Plots.jl/examples/meetup/slides_20151028.ipynb
Thomas Breloff 1db36c05a8 animations
2015-10-16 16:36:40 -04:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Visualization and Learning in Julia\n",
"\n",
"Tom Breloff\n",
"\n",
"https://github.com/tbreloff"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Outline\n",
"- Background\n",
"- Julia packages\n",
"- Plots.jl\n",
"- Fun with data"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## My background\n",
"- BA Mathematics and Economics (U. of Rochester)\n",
"- MS Mathematics (NYU Courant Institute)\n",
"- Trader, researcher, quant, developer at several big banks and hedge funds, including one which I founded\n",
"- High speed algorithmic arbitrage trading and market making\n",
"- Machine learning and visualization enthusiast\n",
"- Lifelong programmer (since learning BASIC in 4th grade)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Before Julia\n",
"- Python and C/C++\n",
"- MATLAB and Java (so many files!!)\n",
"- Throughout the years: Mathematica, Go, R, C#, Javascript, Visual Basic/Excel, Lisp, Erlang, ..."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Things I like\n",
"- Python\n",
" - Solid packages\n",
" - Easy to get stuff done\n",
"- C/C++\n",
" - Fast (when you put in the effort)\n",
"- MATLAB\n",
" - Great matrix operations\n",
" - Easy visualizations\n",
"- Java\n",
" - Hmmm... \n",
" ```\n",
" public static boolean DoTheFunctionNamesReallyNeedToBeLongerThanThatMaryPoppinsSong() {\n",
" return true; \n",
" }```"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Why Julia?\n",
"- Easy to code\n",
"- Fast with little effort\n",
"- Solid vector/matrix support, but more flexible\n",
"- Macros and staged functions\n",
"- so much more!\n",
"\n",
"(Slow clap...)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Julia's Package Ecosystem"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Top packages by stars\n",
"Package | Github Stars | 2-week change | Type\n",
"------ | -------- | ------------- | --------\n",
"Gadfly\t| 732\t| 14 | Plotting\n",
"IJulia | 732 | 11 | Workflow\n",
"Mocha | 496 | 36 | Learning\n",
"DataFrames | 230 | 12 | Data Structures\n",
"PyCall | 204 | 4 | Language Wrapper\n",
"JuMP | 182 | 5 | Optimization\n",
"Escher | 135 | 10 | GUIs\n",
"Optim | 131 | 4 | Optimization\n",
"Morsel | 128 | -1 | Web (deprecated)\n",
"Distributions | 125 | 7 | Statistics\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Recent trends\n",
"Package | Github Stars | 2-week change | Type\n",
"------ | -------- | ------------- | --------\n",
"Mocha | 496 | 36 | Learning\n",
"Gadfly | 732 | 14 | Plotting\n",
"DataFrames | 230 | 12 | Data Structures\n",
"IJulia | 732 | 11 | Workflow\n",
"Escher | 135 | 10 | GUIs\n",
"Interact| 102 | 8 | GUIs\n",
"Distributions| 125 | 7 | Statistics\n",
"Plots| 23 | 6 | Plotting\n",
"Seismic| 7 | 6 | Statistics\n",
"Immerse | 23 | 5 | Plotting\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Statistics and Learning in Julia\n",
"- Stats (mostly in JuliaStats)\n",
" - StatsBase\n",
" - Distributions\n",
" - DataFrames, DataArrays, NullableArrays\n",
" - MultivariateStats, GLM\n",
" - OnlineStats\n",
" - many more...\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Statistics and Learning in Julia\n",
"- Optimization (mostly in JuliaOpt)\n",
" - MathProgBase\n",
" - JuMP\n",
" - Optim\n",
" - Convex\n",
" - NLOpt\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Statistics and Learning in Julia\n",
"- Machine learning\n",
" - Mocha\n",
" - GeneticAlgorithms\n",
" - Orchestra\n",
" - TextAnalysis\n",
" - Clustering\n",
" - OnlineAI\n",
" - many more..."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Visualization in Julia\n",
"\n",
"Lots of packages: Gadfly, PyPlot, Vega, Winston, UnicodePlots, Qwt, Bokeh, Immerse, GLPlot ... \n",
"\n",
"Strengths:\n",
"- Interactive: Immerse, PyPlot, Qwt\n",
"- Fast: GLPlot\n",
"- Easy/concise: UnicodePlots, Winston, Qwt\n",
"- Pretty: Gadfly, Vega, Bokeh\n",
"- Native: Gadfly, Winston, UnicodePlots\n",
"- Features: PyPlot\n",
"\n",
"Learning more than one or two packages is time consuming and impractical...\n",
"\n",
"### Why do I have to choose one?!?"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# What makes good code design?"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Good design: AbstractArray\n",
"Many concrete array-types:\n",
"- Dense arrays\n",
"- Sparse arrays\n",
"- Ranges\n",
"- Distributed arrays\n",
"- Shared arrays\n",
"- GPU arrays\n",
"- Custom data structures\n",
"\n",
"Common code is implemented once for AbstractArray, and all concrete types get the benefit."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"5-element ScaryVec:\n",
" 1 \n",
" \"BOO!\"\n",
" 3 \n",
" 4 \n",
" 5 "
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type ScaryVec <: AbstractArray{Int,1}\n",
" boo::Int\n",
" n::Int\n",
" ScaryVec(n::Integer) = new(rand(1:n), n)\n",
"end\n",
"Base.size(sv::ScaryVec) = (sv.n,)\n",
"Base.getindex(sv::ScaryVec, i::Integer) = (i == sv.boo ? \"BOO!\" : i)\n",
"\n",
"sv = ScaryVec(5)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"4-element Array{Int64,1}:\n",
" 1\n",
" 3\n",
" 4\n",
" 5"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filter(x -> isa(x, Number), sv)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Good design: AbstractArray\n",
"- Inheriting from AbstractArray gives you a lot \"for free\":\n",
" - Iteration (`map`, `for x in ...`, `filter`, ...)\n",
" - Operations\n",
" - Printing\n",
" - etc\n",
"- Few methods to implement... only what's needed.\n",
"- Abstractions put overlapping functionality in one place\n",
" - Easy to code\n",
" - Easy to maintain\n",
"\n",
"\n",
"### Imagine if there were no AbstractArray..."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Gadfly : `____________` :: ScaryVector : AbstractArray\n",
"\n",
"Thinking of graphics packages as concrete types, we see that we have many different types, but no abstraction linking them together. "
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Plots.jl\n",
"### The AbstractArray of plotting..."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[Plots.jl] Initializing backend: gadfly"
]
}
],
"source": [
"# setup... choose Gadfly as the backend, set some session defaults\n",
"using Plots\n",
"gadfly()\n",
"default(size=(600,500), legend=false)\n",
"\n",
"# create parametric functions\n",
"fx(u) = 1.6sin(u)^3\n",
"fy(u) = 0.1 + 1.5cos(u) - 0.6cos(2u) - 0.25cos(3u) - cos(4u)/8\n",
"\n",
"# plot and annotate\n",
"p = plot(fx, fy, 0, 2π, line=(5,:darkred), xlim=(-2,2), ylim=(-2,2))\n",
"annotate!(0, -0.15, text(\" I ♡\\nPlots\", 45, -0.1π, :darkred));"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
},
{
"data": {
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",
"text/plain": [
"Plot{Plots.GadflyPackage() n=1}"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"source": [
"# use the same parametric functions to create a custom marker\n",
"us = linspace(0, 2π, 100)\n",
"heart = Shape([(fx(u), -fy(u)) for u in us])\n",
"\n",
"# generate some data\n",
"n = 50\n",
"xy() = 4rand(2) - 2\n",
"# x, y = Vector[4rand(n)-2 for i in 1:2]\n",
"# numbers = [(x[i], y[i], text(i)) for i in 1:n]\n",
"\n",
"# add to the plot\n",
"title!(\"Let me count the ways...\")\n",
"scatter!(zeros(0),zeros(0), z=0:n, marker=(heart,15,:reds))\n",
"\n",
"# animations!\n",
"anim = Animation()\n",
"for i in 1:n\n",
" x, y = xy()\n",
" push!(current(), 2, x, y)\n",
" annotate!(x, y, text(i))\n",
" frame(anim)\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false,
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO: Saved animation to /home/tom/.julia/v0.4/Plots/examples/meetup/iheartplots.gif\n"
]
},
{
"data": {
"text/html": [
"<img src=\"iheartplots.gif?0.35511351462964247>\" />"
],
"text/plain": [
"Plots.AnimatedGif(\"/home/tom/.julia/v0.4/Plots/examples/meetup/iheartplots.gif\")"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gif(anim, \"iheartplots.gif\", fps=3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Fun with data - UCI Wine Quality Dataset\n",
"![wine](wine-toast.jpg)\n",
"\n",
"P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. \n",
"Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553, 2009."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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WA8OE6+udCCGDQetwMDabR6+naVpTX+9yOn1Wq5EgUGVls98fzskxhkJsba2D5wWTSe/xHI+i09FNTR673Wsy6TQaqqbG7nIF8vJMHHciit8frq93ShIyGo9H0elorVZTX+9yOHxWq5EkicpKmxwlHOZqax0cJ5jNeo8n2NjooihSr6dtNm9zcySKw+Vi8vLM8u8SDHJWaySKZDTqnE6mqcmj02kiUSwWA0mSlZU2hgnn5p4UxesNNjScFMVo1Gk0VG1tJIpYXd0sRwkE2Lo6pyjKUfxNTW6tVqPVahoa3FFRmhkmmJtrYlmupsbBsnwkCkkSer22udnb3OwVRZEkycZGt8vF5OaaRFGqqooTxeXyNzW5aVqj0x2PYjYbKIqsqmr2eoO5uSaO42tq7HIUny/U0OAiCMJg0DY3+5qbPQaDlqapujqn08nk5pokSY7CWq3GYJCtq3MKgmgyRaJQOh3d2Oi2233ybRMTJRzmLRY9w4Tq649Hsdt9NptHrz8RJSfHJEmoqqo5EGBzcozyzSlHidycOh3d2Oix270tbk6+utoeDnMWi0GOIt+cv0eRb06n08lEbs7fo7CRIhDv5tRrNCeitLw5o4tA5OZsaHDl55sJIvbm/L0InLg54xaB6IKWvAhYLAmLQKKbM6oIxN6c0UVAvjlPLgLNDBPKzTXKN2d0FJIk9Xpavjmji0BurlkUxaqq5lAo/s0ZXQTkm7Oystnniy0C8s35exGIc3NGFwH55mxZBOSb02IxhMN8dbWdYUIxN2d0EZBvm+goMTdnMMjV1Z10c/5eBOLcnL9HSXRzammakm/OuEUg5u9z5ObsqH+fOU7QajVx/z5Haq50m0YdDkdhYeHOnTuHDx8uH9m1a9fIkSMZhknZRsrzQm2ts7y8KJ1AQHlNTR6jUWex6NVOBMR35EhT375d1M4CxOfxBFiWLyqyqp0IiK+iwlZeXkSSyZpG060IRVHU6/U2my03N1c+4vF4cnNz6+vrS0tLk79XkhDH8dAFhS2OE0iSoChYbw9T4TAHM9WwJTfKaTQwExdT6RSfdP/2kSQ5ZcqUDz74IHJk1apVRUVFJSUlKd9LEAhqQZzRNAW1IM6gFsQZRZFQC+IsneLTivrprrvumj59+s6dO88444xdu3a9/vrrL730UvKhODKeF5ua3N265acfCyjJbvcZDFpY/QdbVVX2nj0L1c4CxOfzhTiOz883q50IiK+mxtGtW37yptFWPAdMmDBh1apVu3btuvPOOzdu3Pjmm2/eeOON6b1V4jhYlBZfLcdQAaxA8cFZ9JhGgKF0ik8rllgDAAAAOh6FtmGCbUpwBk+EmIMnQpzJE9fUzgIklE7to9A2TLW1sI8Mvux2n98fVjsLkFBVlV3tFEBCPl/Q6YQ18PBVXe3I8jZMmSEIQqeDUaP4ommKolIPegJqgeKDMxg1ijmdTpPNbZgAAACAjkeZPkIJWt5wFgpx0ImLM4aBzQ3wxXFCOMypnQVIyO8Pp3zcU6aPUGxu9ioQCGTG4wkEg1CS8dXY6FE7BZBQIBD2eoNqZwESamrypGz4VKLvgSRJ2IMJZyaTjqahFwpfeXlQfPCl09HQR4iz3Fwj9BECAAAAySjRNCqKEuxQjzPYoR5zDodP7RRAQqEQB2MgcOZ0Mimf95SpCEWPJ6BAIJAZvz/MslAR4svlguKDr3CYCwSgIsSX2x1I2e6pRNOoJEmBAAtrOmMrFOI0GpgLhS+GCZnNsFskpjhOEEURdgjBlt8fNhp1ybsJoY8QAABAp6bQ9ImGBpcCgUBmnE4G2nZwVlPjUDsFkBDDhGAMBM7q6pxY9BFKkgRjMXDGcYIgQMMAvqD44EwQRFiPAmfhMI9JHyESBAG6oLAlCCJBEMk3rgQq4jiBpqH4YEoUJUmSKEqJhwqQAZ5PXftAHyEAAIBOTYlvMTwvVFY2KxAIZKapyePzwWqW+DpypEntFEBCHk8AlpDEWUWFDYttmBAioGEHZxRFQrsozqD44IwkSWgXxVk6xQeaRgEAAHRqyowaRbBwCc44ThAEUe0sQEKwyw/OYNQo5tIpPsrMIxTq62EeIb6cTiYQYNXOAiRUU+NUOwWQEMwjxFxdnStlH6ESm+8QBAHrq+FMr6ehFwpnZjMUH3zRtIZIuc0PUI/ZnGJ9NQR9hAAA0OFx4bC9qsZRXSvyvMFqzetWWlDWjSBb3SLIhcL26hp3fSMXCmlNxqKePfK6lZLUKf81WomKUBQlvz9sscCqwZgKBlmNhoKHQmx5vUGr1aB2FiA+luVFUdTrtWonEl/zsartqz47vPUXq8VSkJdP0xqW55tsNkFCQ6dPPH3uTL3ZlM51nLV1v/x39cFNW/Ly8wvz8kiCCIbCzXa7gKShUyeOnDvDmGNt798lMz5f0Gw2qL/oNs8LtbXO8vKi9g4EMtPU5DEadfBNBVtHjjT17dtF7SxAfB5PgGX5oiLsqgE2EPxh+btHt2wbNXzYwH59ddqTGtgbbc27Dx08WlU9/vqrBk8an+Q6As//sPz9A99vGDl48KB+fS1mc/RP3R7vb/v27684MvryBSNnTUf4tRJXVNjKy4uSzxBT6InQ5wvm5BjbOxDIjN8fpmlKq1WiwxhkwOXy5+Wl9bUdKC8c5gRBMhrxeiL0NDZ9/PDS0vyC8WefpaUT5tbsdH7+3Xe9Rp818cZr4tZhIR/z0SNPGUViyrixBl3C78pur2fN9z/k9Oox/c5bNFq8Pgq3O5CTY0jejwt9hAAA0KF4bc0f3vXQ2UOHDh04MOXJYTb8yTdri4cNmnTTdTE/YgPBlfc90i0nb/yoUSkf9QRB+HbDxoBWc9Fjf6U0p9i3aoW2YYIliHDm8QRCIZiphq/GRrfaKYCEAgHW6w2qncUJbDD4vwceP3PwkHRqQYSQTqu7aOrUml927FrzbcyPvnr+lUKDafzZZ6fT4ElR1LTzx2sCoa+XvZZJ3u3GZvPgsg2T3w/b3eErFOI4DmYE44thoPjgi+N4rFY8+P6Nd7vmFYwYPCj9t2i19KxJEza++6G74cSqtnvXfu+prJ44ekz61yEQuuD88Q179h3atKUVGbczhgmnbPdUoiKkKLKkJEeBQCAzeXkm3Ho4QLSuXfPUTgEkZDLp8BkA0XDwSOXW7eefc05r35ifm3fmkCHrXn1Tfhn2+398e8Xkc89t7fZ5tEYz7bzz1r32Fs/i8uWgtDQ35URPJSpCgiCwHVsMEEJarQZWDcYZfE3BmUaD0UCzrf9eNWr4cK2WzuC9pw8Z6qyqrtt3ECG0/ZMvepV171JYmMF1unbpUlJUtHft+gze2x4MBm3Kll1ltmES6+pgjSh82e0+aLvGWVWVXe0UQEI+X8jpZNTOAiGEvM32+v0HB/c/LbO3kxR5xuAhv6z8hGe5HZ9+ddaQYRlncuaQIb9+/EXGb8+umhoHJtswSdAFhTNBEFPeKEBFUHxwJooiJmvWH960tXd5OdWGdV4Gnta3Zs/+vd99X1hYkJebeX9W1+JiLhC0V9dkfIUsSqf4KFERajQUzKbHWZcuOTCbHmcwmx5nOTlGTGbTV/78a9+y7m25gpbW9uhRtuGdfw/o2bNNqRBE7549Kn/9rU0XyZLevYtT7reqUM8QPHDgTJIkmE6KM1HE4oEDxIVP8WmurinMqFcvWo8uxSHGX9a9WxuvU5yXbz9a2caLZEU6tY8yfYRCdTV0cuDLZvPCAH2cVVQ0q50CSMjrDdrtPrWzQFwoHPYHraa2rkBUVFio1WpzLW19xs3NzXXV1rfxIllRWdmMRR8hQRA6HS6jqkBLNE1RFHYrBIIIKD44oyiytXMM2gMXCtE6bduX+iwqKLhoxgVtv46W1rChUBsvkhU6nSblb6NEAaMosrQUJkLhKz/fnPokoJ6ysgK1UwAJmc1Y9K8LPN+WYTIRtEbTraSk7dehKEoUsBjk1a1bfspzYGUZgEIhjuexuGVBXAyDxTdrEBfHCTisLGOwWoMBv9pZnBAMhgwWi9pZIISQ34/HyjKw1ijmPJ5AMKh+SQaJNDZ61E4BJBQIhHFYa1SjpTU0HcSjNRIh5A/4zfmpH8UU0NSEx1qjJEnA6HycGQxa2JUXZzk5sCsvvrRaDSYrZxX36tnY1JT6PEU0NNuLT+utdhYIIWS1ptiVFylVEZIFBVg8I4O4rFaDXp/JmkxAGZhMUwNxGQxaTL7odx0ysK7JpnYWx9U3N3Ud2F/tLBBCqLDQgsVao6IouVwYNV6DGAwTCod5tbMACTkc6o/OB4mEQhwmYyB6n3X6keoqtbNACCGPz+fx+koH9FM7EYQQcjoZLJpGRVH0eAIKBAKZ8fvDLAsVIb5cLig++AqHuUAAi4qwa/9+EkU1YPBQeODwkf7jRmOyPa/bHcBisAxFkdC2g7OcHKPBAE2j+IJdzHBmNOqsVjw6cQli2Iwp2/buVTcLXuB3Htg/7IIp6qYR0aVLDhZNowRBmEw6BQKBzOj1NA4zgkEimMxUA3HRNKXT4fI9csTMqXWNDXanmrv97Np3oLR/v+Le5SrmEM1k0mExWEYQxKYmGP+NL5fLHwyyamcBEqqvd6mdAkjI7w/j0/VD6/XnXHLR+q1b1UogEAz+vHPn2EWXqZVASw0Nbiz6CCVJgr+zOGNZnudhWWd8BQJQfPDF8wJWXewjZ1/AEujg0aOqRN+wbdvgaROLynuoEj2uYJDFpI+Q6t4di5mVIK7CQgu0XeOsZ8+2bikA2o/FYsBqkUKCJKfevnj95i1en9KDjQ9XVNQ128ZcvlDhuMn16FGAxTZMBIGgCwpnFEWmvFGAimC5A5yRJEFRCu1nl6YufXuftWDOl99/Lyq4Y7DH5/vup82z/voXWo/Xt+p0ah+FtmGqrIR9ZPDV1OTx+XBZmQm0dOQILsuFgJY8ngCGS0ieNX+OsWvJus2blQnH8dyn364dfcXCkn59lImYvooKGxbbMCGE3TcmEI0gUo4uBmqCTbJwRpJYlh+CmHHPbfVu547de9o7lCRJX6xbXzps8MjZ09s7VgbSae4iMNlbGQAAQHZ5mpo/vOuhCaNG9e1V3n5RvvvpJ7ckznv8fkxm0GdAmVGjCKtRVSAGxwmCgn0JoLVw2OUHJCIIIra7mOV0Kbro0fvW/rSpsrqmnUJs/GVbg9c99+G7sa0F0yk+yswjFGAiFM6cTgYG6OOspkbN+dEgOYYJ4byWcnHv8jkP3r3m+x9q6uqyfvHNv/56tKF+wRMPaQ14rK0TT12dC4s+QlhZBnN6PQ3jEnFmNkPxwRdNa/BZWSau7oMHzH7gL59/t66moT6Ll926Y+f+ysqFTz9izMV6CUCzOfXKMtBHCAAAHV/Vjl2fP71s1sSJZd26tf1qW3bs2F9VdfHTj1gKC9p+NdUptA0TjM7HWTDIchymnRwAIYTDBuggEZblQ6FToGeh58hhs++/8/N169reRrp5+68Hqqsv+b9HT4la0OcLYrGyjCiKsKEazrzeYCgEwzHwZbNhN00NRASD7KnyRb/H8CGzH7irjXXh5l9/PVhbc8kzS8z5eVnMrf00N/uwWGuUJMm8PJMCgUBmzGa9TofpiC+AECoowGgFLxBDr6dNplNme5AewwbPfuCuz9evr67NpC7cvGPHwdraS55ZYjpFakGEUH6+GfoIAQAAnKRm975Pn/jbrIkTWtVfuPnXXw/V1lz8zKOmvNz2y00VCm3DhOESRCDC4wlA0yjOGhvdaqcAEgoE2FOuE7ds6KDZ9//li++/T387+1937zlQXX3x00tOuVrQZvNg0TQqSZLfH1YgEMhMKMTBYBmcMQwUH3xxHH8qrnjQY/iQGff8efW339pdqWep7j14cMehg6dWi2gEw4RTtnsq0TQqSVI4zOn12vYOBDLDsjxFkbAeLLYCAdZohOKDKZ4XRFHSak/JXvYDP2z68fV3Lpkz22JKOIzjWFXVNz/9dOn/PZbXrVTJ3LIlGGT1em3ybkKFJtRDLYgzrVYDtf7ZYUAAACAASURBVCDOoBbEmUZDnaK1IEJowPixIy6a+cnXX7Nc/BkgNrv9qx9/nPvQ3adoLYgQMhhS1IJIqW2YxLo6WCMKX3a7D9qucVZVZVc7BZCQzxdyOhm1s8jcqAVzS4YO/uqHDahF62AwFPps7dpJN13fdcBpquSWFTU1DiyWWENIgi4onAmCmPJGASqC4oMzURRP9TXrp9x6QwBJ23btij4oIfTl+vUDJo0fMH6sWollRTrFB6ZPAABAZ+dpan7/1nsXzLygqOD4YjE79uzZX193+bKnSKrjL0SsUM8QPHDgTJIk+D6EM1E8tR84OraOUXxyuhSNu+aybzdulH8TL8Ns+XXHBXff1gFqwXRqH2X6CIXqaujkwJfN5oUB+jirqGhWOwWQkNcbtNs7whKSw6ZPJi2mA4cOIYQ2bd8+Ys4FBWVZWJ5bdZWVzVj0ERIEASt44YymKYpKNawKqAeKD84oitRoTvnHJoQQIohx1165ddcul9tTVVt71vzZaieUHTqdBpZYAwAAkK4Pbv8r7/H2mTR+7JUXq52LchRaWeaU2Kak02JZ/lQf9taxBQJQfPDF8wLL8mpnkTUDJ59va7YPmjBO7USyJhhksdiGSRDExkaPAoFAZlwuP/ypxVl9vUvtFEBCfn/Y4wmonUXWdB88wJiTc+pOn2+pocGdsuFTib4HkiQsllNmm5JOyGDQ0nSH6OTooHJyDGqnABLSajUk2XEWZsrv3vXCh+5SO4tssloN0EcIAAAAJKPMDvWSy+VXIBDIDMOEwuGO08nR8TgcHWF0fkcVCnGwQiHOnE4Gi22YRFHsSG3oHY/fH+5Ivf0dj8sFxQdf4TAXCEBFiC+3O5Cy3VOZPkKyoMCiQCCQGavV0EEmQnVQxcVWtVMACRkMWpjoibOiIguRqpMQ+ggBAAB0agpNn2hqgukT+HK5/MEgTJ/AF0yfwFkHmz7R8aQzfUKhCfXwdxZnLMvzPEyoxxfM8sRZB5tQ3/GkM6FeiaZRSUKCIEAvFLYEQSQIgiRhuVFMcZwAEz2xJYqSJEkU1XGmEnYwPJ+69oE+QgAAAJ2aMtswiTU1DgUCgczYbF6GCamdBUjo2DGb2imAhHy+DrINU0eFyzZMAAAAALagaRQAAECnpsyoUQSjqnDGcQJsw4SzcJhTOwWQkCCIPC+onQVIKJ3io8w8QgEmQuHM6WRggD7OamqcaqcAEmKYEKyljLO6OlfKPkIlVgYiCMJg0CoQCGRGq9VoNNBbjC+jEYoPvmBiGOYMBi1swwQAAAAko9A2TD4fjM7HVzDIchx0cuDL6w2qnQJIiGX5UAh6FvDl8wVTPu5lWBFu2rSJotJtEBBFETZUw5nXGwyFYDgGvmw2r9opgISCQRa+6OOsudmXsuEzkz5Cr9d71VVXiWK64wxJkszLM2UQCCjDbNbDCl44Kygwq50CSEivp2katmHCV36+OWUfYSb/f7feeqvL1YpRoCRJ5OQYMwgElGEy6dROASQD3yNxptPRaqcAksnNTV37tLppdOXKlf/+979ffvnl9N8CTaOYg6ZRzDU3Q9MovqBpFHN2e+qm0dZVhDU1NTfeeOMTTzxxxhlnpP8uGCyDORgsgzmPBwbL4AsGy2DO6009WIZasmRJmpcTRXHevHmlpaWvvfaa0+l85ZVXWr6X4wS3OyCKolarCQZZrzdIkgRNU6IoBoOcVqshSULeBtZg0AqC6HL5eV7Q6ehwmJNLO01Tfn/Y5wtpNCRFkR5PwO8PGww0QoTTybAsp9dr40bRaCifL8gw4aRReI8ngJBE05qWUfR6miAIh+N4FJ4XXK7jUUIh1uOJRAkxTEirpUiSdLn8gQBrNGpFUXI6/RzH6/U0y/Jud0CSJK02WZRwmDMYjkcRBFGn04RCnMcTJEmk0VAME/L50o0SCIS93uNRvN4gw4T1eg1BEE4nEwpFRxF0OlqOQhCIpo9HMZl0BoPW6w34/azBoJWkZFEoitBoKDmKTqchyegoosvlTxSFpimKIt1u+T9Ui9CJKBwXHYX1eoNxo0T/h8pR5NsmcRQaIeR0+llWjhJ728hR5NsmbhRlb045SpybkyAIk0kXfXOmihJz24hO5/Eo8n9oyiKQ+OZsdRGId3OmiBL9HypHcbv9fn/qKBRFajRkG25Ov1wEom/Ok6PEuTlpmgoG2XCYj7k5UxWB4zfnyUUg9uZMUgTi3ZxylJibM1kRaOXNeUr+fc7PN1EU5XLF+Q+N1Fyt6CN8/vnnd+7cuWvXriTjRQkCURRJkiRCiCAIiiJJkiAIQv505B5LkiQQIqJOJqJPlk+gKJIg5H+TkWgURVJU7BtbnCzJUSiKlB+Ho6+c6I0URUoSirzx9535iJj0IvlHv5EgpKj0yJRRIifHi4KifheCokj5g0oQJfYTk09o8cbojzf+G7Vaze+XlaI+hJYnkzHpRX0I0R8vGe//hfz9ykSkHSLuh3DylQlRPHFy5DaLSS9llJNvm7hvlGKiyCf//sYMb84Wn17ym5NI9OlFZgSnvJN/j0L8frIU9x5r1c0Z/XtFF4E0b86WZUc+WaOJuTnjpydHIUkSISnuf+LJN+eJKClvzpM/hMj//onfJVF5ObkIIIqiorsJ0y4CBEJSi08p9uakKDKyKkpMEYh3c8aW0Lj/iQk+Pamj/n02GLSiKMX9+xyR7oT6ioqKAQMGLFmyZN68efLLmTNn7t+/X6/Xl5eXJ38vz4tNTe5u3fLTCQSUZ7f7DAYtDJnBVlWVvWfPQrWzAPH5fCGO4/PzYWQvpmpqHN265SffeDzdJ8L6+nqO4x544IEHHnggcnDgwIFnn332li1bUr1bgi4onAmCmHItPqAiKD44E0UR1qzHWTrFJ8Ml1g4cODBw4MD03yuKUvIKGago0kahdiIgPlEU5eYsgCEoPphLp/aB0gUAAKBTU6Ii5HmhutquQCCQGZvNyzBhtbMACVVUNKudAkjI6w3a7TBPGl+Vlc0pu34yrAgHDBiQfrsoQRA6HSxBhC+apuThXgBPUHxwRlEk7MSEM51OA9swAQAAAMko0TQqSRKsvIAzluVh2BvOAgEoPvjieYFlebWzAAkFg2x7bcPUKoIgNjZ6FAgEMiOvv6B2FiCh+vpWrHEPFOb3hz2egNpZgIQaGtztsg1Ta5EkYbHoFQgEMmMwaGEbJpzl5BjUTgEkpNVqYHILzqxWA/QRAgAAAMko8UVGFCWXy69AIJAZhgmFw9DJgS/YxQxnoRDn98PsI3w5nUyWt2HKjCiK0IaOM78/DL39OHO5oPjgKxzmAgGoCPHldgdStnsq00dIFhRYFAgEMmO1GmAiFM6Ki61qpwASMhi0MNETZ0VFlpQL4EEfIQAAgE5NoekTTU0wfQJf8iaZamcBEoLpEziD6ROYS2f6hEIT6uHvLM5Ylud5mFCPL5jliTOYUI+5dCbUK9E0KklIEATohcKWIIgEQcA+WdjiOAEmemJLFCVJkqK3jwdY4fnUtQ/0EQIAAOjUlNmGSaypcSgQCGTGZvMyTEjtLEBCx47Z1E4BJOTzwTZMWGvHbZgAAACAjgGaRgEAAHRqyowaRTwvKBAIZEYQxJRNB0BFHAfFB1+iKMEuZjhLp/ZRZh6hUFvrVCAQyIzd7oPFEnFWVWVXOwWQkM8XdDoZtbMACVVXO1J+0VdiZSCCIAwGrQKBQGa0Wo1GA73F+DIaofjgCyaGYc5g0MI2TAAAAEAyCm3D5PPB6Hx8BYMs9ELhzOsNqp0CSIhl+VAIlv7Bl88XTPm4p9A2TLChGs683mAoxKmdBUjIZvOqnQJIKBhk4Ys+zpqbfSkbPhXahiknx6hAIJAZk0lH07CPDL7y8qD44Euno6GbEGe5uUboIwQAAACSgaZRAE2juGtuhqZRfEHTKObs9tRNozBYBsBgGdx5PDBYBl8wWAZzXm/qwTLKbMMkhcOcXg9zoTDFsjxFkbCPDLYCARamEmKL5wVRlLRa6GXHVDDI6vUpphJCHyEAAIBOTZkl1sSGBpcCgUBmnE4mEIAl1vAFu5jhjGFCLpdf7SxAQnV1Tiz6CCVJCod5BQKBzHCcIAjQMIAvKD44EwQRNhXAWTjMY9FHiBASRYkkU03lACqR7wEi5VwboBJRFEkSenAxBcUHc+nUPlC6AAAAdGpKVIQ8L1RXwz4y+LLZvAwDfYT4qqhoVjsFkJDXG7TbYZ40viorm1Nuw6TMEyFB07AEEb4oioSGa5xB8cEZScLUI6ylU3xg+gQAAIBOTaFRo7DyAs5YlhcEUe0sQEKBABQffPG8wLIwrBdfwSCLxTZMgiA2NnoUCAQy43L54U8tzurrYRouvvz+sMcTUDsLkFBDgxuTbZgIi0WvQCCQGYNBC71QOMvJMaidAkhIq9XA5BacWa0G2IYJAAAASEah3Seg6QBnfn8YOjlwBit44Swc5qBnAWdudwCLJdZEUYSSjDOGCcEiXjhzOBi1UwAJhUKc3w/bzOHL6WRStnsq00dIFhRYFAgEMmO1GjQa6CPEV3GxVe0UQEIGg1angz2Y8FVUZEm5AB70EQIAAOjUFJo+0dQE0yfw5XL5g0Ho5MAXTJ/AGUyfwFw60ycUmlAPf2dxxrI8z8OEenzBWAycwYR6zKUzoV6JplFJQhzHa7XQjI4pjhNIkoD1ErEVDnM6Ha12FiA+QRAlSYJedmylU3ygjxAAAECnpsw2TGJNjUOBQCAzNpuXYWD8N76OHbOpnQJIyOeDbZiwhs82TAAAAACmoGkUAABAp6bMqFHE84ICgUBmBEFM2XQAVMRxUHzwJYoS7GKGs3RqH2XmEQq1tU4FAoHM2O0+vz+sdhYgoaoqu9opgIR8vqDTCWvg4au62pHyi74SUxoIgjAYtAoEApnRajUaDfQW48tohOKDL5g4gTmDQQvbMAEAAADJKLQNk88Ho/PxFQyy0AuFM683qHYKICGW5UMhWPoHXz5fMOXjnkLbMDkcMM8GX15vMBTi1M4CJGSzedVOASQUDLLwRR9nzc2+lA2fCm3DlJNjVCAQyIzJpKNpWAAPX3l5UHzwpdPR0E2Is9xcI/QRAgAAAMlA0yiAplHcNTdD0yi+oGkUc3Z76qZRGCwDYLAM7jweGCyDLxgsgzmvN/VgGWW2YZLCYU6vh7lQmGJZnqJI2IYJW4EAC1MJscXzgihKsM0ctoJBVq9PMZUQ+ggBAAB0asossSY2NLgUCAQy43QygQAssYYv2MUMZwwTcrn8amcBEqqrc2LRRyhJUjjMKxAIZIbjBEGAhgF8QfHBmSCIsKkAzsJhHos+QoSQKEokmWoqB1CJfA8QKefaAJWIokiS0IOLKSg+mEun9oE+QgAAAJ2aEl8zeV6orGxWIBDITFOTB+a34OzIkSa1UwAJeTwBmOiJs4oKW8ptmJRpbyFoGpYgwhdFkdBwjTMoPjgjSZh6hLV0ig80jQIAAOjUFBo1Cisv4IxleUEQ1c4CJBQIQPHBF88LLAvDevEVDLJYbMMkCGJjo0eBQCAzLpcf/tTirL4epuHiy+8PezwBtbMACTU0uLHYhokgCJNJp0AgkBm9noZeKJyZzVB88EXTGpg7gTOzWQfbMAEAAADJKLT7BDQd4MzvD0MnB85gBS+chcMc9CzgzO0OYLHEmiiKUJJxxjAhWMQLZw4Ho3YKIKFQiPP7YRouvpxOJmW7pxJ9hCRJFhRYFAgEMmO1GjQa6CPEV3GxVe0UQEIGg1angz2Y8FVUZEnZiQt9hAAAADo1haZPwBJEOPN4AqEQp3YWIKHGRrfaKYCEAgHW6w2qnQVIyGbzYNFHKEmS3w/b3eErFOI4DvaRwRfDQPHBF8fx4TB8j8QXw4Sx2IZJkhDH8VotNKNjiuMEkiRgvURshcOcTkernQWITxBESZKglx1b6RQf6CMEAADQqSmzDZNYU+NQIBDIjM3mZRgY/42vY8dsaqcAEvL5gna7T+0sQEKVlc2YbMMkwZrOOJMkaBfAmiDAfw++RBHKD9ZS1oIImkYBAAB0csqMGkU8D4MS8SUIYjpfmoBaYEwvzkQRWrywlk7to8w8QqG21qlAIJAZu90H81twVlVlVzsFkJDPF3Q6YQ08fFVXO1J+0VdoGyaDQatAIJAZrVaj0cDcCXwZjVB88AUTJzBnMGhhGyYAAAAgGVhZBqBQiINOXJzB5BaccZwAK8vgzO9PvbIMrDUKkMcTCAahJOOrsdGjdgogoUAgDGuN4qypKfVaowptw5STY1QgEMiMyaSjaVgAD195eVB88KXT0dBNiLPcXCP0EQIAAADJtKJplOf5Z599dty4cVartV+/fk8//TTPp7WtuSiKDgcsQYQvrzcI2zDhDHoWcBYMsj4fdOLiy273ZXMbprvuuuuee+4pKSl5/vnn58+f/9hjjz311FPpvFEUJbhRcBYMsjBlG2ceD3RB4Ytl+VCIVTsLkJDXG8zaNkxOp7O0tPTiiy9+99135W3vV65cee2113o8HopK0T4uSVIgwJpMuvTSBkoLhTiNhoR+DmwxTMhs1qudBYiP4wRRFGGfLGz5/WGjUZe8mzDdJ8IDBw6wLDt37lzi9+tNmTLF7/fX19enfC9BEFAL4kyvh95+rEEtiDOapqAWxJnJlKIWROlXhEOHDt29e/eMGTMiRzZs2GAwGIqLi1O+VxDEhgZXmoGA8pxOJhCAiZ74gl3McMYwIZfLr3YWIKG6OmfKhk9qyZIl6VxLp9MVFxfT9PEvPlu3br3ssssWL148bdq06NMCgfCxY80cJ5jNeqeTqalxaDQUTVP19S6Xy2826zUa6ujRJqeTyc83syx/9GhTMMhZrQavN1hVZZckZDTqbDZPXZ1Lr9dqtZrqantTkyc310QQ6PDhRp8vlJtrCgbZY8ds0VEoitLr6fp6V0OD22TSazRURUWT3c4UFJg5Tjh6tCkQYHNyjD5fdBRvXZ1Tp6MjUXJyTCRJHDrU4PUG8/KOR2FZwWLRu1z+mhoHRZF6vbahITqKzW73FhRYeF44ciQSJVRV1SyKksmka2721tU5tVpap9PU1Diamjw5OUaSJA8fbvB4gnl5plCIq6iwsSxvsRjcbn91tYMkSYNB29DgbmhwGY06mqaOHbM1N5+I4veHc3KMDBOS99kymXR2u6+21qnVanQ6Wo5itRopijx8uNHjCUSihMNylEB1tV1e966x0V1f70KI0GrphgaXzebNzzeLonTkSKMcxe8PVVY2C4JoMunlKDSt0eno2lpnY6PbajVQFHnkSKPL5c/PN4fDJ6J4PLFRDAYdTVOVlc02mzcv73gUhgnn5hr9/nBlZTPPi2az3uE4EaWuztnY6LZYTooi3zahEGe1Ho+CEGE0apuaPPX1x2+bqqrjUSTpxG0j35xylMjNqdcfj2I2GzQaMsnNiVDszVlVZbfZYm/OQCD25pSjyDenXAQqKpocDiY/38xxchTWak12c3o8wcJCixwl+uaUo0TfnCcXgeM3Z8siEH1zylGib85IEQiF2IqKk4rA7zfniSgxN6ccJfrmbFkEfr85TyoCv9+cyYpAfr5FEMTIzSlHEYTYIlBb62hsPB7lyJFGt9ufl9eKmzNSBKJvzkRFwGIxsCzf0OD2eoORIhB9c8pR5JvTYNDStCZSBCRJOny4kWFCubmmk4sAU1t70s0pF4GjR5ucztgiEH1znlwEjt+cCMUWgZY35+9FoGP+fRZFZDbro6Kc+PscqblaPX3Cbrc/+uij//jHP6655ppXX31Vo0lr/pkoSiSZ6ukUqES+B4iUzQdAJaIokiQsBospKD6YS6f2ad006lWrVi1evLigoOCzzz6bPn16+m+EWhBnUIYxB7UgzqD4YC6d2qcVBexf//rXggULLr300l27drWqFuR5obKyOf3zgcKamjwwvwVnR440qZ0CSMjjCcBET5xVVNiytg2T2+2++eabb7311hdffLH1mRA0DYMS8UVRJDyy4wyKD85IkqQoeGTHVzrFJ90+wnfffXfRokXXXXdd9+7do4/fcssthYWFGSYIAAAAqC3dJ8LDhw8jhN58882Y45deemnKilCSpHCY0+thc1FMsSxPUfCtFl+BAAt782KL5wVRlLRaWLYeU8Egq9en2JtXiUW3eV6orXWWlxe1dyCQmaYmj9Gos1hg1jamjhxp6tu3i9pZgPg8ngDL8kVFVrUTAfFVVNjKy4uS9/4o8S0GVpbBnF5PQy8UzsxmKD74omkNDBzFmdmcemUZ2IYJAABAp6ZEt5AoSh5PQIFAIDN+f5hl09pRC6gCVvDCWTjMBQKw+wS+3O5ANrdhypgoilCSccYwoXAYKkJ8ORyM2imAhEIhzu+Habj4cjqZlO2eSvQRkiRZUGBRIBDIjNVqgN0ncFZcDAMx8GUwaHU6GDKKr6IiS8pOXOgjBAAA0Kkp0TQqCCIsQYQzjycQCnFqZwESamx0q50CSCgQYL3eoNpZgIRsNg8WfYSSJPn9sN0dvkIhjuMEtbMACTEMFB98cRwfDsP3SHwxTDhlu6cSTaOShDiOh5UXsMVxAkkSsLIMtsJhDvZAx5YgiJIkQS87ttIpPtBHCAAAoFNT4iGA58W6OqcCgUBm7HYftF3jTN6CHODJ5ws5nTC/BV81NY6U2zAp0xomQRcUzgRBTHmjABVB8cGZKIqCIKqdBUgoneIDTaMAAAA6NWVGjSKeh6+0+IInQszBEyHORFGCJ0KcpVP7KDOPUKithT5CfEEfIeagjxBnPl8Q+ghxVl2duo9QoW2YOtsSRCLPB+12PhBACCGC0OXmUjodbTSqnVd8NE1RFL77yLBer8CyrPf4mgxaq9VQUIA608Y3na34nFooioS5EzjT6TSwDVN7kiRPVZXr4EHHvn2OAwf8DQ3e6mp/fX3AbkfxPlWNwWAoLDQWF+f06mXu2jV/wICCQYMKhwwxFBQonzuGvFVVjv377Xv2eI4d81ZWemtqgnZ7yOEQ2DhL+5M0bSgstPboYe7a1dKjR8HAgfLnaSyC/Z8BAK2jzIR6KRBgO8bevALLNv78c82PP9Zt3Fi3cSPr87XxgqRGk9O7d/GIEd3PO6/HhAkFgwZlJc9WCYU4jUaFb7Uizzf+8kvN99/Xbtjg2LvXW13d9muaSku7jxvXfdy4svHjC4cM6RgPjgwTMpv1amcB4uM4QRRFWPEAW35/2GhMsTevEhUhzwu1tc7y8lP4q7qnsvLo6tVHP/+8buNGPtSOW66Yu3XrO2dO71mzyqdOJTUKNYg1NXmMRp3FotCfWtbnO/LJJxVfflnxxRdt/yaRhD4/v+ekSX1mz+41Y8Yp/dh95EhT375d1M4CxOfxBFiWLyqCHUIwVVFhKy8vIslkNaESFaG8MW9enqm9A2VdoKnpwMqVe995p2n7doVDGwoL+82bN+Tqq7uec057P9YwTIimNe3dESWEw8e++mrXG29Ur1vHBxVdpJigqF7Tpw+64oo+c+di21ObhMPhg43MsBUKcYIgdowWrw7J6WTy8kzJd2KCPsI4JFE8tmbNrjfeOLZmTdwOqpS0FotGr6ctFoSQJAis18syjMhlsjJvXr9+I266adj119NmcwZvx4G3unrnq6/uXr486HBk8HaNwaDR63V5efLLsMvFh0KZVaX6vLx+8+ePWLy4y+mnZ/B2AECHBE+EJxHC4X3vv7916VL30aPpnE8bjQWDBhUOHVo4eLC5e/fcPn1MJSWGwkKNPk4zY9DhCNhsweZmz7FjnspKx759zbt2uQ4floTU01y0FsvQ668/8447LGVlrf6tUmm/J8Km7dt/fuaZQx99lM7vqNHrCwYPLho2LK9fv7x+/cxduxqLi00lJXG/AXB+v7+xMWCzuQ4f9lVXN+/ebd+zx3XokMjz6STWbezY0Q8/XD5lyinRiQhPhDiDJ0LM4fJEeEr0EQrh8M7XXtv69NOBpqbkZ1rKynpOmlQyalTZ+PH5AwYQZJvmYnJ+f/3mzXUbNx77+uvGX35JXmFQWu2Im28++957jV2y2WPUHn2E9t27Nz3yyOGPP05+Gm00dj/vvPJp07qec06XM89sY7eowLJN27fXbdpU/9NP1evXh90ptvErHDLk3Mcf7zt3LubVIfQR4gz6CDGHSx8h5qNGJVHc9957mx5+OPmoxYKBAwdcemmf2bOLR45sp0zCbnfV2rWHPvro6Kefcn5/otNoo3HUvfeedffdGoMhK3GzO2qUqa/f+MADe999VxITLrdhKinpv3Bh34su6jp6dNyn57aTBKF6/fqjn3124D//Sf7lpvTss8975pmy8ePbI42sgFGjOINRo5jDZdQozuo2bVp7003Nu3YlOsFUUjLshhuGLFqU07u3YlnxweDhjz7a9cYbNT/+GHdKIkIop1eviS++2GfWLMWySknk+R0vv7zp4YcTjQWldLp+F1449Prre0yc2MYn6VZp2Lp191tv7X//fU5e4iCefhddNOHvf7f26KFYVgAATChREQqCaLN5Skvz2jtQq4Q9nu/vvHP3W28lqml6Tp484qab+syerdg0hpZchw5tW7Zs33vvJXpA7Ddv3uSXXzaVlrYlitPJ6PW00dimR/am7du/vv56286dcX9qKikZecstw2+80VBY2JYobcH6fAdXrtz2/POOffvinqAxGMY++uiZf/kLQeG1UEhNjaOs7BSe/tGxMUyI44RTYgxE51RX5+zaNQ/6COOo+PLLb264gamra/kjgiT7XXTRqHvvLTnrLOUTiyvQ3Lztued++8c/wh5Py58ai4snvfxy/4ULM75+G/sIRZ7funTpliefFMJxFizN6dXrjDvuGH7DDZQOi7ZxSRSPfvrp1qefbti6Ne4JpaNGTX/7bVVWNkgE+ghxBn2EmMOnjxAJgoDJcnxcILDuttt2v/lm3J/2nTt33NKlBQMHKpxVOkJO5+Ynntjx8stxp2EMbz7ifAAAIABJREFUvfbaSS+/nFmvoSCIBEEkv1ES8dXWfn7ZZXUbN7b8kT4/f+yjjw674QZKq83gyu2t6ttvf7jnnriPsJRON+6pp878y1+UzyoujhNoGoviA1oSRUmSJIpSrqkftArPp659OlcfofPAgU8XLLDv3dvyRyVnnTXx73/vOmaM8lm1ivPgwXV//nPl11+3/FHhkCFzP/oor18/xZKp/OabLy6/vOXsQIIkRyxePPbxx/V5eLWHx5AE4eDKlT/cc4+vtrblT/vOnXvBv/6ly81VPjEAgJI6UdPokdWr1yxa1LJ1UZebO/6ZZ4Zef72Swzfa6NCqVWsXLw40N8cc1+flzV65sufkya26WmZNo9uef/6He+5pOd+jcOjQGe+8035ja7OO8/t/WrJk27JlLX+X/P7956xaVTh4sCqJRUDTKM6gaRRz6TSNKvOnn1C5YUeStjz55Op581rWgr1nzrx2375hN9xwCtWCCKHT5s+/Zt++fvPmxRwPuVyrLrjgt3/+s1VXoyiyVe2iIs9/c8MN3995Z0zNQVDUOQ8+eNW2badQLYgQok2m8c8+e+XPP7dsEncePPjB6NFHP/9clcQioF0UZyRJQrsoztIpPh2/aVTk+bU33bTrjTdijtNG48SXXhp67bWqZJUtu5cvX3f77S3HlI555JExS5a0R0Q+FPp0wYKKL76IOW4pK5u5YkX3cePaI6gyBJb98b77tv/97zEDiUmNZvIrrwy74Qa1EgMAtCuFBstwHK/VqjAJQQiHP7vkkiOrV8cczx8wYM7//qd6k1dWNP/22+oFC9xHjsQcP/3WWye+8EI6a6ZwnECSRDrfalmv9+M5c2p++CHmeM8pU2auWNEx9gI8snr1mquvbrkqzbmPP37Ogw+qklI4zMF8bWwJgihJEiaDAUFL6RQfJZ7oBUGor3cpECgGHwx+ctFFLWvBfvPmXfnzzx2jFkQIFQ0ffuXWreVTp8Yc//Wll9befHM6V3A6mUAg9drirNe7asaMlrXgmXfeuWDNmo5RCyKE+s6de9UvvxQOHRpzfONDD2186CFVUqqpcaoSF6SDYUIuV8J1oIDq6upcopjieY9a0j4NaNEkCSm/KK3AsqvnzTu2Zk3M8bPvv3/Ka6+107JeatEYDAMuvZRpaLD9+mv08cZt21ifr3zatORvFwRRq9Uk/0rLBQIfz55du2FD9EGCoqa8+uo5999/avWwpqTPzx90xRXNu3e7Dh+OPl77448IobLzz1c4H5blYYk1bImiRJIEPLJji+N4k0mXfEK9EhUhSRIK14KSIHxxxRUxz4IERU166aWz77sv+SdyiiIoqu/s2XwoVLdpU/Tx+s2bSZruft55Sd6r19PJa0GR5z9buLDym2+iD2r0+pkrVgxetKgtaWOL0un6L1zoq6mJmWhY88MPupycrqNHK5kM1II4o2kKakGcmUz6lH/zlagIRVHyeoN6vXL3yoa//jVmdAxBUTPfe+9UHxqTAkH0nDyZ1Giq16+PPly9fn1Or17Fw4cnep/fH0YIJekj/Hbx4gP//nf0EY1eP/fjj/vOndvmpPFFUFTfuXNDbnfMGjRV335bPGJE/oABimXicvkNBhwXJQAIoXCYY1lY8QBfbndAp9MkrwuVaNESRVHJNvTdy5f//H//F32EoKiZ778/4LLLFMtBRec8+GDsmA5J+vr66+VmvbgYJhQOJ9zG75dnn931+uvRRyidbvbKlb2mT29zstgjiInLlp3+5z9HH5NE8Ysrrmjctk2xLBwORrFYoLVCIc7vD6mdBUjI6WRSDglV4okQIYIkCWWeCOt/+umzSy45aX4bQUx/881BV16pQHRM9Jg4kWWY+s2bI0ckUaz48sv+F18cd50UgiC0Wk3cJ8JjX3311XXXRU8nIChq5ooV/S66qD0yxxFB9Jo2jamvb4rqfxU5rvKbbwZefjltUmKpZYIg4IkQWwSBNBoNPBFiiyAIvZ5Wf9FtxQTt9ndHjoxZLuvcJ5885/771UpJNZL0+RVXxLRnlp599qU//JBk8WvnwYM169e7Dh9mfT6txWIsLt76zDNh10kjfie99NLIW25pr7RxJQnCJxdeGDOzvueUKQu++qqDDRQCoBNSaBsmp5NRYAmij+fMOfrZZ9FHhl577bTlyzHff7ydCOHwysmTY5bDPuP22ycsWxZzpscTqPvmqx1/e6bh558RQpRWS+n1kihyTGyLXNy3dxKc3//vceNsO3ZEHzzv6adH3Xtve4dubHSXlMCSp5gKBFieF6zW7OySDbLOZvMUFVnV7yOUJEkejtGudr/1Vkwt2G3s2EmvvNI5a0GEEKXTzf3f/yxlZdEHt7/wQszgT4Fl1153zZcXzw86HBNfeOGavXtvDwZv83jOuvPOmAuWTZhw/t/+1u5544o2mS785BNjcXH0wU2PPGLfs6e9QzNMuxcfkDGO48PhOBvCAEwwTDjl414HWVmGqat7e/Dg6KVE9fn5i377zdK9e/sFPSU0/Pzzh+edF71ToKV796t375Y7CyVR/HjOnGNr1pzz0MNjHn4o0srXuG3bB6NHi3zUCBqCyO3de/6XX+addpqyvwFeKr/+etWMGZIoRo6UnHnmFVu2tOtevrCyDM5gZRnM4bKyDEGg9l5f7bvbbjtpQW2CuODtt6EWRAiVjhp13tKl0Ud8tbXf3323/O+fn3mm4osvpr/99tglj0RqQZHjvr7++uhakKCoOR9+KAnCysmT/Y2NiiWPofJp0866667oI43btu14+eV2DQq1IM4oioRaEGfpFB8lKkKeF+vq2nGNqOrvvjv80UfRR4YsWtRnzpz2i3hqOeP222MWYNvz1lt1GzcGbLbNjz8+/E9/6jLjoui261+ee675t9+izz/n/vtPu/jii9et4wOBNVdfrUza2Br72GOFQ4ZEH9n0yCOBpqb2i1hVZW+/i4M28vlCTifMb8FXTY0j5RJrygx4kzgudqe3rF1aFNfdcUf0EVNJSacd0BEfQUxbvlxrPTFYSRLFtTffLD/HjH3sMUEQIzeKr7Z2yxNPRL+7eMSI0Q8/jBDK6dVrwrJllV9/XfHllwpmjx1Kp5u2fHn0YNGwx7PpkUfaL2L7FR/QdqIoCoKY+jygknSKzyk/fWL/ihVfnDxHcNYHH3SSufMxRJ4/+tlnR1avbvz556DdrjEY8k47rXzatMF/+IOxuHjnq6/GrMFtKinpM3v21JMny39x5ZX7V6yIvCQo6qpt24pHjDj+WpLe6Ns3r2/fBV9/3f6/ENbW3nzzzldfjbwkafraffty+/ZVMSUAQGaUGTWKeL5dvtJKgrD58cejj5Sec86ASy9tj1iYq/jyy7cGDlw9b96xr74qGDx40FVX9Zs3T2MwbHniiTd69dpw//1Drrmm5Kyzot/ib2zsOXEiQijyRGjbsWP/Bx9EnzPy5ptP1IIIIYIYsmhR1dq1IZcK24lgZexjj+lyciIvRY7b8uST7RQLnghxJooSPBHiLJ3aR6FtmGpr26WP8NBHHzkPHow+cv6zz3bC+RIbHnjgo5kzaZPpos8+W1xfP+e//z3/uecmLFt20aef3tTUNPGll/a+++57Z5wx6u67Yz4cx6FDCCG73Sf3EW544IHoRWSMxcVjH300JlbvmTMlUaxet679fy2sGQoKRt13X/SRfStWeCor2yMW9BHizOcLQh8hzqqr8egjJAhCp2uXUaPbnn8++mX5tGndzj23PQLhbOODD2596qkz//KXP2zf3mfWrJiFTiidbui11167b1/xyJHf/OlPMaNmdrz0EscwNE1RFNG4bduxr76K/umYJUtaLslWPGIEbTY3/vxzO/06p5DTb701elqhyHE7XnqpPQK1U/EBWQGjRjGn02lSPhwpURFSFFlampf1yzZu29awZUv0kU64lNqxr77a8tRTZ9111/nPPZdkKpvWap25YsXpt95at2kTSZ8YTBy023e98UZ+vtlo1G1dujT6cTCnvHzodde1vBRBUcXDhzsPHcruL3Iqok2m02+7LfrInrff5gKBrAcqKyvI+jVBtpjN+rw8JZacBZnp1i0/5TZMp/DKMrvffDP6ZZczzki+617HwweD3/7pT6WjRp339NPpnD9myZIz/vxn8uT6cvsLLwT9Iefhw0c++ST6+OiHH6a08Rd6NhQWBmy2jNPuSEbcdBNtNEZehlyuIx9/nPUoDAObG+CL4wRYWQZnfn/qlWWU6SMUm5u9Wb5mOHzgww+jj4y46abshsDfrtdf91ZVJX8WjDH2sceKR4yI7in0VlXt/e9H2156JXq1FEtZWZL9OnS5uZxfuX21cKbPy4sZnLXnnXeyHqWx0ZP6JKCSQCDs9QbVzgIk1NTkSTk5QomKkCQJiyXLW2xXfvtt2O2OvNRaLJ1wsOiOV1/tcsYZ3caOTf8tBEnOWbWKok9aauHQW68f+mBF9JHTb7uNpBMux8D5/Ro97Jl+3NDrr49+WbN+fdCe5bEtOTmwoDO+tFqNXg+bZOHLajVg0UdIkmRBgSW714xpx+t74YXRLVSdgevQIdehQwMuuaS1bzR37Xr2ycMd6zf8EHKc+NutMRji9g5GBO32uPsadk5dzzknp3fvyEuR52N2a2o7BXZuARkzGLRZ/6IPsqiw0IJFH6EoSlneoV6Sjq1ZE32g/4IF2bz+qaBpxw6EUI+JEzN475glS2izOdFP+y9cqM9LNrjJW1WV26dPBnE7JoI4bf786APHsr3yjsPhy+4FQRaFQpwCu+uAjDmdDBZNo6IoejzZHErn2L+fqa+PvNTo9T0mT87i9U8J/oYGhJC1vDyTNxPEyMWLE/1w8KJFSd4adDg8x44VDBqUSdwOqs/s2dEvq9etQ1ldsMnlyv5IVJAt4TAXCEBFiC+3O4DFYBmKIrPbtlO7YUP0y65jx+LZLuqrrW2/i8sP+xlvjz7k2mvjHjd26VI2fnySNzZt24YQ6t755msm0fWcc7SWE43/QYfDvndvFq9fUpKT+iSgEqNRB7vy4qxLlxwsmkYJgjCZdFm8YMxs7u7jxmXx4m3nPHBgy5NPvnv66f8sK/NWVbVTFHP37gih6CfjVskfMCCvX7+Wx/vMmpV8DOrB//7XUFhYNGxYZnE7JJKmS885J/pI4y+/ZPH6ZjN0QeGLpinYJwtnJpMOi8EygiA2NWVz/Ldt587ol6Vnn53Fi7fR6vnz3xo4cOODD9p27EAIxewPlUVdTj8dIVS/aVPGV4hp0JP1njkzyVs4hjnwn//0mzevE65jl1zpqFHRL+X//Wypr+/sK7vizO8PZ7frB2RXQ4Mbiz5CSZKCQTZrVxNFx/790UdOWhVabTE71R383//aKVBOr14FAwceWLky4yv0mDQp5ghBkj0mTEjylgMffsgxzMDLL884aEdVPHJk9Ev7vn1ZvHggkLXiA7KO5wWW5VOfB1QSDLKY9BFS3bvnZ+tqvtpaPnhi+qouN9dUUpKti7ddzADC+p9+yrj1MqXhN95YvW6d+8iRzN7ebcyYmAe7goEDk8+L2LV8ecGgQck7ETunmNFD7sOHs3jxnj0L/7+98w5o4nwf+N1lEzaEDQLiVpyIe4N7INY9WkdbV9uf3a3t11bt3tpltdZdBw4UtW7cSl1oBRHZEEggIWSPu/v9EY2XyyRkHPB+/uJe3rvnTfK+efI+7zOc+DSAc/Hx4QQGWvTBBnicmJggBKHEGSHkxKS00vJy4iXV/Ph53bqRitI9dkHOLT1dXnyR4eV1Zc0ax25n+fv7GTudkrY1JGofPODfuNH79dcdE9ey8YuLI/6qkFZWYjqn7RIYDJDTmbogCEyjuafCOcAR7NE+7vj8dDq0pETorKeRNlg+UVHOerJzgGFSUOPjjAwXiWL5+fX/6KO83bvLL1xw7AmBHTpYuSSRu3kz08en05w5jslq2dDZbK/g5/s2HEWVQqfN+cLCGmc9CuB0JBKF01NIApxIUZGAEmWYIMiZv5hUIqPShhwez1lPdhbtjK2j5dnZCud9J5Lo8+abwV27nnzpJWVdnQO38xITo4cOTZg1t8f/vdnr9detZC1H1eq8nTs7zprF4IJE++bhBBsZMB37RMxCowHXJOqCILBN73yAB7FpF4UgyB11zuh0xIl1ZDRSoywbxCrhFCGsd2/fNm0MgRM4hj05coSUkdJZIHT6+J07dw8ceGTq1BdOnaKxGhemMuTLL+3s+fjgQWVdXaJrXkXLgGk8FbUypxVrjYsLsd0J4CF8fDg+Ts4gCXAmsbG2N0vu8RqFnOhVhaqNkjhQMfszDLebOpXY4DrfUQiCeImJE/furbxy5XBamk7lSL0erRZFUcx6n9zNm3mJiWFJSQ6NsVVAN/4V4thnYRZQ5YfKoCim06GeHgXAIvYsH/fEEaLODIQiecJS0ihB8h0tO3tWJXZhKFj8uHFjtmwpPX36QGqqA2ZYkUhm3UFfUlRUdv68iza1LQZSlh+boUv2U14ust0J4CFkMpWTcykDnEplpZgSZ4TOzSwD043MuZiWij+WI/r354aHGy4xne7J0aMuldhlwYK0zMyaO3d2JiVVXbvWqHvZbIZ1v8TcLVvoLJaVCoUACIJQ46mI0J127uDt7czETADnwmDQQWYZKuPtTY3MMs7NNUpKK+rEkxgnAiNIe2PraIHLfEcNxI0dO+vSJaaPz57Bg698/DHJhmwFPz8vNtviSsZR9L+//mo3dar1khQA0um1E72KwsJA0Svq4uXFBLlGqUxICDVyjWIYLpU67byEFPHtUpNjUyD5jpb88w/pi9IVhPToMe/Wrf6rV9/88sutXbuWnDplz11KpUartXjIUXT8uKyqCthFbaI2nops55VsBAXQqYxGo1OpQOof6iKVKimRWQbDMCcWVOOGhhIv9dWIKEjU4MFEf3pUrS5ydpk6s9CYzAFr1sy7fZsTFHRg9Ojj8+fb9ONvaFCqVBYtzLmbN/snJMQMG+bkgbYwcFxeYxTt58TAHoEAhKlRF6VS48Qf+gCnIxRKKZFrFEGQgACnmYm8IyOJlxKXlXdoIgidnjBlCrGlwJW+oySCu3SZffXqsG+/fZyRsbVTp/w9e6x09vZms1jmD7TkfH5RVlbi4sXUdEqiDjI+n2iLZvn5MZ3nUx8UBDJ4URc2m8HlUs93HfCMwEBvSpwRIgjs5+e0eoF+sbFGuazKyuw/DHMzpoXLtQr3ZamHEaTPqlUv3r8fnJh4bPbsg+PHk7LTGeByWUymeUX4YOtWGIa7vviiCwfaIhAbJxf1i4934sOd+DsS4HRYLIaXF9PTowBYxN/fy+YZoTsC6lEUE4lkzvKXYXh7+0RFGb7TMZ1O9OgRNcvjxYwYwfLzU0uelqDSKhQl//zTLi3NDaL5BYVFN24JC4vkonqkW98If17ZyaNbOnUa+sUXPZYtIzn6SyQKFothxl8Gx+/+/rt/j15nNu2QCmthGPILCw1p17b94P5+oZRL6ONZ6owr8VpPVtdYqqvrgb8MZVEoNDodCvxlKItAIOHxfK3rQjeVYZLLnblpC+7ShXhZc+uWEx/uRGhMZsLkycQWN/iOlt7J3bny3dNfb4CKKzqHhI3q23dEz969h6a0X7gc9w8+u3Lljr5964yLBKlUWlNnmfL7D7e+MFdaVsbr2K0rL3RUUtLwXr3jON6ye3l73/ro8JovRBWuqqrRHCFNQtIUbSIyGUVtHgAIgrRaHch4QGVkMrVNZxnYiWG/lsBxXK3WstlOsx5c+vDDG599ZrhMXLIkddMmZz3cuTzJzDxE0IVMX9/lAkFjE6HZiValPvXjb8KCJ8OSk2Ojo0076FDdqT07Hx78G9Fp+61enfz++zQmE4IgjUZHoyGGfLAYip7f9FfR9X+9H96RlpYs+etvGDb6wYRh2P28vOt37/aYOCZ5+hRwfAhB0NbOnYllMtOPH48bO9ZZD1coNMD4Rll0OhTDcEuHCwCPo1Rq2Gym9W8pNwXUO1ELQhAU0a8f8bLi4kUnPty5tElNZXg/93TQNDSUnj3rCkEKScPfb33EqJfOS0szqwUhCKLT6OPmvjjrh02MNm2vrlmzvWdPfeg9k0k3aEFUqz285gtJfuH0Uak1uXe6jR5P0oIQBCEI0r1Ll7lpaUXZV45//ROGtvb8UgqBoC4///k1DIcZF6xvIkALUhk6nQa0IJXhcGxoQchdZZiwykpn5oiKHDiQeMolevSooazMic93InQ2u+348cQWV/iOahTKgx9/1j4iMnXIEBrNRvGtyJiYxV//5D9mslxYu2fQoHOvvVZdWv3Udo3jWV/+yFJp00aPeXLlAqrTdU0dZ+k5XC+v6ePHa6uFp374jZz3rpVRdvYs8R0I7tKFE+S0LPMQBJWW1jrxaQDnIpWqRCIqpvUA6Ckvr6NEijUIwq3EazsAOzCQVEK22C0heo5BiqwvPHLE6WnhTv34W5i3b7LVsrpEOGz2jIVL6MPHtZs1587PPx8amFRy8gQEQbcyj8sq+GOGDYVhOPefY/F9+vkEW3OKoSG08cOHix4/uXU4ywkvo9lCihCNGTnSuc937vIBOBcMw2zmrAd4EHuWjzsUIZ1Os6cQRqOIJ22zXO+E4jDxY8cSS2SoRKLy7GwnPr/wek7dk+Jh/fo36i4fb5+UYcPruIEzzp9n+/qcmJZ2aOrUG9v3TBgxkobQ+I8e1pYUJY6baPM5dDpj3LARN/cfEVdVO/oKmjeoRkNKJBs/zuI22jESEkJtdwJ4CD8/LyemkAQ4nfj4EJslCd2zI4Rs7kwbC8kbs/zCBXk1Rb+IGd7eJL8JJ6ptHMMu/bkzdeBgOt2GRdSUtrGxgVyf6lrJvNu3+3344ZPMTO3JwxU5VyEIyj2Z5cMLie/Tz+ZDIAjy9/NNSky8tnNfo0ffIig+ftwQIQNBENPXN3roUOeKwDCw4aAuOI67weUQ4DD2aB/3nBGiZWVOPuQI7dXLv21bwyWm0+Xt3u1cEU6EFFn/+NAh3EkOJgVXbviwvcLDHNwxDOzd+9ahLEGtLGrWAu7oKQERkce/WX9g9VuPLp5LHD2BFG5ohe6du5Tn/iepaXQFqBbAw507iZcJkyc73Su4qKg1vrHNhYYGZW2ty9MIAxympERIiTNCGIYtZfBqCh1nzSJe3t+82ekinEX8hAkI43m4uqKmpvLqVac8+cE/ZxPbOx67HRwYGBwUWHnvXv6Z8z0HDJr3w+9DFr5a8SBXp1F3Gz3e9v3PYDDoHeLj8s5fcngkzRR5dXVhZiaxpZPxtHQKrlg+AGdBoyEO2GMAboPFolPCa5RGQ8LDnV/Bp+uCBcQItrq8vLJz55wuxSmw/PxiU1KILU7xHVXJ5PyCwrgY88ESdtK1bUL5tevFN3O6tG8PI0jfabNe/GXrkIWvegcF276ZQNs2sY8vX2/KSJojuZs2EV2fvCMjY1NTnS4lOtqZPqgA5+LtzQY58KhMZGQgJcowOT2zjB7/hISYESOILbd++MHpUpwFyXf08cGDeJMPfmoKi0JCQxmMJhUFjYuJKfsvz8fb2+dZvKN/RGSftOmNfU5kWJi4ukarakU5UHQq1d3ffiO2JC5eDNsKX3EAmQwUN6AuWi0KMstQGbncdmYZdyhCFMWEQpfUkem5fDnx8smxY7XGKR+pQ8LkycSvSGlFRXVOThOfWVtWzmtysVwmkxkYHBzBC2nicxAECQwKqiuvaOJzmhEPd+wgVgFDGIzEJUtcIai6WmK7E8BDKBRqUDCSytTUSChShgn28XFJmZKESZOILjMQjl/79FNXCGo6nKCgmOHDiS1N9x2V1Yp8OE4o6xEWFMQLDGz6c3y8ubI6itZJdjqYVkvM8wdBUMcZM0g1wpyFnx9I6ExdmEy6czNnAZyLry+HEmeECIIEBTmtNhsRmEbr8+abxJaCAwcEd+64QlbTIfmOFmRkNDEhC6rS0BlOcKNIHTq0W6dOTX8OnU7XaVpLqe7cP/6QlJQ8v4bhpLffdpEsEKZGZTgcpot+6AOcQnCwDyXOCDEMF4vlLnp4t4ULvSMiDJc4hl364AMXyWoiCVOM8lNLiooE9+415YEwDcadHaDZFHAcR+yOuGjWaGWya+vWEVsSJk1yXS2wujrgnU9dVCqtK3wgAM5CJJJRwjSKYZhE4qqCtDQWq9/q1cSW4pMni0+ccJG4psANC4saNIjY0kTfUW5QoFxJocMJuULBDWwVZfOuf/458XQQRpCBn3ziOnFisfvqOQMai1qtVSiAIqQu9fUKJzvLXLlyZeDAgX5+fgMGDLh8+bKdd9FoiEttO4mLF5MKgp9ftQqlpI3OjHW0CfiGBNfLKLRXkNRLfHmNC7pojkiKi2999x2xpcP06bzu3V0nMSzMz3UPBzQRLy8WqMpLZUJD/ZxpGs3LyxsxYgSPx1u7dm1wcPDIkSPziaVnLAPDMJfrkgp8ehAGY8jnnxNbRPn5OV9/7TqJDtNu6lTipSg/n1Qjt1FEdGxfUcW33c8t1Dc0wDTEpxUowjPLl+tUz+MZaCzW4PXrXSrR2xscQVEXBoPGYjUphAngUrhcljOdZTZs2JCamnro0KHXXnvt8OHDo0aN2rhxoz03oihWU+Na/+8O06eTfDKvr1snLihwqVAH8ImODk9OJrY0ZVPoG8JD6HRRPSUcNcurKiM6OZ7jprmQt3s3yfDe9513SAYJp1NVRYmPGGAWuVztuqMfQNPh8+udeUaYkZGxZMkS/R4TQZAlS5YcsO+IC8dxpdLlhsoRP/1ETGOmU6lOvPRS04PWnY5zraMdhw18+LiwaSNyDg+fFHUcPtjTo3Atipqac6+9RmzxjYnp+957LperoKKdH6BHp0M1Gp2nRwGwiFKpcdoZoUajEQgEPQkV73r27CkQCHQ62zOARqNFRTkhTM06wV279n7jDWJL1dWrN774wtVyGwupgS+ZAAAgAElEQVRJEQrv3asvdFyTdRw6MO9JocerE4glEpFYFNvLVW6TlADHTy5apKyrI7aN+OknhpcTQjmt06ZNyzc4N198fDiBgd6eHgXAIjExQU4rwyQQCCAICiLU3ebxeDiOC4VGefExDNdodDodCkEQimIajQ5FMb19VqPR6fenGo1O/wMKx3GNRqevmqi/UV/fUqfDNBqdPl+4VotqNDq9PtdodFqtzpIUCIL6rv7IjxhfD0HXPvmEn5PTWCnE4ZlK0f8ANHktEEmKTmdeim9cfEiPHsRB5u3b77CUwJiYwJjoB48e2fk5uogbd+/2nDgWodOtvGPP3gSd4eez2XdMf6NetT/7XMxMG70UDLMkBbUsBSVJsfBWEycnptHobv/8S1GWUf3hdunTYsaOt3Ny2iHF4uQ01PkxSHHR5HTPEnCFlGcfKFGKxWljc3LakmI0OREE1rc3Voo9k9PKayFOTjuWgKsmp/3fz86S0thpQ6fTLH2gBuxVhPrnEn1vnkkyMtpoNDo+X1xfr4AgSCZT8flihUKj06FPntTw+WL9OGpqJNXV9fqXyueLRSIZBEFKpZrPF0ulSgiCGhoUfL5Yn76vtraBzxdjGIbjOJ8vFggaLEhRQxAkVeE9P/+eWDwI1WiOzZpd/rhMH4mlVGr4fLE+H5JeikqlgSCotlaqlwJBEJ8v1ieE00vRR0DK5Wo+X6yPFhKL5Xy+WP9hCAQNfL5Y/0nw+WKiFOJr0Uupq5Py+WIUxUibwrx9+61LEQqfSsEwjM8X62u+qFT616JInpF2895dHeox44xIXP+kpKTHhNFaLWr4QBUKDZ8v1ifJrK9XkN4xHMcxDDe81Wq1ls8X6w9apNKn0waCIJFIxueL9VO2urpef9Ks05GlSKUqCIIkkufTRv+OYZiRFI3muRTD5DRIsTI5FQpN/vmr2W+9RXzVXiEh3T5ez+eLcdyuySkSyU2lmE4b48n5dAkUFFRjGIbjkEGKWv1cin7a6KXop41eikAg4fP1UlCbk5O0BIivpVFLgDQ5IQiSSpV8vlh/OPJsCaAQBPH59QKBBIIgjQY1SFEonkvRTxu1+vkSwHHSEtAapDQ0mEoxmjbPJudzKVYmJ47rpZhOTqXp5JRIFKWlQmMplpaAfnJKTSenrSVgbXJaXwL6ySkUSi1MTruWgFO+n0lL4NnktL4EnPD9XFQk0H8upkvAAGxnSUmVSsXhcMrLy6OiovQtZWVlbdq0UalULFvV1/RvqNsy6Ge//XbON98QW9qnp09yRrUHZ1GXl7e1c2diy8ulpb4xMQ4/8PhXP/mpdAOT+jR5aI0Hx/dmHeswblSP8aM9IN0taBoadvTpI378mNg45dChhClT3DOA4mJBXFxTk8ECXIRUqlSrdcHBLkmeBWg6JSXCmJhg69ZRe3eEbDabx+Pl5uYaWh48eBASEmJTC0IQRKcj7qwjM/izz8KSkogtBRkZ/xoHfnmWoE6dggiKkBsW1pRjQgiChiyed78gv04kavLQGs3Dx491NFr3sSm2uzZTcPzESy+RtGCPZcvcpgUhCAJakMr4+HCAFqQysbE8p50RQhA0derU7du363eQOI5v37493djEZwm9fdZ+QU0EYTAm7N7N9DUK4c9+553SM2fcNgabtE9P942J6f3GG7MuXXq1spJUT6qxeAcGjHhlYeaZ0xqtW8vBCOvqsm/eGPfeG/bXsm92XF+//vHBg8SW4G7dhn37rTvHAKr8UBkUxfSmSwA1sWf52GsahSDo/v37/fr1mzt37qhRo06dOrVnz57r16937drV5o06HVpRIYqN5dkpyCk8PnToSHo6Mas1OzBwzvXrAe3auXMYltCpVHQWC7IZ59kYjn+1gSauHz1kqBOfaQWdTrsn82hi2vju41rsdrDw8OEj6enEIByWn9+8f//1T0hw6zAKaxISQt0pEWA/EolCo9GBxOiUpahIYHNT2Igf8t26dTtx4sTDhw8XL1786NGjkydP2qMFIQiCYZjDcXeZknZpaX1WrSK2qESijHHjSO7vnoLOZjtXC0IQlPrGK3UqxY07d537WLPgOH707Lnw7p1bsBaszsnJmjPHKBQVhsds3epmLQhBkJcXqPJDXeh0GpPphCIwABfB4TBtftc2YkfY7MBR9MDYsaWnTxMbIwYMeOH0aTfEfnkESY3w77c+GjVgQNvYWJcKupxzs6JBMu2zj+nMlplcSlJUtHvgQHl1NbGx/0cfDaRqwUsAAOAwbirDpPfudTMwjTZp376A9u2JjVVXrx6bNQuzIw9Ac8QvlJe+7sPTVy6XVVS6Tsqt3NxioWDqpx+0VC2oEAgOjBlD0oIJU6YMWLPGI+MBBdCpjEaj03v5A6iJVKp0cvUJx8AwzFMF1Vj+/lOPHmUHBBAbn2Rmnnr55SYWxaUswW2ix7654kT2BUFtrSue//Bxwe38vMkfvcP0apkZ9zUNDRnjxpHcREN69Bi/Y4enfIL04VkAaqJUajzyQx9gJ0Kh1Kbhk7bGHT9yYQSB2WzP7B44QUHhycn5e/bg6HPPLsHdu2qJJG7MGI8MydX4h4cGREZk7dobExHBdaoR+OHjgsu3br2w/iP/8Jbpu6FTKg9OmFB17Rqx0Scqasb585wg94UAkfDIKTvATmAYotPpDAbN0wMBmAeGYTabYb0SkzsUoX4crpZiBb/Y2MCOHR9nZBB3gfzr13EMI9WsaDEERkX4hvCO79kXHRnh7cV1yjMfFjy69O+taetWB0ZHOuWBVANVq4+kpZWePUtsZAcGzjh3zt/F9SWsA7QglaHTaUALUhmbWhByjyLEMEwkknl5ubAkoU2Cu3RhBwaSCuhUXLyIMBhRQ4Z4alQuJahNlF9Y2PHd+6LCw725TdWFDx7lX7l9Z9pnHwXFRDlleFQD02ozX3iBlE2UweWmZ2WF9u7tqVHpEQobXFrRE9AUlEqNSqVlsYDjKEWprZVyOEzP7whRFKutlfr7O2df4jDhyck4jldkZxMby86do7HZUYMGeWpULiUoJtI/MuL4nr1RYU3ShQ8e5V+9c3faZx8FtdC9IKbVHp0xo/DIEWIjwmCkHTlCBZsBn18P6htQFoVCrVZrwS8VylJdLfH353peEcIwzOEw6HTPWw9ihg/XKZWVV64QG8vOntUplW1SWmY8XGBURBN14VMtuH51YFSE04dHBbQKxaGJE4uOHyc2IgzGxL//bjthgqdGRYTNZgLjG2Wh0xEWi0GjtdjkSs0dNpvBYNCtG0fdpAipoAX1tElJUYnF/Bs3iI2VV66oJZK40aOdHuROBZqiCx88enT1bovWgjLZwQkTys6dIzbCCDJ+164OL7zgqVGRAFqQyiAIArQglWEwaJQIqNfpsJqa+shIl9fmtRccP71s2b3ffiM1d33xxdQ//kDoLdPWX3j939Mbfp82dhzPbu/HhwUFl2/feuGzjwMiw106tkbRUFpanp1dnZMjr65WicWcoCDfmJi4sWOjBg9GGI3zyVIIBIcmTuTfvElshGm0MVu2dFmwwKmjbhKlpbWgNi9lkUpVWq0O2K4pS3l5XWRkoPUUa+750sf1NaioAgyn/PILnc2+9cMPxOYHf/2lEosn7t1Ls6OkRrMjoV8fHMMO/bpl2tjxgQH+NvsXFhdfvnUrff3qJmpBHMP4N24UZGREDxnSdtIkh5+jlkge7tx57/ffa+/fN/1vzjff+MXGDv/+e/uLQkjLy/enpory84mNCJ0+bseOjjNnOjxOV0Ct5QMwBsMwfe1DADWxZ/m4KcUahuE2C2G4n8sffXR93TpSY8zIkVMOHiQVr2gxPDx/6epfe2ZOnGjdRlpRVXXs/Pn0tR/w4to4LEuUn3/n558fHzwoq6qCIChh8uQphw878BxMp7v766+XV6/WNNiOK0/+4IPB69bZNHHX/vffoQkTJCUlxEYaizVx796EyZMdGKRLwTAMabn1PZo7pkXLAZTCHu3jnoB6CMepOFFiRoygsVhlxnFjkuLiJ8eOJUye3CJ1IS+uDYqhl06e7pSQQKOZP3mqE4kOnfpnwntvhHdoUqUOYW7u2RUrNNKnSYUaSkt7v/EGjdm4kDhZVdX+UaPub9mCqtX29K+8dInGZEYNHmytz+XLB1JTSRnU6BxO2pEj8ePHN2p47gHHcQouHwAR8AFRFnu0jzt+Zup0aFmZS9J9NZ3k999P3bQJNlYJtQ8e7ExOFty546lRuZSk9EnhiV2yLpw3awxQKpWHTp0asnBedLfOpv9tFFFDhhCzsehUKpJnpk1E+fm7kpOr//23UXdd+d//BHctluDI37Nnf0qKSiwmNuqj5mNTUxslyG0UFQk9PQSARRoalLW1nkkhCbCHkhIhhtkwfLpDEcIwTOVo08QlS8bv3Elns4mNssrKv4cNI1WuaDGMXL4I9WJfvXWL1I7jeNaF851GDuky0glJBhA6nXRiV5CRYf/tmoaGw1OmSCsqTP8V3KVLl/nzh3377YA1azrNnk0608V0uovvvWf2mTnffHNszhydyigzpHdk5Mzs7PB+/ewfm5uh8vIB0GgIdbziAaawWDZiJ6CWXYapUZSdP394yhTSKRRMo436+efur7ziqVG5DqWkYedr76YOGtwm6nmmmGu3blUqZenrVjvLzlN84kTGuHGGSwaXu1wopHPsytZ9eulSkmcvjCDt09P7vvsuKdVL3cOHx2bNEubmEhsX5ucHduhguMR0utOvvnp/yxaSlKBOndJPnPBt4/hRKAAAaO64Y0eI4zj1y5TEDB8+6+JF7wijaDkcRU+/+urZFStaXtkmjp/vqNdeOXXpkkbz9KMRCIV3Hv43+v+WOfG0I2bkSJafn+FSK5eX/PMPsYOlkz9ZZSVJaTF9faefOzdx3z7ThGdBnTtP2r9fHzuB0Omxo0eP/uMPr5AQQwdlXZ3+oJF0Y0T//jMvXaK+FlQoqL58WjM6HarRtLTvh5aEUqmhRBkmFMWqqyVuENREeN27z756NahTJ1L7nZ9/PjBmjLq+3iOjch1xvXu06d39uv44DcfP3bg+ZOFcn2Bn1ligMZmkkAm9dVTO59/95Zd9I0f+2bGjUQn4Zzzatw/Tap8/h8WamZ0dPXSoJUEB7duP2rhx7LZtywSCaSdPdlu82FB7q+7hw51JSeXGqfUgCGo7adILZ854sKaE/VRViW13AngIuVwtkSg8PQqARfj8epuGT3coQgSBfXzYtvtRAN82bWZfu9Zm1ChSe9nZszuTk+vy8jwyKtcx6MXZD/LzpXJ5YUkJSqd1HWlR0zhM+/R04mXhkSN7Bg/+NTLyzPLlZefOSUpKqo3j2fWQCiF1njcvpEcP64ISX365y/z55NqTR4/uHjBAUlxM6tznzTenHDrEcGqNKtfh59cySz+2DJhMOpsNyoNQF19fjk0jl3sUIRIU5OMGQU6B5eeXfuKE6bmguKBg94ABjfV7pDhefr7dUkfcfnD/Zm5u/7nTXZFhLjY1lUGIWdRIpZWXLxPrYZn1oJHx+cTLznPmNFowjt/88svDaWlqiZE1AqHTUzdtGvbNN56qsusAPF4LjORpMXA4zObyQ791EhzsQ4nwCQzDxWK5GwQ5C4ROT/ntt6Fff00Kq1DX1x+aOPHqJ580l+r24oKCG59/rpXJrPTpMXH0vQf/KTTquD49nSu97uHDa2vX7urfXyu39umTNn96SFqqsXnvtDLZkfT0i++9R6zGDEEQOyBgalZW4pIljXqax6mrA9751EWl0srldgW5AjyCSCSzaRp1h1s2hmESiSIgwMNlmBpL0ltv8RITj06fTtxS4Bh2dc2a2vv3x/z5J2Uj7usePny0b19BRkbtgwcQBPknJFjJH+0THOQfFhbRuaNzI4JvfvXVxXfftdLBt02b9unp7dPTzcYt+MbEEC+LTpyItLtUlrigIPOFF0hOpBAEBXbsOPXYMf+2be18DnUQixXNyKbS2lCrtRqNDpRhoiz19Qp/f671rzdgGrVGbGrq3JwcU/eZgoyMHX36UPbI8N9vv736ySd6LQhBUMGBA9b7R/foFtm1o3PHEDNihJX/jty48eXi4mHffhsxYIBZE2VE//7Ey1vffVedk2OP3CdHj+5ISjLVgm0nTZp740Zz1IIQBIWEUPQnFwACplHKw+PZNo2COELbqCWSEwsWkKq2QhDE8PJK/eOPTrNne2RUVig6fvwgIVVYo6L3rINptRiKYlotg8u1ccaG45vi4hpKS/VXdA5Hp1Qa/tn9lVdSTKp/EJGUlPwRH080QcMI0mX+/KghQ4I6d4YRBNPptHK5srZWIRQqhUKFUIiqVDW3b5uqQAiG+69ePWDNmmZ0KAgAANyJOxShvkJ9aKif7a5URW8Rvb5+vamvf6/XXhv69deNTaHpUlC1+ueQEGJygCmHD1vJJS0Wy9lsBodj/iVIioufZGZWXr1aeeWKrLJS38jy8wvv1y9y4MDExYu54ebLU1x4883yCxfap6e3S0+vuXUri+Dw4hUSsrSqCraQ7FTPwQkTirKyrHSwBxqLNXbbto4zZjTxOZ6lqkocERFgux/AE8jlap0O9fNrHh7IrRA+vz4szM/6ptA99QjRigpRbCzP1YJcTVFWVtbcuaYBhWFJSZMzMnyioz0yKrMcnzfv4c6dhsvO8+aN277dUueaGomXF4ts3sHx8uzsWz/+WHjkiBXnIBqLlbhkSb8PP+SGhZH+haOoQdVpGhp+5vFQzfPA8JnZ2VFDrCVyEz16tC0xkXiLY0QPHTo1K4vRyIrElKKwsCYhIdTTowCYRyJRaDQ64NlLWYqKBLGxPOsFKNxhLKLRaFFRlKnK2wTix4+fe+MGMXGXnuqcnB29e5OqnHsWUvTek8xMKxolONiHdNSvrq8/NmfO3uHDCw8ftu4ii6rVdzZu3N6rF98kHJC44WP6+rZJSSH+12be0cAOHSbu29f0Osnl2dmnmnmSPFCVl8r4+HBAVV4qExMTZLMMk3uSbkMtJiltQPv2c3NyTAu3KoTC/amp1z791GyeFPcTO3o0cQ+klkis6GkaDSFOlJrbt7d1756/Z4/94uR8/t9DhuTv3WulD0k3Pz540OZ7lTB58rxbt9qkpDQxwDFv167Ky5eb8gTPwmC0kOXTIkEQmEYDx8/UxR7t4x7TKMbni6Ojm0EuK/u5s3Hj+VWriGnA9MSMHDl+505TO2Fj0SoU/OvXyy9cqLp2TVZVJa+u1imV3LAwblhY9NChCWlpYX36WPf+ODp9+qP9+w2X3RYtGr15s9meAkGDlxfT25sNQZCkqGhX//4KgcCBMSMMxozz5yMHDjT7X2Vd3S+hocTAvjnXr4cnJ9vzZFllZfmFC3X5+RqJBIJhCIYVQmHx8eOmZmqmr2+3l16qvnWLpPk6zpgx4e+/G/mCqEJxsSAuLsR2P4AnkEqVarUuOLhZOsa3BkpKhDExwdY3hUAROk7llSvHZs2SlpeT2rlhYeN37owZOdKBZ6pEosLMzMcZGSWnTlk/HgtLShr1yy9hffpY6pC/d+8xws6VExS0tLrarKXRoAjVEsnOvn3FBQWkDt6Rkd1feSV66NCQHj1gGk1dX19+4cJ/27eXnDpF6unF4839919SFKCB/SkppWfOGC6T3n576FdfWXmN5sHx2xs3Zr/9tmnC7ogBAybs3u3bpg2OomeWL7/3+++GfzF9fVeKxc3UcRQoQioDFCHFoYoibMEoa2tPLFhgmncNRpB+q1cP+Phj646RBhQ1NY8PHy7IyCg7d46UDMUaMDz4s8+SLdTe00ilP/N4RG0x/exZ6+F9l1evvr5+PbEFYTCGfPFFzxUrzLrFlp4+nTVvnqKmhtgYM3z49LNnzRoz7/322+mlSw2XfvHxSwoLG2X2VNfXn1y06PHBg+R/wHDft98etH69QdOrJZI/4uKIBXhf+u+/oM5NrTYMAABaHu4pwwS11DIlnODgtKNHTWPUcAy79umn+1NS5MY5M0lIKypub9iwd9iwXyMiTr/6aunp043QghAE4fil99+/umaN2X8yfXzixowhtljyT9FqURTFFDU1t374gdhO53BmnD/fZ9UqS8EhbVJS5ly96p+QQGwsO3++MDPTbP92aWlEtScpKhLcu2e2p1mqc3K29+plqgWZvr6TMzKGfPklcb/L8vMjeaVKSkrsl0Up1GqyBR5AHVAU0+kas2wB7sWe5eOeMkxoC64jAyPIgP/9b9rJk16hZAf3svPnt/XsaVrmXlJcnPPNN7v69/89Ovrca6+VZ2c3xcXm6iefmNkhQRBk6p9y6JBZQSKRTKHQ3N+yhZQUdPTmzZYO/Az4xcdPPXaM6WNkF7rw1ltm7bpeoaFRgwcTW+ytWY/jt3/8cc+gQaZ1JEJ79Zp/61a7tDTTm0h2YOfmkHMn5eUiTw8BYBGZTNW8cim3NiorxRhGgTJMMAxbCtZuMbRJSVlw966p4VFRU3NgzJjLq1fjKCp69OjGZ5/t6N37j/j47Lff5l+/bv2ZAe3adVu8eNi3347fuTN106bk996zVIro9LJlKpGZ78q2Eyfqy9XqkfP5ZjNcM5l0Oh0hHfhFDhxoZ9KcwA4dUjdtIrbUFxYSoxiJkHWzHYpQJRYfTks798Ybpsq118qVs022pHowna7C2F+GWKq3eeHl1cKXT7OGTqcxme5I2gxwDA6HafM3MDgjdCY4il7/7LOrn3xiauFkcLnWizAYCEtK0mejNvP9juPFJ0+eeuUVUw+dPqtWDfv2W9OnZYwdW3zypOGy9xtvDP/+e9NuWrl8Q0AA0Ql20v797adNs2fA+oHtGTKE6KgZ0b//7KtXTTtKKyp+N8488NLDh6bZXA1U5+QcnT7d1KrJ8vcfs2VLu6lTLd1IyvrN8PZeKRY3PSoRAAC0PNxUhkkqVblBkMeBabT+H300/exZ74gI0r9saEEYjhw4cPh3371cWjr35s2+775rdpcDwXDc2LGzr171i48n/ef+n39qFWbKZJtG75kGyCuVmrqCQlIoiHW3GtOBkfw/q65dq/3vP9OOPlFRpJAJi5tCHL/1/fd7Bg0y1YLhycnz79yxqAVxPOebb0i1L9pNmdJ8tWBDg9J2J4CH0Gh0KlVT8x8BXIdUqrS53XOPIsRaVUG16KFD59+9Gzt6tM2eMILEDB8+cuPGVysqZl2+3Pv//s9S4AERn6ioCbt2kdxz1PX1ZkPg206eTOzZUFZW/e+/pD4NDcqGGiGxxb9tW3Zg45IBRfTvT4rluG8hbJGkm80eEyoEgv2pqedXrTJz1gjD/T780C821uzD6wsLjy9YkP3226a3WB8/lREIGmx3AngIpVLTSn7oN1OEQqlNw6ebyjA1u2KETcSLx0s/fpzozU8isFOn0X/8sbS6evq5cz2XLzfdQVonvF8/0/2Q2RTVXjxe9LBhxBZTxePtzcYVRr9UWH6OZEgnFbw1jSrRQ1KEgrt3JUVFxJaKixe39+xJjDg0AscPp6Xd+OILZW2toU3T0FB84sTR6dO3dOjwcMcO0h0DPv44sKOT60y5k6AgkMGLurDZDC4XlGGiLoGB3jbPCN2jCOFWmJodRpB+H3ww/dw5n6go0/9Knjzhhod78RxPRN795ZdJLZWXL5vNC2pmB2bcjctl0ZkMYguN5UiV0Q7TpxN3n+KCAllVlWk3v/j4kJ49yUPSg+M3v/xy38iRZm80gKPopfff/yU09PeYmG3du/8eE7MhICBj3LhH+/ebusW2mzq1/8cfO/ByqENr+x3ZvGCxGMCbicr4+3vZ9BgHplHXEjV48Lxbt2JTU0ntqEZzcOLEsytXmqZHsZOI/v1J1lGFUGg2VI4UvVdfWCi8f5/YoaFByeIZxX4ohEaWUjth+fuH9u5NbCm/cMFsT7PWUWVt7aFJky6+9x6mM446heFuixYxvMm7IhzDpOXlwtxcaXm5pfiTnitWTNy7t5kmlDEgFALTKHUBplGKU1tLDdNo63GWMYtXSEj6iRODP/+c/JsEx+9s3Pj3kCENZWUOPJbh7W2a0ZRYg9AANzw8csAAYgupZr1SqWHyjB4lLStzLLQxZvhw4qXZaA3IRBHyb9x4fOjQtu7dnxw7RurJCQ5Oy8wcvXnzhF27iKEgNvGOiJiwZ8/IDRuar4+MAYkEOMtQF+AsQ3EaGqjhLEOjIWFhzbgqb9OBEST5vffiJ00y/Rf/5s3tPXqQNJPdzyXrVp3K/A8O6/4pAQHcwOhwYrUKVKMRPXrkwIgCjGtUGQr5kgjs2JGU7Sxz2jRTc2j00KEL7t1rO2ECBEFtJ02anJHB9LVd9c07ImLAmjWLHj0yLRLSTAFVeakMl8tqhUc/zYjwcH9KmEZhGGazgQ0d6vHqq2bbVWJx5vTplrKxWEJdX2+qZjjB5gvXkTxr6h4+FOXnGy6ZTDqdQY8cNIjYp+zsWfsHY4Dk9WrlqI+km8kbUBjus2rVC2fOEN2I2k6cuOjRI7NmUgiCvCMiOs+dO+Xw4ZdLSwf8739m+zRTwBEUlQEB9RTHnoB6dyhCnQ6rrAQ5oqCYkSMtemPi+L/ffrtn0CDTSHlLPD58mNTCCQryN4kv1OPbpk1YUhKxhbgprK2VyuVqUuCgaWUJe2Aaqx95dbWlniRFaAQMQzge0b+/qVWTGxY2evPm5ULhC6dOjd68eehXX4365Ze0zMyF+fmvVlSM27EjYfLkFmALJVFaWmu7E8BDSKUqkUjm6VEALFJeXkeJFGsQhGu1ICktRGMy25qzjhqozsnZ0adPyT//2HyUVi6/8dlnpMbo4cOtVHKwYh1FUQzDcJIiLD550gGXGY3M6BuBzrbgVo7jZRYqVOj/C5kcZJIe2yYlpduiRUlvv91j6dK2EycGdujQxOK9VAYsHyqDYRiKUqIcN8As9iwfdyhCOp0WE2PeZNfaIGkjU+8PhUCQMW6c2W+sQ9AAABtSSURBVCRtBjCd7p9Fi8SPH5Pak958037Rgjt3DNF7ISG+3t6s0J49iZEemFZrGpBnE5ItlB1kpgilWiI5Mm3a+TffNBvsYeBJVpZOCZxEIAiC4uMdD7MBuBpfXw4oRkhlYmN51osRQu7aEQKeEpuaSvRJwbTaxCVLSEWOcAy7umbNoUmTiAHjBhRC4aGJE/P37iW1x4wYEd6vnxXR/gkJvMREYgvJZQam0bouXEhsubNhQ2OjOyqvXCFemp5ZCnNzd/TubalcBhGtTFaend0o6QAAAOAA7jkjRMvKwCEHBEEQncOJHz+e2ILj+IwLF7wjI0k9i44f35mUVHP7tqFFXV//73ffbWnfnphEWw/Tx4dU/8EslqyjAkGDTKaGIKjbwoVG9QJLSu5s3Gj7VT0DVatJ2W0ijNOK5u/du7t///onT2w+KmrIkPQTJ+LsSFPXGigqciSsE+AeGhqUtbWtNE66WVBSIqTIGSHMYNhVqL01QNJGhYcOhSUlLbh71zToXlJS8vfgwfe3bn2SmXl83rxfIyIuvPmmur6e/EQYTv3jD/+2bW2KbmcSvSetqIAgiEZD9KYD3zZt4seOJfa5+umn9ugtPf9t305yZDUkXMW02ux33jk2c6ZpZvDOc+Z0mjMnsEMHpq9veL9+iS+/PPvKlZnZ2XFjxrTgY79GAZYPlUEQhEYDpjXqYs/yAWWY3I1WJvuZxyMG/E0/ezZmxAgcRa+vX3/1k08aFckO02jjtm3rNGeOXb1x/M9OnYgBgiN+/LHXa68Ruwju3t3eqxfx9I6XmDj72jWGl41IqfonT3b06UPU094REa+Ul8MIoqytPTpzpmk8BtPHZ+xff1kppQQAAABuwB0/ZHAcB5kXDDC8vWPHjCG26E2UMI3W/+OPJ+7dy7Q7AM6/bdvpZ87YqwUhCIJhUolBvWiNRmdwewvp0SNx8WJiH2Fu7oHUVLMHlgbEBQUHx48n7Vb7f/wxjCDVOTnbe/Uy1YLBXbvOvXkTaEF7UCjA8qEuOh2q0ehs9wN4CKVSQ4nMMiiKVVdL3CCouUCuEXjokEIofLB168EJE47Nnk2KQDALNzx80Nq1L96/T6os0VjRFZcuKWpqxGI58at20Lp1pBpMlVeu7Ozbt/DIEVM/T61cfmfjxh19+pAy0QS0b99t4cK8Xbv2DhtmGhzZcebM2VevNuuKEO6kqkrs6SEALCKXqyUSM6VAARSBz6+3afh0h2kUwzCxWB4UBDyMn6Kur/85JMSoEC4MW48leNoLgkL79k1+9922Eyc2KvHmc3D8j7ZtJcXFhoaUX3+Nm72AyaSz2c8fWHbu3P7UVNMQDl5iYvy4ccHdutGYTHlNDf/GjaKsLJWInC2B4eX1wtmzjzMycr75hvwSaLTh33/fa+VKRwbfWhEKG3g827nlAB5BqdTodJiPD6jERFFqa6VBQd7Ws6yBM0LPkDFuXPGJE47cCcPJ7703aN06hysqZL/9NlE/tRk16oXTp0273f3llzPLlzsyQBptwu7d/23fblofkRMcPGn//sbuYgEAAMCluKn6BDAdkLCWYOwZ7MDAuHHjWP7+Rq04fuPzz4/NmuVwsDlJdNn583XlfNNDjh7Llo346SeY1jh/Ra/Q0LFbt15fv95UC4b06DH/9m2gBR1ALJZ7eggAi6jVWnCIS2Xq6xUUKcOEgZVMImHyZEs6xis0tPsrr7xw+vSy6ur0rKwXc3PD+/Yl9Xm0b9/fQ4dar15ribC+fYkZZHAUfXTwkFpt5rS/18qV08+csb96cLu0tLFbt2a/844wN5f0r87z5s26csUnOtqBAQPq6kAqS+qiUmnl8tZbZo76iEQySjjLIAgCDghJcIKDSXsjdkBAr9dem5mdvbSyMuW339qMGqU/BfSJjp6RnW26g6zOydmVnFz38GFjRcMIQvLVrDx5jHhASCR62LDFhYWD16/nmEuWpofO4SS+/PKLDx50njv3yNSp5ETbMDxo/fpx27fbDMAAWCIkBBwQUhcOhwkOCKkMj+djswwTOCP0GHd//fXMsmWGS/+EhMUFBVbyUF9Zs+ba2rUknxp2YOCUw4ejBg9ulOiKixf/HjrUcEljMpcJBBYrY0AQBEFaubzi4sWqa9dqbt1CNRoYQRhcblifPhEDBoQlJTG43Lu//HL2tddI/jUMb+9x27aBGAkAAEBl3KEIURSrrZWGhrbq2rymyKurf42IICq2BffukdKBkni0b9+JF18knQ7SWKyx27Z1nDHDftE4iv4aEaEQCAwtKX/+1f2lBfY/wfhx+MX33rv51VekZp/o6KlHj/K6d3fwsYBnVFWJQW1eyiKXq3U6FNTmpSx8fn1YmJ/1TaGbAuqVSnCYTIYbFhY5cCCxhZQF25QO06fPuHCBGxZGbETV6qzZs2//9JP9omEarV1aGrGl8JDtLNhmwbTa4/Pnm2rBsKSkuTdvAi3oFIAvBpUBAfUUhyoB9TQaDfyeNQs5st6WIoQgKLxv39nXrgV16kRsxDHs3OuvX/n4Y4dFl585rZU32qFJp1QenjLl4c6dpPaEyZNNFTbAYaKjA213AngIb292QADXdj+Ah4iMDKBEGSYYhpjMllY03CmQDs9q//tPlJ9v8y6/2NhZly9HDhpEar+2du3ZFSusFDIkEj1sGDF9jE6pbGxco0osPjBmTNHx46T2HkuXTs7IAK4xToTFcih5AsAt0GgInQ6yolMXe5aPe8owYeXldW4Q1OzwjYkhhUbYtI7qYQcGvnDqlGm9+zs//5w1b55RzhoLIAxGwuTJ+r+5ERHdli4PNN5lWkdRU7Nv5MiKixdJ7QPWrBn1yy+NjT4EWKe4WGC7E8BDSKWgDBOlsacME9ioeZh26en8mzcNlwUZGf0+/NCeG+kczpSDB8+98QapZGD+nj2YRjPh778Ruo0Pt8uCBZzg4Pbp6bTYjl5clre3vS7gipqavSNGkCI3EDp99JYtXebPt/MhAAAAQBFA+ISHqX/yZHNCArFlyZMnfvHx9j/h8urV19evJzUmTJ48cd8+GpPphCEaI6uq2jdyJMmES2ezx+/eTXLAAQAAgGaBe7xGIZ3OroOrVoh/27Yk10o7raMGBq1bN/z770mNhUeOZM2ebY+NFIIgFMVsmg70KGpq9o8aRdKCDC43/cQJoAVdh1YLlg91wTDcUMUMQEHs0T7uKcOEVlSQCxQADJAcOBurCCEI6v3GG6mbNpGC8QsyMrLmzrXHd6a2ViqXq212U9bV7R0xoi4vj9jI8vObfvYsyCDqUkpLrRWDBHgWqVQpEoEceNSlrKzO5g9993iNwhyO8210LQaSIuTfuCGtqGjsQxKXLBnz55+kkhSP9u37Z8kSmwWemEw6nW5jJmgaGg6kppLOBVn+/tPPnQtPTm7saAGNwssLLB/qQqfTgFc8leFwmLYyrLkpjhABaWWsENS5Myku8PFBR8Lbu774oqkufLB1a/a771q/MSCAa/2XCqpWH5o8ueb2bWIjOyBg+tmzob16OTBUQKMAYbhUhstlgbQyVCY83N9mrlE3lWGSSkF2dmu0I1lHDxxw7DldFiwwtZHmfP31zS+/tHKXUqmxcgqFo+ixWbPKL1wgNrL8/Kb98w/Qgu6hocHBklsAN6DR6FQqkPqHukilSkpklsEwrK4OxNlYg2Qdrbh8mVzDwW66LVo04scfSbrw4vvvWzl6bGhQqlQW3WrOvfHG40OHiC0MLjft6NGwpCTHRghoLAJBg6eHALCIUqkBP/SpjFAopUQ9QgRBgOnAOiHduxuFTOB44eHDDj+t18qVg9atM2rC8eNz51ZdvWq2P5fLsnTIcXvDBlKcIo3FcqDeBaApBASA5UNdWCyGlxfL06MAWMTf34sSZ4QIAoNcfDaAYdKm8JGj1lE9/T74oM+qVcQWnUp1eOrUhrIy087e3mwWy4wiLDl16oLxQ2AEGbdjR5tRo5oyNkBjAeU8qQybzeBygSKkLoGB3hQ5IwSmUduQs2BfuKCsa1JeuqFff016pqKm5khaGqmKE2TBNFpfWHhs1ixMZ5RWf+jXX3d44YWmjArgAEIhMI1SF2AapTi1tdQwjQJnGXsIS0ryiYoyXOIoWnTsWFMeCCPI2O3bI/r3JzbW3L79z5IlpJ6mzjJamezwlCkqkVH0Z8/ly0m7TIB7kEiAswx1Ac4yFKehgRrOMjQaEhYGwidsACOI3nfUJzq61+uvz7x4sfPcuU18JsPLa8qhQ36xscTGvF27cjdtIrYEBHBJkWqnly2r/e8/YkvcmDHDf/ihieMBOAYIn6AyIHyC4tgTPgFyjVKI+sJCZV1deN++kM2z3cZQc/v234MHaxUKQwvDy2tuTk5Q585m++ft2pVlrIP9ExLm3rzJDgBfxwAAoAXinhRrGJ8vdoOg5o5/QkJ4crJztSAEQaG9eqX89huxRatQHJs9G1U/TasmEskUiqd/S4qKTi9bRuxM53CmHD4MtKAHAVXMqIxMphKLG13UGuA2KitFlDgjxHFcrdbZ7gdwGZ3nzUs0PhoU3rt3be1a/d9aLYqiOARBEI6fXLRI02DkmpHy66/BXbq4a6QAM4DlQ2VQFANFBaiMWq2zafd0k2kUw3AEcfJGB9AodCrVzj59iCd/CIMx9+bNkB499HMAhuHcTZtOvfIK8a4u8+eP3bbN3WMFGINhGIK44zcrwAEMy8fTAwGYxx7tAxRhK0Jw586ufv1QzXMPt7CkpDnXr+uNsYqamj87dVLX1xv+6xMd/dKDB0xfXw+MFUAAKEIqAxQhxbFH+7hjdel0aFkZqCPjeUJ69uz/8cfEluqcnPubNwsEDTKZ+uK77xK1IATDY7dtA1qQChQVCT09BIBFGhqUtbUgTpq6lJQIKVGGCYJgBoPmFkEAG/R9553grl2JLVf+9z9cpazLvftw505ie7eXXooZPty9owOYBywfKoMgCI0G9uvUxZ7lA8InWh2Vly/vGTKEWKRw0Lp1lVeuFJ84YWjhBAcvzM/nBAV5YoAAAADgVtyhCHEcV6u1bDYoLkoVsubMydu923DJ4HK1ciP/71E//9zDOIgC4EEUCg2ozUtZdDoUw3BQm5eyKJUaNttGbV43xRFWV0vcIAhgJ4PWrUMYDMMlSQsGtGuXaJKGDeBBqqpAGC51kcvVEonCdj+Ah+Dz6ykRR4ggsI8P2w2CAHbiFxfX9cUXLf2334cfEtUkwOP4+XE8PQSARZhMOjB3URlfX45Nl15wRthKET9+/GenTjhKDgT2iY5eUlSE0IGdBwAAtBbcVH0CmA6oRkC7drGpqabt3V95BWhBqgEyeFEZtVqrUIDqE9Slvl5BCdMohmFgJVOQri+9RGqBEaTLggUeGQzACnV1Mk8PAWARlUorl4Myc9RFJJJRogwTgiCgxDYFiR83jsYyqqxNqokIoAghISCtAXXhcJjAB4LK8Hg+lKhQD5xlqAmDyw1LSiK2RA8b5qGxAKzh6wucZagLcJahOD4+tp1l3HEahKJYba00NBTU5qUcAe3aqUSimIlTgtolqAXVMSNGeHpEADNUVYlBbV7KIperdToU1OalLHx+fViYn/VNYSMUoU6n+/777zMzM+/duxcaGrpo0aK33nqLbodjBY7jSiU4TKYiIzdsYHC5NTUSLy8W2LVTFuCLQWV0OlSjAXWyqItSqcFxG2VeaWvWrLHzcatWrVq3bl3fvn2XL18eFhb21Vdf4Tg+dOhQmzfCMMLlskA6PgpCYzIhCGKxGEwmHZQHoSxcLotOB+lGKQqDQWOzGaA8CGXx8mLaTDdqbxyhSCQKDw+fPn369u3b9XvMffv2LVy4UCKR0GhgiQIAAACguWLvr5j8/HyNRjN58mSDpTUlJUUul1dVVdm8V6fDysvrHB8jwMUIBA0yGfD/pi7FxQJPDwFgEakUlGGiNPaUYbL3jLBbt27379+Pj483tFy6dInD4YSEhNhxN46imJ2CAO4Hx0F+IUqDouDjoS4YBtYPpbGpBSH7zwhZLFZISAjjWQrKGzduzJo1a+nSpaNHjyZ202h0dXUyFMVYLIZcrq6vVyAIzGIxYBhuaFCyWHQEQWprpXK5mstl6b1JtVodm81UqbQikRyCcCaTLpUqJRIlnU6j0xGRSCaVqjgcJgTBQmGDSqX18mISpSgUarFYgSAwg0GTSBSWpGg0Og7nqRQc10tRSSQKOh2h02lisVwvBYZhgaBBpdJ4ebG0WpQkBYafS2Ey6TQaUlsrlcnIUtTq51JkMlV9PUkKQy9FqXwuRadD2WyGQqERi+WmUurqnkrBMFwoNJKCYTiL9VQKjfZcCpvNQJDnUnQ6tLb2qRSlUi8FYjDoDQ1KiUQZGMjlcJh6KV5eLBzHhUKpWq3lcJhqtU4kkmEYxmIxiFLq6+UNDU+lCIUWpUAQxGQ+lcJg0Gg0pK5OJpOp9LUUDFL0H6hein7aEKWwWE+lKBRqLpel0+mnDcpmM1QqjUj0VIp+2uil6KeNTSn6aVNfb2baPJNCnJzmpXA4T6WYTk6iFCuTkyjFdHKKRDIGg05YAvppY20JWJmcRClWJidxCVifnAYpGIaRJqclKaTJSZRiOjnNLoFnk9P2ErAyOYlSjCen0RIwnjZmlgCHw1Qo1EQp+slpaQnYOTlpNJhON0xOZy4BhydnM/1+jooKxDDc7PezbUWYn59f+4zg4GBDe21t7bvvvrts2bJZs2Z9++23Zo+ImUy6/mwfhmEmk44giE6H0uk0vUbEMJzBoOkHgeMQk0lnMGg4DsEwzGDQ6XQEgiAEQfTuGziO02g0FotOutEgRX+j/mXjOE6jPb+RTn8uhcGgPzsvhZlMGp1OgyD8mRTERArdrBQWi0ajIYQbYRyH6HT9jeal4DhRCkSjIQYpTCZRytPOMAwzmXopkKmUZ6+FxmDQTaXoZ5heCpNJh2EYx5++Y/ofrAwGjcGgQRBOeMeelhXVW7yJUphMvRQcgmDDm4Agz28kSjF+q/VSIJIUFov4uTCIUp4Nz2jaGKTo3zHDayHcSPr0n79jGGaQYvommErBaTTE5uQ0lWKYNkQpZpcAQYqZd0wv5dkHql8CRpMTx2G9irIyOZ9NG6PJSXwtjZqc5qTYOTntlYLjJClPV6WFt9rs5CRKgRAE1i8BCDKzBOyfnCQp+mlj7gN9KgXHIQzDnr0W2DA5LUkhTU5bSwB3bAnoJ+ezIdk5OVvm9zONBuvfHHNSnmLRWYYYdWHok5GRsXTp0qCgoO+//37MmDFmbzRFp0MrKkSxsTw7+wPcDAifoDiFhTUJCaGeHgXAPBKJQqPR8Xgg+w9FKSoSxMbyrHvFW3SWwQnoW/76669p06bNnDkzNzfXfi0IQRAMw3rzEYCaPNuFACgKqMpLZQw7GwA14XBsVOWF7A+fqK+vj4yMXLRo0U8//eSEoQEAAAAAQA3s/SGTmZmpUCgUCgXpTHHFihXEE0Sz4DiuUGi4XJb1bgBPoVJp9YfSnh4IwDwymcrbGxiuKYpWi+qdXDw9EIB55HK1lxfL+qbQXkX4+PFjCIK2bNlCap85c6ZNRYiimFDYwOWCM0KKIpEovLxYPj5AEVKU6mpJQgJQhBRFoVBrNDoeDyhCilJTI4mN5VnPNeqOCvX6wrwBAVxXCwI4hkymYjDoemc5AAWpq5OCQmaURaXSoigGLF6URSSSBQRwPa8IAQAAAACgLMBXEAAAAACtGqAIAQAAANCqAYoQAAAAAK0aoAgBAAAA0KoBihAAAAAArRqgCAEAAADQqgGKEAAAAACtGqAIAQAAANCqcYci1Ol0X3/99eDBg319fdu1a/fFF1/odDo3yAXY5MqVKwMHDvTz8xswYMDly5c9PRzAc8CqaUZcuXKFRgMZCilHdXX13LlzQ0ND27Zt+/vvv1vp6Q5F+NZbb73zzjthYWHfffddenr6p59++tlnn7lBLsA6eXl5I0aM4PF4a9euDQ4OHjlyZH5+vqcHBXgKWDXNhYaGhnnz5mEY5umBAIwQiUQjRowoKSn54IMPRo8evXTp0iNHjljsjbuYuro6JpM5d+5cDMP0LXv37uVyuTqdztWiAdZZunTphAkT9J8LiqLjxo1bvny5pwcFwHGwapoV8+fP9/f3d8N3KaBRfPfdd8nJySqVSn+5YsWK4cOHW+rs8h1hfn6+RqOZPHmyIedpSkqKXC6vqqpytWiAdTIyMpYsWaL/XBAEWbJkyYEDBzw9KAAEgVXTfNi3b9+ePXs2btzo6YEAyOzYsWPFihUs1tNk6O++++7SpUstdXZ50m2pVFpaWhofH+/l5aVvyczMnDlzplgsNgwR4H40Gg2LxSorK4uOjta3lJaWxsXFaTQaOh2UofAwYNU0C8rLyxMTE99///1JkyZ16tTJ1d+lAPvBcZzFYuXn58fFxVVXV/v7+3M4HCv9Xb4j9PHx6dq1q2E937hxY/Hixa+//jpYz55FIBBAEBQUFGRo4fF4OI4LhULPDQrwFLBqqA+GYQsWLOjZs+ebb77p6bEAyEgkEq1We+bMmbCwsIiICG9v7xkzZtTV1Vnq73xFmE+A2F5bW7ty5cpBgwZNmTJl7dq1TpcLaBT6X6/EGl36Fo1G47ExAUwAq4ayfPfdd3fv3t2+fTvwF6Ugep23cePGgwcPymSyf//9t6ioyIpp1PkHvGYffuDAAR6P17FjxxMnTjhdIsABlEolBEHl5eWGltLSUgiCDGfLAI8DVg1lefLkCYPBWL9+fV5eXl5eXlZWFgRBeXl5xcXFnh4aAMdxvLa2FoKgu3fvGlru3buHIIhCoTDb3x2eTlu3boUgaOXKlRqNxg3iAHbC4/GysrIMl1lZWSEhIR4cD4AIWDVU5tKlS2b3FcnJyZ4eGgDHcRxFUQaDIRaLDS319fUQBFVVVZnt7/Izwvr6+uXLl69cufKnn35iMBiuFgewn6lTp27fvh3HcQiCcBzfvn17enq6pwcFgCCwaijPoEGDiF+jeXl5EAThOH79+nVPDw0AQRCEIEhKSsru3bsNLRkZGTweLywszGx/l/sHZmZmKhQKhUKxZs0aYvuKFSuCg4NdLR1gheXLl/fr1+/VV18dNWrUqVOnjh07BpYxRQCrBgBoIm+99daYMWPu3r3bu3fv3NzcTZs2bdiwgegVYYQLd6c4juP46tWrzcrNy8tztWiATbKzswcNGuTr6zt48OBLly55ejiAp4BV07ww7AgBlOLo0aPJyclcLjcxMXHbtm2G9BSmuDyOEAAAAAAAKgOqTwAAAACgVQMUIQAAAABaNUARAgAAAKBVAxQhAAAAAFo1QBECAAAAoFUDFCEAAAAAWjX/D5wPX3owvc6eAAAAAElFTkSuQmCC",
"text/plain": [
"Plot{Plots.GadflyPackage() n=2}"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"push!(p, 2, 5,5)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"1-element Array{Gadfly.Layer,1}:\n",
" Gadfly.Layer(0x0 DataFrames.DataFrame\n",
",Dict{Symbol,Any}(:y=>[0.625,0.625102,0.625407,0.625916,0.626629,0.627544,0.628662,0.629982,0.631503,0.633225 … 0.633225,0.631503,0.629982,0.628662,0.627544,0.626629,0.625916,0.625407,0.625102,0.625],:x=>[0.0,3.98065e-7,3.18434e-6,1.07461e-5,2.54686e-5,4.97346e-5,8.59226e-5,0.000136407,0.000203556,0.000289731 … -0.000289731,-0.000203556,-0.000136407,-8.59226e-5,-4.97346e-5,-2.54686e-5,-1.07461e-5,-3.18434e-6,-3.98065e-7,-2.35095e-47]),Gadfly.StatisticElement[],Gadfly.Geom.LineGeometry(Gadfly.Stat.Identity(),true,2,symbol(\"\")),Gadfly.Theme(RGB{U8}(0.545,0.0,0.0),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.9,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(1.322751322751323,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Any[],nothing,nothing,1.0,nothing,Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(5.0,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.816,0.816,0.878),[Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.5,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.5,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0)],RGB{U8}(0.627,0.627,0.627),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.2,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),\"'PT Sans Caption','Helvetica Neue','Helvetica',sans-serif\",Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(2.822222222222222,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.424,0.376,0.42),\"'PT Sans','Helvetica Neue','Helvetica',sans-serif\",Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(3.880555555555555,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.337,0.29,0.333),\"'PT Sans Caption','Helvetica Neue','Helvetica',sans-serif\",Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(2.822222222222222,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.298,0.251,0.294),\"'PT Sans','Helvetica Neue','Helvetica',sans-serif\",Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(3.880555555555555,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.212,0.165,0.208),\"'PT Sans','Helvetica Neue','Helvetica',sans-serif\",Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(2.822222222222222,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),RGB{U8}(0.298,0.251,0.294),40,Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(-0.05,Compose.MeasureNil(),Compose.MeasureNil(),-0.0,-0.0),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(1.0,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(3.0,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Gadfly.default_stroke_color,Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.3,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),Gadfly.default_discrete_highlight_color,Gadfly.default_continuous_highlight_color,(anonymous function),1.0,Gadfly.default_middle_color,Compose.Measure{Compose.MeasureNil,Compose.MeasureNil}(0.6,Compose.MeasureNil(),Compose.MeasureNil(),0.0,0.0),:left,:square,:right,RGB{U8}(0.545,0.0,0.0),1000,10.0,0.5,0.2,4),0)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"celltoolbar": "Slideshow",
"kernelspec": {
"display_name": "Julia 0.4.0-rc4",
"language": "julia",
"name": "julia-0.4"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "0.4.0"
}
},
"nbformat": 4,
"nbformat_minor": 0
}