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sharanry/viz_v0.1.ipynb

Created February 8, 2021 18:59
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viz_v0.1.ipynb
{
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"execution_count": 5,
"metadata": {},
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"source": [
"using DrWatson\n",
"@quickactivate \"ParamRegNN\"\n",
"using Plots, CSV, DataFrames, StatsPlots\n",
"using PlotlyJS\n",
"# using SimplePlots\n",
"using Interact"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# using Plots\n",
"# x = y = 0:0.1:30\n",
"# freqs = OrderedDict(zip([\"pi/4\", \"π/2\", \"3π/4\", \"π\"], [π/4, π/2, 3π/4, π]))\n",
"# mp = @manipulate for freq1 in freqs, freq2 in slider(0.01:0.1:4π; label=\"freq2\")\n",
"# y = @. sin(freq1*x) * sin(freq2*x)\n",
"# Plots.plot(x, y)\n",
"# end"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Dict{Float64,Dict{Any,DataFrame}} with 2 entries:\n",
" 0.5 => Dict{Any,DataFrame}(0.0001=>\u001b[1m100×8 DataFrame\u001b[0m…\n",
" 0.05 => Dict{Any,DataFrame}(0.0001=>\u001b[1m100×8 DataFrame\u001b[0m…"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results = Dict(\n",
" 0.5=>Dict(\n",
" \"map\"=> CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout_glorot_map\", \"batchsize=256_epochs=100_mcmc_steps=1_prior_var=0.5_η=0.csv\"), DataFrame),\n",
" 0.1=> CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.1_mcmc_steps=1_prior_var=0.5_η=0.csv\"), DataFrame),\n",
" 0.01=> CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.01_mcmc_steps=1_prior_var=0.5_η=0.csv\"), DataFrame),\n",
" 0.001=> CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.001_mcmc_steps=1_prior_var=0.5_η=0.csv\"), DataFrame),\n",
" 0.0001=> CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.0001_mcmc_steps=1_prior_var=0.5_η=0.csv\"), DataFrame),\n",
" ),\n",
" 0.05=>Dict(\n",
" \"dropout\"=>CSV.read(datadir(\"sims\", \"baselines\", \"dropout_batchsize=256_epochs=100_initial_ϵ=0.01_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" \"vanilla\"=>CSV.read(datadir(\"sims\", \"baselines\", \"vanilla_batchsize=256_epochs=100_initial_ϵ=0.01_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" \"map\"=>CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout_glorot_map\", \"batchsize=256_epochs=100_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" 0.1=>CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.1_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" 0.01=>CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.01_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" 0.001=>CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.001_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" 0.0001=>CSV.read(datadir(\"sims\", \"train_attempt-mala-dense_prob_dropout\", \"batchsize=256_epochs=100_initial_ϵ=0.0001_mcmc_steps=1_prior_var=0.05_η=0.csv\"), DataFrame),\n",
" ),\n",
")"
]
},
{
"cell_type": "code",
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(WebIO.setval({\\\\\\\"name\\\\\\\":\\\\\\\"click\\\\\\\",\\\\\\\"scope\\\\\\\":\\\\\\\"5297196054402219731\\\\\\\",\\\\\\\"id\\\\\\\":\\\\\\\"8911968687776290668\\\\\\\",\\\\\\\"type\\\\\\\":\\\\\\\"observable\\\\\\\"},filtered_data.out)) : undefined}))}));\\\\n (WebIO.importBlock({\\\\\\\"data\\\\\\\":[{\\\\\\\"name\\\\\\\":\\\\\\\"Plotly\\\\\\\",\\\\\\\"type\\\\\\\":\\\\\\\"js\\\\\\\",\\\\\\\"url\\\\\\\":\\\\\\\"\\\\\\/assetserver\\\\\\/80e93471f280df210a5c6dda4a2b36fc829d3066-plotly-latest.min.js\\\\\\\"},{\\\\\\\"name\\\\\\\":null,\\\\\\\"type\\\\\\\":\\\\\\\"js\\\\\\\",\\\\\\\"url\\\\\\\":\\\\\\\"\\\\\\/assetserver\\\\\\/24f578911c07b6875768cb9a43d8547041c65d4e-plotly_webio.bundle.js\\\\\\\"}],\\\\\\\"type\\\\\\\":\\\\\\\"async_block\\\\\\\"})).then((imports) => handler.apply(this, imports));\\\\n}\\\\n\\\"],\\\"observables\\\":{\\\"_toImage\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"8393621645212535049\\\",\\\"value\\\":{}},\\\"hover\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"1801606762083986358\\\",\\\"value\\\":{}},\\\"selected\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"7185035130503739725\\\",\\\"value\\\":{}},\\\"__gd_contents\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"10447163033576509159\\\",\\\"value\\\":{}},\\\"click\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"8911968687776290668\\\",\\\"value\\\":{}},\\\"image\\\":{\\\"sync\\\":true,\\\"id\\\":\\\"11394585473943300020\\\",\\\"value\\\":\\\"\\\"},\\\"__get_gd_contents\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"4433019374575458594\\\",\\\"value\\\":\\\"\\\"},\\\"_downloadImage\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"9991633768248962807\\\",\\\"value\\\":{}},\\\"relayout\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"7361212773512285513\\\",\\\"value\\\":{}},\\\"_commands\\\":{\\\"sync\\\":false,\\\"id\\\":\\\"125095274781401209\\\",\\\"value\\\":[]}}},\\\"children\\\":[{\\\"props\\\":{\\\"id\\\":\\\"plot-45ee7457-d830-42a9-95c8-c75e3a8d599d\\\"},\\\"nodeType\\\":\\\"DOM\\\",\\\"type\\\":\\\"node\\\",\\\"instanceArgs\\\":{\\\"namespace\\\":\\\"html\\\",\\\"tag\\\":\\\"div\\\"},\\\"children\\\":[]}]},\\n window,\\n );\\n } else {\\n document\\n .querySelector('[data-webio-mountpoint=\\\"4084114492660062417\\\"]')\\n .innerHTML = (\\n '<div style=\\\"padding: 1em; background-color: #f8d6da; border: 1px solid #f5c6cb\\\">' +\\n '<p><strong>WebIO not detected.<\\/strong><\\/p>' +\\n '<p>Please read ' +\\n '<a href=\\\"https:\\/\\/juliagizmos.github.io\\/WebIO.jl\\/latest\\/troubleshooting\\/not-detected\\/\\\" target=\\\"_blank\\\">the troubleshooting guide<\\/a> ' +\\n 'for more information on how to resolve this issue.<\\/p>' +\\n '<p><a href=\\\"https:\\/\\/juliagizmos.github.io\\/WebIO.jl\\/latest\\/troubleshooting\\/not-detected\\/\\\" target=\\\"_blank\\\">https:\\/\\/juliagizmos.github.io\\/WebIO.jl\\/latest\\/troubleshooting\\/not-detected\\/<\\/a><\\/p>' +\\n '<\\/div>'\\n );\\n }\\n <\\/script>\\n<\\/div>\\n\"},\"nodeType\":\"DOM\",\"type\":\"node\",\"instanceArgs\":{\"namespace\":\"html\",\"tag\":\"div\"},\"children\":[]}]}]},\n",
" window,\n",
" );\n",
" } else {\n",
" document\n",
" .querySelector('[data-webio-mountpoint=\"13357267915588967354\"]')\n",
" .innerHTML = (\n",
" '<div style=\"padding: 1em; background-color: #f8d6da; border: 1px solid #f5c6cb\">' +\n",
" '<p><strong>WebIO not detected.</strong></p>' +\n",
" '<p>Please read ' +\n",
" '<a href=\"https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/\" target=\"_blank\">the troubleshooting guide</a> ' +\n",
" 'for more information on how to resolve this issue.</p>' +\n",
" '<p><a href=\"https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/\" target=\"_blank\">https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/</a></p>' +\n",
" '</div>'\n",
" );\n",
" }\n",
" </script>\n",
"</div>\n"
],
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" Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[Scope(Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[Node{WebIO.DOM}(WebIO.DOM(:html, :label), Any[\"σ\"], Dict{Symbol,Any}(:className => \"interact \",:style => Dict{Any,Any}(:padding => \"5px 10px 0px 10px\")))], Dict{Symbol,Any}(:className => \"interact-flex-row-left\")), Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[Node{WebIO.DOM}(WebIO.DOM(:html, :input), Any[], Dict{Symbol,Any}(:max => 2,:min => 1,:attributes => Dict{Any,Any}(:type => \"range\",Symbol(\"data-bind\") => \"numericValue: index, valueUpdate: 'input', event: {change: function (){this.changes(this.changes()+1)}}\",\"orient\" => \"horizontal\"),:step => 1,:className => \"slider slider is-fullwidth\",:style => Dict{Any,Any}()))], Dict{Symbol,Any}(:className => \"interact-flex-row-center\")), Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[Node{WebIO.DOM}(WebIO.DOM(:html, :p), Any[], Dict{Symbol,Any}(:attributes => Dict(\"data-bind\" => \"text: formatted_val\")))], Dict{Symbol,Any}(:className => \"interact-flex-row-right\"))], Dict{Symbol,Any}(:className => \"interact-flex-row interact-widget\")), Dict{String,Tuple{Observables.AbstractObservable,Union{Nothing, Bool}}}(\"changes\" => (Observable{Int64} with 1 listeners. Value:\n",
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" Observable{Any} with 0 listeners. Value:\n",
"PlotlyJS.SyncPlot(data: [\n",
" \"scatter with fields linewidth, name, type, x, and y\",\n",
" \"scatter with fields linewidth, name, type, x, and y\"\n",
"]\n",
"\n",
"layout: \"layout with field margin\"\n",
"\n",
", Scope(Node{WebIO.DOM}(WebIO.DOM(:html, :div), Any[], Dict{Symbol,Any}(:id => \"plot-45ee7457-d830-42a9-95c8-c75e3a8d599d\")), Dict{String,Tuple{Observables.AbstractObservable,Union{Nothing, Bool}}}(\"_toImage\" => (Observable{Dict{Any,Any}} with 1 listeners. Value:\n",
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},
"execution_count": 45,
"metadata": {
"application/vnd.webio.node+json": {
"kernelId": "3309d807-07e1-438f-baaa-a9d0df7f1c22"
}
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"output_type": "execute_result"
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"source": [
"ϵ = widget([10.0^i for i in (-4):(-2)], label=\"ϵ\")\n",
"σ = widget([5*10.0^i for i in (-2):(-1)], label=\"σ\")\n",
"\n",
"function create_plot(ϵ, σ)\n",
" plt = PlotlyJS.Plot([\n",
" PlotlyJS.scatter(;x=1:length(results[0.5][ϵ].test_acc), y=results[0.5][ϵ].test_acc, name=\"test\", linewidth=0.5),\n",
" PlotlyJS.scatter(;x=1:length(results[0.5][ϵ].train_acc), y=results[0.5][ϵ].train_acc, name=\"train\", linewidth=0.5)\n",
" ])\n",
"# return plt\n",
" return PlotlyJS.plot(plt)\n",
"end\n",
"interactive_plot = map(create_plot, ϵ, σ)\n",
"\n",
"vbox(\n",
" hbox(ϵ, σ), # stack horizontally\n",
" interactive_plot\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
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{
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"type": "js",
"url": "/assetserver/2182d55e67ae0c357235a5e27282375a80af142a-all.js"
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"type": "css",
"url": "/assetserver/f63eeede81ecdf76ba8e57d355ff65afe211c1f4-style.css"
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"type": "css",
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},
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"max": 2,
"min": 1,
"step": 1,
"style": {}
},
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}
],
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(WebIO.setval({\\\"name\\\":\\\"click\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"2972377240707377890\\\",\\\"type\\\":\\\"observable\\\"},filtered_data.out)) : undefined}))}));\\n (WebIO.importBlock({\\\"data\\\":[{\\\"name\\\":\\\"Plotly\\\",\\\"type\\\":\\\"js\\\",\\\"url\\\":\\\"\\/assetserver\\/80e93471f280df210a5c6dda4a2b36fc829d3066-plotly-latest.min.js\\\"},{\\\"name\\\":null,\\\"type\\\":\\\"js\\\",\\\"url\\\":\\\"\\/assetserver\\/24f578911c07b6875768cb9a43d8547041c65d4e-plotly_webio.bundle.js\\\"}],\\\"type\\\":\\\"async_block\\\"})).then((imports) => handler.apply(this, imports));\\n}\\n\"],\"observables\":{\"_toImage\":{\"sync\":false,\"id\":\"13911479075482936662\",\"value\":{}},\"hover\":{\"sync\":false,\"id\":\"1604814652504308591\",\"value\":{}},\"selected\":{\"sync\":false,\"id\":\"16506455463898317743\",\"value\":{}},\"__gd_contents\":{\"sync\":false,\"id\":\"6497331153570625402\",\"value\":{}},\"click\":{\"sync\":false,\"id\":\"2972377240707377890\",\"value\":{}},\"image\":{\"sync\":true,\"id\":\"10115380771835592724\",\"value\":\"\"},\"__get_gd_contents\":{\"sync\":false,\"id\":\"7331584987353820764\",\"value\":\"\"},\"_downloadImage\":{\"sync\":false,\"id\":\"1586072828260080457\",\"value\":{}},\"relayout\":{\"sync\":false,\"id\":\"8386376565731521516\",\"value\":{}},\"_commands\":{\"sync\":false,\"id\":\"8295217815419270535\",\"value\":[]}}},\"children\":[{\"props\":{\"id\":\"plot-66448816-25da-48b8-831b-279e4816df29\"},\"nodeType\":\"DOM\",\"type\":\"node\",\"instanceArgs\":{\"namespace\":\"html\",\"tag\":\"div\"},\"children\":[]}]}]}}}},\"children\":[{\"props\":{},\"nodeType\":\"ObservableNode\",\"type\":\"node\",\"instanceArgs\":{\"id\":\"4299249214729925338\",\"name\":\"obs-node\"},\"children\":[]}]}]},\n",
" window,\n",
" );\n",
" } else {\n",
" document\n",
" .querySelector('[data-webio-mountpoint=\"9447188204107521833\"]')\n",
" .innerHTML = (\n",
" '<div style=\"padding: 1em; background-color: #f8d6da; border: 1px solid #f5c6cb\">' +\n",
" '<p><strong>WebIO not detected.</strong></p>' +\n",
" '<p>Please read ' +\n",
" '<a href=\"https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/\" target=\"_blank\">the troubleshooting guide</a> ' +\n",
" 'for more information on how to resolve this issue.</p>' +\n",
" '<p><a href=\"https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/\" target=\"_blank\">https://juliagizmos.github.io/WebIO.jl/latest/troubleshooting/not-detected/</a></p>' +\n",
" '</div>'\n",
" );\n",
" }\n",
" </script>\n",
"</div>\n"
],
"text/plain": [
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(WebIO.setval({\\\"name\\\":\\\"hover\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"1604814652504308591\\\",\\\"type\\\":\\\"observable\\\"},filtered_data.out)) : undefined})); gd.on(\\\"plotly_unhover\\\",(function (){return WebIO.setval({\\\"name\\\":\\\"hover\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"1604814652504308591\\\",\\\"type\\\":\\\"observable\\\"},{})})); gd.on(\\\"plotly_selected\\\",(function (data){var filtered_data=WebIO.PlotlyCommands.filterEventData(gd,data,\\\"selected\\\"); return !(filtered_data.isnil) ? (WebIO.setval({\\\"name\\\":\\\"selected\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"16506455463898317743\\\",\\\"type\\\":\\\"observable\\\"},filtered_data.out)) : undefined})); gd.on(\\\"plotly_deselect\\\",(function (){return WebIO.setval({\\\"name\\\":\\\"selected\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"16506455463898317743\\\",\\\"type\\\":\\\"observable\\\"},{})})); gd.on(\\\"plotly_relayout\\\",(function (data){var filtered_data=WebIO.PlotlyCommands.filterEventData(gd,data,\\\"relayout\\\"); return !(filtered_data.isnil) ? (WebIO.setval({\\\"name\\\":\\\"relayout\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"8386376565731521516\\\",\\\"type\\\":\\\"observable\\\"},filtered_data.out)) : undefined})); return gd.on(\\\"plotly_click\\\",(function (data){var filtered_data=WebIO.PlotlyCommands.filterEventData(gd,data,\\\"click\\\"); return !(filtered_data.isnil) ? (WebIO.setval({\\\"name\\\":\\\"click\\\",\\\"scope\\\":\\\"2845923228676453660\\\",\\\"id\\\":\\\"2972377240707377890\\\",\\\"type\\\":\\\"observable\\\"},filtered_data.out)) : undefined}))}));\\n (WebIO.importBlock({\\\"data\\\":[{\\\"name\\\":\\\"Plotly\\\",\\\"type\\\":\\\"js\\\",\\\"url\\\":\\\"/assetserver/80e93471f280df210a5c6dda4a2b36fc829d3066-plotly-latest.min.js\\\"},{\\\"name\\\":null,\\\"type\\\":\\\"js\\\",\\\"url\\\":\\\"/assetserver/24f578911c07b6875768cb9a43d8547041c65d4e-plotly_webio.bundle.js\\\"}],\\\"type\\\":\\\"async_block\\\"})).then((imports) => handler.apply(this, imports));\\n}\\n\")]), Dict{Any,Any}(), nothing)], Dict{Symbol,Any}(:className => \"interact-flex-row interact-widget\"))], Dict{Symbol,Any}())"
]
},
"execution_count": 46,
"metadata": {
"application/vnd.webio.node+json": {
"kernelId": "3309d807-07e1-438f-baaa-a9d0df7f1c22"
}
},
"output_type": "execute_result"
}
],
"source": [
"Interact.@manipulate for ϵ=widget([10.0^i for i in (-4):(-2)], label=\"ϵ\"), σ=widget([5*10.0^i for i in (-2):(-1)], label=\"σ\")\n",
"# plt = Plots.plot()\n",
" plt = PlotlyJS.Plot([\n",
" PlotlyJS.scatter(;x=1:length(results[0.5][ϵ].test_acc), y=results[0.5][ϵ].test_acc, name=\"test\", linewidth=0.5),\n",
" PlotlyJS.scatter(;x=1:length(results[0.5][ϵ].train_acc), y=results[0.5][ϵ].train_acc, name=\"train\", linewidth=0.5)\n",
" ])\n",
"# Plots.plot!(plt, 1:length(results[σ][ϵ].test_acc), results[σ][ϵ].test_acc, label=\"test\", linewidth=0.5)\n",
"# Plots.plot!(plt, 1:length(results[σ][ϵ].train_acc), results[σ][ϵ].train_acc, label=\"train\", linewidth=0.5)\n",
" PlotlyJS.plot(plt)\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import Pkg; Pkg.add(\"WebIO\")\n",
"import WebIO\n",
"cd(joinpath(dirname(pathof(WebIO)), \"..\", \"assets\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# using Pkg\n",
"# cd(joinpath(dirname(pathof(WebIO)), \"assets\"))\n",
";jupyter labextension install webio\n",
";jupyter labextension enable webio/jupyterlab_entry"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ϵ_slider = slider([10.0^i for i in (-4):(-2)], value=0.01, label=\"ϵ\") \n",
"# σ_slider = slider([5*10.0^i for i in (-2):(-1)], value=0.5, label=\"σ\") \n",
"\n",
"@demo for ϵ in ϵ_slider#, σ in σ_slider\n",
" SimplePlots.plot!(;x=1:length(results[0.5][ϵ].test_acc), y=results[0.5][ϵ].test_acc, label=\"test\", linewidth=0.5)\n",
" SimplePlots.plot!(;x=1:length(results[0.5][ϵ].train_acc), y=results[0.5][ϵ].train_acc, label=\"train\", linewidth=0.5)\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"@webio": {
"lastCommId": "f38918d57f81452f915baaee0eb6fbf9",
"lastKernelId": "3309d807-07e1-438f-baaa-a9d0df7f1c22"
},
"kernelspec": {
"display_name": "Julia 1.5.3",
"language": "julia",
"name": "julia-1.5"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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