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.ipynb_checkpoints/
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PGFPlotsX_Examples.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# まえがき\n",
"\n",
"PGFPlotsXはリポジトリのREADMEにも記述があるように，pgfplotsの文法との類似性を意識して作られています．これはpgfplotsのマニュアルがそのまま転用できたり，ネット上にある多くのexampleを参考に図を作成できることを意味します．このノートブックの役割として，PGFPlotsXの入門者を対象に，基本的な図の作成方法を提示することでライブラリ利用のハードルを下げることを目標としています．\n",
"\n",
"\"目的のグラフ描画はどのコマンドで実現されるか\"を念頭に，目的のグラフに対して作成例を1つ2つ挙げる，という記述をしています．これらを検索キーワードに，詳細なオプション等は各自で調べて貰えればと思っています．\n",
"\n",
"以下の実行環境でこのノートブックを作成しています．"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Julia Version 1.3.1\n",
"Commit 2d5741174c (2019-12-30 21:36 UTC)\n",
"Platform Info:\n",
" OS: Linux (x86_64-pc-linux-gnu)\n",
" CPU: Intel(R) Core(TM) i5-8400 CPU @ 2.80GHz\n",
" WORD_SIZE: 64\n",
" LIBM: libopenlibm\n",
" LLVM: libLLVM-6.0.1 (ORCJIT, skylake)\n",
"Environment:\n",
" JULIA_NUM_THREADS = 6\n"
]
}
],
"source": [
"versioninfo()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[32m\u001b[1m Status\u001b[22m\u001b[39m `~/.julia/environments/v1.3/Project.toml`\n",
" \u001b[90m [d38c429a]\u001b[39m\u001b[37m Contour v0.5.1\u001b[39m\n",
" \u001b[90m [31c24e10]\u001b[39m\u001b[37m Distributions v0.22.5\u001b[39m\n",
" \u001b[90m [7073ff75]\u001b[39m\u001b[37m IJulia v1.21.1\u001b[39m\n",
" \u001b[90m [b964fa9f]\u001b[39m\u001b[37m LaTeXStrings v1.1.0\u001b[39m\n",
" \u001b[90m [8314cec4]\u001b[39m\u001b[37m PGFPlotsX v1.2.4\u001b[39m\n"
]
}
],
"source": [
"using Pkg;\n",
"Pkg.status([\"Contour\", \"IJulia\", \"LaTeXStrings\", \"PGFPlotsX\", \"Distributions\"])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"using LinearAlgebra, PGFPlotsX, LaTeXStrings, Random, Distributions, Printf\n",
"Random.seed!(0);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 部分適用のための関数\n",
"\n",
"また本質的ではありませんが，表記の簡単のために次の関数を定義しておきます．以下の`lprtl`関数は部分適用(partial application)のための関数です．\n",
"以下の関数は[こちらのページ](https://michaellindon.github.io/lindonslog/programming/partial-application-functions-julia/index.html)で学びました．\n",
"\n",
"ある配列，例えば`[1,2,3]`があって，これの全要素に`sin`を適用して，`log`を取って，最後に`1`を足す，みたいなことをしたい場合，愚直に書くのであれば\n",
"```julia\n",
"log.(sin.([1,2,3])).+1\n",
"```\n",
"ですが，パイプライン演算子を使えば\n",
"```julia\n",
"([1,2,3] .|> sin .|> log).+1\n",
"```\n",
"のように書けます．ここでネックなのは，`1`を足す，という部分のみ，`sin`や`log`と同様に記述することができません．無理やりこれをしようと思うと，\n",
"```julia\n",
"[1,2,3] .|> sin .|> log .|> (x -> x+1)\n",
"```\n",
"となるのですが，これは個人的に好きでないです．Haskellなどのように，`(+ 1), (1 +)`で1引数関数にしてほしいところですが，Julialangにこの機能はありません．\n",
"以下の`lprtl, rprtl`関数によって次のように記載することができるようになります．\n",
"```julia\n",
"[1,2,3] .|> sin .|> log .|> lprtl(+,1)\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"#7 (generic function with 1 method)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lprtl = (f, a...) -> (b...) -> f(a..., b...)\n",
"rprtl = (f, b...) -> (a...) -> f(a..., b...)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 配列の配列を，展開して配列とする方法\n",
"`[[1,2], [3,4], [5,6]]`を`[1,2,3,4,5,6]`へ展開する方法について記述しておきます．\n",
"```julia\n",
"vs = [\n",
" [i, i+1]\n",
" for i in 1:2:6\n",
"]; # vs = [[1,2], [3,4], [5,6]]\n",
"\n",
"v = [vs...;] # v = [1,2,3,4,5,6]\n",
"maximum(v) # 6\n",
"max(v...) # 6\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 動作確認\n",
"\n",
"簡単なプロットは次のようにして描画できます．"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 0; 2 1; 3 0; 4 2], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X=[\n",
" 1 0\n",
" 2 1\n",
" 3 0\n",
" 4 2\n",
"];\n",
"\n",
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" Table(\n",
" x=X[:,1],\n",
" y=X[:,2]\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 図の保存\n",
"\n",
"`pgfsave`を使うことで保存ができます．"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"X=[\n",
" 1 0\n",
" 2 1\n",
" 3 0\n",
" 4 2\n",
"];\n",
"\n",
"fig = @pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" Table(\n",
" x=X[:,1],\n",
" y=X[:,2]\n",
" )\n",
" )\n",
" )\n",
");\n",
"# pgfsave(\"out.pdf\", fig);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# マーカーの指定"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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"</clipPath>\n",
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"</clipPath>\n",
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"</clipPath>\n",
"</defs>\n",
"<g id=\"surface1\">\n",
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"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 1.359732 44.757091 L 4.180989 47.574424 M 1.359732 47.574424 L 4.180989 44.757091 \" transform=\"matrix(0.995512,0,0,-0.995512,35.599496,147.802298)\"/>\n",
"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 23.403987 133.091067 L 26.22132 135.908399 M 23.403987 135.908399 L 26.22132 133.091067 \" transform=\"matrix(0.995512,0,0,-0.995512,35.599496,147.802298)\"/>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"mark\" => \"x\"), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.8236475079774124 0.20347655804192266; 0.9103565379264364 0.042301665932029664; … ; 0.17732884646626457 0.3618283907762174; 0.278880109331201 0.9732164043865108], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {mark=\"x\"},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# マーカーの除去"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"no_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.5858115517433242 0.6554484126999125; 0.5392892841426182 0.5758873948500367; … ; 0.910046541351011 0.9677995536192001; 0.16703619444214968 0.7676903325581188], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {no_marks},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# マーカーのみ描画(散布図)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
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"</clipPath>\n",
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"</clipPath>\n",
"</defs>\n",
"<g id=\"surface1\">\n",
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"</g>\n",
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"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"only_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.46930370935301835 0.2679846344919068; 0.06236755817015882 0.06684644402498341; … ; 0.767601895961374 0.6052967398293401; 0.043141023329413164 0.13574455851185352], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {only_marks},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# マーカーサイズの指定"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"mark\" => \"*\",\"mark_size\" => 10), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.838117753907359 0.7670696322682211; 0.9147120238969264 0.8019235854122897; … ; 0.7228497594213787 0.48466052213279887; 0.1196525672223625 0.8991991479715158], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" mark=\"*\",\n",
" mark_size=10\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# マーカーの色指定"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
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"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"only_marks\" => nothing,\"mark_options\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"red\" => nothing), true)), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.951690700362799 0.7766742218683131; 0.8011185163108001 0.1048226490565447; … ; 0.11426876182995338 0.18411485558080476; 0.07955447119057157 0.3121451099216308], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" only_marks,\n",
" mark_options={red}\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 白抜きマーカー"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"<path style=\"fill:none;stroke-width:0.99628;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,100%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 98.290263 53.672474 C 98.290263 56.423088 96.06152 58.651831 93.306982 58.651831 C 90.556367 58.651831 88.327624 56.423088 88.327624 53.672474 C 88.327624 50.92186 90.556367 48.689193 93.306982 48.689193 C 96.06152 48.689193 98.290263 50.92186 98.290263 53.672474 Z M 98.290263 53.672474 \" transform=\"matrix(0.995516,0,0,-0.995516,35.599662,147.795103)\"/>\n",
"<g clip-path=\"url(#clip-1582954814696296-5)\" clip-rule=\"nonzero\">\n",
"<path style=\"fill:none;stroke-width:0.99628;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,100%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 109.284872 134.491877 C 109.284872 137.246415 107.052205 139.475158 104.301591 139.475158 C 101.550977 139.475158 99.322234 137.246415 99.322234 134.491877 C 99.322234 131.741262 101.550977 129.512519 104.301591 129.512519 C 107.052205 129.512519 109.284872 131.741262 109.284872 134.491877 Z M 109.284872 134.491877 \" transform=\"matrix(0.995516,0,0,-0.995516,35.599662,147.795103)\"/>\n",
"</g>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"mark\" => \"o\",\"mark_size\" => 5,\"mark_options\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"line_width\" => 1,\"draw\" => \"green\"), true),\"blue\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.19640742703220093 0.7350038044058131; 0.8735809112632831 0.548342114623342; … ; 0.5867124396397687 0.6023746021111653; 0.6326955174849529 0.7913462490414747], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" mark=\"o\",\n",
" mark_size=5,\n",
" mark_options={\n",
" line_width=1,\n",
" draw=\"green\"\n",
" },\n",
" blue\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`mark=o`とすると，塗りつぶしのない白抜きマーカーになり，散布図においては期待する結果が得られます．\n",
"\n",
"しかしline+marker図の場合，上記のようにmarker内でlineの色が見えてしまい見栄えが良くありません．この場合は下のように，`mark=*`として`fill=\"white\"`で塗りつぶせば期待した結果が得られます．"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
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"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"mark\" => \"*\",\"mark_size\" => 5,\"mark_options\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"line_width\" => 1,\"draw\" => \"green\",\"fill\" => \"white\"), true),\"blue\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.04912193901316875 0.9388569303494545; 0.48276146782949847 0.7837260309016443; … ; 0.8422557594578175 0.6221557939669518; 0.16910729451857898 0.30680415689806817], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" mark=\"*\",\n",
" mark_size=5,\n",
" mark_options={\n",
" line_width=1,\n",
" draw=\"green\",\n",
" fill=\"white\"\n",
" },\n",
" blue\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 線の種類変更"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
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"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"dashed\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.7963633990166934 0.4799481236784777; 0.5058741376644247 0.4683970163381419; … ; 0.47935649090647914 0.6442110258372615; 0.06822341709242075 0.6692753552886208], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {dashed},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 線の太さ変更"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
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tXFBfejsi3b59u5GRUbcrfkeOHMn7saCgICUlhffj4cOH1dTUnj9/zv2xvr5+yJAhGRkZuCQexElaWlq3i/BI4ebmNsB3YfOkp6dTeEqRTqe7u7vzckNU9HVJfF1dnZ6eHu9M5Zs3b4yMjBITE3krcL+Jv3jxgndJ8JQpU8rLyzkcTkdHh4eHx8qVK/vYNqITRE56erqsrCzp8eHq6kpJbj58+JDayyQZDMbt27dFcSS848lJ9+/fd3Jy2rt3b2Ji4ldffXXw4EH+f42Li1u2bBmbzeYdZs6fPz8iIiImJsbR0TEmJqbvbSM6QbRcvXq125XOpHB0dGxraxtsc0Fjx45NTk4W3cHQr4fOvXjx4v79+ywWqz8llpWV3b9/v7W19Z1rIjpBhOTk5CgqKpKeIHZ2dv35ZSHRmzdvoqKiKDylqKOjExcX19nZKdLjQV1dncah6N2eNBplmwZ4L3fu3LG1teVep0wiS0vL1NTUbjeeiPFckLy8/E8//bRhwwZB/BEa+IsB8G4igL7cu3ePwWCQnpszZsxISUkZsNxMT08PCAi4e/cuVXNBHh4eW7Zs0dbWFpuBgegE6NWjR48cHBzq6urILdbc3DwlJUUQZ07f9vDhw8DAwHPnzlE4F7Rt27ZJkyaJ2dig49cDoEdFRUU2Njbdrm7+eJMnT75w4cIAnG0sLy9funSpiYkJVbk5bty4c+fOMZlM8ctNHHUC9KykpMTOzq68vJzcYk1MTNLT09XU1ARa+Tdv3uzevXvz5s3dbggcMLq6uj///PMPP/wgiHtVEZ0AQqq0tNTa2pr06RRjY+O0tDR1dXXB1byrq+v48ePBwcEVFRWU7DpxmgtCdAK8h6qqKnt7e9KfMzty5MiMjIyhQ4cKrubp6elr1qy5d+8eJfuNOxcUHR0t0DYiOgGEUXV1tY2NTWFhIbnFGhgYMJlMHR0dAVX7wYMHgYGB58+fp2q/MRiM3377beLEiYNnqGCaCOB/amtrbW1tHzx4QG6xenp6GRkZhoaGgqhzWVnZ0qVLJ06cSFVujh8//vz580wmc1DlJo46Af6noaFh9uzZBQUF5BarpaXFZDJHjBhBeoUxF4ToBKBYY2Ojvb39jRs3yC1WU1Pz8uXLY8aMIbdY7lxQUFAQ6RdO9RN3LigkJGRgLk1FdAIIo5aWFhcXl7y8PHKLVVFRSU1NHTduHLnFUjsXJCkp6e3tHR4ePkjmghCdAD1rbW11dna+cuUKucUqKyszmUxTU1MSy7x//35gYOCFCxeo2lcMBmP79u0mJiYYNgSmiWAwY7FYbm5uGRkZ5BarpKR08eLFqVOnklUgdy5o0qRJVOXmlClTLl++zGQykZs46oTBrqOjw83NjfQwkpOTS0pKMjc3J6U07lzQpk2bmpubKdlLenp6oaGhg3YuCNEJ8P9hs9menp7JycnkFisrK5ucnPzO93f1R2dn56FDh8LCwqiaC1JQUFizZk1QUJAgHowvDqh6ViiBRx0DRTo7OxcsWED6r5K0tPS5c+dIqSG1X40lJSV9fHwqKysxVD7qKfGIThAnXV1dixcvJj1upKSkzp49+/HVu3Hjxueff07hsRSDwcjPz8c4QXQC/H+56evrS3rcSEhInDx58iPrVlpa6uPjQ+EpxalTp/bxCltAdMLgzc3ly5cLIjePHz/+MRVramoKCwuj8JSinp5eXFwc7xWNgOgE+D9BQUGkhw6NRvvjjz8+uEodHR1xcXFaWlpUhaaCgkJYWNgAv1oO0YnoBJGxYcMGQeTm3r17P7hKTCZzwoQJVIWmlJSUj49PVVUVxgaiE6Bn4eHhgkifrVu3flh9rl+/bm1tTe1cUEFBAQYGohOgV9u3bxdE+kRGRn5AZUpKSnx8fOh0OoVzQZmZmRgViE6AvuzYsUMQARQREfG+NeHOBQ0ZMoSq0NTX18dcEKIT4N0OHjxIo9FIz6DQ0ND3qgaLxYqLi/vkk0+oCk0VFZWoqCjMBSE6Ad7tyJEjgvhe7O/v/17VYDKZ48ePx1wQohPRCSIgPj5eUpL85zP4+fn1vw55eXmk3Mz+wZydnYuKijAYEJ0A/XL69GlB5Ka3t3dXV1d/KlBSUuLp6SmIcwX9NG3atKysLIwERCdAf6WkpMjIyJAeRgsXLuzPBEt9fX1QUBCFc0EGBgZHjx7tZ8QDohOAw+Fw0tLSBBFbbm5uHR0dfW+a8rkgVVVVzAUhOgHeW3p6uiBuA3d1dX1nbiYlJY0cOZLauaDq6mqMAUQnwPu5evWqIN7O6Ojo2NbW1sd28/LyZs2aRe1c0JMnTzAABj468W4iEHnXrl1zdHQk/RUUdnZ2iYmJvZ05LSkp8fLyMjc3J/2VcP1kZmZ25cqV5ORkIyMjjIGBhxdsgGi7c+eOk5NTU1MTucVaWlomJib2eOb01atXW7Zs2bFjR1tbG1VzQREREdRO4gOiE0TYvXv3GAxGfX09ucXOmDEjJSVFXl6+2/KOjo7Dhw+HhITU1NRQ0l41NbXAwEB/f39BXEUAiE4YFB49euTg4FBXV0dusebm5ikpKW+fOU1OTl61atXTp08paayUlNSiRYs2bdqkqamJrkd0AnygoqIiGxsb0t8WOXny5AsXLigpKfEvzMvLCwgI+Oeff6hqrLOzc2xsLM5pChVME4HoKSkpsbOzKy8vJ7dYExOT9PR0NTU1/g15eXlNnz6dqtw0Nzf/559/MBeEo06Aj1VaWmptbf3ixQtyizU2Nk5LS1NXV+f+WF9fHx0dHRsb297eTkkzR40atXnzZjc3N8wFIToBPlZVVZW9vX1xcTG5xY4cOTIjI2Po0KEE5oIA0Qliprq62sbGprCwkNxiDQwMmEymjo4Oh8M5derUunXrqJoLkpaW9vX1DQ8PV1FRQXcjOgFIUFtba2tr++DBA3KL1dPTy8jIMDQ0zM3NDQgI+PfffylpHY1Gc3Nzi4qKGjFiBPoa0QlAjoaGhtmzZxcUFJBbrJaWFpPJZLPZ8+fPP3XqFPf+4IE3ffr0bdu2ffbZZ+hoRCcAaRobG+3t7W/cuEFusZqamgkJCUeOHKFwLsjY2HjTpk2YC0J0ApCspaXFxcUlLy+P3GLl5eW/+OKLOXPmvH79mpJ2YS5I1NGo+pJCo1G2aRCh3HRycsrMzBSnRg0ZMsTf3z84OFhZWRldLKI0NDRw1AlCisViubu7i1NucueCtmzZMnz4cPQvvrADkK+jo8PNze3ChQti0yILC4tt27bNmDEDnSsecCMmCB02m+3p6ZmcnCwezTE2No6Pj8/OzkZu4qgTQIC56eXl9ffff4tBW9TV1deuXbtq1SppaWn0LKITQFA4HI6vr++JEydEvSHc+4I2btyIuSBEJ4DAc3PZsmUHDhwQ6VZw54Kio6MNDQ3Rp4hOAIHnpp+f3++//y7SrbCxsdm6daupqSk6VOxhmgiEwrp16/bs2SO69R89enR8fPylS5eQmzjqBBggISEhW7ZsEdHKa2hohISELF++XFISv02IToCBsnHjxs2bN4tizeXk5Pz8/NavX9/thRyA6AQQrJiYmLCwMJGrNp1OnzdvHuaCEJ0AFNi5c+fq1atFrtq2trZbt2799NNP0YOIzp5xOJz9+/eXlpbKysq2tLT4+/traGj0vf6RI0devnzZ2tra1dW1ZMkSvIsKenPo0CF/f3/RqvOYMWM2btzo7u6O7gOC07tvv/02IiKC+/+3bt0aPXp0RUVFH+uvXLkyPz+f+/8VFRU2NjY5OTm9rdz3pkG8HTlyhE4Xpas7NDQ0YmNjOzo60HfA4XDU1dV7za+zZ88qKyuzWCzekqVLl7q7u/e2/rlz52JiYviX3Lt3z87ODtEJ3cTHx4vQZLScnFxQUFBDQwM6Dvijs9cRfOLECUtLSykpKd4SKysrb2/v1tZWWVnZt9fPzc3t7OzkX2JkZPTs2TMc1wO/M2fOLFiwoNtQEU7cuaCtW7cOGzYMHQfdh0ePS7u6uphMZrfbb7W1tdva2np7fqKWltZvv/22d+9e3gOMk5OTv/jiC+xi4ElNTRWV3GQwGDdv3oyPj0duwntEZ01NTX19vYKCAv9CbpI+fvy4x494eHh88skny5cvt7a2fvz4cXJycnp6emRkJHYxcDGZTFdXV6reAtR/Y8eOjY+PZzKZkydPRq9Bb3r+wt7U1EQQhLy8PP9CCQkJgiAaGhp6/IiKiso///zzzTffXLlyZeLEiTNmzGAymdyPAFy6dOnLL79sa2sT5kpy7wv66aefMG7hA6OTO8S7PWSQzWYTBNHa2tpbWXJycqamprNmzdq9e3dGRsb06dMTExP19PR6Wz88PLzH5VZWVtbW1ugbsZGdnT137tw+Rg7lcF8QvC0zMzMrK6vHf+rs7Ox5mvv58+cEQQQEBPAv5J7l3Lx5c48fyc/PnzVrVm1tLYfDefr0KYPBIAjC3Ny8q6sLM+yDWU5OjqKiovCesaLTPT09y8vL0VPwXjPs9N6+fb99gNnY2Mg74/k2Hx+fTZs2qaurEwQxYsQIJpMZHh6em5ubmpqKP1+D1p07d5ycnLjnf4QQg8G4devWsWPHtLW10Vnwfn90e1yqrKw8ZsyYqqqqt6PTzMysx3Oj+fn5M2fO5F/4888/z5o1q7dpJRB79+7dYzAY9fX1Qli3sWPHJicnM5nMSZMmoaeAtOgkCMLV1bW4uJh/SUVFhbq6+pQpU7g/slgs3m+FrKwsnU5/++DCwMBgwoQJ2MuD0KNHjxwcHOrq6oStYjo6OnFxcfn5+c7OzugmID86Fy5c+ODBA/70TExMXL16Ne/+OSsrK319/ZqaGoIgJCUlv/nmm5iYGP4SysvL6+vrZ82ahb082BQVFdnY2FRWVgpVreTl5YOCggoLC318fDCHDh+JxruC/W3x8fH79u3bu3evtrb25s2bq6urDx48yLuFztvbOzc3Ny8vj3sNE4vF8vX1lZKS8vDwUFVVzc3Nzc7ODg8P19fX73nDtL42DaKrpKRk1qxZL168EKIDBDrdw8Njy5YtOKcJpNDQ0HhHftXU1KSkpDQ3N1tYWPTnKVtPnjy5fv16S0vLxIkTp02b1ldmIzrFUWlpqZWVVbdTPdRiMBi//fbbxIkT0TswcNEpwMNdRKfYqaqqsra2LiwsFJL6jBs3buvWrbgbGAQRnXitG5CjurraxsZGSHJTV1c3Li7u3r17yE0QEDwlHkhQW1tra2v74MEDymsiLy//008/hYSEdHsCAwCiE4RLQ0PD7NmzCwoKqK0Gdy4oOjp66NCh6BRAdIJQa2xstLe3v3HjBrXVYDAY27dvNzExQY/AAP2pxi6AD9bS0uLi4pKXl0dhHUxNTS9fvsxkMpGbgOgE0TjedHJyunLlClUV0NfXP3bs2PXr1z///HN0ByA6Qdh1dXUdO3Zs9OjRvb0yQNDk5eXDwsIePXrk6ekpWq+HA7GBc53wftLT01evXp2fn0/NeJWU9Pb23rhxo5aWFvoCEJ0gAm7duhUQEJCRkUFVBRgMRkxMDB4oA/jCDqLh5cuXS5cuNTMzoyo3p0yZkpGRwWQykZuAo04QAc3Nzdu2bYuOjqbq9Rh6enqhoaGLFy/GOU1AdIII6OzsPHTo0M8//9ztidcDRkFBYc2aNUFBQbKysugOQHSCCEhPT1+1ahVVNwhJSUktWrQIc0GA6ASRcfPmzYCAAKquOiIwFwQiAueP4H94c0FU5ebUqVMzMzMxFwQ46gTRQPlckL6+fkhICOaCANEJoqGjo+Pw4cOUzwUFBwcPGTIE3QGIThAB6enp/v7+9+/fp2Tr3LmgiIiITz75BH0BiE4QATdu3AgICMjKyqKqAs7Oztu3bx81ahT6AkQUTi0NLqWlpUuXLjU3N6cqN6dNm5aVlZWcnIzcBBx1ggjgzgVt2bKlra2Nkgro6+tv2rTJ09OTRqOhOwDRCcKOOxcUGhpaXV1NSQVUVVWDgoJWrlyJuSBAdIJoOH369Lp164qKiqiqwLfffrt79241NTX0BSA6QQRcv36zH9e0AAAfNUlEQVQ9ICCAwqe4EwTh5uZ27NgxSUkMMxA3mCYSQ6WlpV5eXubm5tTmpqur68mTJ5GbgKNOEHavXr3asmXLjh07qJoL4nF0dERuAqIThB13LigkJKSmpobyytjZ2SUmJsrIyKBfANEJwis5OXn16tVPnjwRhspYWlomJiZiMh3EG851ira8vLxZs2bNmTNHSHJzxowZKSkp8vLy6BpAdIIwKikp8fLymj59+j///CMkVTI1NT1//ryCggJ6B/CFHYQOdy4oNja2vb1deGo1adIkJpOpoqKCDgJEJwgXoZoL4mdiYpKeno7r3gHRCUInOTl51apVT58+FbaKGRsbp6WlaWhooI9g8MC5ThGQm5s7c+bMOXPmCGFujhw5MiMjY+jQoegmQHSCsHjx4oWXl5eFhcW///4rhNUzMDBgMpk6OjroKcAXdhAK9fX10dHRwjYXxE9PTy8jI8PQ0BCdBYhOoB6Lxdq3b98vv/zy+vVroa2klpYWk8kcMWIE+gsQnUAxDodz6tSp4ODgZ8+eCXM9NTU1L126NGbMGHQZIDqBYteuXQsICLh69aqQ11NFRSU1NXX8+PHoMhjMME1EvaKiovnz58+YMUP4c1NZWZnJZJqamqLXAEedQBnhnwviJy8vf+7cualTp6LjABCd1BCJuSB+cnJy58+ft7S0RN8BIDopwJ0LCgoKKi4uFpU6y8rKJicnW1lZofsAEJ0UuHbt2po1a7Kzs0WoztLS0gkJCTY2Nug+AB5MEw2Qx48fz58/38LCQrRyU0pKKiEhwcnJCT0IgKPOAVVXV7d169aYmBgWiyVaNZeQkDh27NicOXPQiQCIzoHDnQsKCwtraGgQucpLSEgcPXr0m2++QT8CIDoHiCjOBfGj0Wj79u3z8PBAVwIgOgdITk7OmjVrcnJyRLT+NBptz549S5YsQVcC9AbTRGR69OgR974g0c1NgiCio6N//PFH9CYAjjoFrq6ubuPGjXv37u3s7BTphkRGRgYEBKBDARCdgtXa2rpz587IyEhRnAvqJiIiIjg4GH0KgOgUIO5cUGBg4PPnz8WgOQEBASEhIehWAESnAF2+fDkgIOD27dvi0Rx/f/+tW7eiWwH6CdNE762wsHD+/Pm2trZik5t+fn4xMTHoWQAcdQpEbW1tRESEGMwF8fP29t6xYwc6FwDRSb6WlpZdu3b9+uuvjY2N4tSuhQsX7t+/n0ajoYsB8IWdTF1dXYcPHzY2Ng4ODqYkN+Xl5c3NzQVR8rfffnvw4EE6HWMAgOzoZLPZOTk5aWlpr1696nvNsrKyixcvitneuXTp0pQpU7y9vcvKyijoGzrd3d19586d9+7dI71wV1fXY8eOSUhI4HcAgOQv7Dk5OaGhoWvWrNHU1Fy5cuW4ceP6uOgvNzd33rx5ampqSkpKkpL/V6ysrOzNmzelpKREa78UFhb+/PPPCQkJVFWAwWBs27btzZs3Dg4Ora2t5Bbu6Oh48uRJ/m4CAHKis7q62tnZ+erVq9x3xh45csTMzExHR8fLy6vH9R8+fDhu3DgtLS06nc47d/bo0SN/f3/Ryk3K54LGjh0bHR3t7Ox87do1R0fH5uZmcsu3s7NLTEyUkZHB6Af4cJxehISEmJqa8i+JiYkxMjLqbf3ly5d3dHTwLykvL/fy8upt/T42TZU3b95ERUUpKSlR1Rc6OjpxcXGdnZ0cDuf27dtqamqkb8LS0rK5uZkDAB9BXV291/yaMmWKm5sb/5KkpCSCIB4/ftzj+r///jv/j11dXR4eHpWVlSIRnWw2Oz4+3sDAgKrQlJeXDwoKamxs5Nbn7t276urqpG/FwsKiqakJ4x5AUNHZ1NREo9G+//57/oW5ubkEQezfv78/RW/fvj0pKamPFYQnOplM5qRJk6gKTTqd7unpWV5ezqtPYWHh0KFDSd+QqalpfX09Bj0AKdHZ8wz7q1evOByOvLw8/0JpaWmCIOrq6t75W1pWVpaWlubi4iLkJysePnzo4uJiZ2d39+5dquaCbt26dezYMW1tbe6SoqIiGxubyspKcjc0adIkJpOpqqqKM1QAApwm4l7AKCcn1+34iCCI/jwfaN26dcuXL3/nauHh4T0ut7Kysra2Fmizy8vLw8PDDx48yGazKdnv48aNi46O7va6tJKSEjs7u/LycnK3ZWJikp6eLogzpwBiLDMzMysrq8d/6uzs7Plb86NHjwiCWLt2Lf9C7uN7f/75574PZZ89e6aoqNhtykh4vrA3NzdHRUUpKipS1R+6urq8uSB+JSUlw4cPJ31zxsbGFRUV+IYFQO4X9p6POrmzzN2uzuEeir5zAvrQoUOjR48WwmsGu7q6jh8/HhwcXFFRQdVc0E8//bRhw4a3g7uqqsre3p70FxmNHDkyIyNDEGdOAfCFvQfq6upycnLd7iDiRqeenl7fJZ46dUoQR08fKT09fc2aNYK4Lac/6HS6h4dHdHR0jylWU1NjY2NTWFhI7kYNDAyYTKaOjg5GOQD5v9Q9LpWSknJwcOh2dNbY2Ein021tbfsorra2trCwUKimIx48eODs7GxnZ0dVbjIYjNu3bx87dqzH3KytrbW1tX3w4AG5G9XT08vIyDA0NMQQBxi46CQI4quvvrp58yb/d/br16/PnDlTQ0OD++Nff/0VHBzMPWvJ8/DhQ4IghCo6T548ef78eUo2PX78+PPnzzOZzIkTJ/a4QkNDw+zZs/Pz88ndrpaWFpPJHDFiBMY3gKD0dh60s7Nz5syZu3fv5v5YXFysq6ubn5/PW8HIyIggiOLiYv5PJSYmEgTh7+//zvOsxEBNEzU1NQ38yb7e5oL4NTQ0mJmZkb5pTU3NgoICnMgHoGCaiCAICQmJ1NTUiIiIdevWKSoqPn36NDU1dcKECbwV/vOf/xQXF3f7Sjh27FgDA4PPPvtMeP42KCgohIWFDdjbcblzQSEhIQoKCn2s1tLS4uLikpeXR+7WVVRUUlNTx48fj2MCAIGidfvGPXAbpg3cptls9qRJk+7fvy/QrUhKSnp7e4eHh7/zILe1tdXJySkjI4PcCigrK6enp0+dOhXDGkCgNDQ0BsVjbiUkJKKiogS6Ce59QXFxce/MTRaL5ebmRnpuysvLnzt3DrkJMDAGyxPCnZ2dGQyGIEqeMmXK5cuXmUymiYnJO1fu6Ohwc3O7cOECuXWQk5M7f/68paUlBjQAopNk27ZtI/dlEnp6enFxcbm5uZ9//nk/zxt4enomJyeT2y5ZWdnk5GQrKyuMZgBEJ/kmTZr03XffkVIUd+rp8ePHPj4+/XxHBZvN9vLy+vvvv8ltlLS0dEJCgo2NDYYywEAaFNNEPGVlZcbGxi0tLR9cAncuaOPGjVpaWv3/FIfD8fHxOXDgALnNkZKSOnXq1Jw5czCOAQbSYJkm4tHV1fX39//gj3PvC4qLi3vf3Fy2bBnpuSkhIXHs2DHkJgCOOgdCU1OTsbHx+z4Qc+rUqVu3bv2AR+FxOBw/P789e/aQnptHjx718PDACAbAUedAUFRUDA0N7f/6vLmgD3uE6Lp160jPTRqNtm/fPuQmAI46B1Q/r5BXUFBYs2ZNcHDwkCFDPmxDISEhmzdvJn2/7dmzZ8BujgKAHo86KXtBEEHpu4nOnj3bx36RkpLy8fGpqqr6mE309gz8j7R161bcQQxA+T3sgzQ6ORxOb0/PYzAYH//4jO3btwsiNyMjIzFqAYQhOumD9pD77Svkp06dmpmZyWQyP/LxGbt27Vq9ejXpFY6IiAgODsZ3JQBhMHijc/LkyQsWLOD+v76+Pncu6OPvyTl06NDKlStJr21AQEBISAjGKwCmiSjbNE9ZWZmZmdmKFStWrlz5wXNB/I4ePert7d3V1UVuPf39/WNiYjBYAYRnmmhQRydBECwWi/t++Y934sQJLy8v0t9O7Ofnt3PnTgxWAESnEEUnWc6cOfP11193e4fox/P29j5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"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"line_width\" => 10), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.09479186551379559 0.6821935901697289; 0.9488838151206662 0.9293597577149693; … ; 0.17740896332315637 0.6517776347893842; 0.08002265274552212 0.596532097629072], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" line_width=10\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"lineを太くすると連結部分の描画が気になるところです．デフォルトでは角ばった連結となり，望んだものと違うかもしれません．このときは`line join`オプションで検索してみるとよいでしょう．"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
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"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"line_width\" => 10,\"line_join\" => \"round\"), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.4792609158905863 0.2161052678391404; 0.0632370551390915 0.8631896591631327; … ; 0.3824528206459128 0.6999897089476348; 0.9765501230411475 0.8502054654407449], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" line_width=10,\n",
" line_join=\"round\"\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 線の色変更"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"</symbol>\n",
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"<path style=\"stroke:none;\" d=\"\"/>\n",
"</symbol>\n",
"<symbol overflow=\"visible\" id=\"glyph-1582954814696301-1-1\">\n",
"<path style=\"stroke:none;\" d=\"M 1.90625 -0.53125 C 1.90625 -0.8125 1.671875 -1.046875 1.375 -1.046875 C 1.09375 -1.046875 0.859375 -0.8125 0.859375 -0.53125 C 0.859375 -0.234375 1.09375 0 1.375 0 C 1.671875 0 1.90625 -0.234375 1.90625 -0.53125 Z M 1.90625 -0.53125 \"/>\n",
"</symbol>\n",
"</g>\n",
"<clipPath id=\"clip-1582954814696301-1\">\n",
" <path d=\"M 0 0.320312 L 213.085938 0.320312 L 213.085938 174.394531 L 0 174.394531 Z M 0 0.320312 \"/>\n",
"</clipPath>\n",
"<clipPath id=\"clip-1582954814696301-2\">\n",
" <path d=\"M 23 0.320312 L 192 0.320312 L 192 162 L 23 162 Z M 23 0.320312 \"/>\n",
"</clipPath>\n",
"<clipPath id=\"clip-1582954814696301-3\">\n",
" <path d=\"M 19 0.320312 L 213.085938 0.320312 L 213.085938 162 L 19 162 Z M 19 0.320312 \"/>\n",
"</clipPath>\n",
"</defs>\n",
"<g id=\"surface1\">\n",
"<g clip-path=\"url(#clip-1582954814696301-1)\" clip-rule=\"nonzero\">\n",
"<path style=\" stroke:none;fill-rule:nonzero;fill:rgb(100%,100%,100%);fill-opacity:1;\" d=\"M 0 174.394531 L 213.882812 174.394531 L 213.882812 -0.332031 L 0 -0.332031 Z M 0 174.394531 \"/>\n",
"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696301-0-1\" x=\"118.046544\" y=\"171.089269\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
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"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696301-0-1\" x=\"3.306171\" y=\"31.154895\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696301-1-1\" x=\"8.264931\" y=\"31.154895\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696301-0-8\" x=\"11.019576\" y=\"31.154895\"/>\n",
"</g>\n",
"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(100%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 161.892071 -0.000983333 L 68.667217 6.55956 L 14.601589 134.498008 L 35.028736 73.09493 L 0.0012406 102.644842 \" transform=\"matrix(0.995535,0,0,-0.995535,35.600327,147.803709)\"/>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"red\" => nothing,\"no_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.7145890517231919 0.07362716161818517; 0.4394579359338935 0.1132182900932166; … ; 0.3401842212195725 0.5146689804348994; 0.23679985501360878 0.692970759120777], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" Plot(\n",
" {\n",
" red,\n",
" no_marks\n",
" },\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# タイトル，xラベル，yラベル"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"title\" => \"Hoge\",\"xlabel\" => L\"$x$ huga\",\"ylabel\" => L\"$y$\"), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 0; 2 1; 3 0; 4 2], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X=[1 0;2 1;3 0; 4 2];\n",
"@pgf TikzPicture(\n",
" Axis(\n",
" {\n",
" title=\"Hoge\",\n",
" xlabel=L\"$x$ huga\",\n",
" ylabel=L\"$y$\",\n",
" },\n",
" Plot(\n",
" Table(\n",
" x=X[:,1],\n",
" y=X[:,2]\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# ラベルのフォントサイズ変更"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
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" <use xlink:href=\"#glyph-1582954814696303-0-1\" x=\"13.60467\" y=\"113.90821\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-1-1\" x=\"18.580064\" y=\"113.90821\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-0-2\" x=\"21.344948\" y=\"113.90821\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-0-1\" x=\"13.60467\" y=\"76.329554\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-1-1\" x=\"18.580064\" y=\"76.329554\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-0-4\" x=\"21.344948\" y=\"76.329554\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-0-1\" x=\"13.60467\" y=\"38.749899\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-1-1\" x=\"18.580064\" y=\"38.749899\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-0-6\" x=\"21.344948\" y=\"38.749899\"/>\n",
"</g>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,0%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 163.883331 134.491818 C 163.883331 135.590711 162.991703 136.48234 161.892809 136.48234 C 160.790006 136.48234 159.898377 135.590711 159.898377 134.491818 C 159.898377 133.389015 160.790006 132.497386 161.892809 132.497386 C 162.991703 132.497386 163.883331 133.389015 163.883331 134.491818 Z M 163.883331 134.491818 \" transform=\"matrix(0.998874,0,0,-0.998874,46.008158,148.035755)\"/>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,0%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 124.209771 99.182545 C 124.209771 100.285349 123.318142 101.176977 122.219249 101.176977 C 121.116445 101.176977 120.224817 100.285349 120.224817 99.182545 C 120.224817 98.083652 121.116445 97.192023 122.219249 97.192023 C 123.318142 97.192023 124.209771 98.083652 124.209771 99.182545 Z M 124.209771 99.182545 \" transform=\"matrix(0.998874,0,0,-0.998874,46.008158,148.035755)\"/>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,0%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 1.994087 0.00059923 C 1.994087 1.099492 1.098548 1.991121 -0.000345465 1.991121 C -1.099239 1.991121 -1.990867 1.099492 -1.990867 0.00059923 C -1.990867 -1.102205 -1.099239 -1.993833 -0.000345465 -1.993833 C 1.098548 -1.993833 1.994087 -1.102205 1.994087 0.00059923 Z M 1.994087 0.00059923 \" transform=\"matrix(0.998874,0,0,-0.998874,46.008158,148.035755)\"/>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,0%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 9.651143 67.858226 C 9.651143 68.96103 8.755603 69.852658 7.65671 69.852658 C 6.557817 69.852658 5.666189 68.96103 5.666189 67.858226 C 5.666189 66.759333 6.557817 65.867704 7.65671 65.867704 C 8.755603 65.867704 9.651143 66.759333 9.651143 67.858226 Z M 9.651143 67.858226 \" transform=\"matrix(0.998874,0,0,-0.998874,46.008158,148.035755)\"/>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,0%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 150.993823 130.886198 C 150.993823 131.985091 150.102195 132.876719 148.999391 132.876719 C 147.900498 132.876719 147.008869 131.985091 147.008869 130.886198 C 147.008869 129.783394 147.900498 128.891765 148.999391 128.891765 C 150.102195 128.891765 150.993823 129.783394 150.993823 130.886198 Z M 150.993823 130.886198 \" transform=\"matrix(0.998874,0,0,-0.998874,46.008158,148.035755)\"/>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-2-1\" x=\"119.792017\" y=\"195.425356\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696303-3-1\" x=\"6.772369\" y=\"82.957086\"/>\n",
"</g>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"xlabel\" => L\"$\\lambda$\",\"ylabel\" => L\"$\\lambda$\",\"xlabel_style\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"font\" => \"\\\\Huge\"), true),\"ylabel_style\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"font\" => \"\\\\tiny\"), true)), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"only_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.8497031958709513 0.7162691383894721; 0.6974056124492531 0.5285764697107829; … ; 0.2576252988200516 0.3620530982794181; 0.8002161278923636 0.6971063069555032], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" {\n",
" xlabel=L\"$\\lambda$\",\n",
" ylabel=L\"$\\lambda$\",\n",
" xlabel_style={font=raw\"\\Huge\"},\n",
" ylabel_style={font=raw\"\\tiny\"},\n",
" },\n",
" Plot(\n",
" {only_marks},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 描画範囲の変更"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
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"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"xmin\" => -1,\"xmax\" => 5,\"ymin\" => -1,\"ymax\" => 1), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 0; 2 1; 3 0; 4 2], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X=[1 0;2 1;3 0; 4 2];\n",
"@pgf TikzPicture(\n",
" Axis(\n",
" {\n",
" xmin=-1, xmax=5,\n",
" ymin=-1, ymax=1,\n",
" },\n",
" Plot(\n",
" Table(\n",
" x=X[:,1],\n",
" y=X[:,2]\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 目盛のフォントサイズ"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
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],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"xticklabel_style\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"font\" => \"\\\\Large\"), true)), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"only_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.4350912679355716 0.8587941857319608; 0.9864741595827231 0.9051677731600487; … ; 0.5075945203340313 0.06589654910523945; 0.21580452555225316 0.13571717910373815], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf TikzPicture(\n",
" Axis(\n",
" {\n",
" xticklabel_style={font=raw\"\\Large\"},\n",
" },\n",
" Plot(\n",
" {only_marks},\n",
" Table(\n",
" x=rand(5),\n",
" y=rand(5)\n",
" )\n",
" ),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 補助目盛りの追加\n",
"PGFPlotsのマニュアルを読み込んだわけではないため正確な事は言えませんが，経験的にnumというパラメタは，主目盛間に補助目盛をいくつ加えるかに相当するようです．"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"minor_y_tick_num\" => 3), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 0; 2 1; 3 0; 4 2], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X=[1 0;2 1;3 0; 4 2];\n",
"@pgf TikzPicture(\n",
" Axis(\n",
" {\n",
" minor_y_tick_num=3\n",
" },\n",
" Plot(\n",
" Table(\n",
" x=X[:,1],\n",
" y=X[:,2]\n",
" )\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1つのaxesに複数のプロットを描画\n",
"描画したいplot数が固定の場合は列挙して記述すればよいのですが，数が動的に変化する場合はよしなにしなければいけません．自分がよく使う方法を2つ紹介します．"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 逐次的にplotをpushする方法"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
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"</g>\n",
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"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"title\" => \"hoge\",\"xlabel\" => L\"$x$\",\"ylabel\" => L\"$\\lambda$\"), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.9220147070665194 0.26626167837305137; 0.2448805061354682 0.7880732580005387; … ; 0.42545473351381125 0.032592789223109486; 0.5481595095886773 0.685866021533083], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.8412250302435809 0.7770970328665303; 0.1897771927323526 0.8684612320353153; … ; 0.8974818161918676 0.7981679082902882; 0.09536009966222059 0.18604743250058542], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.1871184794975762 0.5851655361185044; 0.5190887586851223 0.40303687271360666; … ; 0.19743479244592632 0.6572653424481525; 0.5285858195976607 0.5479924055740557], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf ax = Axis(\n",
" {\n",
" title=\"hoge\",\n",
" xlabel=L\"$x$\",\n",
" ylabel=L\"$\\lambda$\"\n",
" }\n",
")\n",
"for i in 1:3\n",
" push!(\n",
" ax,\n",
" Plot(Table(x=rand(5), y=rand(5)))\n",
" )\n",
"end\n",
"@pgf TikzPicture(ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## リスト内包表記で記述して展開する方法\n",
"\n",
"個人的には，こちらの方が扱いやすくお勧め．"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 1; 2 2; … ; 4 4; 5 5], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 2; 2 4; … ; 4 8; 5 10], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([1 3; 2 6; … ; 4 12; 5 15], [\"x\", \"y\"], Int64[], true)), Any[])])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf Axis(\n",
" [\n",
" Plot(Table(\n",
" x=1:5,\n",
" y=1:5 .|> lprtl(*, k)\n",
" ))\n",
" for k in 1:3\n",
" ]...\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"リストをsplatしているだけなので，複数のリストを与えることもできます．"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
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"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-1-2\" x=\"248.671024\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-8\" x=\"254.350408\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-9\" x=\"260.9675\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-11\" x=\"271.459054\" y=\"64.78268\"/>\n",
" <use xlink:href=\"#glyph-1582954814696309-0-12\" x=\"275.378233\" y=\"64.78268\"/>\n",
" <use xlink:href=\"#glyph-1582954814696309-0-13\" x=\"278.13875\" y=\"64.78268\"/>\n",
" <use xlink:href=\"#glyph-1582954814696309-0-7\" x=\"283.659784\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-1-2\" x=\"287.52902\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-8\" x=\"293.208403\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-14\" x=\"299.278957\" y=\"64.78268\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696309-0-2\" x=\"309.214036\" y=\"64.78268\"/>\n",
"</g>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"legend_style\" => PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"legend_pos\" => \"outer north east\"), true)), true), Any[Plot(false, true, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"no_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.0 0.0; 0.6981317007977318 0.6981317007977318; … ; 5.585053606381854 5.585053606381854; 6.283185307179586 6.283185307179586], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, true, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"no_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.0 0.0; 0.6981317007977318 1.3962634015954636; … ; 5.585053606381854 11.170107212763709; 6.283185307179586 12.566370614359172], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, true, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"no_marks\" => nothing), true), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.0 0.0; 0.6981317007977318 2.0943951023931953; … ; 5.585053606381854 16.755160819145562; 6.283185307179586 18.84955592153876], [\"x\", \"y\"], Int64[], true)), Any[]), LegendEntry(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), L\"$f(x) = x$\", false), LegendEntry(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), L\"$f(x) = 2x$\", false), LegendEntry(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), L\"$f(x) = 3x$\", false), Plot(false, true, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.0 1.0; 0.6981317007977318 1.6427876096865393; … ; 5.585053606381854 0.3572123903134604; 6.283185307179586 0.9999999999999998], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, true, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0.0 2.0; 0.6981317007977318 2.6427876096865393; … ; 5.585053606381854 1.3572123903134603; 6.283185307179586 1.9999999999999998], [\"x\", \"y\"], Int64[], true)), Any[]), LegendEntry(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), L\"$f(x) = \\sin(x) + 1$\", false), LegendEntry(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), L\"$f(x) = \\sin(x) + 2$\", false)])"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf Axis(\n",
" {\n",
" legend_style = {\n",
" legend_pos = \"outer north east\"\n",
" }\n",
" },\n",
" [\n",
" PlotInc({no_marks}, Table(\n",
" x=range(0,2π,length=10),\n",
" y=range(0,2π,length=10) .|> lprtl(*,k)\n",
" ))\n",
" for k in 1:3\n",
" ]...,\n",
" [\n",
" LegendEntry(latexstring(k!=1 ? \"\\$f(x) = $(k)x\\$\" : \"\\$f(x) = x\\$\"))\n",
" for k in 1:3\n",
" ]...,\n",
" [\n",
" PlotInc(Table(\n",
" x=range(0,2π,length=10),\n",
" y=range(0,2π,length=10) .|> sin .|> lprtl(+,k)\n",
" ))\n",
" for k in 1:2\n",
" ]...,\n",
" LegendEntry(L\"f(x) = \\sin(x) + 1\"),\n",
" LegendEntry(L\"f(x) = \\sin(x) + 2\")\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 凡例の追加\n",
"前述の例で既に使っていますが，凡例の追加方法を挙げます．PGFPlotsのマニュアルにはいくつかの方法が紹介されていますがここでは2通りの方法を挙げます．"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## `legend entries`で最初に列挙する方法"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
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"<path style=\"fill-rule:nonzero;fill:rgb(59.999084%,39.99939%,19.999695%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(44.999695%,29.998779%,14.99939%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 10.497095 0.000418229 C 10.497095 1.101846 9.603409 1.991612 8.505901 1.991612 C 7.404473 1.991612 6.510787 1.101846 6.510787 0.000418229 C 6.510787 -1.10101 7.404473 -1.990776 8.505901 -1.990776 C 9.603409 -1.990776 10.497095 -1.10101 10.497095 0.000418229 Z M 7.094819 -1.410664 L 9.913063 1.407581 M 7.094819 1.407581 L 9.913063 -1.410664 \" transform=\"matrix(0.996575,0,0,-0.996575,172.866978,36.715261)\"/>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-1-1\" x=\"192.001227\" y=\"39.417973\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-2-3\" x=\"196.861526\" y=\"40.906857\"/>\n",
"</g>\n",
"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 0.000210324 0.000492432 L 17.007672 0.000492432 \" transform=\"matrix(0.996575,0,0,-0.996575,172.866978,49.070803)\"/>\n",
"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 8.505901 0.000492432 L 8.505901 1.991686 M 8.505901 0.000492432 L 10.399103 0.615881 M 8.505901 0.000492432 L 9.673963 -1.610493 M 8.505901 0.000492432 L 7.333919 -1.610493 M 8.505901 0.000492432 L 6.608779 0.615881 \" transform=\"matrix(0.996575,0,0,-0.996575,172.866978,49.070803)\"/>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-1-1\" x=\"192.001227\" y=\"51.773516\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-2-4\" x=\"196.861526\" y=\"53.2624\"/>\n",
"</g>\n",
"<path style=\"fill:none;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,100%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 0.000210324 0.000566634 L 17.007672 0.000566634 \" transform=\"matrix(0.996575,0,0,-0.996575,172.866978,61.426346)\"/>\n",
"<path style=\"fill-rule:nonzero;fill:rgb(0%,0%,79.998779%);fill-opacity:1;stroke-width:0.3985;stroke-linecap:butt;stroke-linejoin:miter;stroke:rgb(0%,0%,100%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 8.505901 1.991761 L 9.999296 0.000566634 L 8.505901 -1.990627 L 7.008586 0.000566634 Z M 8.505901 1.991761 \" transform=\"matrix(0.996575,0,0,-0.996575,172.866978,61.426346)\"/>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-1-1\" x=\"192.001227\" y=\"64.129059\"/>\n",
"</g>\n",
"<g style=\"fill:rgb(0%,0%,0%);fill-opacity:1;\">\n",
" <use xlink:href=\"#glyph-1582954814696310-2-5\" x=\"196.861526\" y=\"65.617942\"/>\n",
"</g>\n",
"</g>\n",
"</svg>\n",
"\n"
],
"text/plain": [
"TikzPicture(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Union{String, PGFPlotsX.TikzElement}[Axis(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(\"legend_entries\" => LaTeXString[L\"$f_1$\", L\"$f_2$\", L\"$f_3$\", L\"$f_4$\", L\"$f_5$\"]), true), Any[Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0 0; 1 1; … ; 4 4; 5 5], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0 0; 1 2; … ; 4 8; 5 10], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0 0; 1 3; … ; 4 12; 5 15], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0 0; 1 4; … ; 4 16; 5 20], [\"x\", \"y\"], Int64[], true)), Any[]), Plot(false, false, PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), Table(PGFPlotsX.Options(OrderedCollections.OrderedDict{Any,Any}(), false), TableData([0 0; 1 5; … ; 4 20; 5 25], [\"x\", \"y\"], Int64[], true)), Any[])])])"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@pgf ax = Axis(\n",
" {\n",
" legend_entries=[\n",
" L\"f_1\",\n",
" L\"f_2\",\n",
" L\"f_3\",\n",
" L\"f_4\",\n",
" L\"f_5\"\n",
" ]\n",
" }\n",
");\n",
"\n",
"for i in 1:5\n",
" push!(\n",
" ax,\n",
" Plot(Table(\n",
" x=0:5,\n",
" y=0:5 .|> lprtl(*, i)\n",
" ))\n",
" )\n",
"end\n",
"\n",
"@pgf TikzPicture(ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## `LegendEntry`で逐次追加する方法"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
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0UDrrRUEBODmBlhacPAmfr05DkBZY4bHIKqUTG0v1QlUVbt0CBgPs7SEvD+2BIK0FlM76wmLBqVMwZAhYWkJKCtoDQVoFuP2HVBr24OEBenqfHBz1748mQRBsdSK1Y+5cOHECnJ3h/Hk0BoJgqxOpNRIHRyNHQloauLujPRAEW51I7TAzg4gIOHMG3NygiRyxIAiC0tkM0dWFhw8hORnGjoWyMrQHgqB0IrWjTRsIDAQNDbC1RQdHCILSidQaOh0OHoRhw8DKCmrxfi2CICidCAD8f9HSunUwaBDcv4/2QFopjx8/Dg4Oltq+GyidrYQZM+D0aRg/Hk6dQmMgzYCSkpI7d+5IxdlkSUmJnZ1dbGxsXFyckZFR3TaWlwqvXr3y9vb28PA4f/58mTSmIFA6GwOJg6M1a9DBEdIMcHNzs7e3lzh3qyerV6/W1NRcsGCBgoICh8MhmmjRyZ49ey5evDh06FAHB4dTp04ZGxuHhYXVt0+J2380GllZ4OgI5ubg4wMMBsTFwZ07UFIC3buDgwNU75YVaQk0owp/48aNAwcO7Nmzx8DAoJ5RmZqazp8/f+nSpU2YnfDw8FOnTnl7e0sOCYIwMzPLz89//vy5mppa3YoMt/9oVLS14f59yMmBYcPA0ZHo31+0alWuh0fW1KllBgZEo+9yjTRLCEJMEOIGTWLYsGFXr16tv24CQE5OjsSJZhNy+vTp2NjY169ff+poU6lTp07Nzs6+fv16faLFt4kaFXl5uHIFunQhUlN5BJEKQABAcXEmj6dqY9M+OZla468g0qpJjLpz/eTOnPdpANBW33D4zN+79LSuf7QikYhOb646IBaLv3ax+QUlJSXh4eHx8fGVe33q6uoCQNV95lE6mwEpKZCZSVbqpgSSLCgtbbNrl9qmTRQ0EfI19y79e/3kzrbKTCMtOQAoLX5/bOMCxznuA0bNqFuE7969O3LkiIGBAZ/P53K5t27d2rFjR/fu3devXx8SEpKbmxsUFNSlSxculztp0qSsrCxlZeXg4OB9+/aRJJmamqqsrLxx40ZG9cNMfn5+ISEhPB7Px8cnNDRUX19/xIgRa9euzcnJMTc39/PzA4Bjx44dPXo0Ly9vwYIFbm5uALBo0aInT57k5uZGRkaGhIRkZWVxudz09PRt27Zpa2tXbcyuXLlSQ0NDUVExOzvb1tbWxcWlujvZs2fPtGnTbG1tK0PS0tLgK3fzP4x0N+4vKysLDw+PjIzk8Xgt28FGnfHxIeXk8gGiv/okmZmJ0BEFOtj4mpyM1D9dzFePMf5rfFcf154HXXtuHG+6eozxny7meZnv6hanpaVlXl5e5eHo0aOjo6Ml/0smiJ4/fy45JAhizpw5Xbp0OXLkSFFREUmSkg3kDx069N1U1NXV9+zZU3lYXl7euXNnBweHypCMjAwqlfr3339Xhpw4cQIAjh49mpiYKAkZMWLE5MmTK09IS0vT1tb29fWVHMbGxurq6sbFxdU+7yYmJjo6OvXRKE1NTWmOdR4+fNjd3T0pKcnf319fX3/16tUCgQDbC19QUQHVLPsgWta6N0RqPL1zpQ2LoqfGqRCJc4v4H4sqBGJCT01OgU19di+gbp30yMjIrKysypAJEyZU9ny/aI5RKBQjI6M3b94YGRlJBi4ZDIapqWnQj/s1ZLPZX7hQ19XV5XzuX6Fz584AkJ2dbWxsLAmxsLComtbSpUt1dHQkDpQAIDo6OjMzs7CwsJb34O3t/ebNmxMnTigoKMhEh/3KlStv377du3dv5Uizra1teXn5rl27sOpXxcICmEzFr1WSRlPs2xd7662Lm6f33Tzj9d3TqBSKpjKLSqHpqXLSckopQOmgJU+lAAPEt854hZz+fgxDJi0eMnnJf489nW5tbW1lZeXo6DhkyBA7OzuJM7VKrfzicgqFIhKJJM7dJCgrK9dtkebXQ5NfJCc5tLCw+GZahYWFgYGBv/zyS+W3c+bMGTt2rLKycm1ST0pKWrNmzblz5wYPHlzPspOadO7cuXPcuHGVh4MGDerXr9+ePXvWrl2roqKCD0klAwdCu3aMpCQtsbjqy+1sgLbLluGCh9bFkMlLqipadVw9tOnlg/MAkFvMZzKoJAl5XL6GMksEFGun2SNn12V/w/Pnz//666/nz58/ffo0lUpduHChp6dnDVMuLBZLTk7us15SQy7S/EI0KtOS+Fv/oulaS90sKCiYMWPGxYsX7e3t63+HUntWk5OT3dzcMjIyKkOMjY1JkoyLi8Mn5PMfVQgKorZtqyMnZwigDNCGRtORkzPu3ZuyePEPODgqLS58ejfg7sXDcWE3KspK0LAtGLOBw0uFtI+FFQIxoasqJ+m5fyyqKBVQzAcOr0OEJElSKJSTJ09yudzIyMiVK1cePHjwyJEjTZK7H1ruqqmpKRHBH02lvLx8zpw5Pj4+lbpZT2mSWqtz//79Hz58qPQXCgB5eXkA8E1Ho62cDh0gKYl68KDSlStteDywtKQuW0bp1Ak2bAArKwgKgk6dvhNDeNCpoOPb5dkMCikkKIwLfGK82yaz/g5o25ZZYYwtjPvYxdwP0tfgUCkAQGmrxE7PL+tt79iuU7c6RFhcXPzbb78dP36cxWL16dOnT58+HA7n7t278+fPb+i80Ol0oVBYecjj8UpLS2t/eadOndTV1V99taHO8+fPu3btWt1VYrF4+fLlmzZtMjExkYSkp6c/fPjQ3Ny86aVz7NixVQ/Lysru37/ftWvXLl26YNX/Gnl5WLGCsmLFZ/0jDw/Q1QU7O7h0CaoMK31J7MPrl3w2Kisw1eXoAHQSyOwKvu+2ZQs3+Rp07Y22bZFMWL5VVUvv/pVjLBYdAPgC4c8TFw+e+EudIwwICMjPz698ncbQ0LBSwiS9Y5FIVLW//EX3nCCI2rQWCYKoKpQA0KFDh6ovQQYHB7PZ7KoTp5KEqiZXNS0qlbpz5865c+cmJydLJpQkkZSUlNQgnYsXL9bW1k5ISEhISCBJUiQShYaGTps2TSZanV+wY8cOPp9/8ODBGkZPNmzY8M1wGxubQYMGtc4nZN480NeHUaPg4EEYNerbvZurh/7WVeXkFQvyqQJVBWYOt0JIEJpKrIBDfy3fexVVpkVCpdKGTl1mP35hdvprCgW09DvRGcz6RCgQCP7444/ly5cbGhrGx8dfvHjx0KFDAHDp0qXLly9LHuE5c+b07dv35MmTly9fFggEGzduHDx4sK6ubmBgYHR0dGlp6Y4dO5ydnb+5QDIqKio0NLSwsNDX15fD4VhbW3fr1g0A5s+ff+nSpQcPHvTp0ycsLKygoEBdXf3cuXNqamqzZ8++du2aJHVvb+/MzExHR8djx475+/uLxeIVK1Y4OTlZW1tPnz49Ly9v7Nixu3fv7t69e1hYWEJCwtq1a6vL6fbt2318fL4O37x583etVJ1GCYXCBnmv9smTJzY2NufOnXN0dKzunFb4DnvtiYuDUaPgt99gyVdTCPnZ7/e4jWqnTBMTZEZeOYUCQAE9NQ4VKG9yK/4+F81gstGAMohMVXiRSBQVFWVhYXHlypXs7GxDQ8OhQ4eyWCwAiImJEQgETCZTsnizY8eOkZGRLBaLRqPx+XwNDQ0VFZWkpCQmk0mhUPh8fqdOnb45KJeamvrx40cWi0UQhEAg0NfXrxzNy8zMDAoKKi8vt7e3NzU1PXToEJPJ1NDQ+PnnnxMSEkQikSR1BoNhbm4eEREhSV0gEKirq1e+EfThw4ewsLCioiIrKyuJKFdHQkLCN8dGbWxs6lxkWlpa0i/OvLy8wYMHb9myxcHBobnUJBnk7VsYPhx+/hl27wZqlcm8j+9f+7hP0m5DkgA5RRXccqGaPEtNkQkAabn8db6POPKKaD2UTqRBi0z623+UlpbOnDnz8OHDEt0UCAQVFRVYBnWgQwd49Aji48HF5TMHR2pa7fgCgUhM5nIr+CKio4Z8SYUov0TAFxIEKd7t5nzRe11i1B2REF9GQJCGHEKRbi9gyZIlW7durVw6GxQUFB8fj1auGyoqEBIC8vJgZwc5OZ8C6UxWN8sh6XllFUJCT43DoFN11dm8MmEWVzBixsr5fx/Xamf0MNDXY5rV0Y0LHgef4+ajayQEaYA2qRQ7EcuXLx89erTk9SmSJPl8/po1a7y9vRUVFbH/UmdIEjZsAF9fCAqCLl0gOSbs9I7fFZRUSotyFOgiBp0iEBI8Ib1TD+spv++kUD79FpbxuClxEYlRdxKf3FVU0TTpa2vS27aDcY+vXxRBsMOO1KHDLrXiXL169dczVrq6ulUXyWNNqjPHj8OqVbB99bnUJ3unr9rbwdgi5n5Q9G1/bl62Wlv9vg4TTfvaffNCghBnpr6SaGhRbtZPPQaa9LH7qccAtpwCWhWlE2l66dy8efMXC7gAoF27drNnz8aaVH8IQuzz9+6YB/esJhycNU+3bpEUfMxIjnmUGHX3dcJjnY7Gpn3sTPvZa+oZoHlROpEmk06sSQ0Hv6Ls1PZfRQJ+r9F7xrgozpxZXx9HQn55SlxE4pN7L5/cozOYxr1tTfvYGnTtQ6txy9vcD2/fpyTQ6PQOxj2U1LSwXLDCo3RiTZJdigty/t24QM/QZMxCDxqdnpUFI0eChQUcOCAdd0bZ6Skvo+69iLqTk5HaybxfJ3Mr0372bZTVq55TxuOe3r787asYeTaTBCgtq7CwGem0YH09V2Xjc4igdGJNahAy014d/Wthn8Fjqu6vU1ICEyeCQAAXL4Ki9BZxlnALXj198PLJ3eSYcDXtdia9bU362OkampAE4bnMOTs9pYOGHI1GAYAKIfE+t8ys/5Bpq/ZiGWGFR+nEmiRbPI+4ddF7/bglf5n2/XKPLLEYliyBsDAICoJ27aScrkjAT0t8mhwX/jwiVCwUqLRtl5MaTwdRGV+sp8YRk2RGXrmqAoMnpLv+fbJdp65YUljhUTqxJskK9y4dCQv0m7XGW9fQtLpzPD1hxw4IDITu3RvqNrLfpZzavpzkvleUY+QW88v4YjFBqrVhKskx8ktEvRzn/TxxERZWLSs8GqHZUYN0ols3mUMsEl3y2ZCR8nzJjnM1z8a4uYGuLgwZAidOwLBhDXIzbdt3UlBSKeNlAICSPINbKqBRqQpsOgBQgSgvKcbyqudDiDRTcFty2YJfXnp80y/cvKyF//jWZhbbxQUCAmD2bDh4sKFuScfQhC8GgZjIyCvXUGIrcOgZ+eVighRRWNodf8IiQ1A6kSam4GPG3l/HK6m3nb32YO2XrFtawsOHsHMnuLlBQ7RsLB0ml/AhI69c0k/XUGTJsWjv88r4YjCzGoqlhqB0Ik3Ju6RYr5WTrIZPclm0kVr9JqffxMgIIiLg2TOYOBGkvt2Kuk77UfPXUOkMAIpQRAhEBJ1GExLkmIUeLI48FhzSOsFpIpkg/lHIpQMbxrttMultW+dIKipg5kzIyYFLl6B2fq5+gPcpCaFnvTNSnlPpNMNu/RRVNF4nRP6y5RQu7URaITjDLhM8vHry/uWjs9bu1zUwqWdUkr1CLlyA69fhc6eBUoYkyZNbliqpaTm5rsESRFqhdGKHvSkRi4Rnd7vH3A9023Wx/roJABQKeHiAqyv07w/R0Q37yzd+6aaX0fef3kWXHkhrBKWzySjjcQ+tmy2oKF+4+WQbFXUpxuzmBl5eMHw4BAY24P1z5BVn/ukV+O8/H9+/xtJEUDqRxiA/K33f7xO0O3SZtmoPg8WRevxOThAUBAsWgJdXA+ZCu8NPw6Yt992yTFBRjmWKtCpwrLMJePvy2cktS3+euMhy2KQGTSgtDUaM+IaDI+lybs8fIqFgyu878XFCWgk41tkEPLl96cTmJZN/3dnQugkAHTvCo0cQFwfjxkF5g7ULx/7ikZORGhF8FgsXwQ47In1Ikrx5el/ouQMLNp80MuvbOImqqMDNmyAn95mDI+lCZ7Kmue8J8dub8foFljKC0olIE5FQcHrn70kxj5ZsP6vVzrAxk2Yy4eRJGDoUrKwgKalBklDXaT9uyV/s3tGlAAAgAElEQVQn/llcxivCskZQOhHpUFpceHDNTEIsWrDpuIKSWuPfgGTR0urVYGMDDx82SBKmfe279ht8dvcqXK6LoHQiUiA7PcVzhUsHkx5TV+5mMNlNeCezZoGfH7i4wJkzDRL/yFnuZSXce/5HsNARlE6kXiTHPvL5c8bQKW4jZvwmCzs2Dh4Mt2/DH3/U17vRN6HR6dNW7n4QcDwlNhyLHmnZ4OIk6UCSRNKzsHdJcRQKpaNJTyOzfhQKJfLmhWC/PdNW7jHo2lum7jYzE0aOhJ494cABoEt7y9aUuIgzu1Yu2+2vqKqJDxjSIsF32KVDUV7WkXVzyrg5DFIAFAqfZChrtjM06/ci8vacdYc0dDvI4D2XlMCECSASwYUL0nRwJOHm6X1vEqLm/338R7eAQhCUztYinWKRcPtCh4KPH/Q15Jh0Kki8nuWVsdhyfx69I6egLLN3LhLBkiUQHg5BQaCnJ+U2+BGPebqGpsOnr8DHDGmR0oljnfUl5kGQqJyrpczKyCsTiAi+UPyhoExbhc1kUFOfR8vyndPpcOAAzJ4NlpYQGyvd30XqlN92xd6/9vxxKNYQpEWC0llfkp8+YFGEbTgMDSVWRl5ZRkF5WyW2ApvOogiTYx/J/v27ucGuXTBkCAQHSzNauTZKk3/b6e+9viDnA1YSBKUT+arbKxRIZs4lvXUAYNCpAEABEAv4zSIL48bBlSswaxYcPizNaDsYW9i5uPr+s1QkFGA9QVA6kc8FwqSXgKTzheIP+RVaymxNxU89dwEw2xv3bC65sLKChw9hxw7w8JCmg6OBo2eoaOlePbIZ6wmC0ol8Ru/BYypElIz8ci1lljybXtlzF1PoFtbDm1FGjIwgPBxCQ2HWLBAIICEBpk8njI3F3buL16whCwrqGO2EZVtex0dG37mCVQVpSeAMuxR4+/LZgT+nKnKYHCYACRViKp+gu/51TNfQtNnlpawMJk+G5GTy7VuCz88mCB4Alc1Wk5dXefCAalKnneyz3iYfXDNjweaTbfU74SOHtABwcZJ0eHr36u0LB82shqS9iKIAdLIYaDV8MkdBsZlmJyEBevQgRKKXABVVykutXTv9N2+odVtC/+xe4K2zXm67/GvvJBlBZFk66WiF+jbTeNxrx7bO/NOrfReLlpGjvXsJksyuqpsAQJL5RUVaN29yhtdpEKLHIMfX8Y8veq2dunI31hmkBYBjnfUl6Ph28wHDWoxuAkBUFCkW877Vly+Oj697tGMWrMvNfPco6BTWGQSls7WTlvj0ZfT9oVOWtqRMyckBwDdeoKTTaXJydY+WzmRNc9998/S+ty9jsOYgKJ2tF7FIeNFrndP8NRx5xZaULycnKofz9aaiVCpV2d6+XjGra7ef4Lb51I4VpcWFWH8QlM5Wyt1LR1Q0dcyshjZ2whRKtR9p8MsvFGVlJRpN83PdNFRVpRoY1Ddykz525v2Hnd3tTpIEViGk+YIz7HUkL+vd3l/HL9vtr6ql1/i2e/qt4J4A0lrOnpoKw4cTmZlCPr+YTqcBKI0cSaFQqO/ewdWroKFRr8gJsfjA6uk/9RgwePxCfAKR5gjOsNedgEOb7Ma5NoFuNgoGBpCYSL1/nxUXp8Fmg60t/PQTkCRs2ACWlnD9OnTuXI+eDo023d1zz/Ix+p3NOnfvj3UJwVZna2l1PrsXeNf/0LLdl2l0epPYrqFbnTVw9Cj8+SdcuAADB9Yrntfxkad3/uq2y19JTQufQ6TZtTpxrPOHqSjlBR3f7rJoY9PoZlMzezb4+oKLC5ytn991I7O+VsMnn9ziJhaJsFIhzQ6Uzh8m8Ni2rv0Gy+hCTldX2L4drlyBly9B0FD7Ff38M4SGgrt7fR0c2Y9fqKCkeuPkLqxUSLMDxzp/jPSkuJdP7v2+P6hpkidJuH27phMGDIDERHjyBFJTITERlJXB1BQMDD59TEygSxf4UacX35q47wbwDgA2gGsmuX9/HR0cUSiUicu27F7mrN/FvAkWKiBIPcCxzh+AEIv3LB9jP36h+QCHxk6bx4MzZ2DvXmAyISamVmOdIhGkp0Nq6qfPixeQmAiZmaCj80lGK1W1Y8eaFjZVM7QqSXH4MJIg4MIFaNOmjjl7n5JwxGPe4m1nNHQ74gOJNAtw+48f4/Z5n7TE6LkejetnPCUF/v0XjhwBS0twc4PBg+s1TSQQQEbGJxmtVNXMTDAw+E9JTUygWzdQUqqNdIqE5OLF8PgxBAWBrm4ds/jomt/jkPNLd5xjsDj4WCIonS1KOgtyPuxd4bJkx3m1tu0apYlLwJ074OkJT57AzJnwyy+gr19DD/q/Hn0dKCz8snGanAx0+iclvXChBumUpOjpCZ6eEBQExsZ1zO6ZXSvpDOa4JX/jY4mgdLYo6fx343zDrr0HjZnb4CkVFcHRo7B/P6ipwZIlMG4csFhNkOGMDEhJgeRkWLDgu9IJAOfPw7JlcOoU2NrWJTV+RdneFeMGjZnde/BYfDIR2ZdOnGGvFTEPrhXlZg4cNbNhk3nxAhYsAAMDePYMTp2CyEiYOrVpdBMA9PTA1hbmz6/l6ePHw4ULMHUq+PrWJTUWW27maq+g4zs+pCZifUNkH5TO71NRyrt2bPvYXxpsISdBQGgoODrC4MGgrAzx8eDnB337NjtD9e8Pt27BunV1XLSkodvRyXWN79ZlFaU8rHUISmezJ+j4DtM+dh2MG2AhJ5cLnp5gaAirVsG4cZCeDlu2gF6zerkz9DNP6yYmEBEBQUEwaxYIhT8cWXfrEZ3MLc/sdm8xHgSQlgqOdX6H9KS445sX/74/SMo7y716BQcOgK8vDB4My5eDpaUM15EaN2Rq3x6srWHPHlBVrQwrLYXJk6G0FPz9/5uoryUiocB75aQeg0b1tBudFBNWyi1U0dTtbGHFYLLxcUVkBJwm+l5P+tNCzgXmA4ZJrW8eFAR798KLF+DqCosW1XcboianrAw2bgQ/P9i3D5ydK4PFYli2DO7dg6Cg/5YG1JKi3Mwdix0JsVCBw6GASAw0IUGZ+vvuTt2t8KFFZEQ6scNeE/cu/9tGRf07ulnD7plV22u5ubB1K3TsCBs2wLRp8O4deHg0e90EADk52LIFzp2DP/6A8eMhN1cSTKPBvn0wdy5YWcGzZz8W5euEqIqyEgUmqMuJ1eQomnIECEoOb5iXmfoS6yQiI6B0VkthTuaDK8fGLPT47plPq/l84tkzmD8ffvoJXryAq1chOhqmTwcGo0UZq39/iIkBAwMwN4eTJyuD3dxg3z5wcICgWr+5ShDiq4c36ahyeGWCojIhAHwsqiAIUl2eEXjkH6yWCEqnrOO/f52N0+z6LoD/+WdwdARtbUhOhpMnwdy8xdqLw4EtW+D6ddizB0aOhIwMSbCzMwQGwrx5sH9/raL5mP6GCqQCm66nLlfI46fnlQlEhK6anKIcPfXlM5w+QlA6ZZrYh9e5+R+tnWbVNyJX1099c3X1VmG47t0hMhIGDoSePeHQIcmC+b59ISwM9u4FNzcgvudWQ8Avo9FoAMCgUdlMeoVArMCmUyWDHyRBiMVYORGUThmloqwk8OhW6SzkHDcOWtu2ngwGuLvDrVtw+DA4OMC7dwBgYADh4RAbCxMmQHl5TVdr6hmUlZcTBPmxqEIkJtpryBeVCorKhBVCsZKqZuvcIxVB6WweXD+xw6T3oAZZyNl6MDODiAiws4PevcHbGwhCVRVu3gQGA+ztKyeTvtXvl1fsZjk4Pb9C0k9nMaiSnntOsWjQuPloVwSlU0ZJT45//vj28Om/oinqC50O7u4QEQH+/jBwILx6xWLBqVMwZAhYWUFycrXXjV30l4aeEYPFKReI+CKiQiAGCtW4j72lw0Q0KoLSKYsQYvFF73Wj5qziKCiiNaSDoSHcvg0zZoC1NXh4UERCDw9YtQqsrSEs7NtXsDjyS3ddtJ+ygq7eqYSi3Ka9hd5PFpp6hhQpeUtGkPqDS+I/4+7Fw68THs/b8G9tL0hIADOz2mwshMDbtzB/Pnz8CEePQo8eN2/C1Kmwbx9MmPD9S7l52bvcnNx2XWypLkiR5oWWlhaQTQRAkyVdHYU5H9ZN7puX+a62F5w7R6qpkQA1fZAvOH+e1NIi3d3Jioq4OFJfn1y/vlbX3TrrfWLzErQfIgtoampih/0/Lvn8ZeM0S027Fq8NkiRs3Qq//w7BwUCSNX2QLxg3DmJj4fVr6NXLrCIqPBwCAmD+fPiuW8xBY+Zmvn2V9CwMTYjgWKcMERd2oyD7vY3znO+fWlwMTk5w/To8eQK9eqHpfpi2beHiRVi3DkaN0t04/2FwaXo6uLhAWVlNF9EZTMfZ7leP/IPOhxGUTlmhoqzk6r9bXBbXYiHnq1fQty+0bQuhoaCpiaarV/Pz5UsAUOhvfm3FHS0tGDQIPn6s6QrTvvYqmjrh10+j8RCUTpng+omdJr0GdTDu8Z3zAgPBxgbc3eHgwZb2EnqToKICBw/C3r20ubMOwvxJI3mWlhI5rRYn1zW3zx/gFeah8RCUzibmfUrC88e3hs+ocSGnZHBz8WK4dg1mzkSjSZPhwyE+HgCWHzL+d/RVW1u4d6/ac9V12ve0cwr224NmQ5qW1r44iRCLPVe4DBoz28LGsdqTioth+nQoLITz50FLCytNQ/HwIcydm6Ntrnn/Qg2/Yfzy0m0Lh83400u/sxnaDGkScL9OeBBwTF5JtSbdTEqCvn1BSwtCQ1E3G5aBAyE2VrOfAdS4iR+LI+8w1S3g8GbcRQnBDnvTUJSbee/Sv2MXrq/2jMBAsLbGwc3GQ7Jz3ffoZT8GSPLp3QA0GILS2QRc8vlr4KgZ317ISRCwejUsXQo3buDgpqxBoVCcF6y7fmIH+s5EUDobm/hHIbkf0mycZ3+rOVoEjo4QEQFRUdCjB9YSGUTPyLRLT+vQ8z5oCgSls/GoKCsJOLJ57C8b6Azml98lJYGVFejpQUhIS/Ad1HIZPuPX6NuXcj+koSkQlM5G4obv7i49rY3M+n75xbVrYGMDv/+Og5uyj4KSmq2L62Wfv9AUCEpnY/A+JSE+LHj49BWfhUpWbi5aBIGBMGsW1gzZ5OKfn3nXHOg4vbgwJzHqDloGaWRanbsCQiy+6LXOcc4qeUWV/0J5PJg+HfLzISoKVyDJAj2rCbfdNuxwwuE5AaOoVAAAoYhm5bzB/+C6zt3705kstBuCrc6G4uHVE2x5BQubkf8FJSdD376gqQm3b6NuygTV70RFvx3ieGvpme5b09PBxYVQUiJ/HtV944krAyyz0tPRcEjj0breJirKzdzl5rxk+1kN3Y6fgq5dg7lzYfNmmD0ba0OzQJD2Ic5i5hDehRIqXyTKAhADUKkUDUWltjEx9A4d0EJIg9Pq3ia6fPAv69EzPummZHDzl1/g6lXUzWYEs6PuNtugErJUJMoAkPgWJgjyY3Fx9pw5BNoHaRykP9ZJkqRQKGQymbKW1fjwkJyMtGnungD/H9zMy4OoKGjbFutBM0IohMAbDBH5pVNNgsgNC9PmckFJCY2ENCvpzMvL+/PPP7W1tRUVFWNjY11dXQcOHCgj+eSXlwYc3jxp+TY6gwnJyeDkBAMHwvnzuAKp2VFQADQa8f/25mfiSYWSjAwFJSUaWglpNtIpEAhsbW03b97s6OgIAAUFBb169Tp79myfPn1kIZ83fHd36THQyKwvBAXBnDk4uNl8UVEBsZgKQPtKPSkiMedD4hVT07FoJaTZSOfhw4d5PJ5ENwFAVVV16tSpy5YtCw8Pb+w8USgAUMKkvdSS57LpShUik4+lTgIxAEBZG/D2hoAA6NsXy76ZwmTC0KHk9etaIlFm1XAqRd3CQhgesHOAg71cG2U0VCuCQgEAEZWSpCmf1YbJFhKd88o0SwQADeiSVmrT3EOGDFFQULh06VJliL+///jx47OzszW+9TpjA86wUyjn2yvHmGrIM2k0NkNUISoViHo8zx2fXgQDBsCFCzi42dzJyABzc6K4OFsk+ghAAFCoVE05Uslb+x+OO5POpDovWIdWalXSeUuJ/aCvLo1FY8kxCRFRWi7Uy+LNj/1IIxpk5lBqM+x8Pv/BgwcKCgpVA7W1tQmCuH37diOb8YWWQlQ3TY4CU0NTXk2RqakpJyfPjDLTTNSSh9u3UTdbAHp6EBNDtbVty2KZt2ljxmJ1799fOzKKbkp72cEjNPbBjcy0V2il1gOXTb9j1U4kx2irpaCmxNJQ46iqcdJ0FQO6NaD3MOlIZ35+Pp/P/0I65eTkAODDhw+NbMer3bR0VDkCEZHL5ZMAuVy+QEzoqHACummB7M37I3VDXx9u3qTm5lKjoxnZ2dQHD2gmvTg93l4qNRvcOzL/zD9/4EbIrYc7nVQV2zDlWfSMgnKCIEvKRXlcga6a3NN2ity8bJmWTh6PBwDy8vJVA2k0GgBwudzGNGIJt4DHosqz6XqqnAqhOD23tEIo1lPlyHPoPCathFuA9awl0aYNdO4Myv8f2KRQKYPueagMXEG8eh6wDv0XtRaStBTk5ZkaSiw2g/Y+ryyHy9dVY8uxaAp0WuqLJw2UqHSmicRiMQBQqdQvevEAIKrea/aGDRu+GW5jYzNo0KC63YlIyKeRFAoAUClsOpVbJlSSY1CoFAoAlQIiIR/rWYun//EFpWvgccQu1V9UrffPQIO0eMRUCoUCFAA5Jo1bJmDSaQwaFQCAShEJBXWO9t69e/fv3//mV0KhUDrSqaSkVCmglRQXF1d+9U3Wr18vdSMqqWmRJCkUkUWl/AoR0UFLIauwPI9boSTPpBCgpIavqLcKhvy9IHVFTFbw5rABLwc8/EcyA4u0VHSLKnLV5YU0IofL11eX45aJMgrKdVU55QKxjoFxnaMdNGhQdW24/fv3S6fDrqKiQqVSJd32L6RTo3F3C6ZQqDZvCjJyS8qFhJ4qh0Gj6KlyyoVERm6pzZsCCgWdJ7cWpqzd9MJcmUh++MRworC4HA3SgrFLzi8oqpD001kMmqTn/i6nVKO4QtfApIESlY6UyMnJ9e/fPzs7+2vptLGxaWQ72qfkt/1YShWISypE5QJxSYWIIhBrZ5fapeRjJWs9tFFRHzRmdvJCs1IBI0XfnvcmB23SMgkO1i+qME/MoYqIsnJxuUBcWiEi+CJOqXDGk8yGS1ZqrTBnZ+cXL15UDUlOTjYyMjI0NGxkS1JJcIv6MCE6Uy0ln3hbpJaSP/FJptuTD1SccW1l2DjPzv+YqnnJ9W3nIUUmVtl3X6JNWhSSHXxmzQKAiW+LloS9M3iZS7wtkntTaBf38c97aYoVogZNXTrk5+fr6enduXNHclhaWmpoaHj58uXqzpdi0ghSHS8ib29bOEwkFF6fcfYjTTvl4G20SQuBxyNdXMiePcl37zLTktZPseQV5TVa4pqamlJ7EVNVVTUkJGTlypWvXr3S1tb29fX9888/nZyc8KcRaUJM+thF3Dgbds132PFZ9zq3M17o8iJ+ranXQrRM8+bNG3ByAgsLePiQZLP83ScPm7ZMQUmtMW9B+m9Dpqenl5SUdOrUiVHjpkRNstUx0grJy3q377cJv+4LVFTViLn4ps2kkRXWQ7re2g1UnDNsroObMH06/PoruLsDQPj109F3rizZfrYxJ4G1tLRa1y7xSOsk6Pj2Em7hBLfNAJD2rDBn4Fi2topZnC9FXg6N08wGN7dtgz174MwZGDQIAHiFeTuXOLr+dUynY5fGvJFWt0s80joZPOGX5Jiw9KQ4AOjYQ8XodXAmr807vf78NxlonGZDSQlMmADnz0NkJPx/ueWVQ3/3GzqhkXVTAkon0vJhceSHTV9xyWcDSRIAoKbNtEs/fr/jTK6pVdHdGLRPM+DNG7CyAhYLwsJAX18SlvQs7H1yvN24+U1yRyidSKugp+1oBosTffvyJzFlwfSnbvdG7yaGOACFUtMHaXJCQsDSEqZMAV9f4HAkYUJBxaUDHs4L1jHZnCa5KRzrRFoLH968+Hfj/JX7b7Dl21QGXvkj0mlLv6fVCS404F65yPeRDG7u3g1nzoCtbdVvgk7sKMrNnvLbjia5LxzrRFoRuoamxr0G3Tq3v2qg0z/oL0BWKS39NLgZFfWFbma/S4m6edFx9somvDuUTqQVMWLmb8/uXs1+l4KmkHXS08HG5ovBzf+3RImL3muHTVuuqKrZhDeI0om0IuTaKNuNmx9weBOaQqa5eRP69IHZs6sOblbyOPgcQRB9h45r2ntE6URaF/1HTCnh5j9/HIqmkEUkg5uzZsGFC/DLL19/zyvKCzm112XRxibfBQ2lE2ldUGm00fNWB/67RSTAfa9ljIoKmDkTzp2D8HAYOPCbpwQc3txnyLgmWciJ0om0dozM+ukamNy7/G+tzhYK0WKNwfv3MGAAiMUQFgbt23/zlKRnYemvYgePl4ktCFA6kdbIqHl/PLx6sjCnFvs59u4Nz56hxRqW+/ehb18YNw78/L4e3Pz0EyaouOSzoQkXcqJ0Iggoq2v3HzEl6MSnVYE9q/kAQJjNahg+HFatAj528BuGQ4dg0iTw85Ns51Edt854t+vUzbj3IBm5a5ROpJVi6zIvPSnuTUIUkGR1n+cJ5NSAcTumxsLr19CzJ0RFod2kSUUFzJgBPj4QEQF2djWcmJ2eEnnzwqg5q2Tn3lE6kVYKg8keOWvlZZ+NxOfuCKvStSuEh8OZu23nKl8U//0PjB0L8+dDaSlaTwq8fw8DB4JYDI8eVTe4KYEkiYte6xymujXtQk6UTgT5hFn/oYpqWhHBZ2s4R0cH7t+H7GwYfsCR9ygeAMDMDO7cQevVi/v3oV8/cHGpYXCzksch5wmxqJ/DBJnKAUon0qoZPe+PW2e8S4sLazhHQQECAsDQEAY4qmSsPQheXjBrFsyfD5+7gEVqi2Rw09e35sFNCbyivBA/T1lYyInSiSD/odXOqLv1iJBTnjWfRqPB/v0wezZYWkKs9jBISAA2G0xMICAAbfgDSFZu+vhAeHjNg5uVXD38T++fx9bHnTpKJ4I0CA5T3Z4/vv0+5fl3z3Rzg927YcgQCA5XBE9POH0aVq6E8eMhLw/N+BnV7eDH4YBIBGFh0KFDbaJJjgl7++rZzxMWyWIWcdM5BIkMOR8VemmA47SstJc0OtPIrJ9htz7VnRweDmPHwoYN4OoKUF4OGzaAry94eoKLC1qy8vH+5j5+P7SJn1BQsWOx4+h5f5r0tpW5zgr6JkIQAMhMe7nv13FsFoNFFQNJqSAZWu07z1zrw5FX/Ob5r1/D8OEwZgz88w9QKAARETB3LhgYgI8P6OqiPaUinTd8d+dnpU9duVsG84f7dSIIlJcUH1w9gyBE6vJUVQWmahuGElOU+uLZyc2Lq7vEyAgiIiAsDGbOBIEAwNISnj4FMzPo2RN8fdGk9Sf3Q1pkyHlHWVrI+QUonUhr59E1XxZVrKbAzMgrFYrJ0gpxdlGFnjon883zd0mx1V2lpgahoVBRAcOGQVERAJsNmzbBjRuwaxeMGAHv36Nh6wxJkhe91w2ZvFRJTQulE0FklOSYhxyaWFmeqaLAfJ9Xll1UrqvK4TBpbDqZ9iK6hgvZbDh7Fnr3hgED4N07AACwsIAnT8DaGnr1Ak9PIIhWZ02xGAID6xlH1K2LIoHActgEWc4oSifS2hGLRBLvbQwajSRIKgVoNCoAUIAUf2/bJAoFtmyBefOgf394Khneo9PB3R0ePYLLl8HGBpKSWosdc3Jg61bo2BG2bq1PNCXc/Bsnd7sslrmFnCidCPIZHUx7VogopRXi7KJyXTWOyv977nyC3q5zt9rE4OYGXl4wbFiV9paREdy9C9OmwcCBsHUrVP+uZ0vg6VOYPx+6dIEXL+DaNQgLq09kV4/803uws3aHn2Q803R8cpBWzkDHGZHB5wv55bqqHDaTxmbSAOBdbqmGbsdO3a1qGYmTE+jogLMzpKfDokX/b5G6usLPP4OrK1y5Av/+CyYmLcpwAgEEBMChQ5CaCq6ukJICamqVX/asU5RvEqLSEp/+5h0k+7nHVifS2lHW0Jm60pPB4pQKoaRCxCsX8gk6AGWU65of6jP26QNhYeDlBW5unwY5s7LgbGTHfyfcfDxkHWlnD6tWgUDQEkyWnQ1bt4KhIXh6gqsrJCWBu3tV3axhM6oaYhUJBRe91znPX8tiy8m+DXBdJ4IAABQX5ERcP52W+IzJYhr3tmOw2LcvHHTb5c+WU/iheAoLwdkZVFVBX588dIhkMEpEIhGNpqCrBYEGy42yHsK//0Kfatfby7rb96dPwdMTgoLAxQWWLIGuXaUYd7DvntzMtGnunrJfW3BJPIJUy4V9ayrKSqa57/nRC/l8sLAgk5LKCSIFQPSpf0fVVFPTTdoWqPLHAsjOrv+K8UaFz4erV2H3bsjJgXnzYN48UFWVbgq5H9K83Scv97wiywuSqkondtgR5Ns4z1+bl5X+6Jrfj16Ynw9v35JVdRMACCKHxyvcnjwK4uKakxWyssDDA/T14dAhWL78U99c2rpJkqT//vU/T1rcLHTz028hPiEI8k3oTNZ09z23znq/fRnzQxfevQt0Oq+qbkqoqMi7fJkATc3mkf+nT2H6dOjaFbKy4O5duHULxo0DGq0hkoq6dZFfXmY5bGIzqh4onQhSLWra+uOXbvLbvqLmDT2/oKQExGLRt74RfX+D+Zcvm3gqqbwcjhyB7t1h2jTo1w/evYODBxt0bUBpcWGw3x6XxRupVFozqhu4OAlBasKkj13q82i/7SvmbThSy2fb1BRotG9MLlEoCt26Ub5zsZMTpKeDjg506gSdO8NPP336R18fqHVt6FAoNXSV//v/7VvYvx+OHQMrK9i+HQYPrulC6XH1yOaeg0brGjSzlVsonQjyHYbP+PXA6ul3LhwcPOGX2pxvZQVt2zJKSzUIIrdKMING0/3tt+/JX2nr+I4AABcaSURBVFISiESQng6pqZ8+wcGQmAiZmaCjAwYGYGICpqZgYAAGBtCxYy3VrdpZKQlhYbB3L9y+DS4u8PAhdOnSaLZ98zwq9UV0s1jI+eXvEc6wI8h34RXm7Vk+ZoLb5s4WA2pzflIS9O9PlJQU8Pl5AGIABTk5XT09WseOlAsXoI3ij+/JJhBARga8eAGJif+pamYmGBj8p6QmJtCtGygpff2wVZvciROwYwcIBLBwIcydC/LyjWlVkVCwa+noETN/N+1r17zqAy5OQpDa8jo+8vTOX912+ddyFjgvD7ZuJa9cIcrKoFs3WLWKNmAALFkC4eEQF1+7HvR3KSz8T0YlqpqcDHT6f0oqUdVevaqVzpEjwc0N7O0bp2/+BSGnPD++fzN91d5mVxlQOhHkBwg9t//lk/u/bPGj0Rl1jsTTE3buhMBAMDdvmLvMyICUFEhO/vQ3ORmSkmRwGWnuh7fe7pOay0JOlE4EqTskSR7ftEhDp8PI2SvrE8+FC7BoEZw8CQ4OjfSwyZp0kiR5cM3Mrv0GD3Cc1hxrAi6JR5Af+72fuGxLfHhIfHhIfeIZNw6uXIE5c1rvjvJPQi/xy0qsRkxuvllA6USQH4CjoDjNfY+/9/rcD2n1icfKCu7fh7/+Ag8PaG29rzJe0Q3fXc1uISdKJ4LUi3adug2ZtPjkFjchv7w+8RgZwYMHEBQEs2fD97ZUblFcPfJPj0GjdA1Nm3UuUDoR5IfpP3KqTscuVw5tqmc8bdvCvXtQUADDhgGX24A33PNbnybhzfOo1wlRQyYvae51AKUTQerCmF883r6MeRLqX8945OXh0iUwMYH+/SE9vWHutU67ZzYEIqHA33u98/w1zWJHTpROBJE+LLbczNVeQcd3fEhNrGdUNBrs3Qvz5oGV1f8dHLVQ7lw4qKVvZNrXvgXkBaUTQeqIhm5HJ9c1vluXVZTy6h+bmxvs2wfDhsG1ay3TXLkf3oZfP+00b3XLyA5KJ4LUne7WIzqZW57Z7S6VRcrOzhAYCK6usH9/SzOUZEfOwRMWKqm3bRk5wiXxCFIvREKB98pJPQaNGjh6hlQiTE2FESNgyBDYvbvumyXJAkV5Wckx4eWlxZq6HbkFHx8Hn1u680KzXpBUCb5NhCDS0IjcTM9fx01ftbejiXQmrgsKwNkZNDTA1xc4nGbZxrxxYueja74KckwKKRYSVF5J6film3vZO7eMEse3iRBECihr6IxfsunUjt9KuAVSiVBVFW7eBBYL7O0hN7f5GeTWmX13/A8rsUGNQ6rKUTXlgUmDSwc8Cj5mtJhCR+lEEClg3HtQD5uRftuWE4RYKhGyWODnB0OGgKUlJCc3J1NUlPLuX/5XV02uoITPKxeSJGQWljPoVCU2Jdh3N0ongiCf4TB1GUkQoecOSCtCCgU8POCPP8DaGsLCmo0d3r6K5bDZ8iyanqpcbjH/fV4plQLayhwFFjUlNhylE0GQz58lGm3qyt2RIeeTY6Spc3PmwMmTMGYMnDvXPOwgElRINv9k0KlMGpUvJOXZdKAAlUoRCgUtp7ixxiOItGijoj75tx2nd64syPkgxWiHDIHQUFi5Ejw8moERtDv8VF7OJ0gys7CcRqPoa3Dyivm8cmEZX9xW3wilE0GQb2DYtY+100y/bcvFImlu6WFmBhEREBAArq4gEsm0BdS09dV1Orz9WCbpp7MYn3ruBeWEfe2cO6F0IkhrxHbsPEVVzWvHt0s3Wh0dePAAMjLA0RF4PNnNftQt/6L8jwoqGjQGu1QgqhCKy4ViOpMzYNQs4142LaaUcV0ngkif8tLiPcvHDp/+q/kAKW8ELxLBokUQEwOBgaAlY54pSJK8dcbr2b3AOesPKmtoR9w4F/8wqKK0WFO/08BRMzqa9mox5YtL4hGkochMe3Vo7ayF//hptTOUeuSenrB3L1y7BsbGspJfkYB/1vOPotysmau9FZRUW3bh4pJ4BGkodDp2GTplqe/W+u6I/E3c3GD9erC1hXv3ZCKzxQW53qumMBishZtPtnjdlIDSiSANheWwSXpGXc/vW9sQkU+fDqdPw4QJ4OfXxNnMfpfi9fsE4142E5b9Ux9foSidCIJ8YuwvHh/TUyJvXmiIyO3s4M4dWLu2KRctJceE+ayeMWz68haw8TtKJ4LICgwme5q7542Tuz+8edEQ8ZuaQkQEBAXBrFlN4ODocfC5M7vdZ/y5z8LGsbWVLEongjQsGrodnBesPbF5SRmvQdwPSRwc5efD8OEN6+CoKgQhDjqxIyzQd8mO89LaLwqlE0GQzzAfMMy4j+3ZPasaaFWJvDxcvgw//QQDBjSYg6Mq8CvKjm9a/OF14qJtp1U1dVtnmaJ0IkhjMGrOH2W8wvtXjjZQ/DQaeHnB3LnQvz88e9aAGSkuyNm/amobZbU56w9x5BVbbYGidCJIY0Cj06eu3H3/8tG0F9ENl4qbG3h6goMDBAU1SPyZaa/2/jbBtI/tuCV/0+j01lygKJ0I0kgoq2tPXrHdd9vy4oIG3L54zBi4ehXmzYMDB6Qc8/OIW4fWznaev6a1TaZ/E3ybCEEalWA/z7cvn7r+daxBvfSkpsLw4TB0qNQcHD28evLe5X9nrd6vZ2SKhYgvYiJIY0OSxOH18/Q7mxn3sk54HFpamKvZvlMPa0epu4osKAAnJ9DSgpMn6+XgiBCLrxz6Oy3x6Zx1PsoaOliCKJ0I0jQUF+RsmT+ECmQbFlABREDjVYidF3r0lrbXMz4fZs2Ct2/h6lVQV69TDOWlftuWkyQxdeUetpwCll2ldOJYJ4I0NvcuHxHyKzh0QkWeoSTPUOFQqITg4r41aYlPpZsQiwWnTn1ycJSS8uPt1o8Ze38dr6bdfva6g6ibX4DSiSCNSkVZyePr5/Q15Mr44lwenyDID/nlbAZNQ5ERfHJHA3TvwMMD3N3B2hoePfqBC98lxXqtnGQ1fJKT6+qW4TxdutDRBAjSmHx4kygnx2bRxe3UOO/zy3llpQosuoYymyDJ9ykvGijRuXOhXTtwdgYvLxg//vvnxz4IunJo06QV237qMQCLDKUTQZoekiQByMpOn4gECo1CAaCQQBCEWCRsoM2Hhg6F0FAYORLS0sDdvabbCz134Emo/4JNJ9q274TlVW1zHqeJEKQxKS8t/mv6QF0VWnZBBYtBVVNkZeSXy7FpbDqVK2ASJGFg2tukj61x70H/a+/ug5q+7ziAf/ILCUl4ElKewqNVtCAWdEoVRQSxILHCWrS6a6uo3DmHl+lmV1e2016723q9aadMPbueOtGiXBEVkRYF5PFAHUgH8iAREKU8pEBA8pz9QS+jATF6CEl9v/7LN8n5yyfh7eeb7y+/r4Nw4q8C395OYjGFh9P+/dTZSYcP64uKdNbWtHo1e/Nm4nLU5w6mdN5vTkw5bOf4Et6sx8EKO8AU+Prw3vIrX9nzrZwdeCwinU7f1v1Iq2e2fvSlaPrsxury2oprtRX59k4uAa9FBCyM8PWfzxren3ciyOW0bh3J5VRdrVOre5TKfiLGxkboYC/YFv8HHy/1hl1/41jz8TYhOgHMi1ajPvGX37TW3RSwNWyG1DpGrtSLE98Pjf2V4TE6nbblTlVtZX5jVWlv18PZ88MCQiJnz186ISvd9+6Rn59Oo2kkGhjxJ+ns9pKg9YGTlRVWjyc9Oq9fv15SUsJms+fNmxcVFTXOf5WITnjBNVaV3i7Jlcs63XxnLYx6S+ju/bhHyr6/3/CfktqK/ObaG15+c2cFhQYujnL2mP7M//SePfq//71bpTK+yJKdXcCZM3yxGG/OJEanRqNJTk5esmRJWFhYXV3dzp07hUJhRkaGu7s7ohNgQqiVQ43VZbWVBbUV+Ryutf/CiDkhES8HhjztlThCQ7VlZVIi46t7MowoJcVt3z4WSv3E6JywFfbPPvssIiLi7bffJiJfX9/AwMCZM2e+99573377LQoNMCE41vyAkMiAkEj6DXW0NtZVFOSePth5v9kvaJFfUOicRSvspr00zrcE/6241iGt5/AE03ivEQnGbGg4HOSmSSas9QsODp49e/apU6c4nB9PrYiJicnNzW1tbfXy8kLXCfCcDPT13LlZVFeZ3/CfUqG7V8DCiICQSKOLdDyQ3vnXviSWRsHWq4jF9A9SU8eC85WbNVruyD9KO7vA7GxuWBiKOoldZ29vb2Zmpkwmc3X98YwKDw8PImpoaBgzOgFgQtg6CBdExi+IjNeolNLamw3VpWmf/U6rVs2avzRg4fJZ85YqHskP//EdjWLA+yUbNsMhImtGo9FcF8/TZ9349YhuxksgsFq0CBWd3K6zubn5hx9++MUv/r9LSWRkZH5+vlQq9fX1RdcJMJl6OtpqK/JrK/PbGmsEtg76oR5Gp5UrNV5CgUKl7ehVuDvx2rpZ5yr/3fa9I8MwNjZO/v4cR0dGp6OMDLK3Rwmf0HU+r/x68OCBj49PbGxsVlbW2JmN6AR4/h7Jew/8Nl6g6xVwrXr6lfIhjVav93Di87js7kdk/8rvW3rf5vNp+XJWZCRptSSR0PXrlJ1NmCtO0oTdiEQiEYlEqampqDLAFBLYTeNa85mhPiLicdmyQTWHzeJYMcNTzuBXVclv/H9daHiDo88/p9BQunCB5s1D/R7rsdE5ODh44cIFnU433myfxVq5cqWzs7PR+MmTJ8vKygoKCjw9Pcd5+
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X_1.dat
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X_2.dat
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X_3.dat
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