction_styles = Dict( i => "draw, rounded corners, thick, fill=red!10, font=\\large" for i in reaction_nodes)
 
   node_labels = [ species_labels; reaction_labels ]
@@ -85,7 +85,7 @@ function draw(x :: PetriNet, options)
   edge_labels     = x.edge_labels
   edge_styles     = x.edge_styles
 
-  labels = map(x -> replace(x, "_", "\$\\cdot\$"), labels)
+  labels = map(x -> replace(x, "_" => "\$\\cdot\$"), labels)
 
   TikzGraphs.plot(graph, TikzGraphs.Layouts.Layered(),
     labels,

src/output/summary.jl

@@ -57,7 +57,7 @@ function get_regular_path(xw::SamplePath{T1,T2}, tfinal, epochs) where {T1,T2}
 
   x0 = xw.xdata[1]
 
-  tdata = collect(linspace(0.0, tfinal, max_epoch))
+  tdata = collect(range(0.0, stop = tfinal, length = max_epoch))
   xdata = zeros(T2, length(xw.xdata[1]), max_epoch)
   epoch = 1
 
@@ -103,9 +103,9 @@ end
 
   if species == nothing
     species = collect(keys(result.id2index))
-    labels = map(String, keys(result.id2index))
+    labels = [string(s) for s in keys(result.id2index)]
   else
-    labels = map(s -> String(s), species)
+    labels = [string(s) for s in species]
   end
 
   label --> reshape(labels, 1, length(labels))

test/independent.jl

@@ -1,26 +1,30 @@
-x0 = 1_000
-model_size = [10, 100, 500]
-
-t = 10.0
-n = 1
-u = 5357
-m = 1
-
-algorithms = [
+function test_independent()
+  x0 = 1_000
+  model_size = [10, 100, 500]
+
+  t = 10.0
+  n = 1
+  u = 5357
+  m = 1
+
+  algorithms = [
   Direct(),
   FirstReaction(),
   NextReaction(),
   OptimizedDirect(),
   TauLeaping(),
   StepAnticipation()
-]
-
-for algorithm in algorithms
-  @printf "%+6s\n" algorithm
-  for M in model_size
+  ]
+  
+  for algorithm in algorithms
+    @printf "%+6s\n" algorithm
+    for M in model_size
       model = independent(M, x0)
-      srand(u)
+      seed!(u)
       @printf "%+6s: %3d" "M" M
       @time run_test(model, algorithm, t, n, m)
+    end
   end
 end
+
+test_independent()