11.1-filter_app_no_log-PS1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (11.1) Application of filter with new distance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook we use the new objective function $D_{new} = D_{HD}\\times D_{euc}$ in combination with the averaging filter designed in notebook 10. The filter width will be chosen so that the autocorrelation function of the artificial experimental lineage is $1/e$.\n",
    "\n",
    "Let's start by importing the SSA and the experimental data (only to be used to given initial volumes, molecule numbers and exponential growth rates) and processing it as was done in notebook 5:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "include(\"./SSA_file.jl\"); using .SSAmod;\n",
    "include(\"./extract_gens.jl\"); using .extract;\n",
    "using DelimitedFiles;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filelist = readdir(\"Analysis_MC4100_37C/MC4100_37C/\"); # take the file names - each file is for a different lineage.\n",
    "raw_data = []; # define the raw data array.\n",
    "for (i,file) in enumerate(sort!(filelist))\n",
    "    push!(raw_data,readdlm(string(\"Analysis_MC4100_37C/MC4100_37C/\", file), ',', Float64, '\\n'))\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fluor_all_lins = [raw_data[x][:,4] for x in 1:length(raw_data)]; # non-separated fluor data.\n",
    "vol_all_lins = [raw_data[x][:,3] for x in 1:length(raw_data)]; # non-separated vol data.\n",
    "\n",
    "fluor_sep_all_lins = extract_gens(raw_data,4); # the fluor. data for each lineage sep into gens.\n",
    "vol_sep_all_lins = extract_gens(raw_data,3); # the vol. data for each lineage sep into gens.\n",
    "times_sep_all_lins = extract_gens(raw_data,1); # the time pt data for each lineage sep into gens.\n",
    "\n",
    "fpm = readdlm(\"MN_props.csv\")[1];\n",
    "exp_grs = readdlm(\"exp_grs_all.csv\", ',', Float64, '\\n');\n",
    "\n",
    "num_sep_all_lins = []; # sep into gens.\n",
    "for i in 1:length(fluor_sep_all_lins)\n",
    "    push!(num_sep_all_lins,fluor_sep_all_lins[i]./fpm)\n",
    "end\n",
    "\n",
    "# un-sep molecule number and concs for each lineage (including 70th gen to be removed) later).\n",
    "num_all_lins = [fluor_all_lins[x]./fpm for x in 1:length(fluor_all_lins)];\n",
    "conc_all_lins = [num_all_lins[x]./vol_all_lins[x] for x in 1:length(fluor_all_lins)];\n",
    "\n",
    "v0_n0_th = []; # 2-d array to storing (1) the initial values of vol (2) molecule #  and (3) theta for each gen in each lin\n",
    "for x in 1:length(fluor_all_lins) # the lin loop\n",
    "    v0_n0_th_x = [];\n",
    "    for y in 1:length(fluor_sep_all_lins[x]) # the gen loop 1 --> 69\n",
    "        num = fluor_sep_all_lins[x][y][1]./fpm;\n",
    "        push!(v0_n0_th_x, [vol_sep_all_lins[x][y][1], num, exp_grs[x,y]])\n",
    "    end\n",
    "    push!(v0_n0_th, v0_n0_th_x)\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First attempt at inference from artificial data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's create the experimental data of which we wish to infer the parameters of. We again introduce the lineage function created in notebook 5. We set $\\alpha_0 = 5.0$, $\\alpha_1 = 0.3$, $\\beta_0 = 1.0$ and $\\beta_1 = 0.5$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "true_par = [5.0,0.3,1.0,0.5];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Single_lin (generic function with 1 method)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lineage_data = num_sep_all_lins[1]; # take the data for the first lineage, this gives the data form for Single_lin.\n",
    "lin_ic = v0_n0_th[1]; # pre-set params for lineage 1.\n",
    "\n",
    "function Single_lin(lin_data::Array{Array{Float64,1},1}, inf_par::Array{Float64,1}, ics::Array{Any,1}) # arguments are wrt each lineage.\n",
    "    SSA_data_c = [];\n",
    "    for (i,gen) in enumerate(lin_data)\n",
    "        ssa = SSA_deg_zero(1, inf_par, ics[i], length(gen)); # for each gen run the SSA with correct ics.\n",
    "        push!(SSA_data_c, ssa[2][:]);\n",
    "    end\n",
    "    return convert(Array{Array{Float64,1},1},SSA_data_c) # return \n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We take the initial conditions on molecule numbers and volume from lineage 1 of the Tanouchi data, as well as the fluorescence per molecule and exponenital growth rate in each generation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "expt_ssa_conc = Single_lin(lineage_data, true_par, v0_n0_th[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot this data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Plots.PyPlotBackend()"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using GpABC, LambertW, Distances, Plots, Distributions, LaTeXStrings, StatsBase, Statistics, LinearAlgebra; pyplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PyPlot.plot(range(1,length(vcat(expt_ssa_conc...)[:]),step=1),vcat(expt_ssa_conc...)[:]);\n",
    "PyPlot.ylabel(L\"c_{true}(t)\"); PyPlot.xlabel(L\"t\"); PyPlot.xlim([1,length(vcat(expt_ssa_conc...)[:])]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the histogram (appropriately chosen x axis) and store the bin values as from the PDF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "0.9899999999999998"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = PyPlot.subplots(1,1);\n",
    "mod_bins = LinRange(0.0, maximum(vcat(expt_ssa_conc...)[:])*1.5, 100);\n",
    "true_bin_vals, other_stuff = ax.hist(vcat(expt_ssa_conc...)[:], bins = mod_bins, density = true);\n",
    "print(\"\\n\",sum(true_bin_vals*(maximum(vcat(expt_ssa_conc...)[:])*1.5/100))) # check the sum of bins is 1.\n",
    "\n",
    "true_bin_vals_form = convert(Array{Float64,2},transpose(true_bin_vals));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at the autocorrelation function of the lineage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "using StatsBase;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "expt_ac = autocor(vcat(expt_ssa_conc...)[:], range(0, length(vcat(expt_ssa_conc...)[:])-1, step=1), demean = true);\n",
    "fig, ax = PyPlot.subplots(1,1, sharex = true);\n",
    "ax.plot(expt_ac); ax.plot(ones(length(expt_ac)).* exp(-1)); ax.set_xlim(0,20);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly this is not reasonable. Let's choose $n = 4$ and plot the filtered experimental SSA lineage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 4;\n",
    "\n",
    "lin_expt = vcat(expt_ssa_conc...); filter_expt = filter_lin(expt_ssa_conc, n)[2]\n",
    "filter_expt_form = hcat(filter_expt);\n",
    "\n",
    "fig, axs = PyPlot.subplots(2, 1, sharex = true, tight_layout = true);\n",
    "axs[2].set_xlabel(L\"t\"); axs[1].set_ylabel(L\"c_{exp}(t)\"); axs[2].set_ylabel(L\"c_{filter}(t)\"); \n",
    "axs[1].plot(range(1,length(lin_expt),step=1),lin_expt); axs[2].plot(range(1,length(filter_expt),step=1),filter_expt);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "simulator_function_conc (generic function with 1 method)"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# function that returns the SSA concentration for lineage specified abvove.\n",
    "function simulator_function_conc(var_params::Array{Float64,1})\n",
    "    lin_conc = filter_lin(Single_lin(lineage_data, var_params, lin_ic)[:], n)[2] # choose up-sep form [2]\n",
    "    return hcat(lin_conc)::Array{Float64,2}\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create the new distance function that takes in the sample trajectory vector and experimental trajectory as inputs and outputs the product of the hellinger distance and the euclidean distance between the two trajectories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "new_distance (generic function with 1 method)"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function new_distance(samp_traj::Array{Float64,1}, exp_traj::Array{Float64,1})\n",
    "    euc_dist = euclidean(samp_traj[:], exp_traj[:]); # euclidean distance\n",
    "    samp_bins = normalize(fit(Histogram, samp_traj[:], mod_bins), mode=:probability).weights;\n",
    "    exp_bins = normalize(fit(Histogram, exp_traj[:], mod_bins), mode=:probability).weights;\n",
    "    hell_dist = hellinger(samp_bins, exp_bins); # HD\n",
    "    \n",
    "    return euc_dist*hell_dist::Float64 # return the product\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66.03432952183275"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "thres_cutoff = sum(new_distance(simulator_function_conc(true_par)[:], filter_expt_form[:]) for i in 1:1000)/1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.008103 seconds (22.95 k allocations: 2.003 MiB)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "64.37538191989117"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@time new_distance(simulator_function_conc(true_par)[:], filter_expt_form[:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC rejection simulation. ϵ = 500.0.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:47\n",
      "┌ Info: GpABC rejection simulation. Accepted 48/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 97/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 140/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 194/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 239/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 288/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 333/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 387/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 442/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 498/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 546/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 586/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 634/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 686/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 739/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 787/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 842/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 892/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 940/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 993/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC SMC simulation ϵ = 250.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 51/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 100/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 134/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 180/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 226/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 271/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 312/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 364/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 407/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 450/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 485/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 520/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 565/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 621/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 670/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 716/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 762/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 815/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 868/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 922/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 970/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 150.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 47/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 85/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 125/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 173/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 205/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 257/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 309/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 359/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 399/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 447/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 490/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 526/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 564/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 607/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 655/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 703/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 744/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 781/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 824/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 863/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 900/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 954/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 100.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 43/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 81/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 134/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 184/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 238/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 284/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 324/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 374/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 427/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 462/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 509/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 557/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 604/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 641/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 692/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 738/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 788/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 845/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 897/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 937/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 995/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 80.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 29/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 52/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 84/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 112/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 136/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 163/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 192/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 224/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 240/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 267/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 292/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 318/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 353/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 370/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 396/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 421/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 448/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 473/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 494/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 521/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 541/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 565/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 585/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 619/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 642/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 661/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 681/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 702/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 721/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 748/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 770/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 792/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 812/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 838/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 862/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 903/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 937/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 973/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 70.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 25/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 55/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 71/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 96/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 122/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 148/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 168/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 186/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 213/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 244/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 273/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 296/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 323/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 342/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 370/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 389/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 424/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 453/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 475/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 500/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 520/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 551/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 567/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 583/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 618/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 641/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 667/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 687/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 717/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 746/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 771/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 799/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 818/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 843/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 865/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 886/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 916/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 950/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 980/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 65.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 20/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 46/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 66/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 89/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 116/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 144/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 170/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 196/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 218/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 240/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 262/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 280/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 307/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 336/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 366/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 392/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 414/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 435/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 456/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 486/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 514/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 543/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 563/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 590/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 609/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 616/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 641/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 661/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 692/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 714/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 735/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 763/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 782/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 807/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 834/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 865/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 889/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 913/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 940/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 962/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 991/41000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_particles = 1000;\n",
    "threshold_schedule = [500.0, 250.0, 150.0, 100.0, 80.0, 70.0, 65.0];\n",
    "\n",
    "priors = [Uniform(0, 10.0), Uniform(0.0, 1.8), Uniform(0, 10.0),\n",
    "          Uniform(0.0, 1.8)];\n",
    "\n",
    "sim_abcsmc_res_conc_1 = SimulatedABCSMC(filter_expt_form,\n",
    "    simulator_function_conc,\n",
    "    priors,\n",
    "    threshold_schedule,\n",
    "    n_particles;\n",
    "    write_progress=true,\n",
    "    distance_function = new_distance,\n",
    "    max_iter = convert(Int,5E4))\n",
    "\n",
    "# plot the results.\n",
    "population_colors=[\"#351D17\", \"#502C23\", \"#754134\", \"#935343\", \"#B86854\",\"#DA7E67\",\"#E57053\"]#,\"#E75935\",\"#E84D26\",\"#E84117\",\"#CF3008\",\"#AB2402\",\"#351D17\"]\n",
    "plot(sim_abcsmc_res_conc_1, population_colors=population_colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 8.241086427073727\n",
       " 0.8085200496677027\n",
       " 0.5233407617205565\n",
       " 0.15170630908582114"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pars_conc_1 = [median(sim_abcsmc_res_conc_1.population[end][:,i]) for i in 1:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 5.0\n",
       " 0.3\n",
       " 1.0\n",
       " 0.5"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_par"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the differences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       "  3.2410864270737267\n",
       "  0.5085200496677027\n",
       " -0.47665923827944345\n",
       " -0.34829369091417883"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff = (pars_conc_1 - true_par)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot an SSA trajectory using the inferred parameters and compare against the experimental SSA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.015953 seconds (45.84 k allocations: 4.263 MiB)\n"
     ]
    }
   ],
   "source": [
    "single = @time Single_lin(num_sep_all_lins[1], pars_conc_1, v0_n0_th[1]); # do for first gen.\n",
    "concs_ssa_1 = vcat(single[1:length(single)]...)[:]; expt_c = vcat(expt_ssa_conc...)[:];\n",
    "\n",
    "fig, axs = PyPlot.subplots(2, 1, sharex = true, tight_layout = true);\n",
    "axs[2].set_xlabel(L\"t\"); axs[1].set_ylabel(L\"c_{exp}(t)\"); axs[2].set_ylabel(L\"c_{SSA}(t)\"); \n",
    "axs[1].plot(range(1,length(expt_c),step=1),expt_c); axs[2].plot(range(1,length(concs_ssa_1),step=1),concs_ssa_1);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The inability to infer parameters here seems to arise from the indistinguishability of parameter sets with respect to this objective function of the HD. This is also shown above by the similarity of the behaviour in the concentration trajectories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hellinger distance between these is: 0.1300734359179609"
     ]
    }
   ],
   "source": [
    "fig, ax = PyPlot.subplots(1, 2, sharey = true);\n",
    "true_bin_vals_inf, other_stuff = ax[1].hist(concs_ssa_1[:], bins = mod_bins, density = true);\n",
    "ax[1].set_title(\"inferred params\"); \n",
    "true_bin_vals, other_stuff = ax[2].hist(expt_c[:], bins = mod_bins, density = true);\n",
    "ax[2].set_title(\"real params\");\n",
    "print(\"Hellinger distance between these is: \", hellinger(true_bin_vals_inf[:],true_bin_vals[:])) # print the bin values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run them again!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC rejection simulation. ϵ = 500.0.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:47\n",
      "┌ Info: GpABC rejection simulation. Accepted 48/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 101/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 149/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 200/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 262/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 320/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 360/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 423/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 477/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 528/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 575/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 622/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 681/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 722/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 784/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 833/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 887/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 928/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 984/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC SMC simulation ϵ = 250.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 49/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 87/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 142/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 190/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 234/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 275/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 316/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 356/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 406/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 449/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 490/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 535/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 583/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 628/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 659/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 697/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 735/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 783/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 818/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 877/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 920/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 970/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 150.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 59/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 121/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 179/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 236/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 289/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 347/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 396/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 449/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 511/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 548/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 609/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 658/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 724/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 786/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 829/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 883/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 946/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 996/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation ϵ = 100.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 43/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 92/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 137/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 180/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 217/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 267/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 322/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 377/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 417/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 462/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 506/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 547/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 593/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 631/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 679/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 730/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 774/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 825/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 867/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 918/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 968/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 80.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 31/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 55/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 74/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 105/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 127/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 148/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 170/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 192/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 212/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 242/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 260/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 285/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 317/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 345/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 375/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 397/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 425/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 449/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 476/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 506/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 533/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 561/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 594/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 614/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 642/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 657/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 678/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 703/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 727/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 761/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 781/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 804/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 824/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 852/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 872/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 889/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 917/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 942/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 963/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 983/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 70.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 26/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 49/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 79/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 106/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 130/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 153/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 179/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 208/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 233/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 264/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 292/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 313/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 341/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 359/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 385/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 407/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 432/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 449/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 472/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 492/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 520/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 539/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 565/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 590/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 616/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 635/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 657/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 681/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 700/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 733/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 751/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 770/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 796/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 822/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 843/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 870/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 905/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 929/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 952/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 976/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 995/41000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 65.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 22/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 50/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 71/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 83/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 101/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 124/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 147/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 164/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 185/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 212/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 230/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 247/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 265/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 290/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 307/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 335/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 361/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 381/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 406/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 421/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 448/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 462/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 485/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 507/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 528/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 547/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 567/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 588/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 602/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 613/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 634/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 651/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 672/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 695/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 714/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 733/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 760/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 778/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 812/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 830/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 846/41000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 870/42000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 890/43000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 908/44000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 926/45000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 941/46000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 965/47000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 986/48000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_particles = 1000;\n",
    "threshold_schedule = [500.0, 250.0, 150.0, 100.0, 80.0, 70.0, 65.0];\n",
    "\n",
    "priors = [Uniform(0, 10.0), Uniform(0.0, 1.8), Uniform(0, 10.0),\n",
    "          Uniform(0.0, 1.8)];\n",
    "\n",
    "sim_abcsmc_res_conc_2 = SimulatedABCSMC(filter_expt_form,\n",
    "    simulator_function_conc,\n",
    "    priors,\n",
    "    threshold_schedule,\n",
    "    n_particles;\n",
    "    write_progress=true,\n",
    "    distance_function = new_distance,\n",
    "    max_iter = convert(Int,5E4))\n",
    "\n",
    "# plot the results.\n",
    "population_colors=[\"#351D17\", \"#502C23\", \"#754134\", \"#935343\", \"#B86854\",\"#DA7E67\",\"#E57053\",\"#E75935\",\"#E84D26\",\"#E84117\",\"#CF3008\",\"#AB2402\",\"#351D17\"]\n",
    "plot(sim_abcsmc_res_conc_2, population_colors=population_colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 6.406738630942437\n",
       " 0.37151641743770514\n",
       " 0.987812190590269\n",
       " 0.1747463643066638"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pars_conc_2 = [median(sim_abcsmc_res_conc_2.population[end][:,i]) for i in 1:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 5.0\n",
       " 0.3\n",
       " 1.0\n",
       " 0.5"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_par"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the differences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       "  1.4067386309424368\n",
       "  0.07151641743770515\n",
       " -0.012187809409730965\n",
       " -0.3252536356933362"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff_2 = (pars_conc_2 - true_par)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC rejection simulation. ϵ = 500.0.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:47\n",
      "┌ Info: GpABC rejection simulation. Accepted 54/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 102/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 152/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 194/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 242/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 304/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 346/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 400/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 446/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 496/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 540/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 578/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 633/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 681/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 726/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 786/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 843/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 904/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC rejection simulation. Accepted 954/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/rejection.jl:87\n",
      "┌ Info: GpABC SMC simulation ϵ = 250.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 39/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 75/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 125/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 166/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 210/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 256/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 301/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 352/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 393/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 435/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 474/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 521/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 582/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 628/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 656/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 704/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 751/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 797/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 841/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 891/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 925/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 973/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 150.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 18/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 35/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 47/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 66/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 83/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 100/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 110/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 125/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 133/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 149/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 168/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 186/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 200/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 213/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 229/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 241/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 251/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 265/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 278/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 300/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 312/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 329/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 342/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 365/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 377/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 394/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 411/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 424/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 438/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 451/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 473/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 491/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 508/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 524/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 539/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 556/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 572/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 587/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 608/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 620/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 637/41000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 658/42000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 674/43000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 685/44000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 702/45000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 720/46000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 734/47000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 760/48000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 772/49000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 785/50000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Warning: Simulation reached maximum 50000 iterations before finding 1000 particles - will return 785\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:248\n",
      "┌ Info: GpABC SMC simulation ϵ = 100.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 25/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 52/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 81/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 111/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 141/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 169/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 201/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 225/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 265/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 286/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 323/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 351/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 376/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 408/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 439/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 468/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 504/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 534/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 569/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 609/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 639/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 661/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 686/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 722/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 747/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 775/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 800/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 822/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 853/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 885/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 912/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 939/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 973/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 80.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 27/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 46/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 69/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 90/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 121/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 151/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 175/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 213/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 242/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 269/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 292/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 314/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 343/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 368/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 395/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 424/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 445/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 464/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 492/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 509/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 543/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 572/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 598/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 620/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 646/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 669/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 703/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 729/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 747/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 779/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 812/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 841/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 869/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 898/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 926/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 946/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 976/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 70.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 31/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 61/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 81/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 104/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 140/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 169/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 202/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 233/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 261/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 292/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 325/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 351/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 374/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 400/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 425/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 449/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 479/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 503/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 540/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 564/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 596/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 628/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: GpABC SMC simulation accepted 662/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 696/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 721/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 748/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 787/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 822/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 855/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 888/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 921/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 944/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 971/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 993/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation ϵ = 65.0\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:193\n",
      "┌ Info: GpABC SMC simulation accepted 17/1000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 34/2000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 51/3000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 64/4000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 78/5000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 92/6000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 107/7000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 128/8000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 147/9000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 171/10000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 193/11000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 215/12000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 243/13000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 256/14000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 272/15000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 285/16000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 304/17000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 324/18000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 348/19000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 367/20000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 388/21000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 407/22000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 422/23000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 437/24000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 450/25000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 471/26000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 490/27000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 506/28000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 528/29000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 545/30000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 569/31000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 584/32000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 600/33000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 622/34000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 647/35000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 669/36000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 679/37000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 693/38000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 714/39000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 732/40000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 752/41000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 774/42000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 796/43000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 817/44000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 842/45000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 857/46000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 875/47000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 889/48000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 904/49000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Info: GpABC SMC simulation accepted 925/50000 particles.\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:238\n",
      "┌ Warning: Simulation reached maximum 50000 iterations before finding 1000 particles - will return 925\n",
      "└ @ GpABC /home/s1402978/.julia/packages/GpABC/cR3wm/src/abc/smc.jl:248\n"
     ]
    },
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_particles = 1000;\n",
    "threshold_schedule = [500.0, 250.0, 150.0, 100.0, 80.0, 70.0, 65.0];\n",
    "\n",
    "priors = [Uniform(0, 10.0), Uniform(0.0, 1.8), Uniform(0, 10.0),\n",
    "          Uniform(0.0, 1.8)];\n",
    "\n",
    "sim_abcsmc_res_conc_3 = SimulatedABCSMC(filter_expt_form,\n",
    "    simulator_function_conc,\n",
    "    priors,\n",
    "    threshold_schedule,\n",
    "    n_particles;\n",
    "    write_progress=true,\n",
    "    distance_function = new_distance,\n",
    "    max_iter = convert(Int,5E4))\n",
    "\n",
    "# plot the results.\n",
    "population_colors=[\"#351D17\", \"#502C23\", \"#754134\", \"#935343\", \"#B86854\",\"#DA7E67\",\"#E57053\",\"#E75935\",\"#E84D26\",\"#E84117\",\"#CF3008\",\"#AB2402\",\"#351D17\"]\n",
    "plot(sim_abcsmc_res_conc_3, population_colors=population_colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 7.614209203410708\n",
       " 0.5200621877426711\n",
       " 0.520189999845482\n",
       " 0.496955509021759"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pars_conc_3 = [median(sim_abcsmc_res_conc_3.population[end][:,i]) for i in 1:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       " 5.0\n",
       " 0.3\n",
       " 1.0\n",
       " 0.5"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_par"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the differences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4-element Array{Float64,1}:\n",
       "  2.6142092034107076\n",
       "  0.2200621877426711\n",
       " -0.479810000154518\n",
       " -0.003044490978240999"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff_3 = (pars_conc_3 - true_par)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary of results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model that we are attempting to infer the parameter for is:\n",
    "$$\\varnothing \\xrightarrow{a_1(t)}m\\, P\\xrightarrow{d}\\varnothing,$$\n",
    "where $a_1(t) = \\alpha_0 V(t)^{\\alpha_1}$ and $m$ is a random number drawn from a geometric distribution with time-dependent mean burst size $b(t) = \\beta_0 V(t)^{\\beta_1}$ and degradation rate $d = 0$. The volume of the system grows according to exponential growth law: $V(t) = V_0 e^{\\theta t}$. Later on in this sheet we also go onto assess the minimum threshold for the SMC-ABC data. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see the inferred medians of the posterior distributions in some tables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "using DataFrames;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [],
   "source": [
    "par_conc = convert(Array{Float64,2},transpose([true_par pars_conc_1 pars_conc_2 pars_conc_3]));\n",
    "df_conc = DataFrame(alpha_0 = par_conc[:,1], alpha_1 = par_conc[:,2], beta_0 = par_conc[:,3], beta_1 = par_conc[:,4]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><thead><tr><th></th><th>alpha_0</th><th>alpha_1</th><th>beta_0</th><th>beta_1</th></tr><tr><th></th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th></tr></thead><tbody><p>4 rows × 4 columns</p><tr><th>1</th><td>5.0</td><td>0.3</td><td>1.0</td><td>0.5</td></tr><tr><th>2</th><td>8.24109</td><td>0.80852</td><td>0.523341</td><td>0.151706</td></tr><tr><th>3</th><td>6.40674</td><td>0.371516</td><td>0.987812</td><td>0.174746</td></tr><tr><th>4</th><td>7.61421</td><td>0.520062</td><td>0.52019</td><td>0.496956</td></tr></tbody></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccc}\n",
       "\t& alpha\\_0 & alpha\\_1 & beta\\_0 & beta\\_1\\\\\n",
       "\t\\hline\n",
       "\t& Float64 & Float64 & Float64 & Float64\\\\\n",
       "\t\\hline\n",
       "\t1 & 5.0 & 0.3 & 1.0 & 0.5 \\\\\n",
       "\t2 & 8.24109 & 0.80852 & 0.523341 & 0.151706 \\\\\n",
       "\t3 & 6.40674 & 0.371516 & 0.987812 & 0.174746 \\\\\n",
       "\t4 & 7.61421 & 0.520062 & 0.52019 & 0.496956 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "4×4 DataFrame\n",
       "│ Row │ alpha_0 │ alpha_1  │ beta_0   │ beta_1   │\n",
       "│     │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m  │ \u001b[90mFloat64\u001b[39m  │ \u001b[90mFloat64\u001b[39m  │\n",
       "├─────┼─────────┼──────────┼──────────┼──────────┤\n",
       "│ 1   │ 5.0     │ 0.3      │ 1.0      │ 0.5      │\n",
       "│ 2   │ 8.24109 │ 0.80852  │ 0.523341 │ 0.151706 │\n",
       "│ 3   │ 6.40674 │ 0.371516 │ 0.987812 │ 0.174746 │\n",
       "│ 4   │ 7.61421 │ 0.520062 │ 0.52019  │ 0.496956 │"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_conc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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