diff --git a/Project.toml b/Project.toml index eb936ab8..9673d57a 100644 --- a/Project.toml +++ b/Project.toml @@ -1,13 +1,12 @@ name = "AugmentedGaussianProcesses" uuid = "38eea1fd-7d7d-5162-9d08-f89d0f2e271e" authors = ["Theo Galy-Fajou "] -version = "0.10.1" +version = "0.10.2" [deps] +AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001" AdvancedHMC = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d" ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" -Dates = "ade2ca70-3891-5945-98fb-dc099432e06a" -Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7" Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" FastGaussQuadrature = "442a2c76-b920-505d-bb47-c5924d526838" Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c" @@ -15,7 +14,6 @@ ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210" InducingPoints = "b4bd816d-b975-4295-ac05-5f2992945579" KernelFunctions = "ec8451be-7e33-11e9-00cf-bbf324bd1392" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" -MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d" ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01" @@ -28,16 +26,15 @@ StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c" Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f" [compat] +AbstractMCMC = "2" AdvancedHMC = "0.2.13" ChainRulesCore = "0.9" -Distances = "0.8, 0.9, 0.10" Distributions = "0.21.5, 0.22, 0.23, 0.24" FastGaussQuadrature = "0.4" Flux = "0.10, 0.11, 0.12" ForwardDiff = "0.10" InducingPoints = "0.1" KernelFunctions = "0.8, 0.9" -MCMCChains = "0.3.15, 2.0, 3.0, 4.0" ProgressMeter = "1" RecipesBase = "1.0, 1.1" Reexport = "0.2, 1" diff --git a/docs/examples/.ipynb_checkpoints/Classification - BayesianSVM-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Classification - BayesianSVM-checkpoint.ipynb deleted file mode 100644 index 8eaa6750..00000000 --- a/docs/examples/.ipynb_checkpoints/Classification - BayesianSVM-checkpoint.ipynb +++ /dev/null @@ -1,277 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using DelimitedFiles\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5300-element Array{Float64,1}:\n", - " -1.0\n", - " 1.0\n", - " -1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " -1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " -1.0\n", - " -1.0\n", - " 1.0\n", - " ⋮ \n", - " -1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " 1.0\n", - " -1.0\n", - " 1.0" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "X = readdlm(\"data/banana_X_train\")\n", - "Y = readdlm(\"data/banana_Y_train\")[:];\n", - "unique(Y)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 4 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 13.033565 seconds (47.26 M allocations: 2.497 GiB, 8.08% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 8 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.103591 seconds (932.26 k allocations: 218.974 MiB, 29.09% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 16 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.161026 seconds (932.53 k allocations: 351.215 MiB, 23.87% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 32 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.280851 seconds (933.12 k allocations: 617.235 MiB, 19.89% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 64 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.593067 seconds (934.71 k allocations: 1.128 GiB, 15.72% gc time)\n" - ] - } - ], - "source": [ - "# Run sparse classification with increasing number of inducing points\n", - "Ms = [4, 8, 16, 32, 64]\n", - "models = Vector{AbstractGP}(undef,length(Ms)+1)\n", - "kernel = SqExponentialKernel(1.0)\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, Y, kernel, BayesianSVM(),AnalyticVI(),num_inducing)\n", - " @time train!(m,20)\n", - " models[index] = m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with full model\n", - "└ @ Main In[4]:1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 38.684180 seconds (6.48 M allocations: 15.821 GiB, 4.88% gc time)\n" - ] - } - ], - "source": [ - "@info \"Training with full model\"\n", - "model = VGP(X, Y, kernel, BayesianSVM(), AnalyticVI())\n", - "@time train!(model,5);\n", - "models[end] = model;" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " mins = [-3.25,-2.85]\n", - " maxs = [3.65,3.4]\n", - " xlin = range(mins[1],stop=maxs[1],length=nGrid)\n", - " ylin = range(mins[2],stop=maxs[2],length=nGrid)\n", - " Xplot = Iterators.product(xlin,ylin)\n", - " y,_ = proba_y(model,copy(hcat(collect.(Xplot)...)'))\n", - " return (y,xlin,ylin)\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "function plotdata(X,Y)\n", - " Plots.plot(X[Y.==1,1],X[Y.==1,2],t=:scatter,alpha=0.33,markerstrokewidth=0.0,lab=\"\",size=(300,500));\n", - " Plots.plot!(X[Y.==-1,1],X[Y.==-1,2],t=:scatter,alpha=0.33,markerstrokewidth=0.0,lab=\"\")\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,X,Y)\n", - " nGrid = 30\n", - " (predic,x,y) = compute_Grid(model,nGrid);\n", - " p = plotdata(X,Y)\n", - " Plots.plot!(p,x,y,reshape(predic,nGrid,nGrid),cbar=false,t=:contour,levels=[0.5],fill=false,fillalpha=0.2,title=(model isa SVGP ? \"M = $(model.nFeatures)\" : \"full\"),lw=3.0)\n", - " if model isa SVGP\n", - " Plots.plot!(p,model.f[1].Z[:,1],model.f[1].Z[:,2],msize=2.0,color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast(x->plotcontour(x,X,Y),models)...,layout=(1,length(models)),size=(1000,200))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.2.0", - "language": "julia", - "name": "julia-1.2" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.2.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/Classification - Logistic-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Classification - Logistic-checkpoint.ipynb deleted file mode 100644 index 83bbdfe4..00000000 --- a/docs/examples/.ipynb_checkpoints/Classification - Logistic-checkpoint.ipynb +++ /dev/null @@ -1,241 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using DelimitedFiles\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions;" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "X = readdlm(\"data/banana_X_train\")\n", - "Y = readdlm(\"data/banana_Y_train\")[:];" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 4 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 12.806569 seconds (46.89 M allocations: 2.481 GiB, 8.20% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 8 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.117281 seconds (932.15 k allocations: 220.592 MiB, 27.48% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 16 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.174798 seconds (932.43 k allocations: 352.832 MiB, 25.07% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 32 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.304894 seconds (933.02 k allocations: 618.853 MiB, 21.82% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 64 points\n", - "└ @ Main In[3]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.622581 seconds (934.61 k allocations: 1.130 GiB, 16.72% gc time)\n" - ] - } - ], - "source": [ - "# Run sparse classification with increasing number of inducing points\n", - "Ms = [4, 8, 16, 32, 64]\n", - "models = Vector{AbstractGP}(undef,length(Ms)+1)\n", - "kernel = SqExponentialKernel(1.0)\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, Y, kernel,LogisticLikelihood(),AnalyticVI(),num_inducing)\n", - " @time train!(m,20)\n", - " models[index]=m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Running full model\n", - "└ @ Main In[4]:1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 37.581410 seconds (6.47 M allocations: 15.820 GiB, 4.04% gc time)\n" - ] - } - ], - "source": [ - "@info \"Running full model\"\n", - "mfull = VGP(X, Y, kernel,LogisticLikelihood(),AnalyticVI())\n", - "@time train!(mfull,5);\n", - "models[end] = mfull;" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " mins = [-3.25,-2.85]\n", - " maxs = [3.65,3.4]\n", - " xlin = range(mins[1],maxs[1],length=nGrid)\n", - " ylin = range(mins[2],maxs[2],length=nGrid)\n", - " Xplot = Iterators.product(xlin,ylin)\n", - " y,_ = proba_y(model,copy(hcat(collect.(Xplot)...)'))\n", - " return (y,xlin,ylin)\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 81, - "metadata": {}, - "outputs": [], - "source": [ - "function plotdata(X,Y)\n", - " Plots.plot(X[Y.==1,1],X[Y.==1,2],alpha=0.2,t=:scatter,markerstrokewidth=0.0,lab=\"\",size=(300,500));\n", - " Plots.plot!(X[Y.==-1,1],X[Y.==-1,2],alpha=0.2,t=:scatter,markerstrokewidth=0.0,lab=\"\",size=(300,500));\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,X,Y)\n", - " nGrid = 40\n", - " (predic,x,y) = compute_Grid(model,nGrid);\n", - " p = plotdata(X,Y)\n", - " Plots.plot!(p,x,y,reshape(predic,nGrid,nGrid),cbar=false,t=:contour,levels=[0.5],fill=false,color=:black,linewidth=2.0,title=(model isa SVGP ? \"M = $(model.nFeatures)\" : \"full\"))\n", - " if model isa SVGP\n", - " Plots.plot!(p,model.f[1].Z[:,1],model.f[1].Z[:,2],msize=2.0,color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast(x->plotcontour(x,X,Y),models)...,layout=(1,length(models)),size=(1000,200))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.2.0", - "language": "julia", - "name": "julia-1.2" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.2.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/MultiClass - LogisticSoftMax-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/MultiClass - LogisticSoftMax-checkpoint.ipynb deleted file mode 100644 index c903dc72..00000000 --- a/docs/examples/.ipynb_checkpoints/MultiClass - LogisticSoftMax-checkpoint.ipynb +++ /dev/null @@ -1,282 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using Distributions\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "generate_mixture_data (generic function with 1 method)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Generate data from a mixture of gaussians (you can control the noise)\n", - "N_data = 500; N_dim = 2; N_grid = 100\n", - "minx=-2.5; maxx=3.5\n", - "σs = [0.1, 0.2, 0.3, 0.4, 0.5, 0.8]; N_class = N_dim + 1\n", - "\n", - "function generate_mixture_data(σ)\n", - " centers = zeros(N_class,N_dim)\n", - " ## Create equidistant centers\n", - " for i in 1:N_dim\n", - " centers[i,i] = 1.0\n", - " end\n", - " centers[end,:] = (1.0+sqrt(N_class))/N_dim*ones(N_dim); centers ./= sqrt(N_dim)\n", - " ## Generate distributions with desired noise\n", - " distr = [MvNormal(centers[i,:],σ) for i in 1:N_class]\n", - " X = zeros(Float64,N_data,N_dim)\n", - " y = zeros(Int64,N_data)\n", - " true_py = zeros(Float64,N_data)\n", - " for i in eachindex(y)\n", - " y[i] = rand(1:N_class)\n", - " X[i,:] = rand(distr[y[i]])\n", - " true_py[i] = pdf(distr[y[i]],X[i,:])/sum(pdf(distr[k],X[i,:]) for k in 1:N_class)\n", - " end\n", - " return X,y\n", - "end\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function plotdata(X,Y,σ)\n", - " p = Plots.plot(size(300,500),lab=\"\",title=\"sigma = $σ\")\n", - " ys = unique(Y)\n", - " cols = [:red,:blue,:green]\n", - " for y in ys\n", - " Plots.plot!(X[Y.==y,1],X[Y.==y,2],color=cols[y],alpha=1.0,t=:scatter,markerstrokewidth=0.0,lab=\"\");\n", - " end\n", - " return p\n", - "end;\n", - "plot([plotdata(generate_mixture_data(σ)...,σ) for σ in σs]...)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.1\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 8.198574 seconds (32.61 M allocations: 1.752 GiB, 9.51% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.2\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.174595 seconds (120.48 k allocations: 132.235 MiB, 15.05% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.3\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.162003 seconds (120.48 k allocations: 132.235 MiB, 13.01% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.4\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.173828 seconds (120.48 k allocations: 132.235 MiB, 12.30% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.5\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.163400 seconds (120.48 k allocations: 132.235 MiB, 12.20% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with data with noise 0.8\n", - "└ @ Main In[5]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.161598 seconds (120.48 k allocations: 132.235 MiB, 12.92% gc time)\n" - ] - } - ], - "source": [ - "# Run sparse multiclass classification with different level of noise\n", - "models = Vector{AbstractGP}(undef,length(σs))\n", - "kernel = SqExponentialKernel(1.0)\n", - "num_inducing = 50\n", - "for (index, σ) in enumerate(σs)\n", - " @info \"Training with data with noise $σ\"\n", - " m = SVGP(generate_mixture_data(σ)..., kernel,LogisticSoftMaxLikelihood(),AnalyticVI(),num_inducing,variance=10.0,optimizer=false)\n", - " @time train!(m,20)\n", - " models[index]=m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " xlin = range(minx,maxx,length=nGrid)\n", - " ylin = range(minx,maxx,length=nGrid)\n", - " Xplot = Iterators.product(xlin,ylin)\n", - " global y_p = proba_y(model,copy(hcat(collect.(Xplot)...)'))\n", - " global y = predict_y(model,copy(hcat(collect.(Xplot)...)'))\n", - " return (y_p,y,xlin,ylin)\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,σ)\n", - " nGrid = 100\n", - " (predic_proba,predic,x,y) = compute_Grid(model,nGrid);\n", - " global cols = reshape([RGB(permutedims(Vector(predic_proba[i,:]))[collect(values(sort(model.likelihood.ind_mapping)))]...) for i in 1:nGrid*nGrid],nGrid,nGrid)\n", - " Plots.plot(x,y,cols,cbar=false,t=:contour,fill=false,color=:black,linewidth=2.0,title=\"sigma = $σ\")\n", - " Plots.plot!(x,y,reshape(predic,nGrid,nGrid),clims=(0,100),t=:contour,colorbar=false,color=:gray,levels=10)\n", - "end;" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Here we plot the likelihood of each point by a RGB mapping" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast((x,σ)->plotcontour(x,σ),models,σs)...)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.2.0", - "language": "julia", - "name": "julia-1.2" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.2.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/Online - Regression-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Online - Regression-checkpoint.ipynb deleted file mode 100644 index b5bd1fab..00000000 --- a/docs/examples/.ipynb_checkpoints/Online - Regression-checkpoint.ipynb +++ /dev/null @@ -1,145 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using AugmentedGaussianProcesses\n", - "using MLDataUtils" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "N = 2000\n", - "X,y = noisy_sin(N,0,20,noise=0.1)\n", - "X = reshape(X,:,1)\n", - "X_train = X[1:2:end,:]; y_train = y[1:2:end]\n", - "X_test = X[2:2:end,:]; y_test = y[2:2:end]\n", - "scatter(X_train,y_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plot_model (generic function with 2 methods)" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function plot_model(X,X_test,X_train,y_train,model)\n", - " y_pred, sig_pred = proba_y(model,X_test)\n", - " plot(X,sin,lab=\"f\",color=:black,lw=3.0,ylims=(-2,2))\n", - " plot!(X_test,y_pred,ribbon=sqrt.(sig_pred),lab=\"Prediction\",lw=3.0)\n", - " scatter!(X_train,y_train,msw=0.0,alpha=0.5,lab=\"Data\")\n", - " scatter!(model.f[1].Z,model.f[1].μ,lab=\"IP\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "PyPlot.Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Saved animation to \n", - "│ fn = /home/theo/.julia/dev/AugmentedGaussianProcesses/examples/tmp.gif\n", - "└ @ Plots /home/theo/.julia/packages/Plots/qZHsp/src/animation.jl:98\n" - ] - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "Plots.AnimatedGif(\"/home/theo/.julia/dev/AugmentedGaussianProcesses/examples/tmp.gif\")" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "k = SqExponentialKernel()\n", - "IP_alg = OIPS(0.8,nothing)\n", - "model = OnlineSVGP(k,GaussianLikelihood(0.1),AnalyticVI(),1,IP_alg)\n", - "preds = []\n", - "anim = Animation()\n", - "for (X_batch,y_batch) in eachbatch((X_train,y_train), obsdim=1, size=10)\n", - " train!(model,X_batch,y_batch,iterations=3)\n", - " plot_model(X,X_test,X_train,y_train,model)\n", - " frame(anim)\n", - "end\n", - "gif(anim,fps=4)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.3.1", - "language": "julia", - "name": "julia-1.3" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.3.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/Regression - Gaussian-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Regression - Gaussian-checkpoint.ipynb deleted file mode 100644 index b62dd58a..00000000 --- a/docs/examples/.ipynb_checkpoints/Regression - Gaussian-checkpoint.ipynb +++ /dev/null @@ -1,174 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]\n", - "└ @ Base loading.jl:1278\n" - ] - } - ], - "source": [ - "using Plots; pyplot()\n", - "using Distributions\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "N = 1000\n", - "X = reshape((sort(rand(N)).-0.5).*40.0,N,1)\n", - "function latent(x)\n", - " 5.0.*sin.(x)./x\n", - "end\n", - "Y = (latent(X)+randn(N))[:];\n", - "scatter(X,Y,lab=\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Run sparse classification with increasing number of inducing points\n", - "Ms = [4, 8, 16, 32, 64]\n", - "models = Vector{AbstractGP}(undef,length(Ms)+1)\n", - "kernel = PeriodicKernel(; r=[1.0])\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, vec(Y), kernel,GaussianLikelihood(),AnalyticVI(),num_inducing)\n", - " @time train!(m,100)\n", - " models[index]=m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with full model\n", - "└ @ Main In[16]:1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.316432 seconds (4.38 k allocations: 213.969 MiB, 40.07% gc time)\n" - ] - } - ], - "source": [ - "@info \"Training with full model\"\n", - "mfull = GP(X, vec(Y), kernel,opt_noise=false)\n", - "@time train!(mfull,5);\n", - "models[end]=mfull;" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " mins = -20\n", - " maxs = 20\n", - " Xplot = collect(range(mins[1],stop=maxs[1],length=nGrid))\n", - " y,sig_y = proba_y(model,Xplot)\n", - " return (y,sig_y,Xplot)\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "function plotdata(X,Y)\n", - " Plots.plot(X,Y,t=:scatter,alpha=0.33,markerstrokewidth=0.0,lab=\"\",size=(300,500));\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,X,Y)\n", - " nGrid = 100\n", - " (y,sig_y,x) = compute_Grid(model,nGrid);\n", - " p = plotdata(X,Y)\n", - " Plots.plot!(p,x,y,ribbon=2*sqrt.(sig_y),title=(model isa SVGP ? \"M = $(model.nFeatures)\" : \"full\"),color=\"red\",lab=\"\",linewidth=3.0)\n", - " if model isa SVGP\n", - " Plots.plot!(p,model.f[1].Z[:,1],zero(model.f[1].Z[:,1]),msize=2.0,color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast(x->plotcontour(x,X,Y),models)...,layout=(1,length(models)),size=(1000,200))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.5.1", - "language": "julia", - "name": "julia-1.5" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.5.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/Regression - Laplace-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Regression - Laplace-checkpoint.ipynb deleted file mode 100644 index eadd6c6c..00000000 --- a/docs/examples/.ipynb_checkpoints/Regression - Laplace-checkpoint.ipynb +++ /dev/null @@ -1,244 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using Distributions\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "N = 1000\n", - "X = reshape((sort(rand(N)).-0.5).*40.0,N,1)\n", - "function latent(x)\n", - " 5.0.*sin.(x)./x\n", - "end\n", - "Y = (latent(X)+randn(N))[:];\n", - "scatter(X,Y)" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.089012 seconds (1.02 M allocations: 158.359 MiB, 33.94% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 4 points\n", - "└ @ Main In[33]:6\n", - "┌ Info: Training with 8 points\n", - "└ @ Main In[33]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.121823 seconds (1.02 M allocations: 228.332 MiB, 32.21% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 16 points\n", - "└ @ Main In[33]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.210213 seconds (1.03 M allocations: 370.224 MiB, 26.04% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 32 points\n", - "└ @ Main In[33]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.347083 seconds (1.03 M allocations: 662.310 MiB, 24.10% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 64 points\n", - "└ @ Main In[33]:6\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.775999 seconds (1.04 M allocations: 1.250 GiB, 17.82% gc time)\n" - ] - } - ], - "source": [ - "# Run sparse classification with increasing number of inducing points\n", - "Ms = [4, 8, 16, 32, 64]\n", - "models = Vector{AbstractGP}(undef,length(Ms)+1)\n", - "kernel = SqExponentialKernel(1.0)\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, vec(Y), kernel,LaplaceLikelihood(),AnalyticVI(),num_inducing)\n", - " @time train!(m,100)\n", - " models[index]=m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with full model\n", - "└ @ Main In[34]:1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 1.108469 seconds (4.75 k allocations: 567.738 MiB, 16.83% gc time)\n" - ] - } - ], - "source": [ - "@info \"Training with full model\"\n", - "mfull = VGP(X, vec(Y), kernel,LaplaceLikelihood(),AnalyticVI())\n", - "@time train!(mfull,5);\n", - "models[end]=mfull;" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " mins = -20\n", - " maxs = 20\n", - " Xplot = collect(range(mins[1],stop=maxs[1],length=nGrid))\n", - " y,sig_y = proba_y(model,Xplot)\n", - " return (y,sig_y,Xplot)\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "function plotdata(X,Y)\n", - " Plots.plot(X,Y,t=:scatter,alpha=0.33,markerstrokewidth=0.0,lab=\"\",size=(300,500));\n", - "end;" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,X,Y)\n", - " nGrid = 100\n", - " (y,sig_y,x) = compute_Grid(model,nGrid);\n", - " p = plotdata(X,Y)\n", - " Plots.plot!(p,x,y,ribbon=sqrt.(sig_y),title=((model isa SVGP) ? \"M = $(model.nFeatures)\" : \"full\"),color=\"red\",lab=\"\",linewidth=3.0)\n", - " if model isa SVGP\n", - " Plots.plot!(p,model.f[1].Z[:,1],zero(model.f[1].Z[:,1]),msize=2.0,color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast(x->plotcontour(x,X,Y),models)...,layout=(1,length(models)),size=(1000,200))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.2.0", - "language": "julia", - "name": "julia-1.2" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.2.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/.ipynb_checkpoints/Regression - StudentT-checkpoint.ipynb b/docs/examples/.ipynb_checkpoints/Regression - StudentT-checkpoint.ipynb deleted file mode 100644 index b61c79b4..00000000 --- a/docs/examples/.ipynb_checkpoints/Regression - StudentT-checkpoint.ipynb +++ /dev/null @@ -1,265 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using Plots; pyplot()\n", - "using Distributions;\n", - "using AugmentedGaussianProcesses\n", - "using KernelFunctions;" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "N = 1000\n", - "X = reshape((sort(rand(N)).-0.5).*40.0,N,1)\n", - "function latent(x)\n", - " 5.0.*sin.(x)./x\n", - "end\n", - "outliers = rand(N).>0.7\n", - "Y = (latent(X)+(1.0.-outliers).*rand(Normal(0,1),N)+abs.(outliers.*rand(Normal(0,10),N))[:]);\n", - "scatter(X,Y,lab=\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 4 points\n", - "└ @ Main In[3]:8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 11.391404 seconds (43.92 M allocations: 2.286 GiB, 8.82% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 8 points\n", - "└ @ Main In[3]:8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.121382 seconds (1.02 M allocations: 230.657 MiB, 29.23% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 16 points\n", - "└ @ Main In[3]:8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.200859 seconds (1.03 M allocations: 372.549 MiB, 24.40% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 32 points\n", - "└ @ Main In[3]:8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.362029 seconds (1.03 M allocations: 664.635 MiB, 20.80% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with 64 points\n", - "└ @ Main In[3]:8\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.768050 seconds (1.04 M allocations: 1.252 GiB, 16.46% gc time)\n" - ] - } - ], - "source": [ - "# Run sparse classification with increasing number of inducing points\n", - "Ms = [4, 8, 16, 32, 64]\n", - "models = Vector{AbstractGP}(undef,length(Ms)+1)\n", - "# Create a kernel from KernelFunctions.jl\n", - "kernel = SqExponentialKernel(1.0)\n", - "ν=10.0\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, vec(Y), kernel, StudentTLikelihood(ν), AnalyticVI(), num_inducing)\n", - " @time train!(m,100)\n", - " models[index] = m;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Training with full model\n", - "└ @ Main In[4]:1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 2.807392 seconds (6.47 M allocations: 892.595 MiB, 13.15% gc time)\n" - ] - } - ], - "source": [ - "@info \"Training with full model\"\n", - "mfull = VGP(X, vec(Y), kernel, StudentTLikelihood(ν), AnalyticVI())\n", - "@time train!(mfull,5);\n", - "models[end] = mfull;" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "compute_Grid (generic function with 2 methods)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "function compute_Grid(model,nGrid=50)\n", - " mins = -20\n", - " maxs = 20\n", - " Xplot = collect(range(mins[1],stop=maxs[1],length=nGrid))\n", - "# Xplot = hcat([j for i in xlin, j in ylin][:],[i for i in xlin, j in ylin][:])\n", - " y,sig_y = proba_y(model,Xplot)\n", - " return (y,sig_y,Xplot)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "function plotdata(X,Y)\n", - " Plots.plot(X,Y,t=:scatter,alpha=0.33,markerstrokewidth=0.0,lab=\"\",size=(300,500))\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "function plotcontour(model,X,Y)\n", - " nGrid = 100\n", - " y,sig_y,x = compute_Grid(model,nGrid)\n", - " p = plotdata(X,Y)\n", - " plot!(p,x,y,ribbon=2*sqrt.(sig_y),title=( model isa SVGP ? \"M = $(model.nFeatures)\" : \"full\"),color=\"red\",lab=\"\",linewidth=3.0)\n", - " if model isa SVGP\n", - " plot!(p,model.f[1].Z[:,1],zero(model.f[1].Z[:,1]),msize=2.0,color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - " end;" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Plots.plot(broadcast(x->plotcontour(x,X,Y),models)...,layout=(1,length(models)),size=(1000,200))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.2.0", - "language": "julia", - "name": "julia-1.2" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.2.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/examples/data/banana_X_train b/docs/examples/data/banana_X_train deleted file mode 100644 index e5f2e559..00000000 --- a/docs/examples/data/banana_X_train +++ /dev/null @@ -1,5300 +0,0 @@ -1.14 -0.114 --1.52 -1.15 --1.05 0.72 --0.916 0.397 --1.09 0.437 --0.584 0.0937 -1.83 0.452 --1.25 -0.286 -1.7 1.21 --0.482 -0.485 -1.79 -0.459 --0.122 -0.808 -0.0809 1.93 --0.541 -0.332 --1.02 0.619 --0.768 -1.04 --1.69 -0.0461 -1.26 1.21 -0.724 0.989 -0.444 1.99 --1.01 -1.36 --0.863 0.496 -1.16 -0.458 --0.595 -0.651 --0.77 0.364 --0.871 -0.825 -0.996 -1.7 -1.28 0.691 -0.925 0.895 --0.687 -1.29 -1.74 0.964 -1.18 -0.335 -2.52 1.43 -1.71 -0.044 -0.271 -0.591 -1.12 0.626 -1.3 0.196 --1.59 -0.68 -0.408 0.0673 -1.13 1.48 -0.763 0.921 --1.41 1.11 --0.75 -0.881 -1.16 0.978 -1.13 0.405 --0.522 -1.34 --1.41 0.894 -0.00902 -0.434 --2.14 -1.43 --1.31 1.25 -0.041 -1.13 -0.0483 0.866 --2.11 0.193 -0.522 1.46 -0.0284 1.62 -0.396 -0.606 -0.536 0.921 -0.315 -0.182 --0.123 -1.07 -0.526 1.48 -0.00665 0.0118 --0.352 -0.49 --0.0701 -1.23 --0.149 -1.2 -0.785 0.0481 --1.62 0.593 --0.0314 -1.01 --0.285 -1.1 -1.33 1.51 -1.09 -1.37 --0.223 -1.28 --0.0341 -1.07 -1.22 1.13 --1.67 -1.26 -1.97 -0.772 --0.508 -0.715 -0.603 -0.108 --0.323 -0.213 --0.124 -1.12 --0.439 -0.961 -0.201 0.0024 -0.812 0.708 -0.888 0.817 -0.0238 0.0836 -0.415 -1 --0.308 2.19 -0.767 -0.248 -1.23 -1.2 -1.33 1.63 -0.27 0.0491 --1.69 -1.87 -0.495 -0.281 --0.519 -0.799 --1.99 0.549 -1.36 -0.732 --1.03 0.654 -0.431 -1.33 --0.0583 -1.15 --0.209 0.345 -1.26 -1.37 --1.78 -0.378 -0.98 -0.0439 --0.0536 1.6 --1.39 -0.451 -1.22 -0.361 -1.22 0.561 --0.838 0.356 --0.446 -0.861 -1.17 -1.39 --0.0868 -1.33 --1.12 0.576 --0.28 -1.3 --0.0269 0.958 --0.697 1.35 -1.38 -1.74 -0.408 1.16 -1.2 1.54 -2.07 1.02 --0.462 -0.187 -1.27 0.589 --0.101 -0.765 --0.819 1.26 -0.615 -0.0228 --1.79 -0.98 --1.79 -0.954 -0.826 1.5 -0.845 0.766 --0.476 -1.49 -1.01 0.48 -1.39 -0.376 -0.357 -1.07 -0.77 1.4 --1.08 0.114 --0.795 -1.43 -0.706 1.38 --1.26 0.23 --0.833 -0.569 --0.0303 2.11 --0.223 -0.419 --0.562 -0.873 -0.926 0.972 --1.86 -1.57 --0.806 0.941 --0.214 0.38 -0.744 1.42 -1.94 -0.65 -1.77 1.35 --0.903 0.101 --0.0418 -1.02 -0.309 -0.175 --0.634 -0.969 --1.62 0.102 --1.21 1.27 -0.529 0.133 -0.386 1.55 --0.0962 0.19 --0.536 1.13 -1.02 -0.261 --0.876 -1 -2.35 1.21 --0.982 -1.08 --1.16 0.469 --1.74 0.693 --1.1 1.16 -0.0179 -0.7 --0.62 -0.984 --1.52 0.66 -1.07 -0.985 -0.917 0.525 --0.0482 1.52 -1.49 1.55 --0.584 1.01 --0.0625 -0.12 --1.68 1.08 --1.77 -0.923 --0.202 0.712 -1.06 -0.427 -1.71 1.1 --1.7 0.872 -1.86 1.14 --0.529 -0.357 --0.411 -1.3 -0.666 1.36 -0.162 -0.791 --0.296 0.255 --0.0347 1.3 -0.294 -1.5 --0.52 -1.17 -0.741 -1.2 --1.33 1.08 --0.0987 0.966 -0.0131 -0.969 -0.896 1.58 --0.412 0.492 -0.683 1.07 --0.753 -0.0615 --0.0674 1.85 -1.08 0.683 -1.15 0.243 -0.497 -0.671 -0.174 1.92 -1.64 0.0477 --0.478 -0.796 --0.447 -1 --1.04 -0.2 -2.06 -0.482 --0.89 -1.17 -0.312 -1.23 -0.976 -1.39 -0.291 -0.795 -0.303 -0.143 -1.1 -0.695 -0.579 -1.02 --1.54 0.685 -0.916 0.144 -1.18 0.614 -0.254 -0.862 --0.877 -0.401 -1.97 0.99 -0.471 1.39 -1.63 0.475 -0.945 0.309 -0.121 -1.3 -1.06 -0.69 -1.42 -0.32 -0.535 0.504 -0.912 -0.114 --0.75 1.14 -1.14 -0.209 --1.03 -1.09 -0.268 -1.08 --1.77 -0.828 -0.378 -0.0609 -1.19 0.113 --0.168 1.32 -2.07 1.21 --1.07 0.707 --1.19 0.309 -1.19 0.697 -0.121 1.72 -1.23 -0.0582 -0.44 0.399 --0.723 0.633 --0.63 0.949 -0.143 0.263 -1.23 -0.615 -1.9 -0.0565 -1.22 -0.0172 -0.0107 0.0258 -0.36 -0.715 -0.139 -1.01 -0.308 -1.06 --0.645 -0.238 -1.15 0.715 --0.531 -1.27 -1.05 0.701 -0.0681 -0.76 --0.595 1.46 -0.72 0.989 --1.86 -0.963 -0.0692 -0.828 -0.863 0.765 --0.574 1.32 --0.467 -1.51 -1.43 0.484 --0.592 -1.17 -0.122 -0.041 -0.909 0.118 --0.705 -0.93 -1.05 0.453 --0.786 -1.33 -0.07 1.7 --0.36 -1.28 --1.25 0.985 -1.33 1.42 -0.778 -0.694 --1.87 -1.26 -0.178 1.49 --1.03 1.18 --0.956 -0.818 -0.0345 -0.691 --1.25 0.512 --0.187 -1.38 --1.24 1 -0.329 -0.37 --1.37 -0.803 -0.529 1.62 --0.23 1.08 --0.619 -0.748 --0.914 1.07 -0.163 -1.31 -1.19 -1.34 -0.983 -1.31 --1.63 -1.41 --1.02 -0.296 --0.387 0.26 --1.59 -1 -1.69 -0.724 --0.869 -0.0393 --1.9 0.106 --1.75 0.722 --1.06 -1.07 --0.509 -1.41 --0.112 -0.841 -1.08 0.79 -0.498 0.567 --0.796 -1.63 --0.3 -1.04 --2.34 0.246 -0.842 -1.41 --0.0263 -1.35 -0.586 1.15 -1.87 -0.239 -0.404 -0.868 -0.564 -1.13 --0.0584 0.54 --1.58 -1.26 --0.813 -0.57 --0.579 -0.748 --1.35 1.32 --0.639 -0.938 -1.49 -0.00779 -0.719 0.0781 -0.0346 1.7 --0.274 0.0468 -0.207 0.0304 -1.63 -0.251 --0.207 -0.745 --0.717 1 -1.17 -0.567 -0.661 1.69 --1.13 0.6 --0.109 -1.25 -0.68 0.702 -0.867 0.81 --0.562 -1.01 -1.79 -0.102 --1.87 -1.1 --0.946 -0.197 -0.812 -0.195 -0.287 -0.517 -0.262 -0.673 --0.358 -1.02 --0.392 -1.27 --1.2 -1.02 --0.337 -1.45 --1.54 -0.643 -0.311 1.76 --0.473 -0.749 -1.71 0.0217 -1.88 -0.368 --1.18 -0.0978 -0.0431 -0.0199 -1.23 0.354 -0.0788 -0.0998 -0.0544 -1.59 --0.24 1.72 --0.496 -1.09 --0.636 1.35 -1.15 0.634 -1.29 -1.43 --0.983 1.06 --0.206 -0.474 -0.298 -0.829 --0.972 -1.06 -1.21 0.354 -0.328 1.71 -0.313 -1.07 --1.24 -0.352 --1.39 -0.68 -1.2 -1.56 --0.208 0.332 -0.553 1.54 -0.354 -1.19 --0.74 -1.53 --0.769 1.35 --0.0381 -0.791 --0.102 -0.13 --1.06 0.496 --0.481 1.09 -0.866 -0.917 -1.06 0.266 -1.73 1.68 --0.516 -0.935 --0.893 -1.27 -1.2 -0.948 -0.763 1.15 -0.794 0.762 --0.314 0.0194 --0.456 1.55 -1.04 0.563 --0.0978 -0.424 -1.37 -0.643 --0.201 0.0726 --1.97 0.611 -0.99 -0.0762 -1.28 0.902 -0.569 1.62 --1.2 -0.451 --0.508 1.48 --1.69 -0.175 --0.298 -1.26 -0.301 -1.17 -0.975 1.48 --0.853 -0.254 -0.837 1.75 -0.379 1.36 --0.364 -0.0828 -0.939 -0.351 -1.24 0.554 -1.37 -0.331 --0.48 -0.913 -1.34 -0.261 -0.286 1.23 -0.672 2.03 --0.52 -1.52 --0.513 1.29 --0.648 -0.631 --0.113 -0.197 -0.103 0.329 --0.941 0.976 --0.533 -0.402 -1.09 -1.59 --0.395 -0.756 -1.46 -0.417 --0.724 -1.26 --1.59 -0.98 -0.159 1.51 --0.843 1.4 --0.581 -1.27 --0.268 -1.26 --1.58 -0.842 --0.52 1.2 --0.0203 1.92 --1.52 0.934 -1.05 0.444 -0.351 -0.0402 --0.322 -1.12 --0.654 -0.999 -0.165 -1.58 -2.6 0.951 -1.52 -0.0653 --1.29 -0.529 -1.18 0.392 --0.00264 -1.02 -1.24 0.273 -1.45 0.398 -0.54 -1.26 --0.324 -1.03 --1.69 -1.2 --0.455 0.868 -2.16 1.16 --0.232 -1.4 -0.685 1.69 --0.0537 -1.52 -1.03 0.548 --0.758 -1.21 --0.259 0.496 --0.472 0.411 --0.127 -1.33 --0.784 -1.05 --1.73 -1.32 --1.24 -0.919 -0.275 -0.987 -1.66 0.672 --1.07 0.963 --0.262 1.28 --1.4 -0.37 --0.288 0.305 -0.778 1.44 -1.23 -0.493 --1.27 -0.273 --0.994 1.14 -0.74 1.2 -0.489 0.904 -0.805 -0.237 --1.86 -1.47 --0.617 -1.02 --0.66 0.965 -0.487 -0.13 --0.0508 -1.19 -0.96 -0.522 --1.21 0.778 -0.149 1.98 --1.76 -0.903 -0.0486 -0.389 --0.891 1 -0.263 -1.48 -1.21 1.28 --1.46 0.0829 --1.04 1.19 --1.69 -0.542 -0.707 0.0524 -1.31 -0.254 --0.488 -0.566 -1.8 -0.811 -1.84 1.18 -1.49 -0.156 --0.881 -1.59 -0.529 0.788 -0.571 0.197 --2.07 0.0318 --1.23 -0.308 -0.682 1.5 --1.33 0.0398 --1.35 0.424 -0.307 -0.678 -0.859 -0.952 --0.672 0.683 -1.36 0.258 --0.37 1.48 --1.9 -1.1 --1.38 -0.32 -0.234 0.958 --1.01 -0.771 --0.739 0.578 --0.107 -1.5 -0.592 0.973 -0.52 1.21 -0.416 1.86 --0.181 0.344 -1.27 -0.441 -0.422 -0.934 --0.704 -0.802 -0.088 -1.25 -0.952 0.427 -1.39 -0.218 --1.08 -1.3 -1.25 -0.35 -0.183 -1.21 --0.0765 -1.12 --0.407 0.602 -0.975 0.809 --0.0552 0.882 --0.946 1.02 -1.11 -0.106 --0.794 1.07 --0.652 -1.1 --2.08 -1.78 --0.631 -0.867 --0.856 -1.31 --0.215 -1.01 --1.12 0.154 --1.1 0.135 --0.134 -1.1 -0.844 0.243 -0.472 0.289 -1.64 0.174 --0.413 -0.0275 --0.875 0.591 --0.404 0.178 --0.297 -0.467 --0.698 -1.26 -1.2 0.298 --0.346 -1.5 --1.14 -0.494 --0.0242 -0.659 --0.495 -1.2 --0.803 -0.782 --0.641 0.516 --0.0874 -0.948 --1.04 0.679 -0.701 0.0237 --0.677 -1.41 --0.516 0.831 --0.864 -1.56 -0.863 -1.02 --1.12 0.559 --0.779 -1.14 --0.9 1.49 -2.43 1.39 --1.67 -1.73 -0.743 -1.18 --1.52 -0.658 -1.28 -0.176 -1.58 -1.29 -0.61 0.488 --2.15 -0.858 --0.0307 0.678 --0.227 -1.19 -0.642 1.65 --1.58 -1.25 -0.373 1.48 -0.333 -0.845 --1.18 -0.758 -1.15 -1.52 --0.601 -0.539 --1.57 -1.74 -0.652 -0.646 --1.43 1.26 -0.71 0.0529 -1.18 0.585 --1.01 -1.27 -0.13 1.38 -0.469 -0.321 --1.08 0.72 -0.987 0.858 -1.57 -0.389 --0.411 0.727 --0.72 0.189 --0.00329 -0.0777 --0.937 -0.086 -2.21 1.02 --0.606 -0.997 -1.4 0.377 -0.37 0.312 --1.41 -0.214 --0.192 1.66 --0.0246 -0.141 -1.07 -0.0433 --0.477 -1.25 --1.35 -0.485 -0.996 0.225 --1.25 -1.28 --0.198 1.67 --0.8 -0.282 -0.168 0.345 -0.851 1.46 -1.45 -1.24 --1.02 -1.18 --1.31 0.916 --0.457 -0.322 -0.0744 1.04 -0.902 -1.08 --0.904 0.953 --0.11 -0.911 -1.01 -1.05 -0.441 -1.13 --0.287 -0.726 -0.205 -0.471 --0.625 1.14 --0.623 -0.737 --0.254 -0.932 --0.817 -1.19 --1.73 0.87 -0.176 1.94 -0.899 -0.235 -0.834 -0.584 -0.15 -0.256 --1.23 -0.336 -0.866 -0.807 -1.07 0.0877 --0.256 1.52 -2.34 -1.25 --0.374 -1.08 --1.16 0.381 --1.3 -1.17 -0.527 -0.251 --0.748 -0.57 -1.02 0.997 -0.105 0.103 -0.563 0.137 -0.317 -0.0233 -0.15 1.3 --1.31 0.00723 -1.42 -0.146 -0.576 1.7 --0.106 -0.316 --1.2 0.932 --1.14 0.488 --0.151 1.66 --1.46 -0.909 -1.36 -0.425 -1.41 0.83 -0.176 -1.11 --0.526 1.26 -0.552 -1.07 --1.14 0.304 --1.64 0.143 --0.189 -1.24 -0.775 0.0171 --0.598 1.22 --1.71 -1.29 -1.52 0.409 -0.548 -0.959 --0.636 -0.988 --0.0723 -1.08 -0.0949 -0.854 -0.726 0.289 -1.43 0.147 --0.0238 407e-6 -0.939 1.69 --1.29 0.511 -0.324 1.68 --0.506 -1.09 -0.341 -1.32 --0.978 0.931 --1.31 -0.229 -1.29 0.677 -1.01 -0.94 -0.0219 -0.388 --0.647 -1.22 --0.31 -1.38 --0.146 0.132 -1.38 0.877 -0.24 -1.14 --1.01 -1.53 -1.21 -1.02 --0.623 1.24 --1.42 0.83 --0.0908 -0.846 -1.39 -0.872 -0.502 -0.536 --0.046 1.51 --1.35 -1.19 -1.77 0.109 --0.166 -0.986 -0.152 1.53 -0.308 0.933 --1.11 0.439 --1.87 -0.451 --1.66 -0.735 -1.18 0.424 --0.109 -0.884 -0.243 0.304 -1.04 0.816 -0.514 1.27 --0.145 1.67 -0.169 1.86 --0.984 -0.807 -0.379 -0.755 --1.11 0.655 --0.918 1.13 --0.43 -0.722 --1.62 -1.85 -0.377 0.198 --0.329 -0.858 -0.125 2.16 --0.108 -1.3 --0.118 1.7 -0.826 0.744 --1.1 0.811 -1.2 -0.598 --1.89 -0.727 -1.45 0.229 -0.833 -0.254 --1.7 -0.845 -0.272 1.82 -0.179 1.81 --0.951 0.533 --1.07 0.534 --0.874 0.922 --0.0715 1.41 -0.195 -0.296 -0.373 -1.17 -0.808 -0.831 --0.504 1.03 -1.39 0.262 -1.12 0.862 -0.755 0.22 -1.57 -0.114 -1.32 1.36 -0.802 0.133 --0.558 0.572 -0.27 0.696 --0.606 -0.546 --0.556 -0.505 --1.74 0.254 -0.143 0.337 -1.19 -0.404 --0.16 -1.36 -1.29 0.153 -1.47 -0.312 --0.853 -1.17 --0.377 0.607 -0.816 0.306 -1.16 -1.08 -0.378 -0.56 --0.567 -1.14 -0.934 0.258 -1.01 -0.743 -0.96 -0.9 --0.249 0.0234 -1.45 -0.26 --0.497 1.07 -0.827 0.755 -0.604 0.374 -2.51 1.11 -0.154 -0.653 --0.264 -0.768 --0.573 -0.789 -0.792 0.988 --0.0338 1.52 -1.59 -0.522 --0.61 -0.306 -0.184 1.7 -0.0317 -0.821 -0.781 0.415 -0.118 -1.37 --1.57 0.942 -0.415 1.8 -0.552 2.05 --1.21 -0.934 --2.14 -0.476 -0.0154 -1.41 --0.0789 -1.35 --0.397 1.32 --0.466 0.145 -0.238 -1.51 --0.433 -1.13 -1.3 0.555 -0.0991 -1.05 -0.59 -0.796 --0.235 -0.617 -0.796 0.429 --1.97 -0.271 -0.284 2.37 --0.39 -0.209 -0.165 -0.405 --0.424 2.01 --0.934 -1.58 -0.218 -0.368 --0.283 1.88 --0.347 -1.5 --0.342 -1.31 -0.313 0.189 --0.341 -0.0358 --0.00698 -1.15 --1.73 -1.3 --0.451 0.775 --1.62 -0.712 --0.862 -0.0613 --0.828 -0.839 --1.01 1.07 -1.02 0.858 --0.255 0.387 -0.118 0.13 --0.786 -0.64 --0.0895 1.65 -2.46 1.23 --0.803 -0.705 --0.618 -1.2 -0.713 1.02 -0.976 -1.53 -1.47 1.21 --1.97 -0.674 --0.012 1.42 -0.748 -0.558 --1.45 -0.203 -0.199 -0.86 --1.68 -0.51 -0.56 0.491 -0.216 -1.12 --0.232 -0.843 -1.66 1.42 -0.301 2.01 -1.33 0.825 -1.18 0.08 --1.59 0.138 -1.78 -0.508 -1.37 -1.52 -0.802 0.431 -0.913 -0.318 -0.00564 -1.14 --1.08 1.31 -0.379 1.37 --0.106 -0.933 -0.854 -0.827 --1.47 -0.212 -1.24 -1.33 --0.314 -0.984 --0.474 -0.911 -0.659 -0.057 -1.83 0.349 -1.51 -1.15 --0.237 -1.4 -0.016 -1.13 -0.26 1.91 --0.104 -1.09 --0.724 -1.48 -1.24 -0.145 --0.776 -1.26 -1.16 0.0489 -1.05 -2.08 -0.143 1.05 --1.42 -1.51 -1.21 0.642 -0.551 1.48 -0.191 1.72 -0.345 -0.891 --0.396 -1.38 --1.59 -0.766 -0.903 -1.17 -1.57 -0.0908 -1.18 0.913 --0.323 -0.264 --0.302 -1.22 --1.26 -0.296 -0.874 -1.41 --0.885 1.05 --1.52 -0.74 --0.716 -0.194 --0.579 -0.397 --1.52 0.388 -1.57 -0.566 --0.702 -1.2 --0.366 -0.882 -1.45 -1.78 --1.22 0.831 -1.39 -1.11 -0.969 0.921 -0.659 1.07 --0.238 0.126 --0.576 -0.463 -0.171 -0.886 -0.893 0.345 --1.49 0.885 -0.258 0.309 --0.609 -0.917 -1.05 0.651 --0.827 -0.506 -0.374 -1.39 --0.784 0.969 -1.08 1.42 -0.146 -0.151 --1.93 0.603 --0.734 -1.09 --1.19 -0.529 -0.0176 0.0932 -1.72 -0.448 -1.37 0.625 -1.3 0.186 --0.0618 0.358 --0.929 -1.39 -1.14 -0.0771 --0.85 -0.92 --1.78 -1.49 --1.86 -0.977 --0.699 -578e-6 --0.995 -1.39 --0.233 0.593 --0.415 1.48 --1.66 -0.792 --0.152 -0.669 --0.673 0.313 --1.24 -0.72 -0.73 -0.37 --1.25 0.104 -1.85 1.38 -0.134 -0.922 -0.546 -0.195 -0.604 1.03 --1.13 -1.08 --1.13 0.193 --1.62 1.02 --1.07 -1.11 --0.443 1.86 -0.0438 0.536 --0.262 -1.2 -0.156 0.152 --0.311 0.995 -0.639 1.2 --1.42 -0.36 --1.43 0.707 -1.52 -1.34 --1.91 -2.24 -0.132 2 -2.06 1.12 -0.512 -1.34 --0.138 -0.951 -1.15 0.824 -0.233 -1.29 --0.124 -1.27 -0.0584 -0.638 -0.486 0.245 --0.0227 0.163 -1.15 1.16 -0.834 1.24 --2.03 -1.65 -0.0205 1.23 -0.522 1.36 --0.801 -0.24 --0.178 -0.238 -1.16 1.05 --1.94 -1.03 -1.45 0.273 --1.07 1.16 -0.413 -1.3 -1.32 0.0928 -0.322 1.68 --0.292 -1.32 -0.206 1.19 --0.639 -1.37 -0.407 1.67 -0.144 1.56 --1.58 0.588 --1.58 0.807 -0.683 -0.0347 --0.668 -1.13 --2.05 -1.4 --0.679 -0.0957 --0.924 1.45 --0.547 -1.31 -0.0296 1.2 -2.23 0.895 --0.56 -1.41 --0.558 -1.67 -0.0598 -1.26 -0.51 -1.15 --0.122 -0.0671 --0.502 -1.04 -1.41 -0.808 --0.68 0.314 --0.347 0.574 --0.155 1.29 -1.18 0.0819 -1.8 -1 --0.653 -0.734 -1.3 0.648 -0.265 -0.182 -0.896 0.36 --0.945 -1.43 --1.26 -1.01 --1.65 -0.723 --0.103 -1.71 -1.87 1.19 -0.839 -0.0819 -0.167 0.87 --0.917 -0.863 -1.26 -0.912 --0.786 -1.02 -2.81 1.3 -0.725 -0.54 --0.709 -0.262 -0.56 -1.05 --1 0.078 -1.18 -0.0513 --1.29 0.891 -0.126 -0.865 -1.31 -0.238 -1.62 -0.919 -0.918 0.82 -2.17 1.24 -0.433 0.38 -0.211 -1.28 -1.18 -0.0335 --1.32 -0.403 --0.0936 -1.28 --0.812 -0.411 -0.933 1.21 -0.642 0.909 -1.16 1.48 --0.54 -0.601 --1.48 -0.682 -1.41 -1.48 --1.63 -1.16 -0.663 1.7 -0.0329 1.88 --1.08 -0.0594 -0.981 -0.0572 --0.334 0.18 --0.477 0.676 -1.12 -0.756 -1.36 0.482 -0.123 -1.62 --0.259 0.996 --0.0662 -0.479 --1.4 0.553 -0.1 -1.48 -1.37 0.428 --0.32 0.707 -1.76 1.33 --0.254 0.403 -0.636 1.34 --0.437 -0.984 --0.804 0.396 -0.685 2.2 -1.89 0.834 --0.615 -1.36 -0.387 1.71 --0.238 -1.49 --1.03 -0.422 -0.656 0.844 -0.713 2.04 -1.26 1.72 --0.745 0.987 --1.44 -0.358 -0.127 1.22 -1.79 1.5 --0.27 0.0117 -0.418 -1.12 -2.17 1.45 -1.66 1.3 -2.12 1.1 --0.252 0.623 -0.16 -1.4 -1.27 0.301 --0.93 0.758 --0.966 0.487 -0.0236 -1.07 -0.517 -0.931 --1.95 -0.9 -0.213 -0.752 --0.377 -0.973 -0.395 0.423 --0.76 -0.862 --0.947 0.445 -0.112 0.238 -1.24 0.342 --0.322 -0.356 --1.15 0.587 -0.923 0.246 --0.339 0.806 --0.711 0.0759 -0.157 -0.934 -0.235 -1.05 --0.111 -1.33 --0.651 0.369 -0.527 1.18 -1.76 1.48 -0.0386 -1.26 -0.584 -0.212 --1.02 -1.01 --1.2 -0.248 --0.824 0.858 -0.191 1.94 --0.259 1.34 --1.22 1.12 -1.11 0.57 -0.073 -0.00169 --0.0281 -0.323 -0.48 -1.15 -0.0967 -1.4 -0.375 1.24 --1.63 0.101 -0.02 -1.54 -0.592 1.15 -0.0071 -0.924 -0.784 0.972 -1.33 0.335 --1.42 -0.0747 --0.795 1.17 --0.0247 -1.5 -0.904 1.04 -0.237 0.0367 -0.604 -0.709 --0.948 -0.982 -0.686 -0.19 -1.2 -0.754 --1.59 0.763 -0.255 0.412 -1.78 1.35 --0.629 -0.118 -0.0428 -1.04 -0.973 0.457 --0.639 1.28 -1.23 -0.00847 -2.64 0.966 -0.323 -0.796 --1.12 -1.39 --1.14 0.693 -0.0328 1.22 -0.0496 -1.05 --2.11 -1.45 --1.28 0.213 --0.577 0.206 -2.71 1.35 -0.121 1.63 --0.0275 -1.42 --1.15 0.406 --0.204 -1.54 --0.299 -1.14 -0.216 1.96 --0.567 -1.14 --0.236 -1.17 -1.22 -0.0466 --0.852 -0.59 --1.06 0.917 -0.595 1.02 -1.05 0.768 -0.996 1.04 -1 1.69 -0.799 0.995 -0.725 1.39 -0.782 1.8 -1.93 1.34 --0.791 -1.43 -1.33 -0.486 -1.64 -0.605 -1.13 0.33 --1.58 0.456 --0.0767 168e-6 --1.87 -1.17 --0.892 1.25 -0.785 0.173 -1.04 0.779 --0.693 0.953 -0.682 -0.146 --0.167 1.07 --0.621 -1.12 -0.133 -0.227 -0.871 1.29 --0.719 -0.384 -0.0379 -1.64 -1.57 1.43 -0.314 1.84 -1.68 -0.293 --0.656 -0.334 -0.551 0.921 --1.52 0.946 --0.156 -1.16 -0.0652 -0.766 --1.15 0.771 -1.07 -0.221 -0.535 1.4 --0.0692 1.73 -2.36 1.33 --0.599 -0.965 --0.903 -0.0822 --1.6 0.682 -0.271 -0.0382 -0.838 0.603 -1.34 -0.689 -0.657 1.05 --1.52 0.506 --1.21 0.488 --0.112 1.85 -0.74 1.53 -0.451 -0.00833 --1.6 0.632 --2.1 -0.859 --1.37 0.645 -0.52 1.25 --0.198 -0.536 -1.54 1.24 --0.421 -0.731 -1.1 0.253 -0.734 -0.212 --2.12 -0.575 --0.0531 -1.26 -0.835 -0.0137 -1.1 0.604 --0.505 1.17 --0.524 -0.857 --1.89 -0.799 --0.975 -0.182 -0.616 -1.07 --0.362 -1.7 -0.611 0.649 --1.41 -1.02 --0.614 -1.43 --0.286 -0.571 --0.697 -1.69 --0.859 0.885 -0.526 1.36 --0.251 0.846 -2.01 -0.695 --1.51 -0.593 --0.155 -1.03 --1.8 0.529 --0.162 -0.0223 --0.628 -0.267 --0.746 -0.93 --0.61 0.00888 --0.0339 -1.66 -0.935 0.556 -1.01 0.829 --2.77 0.0962 -1.26 0.0903 --0.638 -1.01 -0.552 0.961 --0.239 -0.848 -0.275 -0.202 --1.83 0.601 --0.507 1.24 -0.908 -0.506 -1.16 0.703 --0.751 -1.37 --0.628 0.601 --0.5 -0.0595 --0.889 -0.884 --0.341 0.169 -0.0554 -0.139 --0.455 -1.3 --0.116 0.0815 --0.71 -0.874 -1.35 -0.25 -1.51 1.59 -1.67 -0.978 --0.116 -1.36 --1.95 -0.16 -1.75 -1.03 -2.36 1.5 -1.24 0.828 --0.526 1.19 --0.0866 -1.37 --1.46 -0.891 -0.637 0.00536 -0.384 -0.314 -0.431 0.266 -1.35 0.644 --0.744 0.196 --0.45 -1.59 -1.31 1.07 --0.696 -1.2 -0.553 -0.817 --0.532 -0.179 --0.861 -0.862 --1.25 -0.897 --0.631 -0.914 -0.524 -0.648 -0.791 1.69 --0.501 1.1 -0.768 -0.917 -1.29 1.07 -1.24 0.00235 -0.811 2 -1.18 1.25 -0.32 -0.465 --1.27 -0.704 --0.869 1.38 --0.468 0.245 -1.44 -1.52 --1.62 -1.16 -1.89 1.1 -0.284 2.31 -0.0066 -0.994 --1.81 -0.643 --1.19 -1.03 --0.747 0.468 -1.19 -0.966 -0.748 1.81 -0.225 1.34 -0.899 0.538 -0.904 0.195 --1.25 0.479 -0.74 1.35 --0.798 -1.21 -0.371 -0.589 -1.11 0.0482 --0.27 -1.28 --0.369 -0.984 --0.752 -0.319 --0.538 -1.15 --0.509 0.912 -2.51 1.3 -0.137 1.69 --0.129 1.57 --1.55 -0.663 -0.818 0.845 --0.717 -1.03 -0.0188 0.0512 --0.71 0.465 --1.43 -1.18 --1.39 -0.282 -0.753 1.84 -0.598 0.484 -0.0256 0.228 -1.02 0.508 --1.32 1.12 --1.7 0.422 --0.037 -1.35 --1.01 -0.211 --1.25 -1.1 -1.5 0.637 --1.02 0.899 --0.827 -0.757 -1.54 -0.26 --0.0979 -1.01 --1.01 -1.29 --0.707 -0.378 --0.878 -1.16 --1.34 0.717 -2.21 1.21 -0.25 0.466 -2.34 1.13 -0.614 -0.157 -2.03 -0.427 --0.568 -1.36 --1.64 -1.27 -0.779 -0.815 --0.707 -0.568 --0.712 -1.1 -1.62 0.0564 --1.01 0.412 -1.61 1.4 --1.26 -0.503 --0.845 -0.377 -1.31 -0.566 --0.218 2.09 --0.68 -1.07 -1.15 -1.56 -0.55 0.857 --0.43 -1.4 -0.403 -0.997 --0.0017 0.282 --0.617 -0.458 -0.143 -1.56 --0.221 0.12 -0.58 1.17 -0.876 -0.969 --0.0237 0.303 -0.0052 0.24 -0.904 0.97 --0.806 0.575 -0.423 -0.334 -1.08 1.36 --0.639 1.25 --0.0782 -1.1 -0.595 0.429 -0.908 1.48 -0.355 0.562 -0.149 -0.295 --1.94 -0.273 -0.222 0.214 --1.44 -0.43 -0.265 -0.375 --0.295 0.565 --1.55 -1.02 --0.93 -0.895 --1.18 0.422 --0.203 -1.08 -1.26 -0.328 -1.48 -1.05 --0.499 -0.766 -0.12 -1.12 --0.338 -0.91 -0.909 0.522 -0.395 0.0856 --0.7 -1.25 -0.0828 -0.879 --0.832 -1.33 --2.01 -1.85 --1.55 0.695 --0.755 -1.09 --0.83 0.993 -0.314 1.54 --1.44 -0.225 -0.287 1.45 --0.278 -0.815 -1.46 -0.509 -0.496 1.52 -1.81 -0.218 -0.824 0.45 --2.56 -0.0784 --0.836 -0.507 -0.066 -1.23 --0.742 0.36 -1.31 0.328 -1.35 1.21 -0.34 -1.03 --1.07 -0.616 --0.634 1.65 -1.95 -1.02 --0.0397 -1.09 -1.04 -1.13 --1.15 0.729 --0.528 0.953 -0.854 1.15 --1.04 1.04 --0.921 -1.19 --1.78 -1.58 --0.0184 -1.13 --1.55 0.386 --0.539 -1.21 --0.455 0.494 -1.44 1.38 --1.2 0.659 -0.731 1.31 --1.39 -1.09 --0.413 0.0554 -0.271 0.38 --0.882 1.29 -1.29 -1.04 -0.299 1.49 --0.754 1.1 --0.0601 2.04 -1.42 -0.697 -1.12 0.173 --0.783 -1.33 --1.55 -1.6 --1.34 0.146 --1.1 -1.17 -0.101 -1.39 --0.484 -1.2 --0.984 1.03 --0.269 0.961 --0.547 1.71 -0.494 -1.01 --0.123 1.86 --0.0853 -1.12 -1.41 0.607 -1.27 -0.159 --0.0373 -1.32 -0.433 1.65 --1.03 -0.858 -0.69 0.745 -0.354 1.06 --1.92 -1.06 --0.541 -0.65 -1.38 -1.36 -1.29 0.525 --0.836 0.959 --0.247 0.775 -0.552 0.942 --0.19 0.168 -0.714 -1.19 -1.19 0.594 -0.428 -1.43 --0.575 -1.62 --1.97 -1.72 --0.0255 -1.3 --0.892 1.02 --0.132 -1.35 --1.85 0.545 --0.491 -0.429 --0.158 0.358 --0.475 -1.02 -1.26 -2.39 --0.807 0.992 -1.19 0.115 -0.439 1.5 -1.44 -1.73 -0.109 1.65 --0.596 -1.33 -1.11 0.431 --0.347 -0.556 -1.47 1.39 -1.63 -0.56 --1.53 1.21 --1.12 1.1 -0.0551 1.34 --0.388 -1.08 -0.136 -1.36 --0.79 -0.823 -0.646 1.82 --0.468 -0.206 -0.735 0.571 --0.777 -1.33 --0.31 1.45 --0.0693 -1.3 --0.162 -0.334 -0.724 -0.574 --1.03 0.153 -0.385 -0.744 -1.23 -0.115 --1.49 0.796 -0.0586 -0.133 -1.05 -0.362 --0.84 -1.05 -0.351 -1.42 --1.34 -0.462 --0.213 0.77 -0.523 1.05 --0.665 1.23 -1.03 1.55 -0.495 1.54 -0.582 0.232 -0.35 0.889 -0.321 1.58 -0.155 0.0373 --0.783 0.931 -0.153 -0.875 -1.08 0.925 -0.614 0.908 --0.353 1.98 -0.0762 -1.27 -0.282 -1.43 -0.876 -0.807 --0.685 0.459 -0.265 1.4 -0.29 0.591 -0.662 1.49 --0.689 -1.45 --0.214 -1.27 --0.119 -0.842 --1.84 -1.23 --0.102 -0.306 --0.995 -0.937 --0.479 0.0719 --1.31 0.463 --0.486 -1.62 -0.115 -0.443 -0.698 0.784 -1.09 -1.24 --1.57 -0.401 --0.274 0.489 -0.764 1.98 -2.41 0.946 --0.348 0.119 -1.27 -0.194 --0.22 -1.38 -1.08 -1.83 --0.414 -1.28 -2.12 1.07 -0.22 2.08 -0.207 -1.38 --0.519 -1 --0.00634 -1 --0.68 1.68 --1.18 -0.522 -0.32 0.282 --0.638 1.32 -0.72 -0.154 -0.92 -0.717 -0.511 -0.773 --0.681 -0.586 -1.11 0.205 -0.087 -1.28 -1.13 -0.541 --0.016 -1.26 --0.439 -0.884 -0.424 -0.84 -2.25 -1.4 -0.139 -0.803 -0.488 1.31 --1.04 1.27 -1.33 -0.704 --1.23 0.89 --0.329 -0.955 -0.174 -1.11 --0.699 0.755 --0.137 -1.16 -1.09 -1.1 --0.0172 -1.03 -0.269 0.605 -0.305 1.63 --1.82 0.904 --0.527 -1.38 -0.557 -0.255 --2.41 0.26 --0.514 -1.07 --0.325 -1.32 -2.53 1.5 -0.471 2.03 -0.986 0.843 -0.746 0.441 --1.32 0.907 -1.33 1.7 -1.59 -0.378 -0.387 -653e-6 --0.914 -0.919 -1.41 0.0907 --0.639 0.522 -0.866 1.14 --1.78 -0.491 -0.391 -0.0901 --1.27 0.184 --1.08 -0.612 --0.717 0.455 --1.11 0.00172 --1.51 -0.966 --0.862 1.53 -0.605 1.86 --0.818 0.654 --0.391 1.1 -0.941 -0.254 -1.59 1.72 --1.51 -1.16 -0.413 0.473 --0.351 -1 -1.68 0.113 --0.834 1.48 -1.45 -0.507 --0.559 0.0594 -1.23 -0.0997 --0.0342 0.145 --0.834 1.41 -0.743 -1.01 -1.01 1.82 -0.191 -1.29 -0.0543 -0.967 -0.768 -1.25 -1.12 0.612 -0.424 0.547 -1.29 -0.391 --0.612 -1.42 --0.201 0.287 --0.779 1.09 -0.44 0.246 -0.778 0.952 -0.0179 -1.01 --0.216 -1.38 --0.554 -0.38 -0.0698 -1.25 --0.869 0.625 --1.53 -1.17 --0.175 -0.909 --1.5 -1.14 -0.528 -1.04 -1.07 0.61 --0.987 -0.735 --0.468 -1.17 -1.77 0.239 -0.885 -0.372 -2.59 -1.15 -1.04 0.285 -0.736 1.64 -1.23 0.458 --0.137 -1.39 --0.0574 -0.208 --0.496 1.03 --1.04 0.984 -0.952 -1.9 --0.21 0.11 --1.95 0.614 -1.68 -0.472 --0.866 0.751 -0.322 -1.04 --1.71 -0.653 --0.486 -1.53 -0.587 -0.311 --0.55 0.236 -1.4 -0.874 --0.384 -1.08 -0.746 0.991 -0.758 -1.45 --0.0468 -0.332 -0.698 1.02 --1.53 0.658 --0.162 -1.24 --0.507 0.69 -1.41 -1.38 --0.735 -1.19 --0.141 -0.119 -1.31 0.628 -1.38 -1.02 -1.18 -1.19 --0.0785 -1.16 -0.844 1.22 -0.913 -1.6 --1.04 1.33 --1.1 0.145 --0.244 -1.2 -0.0643 -1.28 -0.483 -1.23 -1.37 1.29 --0.869 0.634 --0.0547 -1.06 -0.816 -0.133 --1.49 0.744 --0.813 -0.665 -1.6 0.0487 -0.742 1.56 -1.45 -0.188 --0.791 -1.44 --1.31 0.118 -0.0336 0.323 -0.308 -1.34 -0.856 -1.11 -0.532 -0.0431 --0.171 1.68 --0.305 0.247 --0.422 -0.241 -0.836 0.849 -1.77 0.013 --1.56 0.514 -0.137 -0.862 --1.07 -0.017 --1.31 -0.32 --1.33 -0.581 --1.76 -1.58 --0.258 -1.06 --0.253 -0.809 -0.395 1.35 --1.39 -0.156 -0.446 -1.07 -1.52 0.795 -1.44 0.898 -1.04 0.952 --1.82 -0.847 --1.11 0.276 --1.2 -1.19 -0.268 1.14 -1.29 -1.19 --0.935 1.02 -0.247 -0.96 -0.387 1.59 -0.247 0.41 -0.722 0.153 -0.249 -0.451 -0.923 0.166 --0.237 -0.0378 -1.27 0.496 --1.2 1.43 --1.19 -0.939 -0.0209 -0.973 -0.637 0.984 -0.714 -1.08 --0.215 0.549 -0.306 -0.161 -0.205 -1.28 -1.51 1.52 --0.761 0.373 --0.706 -0.697 --0.383 0.671 --1.11 -0.44 -0.496 -0.614 --0.0529 -0.0168 -2.09 1.1 --1.28 -1.17 -1.44 0.0946 -2.06 -0.893 --0.638 -0.752 -0.402 -0.39 -0.122 0.599 -1.42 1.49 --1.55 0.588 -0.854 0.0949 --0.268 0.75 --0.57 0.502 --0.381 -0.959 -0.236 0.443 -0.898 -0.719 --0.432 1.13 -1.14 -0.938 -0.0935 2.1 -0.463 0.935 --0.23 -1.02 -0.671 0.181 -0.168 1.7 --0.175 0.0644 -0.796 0.423 --0.824 -0.471 --0.93 -0.502 --1.06 1.49 -0.375 1.27 -2.45 1.25 --2.04 0.401 -0.0735 -1.01 --0.737 -0.0677 -0.848 0.402 -0.281 0.343 --1.13 -0.0974 --0.821 -1.44 --0.211 -0.334 --0.364 -1.4 --1.27 -0.673 -0.784 1.39 --1.02 0.883 -0.833 -0.0565 -0.478 1.31 --1.14 -0.245 -1.14 0.494 -0.667 -1.01 -2.17 0.926 --0.129 0.877 --0.581 0.582 -0.427 1.77 --0.138 0.425 --1.98 0.875 --0.337 0.559 --0.369 -0.965 -0.325 -0.153 --0.232 -0.364 --0.749 1.26 --0.566 1.19 -1.33 -0.774 --1.25 -1.47 -0.00453 1.47 --1.81 -0.543 --0.307 0.938 --1.18 0.732 --1.68 0.93 --1.52 -1.4 --1.45 -0.701 -0.616 1.77 --0.0222 -0.202 -0.246 -0.767 --0.763 -0.573 --0.581 -0.182 -1.42 -0.0465 --0.139 -1.27 --0.179 0.19 --0.721 1.19 --0.709 -0.942 -0.945 0.239 --0.891 0.593 --1.18 0.862 -1.3 -0.028 -0.576 -0.342 -0.0381 0.167 --0.219 -0.195 -0.855 0.959 --1.08 -1.17 --0.596 -0.989 --1.41 -0.856 --0.298 -0.243 -0.444 1.14 -1.01 0.397 -1.31 -0.36 -1.78 1.19 -1.1 0.458 --1.33 -0.647 --1.6 -0.541 --1.2 0.455 -1.01 1.57 -1.38 0.583 --0.223 1.04 --1 -1.22 -0.576 -0.665 --0.394 1.39 --0.573 -0.88 --2.19 0.0991 -0.729 1.49 -0.308 -0.913 -0.661 0.0147 -0.515 0.884 -1.32 -0.144 --1.05 -0.382 -1.46 -0.0465 -1.22 -0.159 -0.639 -0.815 --0.235 0.352 --2 0.403 --0.158 -1.08 -1.71 1.39 -0.905 -0.551 --0.0949 -0.821 -0.781 1.08 --0.624 1.75 --1.4 1.19 --1.21 0.357 -0.123 -1.24 -1.01 0.446 --0.666 -1.34 --0.819 -0.943 -0.202 -1.17 -0.745 0.681 --0.461 -1.07 -0.622 -0.546 --1.51 -1.39 -1.05 0.409 -0.751 0.608 --1.13 0.164 -2.33 1.21 -0.855 -0.265 --0.0247 -0.765 -0.21 -1.26 --1.67 -0.212 --0.394 -0.338 --0.389 -1.2 -1.11 1.33 --1.24 0.323 --0.116 -1.23 -0.372 1.6 --1.23 -0.806 -1.31 -1.72 --0.254 -1.37 --1.15 -0.647 -1.21 -1.77 -0.00425 1.61 --0.67 1.22 -1.57 1.16 --0.241 0.897 -1.04 0.93 -1.39 0.504 -1.96 -0.709 -0.978 -1.33 --1.67 -0.00451 --0.529 -1.02 --0.137 1.44 --1.87 -0.78 -1.04 -0.24 --1.21 -0.785 -0.8 0.662 -0.133 2.05 -1.34 -1.8 -0.175 0.652 -1.14 -0.0829 --0.634 1.26 --0.617 -0.792 --1.42 0.728 -0.897 0.742 --0.0814 2.18 -1.27 1.6 --0.759 0.366 --0.847 -0.896 -1.23 -0.785 --0.843 -1.14 -0.357 0.647 --1.36 -0.258 -0.977 0.597 -1.05 -0.467 --0.717 1.23 -0.955 -0.0158 -1.6 -0.183 --1.21 -0.733 --0.593 1.28 -1.14 0.814 --0.597 0.232 -0.575 -0.19 --1.34 -0.31 --0.129 -0.061 -0.447 0.92 -0.377 -0.643 --1.54 0.643 --1.25 -0.689 -2.34 1.18 --0.341 1.55 -1.27 0.0842 --1.73 0.562 -0.957 0.0986 --0.639 -1.04 -0.303 -1.35 --0.439 1.37 --0.287 -1.07 -1.46 0.651 -0.957 -0.786 --0.0107 -0.96 -1.21 0.0512 -0.105 -1.67 -0.786 0.859 --1.08 0.356 -0.0909 -1.39 --1.34 0.805 --0.647 1.08 -1.17 -1.4 --0.811 -1.35 --0.961 -0.102 --0.968 -0.226 --0.322 0.535 --1.26 -0.515 -0.62 -0.986 --2.32 0.0861 -1.21 1.31 -0.196 1.08 -1.45 1.33 -0.137 -0.247 --0.974 -1.43 --0.335 -1.69 --0.0999 1.97 -0.272 0.813 -0.56 1.18 --0.0527 -0.746 --0.188 -0.998 --0.369 0.692 --0.226 -1.06 -0.458 -0.709 --1.26 -0.912 --1.33 -0.392 --0.621 1.52 --0.753 1.1 --0.435 -1.08 -0.328 1.28 -0.227 1.71 --0.715 0.0859 -0.81 1.93 -0.364 1.98 -0.624 1.1 -0.922 0.93 --0.416 -0.941 --1.37 0.968 -0.269 1.62 -0.353 1.58 -0.11 0.553 -1.49 0.385 -0.571 -1.53 -0.171 1.59 -0.409 -0.0572 -1.93 -0.842 -0.907 0.191 -0.0413 0.345 -0.484 -1.3 --0.0305 -1.09 -1 -0.0897 -1.09 0.299 --0.543 -0.0204 -0.659 0.913 --0.542 -0.739 --1.02 1.53 --1.63 0.293 -1.49 0.627 --0.583 -1.05 --0.807 1.12 --0.683 1.38 -0.0734 -0.162 -0.388 1.64 -0.874 1.79 -0.584 0.679 -1.42 0.374 --0.779 0.676 -0.678 0.335 -0.204 -1.06 -1.43 0.498 --0.779 -1.2 --1.3 0.577 -1.03 0.0331 --0.532 -1.17 -0.119 -1.28 -1.53 -1.05 --0.481 -0.904 -0.858 0.399 -0.126 0.819 --0.88 -1.27 -0.145 -0.626 -0.534 1.86 -2.03 1.1 --0.546 0.442 -1.42 1.8 -1.41 -2.09 --0.566 -0.563 --0.973 0.495 -0.932 1.43 -0.472 1.37 -0.74 0.053 --0.214 1.76 --0.53 -0.944 --0.936 -1.5 -0.37 -0.0513 -0.695 0.651 -0.88 0.275 --0.563 -0.164 -1.27 -0.675 --1.32 -0.146 -1.7 -0.489 -0.832 0.442 -0.561 1.74 -0.617 1.11 --1.41 1.14 -1.71 -0.225 -0.473 0.339 --0.855 1.44 --1.72 -0.41 -0.18 -0.0627 -0.712 0.837 -0.211 1.71 --0.755 -0.759 -0.661 1.2 -0.902 0.947 -0.544 -0.842 -1.67 0.974 --0.0571 -1.5 --1.61 -0.39 --0.261 -1.27 -1.8 1.53 -0.134 -1.18 --0.279 -1.06 -0.405 -0.555 --1.64 -0.562 --0.146 1.83 -0.499 -1.17 --0.171 -1.09 --0.175 -0.946 -1.54 -0.336 -1.33 0.406 -0.833 0.653 -0.69 1.57 --0.542 0.918 -1.19 -0.319 -1.73 1.26 --2.01 0.439 -0.316 1.43 -0.933 0.711 -2.43 0.869 --0.472 -1.16 --1.17 0.126 -2.22 -2.04 -1.07 0.438 --0.125 0.521 -0.857 0.875 -0.569 -0.858 -0.646 -0.932 --0.983 1.1 --0.829 1.06 -0.22 -0.867 --2.09 -1.22 --1.64 -0.962 -0.0604 1.64 -1.62 -1.16 --0.021 -1.09 --1.11 -0.653 -1.13 -0.0116 --0.838 -1.17 -0.102 -1.03 -0.576 -1.05 -0.635 1.67 -0.336 0.611 -0.32 -0.998 --1.58 -1.61 --0.129 -1.69 --0.249 0.505 --0.986 -1.27 -0.335 -0.483 -0.133 -0.568 -1.08 -1.02 --0.486 -0.887 -2.08 1.35 -0.638 1.11 -0.0965 -1.1 -1.03 -0.382 --0.705 0.129 -1.35 1.1 --0.1 -1.05 -0.431 -1.56 --1.37 -0.123 --0.995 -0.832 --0.981 -1.04 --1.9 -1.32 -0.982 -0.452 --0.494 -0.719 -0.995 0.502 --0.507 0.357 -0.0853 0.789 --0.0659 -1.33 --1.51 -0.276 --1.03 0.681 -1.19 -1.25 --1.49 0.228 -0.409 1.76 --0.606 -0.129 -1.18 0.597 -0.108 -0.304 -0.418 -0.897 -0.381 1.55 --0.951 -1.3 --0.119 2.06 -1.14 0.148 -1.31 1.62 -0.724 0.417 --0.107 -0.232 --1.57 0.905 --0.214 1.58 --0.212 -0.155 --0.0683 -0.404 --0.951 -1.33 -0.533 0.541 --1.36 0.887 -0.98 -0.832 --1.29 1.52 -1.08 -817e-6 --0.147 1.85 --0.135 0.0707 -0.318 -0.87 -0.632 1.74 --1.43 1.25 --0.499 -1.31 -0.296 1.51 -0.416 0.1 --0.337 1.48 --1.3 -0.829 --0.0299 0.617 --1.78 -0.843 -0.314 -1.25 --0.801 1.78 -0.0984 0.629 --1.68 -0.528 -0.423 0.598 -0.00295 -0.125 --0.528 -1.23 -0.17 -0.719 -0.202 -1.37 -0.535 1.99 --0.491 1.22 --1.33 -0.276 -0.595 0.546 --0.219 0.524 -0.0182 1.68 --0.907 0.416 -1.86 -0.36 --0.733 -1.34 --1.39 -0.322 -0.0578 -1.32 --1.7 0.869 --0.166 0.165 --0.8 -1.38 --1.02 -0.146 --0.145 -1.39 --0.439 0.331 -0.136 1.46 --0.669 0.51 --1.49 -0.0266 -0.386 -0.997 -0.812 -0.15 --0.303 -0.883 --0.621 1.16 --2.04 -0.978 --0.772 0.933 --1.06 -0.86 -0.0914 0.493 --1.17 0.222 -0.553 -0.159 -0.759 0.0328 --1.04 -1.24 -0.974 -0.951 -0.33 -1.48 -0.105 1.77 --1.02 -0.305 --0.635 1.94 -0.44 1.16 --0.97 -1.6 -2.22 1.31 --1.18 -0.122 -1.46 0.0665 -0.219 1.59 -1.09 0.812 -1.15 1.68 -0.955 -0.23 --0.103 0.0369 -0.619 1.65 --1.43 -0.357 --0.765 -1.13 --0.664 1.18 --1.09 0.289 --0.766 1.06 --0.436 0.821 -0.6 -0.38 --0.124 0.181 -1.03 -0.0835 --1.71 -1.27 --1.46 -0.179 -1.34 1.37 -1.47 0.574 -0.716 0.487 -0.0337 -1.13 --0.432 -1.34 -0.344 1.49 -1.29 -0.151 -1.85 -0.558 -0.0319 1.39 -1.95 1.09 --0.839 0.111 --0.956 -0.77 -1.08 0.839 -0.0624 -1.05 --1.06 -1.24 --0.366 -1.52 --1.63 -0.363 -1.05 1.07 --0.47 -1.12 --1.45 0.377 --1.56 -1.05 -0.912 2.1 -1.61 0.582 -0.208 -1.21 -0.929 -0.902 --1.66 -1.52 --1.85 -0.347 --1.02 -0.0308 -0.569 -0.538 -1.43 -0.366 -1.47 -0.0578 -0.154 0.629 --1.59 0.176 -0.801 1.14 --1.5 -0.829 -0.271 0.0595 -0.188 0.914 --0.386 1.5 -1.02 0.0541 -0.82 -0.514 -0.804 0.6 --1.38 -1.11 --1.01 -0.155 -0.683 1.6 --1.62 -0.896 --0.00515 1.75 --1.42 -1.28 --1.8 -1.26 --1.76 -0.632 --0.0958 -1.66 --0.473 -1.55 --0.316 -1.36 --0.899 -1.25 --0.236 -1.54 -0.546 -1.12 -1.16 -1.3 -0.00921 -0.00839 -1.63 -0.43 --0.826 0.682 -0.371 -1.23 --0.821 -0.855 -0.309 -1.03 --0.912 -0.484 -0.365 0.632 -1.15 -1.69 --0.714 -1.36 --0.467 1.3 -0.177 -1.07 -0.589 0.557 --1.85 -0.35 -0.676 0.892 --1.49 -0.498 --1.28 0.72 -0.166 -1.25 -0.448 0.71 --1.9 -1.46 --0.922 0.533 -0.307 0.12 -0.328 0.553 --0.847 -0.871 -1.08 0.437 -0.173 -0.428 --0.818 -0.69 --0.583 -0.743 --0.768 -0.0166 --2.04 0.131 --1.16 -1.01 -0.995 0.131 -1.32 -0.616 -0.993 0.397 --0.606 3.19 -0.811 0.00911 --0.462 -0.707 -0.304 -0.00393 --1.94 0.598 --0.372 1.54 -0.341 -1.43 --0.78 -0.43 -0.247 -0.233 --0.561 0.473 --0.524 -1.09 --1.99 -0.912 --2 -0.0624 -0.554 1.19 -0.899 1.4 -0.794 1.01 -0.417 0.348 --0.597 -1.6 -1.71 -0.289 --0.461 0.343 --1.02 -0.469 --0.434 1.98 --0.299 -1.4 --1.67 -0.875 --0.192 1.04 -0.108 -0.769 --0.58 1.34 --1.17 -0.95 --0.124 -0.95 -0.283 -1.56 -0.418 -0.711 -1.2 0.286 -0.295 -0.273 --1.37 -0.904 -0.0175 1.47 -1.64 0.513 -0.557 1.38 --0.878 0.659 -0.254 2.42 -0.961 0.454 --0.994 0.192 --1.07 -0.622 -1.95 1.53 -0.281 -0.4 -1.29 0.283 -0.586 -0.273 --0.0272 1.86 --1.65 -0.0692 -1.22 -0.345 --1.53 0.132 --1.51 -0.248 --1.2 -1.04 -0.299 1.52 --0.687 1.01 -0.479 -0.821 -1.08 -0.133 --0.888 -1.59 --1.52 0.497 -0.198 -1.41 --0.211 -0.492 -0.0647 -1.22 --1.28 -1.07 --0.0779 -0.967 -0.369 1.69 --0.826 -0.966 --0.394 1.6 -1.2 -0.68 -0.942 1.89 --0.817 -1.11 -0.405 1.93 -0.666 -1.52 -0.152 -0.964 --0.82 -0.76 -0.72 -0.316 --0.201 0.596 --0.594 -1.21 --1.07 0.0456 -1.05 0.397 --1.12 -1.2 -1.5 -0.38 --2.06 -1.23 -0.785 0.158 -0.867 -1.19 -0.624 -1.31 --0.509 -0.932 --0.565 -0.853 -0.0662 1.62 -0.0852 -0.852 -0.399 -1.48 -1.27 0.433 --0.441 -1.45 -1 0.285 --1.01 -1.47 -0.873 -1.03 --0.144 -1.03 -1.25 -1.62 --0.149 0.816 -0.893 0.691 --0.136 -1.41 -0.569 1.44 --1.93 -0.0856 --0.625 1.65 --1.16 -0.285 --0.903 -0.988 -0.486 1.05 --0.0145 -1.15 --0.678 -1.32 -1.29 -0.499 --0.116 1.26 -1.1 -0.374 -1.06 0.913 -0.19 0.969 --0.487 -1.19 --1.79 -1.46 --0.0388 -0.984 -0.893 -0.327 -1.38 -0.244 -1.01 -1.12 --1.58 -0.352 -1.52 -1.12 -0.136 -1.49 -0.538 -1.39 --0.503 1.35 --0.991 0.114 -0.675 -1.53 --0.581 -1.34 --1.38 -1.08 --0.298 -0.823 -0.0919 -0.154 --1.01 1.21 --1.89 -0.418 -2.22 1.18 -0.0608 -1.23 -0.677 1.03 -0.641 1.72 --0.539 0.648 -0.934 0.358 -0.0105 -1.26 --0.86 -1.27 -0.883 -1 -2.32 1.3 --0.566 -1.62 --1.25 -1.14 -2.69 1.12 --0.529 -1.22 -1.39 1.52 -1.21 -0.132 -0.126 -1.08 --0.967 1.22 --0.121 -0.498 -1.4 0.43 -0.994 0.348 --0.193 -0.288 --0.545 -1.31 -1.06 -0.232 -1.06 0.763 -0.646 1.23 -0.673 1.07 --0.512 -0.954 --0.701 1.17 --0.957 0.848 --0.676 0.797 -1.47 -0.0839 -0.514 0.715 --0.451 -1.34 --0.484 0.615 -1.17 0.868 -1.2 0.318 --0.795 0.276 --689e-6 2 --2.06 -0.332 -1.42 -1.1 -1.07 0.646 --0.285 1.39 -0.0524 -0.853 -1.81 -0.0547 --0.379 0.638 --1.14 1.16 -0.878 -0.856 --1.08 1.19 -0.13 -0.469 -0.224 1.57 -2.13 1.16 --0.604 -1.2 --0.109 -1.32 -0.0803 -1.15 -0.383 -0.987 -0.799 -0.834 -0.866 0.612 -0.897 0.294 -2.46 1.21 --0.267 1.37 -2.04 -0.462 --1.17 -0.556 --1.49 0.555 -1.08 -1.76 -2.03 0.984 -1.17 1.28 --0.448 0.91 -1.07 0.573 -1.05 0.776 -1.2 0.0691 --0.973 0.712 -0.0399 -1.28 --0.522 0.206 -1.46 -1.61 --0.912 1.34 --0.375 -1.39 --0.117 1.47 -0.388 0.863 --1.53 0.0251 -1.38 1.27 -0.237 -1.26 -1.63 -2.16 --0.148 1.6 -0.159 0.586 -0.262 -0.538 --1.83 -0.964 --1.65 -0.731 -0.737 -0.183 -0.711 0.787 -0.953 1.14 --0.284 -1.02 -1.47 -1.29 --0.89 -1.18 -1.7 0.157 --0.451 0.723 --0.499 -0.858 --0.515 0.625 -1.16 0.776 --1.55 -0.132 --0.325 0.388 -0.372 -0.809 -0.335 1.99 --0.595 0.625 --1.03 -0.95 -0.452 1.95 -0.656 1.25 --0.872 -0.461 -0.425 0.0454 --1.24 0.788 -0.524 0.283 -0.83 0.692 -0.347 -0.242 -1.29 0.622 --0.106 0.552 --0.353 -0.836 --1.28 -0.00494 --0.172 -0.676 -0.303 -1.18 -0.455 -0.869 --0.964 -1.17 --1.85 -0.467 -0.632 1.45 -0.552 -0.199 -2.14 -0.453 --0.688 0.709 --0.0708 0.439 -0.177 -1.37 --0.135 0.136 --0.288 0.385 --0.974 -0.818 --0.511 -0.734 -0.449 0.648 --1.51 -0.193 -0.565 1.56 -1.19 0.19 --1.13 -0.622 -0.651 -1.08 --0.542 1.12 -1.57 0.171 -1.09 -0.538 --0.399 1.3 -1.36 -1.06 -0.614 -0.705 -0.823 -0.248 -0.894 -0.992 --0.731 -0.906 -0.017 -1.26 --0.487 -1.13 --1.03 0.277 -0.816 0.762 -1.03 1.61 -0.889 -0.566 -1.2 -0.944 --0.375 1.36 -1.46 1.69 -0.587 0.322 -0.985 1.16 -1.11 -0.476 -1.18 -0.789 -0.386 1.92 --1.29 -1.03 -0.921 0.3 --0.835 -1.04 --1.04 -1.42 --0.356 -1.16 -0.74 0.203 --0.879 -0.975 --0.603 1.3 --1.05 -0.4 --0.501 -1.43 -0.501 0.0251 --0.55 -1.07 -0.133 2.04 -1.5 0.541 --0.741 0.979 -0.764 0.381 -1.02 -0.549 -1.23 2.19 -0.4 -1.39 --0.167 -0.633 -0.995 -1.63 -0.422 2.33 -0.45 1.6 -0.115 1.41 -0.00914 0.431 --0.992 1.4 --0.95 0.144 -0.297 -1.11 -0.953 0.719 --0.683 0.419 -0.44 -0.778 --0.785 -1.11 -0.182 -0.0823 -1.32 -1.23 --0.762 -1.11 -0.977 -1.01 -0.395 -1.04 --1.16 1.03 -0.786 0.945 --0.0267 -1.09 --1.39 1.09 -1.88 -0.141 --1.81 0.0758 --0.0931 1.52 --0.0677 -0.394 --0.544 -0.773 -0.175 -0.345 --1.07 -0.456 -0.534 -0.763 --0.737 -0.617 --0.291 -0.858 --0.753 -1.25 -0.875 1.82 -0.518 1.41 -0.0526 -1.31 --0.0198 -1.22 -0.28 0.429 -1.19 -1.33 --0.926 0.694 -1.3 -1.28 -1.46 -1.32 -0.475 -0.381 -0.685 0.546 --1.33 -0.0457 --0.943 -1.26 -0.226 -1.02 -0.971 0.64 -0.49 -0.0477 --0.343 -1.39 -0.301 -0.928 -0.343 -1.14 --0.625 -1.14 -2.2 0.935 --0.429 1.13 --0.761 -1.44 --0.409 0.349 -1.07 -1.38 -0.209 -0.455 -0.521 0.375 -0.575 1.42 --1.23 -1.15 -1.11 0.989 --0.595 1.09 -1.2 0.361 --0.629 0.809 -1.15 -1.01 -0.238 -0.551 --1.02 0.409 --0.0743 -1.38 -0.393 1.64 --0.126 -1.67 -1.14 -1.57 --1.82 -0.665 -0.636 0.756 --1.14 0.915 --1.2 0.4 -1.57 -0.0786 -0.196 -1.71 --1.42 0.275 -1.89 -0.243 --1.64 0.767 -1.1 -0.364 --0.113 0.626 --0.48 0.0507 --0.415 -1.3 -1.28 -0.341 -0.399 -0.594 -1.01 -0.205 --0.4 -1.37 --0.239 -0.619 --1.53 -1.72 -0.0745 -0.607 -1.53 0.0838 -2.75 1.47 -0.26 -1.17 -1.08 1.03 --0.239 -1.17 -1.09 1.21 --1.19 -1 -1.29 -0.12 -0.844 -0.402 -0.224 1.75 --1.42 1.13 -1.31 -1.08 --0.275 1.52 -0.948 1.41 --0.999 0.906 --1.63 0.279 -1.13 1.51 -1.24 0.809 -0.0941 1.44 --0.636 1.72 --1.26 -0.457 -0.249 -1.46 --1.02 0.675 --1.77 1.01 --0.292 1.32 -0.391 -1.42 -0.377 1.72 --0.826 -1.67 --0.528 0.296 --0.00835 1.76 -1.64 -0.152 -0.317 -1.13 -1 -0.0347 --2 -2.1 -0.0394 -1.35 --0.633 -1.18 -0.0927 -1.02 --0.389 -1.32 -0.83 1.67 -1.12 1.01 -0.176 1.23 -0.991 0.594 --0.0545 -1.45 -0.927 -1.12 --1.78 0.819 --0.0207 -1.14 -0.915 0.611 --2.98 -0.16 --1.81 -1.21 --0.0982 0.395 -0.98 0.766 -0.47 -0.765 -1.41 0.9 --1.55 1.05 --1.53 0.39 -0.621 1.48 -0.47 1.21 -0.805 1.21 --1.4 -0.386 --2.14 -1.59 -0.974 0.898 --1.16 -0.641 -0.947 -0.888 -1.52 -0.85 -0.39 -1.2 --1.82 -0.899 --1.42 -0.617 --0.927 -0.406 -0.64 1.35 --0.2 -1.02 --0.0611 -1.4 --1.06 0.181 -1.22 0.541 --0.56 1.06 -1.79 -0.834 -0.362 1.59 -2.55 1.4 --0.248 0.514 --0.908 1.26 -1.91 1.37 --1.35 -0.688 --0.0906 2.01 -0.409 0.212 --0.69 -1.33 --1.51 0.213 -0.923 1.54 --0.687 -0.458 --0.928 1.55 -1.01 -0.935 --0.44 1.22 -0.921 1.12 --1.65 -2.05 --1.57 -0.772 -2.32 1.32 --0.64 -0.238 -1.21 -0.271 -0.484 1.04 -1.26 -0.25 --0.659 -1.27 -0.0558 1.88 --1.7 -0.087 -0.739 0.673 -0.67 0.784 -0.592 0.235 --1.64 -1.91 --1.74 -0.521 --2.1 -1.06 -0.487 1.33 --0.772 -1.38 --0.856 -0.664 -0.0844 1.72 --0.792 -0.132 --0.954 0.848 --1.39 -1.35 -1.4 0.855 -1.3 1.04 -0.299 -0.819 --1.1 -1.13 -1.03 -1.12 --1.3 -0.811 --0.178 -1.15 -2.05 -0.105 --1.38 0.0973 --1.01 -1.23 -0.534 2.15 -0.388 -0.0851 -0.484 1.04 -0.646 0.778 --1.3 0.867 --1.38 -0.149 --1.02 0.849 -0.0971 1.58 -0.606 1.77 -0.129 1.52 -0.689 -0.506 --0.811 -1.15 -0.318 1.82 -1.89 1.34 -0.326 1.45 --0.655 -1.44 -1.85 1.61 -1.15 1.49 -0.261 0.214 --0.108 -0.793 --1.08 -1.39 -0.342 -0.701 --0.0615 0.299 -0.905 -0.994 -0.318 0.621 -0.851 0.598 --0.66 1.41 -0.908 0.127 -1.18 1.36 -0.999 0.811 --1.04 -0.0359 --0.492 0.124 -0.409 -1.15 -1.31 0.936 -1.23 -1.4 --1.82 -1.78 --0.0723 -0.428 --0.0681 -1.24 --0.96 0.644 -0.974 -1.47 -0.0292 -1.21 --0.852 1.32 --0.777 1.22 --0.379 -1.6 -0.896 0.363 -2.59 1.16 --0.489 -1.13 --1.12 -0.297 -1.03 0.766 --0.621 0.425 --0.537 -0.223 -1.85 -0.377 --0.0434 -0.442 -0.856 0.669 --0.219 0.128 -1.28 -0.588 --0.999 1.2 --0.834 -1.36 -0.3 -1.18 -1.05 -1.05 --0.0203 -1.42 --0.157 1.84 -0.208 -0.427 --0.21 1.35 --1.51 -0.196 -1.46 -0.14 --0.78 -1.52 --0.00816 -1.38 --0.591 -1.08 --0.0202 -1.26 -0.288 1.62 --1.51 0.384 --1.15 -0.508 -0.245 -0.681 -0.757 -0.208 --0.242 -1.47 -1.01 1.21 -0.651 0.744 -1.4 0.746 -0.0426 -1.18 --1.67 0.809 --0.232 0.626 --1.74 -1.83 --0.31 -1.27 -0.0968 0.589 --0.202 1.64 -0.15 0.442 --0.82 -1.04 --0.804 0.687 -0.148 1.26 -0.832 -1.29 -0.577 0.628 --1.19 -1.14 -1.63 -0.539 -0.289 0.598 --0.679 0.536 --1.78 -1.07 -0.277 -0.324 --0.128 -1.14 -0.613 -0.211 -0.468 0.986 -0.295 -1.36 -0.563 0.661 -0.407 1.8 --0.744 -0.415 -0.203 0.617 -0.0169 -1.22 --0.295 -1.22 --1.01 -1.65 -0.851 0.95 -1.49 1.59 --0.658 0.554 --1.29 -1.14 --1.61 -0.364 --0.738 1.01 --1.45 -0.0697 --1.5 -0.39 --1.1 -1.24 --0.921 0.894 --0.0633 -0.699 -0.31 0.57 -1.12 -0.422 --1.08 0.989 -0.686 1.2 --0.135 -1.12 --0.243 1.76 -0.812 -0.751 -0.477 0.791 --0.838 0.644 --0.711 -1.13 --0.269 -1.47 -1.18 -0.917 -1.03 -0.209 --0.599 -0.521 -1.26 -1.57 --1.2 0.92 -0.0538 -1.01 -0.247 -1.28 --1.37 0.15 -1.21 0.197 --0.431 -0.346 -1.93 0.165 -0.883 0.106 --0.206 -0.0207 -1.24 0.608 -0.262 -1.16 -1.02 0.72 --0.384 -0.397 --0.803 -1.21 -0.677 0.964 --0.148 -1.37 -0.355 2.08 --0.811 -1.21 -1.16 0.598 --1.05 -0.832 --0.326 0.168 --0.372 -1.38 -1.13 1.38 -0.331 0.185 -1.67 -1.77 --0.00621 1.56 -0.166 -0.33 -0.847 -0.61 -0.68 0.739 --0.411 -1.41 --0.917 -1.08 -0.956 0.558 --2.11 -1.51 --0.0791 -1.38 -0.329 1.11 -0.0545 2 -0.451 -1.23 --1.44 -0.775 -0.841 -0.0776 -0.829 1.56 --1.64 -0.121 -0.0291 -1.12 -0.823 1.04 --1.55 -0.744 -0.196 -0.779 -1.16 0.654 -0.35 1.22 -0.487 1.45 -0.811 -1.65 --1.53 -0.665 --1.39 -0.118 --2.13 0.678 --1.8 -1.62 --0.182 -1.54 -0.569 0.481 --0.463 -1.01 -0.311 1.68 -0.923 -1.02 -0.388 1.72 -1.52 0.356 --1.03 1.31 -0.637 1.55 --0.122 -1.14 -0.258 -0.85 --0.581 1.36 --1.78 -0.582 -1.09 0.6 -1.17 0.426 --0.419 1.4 -0.932 0.501 --0.132 0.954 --2.04 -0.584 -0.218 1.32 -0.747 -1.05 -1.32 -0.311 --0.72 -1.39 -1.44 -0.0447 -2.03 1.32 --0.654 -1.02 --1.66 0.835 --0.515 0.976 --0.851 0.405 --0.231 -0.75 -0.271 -1.28 --0.335 -0.81 -0.981 0.26 --1.25 -0.576 --0.849 -0.187 --0.483 1.16 -0.472 0.0979 -0.247 -0.9 --0.651 -0.159 --0.278 -1.32 -1.43 0.57 --0.473 0.085 -0.251 0.171 --1.77 0.457 -1.03 0.252 --0.552 -1.18 -0.91 0.665 --0.431 1.21 -1.41 0.258 --0.579 0.79 --0.383 -1.04 --0.833 -1.23 --2.13 -0.347 --0.975 0.725 -0.139 -0.762 --0.847 -0.213 --0.106 -1.14 -1.22 -0.106 --0.555 -1.02 --0.851 0.681 --0.401 -1.17 --0.11 -0.372 --0.425 0.996 -1.22 -0.607 -0.707 0.948 -0.101 1.93 --0.316 0.177 --1.06 0.665 --0.896 0.207 --0.381 1.41 -0.915 -1.27 -1.24 0.31 -2.44 1.37 --0.0819 1.64 --1.48 0.74 -0.4 1.68 -1.25 1.2 --0.957 1 --0.153 -1.15 --1.98 0.345 --0.675 1.18 --1.39 -0.474 --1.07 0.256 --0.357 -0.944 --0.35 -1.49 --0.747 -0.72 -0.84 -0.176 --1.5 -1.22 --0.294 -1.54 -1.22 -1.58 -2.25 1.21 -0.75 1.92 --0.472 -0.0198 -0.833 -0.593 -0.423 1.74 --1.49 0.738 --0.855 -1.33 -0.325 -0.0325 -0.0526 1.42 -1.72 -0.793 --1.43 -0.546 -0.427 1.99 --1.48 -1.23 --1.19 -0.638 --1.07 0.00513 -1.98 0.417 --0.264 0.0571 --0.0143 1.55 -0.408 0.0179 --0.952 432e-6 -0.667 1.92 --0.945 -0.639 --0.387 0.104 --0.633 -0.698 --0.583 -1.35 --0.692 0.759 --0.935 0.321 -0.544 1.22 -0.0745 1.78 -0.465 0.283 --0.987 -0.814 -1.24 0.79 --0.427 -0.485 -0.708 0.961 --0.502 1.84 -1.32 -0.331 -0.454 1.48 -0.321 0.299 --1.92 -1.5 --1.33 0.719 --0.803 1.25 --0.265 1.28 --1.59 0.913 --1.23 -0.703 --1.46 1.2 -1.44 0.358 -1.07 0.441 --0.139 -1.26 --0.632 1.35 --0.949 1 -2.34 1.16 --0.0753 0.267 --0.179 -0.0492 -1.8 1.32 --0.142 0.231 -1.19 -0.278 --0.924 -0.102 -1.35 0.472 -0.151 0.322 --0.616 0.413 --0.779 -1.04 -0.347 0.414 -0.745 0.366 --0.0187 -1.55 -0.168 -1.06 --2.6 0.217 --0.228 -1.06 --1.06 -0.881 -0.325 0.213 -0.926 -1.17 -0.479 1.48 -0.0109 -0.378 --0.445 -1.24 -0.89 0.864 --0.115 -0.719 -1.05 -0.96 -1.21 0.227 -0.105 -0.208 -0.514 1.52 --0.644 -0.78 -0.63 -1.23 -0.558 -1.06 --1.57 0.679 -0.962 0.851 --0.588 -1.35 -1.08 0.378 -1.96 1.31 --0.0685 0.931 --0.0253 0.0742 -0.552 -0.244 -0.95 -0.0297 --0.298 0.158 --0.279 -1.25 -1.05 -0.23 -1.27 -0.573 --0.292 -0.224 --0.174 -0.478 -1.72 -0.471 --0.862 1.01 --0.383 -1.26 --0.953 1.06 --1.24 1.14 --1.11 1.1 --1.58 0.272 --1.66 0.75 --0.364 1.7 --1.4 -0.107 -0.171 2.11 --1.75 0.318 --0.99 0.231 -1.2 -0.778 -0.57 1.42 -0.802 1.21 -1.25 -0.202 -0.941 1.16 --0.163 -0.759 -1.36 0.86 -1.25 0.555 -1.18 0.204 --0.459 -1.11 -1.66 0.239 --1.05 0.966 --0.334 1.63 --0.593 -1.58 --0.974 1.05 --1.96 0.445 -0.361 0.931 -1.35 -0.461 -0.0727 -1.46 --0.956 -1.61 -2.34 1.64 --1.45 -0.167 --1.83 -0.746 --0.971 -0.906 --0.813 -1.23 -0.482 -0.653 --0.14 -0.694 -0.56 -1.02 --0.693 1.28 -0.358 -0.887 -1.8 1.36 --0.666 -1.1 --0.239 -1.42 -1.14 -0.286 --0.315 -1.3 --0.153 1.97 -0.589 0.714 -2.47 1.12 -0.605 1.28 --1.21 1.19 --0.704 1.46 --0.724 -0.973 --1.67 0.672 --0.0939 1.68 -0.097 -0.593 --1.8 -1.71 --1.49 0.415 --0.722 1.19 -0.407 -0.94 -0.463 -1.28 -0.185 0.261 -1.97 1.41 --0.246 -0.739 --0.889 -0.417 -1.19 0.554 --1.8 0.676 -0.291 1.34 --0.267 -0.896 --0.59 -0.328 -0.0885 -1.22 --1.42 0.624 -0.66 0.835 -2.43 1.31 -0.217 -0.961 --0.877 0.263 --0.899 0.0621 --0.141 -0.797 --0.784 1.81 -0.104 -1.04 --0.973 -0.126 --0.278 -1.09 --0.914 -0.522 -0.238 1.74 --1.84 0.0932 -1.64 1.53 --0.19 -1.42 --0.508 -1.7 -0.187 -1.02 -0.16 0.189 --1.71 -0.319 -0.793 0.836 -0.383 -0.824 --0.0697 1.56 --1.64 -1.05 --0.739 -0.066 -1.22 -1.46 -1.48 1.01 --0.876 0.232 -1.75 0.016 --0.048 -1.06 -0.316 -0.601 --1.87 -1 --0.769 -1.46 --1.53 0.656 -1.29 0.337 -0.403 0.0297 --1.31 -1.11 -1.31 -1.81 -0.617 -0.585 -0.713 0.948 -0.994 0.0734 --0.345 0.376 --0.84 -1.16 -0.515 2.21 -1.37 -0.8 --0.197 0.544 -0.913 -0.374 -1.18 -0.277 -0.834 -0.177 --0.874 0.719 -1.09 -0.384 --0.972 -1.08 --0.85 0.963 -1.21 0.306 -0.933 0.716 -1.66 0.243 -1.75 1.33 -1.58 0.206 -0.415 0.986 -0.0128 1.29 --1.45 -0.0461 -0.928 -0.102 -0.834 0.925 -0.824 -0.673 --0.0275 -0.582 -1.19 -1.67 -1.34 0.32 --0.0839 1 -2.42 1.5 -0.39 1.27 --0.341 0.0621 -0.265 -1.06 --1.78 -0.572 -0.2 -0.609 --1.51 0.348 -0.0311 -0.978 -0.586 0.402 --0.0264 -0.952 --1.19 1.23 --1.19 -1.32 --0.534 1.15 -0.418 0.616 -0.0194 -1.13 -0.83 -0.939 --1.37 -0.213 --0.652 -1.54 --0.453 -0.0737 --0.835 0.671 --3.09 -0.832 --0.598 -1.38 --0.0215 0.704 --0.00124 -0.938 --0.145 0.471 -0.633 0.901 --0.77 0.637 --0.756 -0.943 --1.02 0.968 --0.637 0.942 --0.0254 -0.79 --0.494 -1.22 -1.09 -0.643 -0.366 0.164 -0.595 0.677 --0.132 1.68 -1.32 0.376 -1.09 0.614 --0.26 1.36 --0.467 -0.945 --1.6 -0.0414 -1.23 -2.2 -1.93 1.41 -1.87 1.13 -0.785 -0.601 -1.8 0.757 --0.369 -1.14 --0.376 1.33 --1.43 0.245 --0.96 1.34 -1.22 0.423 -0.0951 -1.39 -0.439 -1.09 -0.886 -0.292 -1.22 0.834 -1.12 -1.72 --1.3 1.16 -0.675 0.667 -0.456 0.278 --0.815 1.18 -1.72 -0.259 --0.497 -1.29 --1.17 0.564 -0.0786 1.63 --0.64 -0.939 -0.264 -0.605 --0.222 0.156 -725e-6 -0.0366 -1.1 1.38 --0.865 -1.1 -1.32 -1.48 --1.51 0.481 -0.518 1.7 --0.845 -0.00258 -0.00273 -0.973 -0.635 0.559 -1.27 -0.685 -1.03 0.28 --0.964 0.108 --0.132 -1.37 --0.186 -0.0925 -0.0585 -0.378 --0.0876 0.255 --0.56 -1.12 -1.47 -2.05 -0.113 0.462 --0.0189 -1.28 -0.378 0.987 --1.32 0.516 --1.07 -0.306 -1.49 -0.886 --0.138 -1.37 --1.7 -1.16 -0.598 0.133 -1.74 0.577 -1.71 0.569 --0.973 0.107 --1.48 -0.297 -1.19 0.812 --0.607 -0.894 --1.02 -1.29 --1.31 -0.627 --1.02 0.521 -0.752 1.58 --0.0666 0.0656 -0.615 0.375 --0.142 1.65 -0.335 1.95 -1.22 0.247 --0.245 -1.18 -0.409 -1.51 --1.3 -1.08 -0.505 1.45 --1.19 -0.976 -0.388 0.484 -1.06 -0.453 --0.911 -0.908 -1.11 0.428 -0.903 -0.339 --0.815 0.334 -1.35 -0.387 -0.185 0.617 --1.96 -0.942 --1.08 -0.952 --1.67 -0.266 --0.856 -0.235 --0.918 1.44 -1.24 1.45 -1.41 -0.447 -0.177 0.731 -0.0886 -0.844 -0.604 0.555 --0.394 -0.253 -0.319 1.61 --0.808 -1.5 --0.44 0.298 --0.634 1.08 -0.0116 -1.09 --0.651 -0.103 -0.0605 2.06 --1.04 0.937 -2.62 1.12 --0.499 -0.241 --1.46 -0.108 -1.01 0.677 -0.627 0.234 --0.436 1.45 -0.0165 -0.639 -1.42 -0.656 --1.23 -1.3 -1.35 -0.177 -1.77 1.59 --1.79 -0.0728 --0.26 -1.23 --0.259 1.52 -1.27 -0.747 --2.07 -0.521 -0.477 1.83 --0.195 1.31 -1.22 1.04 --1.44 0.0919 --0.784 -0.00647 --1.55 0.121 --0.236 1.44 -1.24 -0.687 --2.84 -0.177 --0.767 -1.3 -1.14 0.376 -1.05 -0.723 -0.814 0.817 --1.26 -0.119 -1.41 1.63 -0.933 -1.24 --1.14 0.0337 -0.85 0.726 -0.624 0.621 -1.59 -0.0963 --1.8 -1.25 -0.00356 1.87 -0.178 -1.24 -1.18 0.334 -0.91 0.864 -0.145 -0.415 -1.26 -0.553 --0.187 -0.267 -0.769 0.855 --1.31 -1.16 -1.08 0.148 --1.25 0.857 --0.0656 1.24 --1.82 -0.705 -1.53 -1.81 --0.177 -1.12 --1.03 -0.357 --1.68 0.398 -0.389 -0.804 -0.272 -1.12 -0.846 1.87 --0.0686 1.72 --0.102 -1.31 -0.168 1.97 -0.538 -1.25 -0.677 0.108 -1.23 -0.146 -0.73 -0.99 -1.7 -0.0336 --0.968 0.348 -2.51 0.901 -0.643 -0.403 --0.877 -1.08 --0.975 -0.273 -0.321 0.393 --1.24 -0.0104 --0.509 -0.824 -0.0817 0.418 -1.95 0.902 -1.68 -0.32 --0.67 -0.55 --0.33 0.301 --0.736 0.683 -0.235 -1.06 --0.59 -1.23 -1.08 0.72 -0.527 -1.13 -0.71 1.7 -0.0243 -0.719 -0.207 0.65 -1.57 0.483 -1.02 -0.351 --0.21 0.171 -0.88 -0.241 --1.08 -0.868 --1.52 0.246 --0.834 -1.19 -1.29 0.23 -1.02 0.976 --0.241 0.774 --0.451 1.7 --0.506 -1.2 -1.35 0.657 --1.93 -0.315 -1.21 -0.774 -0.82 1.83 --2.05 -1.93 -1.3 0.739 -0.832 1.33 --0.959 0.41 -0.432 0.749 -2.12 0.978 -1.54 -0.193 --0.0454 1.75 --1.86 -1.3 -0.464 -0.792 --0.539 -1.39 -1.21 -0.873 -1.56 -0.177 -0.292 -0.159 -0.445 -1.38 -2.68 1.17 --0.463 0.0231 --0.951 1.39 -0.572 -0.812 --0.114 -0.147 -0.477 -1.24 --0.254 -1.27 --0.449 1.04 --0.311 -1.07 -0.566 -0.977 -1.47 0.486 -1.37 1.45 --0.543 762e-7 --1.4 0.261 --1.53 -0.466 -0.26 -0.54 -1.96 1.28 --0.707 -1.43 --2.1 -0.604 -0.721 0.731 --0.234 -0.974 -1.26 0.462 --0.527 0.887 -1.03 0.805 -0.276 -0.218 --1.07 -0.039 -1.35 -1.51 -0.507 1.02 -0.306 -1.13 --1.21 -0.392 --0.793 0.905 -0.204 -1.29 -1.39 -0.631 --0.218 -1.63 --1.34 0.626 --0.35 2.07 -0.021 -0.905 --0.614 -1.22 -0.753 0.781 -1.23 0.0999 -0.445 0.0484 --0.959 1.07 --0.204 -0.181 --2.18 -1.88 --0.474 0.264 -0.904 1.15 --0.876 0.92 -1.1 -0.313 -1.26 -1.03 -0.961 -1.33 --0.224 -1.02 --0.558 -1.73 --0.18 -0.639 -0.326 0.00626 -0.279 0.149 --1.43 0.0281 -0.449 -0.0489 -0.465 0.842 --0.49 1.25 -0.368 -0.856 --0.0242 -1.28 -0.42 2.1 --1.09 -0.463 --0.391 -0.547 -0.703 -0.583 --1.3 0.469 --1.44 -0.505 -1.01 0.865 -1.55 -0.649 -0.447 -1.18 --0.0433 0.605 --1.56 -0.329 --1.37 0.808 --0.448 -0.354 -1.53 0.368 --0.672 1.35 -0.883 0.598 -0.491 0.194 --0.11 -1.21 --0.436 1.86 -0.924 0.701 -1.24 0.908 --0.058 -0.904 -0.195 -1.27 -2 1.28 -0.562 0.172 -0.278 0.383 --0.711 0.465 --0.605 -1.52 -1.39 0.155 -0.38 -1.35 --1.07 -0.709 --0.958 0.812 --0.296 0.538 -0.952 0.836 -0.917 0.231 --1.72 0.142 --1.52 -0.368 --1.53 0.257 -1.38 -0.645 -0.102 -1.36 -1.45 -1.25 --1.12 0.589 -0.613 -0.0651 -2.44 -0.448 -1.33 -1.71 -0.289 1.01 --1.05 0.219 --0.405 -1.09 -0.819 0.546 -1.58 -0.468 -1.07 1.53 -0.434 0.295 --0.385 -0.734 -0.85 -0.829 --0.901 -1.68 --0.0677 1.74 -0.244 1.84 --1.84 -0.958 -1.21 0.00827 --1.13 -1.06 -0.0114 1.66 -1.89 -0.633 -0.367 -0.451 -0.344 0.908 --0.416 0.246 --0.716 -1.19 --1.07 -0.552 --1.94 0.832 -0.21 2.18 --0.932 -1.15 -0.23 -1.15 -1.55 1.1 -0.497 1.27 --0.599 1.44 -0.928 1.45 -1.38 1.25 --0.866 -0.197 --0.817 -0.783 -0.221 0.147 --0.314 -0.919 -0.802 0.852 -1.25 -1.38 -0.991 -1.1 --0.927 -0.595 -0.517 1.71 -0.952 -0.782 --0.215 -0.217 --0.207 -1.37 --0.223 1.65 --0.882 -0.726 --0.747 -0.509 -1.27 -0.519 -0.009 0.928 --1.17 0.586 -0.521 0.56 --1.01 0.768 -0.605 0.378 --0.582 -0.587 -0.125 -1.24 --0.471 -0.919 -1.4 0.541 -1.49 -1.53 -0.459 1.69 -0.183 -1.16 --0.104 0.48 --0.0541 -1.31 -0.728 0.752 --1.13 0.654 --0.265 1.71 --1.96 -0.442 -0.675 0.886 --1.76 -1.33 --1.92 -1.17 --1.42 -1.4 --0.39 -1.01 --0.634 1.21 --0.218 -1.05 -0.332 -0.527 -0.171 -0.502 --2.13 -1.85 -0.0273 -0.683 --0.0897 -0.115 -0.603 1.8 --0.0232 -1.24 --1.48 0.944 --0.0127 -1.12 --0.587 1.01 -0.163 -1.13 -0.93 0.65 -1.5 -0.0608 --0.0911 -0.0844 -1.64 -0.308 -0.404 -1.1 -1.37 1.24 --1.22 -0.107 --0.642 -1.35 --0.181 -1.1 --0.218 -0.882 --0.683 0.139 --0.305 1.18 --1.19 0.814 --0.758 0.794 -0.811 1.07 -1.45 -1.03 --0.169 -0.601 -0.462 1.89 --1.89 -1.16 --0.0199 -1.32 --0.396 -1.45 --1.08 0.89 -0.624 -0.285 --0.177 1.51 --0.437 -0.789 -1.22 1.48 --0.961 0.755 --1.64 0.572 -1.34 0.274 -1.16 -0.254 --0.38 -1.34 -0.918 1.72 --1.14 -0.927 --0.516 1.46 -0.188 1.59 --1.51 -0.27 -1.21 0.151 -1.05 -1.11 -0.385 -1.07 --0.139 -0.363 -0.953 -1.3 -0.725 1.33 -0.0966 -1.06 --0.347 -1.15 --0.0605 1.65 --1.88 -1.26 -0.484 -0.427 --0.618 -0.506 --0.121 -1.05 --0.169 -0.135 --1.28 -0.542 -1.62 -0.131 --0.446 -1.53 -1.16 -0.357 -0.298 -0.878 --1.46 1.11 --0.764 0.218 -0.901 -0.952 -0.955 0.142 --1.12 -1.17 --0.0845 1.15 --0.844 0.371 --1.43 0.0911 --0.978 -1.05 --0.899 -1.38 -0.942 1.83 -1.35 0.677 --0.678 1.6 --0.145 1.65 -1.35 -0.518 --1.54 -0.598 -1.12 1.14 --0.715 -1.49 --1 -0.885 --0.357 1.51 --0.859 1.26 -0.8 1.56 --1.53 0.795 -0.707 -0.778 --1.62 0.213 --0.836 -1.36 --1.84 -0.284 --0.685 0.727 -0.875 -1.47 --0.079 0.227 -0.731 1.74 --1.15 -0.659 --1.6 0.788 --0.114 0.846 --1.14 1.08 -0.143 0.845 -0.678 0.961 --0.397 0.563 --0.872 0.663 --0.262 1.71 --1.2 -1.4 -1.08 0.088 -0.523 -1.38 -1.23 -0.0874 -1.13 -1.75 --0.466 -0.851 --0.336 0.182 -1.04 0.0909 -0.553 -0.172 -0.134 -1.06 --0.882 -0.608 -1.24 0.441 --0.714 -1.65 -0.547 1.15 --1.47 0.96 -0.437 2.35 --0.539 0.292 -0.543 0.913 --1.34 -1.05 --0.326 0.0769 -0.843 0.634 -0.452 -0.204 -0.974 0.877 -1.97 0.041 -0.554 -0.454 --1.29 -0.264 --1.18 -0.898 -1.08 1.37 --1.04 -1.07 --0.325 0.969 -0.72 0.677 -0.803 0.349 --1.58 -0.798 -1.3 -0.346 -0.332 -0.69 --0.0128 -1.27 --1.83 0.379 --1.21 1 --0.76 -1.26 --0.665 1.61 -1.12 -0.447 --0.23 2 --0.176 -0.207 --1.75 -1.92 --0.599 1.25 -0.101 0.881 --0.298 -1.16 -1.01 0.257 --0.479 0.91 --0.428 -0.509 --1.74 0.367 -0.637 1.25 -0.00879 1.47 --0.302 -0.116 -0.157 0.956 --0.617 1.61 -0.934 0.32 --0.226 -1.45 --0.667 -0.895 --0.0337 -1.36 --0.0411 0.32 --1.78 -0.607 --0.495 1.31 --0.823 0.729 -0.916 -0.0255 -1.7 0.0023 --0.563 1.29 --0.995 -0.507 --1.39 -0.943 --1.75 -1.63 -0.742 0.744 --0.435 -1.53 -2.27 0.284 -0.175 -0.887 -1.17 1.37 --1.75 -1.27 --1.33 0.878 --0.238 1.74 -0.99 1.02 --1.9 0.856 --1.64 -1.16 --0.415 0.463 -0.435 0.397 --0.306 2.28 -0.569 1.15 -1.04 -1.17 --1.28 -1.12 --1.07 1.3 --0.211 -0.637 --0.104 -1.15 --0.0169 -0.939 --1.4 0.247 --0.897 -0.972 --1.68 -0.472 -0.655 1.72 --0.58 -0.579 -0.688 -0.878 -1.55 -0.00546 --2.25 0.167 -0.252 0.258 -1.54 -0.749 --1.5 0.0847 --0.851 -1.26 --0.403 -0.636 --0.138 -1.03 -1.94 1.25 --0.651 1.12 --0.562 -1.12 -1.66 -0.402 --1.31 0.239 --0.0113 -0.78 -0.0821 -0.398 --0.639 0.68 --1.49 -0.221 --0.006 -0.32 -0.782 -0.139 --1.33 0.897 --1.19 -0.774 -0.127 1.94 --1.29 -0.23 -0.76 -1.16 --0.992 -0.0156 --0.396 1.21 --0.665 -1.04 -1.24 -1.33 --0.22 -1.12 --1.54 0.562 --0.159 -0.12 -1.03 -0.805 --0.625 1.38 --1.79 -0.124 --0.0656 -1.57 -1.12 -0.908 --1.28 -0.259 --0.309 1.16 --0.625 -0.675 --0.752 -0.117 --1.1 0.322 -1.09 1.49 --0.867 0.214 -0.596 -0.172 --0.704 0.71 -0.672 1.57 -1.38 0.698 --1.34 0.54 -0.429 1.94 -0.381 1.61 -0.129 -0.889 --1.01 -0.0908 --0.651 -0.528 -0.0439 2.03 --2.37 -0.01 --0.553 -0.687 --1.47 -0.817 -1.36 -0.412 -1.92 0.0429 --0.673 -0.177 -1.32 0.218 -0.221 0.946 -1.05 0.899 -0.942 0.248 --1.7 -1.79 -0.359 1.52 --0.977 0.639 --1.02 -1.19 --0.496 1.41 -1.45 0.273 -1.16 -1.1 --0.878 -1.46 -0.983 0.203 -0.167 -0.793 --1.67 1.1 --1.28 -0.471 -1.1 0.74 -0.435 1.31 --1.41 -0.357 --0.00145 -0.7 -1.5 -0.993 --0.248 -1.69 --0.819 -1.21 -1.78 0.272 --1.04 1.13 --0.536 -0.814 --0.663 -1.47 -0.355 -0.222 -0.486 0.991 --1.33 -0.12 -0.975 -1.34 -0.431 1.64 --0.516 -0.92 -0.0479 -1.06 --1.04 -1.08 --0.767 -1.2 -0.613 1.35 --0.834 -0.258 -0.473 -1.11 --0.734 1.25 -2.2 1.14 --0.443 1.02 --0.568 -0.873 --0.452 -0.717 -0.14 1.25 -1.22 0.325 -2.18 1.13 -1.52 0.315 --0.276 -1.19 --0.29 0.7 --1.22 0.177 -0.799 -0.99 --0.0163 -1.07 -1.51 -0.355 -0.431 -1.46 --0.264 -1.14 -1.14 0.607 --0.508 -0.694 -1.53 0.228 -2.07 1.37 -1.78 1.01 --0.0175 -1.21 --0.295 -1.27 --0.743 0.685 -0.405 -1.2 -0.351 -0.964 -0.192 1.94 --0.867 1.09 -1.21 0.752 -0.545 1.28 -0.985 0.114 --0.544 -0.831 -1.12 0.293 --1.44 -0.47 --0.077 1.87 --0.956 1.11 -1.35 -0.962 -0.234 -0.413 --0.861 -1.21 -0.599 1.14 --1.38 -0.826 --1.37 0.928 -0.395 1.21 -1.01 -0.437 -1.1 -1.17 -0.999 -1.12 --0.381 -0.917 -0.817 -0.941 -0.184 0.558 --0.334 -1.34 -0.974 -1.32 -0.655 1.14 --0.209 -0.356 --0.511 1.53 --0.891 -0.617 -0.0545 -1.32 -0.545 -0.165 -1.29 0.488 -0.364 -0.269 --1.11 0.308 --0.421 -1.09 -0.849 0.907 --1.17 1.08 -0.629 -0.617 -0.424 0.0533 -0.179 1.87 -1.36 -0.117 -1.02 0.729 -0.252 -0.389 --0.549 1.03 -1.27 0.775 --0.0192 -1.03 --1.31 0.0708 --0.719 0.242 --0.633 0.257 --0.491 -1.55 --1.84 -0.366 --0.457 -0.983 --0.565 -0.0822 -0.401 -1.31 --0.561 -0.787 --1.74 0.697 -0.745 0.877 -0.617 1.34 --1.77 -1.19 -1.88 0.325 -1.09 0.155 -0.0899 -1.09 -0.229 0.613 -1.05 -0.655 --1.15 -0.545 --0.555 0.908 -1.45 0.211 -0.132 -1.49 -1 0.654 --0.487 -0.797 -0.643 -0.351 --0.0744 -0.463 --0.0476 -1.24 -0.478 0.46 --0.398 -1.28 -0.335 1.15 --0.397 -1.1 -0.625 1.38 --0.648 -0.713 --0.4 -1.15 -0.762 -0.334 -0.137 1.94 --0.726 -1.17 --1.13 1.01 -1.34 -0.632 --0.0261 -1.38 --1.21 -1.22 -1.55 0.482 --0.794 1.24 -0.517 1.46 --0.865 1.6 --1.57 -0.561 -0.329 0.606 -0.497 2.23 --0.529 0.365 --1.82 0.474 -0.948 0.985 --0.488 -1.31 -1.46 -1.06 --1.67 0.88 -2.4 1.2 -1.57 -0.909 --0.144 1.68 -0.123 -0.283 --1.23 -0.977 --1.69 0.614 -1.71 -0.945 --0.135 -1.1 --1.35 -0.57 --0.0117 -1.34 -1.31 0.151 -0.983 0.611 --1.52 -0.00335 -0.976 1.24 -0.0271 1.83 --1.4 0.98 --0.45 -0.928 --2.09 0.604 -0.455 0.877 -0.193 1.72 --0.304 1.5 --1.98 -0.655 --0.0237 -1 --0.184 -1.4 -0.458 -0.157 --1.45 -1.22 --0.152 -1.11 --0.0208 1.76 -1.31 0.208 --1.06 -1.54 --1.24 0.1 -0.715 1.3 --1.77 -0.455 -0.75 1.63 -1.12 0.422 -1.88 -1.13 -0.894 -0.742 -0.756 -0.0709 --0.734 0.881 -0.301 -1.29 -0.426 0.194 --1.93 0.96 -0.258 0.482 -0.272 -1.6 -0.194 -1.27 --2.28 -1.02 --1.55 -0.61 --1.36 -0.324 -0.869 0.576 -1.59 -0.111 --0.424 0.0207 -0.621 1.32 --0.0367 -0.144 -0.735 0.932 -1.74 0.195 --0.482 0.0903 --0.201 1.35 --0.0882 1.17 -0.831 1.35 -0.762 0.344 -0.777 0.312 -0.813 1.06 --0.507 1.89 -0.163 -1.08 --0.9 0.858 -1.88 -0.289 -0.273 1.79 -1.47 -0.531 --0.814 0.23 --0.422 -0.241 -0.996 1.46 -0.0432 -1.39 -0.591 -0.427 --0.698 -0.726 --0.536 1.19 --0.53 0.101 -0.494 1.18 --0.305 0.194 -0.0878 -1.08 --0.752 0.342 -0.135 0.0532 --0.0461 1.65 -1.29 0.0437 --0.534 -1.23 --0.269 1.37 --0.803 -1.09 -0.915 1.15 -0.676 0.925 -1.28 0.373 --0.699 -0.359 --0.222 0.259 --1.6 -1.44 --0.665 0.357 --0.615 -0.97 -0.938 -0.255 --0.926 0.916 --0.854 -0.379 --0.611 -1.28 --1.01 0.357 --1.19 1.14 --0.728 -0.76 --0.768 -0.909 --0.173 1.59 -0.229 1.63 -0.513 0.741 --0.0773 -1.22 --0.114 -1.5 --1.3 0.651 -0.5 0.762 --1.15 -0.562 -0.884 -0.766 --0.83 -1.08 --1.6 -1.32 -0.781 0.911 --1.32 0.0399 -0.673 2.52 --0.855 1.22 -0.0893 -1.1 --1.52 -0.993 --0.355 1.28 -0.273 -1.45 --1.27 -0.688 -0.157 -0.652 --1.18 1.17 --0.736 -1.14 -0.603 0.145 -0.722 0.368 --0.38 -1.27 -1.66 -0.384 --0.118 -1.26 -0.689 -0.187 --0.886 -1.27 --1.47 0.52 -1.07 0.668 --1.94 -0.761 -0.41 1.01 --0.78 -1.37 -0.344 1.38 -0.22 -1.36 --0.621 1.11 -0.707 1.37 -0.196 1.76 -0.44 -0.936 -1.37 0.219 -0.284 1.86 -1.45 0.169 -0.941 1.46 --0.275 -1.6 --1.5 0.282 -0.121 0.219 --1.87 0.373 --1.51 -0.626 -1.41 0.319 -0.919 0.798 -0.533 1.76 -0.845 0.00714 --0.203 1.26 --0.52 1.35 --0.0696 -0.896 --0.914 0.317 --0.688 -1.14 -1.07 0.399 --0.411 -1.34 -0.924 0.861 --0.901 -1.13 -1.55 -0.0305 -1.15 0.565 --0.572 1.16 -0.155 1.88 -1.43 -0.816 --0.858 -1.2 --0.0652 0.631 -0.16 -0.616 --1.53 0.501 --1.45 -1.14 --0.113 2.13 --0.241 -0.374 --0.49 -1.45 --0.861 -0.972 -1.14 0.212 --0.44 -1.3 --0.98 -1.49 --1.69 -0.176 -0.84 1.42 --0.972 0.473 --0.668 0.919 -0.732 0.493 -0.535 1.46 --1.4 -0.183 -1.26 0.305 --0.996 -0.984 --0.534 -1.4 -0.733 0.926 -0.587 0.0331 -0.0125 -0.665 -0.835 1.24 --0.942 -1.15 -0.0368 -0.239 -1.5 1.5 --0.744 -1.39 --0.472 0.267 -0.304 1.61 --0.0439 0.305 --1.96 -1.09 -1.31 0.17 --1.78 -0.253 --1.21 0.918 -0.457 0.191 -0.998 0.37 -0.513 1.5 --0.714 -0.161 -0.0722 1.8 -1.33 -0.0673 -0.508 -0.331 -0.862 -1.24 -0.65 1.86 -1.74 -0.143 -0.417 -1.54 -0.466 0.281 -1.73 0.979 --0.314 -0.72 -0.0981 0.465 --1.08 1.01 -2.37 1.07 -0.143 -0.786 -0.032 -1.5 -0.739 2.14 -0.396 1.81 -0.538 1.38 -0.0325 -1.46 --0.391 1.32 --0.695 1.08 --1.84 -0.846 --0.824 1.1 -1.16 -1.24 -0.7 1.14 --0.17 1.18 --0.0932 0.472 -0.164 -1.18 -0.443 1.54 --1.22 0.0836 --0.188 -1.27 -0.109 -0.522 -1.62 1.19 --0.853 0.358 --1.69 -1.14 -0.725 -0.99 -0.25 -1.1 --1.22 0.569 -0.627 0.125 --0.0699 -1.2 -0.594 1.8 --0.901 -1.56 -1.02 0.0975 --0.149 -0.0185 --0.226 -1.09 -1.11 0.685 --0.301 1.69 -0.471 -0.445 --0.827 1.23 --0.672 -0.0414 -0.606 -0.877 --0.64 0.705 -0.14 -0.8 -0.425 -1.21 -0.966 -0.199 -1.06 0.629 -0.839 -1.15 -0.379 1.74 -0.603 -1 --0.463 -1.2 -1.18 1.42 -1.09 -1.12 -0.9 -1.36 -1.11 -1.1 -1.46 -0.111 -0.242 0.347 -0.669 0.98 --1.2 -0.826 --1.13 0.928 --0.799 1.11 --0.108 1.7 --1.18 0.692 --0.787 -0.113 --0.412 -0.689 --0.452 0.524 -0.29 -0.515 --0.518 -0.914 --1.1 0.419 -1.34 1.44 --1.46 0.594 --0.613 1.1 -1.5 0.0442 -1.34 -0.0272 --0.146 -0.869 -0.0726 -1.31 --0.198 -0.661 --0.0776 -1.35 --1.22 -0.68 -1.17 0.407 -1.34 0.0998 -1.25 -1.25 -0.712 1.49 --0.516 -0.915 --1.63 0.728 --0.514 -1.21 -1.12 0.822 --0.076 -1.12 --0.678 -0.417 --0.897 -1.04 -1.12 0.375 --1.94 -1.61 --0.756 -0.679 -0.825 -1.28 -1.8 0.0607 -0.108 -1.21 -2.18 1.21 -0.634 0.366 -1.26 0.799 --0.702 -0.811 --0.336 -0.0523 --0.729 1.5 -1.3 0.749 -0.283 0.394 -0.247 1.65 -0.212 1.81 -1.08 -0.628 --0.852 -0.298 --1.77 -0.592 --0.251 0.327 -0.417 -1.28 --0.12 -1.22 --2.19 -1.3 -2.11 0.942 --0.214 -0.235 -1.05 0.219 --0.863 0.174 -0.244 1.42 -0.0725 0.596 --1.34 0.869 --0.0874 -1.07 --0.452 -1.22 -0.973 0.653 -0.911 -0.832 -0.303 -0.94 -0.282 -0.761 -1.7 -0.554 -0.659 1.28 --0.192 0.791 -0.424 1.64 --0.59 -1.04 -2.04 1.36 --1.11 -0.351 --1.86 -1.78 --1.12 -0.315 --0.932 -1.02 -1.71 -0.424 -0.726 -0.626 --1.46 0.657 --0.347 -1.13 --1.21 -1.16 -0.541 1.41 -0.334 1.04 -1.31 0.118 -0.673 0.172 -1.14 0.866 --0.372 -1.11 -1.29 0.644 -1.26 -1.25 -0.408 -0.664 -0.339 0.881 -0.00275 -0.0555 --0.836 -0.65 -0.838 1.5 --1.4 -1.54 -0.786 1.31 --0.88 0.407 -0.987 0.258 -1.86 -0.213 --1.53 0.679 --1.12 0.699 --1.19 -0.328 -0.829 -0.305 -1.16 0.847 --0.434 -1.1 --0.177 -1.45 --0.131 1.76 -1.19 0.309 -0.189 1.35 -0.0963 -1.38 --0.989 0.48 --0.532 0.181 -0.704 -0.91 --0.301 1.82 -0.0561 -0.479 -1.13 -1.27 --0.206 -1.15 --0.413 1.17 --1.21 -0.854 -1.01 0.555 -0.879 1.03 -0.724 0.706 --2.03 -1.23 -0.414 0.141 -0.466 0.322 -1.44 0.276 -0.97 1.15 -1.1 1.58 -0.719 0.759 -1.07 0.512 --0.753 -1.08 --0.451 1.72 --1.24 -0.706 -0.179 -1.04 -0.214 -0.45 -0.364 -0.858 --1.04 -0.131 -0.273 1.68 -1.19 0.289 --0.436 -0.954 --0.403 -0.488 --0.8 1.66 -0.00854 1.31 -1.47 -1.44 -1.13 1.07 --1.1 0.737 --0.711 0.96 -1.81 -0.551 --0.381 -1.08 -2 1.71 --1.34 0.824 --0.184 -0.751 -0.608 -1.18 -0.957 -0.572 --0.243 -1.24 -0.914 0.26 -0.701 0.564 -1.35 1.33 -0.387 -0.798 --1.02 -1.43 -1.71 1.17 --0.178 -0.551 --0.434 -1.16 -0.512 -0.49 --0.434 2.24 --2.17 -0.523 -1.18 0.766 --0.00948 -0.336 -0.142 -0.698 --1.28 0.559 --1.01 -0.363 --1.74 0.975 -1.34 -1.07 -1.28 1.35 --0.274 -0.99 -1.39 0.0609 --1.36 0.976 -0.99 0.771 --1.82 -0.341 -0.423 1.74 -1.42 -0.208 --0.261 0.204 --1.69 0.706 --1.24 -0.497 --0.074 1.97 -1.4 -1.13 -0.411 1.47 --1.51 -0.285 -1.12 -1.22 --0.652 1.14 -0.608 0.0135 -0.0285 1.72 --0.315 -1.09 -0.222 1.47 --0.376 -0.975 --0.356 -0.0513 --0.42 1.11 --1.17 -0.073 --0.816 0.562 -1.02 0.44 --0.828 -0.82 --0.183 1.15 --0.768 0.209 --0.101 -0.122 --1.55 0.378 --0.825 0.481 -1.23 -1.55 -1.61 -0.387 --0.785 -0.361 --1.53 -1.01 -0.327 0.17 -1.35 -1.23 --1.04 0.621 -0.424 0.471 --0.0567 -1.41 -1.63 0.0545 --0.522 0.877 --0.391 1.03 --1.54 -0.641 -0.0114 -1.46 -1.16 0.151 --0.17 -0.346 -0.809 0.942 -0.602 1.06 --0.879 0.499 -1.18 0.507 --1.06 -0.937 -2.37 1.14 --1.42 0.592 -1.88 0.116 --1.06 0.817 -0.809 0.741 -1.22 0.217 -0.612 1.8 -1.25 -0.146 -1.28 -0.236 --0.298 -1.26 -0.93 -0.375 --0.626 -1.18 --0.102 1.57 --0.918 -0.578 -1.01 1.53 -0.805 0.42 --0.958 0.536 --0.051 -0.972 --0.0443 -0.335 -0.822 0.501 --0.337 1.66 --0.957 0.039 --0.0406 2.09 --0.266 -1.2 --0.216 -0.353 --1.33 -0.861 --1.87 -1.32 --1.1 0.817 -0.568 0.244 --0.672 -0.601 -0.847 1.4 --0.125 -1.48 -0.504 0.0752 -0.257 0.154 --0.269 1.6 -0.29 -0.481 --2.06 0.392 --1.14 0.849 --1.54 0.516 -1.55 -0.466 -0.209 0.755 --1.66 -0.56 -0.299 1.56 --0.418 -1.26 --0.0554 -1.28 --1.1 0.641 --0.016 -0.448 -0.463 0.498 --1.56 -1.1 -0.287 -1.45 --1.03 1.01 -0.826 0.84 --1.31 -0.354 --0.634 -1.15 -1.26 0.144 --0.162 1.84 --0.532 0.978 -0.527 -1.02 --0.208 -0.646 --0.58 -1.09 --0.071 1.63 --0.622 0.804 --0.25 -1.23 -0.504 1.78 -2.29 1.22 -0.625 1.67 --0.165 -0.697 --0.317 1.77 -0.309 -0.689 -1.14 0.647 --1.37 -0.177 --0.988 -0.191 --0.0273 0.739 -0.611 0.978 --1.89 -1.7 --0.936 1.81 -1.25 0.794 --1.34 0.595 -0.469 1.91 --1.57 0.629 --1.61 -0.451 --1.81 -0.488 -1.08 -0.996 -0.445 0.135 -0.764 0.469 -0.369 0.428 --0.367 -1.04 --0.139 0.132 --0.987 -0.863 --1.54 0.503 -0.434 -0.189 --1.57 -1.47 -1.62 -0.0187 -0.659 -0.985 -0.196 1.27 --1.42 -0.327 -1.82 1.43 --0.487 -0.536 -0.235 1.48 -1.38 0.131 --1.44 -0.0746 --0.163 -0.398 -1.25 -0.322 -1.33 -0.0802 --0.18 0.595 --1.29 -0.754 -0.409 1.45 --1.45 -1.25 --1.32 0.995 -1.02 -0.728 -1.72 0.0291 --1.78 -0.687 --0.966 -0.628 --1.57 0.378 -1.12 -0.659 -0.0235 -0.18 --1.17 0.156 --0.105 -0.442 --0.256 -0.115 -0.414 1.16 -0.617 -0.0096 --1.37 0.648 -0.774 0.617 -2.29 1.32 -0.501 0.0553 -0.981 0.532 -0.141 0.0947 -0.0436 0.0126 --1.84 -1.64 --1.22 -0.119 --1.16 0.41 -1.25 -0.00263 -1.03 1.29 -0.773 -0.747 --0.0297 -1.58 -0.217 -1.21 --1.06 1.03 --1.93 -0.92 -0.598 0.855 --1.69 -1.27 -0.822 0.192 --0.539 1.41 -0.00168 0.262 --0.742 -1.02 --1.31 -0.903 -0.878 -1.38 -0.465 -1.26 --1.11 -0.821 -2.41 1.26 --1.56 -0.172 --0.855 -1.05 -519e-6 0.282 --1.88 -0.979 --0.895 -1.07 -0.235 0.772 -1.87 -1.16 -0.735 1.63 -0.0737 0.124 --0.337 1.85 --0.2 1.74 -1.2 -0.213 -0.382 0.175 -1.03 -0.191 --0.739 1.32 -0.952 0.616 --1.57 -0.205 -0.774 -1.22 -1.21 -1.24 -1.1 0.131 -0.397 0.513 -1.07 -1.38 --1.37 -0.205 --0.33 0.0829 --0.718 -1.25 --0.676 1.3 -0.434 2.19 --0.882 -0.582 -1.16 -0.768 -0.572 -1.24 --0.757 0.298 -0.67 1.15 -0.0301 -0.894 -1.22 1.35 --0.685 0.989 --0.377 -0.617 -0.13 1.41 --1.09 1.39 -1.15 -1.14 -0.648 1.41 -0.981 0.0921 -0.318 1.4 --0.501 0.0787 --1.12 0.494 --1.81 -0.994 --0.748 -0.034 -0.544 1.41 --0.944 1.02 --0.533 1.22 --0.446 -1.28 -0.498 -1.02 --0.954 -1.19 -1.65 0.0404 --2.03 0.359 --0.235 -1.22 -0.627 -0.0629 --1.93 0.525 -2.35 1.14 -0.233 -0.275 --0.781 -0.113 --0.327 0.612 --1.41 1.09 -0.0489 -1.36 -0.253 -1.3 --1.25 -0.656 --1.59 0.322 -1.99 1.18 -2.2 1.26 --0.172 -1.31 -0.276 0.397 -0.949 0.422 -1.06 0.842 -1.98 1.27 --0.279 -0.0928 -0.275 1.18 --0.318 0.317 --1.32 -0.088 --0.695 -0.736 -0.916 1.63 -0.974 0.512 --0.567 -1.7 -1.38 0.749 -0.521 -1.04 -1.13 0.429 --0.511 1.5 -1.46 -0.91 -1.67 0.0877 --0.965 -0.978 --2 -1.72 --1.43 -1.02 -0.739 0.139 -0.369 0.49 --1.64 -1.8 --1.31 -0.498 -0.44 0.9 --1.59 -1.36 --0.724 0.215 -1.33 1.43 --0.91 -0.607 -1.19 0.997 --0.914 0.425 -1.11 0.375 --1.46 -0.298 --0.328 0.232 -0.941 -0.789 --1.82 0.885 -0.0949 -1.56 -0.874 -0.769 --0.967 0.592 -0.803 1.35 --0.521 0.726 --0.76 -0.698 --2.25 -1.96 --0.749 0.0101 --0.00626 -0.959 -1.01 -0.984 -0.198 -1.19 -0.544 1.63 --0.213 0.259 --0.729 1.37 -0.112 0.0285 --0.968 -0.912 --0.566 -1.33 --0.271 1.59 -1.56 -0.367 -0.897 1.07 -1.39 -0.498 -0.0968 -0.225 -0.374 0.966 --0.791 -1.26 -0.615 0.558 --0.391 0.181 --0.153 -1.2 -0.298 0.509 -0.557 -1.04 --0.109 -1.07 -0.412 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Process Classification +# # ## Preliminary steps - +# # ### Loading necessary packages using Plots diff --git a/docs/examples/gpevents.jl b/docs/examples/gpevents.jl index 1bde7566..ddbfc1c1 100644 --- a/docs/examples/gpevents.jl +++ b/docs/examples/gpevents.jl @@ -1,3 +1,8 @@ +# # Gaussian Process for Event likelihoods +# +# ## Preliminary steps +# +# ### Loading necessary packages using Plots using AugmentedGaussianProcesses const AGP = AugmentedGaussianProcesses diff --git a/docs/examples/gpregression.jl b/docs/examples/gpregression.jl index ae039057..25be8b6d 100644 --- a/docs/examples/gpregression.jl +++ b/docs/examples/gpregression.jl @@ -1,8 +1,5 @@ -# # Gaussian Process Regression +# # Gaussian Process Regression (for large data) # -#md # [![](https://mybinder.org/badge_logo.svg)](@__BINDER_ROOT_URL__/examples/gpregression.ipynb) -#md # [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/examples/gpregression.ipynb) - # ### Loading necessary packages using AugmentedGaussianProcesses const AGP = AugmentedGaussianProcesses diff --git a/docs/examples/multiclassgp.jl b/docs/examples/multiclassgp.jl index 17e6e3b3..c67a0f07 100644 --- a/docs/examples/multiclassgp.jl +++ b/docs/examples/multiclassgp.jl @@ -1,4 +1,9 @@ -# ## Data generation +# # Gaussian Process Multi-Class Classification +# +# ## Preliminary steps +# +# ### Loading necessary packages +# ## Data generation and setting up packages using Plots using Distributions using AugmentedGaussianProcesses diff --git a/docs/examples/onlinegp.jl b/docs/examples/onlinegp.jl index 0ad551c9..70b7f14f 100644 --- a/docs/examples/onlinegp.jl +++ b/docs/examples/onlinegp.jl @@ -1,3 +1,6 @@ +# # Online Gaussian Process +# +# ### Loading necessary packages # ## Preliminary steps # ### Load the necessary packages using Plots @@ -39,3 +42,4 @@ for (i, (X_batch, y_batch)) in enumerate(eachbatch((X_train, y_train); obsdim=1, frame(anim) end gif(anim; fps=4) +# This works just as well with any likelihood! Just try it out! diff --git a/docs/examples/sampling.jl b/docs/examples/sampling.jl new file mode 100644 index 00000000..413338a1 --- /dev/null +++ b/docs/examples/sampling.jl @@ -0,0 +1,66 @@ +# # Sampling from a GP +# +# ## Preliminary steps + +# ### Loading necessary packages + +using Plots +using AugmentedGaussianProcesses +using Distributions +using LinearAlgebra + +# ### Loading the banana dataset from OpenML +kernel = SqExponentialKernel() +x = range(0, 10, length=50) +K = kernelmatrix(kernel, x) +f = rand(MvNormal(K + 1e-8I)) # Sample a random GP +y = rand.(Bernoulli.(AGP.logistic.(f))) +y_sign = sign.(y .- 0.5) + + +# ### We create a function to visualize the data + +function plot_data(x, y; size=(300,500)) + Plots.scatter(x, + y, + alpha=0.2, + markerstrokewidth=0.0, + lab="", + size=size + ) +end +plot_data(x, y; size = (500, 500)) + +# ### Run the variational gaussian process approximation +@info "Running full model" +mfull = VGP(x, y_sign, + kernel, + LogisticLikelihood(), + AnalyticVI(), + optimiser = false + ) +@time train!(mfull, 5) + +# ### We can also create a sampling based model +@info "Sampling from model" +mmcmc = MCGP(x, y, + kernel, + LogisticLikelihood(), + GibbsSampling(), + optimiser = false + ) +m = mmcmc +@time samples = sample(mmcmc, 1000) + +# ### We can now visualize the results of both models + +# ### We first plot the latent function f (truth, the VI estimate, the samples) +p1 = plot(x, f, label="true f") +plot!(x, samples, label="", color=:black, alpha=0.02, lab="") +plot!(x, mean(mfull[1]), ribbon=sqrt.(var(mfull[1])), label="VI") +# ### And we can also plot the predictions vs the data +p2 = plot_data(x, y; size=(600,400)) +μ_vi, σ_vi = proba_y(mfull, x) +plot!(x, μ_vi; ribbon=σ_vi, label="VI") +μ_mcmc, σ_mcmc = proba_y(mmcmc, x) +plot!(x, μ_mcmc; ribbon=σ_mcmc, label="MCMC") \ No newline at end of file diff --git a/docs/make.jl b/docs/make.jl index 4ecff26a..ee084a84 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,84 +1,50 @@ using Documenter, Literate using AugmentedGaussianProcesses -# Create the notebooks - -# Regression -Literate.markdown( - joinpath(@__DIR__, "examples", "gpregression.jl"), - joinpath(@__DIR__, "src", "examples"); - documenter=true, -) -Literate.notebook( - joinpath(@__DIR__, "examples", "gpregression.jl"), joinpath(@__DIR__, "notebooks") -) - -# Classification -Literate.markdown( - joinpath(@__DIR__, "examples", "gpclassification.jl"), - joinpath(@__DIR__, "src", "examples"); - documenter=true, -) -Literate.notebook( - joinpath(@__DIR__, "examples", "gpclassification.jl"), - joinpath(@__DIR__, "src", "examples"), -) - -# Multi-Class Classification -Literate.markdown( - joinpath(@__DIR__, "examples", "multiclassgp.jl"), - joinpath(@__DIR__, "src", "examples"); - documenter=true, -) -Literate.notebook( - joinpath(@__DIR__, "examples", "multiclassgp.jl"), joinpath(@__DIR__, "src", "examples") -) - -# Online GP -Literate.markdown( - joinpath(@__DIR__, "examples", "onlinegp.jl"), - joinpath(@__DIR__, "src", "examples"); - documenter=true, -) -Literate.notebook( - joinpath(@__DIR__, "examples", "onlinegp.jl"), joinpath(@__DIR__, "src", "examples") -) - -# Events GP -Literate.markdown( - joinpath(@__DIR__, "examples", "gpevents.jl"), - joinpath(@__DIR__, "src", "examples"); - documenter=true, -) -Literate.notebook( - joinpath(@__DIR__, "examples", "gpevents.jl"), joinpath(@__DIR__, "src", "examples") -) +# Create the notebooks and examples markdown using Literate + +EXAMPLES = joinpath(@__DIR__, "examples") +MD_OUTPUT = joinpath(@__DIR__, "src", "examples") +NB_OUTPUT = joinpath(@__DIR__, "src", "examples", "notebooks") + +ispath(MD_OUTPUT) && rm(MD_OUTPUT; recursive=true) +ispath(NB_OUTPUT) && rm(NB_OUTPUT; recursive=true) + +# add links to binder and nbviewer below the first heading of level 1 +function preprocess(content) + sub = s""" +\0 +# +# [![](https://img.shields.io/badge/show-nbviewer-579ACA.svg)](@__NBVIEWER_ROOT_URL__/examples/notebooks/@__NAME__.ipynb) +""" + return replace(content, r"^# # .*$"m => sub; count=1) +end + +for file in readdir(EXAMPLES; join=true) + endswith(file, ".jl") || continue + Literate.markdown(file, MD_OUTPUT; documenter=true, preprocess=preprocess) + Literate.notebook(file, NB_OUTPUT; documenter=true) +end # Make the docs -makedocs(; - modules=[AugmentedGaussianProcesses], - format=Documenter.Writers.HTMLWriter.HTML(; - assets=["assets/icon.ico"], analytics="UA-129106538-2" - ), - sitename="AugmentedGaussianProcesses", - authors="Théo Galy-Fajou", - pages=[ - "Home" => "index.md", - "Background" => "background.md", - "User Guide" => "userguide.md", - "Kernels" => "kernel.md", - "Examples" => [ - "GP Regression" => "examples/gpregression.md", - "GP Classification" => "examples/gpclassification.md", - "Multi-Class GP" => "examples/multiclassgp.md", - "Online GP" => "examples/onlinegp.md", - "GP with event data" => "examples/gpevents.md", - ], - "Julia GP Packages" => "comparison.md", - "API" => "api.md", - ], -) +makedocs(modules = [AugmentedGaussianProcesses], + format = Documenter.Writers.HTMLWriter.HTML( + assets = ["assets/icon.ico"], + analytics = "UA-129106538-2", + ), + sitename= "AugmentedGaussianProcesses", + authors = "Théo Galy-Fajou", + pages = [ + "Home" => "index.md", + "Background" => "background.md", + "User Guide" => "userguide.md", + "Kernels" => "kernel.md", + "Examples" => joinpath.("examples", filter(x -> endswith(x, ".md"), readdir(MD_OUTPUT))), + "Julia GP Packages" => "comparison.md", + "API" => "api.md" + ] + ) # Deploy the docs diff --git a/docs/notebooks/gpregression.ipynb b/docs/notebooks/gpregression.ipynb deleted file mode 100644 index 8ca4910e..00000000 --- a/docs/notebooks/gpregression.ipynb +++ /dev/null @@ -1,24306 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# Regression with a Gaussian Likelihood" - ], - "metadata": {} - }, - { - "cell_type": "markdown", - "source": [ - "## Use necessary packages" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "Plots.PyPlotBackend()" - }, - "metadata": {}, - "execution_count": 1 - } - ], - "cell_type": "code", - "source": [ - "using AugmentedGaussianProcesses\n", - "const AGP = AugmentedGaussianProcesses\n", - "using Distributions\n", - "using Plots; pyplot()" - ], - "metadata": {}, - "execution_count": 1 - }, - { - "cell_type": "markdown", - "source": [ - "We create a toy dataset with X ∈ [-20, 20] and y = 5 * sinc(X)" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "1000-element Array{Float64,1}:\n -0.013647427263629499\n -0.02522464730477865\n -0.006097733819367183\n -0.04265185909502786\n -0.0472070022685936\n -0.08389923923038557\n -0.06344795789101988\n -0.07861783652203101\n -0.09345782383299713\n -0.08510143742153307\n ⋮\n -0.057299891369975826\n -0.056787884872071565\n -0.05493063978152045\n -0.0632415614938504\n -0.04088400119765528\n -0.03550436773797571\n -0.026494709510348005\n -0.011358536669455915\n -0.00841747089839347" - }, - "metadata": {}, - "execution_count": 2 - } - ], - "cell_type": "code", - "source": [ - "N = 1000\n", - "X = reshape((sort(rand(N)) .- 0.5) * 40.0, N, 1)\n", - "σ = 0.01\n", - "\n", - "function latent(x)\n", - " 5.0 * sinc.(x)\n", - "end\n", - "Y = vec(latent(X) + σ * randn(N))" - ], - "metadata": {}, - "execution_count": 2 - }, - { - "cell_type": "markdown", - "source": [ - "Visualization of the data :" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "Plot{Plots.PyPlotBackend() n=1}", - "image/png": 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"source": [ - "Run sparse classification with an increasing number of inducing points" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "5-element Array{Int64,1}:\n 4\n 8\n 16\n 32\n 64" - }, - "metadata": {}, - "execution_count": 4 - } - ], - "cell_type": "code", - "source": [ - "Ms = [4, 8, 16, 32, 64]" - ], - "metadata": {}, - "execution_count": 4 - }, - { - "cell_type": "markdown", - "source": [ - "Create an empty array of GPs" - ], - "metadata": {} - }, - { - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "┌ Info: Training with 4 points\n", - "└ @ Main.##803 string:4\n", - " 1.101748 seconds (2.18 M allocations: 137.147 MiB)\n", - "┌ Info: Training with 8 points\n", - "└ @ Main.##803 string:4\n", - " 0.062053 seconds (17.22 k allocations: 60.749 MiB)\n", - "┌ Info: Training with 16 points\n", - "└ @ Main.##803 string:4\n", - " 0.118101 seconds (17.22 k allocations: 111.759 MiB)\n", - "┌ Info: Training with 32 points\n", - "└ @ Main.##803 string:4\n", - " 0.460034 seconds (17.23 k allocations: 218.390 MiB, 48.04% gc time)\n", - "┌ Info: Training with 64 points\n", - "└ @ Main.##803 string:4\n", - " 0.535430 seconds (18.81 k allocations: 450.235 MiB)\n" - ] - } - ], - "cell_type": "code", - "source": [ - "models = Vector{AbstractGP}(undef,length(Ms) + 1)\n", - "kernel = SqExponentialKernel()# + PeriodicKernel()\n", - "for (index, num_inducing) in enumerate(Ms)\n", - " @info \"Training with $(num_inducing) points\"\n", - " m = SVGP(X, Y, # First arguments are the input and output\n", - " kernel, # Kernel\n", - " GaussianLikelihood(σ), # Likelihood used\n", - " AnalyticVI(), # Inference usede to solve the problem\n", - " num_inducing; # Number of inducing points used\n", - " optimiser = false, # Keep kernel parameters fixed\n", - " Zoptimiser = false, # Keep inducing points locations fixed\n", - " )\n", - " @time train!(m, 100) # Train the model for 100 iterations\n", - " models[index] = m # Save the model in the array\n", - "end" - ], - "metadata": {}, - "execution_count": 5 - }, - { - "cell_type": "markdown", - "source": [ - "Train the model without any inducing points (no approximation)" - ], - "metadata": {} - }, - { - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "┌ Info: Training with full model\n", - "└ @ Main.##803 string:1\n", - " 0.738615 seconds (232.94 k allocations: 286.849 MiB)\n" - ] - } - ], - "cell_type": "code", - "source": [ - "@info \"Training with full model\"\n", - "mfull = GP(X, Y, kernel,\n", - " noise = σ,\n", - " opt_noise = false, # Keep the noise value fixed\n", - " optimiser = false, # Keep kernel parameters fixed\n", - " )\n", - "@time train!(mfull, 5);\n", - "models[end] = mfull;" - ], - "metadata": {}, - "execution_count": 6 - }, - { - "cell_type": "markdown", - "source": [ - "Create a grid and compute prediction on it" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "compute_grid (generic function with 2 methods)" - }, - "metadata": {}, - "execution_count": 7 - } - ], - "cell_type": "code", - "source": [ - "function compute_grid(model, n_grid=50)\n", - " mins = -20; maxs = 20\n", - " x_grid = range(mins, maxs, length = n_grid) # Create a grid\n", - " y_grid, sig_y_grid = proba_y(model, reshape(x_grid, :, 1)) # Predict the mean and variance on the grid\n", - " return y_grid, sig_y_grid, x_grid\n", - "end" - ], - "metadata": {}, - "execution_count": 7 - }, - { - "cell_type": "markdown", - "source": [ - "Plot the data as a scatter plot" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "Plot{Plots.PyPlotBackend() n=136}", - "image/png": 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size=(300,500))\n", - "end\n", - "\n", - "function plot_model(model, X, Y, title = nothing)\n", - " n_grid = 100\n", - " y_grid, sig_y_grid, x_grid = compute_grid(model,n_grid)\n", - " title = if isnothing(title)\n", - " (model isa SVGP ? \"M = $(dim(model[1]))\" : \"full\")\n", - " else\n", - " title\n", - " end\n", - "\n", - " p = plotdata(X, Y)\n", - " Plots.plot!(p, x_grid, y_grid,\n", - " ribbon=2 * sqrt.(sig_y_grid), # Plot 2 std deviations\n", - " title=title,\n", - " color=\"red\",\n", - " lab=\"\",\n", - " linewidth=3.0)\n", - " if model isa SVGP # Plot the inducing points as well\n", - " Plots.plot!(p,\n", - " vec(model.f[1].Z),\n", - " zeros(dim(model.f[1])),\n", - " msize=2.0,\n", - " color=\"black\",t=:scatter,lab=\"\")\n", - " end\n", - " return p\n", - "end;\n", - "\n", - "Plots.plot(plot_model.(models, Ref(X), Ref(Y))...,\n", - " layout=(1, length(models)),\n", - " size=(1000,200)\n", - " ) # Plot all models and combine the plots" - ], - "metadata": {}, - "execution_count": 8 - }, - { - "cell_type": "markdown", - "source": [ - "## Non-Gaussian Likelihoods\n", - "We now look at using another noise than Gaussian noise.\n", - "In AGP.jl you can use the Student-T likelihood,\n", - "the Laplace likelihood and the Heteroscedastic likelihood" - ], - "metadata": {} - }, - { - "cell_type": "markdown", - "source": [ - "We will use the same toy dataset for our experiment" - ], - "metadata": {} - }, - { - "cell_type": "markdown", - "source": [ - "Create an array of model with different likelihoods:" - ], - "metadata": {} - }, - { - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "┌ Info: Training with the Student-t likelihood\n", - "└ @ Main.##803 string:6\n", - " 2.086028 seconds (567.02 k allocations: 886.938 MiB, 4.54% gc time)\n", - "┌ Info: Training with the Laplace likelihood\n", - "└ @ Main.##803 string:6\n", - " 1.756621 seconds (44.60 k allocations: 862.269 MiB)\n", - "┌ Info: Training with the Gaussian likelihood with heteroscedastic noise\n", - "└ @ Main.##803 string:6\n", - " 3.593426 seconds (394.19 k allocations: 1.742 GiB, 1.41% gc time)\n" - ] - }, - { - "output_type": "execute_result", - "data": { - "text/plain": "Gaussian Process with a Gaussian likelihood (σ² = 0.01) infered by Analytic Inference " - }, - "metadata": {}, - "execution_count": 9 - } - ], - "cell_type": "code", - "source": [ - "likelihoods = [StudentTLikelihood(3.0),\n", - " LaplaceLikelihood(3.0),\n", - " HeteroscedasticLikelihood(1.0)]\n", - "ngmodels = Vector{AbstractGP}(undef, length(likelihoods)+1)\n", - "for (i, l) in enumerate(likelihoods)\n", - " @info \"Training with the $(l)\" # We need to use VGP\n", - " m = VGP(X, Y, # First arguments are the input and output\n", - " kernel, # Kernel\n", - " l, # Likelihood used\n", - " AnalyticVI(), # Inference usede to solve the problem\n", - " optimiser = false, # Keep kernel parameters fixed\n", - " )\n", - " @time train!(m, 10) # Train the model for 100 iterations\n", - " ngmodels[i] = m # Save the model in the array\n", - "end\n", - "\n", - "ngmodels[end] = models[end] # Add the Gaussian model" - ], - "metadata": {}, - "execution_count": 9 - }, - { - "cell_type": "markdown", - "source": [ - "We can now repeat the prediction from before :" - ], - "metadata": {} - }, - { - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": "Plot{Plots.PyPlotBackend() n=8}", - "image/png": 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\"Heteroscedastic\", \"Gaussian\"])...,\n", - " layout=(1, length(ngmodels)),\n", - " size=(1000,200)\n", - " ) # Plot all models and combine the plots" - ], - "metadata": {}, - "execution_count": 10 - }, - { - "cell_type": "markdown", - "source": [ - "---\n", - "\n", - "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*" - ], - "metadata": {} - } - ], - "nbformat_minor": 3, - "metadata": { - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.5.1" - }, - "kernelspec": { - "name": "julia-1.5", - "display_name": "Julia 1.5.1", - "language": "julia" - } - }, - "nbformat": 4 -} diff --git a/docs/src/api.md b/docs/src/api.md index 2f34792e..067238b1 100644 --- a/docs/src/api.md +++ b/docs/src/api.md @@ -22,6 +22,9 @@ VGP MCGP SVGP OnlineSVGP +MOVGP +MOSVGP +VStP ``` ## Likelihood Types @@ -55,6 +58,7 @@ MCIntegrationSVI ```@docs train! +sample predict_f predict_y proba_y @@ -66,6 +70,7 @@ proba_y ZeroMean ConstantMean EmpiricalMean +AffineMean ``` ## Index diff --git a/docs/src/comparison.md b/docs/src/comparison.md index 509d023a..cdd8ca06 100644 --- a/docs/src/comparison.md +++ b/docs/src/comparison.md @@ -2,10 +2,11 @@ ## JuliaGaussianProcesses Organization -There is a common effort to bring GP people together through the JuliaGP organization. +There is a common effort to bring the GP people together through the JuliaGP organization. We work on making the building blocks necessary for GP such as [KernelFunctions.jl](https://github.com/JuliaGaussianProcesses/KernelFunctions.jl) for kernels, [AbstractGPs.jl](https://github.com/JuliaGaussianProcesses/AbstractGPs.jl) for the basic GP definitions and more is coming. -The long-term goal is to have AGP.jl depend on all of the constituent and to simply have it as a wrapper. +The long-term goal is to have AGP.jl depend on all of this elements and to use it as a wrapper. +## 🚧 This comparison is now quite outdated and new solutions have been introduced 🚧 ## AugmentedGaussianProcesses.jl vs [Stheno.jl](https://github.com/willtebbutt/Stheno.jl) vs [GaussianProcesses.jl](https://github.com/STOR-i/GaussianProcesses.jl) There are already two other Gaussian Process packages in Julia, however their feature are quite orthogonal. They are roughly compared here: diff --git a/docs/src/userguide.md b/docs/src/userguide.md index b10d1f90..e8f0aebb 100644 --- a/docs/src/userguide.md +++ b/docs/src/userguide.md @@ -10,36 +10,47 @@ There are 3 main actions needed to train and use the different models: ### Possible models -There are currently 3 possible Gaussian Process models: +There are currently 8 possible Gaussian Process models: - [`GP`](@ref) corresponds to the original GP regression model, it is necessarily with a Gaussian likelihood. ```julia - GP(X_train,y_train,kernel) + GP(X_train, y_train, kernel; kwargs...) ``` - [`VGP`](@ref) is a variational GP model: a multivariate Gaussian is approximating the true posterior. There is no inducing points augmentation involved. Therefore it is well suited for small datasets (~10^3 samples) ```julia - VGP(X_train,y_train,kernel,likelihood,inference) + VGP(X_train, y_train, kernel, likelihood, inference; kwargs...) ``` - [`SVGP`](@ref) is a variational GP model augmented with inducing points. The optimization is done on those points, allowing for stochastic updates and large scalability. The counterpart can be a slightly lower accuracy and the need to select the number and the location of the inducing points (however this is a problem currently worked on). ```julia - SVGP(X_train,y_train,kernel,likelihood,inference,n_inducingpoints) + SVGP(X_train, y_train, kernel, likelihood, inference, n_inducingpoints; kwargs...) ``` +- [`MCGP](@ref) is a GP model where the posterior is represented via a collection of samplers. +- ```julia + - MCGP(X_train, y_train, kernel, likelihood, inference; kwargs...) + ``` + - [`OnlineSVGP`](@ref) is an online variational GP model. It is based on the streaming method of Bui 17', it supports all likelihoods, even with multiple latents. ```julia - OnlineSVGP(kernel, likelihood, inference, n_latent, inducing_points) + OnlineSVGP(kernel, likelihood, inference, ind_point_algorithm; kwargs...) ``` -- [`MOVGP`](@ref) is a multi output variational GP model. +- [`MOVGP`](@ref) is a multi output variational GP model based on the principle `f_output[i] = sum(A[i, j] * f_latent[j] for j in 1:n_latent)`. The number of latent GP is free: +```julia + MOVGP(X_train, ys_train, kernel, likelihood/s, inference, n_latent; kwargs...) +``` -- [`MOSVGP`](@ref) is a multi output sparse variational GP model, based on Moreno-Muñoz 18'. +- [`MOSVGP`](@ref) is the same thing as `MOVGP` but with inducing pointsa multi output sparse variational GP model, based on Moreno-Muñoz 18'. +```julia + MOVGP(X_train, ys_train, kernel, likelihood/s, inference, n_latent, n_inducing_points; kwargs...) +``` - [`VStP`](@ref) is a variational Student-T model where the prior is a multivariate Student-T distribution with scale `K`, mean `μ₀` and degrees of freedom `ν`. The inference is done automatically by augmenting the prior as a scale mixture of inverse gamma ```julia - VStP(X_train,y_train,kernel,likelihood,inference,ν) + VStP(X_train, y_train, kernel, likelihood, inference, ν; kwargs...) ``` ### [Likelihood](@id likelihood_user) -`GP` can only have a Gaussian likelihood, `VGP` and `SVGP` have more choices. Here are the ones currently implemented: +`GP` can only have a Gaussian likelihood, while the other have more choices. Here are the ones currently implemented: #### Regression @@ -82,7 +93,7 @@ The two next methods rely on numerical approximation of an integral and I theref - [`QuadratureVI`](@ref) : Variational Inference with gradients computed by estimating the expected log-likelihood via quadrature. - [`MCIntegrationVI`](@ref) : Variational Inference with gradients computed by estimating the expected log-likelihood via Monte Carlo Integration -We also use [AdvancedHMC.jl](https://github.com/TuringLang/AdvancedHMC.jl) to provide a HMC algorithm, although generally the Gibbs sampling is preferable when available. +[WIP] : [AdvancedHMC.jl](https://github.com/TuringLang/AdvancedHMC.jl) will be integrated at some point, although generally the Gibbs sampling is preferable when available. ### [Compatibility table](@id compat_table) @@ -103,6 +114,16 @@ Not all inference are implemented/valid for all likelihoods, here is the compati | | | | | | (dev) means that the feature is possible and may be developped and tested but is not available yet. All contributions or requests are very welcome! +| Model/Inference | AnalyticVI | GibbsSampling | QuadratureVI | MCIntegrationVI | +| --- | :-: | :-: | :-: | :-: | +| VGP | ✔ | ✖ | ✔ | ✔ | +| SVGP | ✔ | ✖ | ✔ | ✔ | +| MCGP | ✖ | ✔ | ✖ | ✖ | +| OnlineSVGP | ✔ | ✖ | ✖ | ✖ | +| MO(S)VGP | ✔ | ✖ | ✔ | ✔ | +| VStP | ✔ | ✖ | ✔ | ✔ | + +Note that for MO(S)VGP you can use a mix of different likelihoods. ### Additional Parameters #### Hyperparameter optimization @@ -123,12 +144,12 @@ The `mean` keyword allows you to add different types of prior means: Training is straightforward after initializing the `model` by running : ```julia -train!(model, 100; callback = callbackfunction) +train!(model; iterations=100, callback=callbackfunction) ``` Where the `callback` option is for running a function at every iteration. `callbackfunction` should be defined as` ```julia -function callbackfunction(model,iter) - "do things here"... +function callbackfunction(model, iter) + # do things here... end ``` @@ -136,9 +157,9 @@ end Once the model has been trained it is finally possible to compute predictions. There always three possibilities : -- `predict_f(model, X_test, covf=true, fullcov=false)` : Compute the parameters (mean and covariance) of the latent normal distributions of each test points. If `covf=false` return only the mean, if `fullcov=true` return a covariance matrix instead of only the diagonal -- `predict_y(model,X_test)` : Compute the point estimate of the predictive likelihood for regression or the label of the most likely class for classification. -- `proba_y(model,X_test)` : Return the mean with the variance of eahc point for regression or the predictive likelihood to obtain the class `y=1` for classification. +- `predict_f(model, X_test; covf=true, fullcov=false)` : Compute the parameters (mean and covariance) of the latent normal distributions of each test points. If `covf=false` return only the mean, if `fullcov=true` return a covariance matrix instead of only the diagonal +- `predict_y(model, X_test)` : Compute the point estimate of the predictive likelihood for regression or the label of the most likely class for classification. +- `proba_y(model, X_test)` : Return the mean with the variance of eahc point for regression or the predictive likelihood to obtain the class `y=1` for classification. ## Miscellaneous diff --git a/src/AugmentedGaussianProcesses.jl b/src/AugmentedGaussianProcesses.jl index ddf63a89..01a48096 100644 --- a/src/AugmentedGaussianProcesses.jl +++ b/src/AugmentedGaussianProcesses.jl @@ -29,20 +29,13 @@ export @augmodel #General modules using Reexport -using LinearAlgebra -using Random @reexport using KernelFunctions -using KernelFunctions: ColVecs, RowVecs -using Zygote, ForwardDiff -using ChainRulesCore: ChainRulesCore, NO_FIELDS, DoesNotExist -using Flux: params, destructure @reexport using Flux.Optimise -using AdvancedHMC -using MCMCChains -using StatsBase @reexport using InducingPoints -using StatsFuns -using SpecialFunctions + +using AbstractMCMC +using AdvancedHMC +using ChainRulesCore: ChainRulesCore, NO_FIELDS, DoesNotExist using Distributions: Distributions, Distribution, @@ -61,7 +54,17 @@ using Distributions: MvNormal, Gamma using FastGaussQuadrature: gausshermite -using ProgressMeter, SimpleTraits +using Flux: params, destructure +using ForwardDiff +using KernelFunctions: ColVecs, RowVecs +using LinearAlgebra +using ProgressMeter +using Random +using StatsBase +using SimpleTraits +using StatsFuns +using SpecialFunctions +using Zygote #Include custom module for additional distributions include(joinpath("ComplementaryDistributions", "ComplementaryDistributions.jl")) @@ -103,6 +106,7 @@ include(joinpath("functions", "plotting.jl")) # Training and prediction functions include(joinpath("training", "training.jl")) +include(joinpath("training", "sampling.jl")) include(joinpath("training", "onlinetraining.jl")) include(joinpath("hyperparameter", "autotuning.jl")) include(joinpath("training", "predictions.jl")) diff --git a/src/hyperparameter/autotuning.jl b/src/hyperparameter/autotuning.jl index e8886eca..6d2d2c0f 100644 --- a/src/hyperparameter/autotuning.jl +++ b/src/hyperparameter/autotuning.jl @@ -46,7 +46,8 @@ end end # Optimize prior mean isnothing(Δμ₀) || update!.(μ₀, Δμ₀, Ref(xview(m))) - if !isnothing(ks) isnothing(Δk) + if !isnothing(ks) + isnothing(Δk) @warn "Kernel gradients are equal to zero" maxlog = 1 return nothing end diff --git a/src/inference/MCVI.jl b/src/inference/MCVI.jl index a05da818..85b6b03a 100644 --- a/src/inference/MCVI.jl +++ b/src/inference/MCVI.jl @@ -158,23 +158,53 @@ function grad_expectations!(m::AbstractGP{T,L,<:MCIntegrationVI{T,N}}) where {T, μ = mean_f(m) σ² = var_f(m) nSamples = length(MBIndices(m)) - for j in 1:nSamples - samples .= raw_samples .* [sqrt(σ²[k][j]) for k in 1:N]' .+ [μ[k][j] for k in 1:N]' - grad_samples(m, samples, j) + for j in 1:nSamples # Loop over every data point + samples .= raw_samples .* sqrt.([σ²[k][j] for k in 1:nLatent(m)])' .+ [μ[k][j] for k in 1:nLatent(m)]' + grad_samples(m, samples, j) # Compute the gradient for data point j end end function expec_loglikelihood( - l::AbstractLikelihood, i::MCIntegrationVI{T,N}, y, μ_f, var_f -) where {T,N} - raw_samples = randn(i.nMC, N) - samples = similar(raw_samples) + l::AbstractLikelihood, i::MCIntegrationVI{T,N}, y, μ, σ² +) where {T,N} # μ and σ² are tuples of vectors + raw_samples = randn(T, i.nMC, N) # dimension nMC x nLatent + # samples = similar(raw_samples) nSamples = length(MBIndices(i)) - loglike = 0.0 - for j in 1:nSamples - samples = - raw_samples .* [sqrt(var_f[k][j]) for k in 1:N]' .+ [μ_f[k][j] for k in 1:N]' - loglike += sum(f -> loglikelihood(l, getindex.(y, j), f), eachrow(samples)) / i.nMC + tot = 0.0 + for j in 1:nSamples # Loop over every data point + samples = raw_samples .* sqrt.([σ²[k][j] for k in 1:N])' .+ [μ[k][j] for k in 1:N]' + # samples is of dimension nMC x nLatent again + y_j = getindex.(y, j) # Obtain the label for data point j + for f in eachrow(samples) + # return sum(eachrow(samples)) do f # We now compute the loglikelihood over every sample + tot += loglikelihood(l, y_j, f) + end end - return loglike + return tot / i.nMC end + +# function expec_loglikelihood( +# l::AbstractLikelihood, i::MCIntegrationVI{T,N}, y, μ, σ² +# ) where {T,N} +# raw_samples = randn(T, i.nMC, N) # dimension nMC x nLatent +# # samples = similar(raw_samples) +# nSamples = length(MBIndices(i)) +# return sum(expec_loglikelihood_datapoint.(l, Ref(raw_samples), Ref(y), Ref(μ), Ref(σ²), 1:nSamples, N)) / i.nMC +# # return sum(1:nSamples) do j # Loop over every data point +# # samples = raw_samples .* sqrt.([σ²[k][j] for k in 1:N])' .+ [μ[k][j] for k in 1:N]' +# # # samples is of dimension nMC x nLatent again +# # y_j = getindex.(y, j) # Obtain the label for data point j +# # return sum(eachrow(samples)) do f # We now compute the loglikelihood over every sample +# # return loglikelihood(l, y_j, f) +# # end +# # end / i.nMC +# end + +# function expec_loglikelihood_datapoint(l::AbstractLikelihood, raw_samples, y, μ, σ², j, N) +# samples = raw_samples .* sqrt.([σ²[k][j] for k in 1:N])' .+ [μ[k][j] for k in 1:N]' +# # samples is of dimension nMC x nLatent again +# y_j = getindex.(y, j) # Obtain the label for data point j +# return sum((f->loglikelihood(l, y_j, f)).(eachrow(samples))) # We now compute the loglikelihood over every sample +# # return +# # end +# end \ No newline at end of file diff --git a/src/inference/analyticVI.jl b/src/inference/analyticVI.jl index c8096601..fbfbdae6 100644 --- a/src/inference/analyticVI.jl +++ b/src/inference/analyticVI.jl @@ -283,7 +283,8 @@ end ), ) tot -= GaussianKL(model) - return tot -= Zygote.@ignore( + tot -= Zygote.@ignore( sum(getρ(inference(model)) .* AugmentedKL.(likelihood(model), yview(model))) ) + return tot end diff --git a/src/inference/gibbssampling.jl b/src/inference/gibbssampling.jl index 60d42068..235139cb 100644 --- a/src/inference/gibbssampling.jl +++ b/src/inference/gibbssampling.jl @@ -18,7 +18,7 @@ mutable struct GibbsSampling{T<:Real,N,Tx,Ty} <: SamplingInference{T} opt::NTuple{N,SOptimizer} xview::Tx yview::Ty - sample_store::Array{T,3} + sample_store::Vector{Vector{Vector{T}}} function GibbsSampling{T}(nBurnin::Int, thinning::Int, ϵ::Real) where {T} nBurnin >= 0 || error("nBurnin should be positive") thinning >= 0 || error("thinning should be positive") @@ -36,7 +36,7 @@ mutable struct GibbsSampling{T<:Real,N,Tx,Ty} <: SamplingInference{T} ) where {T,Tx,Ty} opts = ntuple(_ -> SOptimizer{T}(nothing), nLatent) return new{T,nLatent,Tx,Ty}( - nBurnin, thinning, ϵ, 0, nSamples, true, opts, xview, yview + nBurnin, thinning, ϵ, 0, nSamples, true, opts, xview, yview, [] ) end end @@ -67,53 +67,6 @@ function tuple_inference( ) end -function init_sampler!( - inference::GibbsSampling{T}, - nLatent::Int, - nFeatures::Integer, - nSamples::Integer, - cat_samples::Bool, -) where {T<:Real} - if inference.nIter == 0 || !cat_samples - inference.sample_store = zeros(T, nSamples, nFeatures, nLatent) - else - inference.sample_store = cat( - inference.sample_store, zeros(T, nSamples, nFeatures, nLatent); dims=1 - ) - end - return inference -end - -function sample_parameters( - m::MCGP{T,L,<:GibbsSampling}, - nSamples::Int, - callback::Union{Nothing,Function}, - cat_samples::Bool, -) where {T,L} - init_sampler!(inference(m), nLatent(m), nFeatures(m), nSamples, cat_samples) - computeMatrices!(m) - for i in 1:(inference(m).nBurnin + nSamples * inference(m).thinning) - inference(m).nIter += 1 - sample_local!(likelihood(m), yview(m), means(m)) - sample_global!.(∇E_μ(m), ∇E_Σ(m), Zviews(m), getf(m)) - if nIter(inference(m)) > m.inference.nBurnin && - ((nIter(inference(m)) - m.inference.nBurnin) % (inference(m).thinning) == 0) # Store variables every thinning - store_variables!(inference(m), means(m)) - end - end - symbols = ["f_" * string(i) for i in 1:nFeatures(m)] - if nLatent(m) == 1 - return Chains( - reshape(m.inference.sample_store[:, :, 1], :, nFeatures(m), 1), symbols - ) - else - return [ - Chains(reshape(m.inference.sample_store[:, :, i], :, nFeatures(m), 1), symbols) - for i in 1:nLatent(m) - ] - end -end - function sample_local!(l::AbstractLikelihood, y, f::Tuple{<:AbstractVector{T}}) where {T} return sample_local!(l, y, first(f)) end @@ -125,15 +78,5 @@ function sample_global!( ) where {T} gp.post.Σ .= inv(Symmetric(2.0 * Diagonal(∇E_Σ) + inv(pr_cov(gp)))) rand!(MvNormal(cov(gp) * (∇E_μ + pr_cov(gp) \ pr_mean(gp, X)), cov(gp)), gp.post.f) - return nothing -end - -function post_process!(m::MCGP{T}) where {T} - # for k in 1:model.nLatent - # model.μ[k] = - # vec(mean(hcat(model.inference.sample_store[k]...), dims = 2)) - # model.Σ[k] = - # Symmetric(cov(hcat(model.inference.sample_store[k]...), dims = 2)) - # end - return nothing + return deepcopy(posterior(gp).f) end diff --git a/src/inference/numericalVI.jl b/src/inference/numericalVI.jl index 222f9474..ecce52d8 100644 --- a/src/inference/numericalVI.jl +++ b/src/inference/numericalVI.jl @@ -180,7 +180,8 @@ function ELBO(m::AbstractGP{T,L,<:NumericalVI}) where {T,L} tot = zero(T) tot += getρ(m.inference) * - expec_loglikelihood(m.likelihood, m.inference, yview(m), mean_f(m), var_f(m)) + expec_loglikelihood(likelihood(m), inference(m), yview(m), mean_f(m), var_f(m)) tot -= GaussianKL(m) - return tot -= extraKL(m) + tot -= extraKL(m) + return tot end diff --git a/src/likelihood/classification.jl b/src/likelihood/classification.jl index 86260954..9e2bc521 100644 --- a/src/likelihood/classification.jl +++ b/src/likelihood/classification.jl @@ -22,7 +22,5 @@ function treat_labels!(y::AbstractVector, likelihood::ClassificationLikelihood) ) end -predict_y(l::ClassificationLikelihood, μ::AbstractVector{<:Real}) = sign.(μ) -function predict_y(l::ClassificationLikelihood, μ::AbstractVector{<:AbstractVector}) - return sign.(first(μ)) -end +predict_y(::ClassificationLikelihood, μ::AbstractVector{<:Real}) = μ .> 0 +predict_y(::ClassificationLikelihood, μ::AbstractVector{<:AbstractVector}) = first(μ) .> 0 diff --git a/src/likelihood/logisticsoftmax.jl b/src/likelihood/logisticsoftmax.jl index 453928e5..97783a58 100644 --- a/src/likelihood/logisticsoftmax.jl +++ b/src/likelihood/logisticsoftmax.jl @@ -192,9 +192,9 @@ end function grad_samples( model::AbstractGP{T,<:LogisticSoftMaxLikelihood,<:NumericalVI}, samples::AbstractMatrix{T}, - index::Integer, + index::Int, ) where {T} - class = model.likelihood.y_class[index]::Int64 + class = model.likelihood.y_class[index]::Int grad_μ = zeros(T, nLatent(model)) grad_Σ = zeros(T, nLatent(model)) g_μ = similar(grad_μ) diff --git a/src/training/predictions.jl b/src/training/predictions.jl index fde57509..256e1c6c 100644 --- a/src/training/predictions.jl +++ b/src/training/predictions.jl @@ -84,7 +84,7 @@ function _predict_f( ) where {T} k_star = kernelmatrix.(kernels(m), [X_test], Zviews(m)) f = _sample_f(m, X_test, k_star) - μf = Tuple(vec(StatsBase.mean(f[k]; dims=2)) for k in 1:nLatent(m)) + μf = mean.(f) if !cov return (μf,) end @@ -95,9 +95,7 @@ function _predict_f( else k_starstar = kernelmatrix_diag.(kernels(m), [X_test]) .+ [T(jitt) * ones(T, length(X_test))] - σ²f = - k_starstar .- diag_ABt.(k_star ./ pr_covs(m), k_star) .+ - StatsBase.var.(f, dims=2) + σ²f = k_starstar .- diag_ABt.(k_star ./ pr_covs(m), k_star) .+ StatsBase.var.(f) return μf, σ²f end end @@ -108,7 +106,7 @@ function _sample_f( k_star=kernelmatrix.(kernels(m), [X_test], Zviews(m)), ) where {T} return f = [ - k_star[k] * (pr_cov(m.f[k]) \ inference(m).sample_store[:, :, k]') for + Ref(k_star[k] / pr_cov(m.f[k])) .* getindex.(inference(m).sample_store, k) for k in 1:nLatent(m) ] end @@ -117,7 +115,7 @@ end function predict_f( model::AbstractGP, X_test::AbstractVector{<:Real}; cov::Bool=false, diag::Bool=true ) - return predict_f(model, [X_test]; cov=cov, diag=diag) + return predict_f(model, reshape(X_test, :, 1); cov=cov, diag=diag) end function predict_f( @@ -147,7 +145,7 @@ end ## Wrapper to predict vectors ## function predict_y(model::AbstractGP, X_test::AbstractVector{<:Real}) - return predict_y(model, [X_test]) + return predict_y(model, reshape(X_test, :, 1)) end function predict_y(model::AbstractGP, X_test::AbstractMatrix; obsdim::Int=1) @@ -160,20 +158,20 @@ end Return - the predictive mean of `X_test` for regression - - the sign of `X_test` for classification + - 0 or 1 of `X_test` for classification - the most likely class for multi-class classification - the expected number of events for an event likelihood """ @traitfn function predict_y( model::TGP, X_test::AbstractVector ) where {TGP <: AbstractGP; !IsMultiOutput{TGP}} - return predict_y(model.likelihood, first(_predict_f(model, X_test; cov=false))) + return predict_y(likelihood(model), first(_predict_f(model, X_test; cov=false))) end @traitfn function predict_y( model::TGP, X_test::AbstractVector ) where {TGP <: AbstractGP; IsMultiOutput{TGP}} - return predict_y.(model.likelihood, _predict_f(model, X_test; cov=false)) + return predict_y.(likelihood(model), _predict_f(model, X_test; cov=false)) end function predict_y(l::MultiClassLikelihood, μs::AbstractVector{<:AbstractVector{<:Real}}) @@ -193,7 +191,9 @@ function predict_y(l::EventLikelihood, μ::AbstractVector{<:AbstractVector}) end ## Wrapper to return proba on vectors ## -proba_y(model::AbstractGP, X_test::AbstractVector{<:Real}) = proba_y(model, [X_test]) +function proba_y(model::AbstractGP, X_test::AbstractVector{<:Real}) + return proba_y(model, reshape(X_test, :, 1)) +end function proba_y(model::AbstractGP, X_test::AbstractMatrix; obsdim::Int=1) return proba_y(model, KernelFunctions.vec_of_vecs(X_test; obsdim=obsdim)) @@ -236,45 +236,34 @@ function compute_proba( return compute_proba(l, first(μ), first(σ²)) end -function StatsBase.mean_and_var(lik, fs) - @show typeof(fs), size(fs) +function StatsBase.mean_and_var(lik::AbstractLikelihood, fs::AbstractMatrix) vals = lik.(eachcol(fs)) - @show typeof(vals), size(vals) return StatsBase.mean(vals), StatsBase.var(vals) end -function proba_y(model::MCGP{T}, X_test::AbstractVector; nSamples::Int=200) where {T<:Real} +function proba_y(model::MCGP, X_test::AbstractVector{<:Real}; nSamples::Int=100) + return proba_y(model, reshape(X_test, :, 1); nSamples) +end + +function proba_y(model::MCGP, X_test::AbstractMatrix; nSamples::Int=100, obsdim=1) + return proba_y(model, KernelFunctions.vec_of_vecs(X_test; obsdim); nSamples) +end + +function proba_y(model::MCGP, X_test::AbstractVector; nSamples::Int=200) nTest = length(X_test) f = first(_sample_f(model, X_test)) - return proba, sig_proba = mean_and_var(x -> compute_proba.(likelihood(model), x), f) - # if nLatent(model) == 1 - # return (proba[1], sig_proba[1]) - # else - # return (proba, sig_proba) - # end + return proba, sig_proba = mean_and_var(compute_proba_f.(likelihood(model), f)) +end + +function compute_proba_f(l::AbstractLikelihood, f::AbstractVector{<:Real}) + return compute_proba.(l, f) end -# -# function proba_y(model::VGP{T,<:MultiClassLikelihood{T},<:GibbsSampling{T}},X_test::AbstractMatrix{T};nSamples::Int=200) where {T} -# k_star = kernelmatrix.([X_test],[model.inference.x],model.kernel) -# f = [[k_star[min(k,model.nPrior)]*model.invKnn[min(k,model.nPrior)]].*model.inference.sample_store[k] for k in 1:model.nLatent] -# k_starstar = kerneldiagmatrix.([X_test],model.kernel) -# K̃ = k_starstar .- diag_ABt.(k_star.*model.invKnn,k_star) .+ [zeros(size(X_test,1)) for i in 1:model.nLatent] -# nf = length(model.inference.sample_store[1]) -# proba = zeros(size(X_test,1),model.nLatent) -# labels = Array{Symbol}(undef,model.nLatent) -# for i in 1:nf -# res = compute_proba(model.likelihood,getindex.(f,[i]),K̃,nSamples) -# if i == 1 -# labels = names(res) -# end -# proba .+= Matrix(res) -# end -# return DataFrame(proba/nf,labels) -# end -# function compute_proba( l::AbstractLikelihood, ::AbstractVector, ::AbstractVector ) where {T<:Real} return error("Non implemented for the likelihood $l") end + +for f in [:predict_f, :predict_y, :proba_y] +end diff --git a/src/training/sampling.jl b/src/training/sampling.jl new file mode 100644 index 00000000..af23fe82 --- /dev/null +++ b/src/training/sampling.jl @@ -0,0 +1,57 @@ +struct GPModel{TGP} <: AbstractMCMC.AbstractModel + gp::TGP +end + +struct GPSampler{TS} <: AbstractMCMC.AbstractSampler + sampler::TS +end + +function StatsBase.sample(model::MCGP, nSamples::Int; kwargs...) + return sample(Random.GLOBAL_RNG, model, nSamples; kwargs...) +end +function StatsBase.sample(rng::Random.AbstractRNG, model::MCGP, nSamples::Int; kwargs...) + sampler = inference(model) + thinning = get(kwargs, :thinning, sampler.thinning) + discard_initial = get(kwargs, :discard_initial, sampler.nBurnin) + progressname = get(kwargs, :progressname, "Sampling with $sampler") + return sample( + rng, + GPModel(model), + GPSampler(sampler), + nSamples; + thinning, + discard_initial, + progressname, + kwargs..., + ) +end +function AbstractMCMC.step( + rng, model::GPModel, sampler::GPSampler{<:GibbsSampling}; kwargs... +) + computeMatrices!(model.gp) + sample_local!(likelihood(model.gp), yview(model.gp), means(model.gp)) + f = sample_global!.(∇E_μ(model.gp), ∇E_Σ(model.gp), Zviews(model.gp), getf(model.gp)) + sampler.sampler.nIter += 1 + return f, nothing +end + +function AbstractMCMC.step( + rng, model::GPModel, sampler::GPSampler{<:GibbsSampling}, state; kwargs... +) + sample_local!(likelihood(model.gp), yview(model.gp), means(model.gp)) + f = sample_global!.(∇E_μ(model.gp), ∇E_Σ(model.gp), Zviews(model.gp), getf(model.gp)) + sampler.sampler.nIter += 1 + return f, nothing +end + +function AbstractMCMC.bundle_samples( + samples, model::GPModel, sampler::GPSampler, state, chain_type::Type; kwargs... +) + resume = get(kwargs, :cat, true) + if !resume || isempty(sampler.sampler.sample_store) # check if either one should restart sampling or if no samples was ever taken + sampler.sampler.sample_store = samples + else + sampler.sampler.sample_store = vcat(sampler.sampler.sample_store, samples) + end + return samples +end diff --git a/src/training/training.jl b/src/training/training.jl index f8da85f8..8f38254c 100644 --- a/src/training/training.jl +++ b/src/training/training.jl @@ -82,20 +82,6 @@ function train!( return nothing end -function sample( - model::MCGP{T}, - nSamples::Int=1000; - callback::Union{Nothing,Function}=nothing, - cat_samples::Bool=false, -) where {T} - if verbose(model) > 0 - @info "Starting sampling $model with $(model.nSamples) samples with $(size(model.X,2)) features and $(nLatent(model)) latent GP" * - (model.nLatent > 1 ? "s" : "") - end - nSamples > 0 || error("Number of samples should be positive") - return sample_parameters(model, nSamples, callback, cat_samples) -end - function update_parameters!(model::GP) computeMatrices!(model) #Recompute the matrices if necessary (when hyperparameters have been updated) analytic_updates!(model) diff --git a/test/inference/gibbssampling.jl b/test/inference/gibbssampling.jl index 6c9b75b5..08ac3e87 100644 --- a/test/inference/gibbssampling.jl +++ b/test/inference/gibbssampling.jl @@ -15,22 +15,4 @@ y = rand(N) @test AGP.getρ(i) == 1 @test AGP.isStochastic(i) == false - i = AGP.init_sampler!(i, L, N, nSamples, false) - - @test i.sample_store == zeros(Float64, nSamples, N, L) - - i.nIter = nSamples - i = AGP.init_sampler!(i, L, N, nSamples, true) - - @test i.sample_store == zeros(Float64, 2*nSamples, N, L) - - i.nIter = 2*nSamples - i = AGP.init_sampler!(i, L, N, 2, false) - - @test i.sample_store == zeros(Float64, 2, N, L) - - i.nIter = 1 - fs = [rand(N) for _ in 1:L] - AGP.store_variables!(i, fs) - @test i.sample_store[1, :, 1] == fs[1] end diff --git a/test/likelihood/bayesiansvm.jl b/test/likelihood/bayesiansvm.jl index 2d5d70aa..5b0ced0b 100644 --- a/test/likelihood/bayesiansvm.jl +++ b/test/likelihood/bayesiansvm.jl @@ -3,7 +3,7 @@ N, d = 20, 2 k = transform(SqExponentialKernel(), 10.0) X, f = generate_f(N, d, k) - y = sign.(f) + y = f .> 0 floattypes = [Float64] tests_likelihood( BayesianSVM(), diff --git a/test/likelihood/classification.jl b/test/likelihood/classification.jl index 237cb315..286bcb9a 100644 --- a/test/likelihood/classification.jl +++ b/test/likelihood/classification.jl @@ -10,6 +10,6 @@ y = rand([2,3], 10) @test_throws AssertionError AGP.treat_labels!(y, l) y = randn(10) - @test predict_y(l, y) == sign.(y) - @test predict_y(l, [y]) == sign.(y) + @test predict_y(l, y) == (y .> 0) + @test predict_y(l, [y]) == (y .> 0) end diff --git a/test/likelihood/logistic.jl b/test/likelihood/logistic.jl index bce215df..5135d254 100644 --- a/test/likelihood/logistic.jl +++ b/test/likelihood/logistic.jl @@ -2,7 +2,7 @@ N, d = 20, 2 k = 2.0 * transform(SqExponentialKernel(), 10.0) X, f = generate_f(N, d, k) - y = sign.(f) + y = f .> 0 floattypes = [Float64] tests_likelihood( LogisticLikelihood(), diff --git a/test/testingtools.jl b/test/testingtools.jl index 61354a9f..50af1530 100644 --- a/test/testingtools.jl +++ b/test/testingtools.jl @@ -450,9 +450,9 @@ function tests_likelihood( @test AGP.output(model) isa AbstractVector @test AGP.input(model) isa AbstractVector @test AGP.nLatent(model) == nLatent - samples = AGP.sample(model, 100) + samples = sample(model, 100; progress=false) @test_broken samples2 = - AGP.sample(model, 100, cat_samples = true) + sample(model, 100; cat=true, progress=false) else @test_throws ErrorException MCGP( X, @@ -471,9 +471,9 @@ function tests_likelihood( @test AGP.output(model) isa AbstractVector @test AGP.input(model) isa AbstractVector @test AGP.nLatent(model) == nLatent - samples = AGP.sample(model, 20) + samples = sample(model, 20; progress=false) @test_broken samples2 = - AGP.sample(model, 20, cat_samples = true) + sample(model, 20; cat=true) else @test_throws ErrorException MCGP(X, y, k, l, HMCSampling()) end