pkofod

using Base.Test

Base.hcat(Xin::Union{SparseVector, SparseMatrixCSC}...) = hcat(map(SparseMatrixCSC, Xin)...)
Base.vcat(Xin::Union{SparseVector, SparseMatrixCSC}...) = vcat(map(SparseMatrixCSC, Xin)...)
Base.hcat(Xin::Union{Vector, AbstractSparseVector}...) = hcat(map(sparse, Xin)...)
Base.vcat(Xin::Union{Vector, AbstractSparseVector}...) = vcat(map(sparse, Xin)...)

function Base.hcat(Xin::Union{Matrix, Vector, SparseMatrixCSC}...)
    X = SparseMatrixCSC[issparse(x) ? x : sparse(x) for x in Xin]
    hcat(X...)

pkofod

julia> using Plots
INFO: Precompiling module Plots...
WARNING: Base.writemime is deprecated.
  likely near /home/pkm/.julia/v0.5/Plots/src/backends/gadfly.jl:696
WARNING: Base.writemime is deprecated.
  likely near /home/pkm/.julia/v0.5/Plots/src/backends/gadfly.jl:696
WARNING: Base.writemime is deprecated.
  likely near /home/pkm/.julia/v0.5/Plots/src/backends/gadfly.jl:696
WARNING: Base.writemime is deprecated.
  likely near /home/pkm/.julia/v0.5/Plots/src/backends/gadfly.jl:696

pkofod

using CUTEst
patho_problems=[       "ARGTRIGLS"
       "BENNETT5LS"
       "BOXBODLS"
       "BROYDN3DLS"
       "BROYDNBDLS"
       "CHWIRUT1LS"
       "CHWIRUT2LS"
       "CKOEHELB"
       "DANWOODLS"

pkofod

+- Any << abstract immutable size:0 >>
.  +- Cycle = Base.Cycle{I} << concrete immutable size:8 >>
.  +- Tuple = Tuple{Vararg{Char}} << concrete immutable size:0 >>
.  .  +- Union{AbstractArray{A<:AbstractArray{Int64,1},1},AbstractArray{Range{Int64},1},AbstractArray{UnitRange{Int64},1},Tuple{Vararg{Union{AbstractArray{Int64,1},Range{T}}}}} 
.  .  .  +- RangeVecIntList = Union{AbstractArray{A<:AbstractArray{Int64,1},1},AbstractArray{Range{Int64},1},AbstractArray{UnitRange{Int64},1},Tuple{Vararg{Union{AbstractArray{Int64,1},Range{T}}}}} 
.  .  +- Chars = Union{AbstractArray{Char,1},Char,Set{Char},Tuple{Vararg{Char}}} 
.  +- AbstractCmd = Base.AbstractCmd << abstract immutable size:0 >>
.  +- NewvarNode << concrete immutable size:8 >>
.  +- TopNode << concrete immutable size:8 >>
.  .  +- ExprNode = Union{Expr,GlobalRef,GotoNode,LabelNode,LineNumberNode,QuoteNode,SymbolNode,TopNode} 

pkofod

using BenchmarkTools
A = rand(10000)
B = Vector[rand(10) for i = 1:1000]
C = rand(10,1000)

D = rand(10000)
E = Vector[rand(10) for i = 1:1000]
F = rand(10, 1000)

function fast!(a, c)

pkofod

using BenchmarkTools
A = rand(10000)
B = Vector[rand(10) for i = 1:1000]
C = rand(10,1000)

D = rand(10000)
E = Vector[rand(10) for i = 1:1000]
F = rand(10, 1000)

function fast!(a, c)

pkofod

julia> using Optim

julia> function rosenbrock(x)
               N = length(x)
               fval = 0.0
               for i in 1:div(N, 2)
                   fval += 100(x[2i-1]^2 - x[2i])^2 + (x[2i-1] - 1.0)^2
               end
               fval
           end

pkofod

function LearnBase.learn!(solver::CrossEntropyMethod, env::AbstractEnvironment, doanim = false)

	# !!! INIT:

	# this is a mappable function of θ to reward
	cem_episode = θ -> begin
		π = cem_policy(env, θ)
		R, T = episode!(env, π; maxiter = solver.options[:maxiter])
		R
	end

pkofod

K = 5
N = 3
z = [rand(20000, K) for i =1:N]
P = [rand(20000) for i = 1:N]
Pm = rand(20000, N)
Pv = [@view Pm[:, j] for j = 1:N]
cache = zeros(20000, K)

function test1(P, z)
    for i in eachindex(P)

pkofod

using BenchmarkTools
K = 5
N = 3
z = [rand(20000, K) for i =1:N]
P = [rand(20000) for i = 1:N]
cache = zeros(20000, K)

function test1(P, z)
    for i in eachindex(P)
        cache .= P[i].*z[i]