gendata and testondata correction in code and documentation

README.md

@@ -219,9 +219,10 @@ All result files are saved in /res directory. To plot a graph run /res/plotcompt
 
 For the computional example on data use the following.
 
-The script `gandata.jl` generates `t = 75000000` realisations of `n = 4` dimensional data form the `t`-multivariate distribution with `\nu = 14` degrees of freedom. 
+The script `gandata.jl` generates `t = 100000000` realisations of `n = 4` dimensional data form the `t`-multivariate distribution with `\nu = 14` degrees of freedom, and theoretical 
+super-diagonal elements of those cumulants. Rasults are saved in `data/datafortests.jld`
 
-The script `testondata.jl` computes cumulant tensors of order `m = 1 - 6` for those data and displays some of cumulants valuse on charts. For superdiagonal values the comparison with theoretical cumulants values of the distrubution is supplied.
+The script `testondata.jl` computes cumulant tensors of order `m = 1 - 6` for `data/datafortests.jld`, results are saved in `data/cumulants.jld`.
 
 # Citing this work
 

test/testondata.jl

@@ -1,69 +1,18 @@
 #!/usr/bin/env julia
 
-using NPZ
+using JLD
 using Cumulants
 addprocs()
 @everywhere using Cumulants
-using PyCall
-@pyimport matplotlib as mpl
-mpl.use("Agg")
-using PyPlot
-mpl.rc("text", usetex=true)
-mpl.rc("font", family="serif", size = 12)
-
-
-"""
-  pltdiag(l::Vector{String}, codd::Vector{Float64}, cev::Vector{Float64})
-
-Plots a chart of superdiagonal elements of cumulants of odd and even order. Those
-elements are in vectors codd and cev and are named by l. Theoretical values are
-computed as those of t-student standard distribution with 14 degrees of freedom.
-"""
-function pltdiag(l::Vector{String}, codd::Vector{Float64}, cev::Vector{Float64})
-  n = length(codd)
-  k = parse(Int, l[2][2])
-  fig, ax = subplots(figsize = (4.6, 4.6))
-  ax[:plot](cev, "o", color = "blue", label = l[2], markersize=4)
-  ax[:plot]([fill(tcum(14, k), n)...], "--", color = "blue", label = "theoretical "*l[2])
-  ax[:plot](codd, "s", color = "red", label = l[1], markersize=4)
-  ax[:plot](zeros(n), "--", color = "red", label = "theoretical "*l[1])
-  ax[:set_ylabel]("superdiagonal element")
-  ax[:set_xlabel]("superdiagonal element number")
-  ax[:legend](fontsize = 12, loc = 5)
-  fig[:savefig]("res/diagcumel"*l[2][2:end]*".eps")
-end
-
-"""
-  pltall(l::Vector{String}, v::Vector{Float64}, v1::Vector{Float64})
-
-Plots a chart of all elements of cumulants in a vectorised form v and v1 named by l.
-"""
-
-function pltall(l::Vector{String}, v::Vector{Float64}, v1::Vector{Float64})
-  fig, ax = subplots(figsize = (4.6, 4.6))
-  ax[:plot](v1, "o", color = "blue", label = l[2], markersize=3)
-  ax[:plot](v, "s", color = "red", label = l[1], markersize=3)
-  ax[:set_ylabel]("cumulant's element")
-  ax[:set_xlabel]("element's number of vectorised cumulat")
-  ax[:legend](fontsize = 12, loc = 4)
-  fig[:savefig]("res/allcumels"*l[2][2:end]*".eps")
-end
-
-"""
-  hypdiag{T <: AbstractFloat, N}(a::Array{T, N})
-
-Returns a vector of hyperdiagonal elements of array a
-"""
-hypdiag{T <: AbstractFloat, N}(a::Array{T, N}) = [a[fill(i,N)...] for i in 1:size(a,1)]
 
 function main()
-x = npzread("testdata.npz")
-   c = cumulants(x, 6)
-   ct = [convert(Array, c[i]) for i in 1:length(c)]
-   pltdiag(["c3", "c4"], hypdiag(ct[3]), hypdiag(ct[4]))
-   pltdiag(["c5", "c6"], hypdiag(ct[5]), hypdiag(ct[6]))
-   pltall(["c3", "c4"], vec(ct[3]), vec(ct[4]))
-   pltall(["c5", "c6"], vec(ct[5]), vec(ct[6]))
+  d = try load("data/datafortests.jld")
+  catch
+    println("please run gendata.jl")
+    return ()
+  end
+  c = cumulants(d["data"], 6)
+  save("data/cumulants.jld", Dict("cumulant" => c))
 end
 
 main()