{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Graphics-and-Devises\" data-toc-modified-id=\"Graphics-and-Devises-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Graphics and Devises</a></span></li><li><span><a href=\"#R-graphics-parameters,-layouts-&amp;-margins,\" data-toc-modified-id=\"R-graphics-parameters,-layouts-&amp;-margins,-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>R graphics parameters, layouts &amp; margins,</a></span></li><li><span><a href=\"#Multifigure-Layouts\" data-toc-modified-id=\"Multifigure-Layouts-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Multifigure Layouts</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "run_control": {
     "marked": false
    }
   },
   "source": [
    "## Graphics and Devises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "?dev.off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<strong>windows:</strong> 6"
      ],
      "text/latex": [
       "\\textbf{windows:} 6"
      ],
      "text/markdown": [
       "**windows:** 6"
      ],
      "text/plain": [
       "windows \n",
       "      6 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<strong>png:</strong> 2"
      ],
      "text/latex": [
       "\\textbf{png:} 2"
      ],
      "text/markdown": [
       "**png:** 2"
      ],
      "text/plain": [
       "png \n",
       "  2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "ERROR",
     "evalue": "Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet\n",
     "output_type": "error",
     "traceback": [
      "Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...): plot.new has not been called yet\nTraceback:\n",
      "1. abline(h = 0, col = \"gray\")",
      "2. int_abline(a = a, b = b, h = h, v = v, untf = untf, ...)"
     ]
    },
    {
     "data": {
      "image/png": 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9lHYmlqTn+vL2btVi7sY0nqHkfa9seR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\nSBDwf9InG4+iui97AAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Not run: ## Unix-specific example\n",
    "x11()\n",
    "plot(1:10)\n",
    "x11()\n",
    "plot(rnorm(10))\n",
    "dev.set(dev.prev())\n",
    "abline(0, 1) # through the 1:10 points\n",
    "dev.set(dev.next())\n",
    "abline(h = 0, col = \"gray\") # for the residual plot\n",
    "dev.set(dev.prev())\n",
    "dev.off(); dev.off() #- close the two X devices\n",
    "\n",
    "## End(Not run)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## R graphics parameters, layouts & margins,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graphs are typically created using a series of **high-level** and **low-level**\n",
    "plotting commands. High-level functions **create new plots** and low-level\n",
    "functions **add information to an existing plot**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**par():** Customize graphs (line style, symbols, color, etc) by specifying graphical\n",
    "parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `par` function can be used to control margins and the layout of plots on the page, using the parameters `mar, mai,\n",
    "pin, oma, omi, mfrow` and `mfcol`.\n",
    "* There are 72 graphics which par parameters holds.\n",
    "* You can view the settings of the parameters by typing \n",
    "`par()`  \n",
    "* View their names by typing \n",
    "`names(par())` \n",
    "* To extract a graphic parameter, `par(\"tag \") or par()$tag` .`  \n",
    "* To set a graphic parameter, `par(tag=value )`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**List of Graphical Parameters:** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " \n",
    "\n",
    "| V1       | V2       | V3        | V4      | V5   | V6     |\n",
    "|----------|----------|-----------|---------|------|--------|\n",
    "| xlog     | cin      | family    | lheight | mkh  | srt    |\n",
    "| ylog     | col      | fg        | ljoin   | new  | tck    |\n",
    "| adj      | col.axis | fig       | lmitre  | oma  | tcl    |\n",
    "| ann      | col.lab  | fin       | lty     | omd  | usr    |\n",
    "| ask      | col.main | font      | lwd     | omi  | xaxp   |\n",
    "| bg       | col.sub  | font.axis | mai     | page | xaxs   |\n",
    "| bty      | cra      | font.lab  | mar     | pch  | xaxt   |\n",
    "| cex      | crt      | font.main | mex     | pin  | xpd    |\n",
    "| cex.axis | csi      | font.sub  | mfcol   | plt  | yaxp   |\n",
    "| cex.lab  | cxy      | lab       | mfg     | ps   | yaxs   |\n",
    "| cex.main | din      | las       | mfrow   | pty  | yaxt   |\n",
    "| cex.sub  | err      | lend      | mgp     | smo  | ylbias |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| High-level                     | Description                                                                             | Low-level | Other                  |\n",
    "|--------------------------------|-----------------------------------------------------------------------------------------|-----------|------------------------|\n",
    "| `plot()`                       | Scatterplot-------------------------------------Add points to a figure                                                                          | `points`  | `par`                  |\n",
    "| `hist()`                       | Histogram-------------------------------------Add lines to a figure                                                                             | `lines`   | `colors`               |\n",
    "| `boxplot()`                    | Boxplot-------------------------------------Insert text in the plot region                                                                                 | `text`    | `palette`              |\n",
    "| `qqplot(), qqnorm(), qqline()` | Quantile plots-------------------------------------Insert text in the figure and outer margins                                                                      | `mtext`   | `colorRamp`            |\n",
    "| `interaction.plot()`           | Interaction plot-------------------------------------Add figure title or outer title                                                                       | `title`   | `rainbow, heat.colors` |\n",
    "| `sunflowerplot()`              | Sunflower scattterplot-------------------------------------Insert legend                                                                  | `legend`  | `grey`                 |\n",
    "| `pairs()`                      | Scatter plot matrix-------------------------------------Customize axes                                                                     | `axis`    | `col2rgb, rgb2hsv`     |\n",
    "| `symbols()`                    | Draw Symbols on plots-------------------------------------Add horizontal and vertical lines or a single line                                                                  | `abline`  | `rgb, hsv, hcl`        |\n",
    "| `dotchart(), barplot(), pie()` | Dot chart, bar plot, pie chart-------------------------------------Draw a box around the current plot                                                         | `box`     | `layout, layout.show`  |\n",
    "| `curve()`                      | Draw a curve from a given function-------------------------------------Add a 1-D plot of the data to the \f",
    "gure                                                      | `rug`     | `windows`              |\n",
    "| `image()`                      | Create a grid of colored rectangles with colors based on the values of a third variable | `lowess`  | `pdf`                  |\n",
    "| `contour(), filled.contour()`  | Contour plot-------------------------------------Draw a polygon                                                                            | `polygon` | `dev.off, dev.new`     |\n",
    "| persp()                        | Plot 3-D surface-------------------------------------Draw a rectangle                                                                    | `rect`    | `jitter`               |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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f080hs5j3T06i3mkUC/cEx/Y60dsA6O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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "GenericFigure <- function(ID, size1, size2)\n",
    "{\n",
    "  plot(0:10, 0:10, type=\"n\", xlab=\"X\", ylab=\"Y\")\n",
    "  text(5,5, ID, col=\"red\", cex=size1)\n",
    "  box(\"plot\", col=\"red\")\n",
    "  mtext(\"Figure\", SOUTH<-1, line=3, adj=1.0, cex=size2, col=\"blue\")\n",
    "}\n",
    "\n",
    "# Figure 1. Default R Plot Area / Figure Area\n",
    "Figure1 <- function()\n",
    "{\n",
    "  oldpar <- par(oma=c(0,0,0,0)) # default values\n",
    "  GenericFigure(\"Plot Area\", 3,2)\n",
    "  box(\"figure\", col=\"blue\")\n",
    "  par(oldpar)\n",
    "}\n",
    "\n",
    "\n",
    "par(oma=c(2,2,2,2))\n",
    "\n",
    "GenericFigure(\"Plot Area\", 3,2)\n",
    "\n",
    "# \"figure\" box and \"inner\" margin box same for single figure plot\n",
    "box(\"figure\",lty=\"dashed\", col=\"blue\")\n",
    "box(\"inner\", lty=\"dotted\", col=\"green\")\n",
    "\n",
    "mtext(\"Outer Margin Area\", SOUTH<-1, line=0.4, adj=1.0, cex=1.5,\n",
    "      col=\"green\", outer=TRUE)\n",
    "box(\"outer\", lty=\"solid\", col=\"green\")\n",
    "\n",
    "Margins <- capture.output( par()$mar )\n",
    "Margins <- substr(Margins, 5, nchar(Margins))\n",
    "Margins <-\n",
    "  paste(\"mar = c(\", gsub(\" \",\",\",Margins), \")\", sep=\"\")\n",
    "mtext(Margins, NORTH<-3, line=2, adj=0.0, cex=1.5, col=\"blue\")\n",
    "\n",
    "#Figure2A()\n",
    "\n",
    "# Text: one string per mtext call\n",
    "mtext(\"mar[SOUTH<-1]\", SOUTH<-1, at=5, line=2,    cex=1.2, col=\"blue\")\n",
    "mtext(\"mar[WEST<-2]\",  WEST <-2, at=5, line=2,    cex=1.2, col=\"blue\")\n",
    "mtext(\"mar[NORTH<-3]\", NORTH<-3, at=5, line=0.25, cex=1.2, col=\"blue\")\n",
    "mtext(\"mar[EAST<-4]\",  EAST <-4, at=5, line=0.25, cex=1.2, col=\"blue\")\n",
    "\n",
    "# Text: vector of strings in mtext call\n",
    "mtext(c(\"oma[SOUTH<-1]\", \"oma[WEST<-2]\", \"oma[NORTH<-3]\", \"oma[EAST<-4]\"),\n",
    "      c(SOUTH<-1, WEST<-2, NORTH<-3, EAST<-4),\n",
    "      line=0.4, cex=1.2, col=\"green\", outer=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uVEjiNz7Ntxt7/dOLLBr037S7zbGf1gHp8Vqc6ncTaH71d2/Fu3E8m/Uz5mAELK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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Margins area\n",
    "par(oma=c(3,3,3,3))  # all sides have 3 lines of space  \n",
    "par(mar=c(5,4,4,2) + 0.1)   \n",
    "\n",
    "# Plot  \n",
    "plot(0:10, 0:10, type=\"n\", xlab=\"X\", ylab=\"Y\")    # type=\"n\" hides the points  \n",
    "\n",
    "# Place text in the plot and color everything plot-related red  \n",
    "text(5,5, \"Plot\", col=\"red\", cex=2)  \n",
    "box(\"plot\", col=\"red\")  \n",
    "\n",
    "# Place text in the margins and label the margins, all in forestgreen  \n",
    "mtext(\"Margins\", side=3, line=2, cex=2, col=\"forestgreen\")  \n",
    "mtext(\"par(mar=c(b,l,t,r))\", side=3, line=1, cex=1, col=\"forestgreen\")  \n",
    "mtext(\"Line 0\", side=3, line=0, adj=1.0, cex=1, col=\"forestgreen\")  \n",
    "mtext(\"Line 1\", side=3, line=1, adj=1.0, cex=1, col=\"forestgreen\")  \n",
    "mtext(\"Line 2\", side=3, line=2, adj=1.0, cex=1, col=\"forestgreen\")  \n",
    "mtext(\"Line 3\", side=3, line=3, adj=1.0, cex=1, col=\"forestgreen\")  \n",
    "box(\"figure\", col=\"forestgreen\")  \n",
    "\n",
    "# Label the outer margin area and color it blue  \n",
    "# Note the 'outer=TRUE' command moves us from the figure margins to the outer margins.  \n",
    "mtext(\"Outer Margin Area\", side=1, line=1, cex=2, col=\"blue\", outer=TRUE)  \n",
    "mtext(\"par(oma=c(b,l,t,r))\", side=1, line=2, cex=1, col=\"blue\", outer=TRUE)  \n",
    "mtext(\"Line 0\", side=1, line=0, adj=0.0, cex=1, col=\"blue\", outer=TRUE)  \n",
    "mtext(\"Line 1\", side=1, line=1, adj=0.0, cex=1, col=\"blue\", outer=TRUE)  \n",
    "mtext(\"Line 2\", side=1, line=2, adj=0.0, cex=1, col=\"blue\", outer=TRUE)  \n",
    "box(\"outer\", col=\"blue\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CJCIkFIESGRIKSIkEgQUkRIJAgpIiQS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\nSFCAkKCARUjAJxMSFPD/nSZG5QH2JgcAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ----- plot region / figure region / device region -------------------------------------\n",
    "\n",
    "old_par <- par(no.readonly = TRUE)\n",
    "\n",
    "par(mar=c(5, 4, 3, 2))\t\t# margins (between plot border and figure border)\n",
    "par(oma=c(3, 3, 3, 3))\t\t# outer margins (between outer border and figure border)\n",
    "par(xpd=NA)\t\t\t\t\t# show text and arrows outside plot region\n",
    "\n",
    "par(xaxt = \"n\", yaxt = \"n\")\t# do not draw axes\n",
    "\n",
    "plot(0:10, 0:10, type=\"n\", xlab=NA, ylab=NA)\n",
    "\n",
    "box(\"plot\", col=\"red3\", lwd=2)\n",
    "text(8.5, 0.05, \"plot border\", col=\"red3\")\n",
    "\n",
    "box(\"figure\", col=\"blue4\", lwd=2)\n",
    "mtext(\"figure border\", col=\"blue4\", side=1, adj=1, line=3.6)\n",
    "\n",
    "box(\"outer\", col=\"green4\", lwd=2)\n",
    "mtext(\"outer border\", col=\"green4\", side=1, adj=1.1, line=6.6)\n",
    "\n",
    "text(5, 4.9, \"plot region\", col=\"gray50\", cex=1.5) \n",
    "arrows(-0.3, 5.5, 10.3, 5.5, code=3, col=\"gray50\", lwd=1.5, lty=3)\n",
    "\n",
    "mtext(\"figure region\", side=1, adj=0.5, line=3, col=\"gray50\", cex=1.5)\n",
    "arrows(-2.15, -1.6, 11.2, -1.6, code=3, col=\"gray50\", lwd=1.5, lty=3)\n",
    "\n",
    "mtext(\"device region\", side=1, adj=0.5, line=6.7, col=\"gray50\", cex=1.5)\n",
    "arrows(-3.6, -3.5, 12.6, -3.5, code=3, col=\"gray50\", lwd=1.5, lty=3)\n",
    "\n",
    "par(old_par)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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205IUFQGibSuCqFdNH4LIcUP02d2EBb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\nu7ZwAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ----- margins overview ----------------------------------------------------------------\n",
    "\n",
    "old_par <- par(no.readonly = TRUE)\n",
    "\n",
    "par(mar=c(5, 4, 3, 2))\t\t# margins (between plot border and figure border)\n",
    "par(oma=c(3, 3, 3, 3))\t\t# outer margins (between outer border and figure border)\n",
    "par(xpd=NA)\t\t\t\t\t# show text and arrows outside plot region\n",
    "\n",
    "par(xaxt = \"n\", yaxt = \"n\")\t# do not draw axes\n",
    "\n",
    "plot(0:10, 0:10, type=\"n\", xlab=NA, ylab=NA)\n",
    "\n",
    "box(\"plot\", col=\"red3\", lwd=2)\n",
    "text(8.5, 0.05, \"plot border\", col=\"red3\")\n",
    "\n",
    "box(\"figure\", col=\"blue4\", lwd=2)\n",
    "mtext(\"figure border\", col=\"blue4\", side=1, adj=1, line=3.6)\n",
    "\n",
    "box(\"outer\", col=\"green4\", lwd=2)\n",
    "mtext(\"outer border\", col=\"green4\", side=1, adj=1.1, line=6.6)\n",
    "\n",
    "for (s in 1:4) {\t\t\t# placement of text in margins\n",
    "\tfor (i in 0:8) {\n",
    "\t\tmtext(paste(\"line\", i), col=\"gray50\", side=s, adj=0.5, line=i)\n",
    "\t}\n",
    "}\n",
    "\n",
    "mtext(\"margin\", side=1, adj=0, line=2, col=\"gray50\", cex=1.5)\n",
    "mtext(\"outer margin\", side=1, adj=0, line=6.4, col=\"gray50\", cex=1.5)\n",
    "\n",
    "par(old_par)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AiJs3boPS9CipcTriOh17oOaTa/1ZIJ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\nERIg8H9LpoiRvqGJpwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ----- setting margins --------------------------------------------------------------\n",
    "\n",
    "old_par <- par(no.readonly = TRUE)\n",
    "\n",
    "par(mar=c(7, 5, 6, 4))\t\t\t# margins (between plot and figure borders)\n",
    "par(xpd=NA)\t\t\t\t\t\t# show text and arrows outside plot region\t\t\t\t\t\t\t\t# set axis values, axis labels, and axis to gray\n",
    "par(col.axis=\"gray50\", col.lab=\"gray50\", fg=\"gray50\") \n",
    "\n",
    "plot(0:10, 0:10, type=\"n\", xlab=\"label for x-axis\", ylab=\"label for y-axis\")\n",
    "\n",
    "box(\"plot\", col=\"red3\", lwd=2)\n",
    "text(9.1, 0.1, \"plot border\", col=\"red3\")\n",
    "\n",
    "box(\"figure\", col=\"blue4\", lwd=2)\n",
    "mtext(\"figure border\", col=\"blue4\", side=1, adj=0.8, line=5.6)\n",
    "\n",
    "box(\"outer\", col=\"green4\", lwd=2)\n",
    "mtext(\"outer border\", col=\"green4\", side=1, adj=1.15, line=5.6)\n",
    "\n",
    "\t\t\t\t\t\t\t\t\t# arrow annotations for margins\n",
    "text(0.4, -2.4, \"7 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(1, -3.7, 1, -0.5, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(0.4, 12.2, \"6 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(1, 10.5, 1, 13.25, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(-1.5, 8.8, \"5 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(-0.5, 9.2, -2.4, 9.2, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(11.2, 8.8, \"4 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(10.5, 9.2, 11.95, 9.2, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(10.5, 12.8, \"mar=c(7, 5, 6, 4)\")\n",
    "\n",
    "par(old_par)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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oQkERKUCEkiJCiFE9LkdJTWXY2PLPb6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\n3AAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ----- setting outer margins ---------------------------------------------------------\n",
    "\n",
    "\n",
    "old_par <- par(no.readonly = TRUE)\n",
    "\n",
    "par(oma=c(3.5, 2, 4, 3))\t\t\t# setting outer margins (in units of lines)\n",
    "\t\t\t\t\t\t\t\t\t# default values for margins are c(5.1, 4.1, 4.1, 2.1)\n",
    "par(xpd=NA)\t\t\t\t\t\t\t# show text and arrows outside plot region\t\t\t\t\t\t\t\t\t# set axis values, axis labels, and axis to gray\n",
    "par(col.axis=\"gray50\", col.lab=\"gray50\", fg=\"gray50\") \n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "plot(0:10, 0:10, type=\"n\", xlab=\"label for x-axis\", ylab=\"label for y-axis\")\n",
    "\n",
    "box(\"plot\", col=\"red3\", lwd=2)\n",
    "text(8.5, 0.05, \"plot border\", col=\"red3\")\n",
    "\n",
    "box(\"figure\", col=\"blue4\", lwd=2)\n",
    "mtext(\"figure border\", col=\"blue4\", side=1, adj=1, line=3.8)\n",
    "\n",
    "box(\"outer\", col=\"green4\", lwd=2)\n",
    "mtext(\"outer border\", col=\"green4\", side=1, adj=1.1, line=7.3)\n",
    "\n",
    "\t\t\t\t\t\t\t\t\t# arrow annotations for outer margins\n",
    "text(4.2, -4.5, \"3.5 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(5, -5.35, 5, -3.55, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(-3, 4.2, \"2\\nlines\", adj=0, col=\"skyblue3\", cex=0.8)\n",
    "arrows(-3.1, 5, -2.35, 5, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(4.4, 13.9, \"4 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(5, 15.1, 5, 12.9, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(12, 4.45, \"3 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(11.45, 5, 12.6, 5, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(10.7, 14.5, \"oma=c(3.5, 2, 4, 3)\")\n",
    "\n",
    "par(old_par)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BCSICRYICRBSLBASIKQYIGQBCHBAiEJ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\nIAkJgDVCAhT8P+eBzshUN01VAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ----- setting both margins and outer margins -----------------------------------------\n",
    "\n",
    "old_par <- par(no.readonly = TRUE)\n",
    "\n",
    "par(oma=c(2.5, 3, 4, 3))\t\t\t# outer margins\n",
    "par(mar=c(7, 5, 6, 5))\t\t\t\t# margins (between plot and figure borders)\n",
    "par(xpd=NA)\t\t\t\t\t\t\t# show text and arrows outside plot region\n",
    "\t\t\t\t\t\t\t\t\t# set axis values, axis labels, and axis to gray\n",
    "par(col.axis=\"gray50\", col.lab=\"gray50\", fg=\"gray50\") \n",
    "\n",
    "plot(0:10, 0:10, type=\"n\", xlab=\"label for x-axis\", ylab=\"label for y-axis\")\n",
    "\n",
    "box(\"plot\", col=\"red3\", lwd=2)\n",
    "text(8.5, 0.1, \"plot border\", col=\"red3\")\n",
    "\n",
    "box(\"figure\", col=\"blue4\", lwd=2)\n",
    "mtext(\"figure border\", col=\"blue4\", side=1, adj=1.2, line=5.7)\n",
    "\n",
    "box(\"outer\", col=\"green4\", lwd=2)\n",
    "mtext(\"outer border\", col=\"green4\", side=1, adj=1.4, line=8.3)\n",
    "\n",
    "\t\t\t\t\t\t\t\t\t# arrow annotations for outer margins\n",
    "text(4, -6.3, \"2.5 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(5, -6.9, 5, -5.5, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(4.2, 16, \"4 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(5, 14.7, 5, 17.2, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(-4.1, 4.45, \"3 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(-4.8, 5, -3.4, 5, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(14.1, 4.45, \"3 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(13.4, 5, 14.8, 5, code=3, col=\"skyblue3\", length=0.1)\n",
    "\n",
    "\t\t\t\t\t\t\t\t\t# arrow annotations for margins\n",
    "text(0.2, -3, \"7 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(1, -5.1, 1, -0.6, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(0.2, 12.5, \"6 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(1, 10.6, 1, 14.4, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(-1.8, 8.7, \"5 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(-0.5, 9.2, -3.1, 9.2, code=3, col=\"skyblue3\", length=0.1)\n",
    "text(11.8, 8.7, \"5 lines\", col=\"skyblue3\", cex=0.8)\n",
    "arrows(10.5, 9.2, 13.1, 9.2, code=3, col=\"skyblue3\", length=0.1)\n",
    "\n",
    "text(10.5, 16.2, \"oma=c(2.5, 3, 4, 3)\\nmar=c(7, 5, 6, 5)\", adj=0)\n",
    "\n",
    "par(old_par)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red; font-family:centurygothic \">Continue...</span><a href=\"http://www.melissaclarkson.com/resources/R_guides/documents/figure_layout_Ver1.R\" target=\"_blank\">http://www.melissaclarkson.com/resources/R_guides/documents/figure_layout_Ver1.R</a>  \n",
    "<a href=\"http://www.melissaclarkson.com/resources/R_guides/documents/figure_layout_Ver1.pdf\" target=\"_blank\">http://www.melissaclarkson.com/resources/R_guides/documents/figure_layout_Ver1.pdf</a>  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multifigure Layouts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qQzKE9fu5obn3N6B7q/8XeXjTs+EmrU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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfrow=c(2, 2)) # 2 × 2 array to be filled by rows\n",
    "\n",
    "plot(rnorm(10), type = \"p\")\n",
    "plot(rnorm(10), type = \"l\")\n",
    "plot(rnorm(10), type = \"b\")\n",
    "plot(rnorm(10), type = \"o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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XMUqXMNcixE9wLoQOiuPu3+Eu7JIl29bQ4XcSj8bBz1pfhwtP1E6jRJ0CIbFyMe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\nBCAAkQAEIBKAAEQCEIBIAAL+B5njnTnEzHReAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfcol = c(2, 2))  # A 2 × 2 array to be filled by columns \n",
    "plot(rnorm(10), type = \"p\")\n",
    "plot(rnorm(10), type = \"l\")\n",
    "plot(rnorm(10), type = \"b\")\n",
    "plot(rnorm(10), type = \"o\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red; font-family:Comic Sans MS\">References</span>\n",
    "\n",
    "http://research.stowers.org/mcm/efg/R/Graphics/Basics/mar-oma/index.htm  \n",
    "https://www.stat.auckland.ac.nz/~ihaka/787/  \n",
    "https://www.r-graph-gallery.com/74-margin-and-oma-cheatsheet/  \n",
    "http://www.pitt.edu/~njc23/  \n",
    "http://www.melissaclarkson.com/resources/R_guides/  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color:red; font-family:brandon\">Further  Resources</span>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "r"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "256px"
   },
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}