Resolve errors in validation/tests

.travis.yml

@@ -1,11 +1,11 @@
 language: julia
 julia:
-    - 1.0
+    - 1
     - nightly
 before_install:
     - sudo apt-get install python3-matplotlib
 after_success:
-    - julia -e 'cd(Pkg.dir("DCEMRI")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
+    - julia -e 'using Pkg; Pkg.add("Coverage"); using Coverage; Coveralls.submit(process_folder())'
 ## uncomment the following lines to override the default test script
 #script:
 # - julia --color=yes -e 'using Pkg; Pkg.activate(); Pkg.instantiate(); Pkg.test()'

appveyor.yml

@@ -1,6 +1,6 @@
 environment:
   matrix:
-  - julia_version: 1.3
+  - julia_version: 1.5
   - julia_version: nightly
 
 platform:

src/DCEMRI.jl

@@ -2,7 +2,7 @@ module DCEMRI
 
 using ArgParse
 using Calculus    #.jacobian
-using MAT
+using MAT, PyPlot
 using Pkg, LinearAlgebra, Random, Statistics, Distributed, Printf, LsqFit
 
 export ser, r1eff, tissueconc, fitr1, fitdce, fitdata,
@@ -11,12 +11,6 @@ export ser, r1eff, tissueconc, fitr1, fitdce, fitdata,
 const verbose = true
 const version = v"0.2.2"
 
-if haskey(Pkg.installed(),"PyPlot")
-    using PyPlot
-else
-    # println("Optional package (PyPlot) not installed.")
-end
-
 include("util.jl")
 include("fitting.jl")
 include("models.jl")

src/demo.jl

@@ -1,24 +1,18 @@
 function demo(outdir::AbstractString="results")
-  cd(joinpath(dirname(pathof(DCEMRI)), "..", "demo"))
+  if outdir == "results"
+    outdir = joinpath(dirname(pathof(DCEMRI)), "..", "demo", "results")
+  end
+  outdir = abspath(outdir)
   isdir(outdir) || mkdir(outdir)
   println("Processing in vivo data ...")
 
+  datafile = joinpath(dirname(pathof(DCEMRI)), "..", "demo", "invivo.mat")
   # run the model
-  results = fitdata(datafile="invivo.mat", outfile="$outdir/results.mat", models=[2])
-
-  if !haskey(Pkg.installed(), "PyPlot")
-    # Do no make plots if PyPlot not installed
-    println("PyPlot not installed. Plots will not be produced.")
-  else
-    # plot the results
-    println("Plotting results ...")
-    makeplots(results; outdir=outdir)
-    if outdir == "results"
-      println("Results can be found in ", Pkg.dir("DCEMRI/demo/$outdir"))
-    else
-      println("Results can be found in $outdir")
-    end
-  end
+  results = fitdata(datafile=datafile, outfile="$outdir/results.mat", models=[2])
 
+  # plot the results
+  println("Plotting results ...")
+  makeplots(results; outdir=outdir)
+  println("Results can be found in $outdir")
   println("Demo run complete.")
 end

src/plotting.jl

@@ -52,7 +52,7 @@ function oplot2(front::Array{Float64,2}, back::Array{Float64,2}, mask::Array{Boo
   if r == 0.0
     back[:] = 0.0
   else
-    back = (back - minimum(back)) / r
+    @. back = (back - minimum(back)) / r
   end
   n,m = size(front)
   img = zeros(n,m,3)
@@ -64,10 +64,12 @@ function oplot2(front::Array{Float64,2}, back::Array{Float64,2}, mask::Array{Boo
       img[j,k,:] = jetrgb(s)
     else
       s = back[j,k]
-      cmidx = 100 - round(Int,99.0*s)
-      img[j,k,1] = s
-      img[j,k,2] = s
-      img[j,k,3] = s
+      if !isnan(s)
+        cmidx = 100 - round(Int,99.0*s)
+        img[j,k,1] = s
+        img[j,k,2] = s
+        img[j,k,3] = s
+      end
     end
   end
   img
@@ -84,8 +86,8 @@ function makeplots(mat::Dict; outdir::AbstractString="results")
   vp = mat["vp"]
   resid = mat["resid"]
   q = quantile(S0map[:], 0.99)
-  S0map[S0map .> q] = q
-  back = (S0map - minimum(S0map)) / (maximum(S0map) - minimum(S0map))
+  S0map[S0map .> q] .= q
+  back = @. (S0map - minimum(S0map)) / (maximum(S0map) - minimum(S0map))
   mask = convert(Array{Bool,2}, mat["mask"])
 
   figure(figsize=(4.5,4.5))
@@ -126,7 +128,7 @@ function makeplots(mat::Dict; outdir::AbstractString="results")
 
   figure()
   clf()
-  Ct = squeeze(maximum(Ct,1),1)
+  Ct = dropdims(maximum(Ct; dims=1); dims=1)
   x = oplot2(clamp.(Ct, 0.0, 5.0), back, mask)
   imshow(x, interpolation="nearest", cmap="jet", vmin=0, vmax=5)
   title("max tissue conc., \$C_t\$ (mmol)")

src/science.jl

@@ -233,6 +233,7 @@ function fitdata(opts::Dict)
   end
   R1 = r1eff(dcedata, R10, TR, dceflip)
   Ct = tissueconc(R1, R10, relaxivity)
+  @. Ct[!isfinite(Ct)] = 0
   params, resid, modelmap = fitdce(Ct, mask, t, Cp, models=models)
 
   results = Dict()

src/validate.jl

@@ -1,11 +1,5 @@
 function analyzer(mat::Dict, outdir::AbstractString; dx=1, makeplots=true, isExt=false)
 
-  if (makeplots==true) && !haskey(Pkg.installed(),"PyPlot")
-    # Do no make plots if PyPlot not installed
-    println("PyPlot not installed. Plots will not be produced.")
-    makeplots=false
-  end
-
   R1map = mat["R10"]
   S0map = mat["S0"]
   modelmap = mat["modelmap"]
@@ -272,7 +266,7 @@ function makeQibaNoisy(n; nRep=10, doOverwrite=true, noiseSigma=-1.0)
     noiseSigma = 0.2 * dceDat[1,1,1] / sqrt(2)
   end
   # Add complex noise
-  Random.seed!(9876543210) # Fixed arbitrary seed for reproducible noise
+  Random.seed!(8702572558940514935) # Fixed arbitrary seed for reproducible noise
   dceDat = dceDat + noiseSigma * ( randn(size(dceDat)) + im*randn(size(dceDat)) )
   # Take the magntude of the complex signal
   dceDat = abs.(dceDat)

test/runtests.jl

@@ -1,7 +1,7 @@
 using DCEMRI
 using Test
 
-ccc4, cccnoisy4 = validate(4, makeplots=false)
+ccc4, cccnoisy4 = validate(4)
 @testset "QIBA v4 Extended Tofts Phantom" begin
   @test ccc4[1] >= 0.9998
   @test ccc4[2] >= 0.8904
@@ -11,10 +11,14 @@ ccc4, cccnoisy4 = validate(4, makeplots=false)
   @test round(cccnoisy4[3], sigdigits=2) >= 0.97
 end
 
-ccc6, cccnoisy6 = validate(6, makeplots=false)
+ccc6, cccnoisy6 = validate(6)
 @testset "QIBA v6 Standard Tofts Phantom" begin
   @test ccc6[1] >= 0.9999
   @test ccc6[2] >= 0.9999
   @test round(cccnoisy6[1], sigdigits=2) >= 0.84
   @test round(cccnoisy6[2], sigdigits=2) >= 0.86
 end
+
+@testset "In-vivo demo" begin
+  demo() # Just test if the function runs
+end