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donovanr/jarred_example

Last active July 13, 2016 21:05
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example plot
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jarred_example
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"library(ggplot2)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<thead><tr><th></th><th scope=col>pos</th><th scope=col>rf</th><th scope=col>chr</th></tr></thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>1</th><td>15.0000000</td><td> 0.5460688</td><td> 1.0000000</td></tr>\n",
"\t<tr><th scope=row>2</th><td>36.0000000</td><td> 0.3892397</td><td> 1.0000000</td></tr>\n",
"\t<tr><th scope=row>3</th><td>63.0000000</td><td> 0.4659786</td><td> 1.0000000</td></tr>\n",
"\t<tr><th scope=row>4</th><td>75.000000</td><td> 0.580312</td><td> 1.000000</td></tr>\n",
"\t<tr><th scope=row>5</th><td>96.00000</td><td> 0.42691</td><td> 1.00000</td></tr>\n",
"\t<tr><th scope=row>6</th><td>107.0000000</td><td> 0.4570076</td><td> 1.0000000</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"\\begin{tabular}{r|lll}\n",
" & pos & rf & chr\\\\\n",
"\\hline\n",
"\t1 & 15.0000000 & 0.5460688 & 1.0000000\\\\\n",
"\t2 & 36.0000000 & 0.3892397 & 1.0000000\\\\\n",
"\t3 & 63.0000000 & 0.4659786 & 1.0000000\\\\\n",
"\t4 & 75.000000 & 0.580312 & 1.000000\\\\\n",
"\t5 & 96.00000 & 0.42691 & 1.00000\\\\\n",
"\t6 & 107.0000000 & 0.4570076 & 1.0000000\\\\\n",
"\\end{tabular}\n"
],
"text/plain": [
" pos rf chr\n",
"1 15 0.5460688 1\n",
"2 36 0.3892397 1\n",
"3 63 0.4659786 1\n",
"4 75 0.5803120 1\n",
"5 96 0.4269100 1\n",
"6 107 0.4570076 1"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"make_data <- function() {\n",
" c_lengths = sample(5:10,11, replace = TRUE)\n",
" n = sum(c_lengths)\n",
" x = 0:(n-1)\n",
" x = sort(sample(0:1000,n))\n",
" y = 0.5 + 0.05*rnorm(n)\n",
" df = data.frame(\n",
" pos=x,\n",
" rf=y,\n",
" chr=rep(1:11, times = c_lengths)\n",
" )\n",
" return(df)\n",
"}\n",
"head(make_data())"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fancy_plot <- function(df){\n",
" p <- ggplot(data = df) + \n",
" # line:\n",
" geom_line(aes(x = pos, y = rf)) +\n",
" geom_hline(aes(yintercept=0.5), linetype=\"dashed\") +\n",
" # shading:\n",
" geom_rect(\n",
" aes(\n",
" xmin = c(0,data$pos[-length(data$pos)]),\n",
" xmax = data$pos,\n",
" fill = factor(chr %% 2)\n",
" ),\n",
" ymin = 0,\n",
" ymax = 1,\n",
" ) +\n",
" scale_fill_manual(values = alpha(c(\"white\", \"gray\"), .3)) +\n",
" # x ticks are the midpoint of the first and last occurances of unique chr entries\n",
" scale_x_continuous(breaks=rowMeans(\n",
" cbind(\n",
" tapply(data$pos[seq(data$chr)], data$chr, min),\n",
" tapply(data$pos[seq(data$chr)], data$chr, max)\n",
" )\n",
" ),\n",
" labels=unique(df$chr)\n",
" ) +\n",
" scale_y_continuous(limits = c(0,1)) +\n",
" # clean up the plot:\n",
" labs(x = \"Chromosome\") + \n",
" theme_bw() +\n",
" theme(\n",
" legend.position=\"none\",\n",
" axis.line = element_line(colour = \"black\"),\n",
" panel.grid.major = element_blank(),\n",
" panel.grid.minor = element_blank(),\n",
" panel.background = element_blank()\n",
" )\n",
" return(p)\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/svg+xml": {
"isolated": true
}
},
"output_type": "display_data"
}
],
"source": [
"data = make_data()\n",
"p <- fancy_plot(data)\n",
"\n",
"# save:\n",
"ggsave(\"plot.pdf\", plot = p, width = 8, height = 2)\n",
"\n",
"# display (coord_fixed is kind of a hack here)\n",
"p + coord_fixed(ratio=200)"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.2.2"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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