Propolis_R.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'mdatools' was built under R version 3.5.3\"Warning message:\n",
      "\"package 'usethis' was built under R version 3.5.3\"Warning message:\n",
      "\"package 'BiocManager' was built under R version 3.5.2\"\n",
      "Attaching package: 'BiocManager'\n",
      "\n",
      "The following object is masked from 'package:devtools':\n",
      "\n",
      "    install\n",
      "\n",
      "Loading required package: Biobase\n",
      "Loading required package: BiocGenerics\n",
      "Loading required package: parallel\n",
      "\n",
      "Attaching package: 'BiocGenerics'\n",
      "\n",
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      "    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,\n",
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      "    lengths, Map, mapply, match, mget, order, paste, pmax, pmax.int,\n",
      "    pmin, pmin.int, Position, rank, rbind, Reduce, rowMeans, rownames,\n",
      "    rowSums, sapply, setdiff, sort, table, tapply, union, unique,\n",
      "    unsplit, which, which.max, which.min\n",
      "\n",
      "Welcome to Bioconductor\n",
      "\n",
      "    Vignettes contain introductory material; view with\n",
      "    'browseVignettes()'. To cite Bioconductor, see\n",
      "    'citation(\"Biobase\")', and for packages 'citation(\"pkgname\")'.\n",
      "\n",
      "\n",
      "Attaching package: 'pcaMethods'\n",
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      "\n",
      "    pca\n",
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      "The following object is masked from 'package:stats':\n",
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      "    loadings\n",
      "\n",
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      "Attaching package: 'MetaboMate'\n",
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      "Warning message:\n",
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   ],
   "source": [
    " #12 de Marzo de 2019\n",
    "\n",
    "library(mdatools)\n",
    "library(devtools)\n",
    "library(BiocManager)\n",
    "#BiocManager::install(\"pcaMethods\", version= \"3.8\")\n",
    "library(pcaMethods)\n",
    "#devtools::install_github('kimsche/MetaboMate', build_vignettes=TRUE)\n",
    "library(MetaboMate)\n",
    "#devtools::install_github('jwist/visualizeR')\n",
    "library(car)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>123</li>\n",
       "\t<li>17</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 123\n",
       "\\item 17\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 123\n",
       "2. 17\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 123  17"
      ]
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     "metadata": {},
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    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>SampleID</th><th scope=col>SampleNMR</th><th scope=col>Date_YMD</th><th scope=col>Probe</th><th scope=col>Shims</th><th scope=col>RG</th><th scope=col>Type</th><th scope=col>Folder</th><th scope=col>Origen</th><th scope=col>Zona</th><th scope=col>Type2</th><th scope=col>Color</th><th scope=col>R</th><th scope=col>G</th><th scope=col>B</th><th scope=col>Extracto</th><th scope=col>Resinas..</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>M46           </td><td>PRO046B_PRO   </td><td>190205        </td><td>2             </td><td>              </td><td>64            </td><td>              </td><td>32            </td><td>Santander     </td><td>bh-PM         </td><td>2             </td><td>red           </td><td>115           </td><td>  2           </td><td> 0            </td><td>5,48          </td><td>ND            </td></tr>\n",
       "\t<tr><td>M47           </td><td>PRO047A_PRO   </td><td>190205        </td><td>2             </td><td>              </td><td>50,8          </td><td>              </td><td>32            </td><td>Santander     </td><td>bh-PM         </td><td>2             </td><td>reddish_yellow</td><td>246           </td><td> 99           </td><td> 1            </td><td>4,23          </td><td>65            </td></tr>\n",
       "\t<tr><td>M47           </td><td>PRO047B_PRO   </td><td>190205        </td><td>2             </td><td>              </td><td>45,2          </td><td>              </td><td>32            </td><td>Santander     </td><td>bh-PM         </td><td>2             </td><td>reddish_yellow</td><td>246           </td><td> 99           </td><td> 1            </td><td>4,23          </td><td>65            </td></tr>\n",
       "\t<tr><td>M48           </td><td>PRO048A_PRO   </td><td>190118        </td><td>2             </td><td>              </td><td>60,5          </td><td>              </td><td>32            </td><td>Casanare      </td><td>bh-T          </td><td>2             </td><td>yellow        </td><td>162           </td><td>133           </td><td>54            </td><td>7,74          </td><td>14            </td></tr>\n",
       "\t<tr><td>M25           </td><td>PRO025A_PRO   </td><td>180917        </td><td>1             </td><td>              </td><td>90,5          </td><td>              </td><td>22            </td><td>Tolima        </td><td>bh-T          </td><td>2             </td><td>light_yellow  </td><td>108           </td><td>102           </td><td>68            </td><td>3,58          </td><td>0             </td></tr>\n",
       "\t<tr><td>M44           </td><td>PRO044A_C     </td><td>190206        </td><td>2             </td><td>              </td><td>64            </td><td>C             </td><td>22            </td><td>Brasil        </td><td>BRA           </td><td>1             </td><td>red           </td><td>115           </td><td>  2           </td><td> 0            </td><td>11,51         </td><td>ND            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllll}\n",
       " SampleID & SampleNMR & Date\\_YMD & Probe & Shims & RG & Type & Folder & Origen & Zona & Type2 & Color & R & G & B & Extracto & Resinas..\\\\\n",
       "\\hline\n",
       "\t M46            & PRO046B\\_PRO  & 190205         & 2              &                & 64             &                & 32             & Santander      & bh-PM          & 2              & red            & 115            &   2            &  0             & 5,48           & ND            \\\\\n",
       "\t M47              & PRO047A\\_PRO    & 190205           & 2                &                  & 50,8             &                  & 32               & Santander        & bh-PM            & 2                & reddish\\_yellow & 246              &  99              &  1               & 4,23             & 65              \\\\\n",
       "\t M47              & PRO047B\\_PRO    & 190205           & 2                &                  & 45,2             &                  & 32               & Santander        & bh-PM            & 2                & reddish\\_yellow & 246              &  99              &  1               & 4,23             & 65              \\\\\n",
       "\t M48            & PRO048A\\_PRO  & 190118         & 2              &                & 60,5           &                & 32             & Casanare       & bh-T           & 2              & yellow         & 162            & 133            & 54             & 7,74           & 14            \\\\\n",
       "\t M25              & PRO025A\\_PRO    & 180917           & 1                &                  & 90,5             &                  & 22               & Tolima           & bh-T             & 2                & light\\_yellow   & 108              & 102              & 68               & 3,58             & 0               \\\\\n",
       "\t M44            & PRO044A\\_C    & 190206         & 2              &                & 64             & C              & 22             & Brasil         & BRA            & 1              & red            & 115            &   2            &  0             & 11,51          & ND            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "SampleID | SampleNMR | Date_YMD | Probe | Shims | RG | Type | Folder | Origen | Zona | Type2 | Color | R | G | B | Extracto | Resinas.. | \n",
       "|---|---|---|---|---|---|\n",
       "| M46            | PRO046B_PRO    | 190205         | 2              |                | 64             |                | 32             | Santander      | bh-PM          | 2              | red            | 115            |   2            |  0             | 5,48           | ND             | \n",
       "| M47            | PRO047A_PRO    | 190205         | 2              |                | 50,8           |                | 32             | Santander      | bh-PM          | 2              | reddish_yellow | 246            |  99            |  1             | 4,23           | 65             | \n",
       "| M47            | PRO047B_PRO    | 190205         | 2              |                | 45,2           |                | 32             | Santander      | bh-PM          | 2              | reddish_yellow | 246            |  99            |  1             | 4,23           | 65             | \n",
       "| M48            | PRO048A_PRO    | 190118         | 2              |                | 60,5           |                | 32             | Casanare       | bh-T           | 2              | yellow         | 162            | 133            | 54             | 7,74           | 14             | \n",
       "| M25            | PRO025A_PRO    | 180917         | 1              |                | 90,5           |                | 22             | Tolima         | bh-T           | 2              | light_yellow   | 108            | 102            | 68             | 3,58           | 0              | \n",
       "| M44            | PRO044A_C      | 190206         | 2              |                | 64             | C              | 22             | Brasil         | BRA            | 1              | red            | 115            |   2            |  0             | 11,51          | ND             | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  SampleID SampleNMR   Date_YMD Probe Shims RG   Type Folder Origen    Zona \n",
       "1 M46      PRO046B_PRO 190205   2           64        32     Santander bh-PM\n",
       "2 M47      PRO047A_PRO 190205   2           50,8      32     Santander bh-PM\n",
       "3 M47      PRO047B_PRO 190205   2           45,2      32     Santander bh-PM\n",
       "4 M48      PRO048A_PRO 190118   2           60,5      32     Casanare  bh-T \n",
       "5 M25      PRO025A_PRO 180917   1           90,5      22     Tolima    bh-T \n",
       "6 M44      PRO044A_C   190206   2           64   C    22     Brasil    BRA  \n",
       "  Type2 Color          R   G   B  Extracto Resinas..\n",
       "1 2     red            115   2  0 5,48     ND       \n",
       "2 2     reddish_yellow 246  99  1 4,23     65       \n",
       "3 2     reddish_yellow 246  99  1 4,23     65       \n",
       "4 2     yellow         162 133 54 7,74     14       \n",
       "5 2     light_yellow   108 102 68 3,58     0        \n",
       "6 1     red            115   2  0 11,51    ND       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Importing data from Github\n",
    "Metadata <-read.csv('https://raw.githubusercontent.com/davidgarciam/propolis_project/master/Propolis_data/Propoleo_metadata.csv', header= TRUE, sep= \";\")\n",
    "dim(Metadata)\n",
    "head(Metadata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>131072</li>\n",
       "\t<li>60</li>\n",
       "</ol>\n"
      ],
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       "\\begin{enumerate*}\n",
       "\\item 131072\n",
       "\\item 60\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 131072\n",
       "2. 60\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 131072     60"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>131072</li>\n",
       "\t<li>63</li>\n",
       "</ol>\n"
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      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 131072\n",
       "\\item 63\n",
       "\\end{enumerate*}\n"
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      "text/markdown": [
       "1. 131072\n",
       "2. 63\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 131072     63"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "part1 <- read.csv('https://raw.githubusercontent.com/davidgarciam/propolis_project/master/Propolis_data/part1d.csv', header= T, sep= \",\")\n",
    "dim(part1)\n",
    "part2 <- read.csv('https://raw.githubusercontent.com/davidgarciam/propolis_project/master/Propolis_data/part2d.csv', header= T, sep= \",\")\n",
    "dim(part2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>131072</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 131072\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 131072\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 131072    123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X <- cbind(part1, part2)\n",
    "dim(X)\n",
    "colnames(X) <- seq_along(X[1,])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ppm <- read.csv('https://raw.githubusercontent.com/davidgarciam/propolis_project/master/Propolis_data/ppmpro_all_center.csv', header= FALSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>123</li>\n",
       "\t<li>131072</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 123\n",
       "\\item 131072\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 123\n",
       "2. 131072\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1]    123 131072"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>123</li>\n",
       "\t<li>17</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 123\n",
       "\\item 17\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 123\n",
       "2. 17\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 123  17"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1</li>\n",
       "\t<li>131072</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1\n",
       "\\item 131072\n",
       "\\end{enumerate*}\n"
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      "text/markdown": [
       "1. 1\n",
       "2. 131072\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1]      1 131072"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_intensity <- t(X)\n",
    "ppm <- t(ppm)\n",
    "\n",
    "dim(a_intensity)\n",
    "dim(Metadata)\n",
    "dim(ppm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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MFeG1T7kMoupNrt8+3s52rW45C4REg+IiE9aF6WRQipqm7tceTaXRfQrHDsTUor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\nTfd15soAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Bad shimming \n",
    "X <- a_intensity[c(-22, -25, -33, -36, -104, -112, -113, -119),]#Eliminar espectros con shims malos\n",
    "Metadata_f <- Metadata[c(-22, -25, -33, -36, -104, -112, -113, -119),]#Eliminar espectros con shims malos\n",
    "ColorRGB <- data.frame(Metadata_f$SampleNMR, Metadata_f$R, Metadata_f$G, Metadata_f$B)\n",
    "\n",
    "matspec(ppm, X, shift= range(ppm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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d+u2q219wt3PS5CkkVIzdcx+0i9QeFCKmchdQlJFiE1X9eE1B8UZRXSq+eDPLMX\nbWAnSRIhNZ3ZReramd2LV+1N88d2+ap6QhIhiSKkpqsOI5ldpHZ7rbQh7Rc8s08eITVd9SyK\nwaC4DGnAM/vEEVLTzULauQjplQmJLZI0Qmq62dRuHtJam5A0EFLjbdvFhn518nd1IMmdtUpI\nogip+YZ7+eDD9ZDYR5JGSI33V7OPNHhtzxCyf1pr2wtycbKdNEJqutmzKOYhle3nbmqXEJIo\nQmq6pFs9HenV5kVI9glJ/b0Xv9X8yBqFkBousWcI5QMT0vN5SINi4J7ZR0iCCKnhqpA2zdTO\nrX7bA0mDnYF7HgUhCSKkhnMXLHb7SBchFYQkj5Aar7ryd9GuZnY2pNkTkthJEkRITbftno60\nfxnSpgupN/ovQhJESE23Pezay0POjsfakJ7bVTsbUr0PrFkIqeGS62cI2amdDcmdI/QbmyQx\nhNRw1SX0W5ch2QNJefU8CkKSQ0jNlrgbX25tDtrPr4Rkn5DU3XtREpIYQmq2pNxOTEj9waur\nIdkbu/QTQhJESM1mQqpOtSs2r4Y0P5BESVIIqemyYXXl73lHLqScc4SEEVLTdUxIPXtiw/wN\n7c1i34bUJyRBhNR0yTBPe/0X10Lamd3YhWU7MYTUbEmZ7V07Q6g62c6FZE9toCQhhNRsybYL\n6cphJBvSfp7mw9E65wjJIaRGS9wZQvamLtXq93ZZnWw3yExInLUqiJAarQppqz8LafugdE9I\nqkLqM7WTQ0iNlpR/zQZ50ZsdRjqwJbXL54MtE5K7agMhCSGkpstSG5K7YsOB2yatzU62S9wF\nuShJBiE13HZ1GMmtNVQh2Z0kdxn9fqdkbieFkBpudjy2cLtI5d5stSGvzhH6mZCkEFKjJX/N\nhnk2P0Noe8+90ewkzY7I/kxGUgip0ZLSrjX0qxMbDlxHB9WBJHuyXf9vhCSFkJrMrn4P8nSz\n/2oe0vYsJDu16/ZfsJMkhZCarAopq47HHtj9I/PrYHZBruEoISQxhNRk9qJ2F4eRroW0dRES\nRBBSs1XPRroMyc7tZle2s6c2EJIUQmq27YvV772D6g12uaFwB5KS/rufSw7JyiCkRvtrYq8O\nuWNCmnVUhbQ5sAeSkqRDSFIIqckSd6adu/KJCWk2tSsP9p4PtqoDSX9jtUEIITVZ4tYa7AlC\n1YkNsxd7ReFCqta/KUkCITVY4naR7Or3ZUhWe6+6jlDXnW1HSBIIqcGSvw6Heb7Vf1HszRft\nnIO9Tbv+3Rsl/Z/JSAYhNZndRTJTuxd77bWD+QbJrTYMTEh2J6lfskmSQUhNtm1CSt1Nxsrr\nIRU77okUey8ISQghNdn2MLX3RrKHka6G1D4wIQ3sdfQ7TO2EEFJz2ROE0tlhpIOLt16ElOWd\nJHlX4+NrFEJqrmTbhmTPtGtfD8nO7b7J3WUbOu5tbJWWRkjNldgrCGXFbGZ3ZWpnN0kmJDO3\n63besZMkgpAay87s9vJs866QymKnekpSFRIlLY2QGqsKKTW7SNcOx1Yhbe5suZCS/2DdTgQh\nNdXe3vYwyc0ukl39PrhyXkNZrTa0q+f2zTZJWBIhNdPenn0ukr3wyU7/yszuafVeE1LxxHcs\nrzUAAA1dSURBVN2Ruc/cTobXkD4djyNrfPRJawhcqha/+6+qxW8b0tOn1Str7YOdvbw6t4G5\nnQiPIU1b0aVMZQhYe+5qQUk5MCGlW9dndk/nIQ32cuZ2gjyGdBTFp2futfNJHB1pDIF5Rraj\n7jBPiw+3dpFm6987+X6W5h0bEpbnMaQ4Ort4/SyKNYYI3SwiK8kGw9zuIg3axexo7GwHaR7S\nnj1LqOP2kkrmdsvyGFIU3fcHsSHCdiUju/ZtNkij1J1odzWkp7P174Odb7YGV5YbCGk5bJEa\nYu/6H5NBx22QNmeX/b6Y2lUhrdlN0pa9U8Uo2StZt1ue332kybl7jX0kaXt7N98ycBukojXr\nyOTzdP4ut9pQFjtP9s3cLrU3pWCTtDSfy9/ZlVW71lRliEDdyqjMOt00z/qb85ndlY5mIT0v\nnuSDD6m7u/k7NknL8nsc6cgdR4rHxxxH0pVtd+wGaet1/4U7GnslpOp3N7fL9+Yr4ES0LM5s\naKJku+zasxo+9AdltdSwfbFBuhLSv+cfMzu567I5Whohrbzbu0eDzHY0yop/Dl4Ua7dCqtYd\n2geDZ/v5wJSUdDssNyyLU4RW3e2O7MQuyXtpf7M/P4h09YzVp/OQiuLftz4OM7MrNZvcUdLX\n4xShFXezo8HAZNPp5nmW9l4PXrTX7glpzW6SivbWP4c9O7nj9IYlcYrQarvRkckoy7bLTmqX\nvj/0b53VUHFHksryoBjs7OfDbJBno0WbpA2Fx904HJBdUdntbfrAbo3sSQ2ddFgdi20X5X0h\nuZLKYv+1KclskqpT7u4MaYOSPgOnCK0iU1Gns3Gtpaoi8ybTkV2xS7deD/ZnB2OvzewudpJM\nSUW7eLaVu8ld1rlnk7Rhh1L5LBqFLdLqsf1s/PnnbmcwyAZzZbWRSkxHSZ73il5/50W7uL2H\nVF6u25Xl5kF7sPWq2iaN3BWFbpXUzXKzv6X7CTUBpwitHPtTbVrJ89RUc/EjPts8bXfSNM9H\ntqNBe7bScGXt+6bnB+2ieL3ZN7Wk6e3ZYpYliWkszbPb507gGk4RWjGZncUl+V5rODQ/+8mu\nK2iWQNLpdNJqwa4/GGwW93d0MbnbPDgYDF59zHtuo5QOsuxim2Tnj0k3H422t0d5mu36+OxW\nF6cIrRY7l+vY+79m2WiUd9PO7Of71atXZvvklhnsvO63Qdt0VN4T0sXczpb0/OCgeL1n/lXu\nUjKbucwMYrdFSZqO3IbKMCX5+yRXEWc2rIZqu2P3hRK3legZ7poLXfOTn5hNUWoluekotet1\nbp3h3g2SKelim1RuFvvFwV7frjmYSaFtyeqaj2wmiVmvX/T79iOPElJagJAeofls7fLXxYJC\nYn+mc/PTXdgrbZkf/VHiCup0bGBGUfRe9wdFsXbR0V0jPL0yuzMlFfsHxjC3H9DF5Nhx+r1i\naD7mhzStSrpj1R2W/5AWL3yLDCHo8mfn9k+33q8LV9bkSrsPZLYUmZm6FflgWAyHJiazBbLT\nPDv5chWlZufIbo7WDuabo7sXGp5eFmbnd6alweDgIM8Pqg2TM7QfcKcwTEt9u4aRpgM763vg\nQQfpkYbk86d24a/q8fj+Obm6qF2mqZmHuemW3eqMbEVmi9Numx9w83ueuh9687upaOAqKsoq\no+3t7Ts3R5WnF39hbc209NzFZCZ5lWL+ysH+/kHbfMwiH9qURmkyGLgHUz3A9xeybP7rEXzb\n/P96pCEtN4S61P6yqj9d/eON36t9l05nVsLs7Z3ZPs38/eXsz4PZD+n8/Z0nT1K3D5Qku9t2\nq2PDMfXs77fXzK/2/r6LKU0L91NtNx7FmqmoyujpPVujmafzmKo/mpyeV33OPpD9bW9vb9N9\nQNeW3UbZZffMbgOT5NpDvnzou/d8KS5/L+dfuLv/kvz3y4PHGVKaPpn/KM2+L53d3Ws/Yk92\nZ7/f/HvzP8/+/vzvXfw7kY/b6Zi/537ZN5u/++SJfbWza37LnnQy+2qW2V/GkyfVL/fDl2W7\niXt1d7f64+ytt19dr151E7b5L/fTfXCwvT3fXKy15689v9iEbLsNzeKI5lxrT7dn1sx0b83a\n3CzNr7W1bRfanrXWvhjKTAAP7DbwwmiUpdVuVff6p2LngfbVwfVPsFoITNPMfcHsF2u3+mW+\nmtUXtvoePHnge/fkxvfuyQPfO9WP+xUlfPk/ufinFxb/vcuJxeVreeH+aMxeujdUr1/+oJnf\nq19XP4B5g3mRX/zdi/fl7uPaD2jfN/toNz6A/bFxH8K9+fpjch/gxuP83Nfyz/y3+ejibVU/\nT+0ynAtgXkA1SbPcWx/YEt1p9q9mH/Hpxe/VW6/WtrlXFLNHN/zML0S+xBfsc//t5/y9vFj6\n41Y/ZPO/NP9Jsa98RQ1f/k8u/umCkK4crY3S+9jHX708MHu+9v+Bl2+4/tr8/5azfzUcphfv\nvPUhr/92x99xb+92L97e2h8Oh/v779/v7797t78/fGP+e7O/b96z/+7t63fv/vH2rXnLi+q9\nr83vr//y/ev/aX4cv//+6V/+8v1fXv+lNL8uf0ifPvDqKrj1yN+/v/wk3r//jM/yxqtv3155\n6y/W06e/zP/Cm/81fPp0OPP3vw9//OGHH3/8eX//j7dv/3j58offf3/9+vc//vhP887/fPnm\nzYs//nhptqrm+/fafOf23K99+x1z/9x9S+e/3/5Duj8f5+IHsPpLB8Pqx8W85+Dg4OGv0E3s\nI+Hz2DWI+cume5z7SITUGCFEZBESIICQAAGcIgQIICRAgPeQJmM7txufKw4BeOc7pKw6iBTF\nC0siJKwYzyGdRNnUhnQSHWoNAdTAc0hxNK2W7biKEBrFc0huWkdIaBzPIbVmW6SzqKU1BFCD\nevaRJnF0ojUEUAPfq3ZjLqKPJqrlOFI0PtUcAvCOMxsAAYQECOCOfYAA7tgHCOCOfYAA7o8E\nCOCOfYCAR7pFAlbMlwfh4Y59aure1DF+2ONf4+GOfWrq/kIyftjjX+Phjn1q6v5CMn7Y41/z\nqB7MF6r7sTN+2ONf86gezBeq+7EzftjjX/OoHswXqvuxM37Y41/zqB7MF6r7sTN+2ONf86ge\nzBeq+7EzftjjX/OoHswXqvuxM37Y41/zqB7MF6r7sTN+2ONf86gezBeq+7EzftjjX/OoHswX\nqvuxM37Y41/zqB4MsKoICRBASIAAQgIEEBIggJAAAYQECCAkQAAhAQIICRBASIAAQgIEEBIg\ngJAAAYQECCAkQMCKhXQUR/HR9N43fNL+dBaNf9K68T6PY996n+fxtT/3h8YvPXzvF1utkKoL\njrfue8M0Vv50Fo1/5F6N1X6aFo19632ex9f+3B8av/TwvX/ASoX0KYrPyrM4+nTPG8Zfcz8O\nofHPokPzc3QSHdYw9q33eR5f+3N/aHxL+3v/kJUK6SiamJen0fHdbzj9qhvbCI0/roZWewSL\nxr71Ps/ja3/uD41fevjeP2SlQhpH9pZMZ9H4zjecR5nyF3Px+I7aI1g09u2H4Xf8GdWvft3f\n+4esVEjRzf/zXXtDFp0rfzEXj29NH7jDu87Yt97nefyK3uf+8Pj63/uHNCek4+hU90fpc36Y\nTtx8w/fYjyMkvc/9wfE9fO8f0piQ3Da+7pDOY7XZ1aMPSfFzf2h8H9/7hzQmpJZdfK05pGms\nN7l57CFpfu4Pje/je/+QlQhpfqfp+OYX8/INh25eofTF/IzxnUzxSM6isW+9z/P4lubn/sD4\nqt/7z7VSIVULNec3V27sG5a5s7vE+Pa3VnauMPhdQ914w633eR5f+3N/YHzV7/3nWomQ5o7d\n/3om0dHtN3j5Yi4Y375UndssGvvW+zyPr/25PzA+IX2ph45ua2/eF41/rvyz9JjPbND+3B8a\n32Fq9wVa7v877rtWfd2uvOHyjbWMf6j9f8VFn/uNL4Pv8dU/9wfGLy/fWJvVCmnqTvh1r1Zf\ntytvuHxjLeOrTy8Wfe43vgy+x/cytar7e/+A1QoJeKQICRBASIAAQgIEEBIggJAAAYQECCAk\nQAAhAQIICRBASIAAQgIEEBIggJAAAYQECCAkQAAhAQIICRBASIAAQgIEEBIggJAAAYQECCAk\nQAAhAQIICRBASIAAQgIEEBIggJAAAYQECCAkQAAhAQIICRBASIAAQgIEEBIggJBWRRSVRxd3\nEb/66nEUH5fmDZHybc2xCCGtiig6jozszlcnmX1JSfUhpFURRfFZeRZHpzdezablyexlXPdj\nDBghrQqz2TEvJ9H4xquf3PvO3ct6H2HQ+Nqvilkm9rdbr159iVrwtV8VhPSo8bVfFYT0qPG1\nXxXV3tAkOrzxavW+y5eoBV/7VTFfqpvceLV63+VL1IKv/aqIInesaHzz1bIkpEeAr/2qMJmM\no9bJ7VdLQnoE+NqviiuZUMzjw7dkVRDSo8a3ZFUQ0qPGt2RVENKjxrcEEEBIgABCAgQQEiCA\nkAABhAQIICRAACEBAggJEEBIgABCAgQQEiCAkAABhAQIICRAACEBAggJEEBIgABCAgQQEiCA\nkAABhAQIICRAACEBAggJEEBIgABCAgT8f78yiuWoWseXAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Spectra Calibration\n",
    "X.cali=calibration(X, ppm, type='Urine')\n",
    "        \n",
    "#Visualization\n",
    "Gray <- gray.colors(115, start=0.1, end=0.5, gamma=2.2, alpha=NULL)\n",
    "\n",
    "matplot(t(ppm),t(X.cali), type=(\"l\"), xlim = c(-0.05,0.05), ylim=c(-1e4, 1e7), xlab=\"ppm\", ylab=\"Intensity\", col=Gray)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mDQAfaCDklkUv2TV4kKq/gIaf6ZcGNfMMOO7Bb+7p5W78WGKAoLhBbSe9Su+2BC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\nEBIggJAAAYQECCAkQAAhAQL+AwvrNNIhhmGFAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Indexing of chemical shifts regions\n",
    "\n",
    "idx.TMS= get.idx(range=c(min(ppm),0.5), ppm)\n",
    "idx.meoh1= get.idx(range=c(3.15,3.29), ppm)\n",
    "idx.meoh2= get.idx(range=c(3.32,3.38), ppm)\n",
    "idx.meoh3= get.idx(range=c(3.51,3.54), ppm)\n",
    "idx.water= get.idx(range=c(4.84,4.94), ppm)\n",
    "idx.noise= get.idx(range=c(14,max(ppm)), ppm)\n",
    "\n",
    "#Excision of undesired regions\n",
    "\n",
    "X.cali=X.cali[,-c(idx.TMS, idx.meoh1, idx.meoh2, idx.meoh3, idx.water, idx.noise)]\n",
    "ppm.ex=ppm[-c(idx.TMS, idx.meoh1, idx.meoh2, idx.meoh3, idx.water, idx.noise)]\n",
    "\n",
    "#Baseline correction\n",
    "\n",
    "X.bl=bline(X.cali)\n",
    "\n",
    "#Spectral normalisation\n",
    "\n",
    "X.pqn= pqn(X.bl, add.DilF = 'dilF.pqn')\n",
    "X.ta= totalArea(X.bl, add.DilF = 'dilF.ta')\n",
    "\n",
    "plot(log10(dilF.pqn), log10(dilF.ta), xlab='PQN Dilution Factor', ylab='Total Area (scaled)')\n",
    "abline(a = c(0,1), col='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualisation\n",
    "\n",
    "matspec(ppm.ex, X.pqn[1:10,], shift = c(1,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iterations: 19\n",
      "iterations: 49\n",
      "[1] 115   2\n",
      "[1] 83970     2\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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szpWvlMKY0JJCYCaWkgjciFmQnG8BiFPnO6Wj5TSmMCiYlASgdppibS5QEpbOZ0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\nRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#PCA\n",
    "\n",
    "ID= Metadata_f$SampleID\n",
    "\n",
    "pca.model=pca(X=X.pqn, pc=2, scale='UV', center=TRUE)\n",
    "\n",
    "plotscores(model=pca.model, pc=c(1,2), an=list(Color=Metadata_f$Color,Timepoint=as.character(Metadata_f$Probe),ID=ID), title='PCA - Scores plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xYDkUTqMbWKtWa8WRDvI01M39AV59tvv41TJGcQSRJEGk/f0PXoX//1X7+NWaR3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\ng0FzhgNrAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotscores(model=pca.model, pc=c(1,2), an=list(Color=Metadata_f$Color,Probe=as.character(Metadata_f$Probe)), title='PCA - Scores plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KapGSBSmkHRRSKcj2QmiZoRkZ4+e/bsqVmkrHNj0gEiMbNakQhnyJpJIscsUulR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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotscores(model=pca.model, pc=c(1,2), an=list(Location=Metadata_f$Origen,Probe=as.character(Metadata_f$Probe)), title='PCA - Scores plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xscPEIkUSxF2r+YD5VI9Y3i6l+KW5eTr9TsvdverJ2/SK6sXKSo95EOL6f0aLdK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\nmRGWHMiWAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotscores(model=pca.model, pc=c(1,2), an=list(Zone=Metadata_f$Zona,Probe=as.character(Metadata_f$Probe)), title='PCA - Scores plot')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (grepl(\"stat|recon\", type, ignore.case = T)) {:\n",
      "\"la condición tiene longitud > 1 y sólo el primer elemento será usado\""
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0a9dv6x6g+V7ft7y/hziw++ZNXTVFV/pKzw09r2r+9IzaNPm1/9a7323sZZD7vq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zwxe/xUqwEAFGvLOXZTJ8OtknGLVlljUwAAASQLu9ne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\ncRrPGpDDYcgAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotload(pca.model, X.pqn, ppm.ex, pc=2, shift=c(1,9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OPLS-DA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparing data ... done.\n",
      "Performing OPLS-DA ... [1] 0\n",
      "done.\n",
      "A model with 1 predictive and 1 orthogonal component(s) was fitted.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call.graphics(C_text, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\"Warning message in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, :\n",
      "\"font family not found in Windows font database\""
     ]
    },
    {
     "data": {
      "image/png": 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iOBBNIQSGcCKQykoYtuNjQHI7yPBBJI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\nssyrDeakAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "###OPLS con Metabomate\n",
    "\n",
    "Origen=as.character(Metadata_f$Type2)\n",
    "propoleo.oplsmet<- MetaboMate::opls(X.pqn,Origen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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UQ7kRz0nQSXIklMQiQRrUSyarsnF0mg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\npBGiGn3o8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kokKDYRHJcY5i35XiVaTi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\nTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#OPLS Scores plot\n",
    "plotscores(model=propoleo.oplsmet, pc=c(1,2), an=list(\n",
    "  Type=Origen),          # colouring according to color type 1:red 2:other\n",
    "  title='OPLS - Scores plot',     # plot title\n",
    "  cv.scores = T)                  # visualise cross-validated scores\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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V5EREREGoQCOxERkYqMfa3YGhjdqKUa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\nAERCsAMAiIRgBwAQif8PDAmE8r9Q++0AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotload(propoleo.oplsmet, X.pqn, ppm.ex, type='Reconstruction', title = 'OPLS Loadings - Statistical Reconstruction', shift=c(0.5,8.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uawZK2918vOZ/5BE1c073qnbevU2Emydq40bswZp7ou3xo7a41kjWGZoqrW2lpv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Wx4YWE0iMS+vUH0/uyDEufWc2qPIgfd47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\n8m8hVJ+1PdA1cauQM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lj9qFM6s/bI79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\nQ20XlRXRFdYNY6u+YQgbkQ2/f0qR8ndcxKnUx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Gkuhza+MTS9lt7dMzixyMQAq3xZ3LfwlQe+SniWzZgHvc4CrX2oyXzY4k5ozCWeqBsk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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Overlayed Spectra with Backscaled Loadings\n",
    "specload1(model=propoleo.oplsmet, X=X.pqn, ppm=ppm.ex, shift=c(7.1,7.45), an=list(\n",
    "  facet='All Spectra', \n",
    "  Type=Origen), \n",
    "  type='backscaled', alp = 0.2, title = 'Overlayed Spectra with Backscaled Loadings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'ropls' was built under R version 3.5.2\"\n",
      "Attaching package: 'ropls'\n",
      "\n",
      "The following object is masked from 'package:MetaboMate':\n",
      "\n",
      "    opls\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPLS-DA\n",
      "115 samples x 83970 variables and 1 response\n",
      "standard scaling of predictors and response(s)\n",
      "      R2X(cum) R2Y(cum) Q2(cum)  RMSEE pre ort pR2Y  pQ2\n",
      "Total    0.375    0.996   0.975 0.0247   1   4 0.05 0.05\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"'permI' set to 0 because train/test partition is selected\""
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPLS-DA\n",
      "58 samples x 83970 variables and 1 response\n",
      "standard scaling of predictors and response(s)\n",
      "      R2X(cum) R2Y(cum) Q2(cum)  RMSEE  RMSEP pre ort\n",
      "Total    0.399    0.997   0.821 0.0207 0.0431   1   4\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "   \n",
       "     1  2\n",
       "  1 10  0\n",
       "  2  0 48"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "   \n",
       "     1  2\n",
       "  1  9  0\n",
       "  2  0 48"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "###OPLS con ropls\n",
    "\n",
    "library(ropls)\n",
    "\n",
    "propoleo.opls <- ropls::opls(X.pqn,Origen,predI=1,orthoI=NA)\n",
    "\n",
    "#Training\n",
    "propoleo.opls1 <- ropls::opls(X.pqn,Origen,predI=1,orthoI=NA, subset=\"odd\")\n",
    "\n",
    "#Predictions on the training subset\n",
    "\n",
    "trainVi <- getSubsetVi(propoleo.opls1)\n",
    "table(Origen[trainVi], fitted(propoleo.opls1))\n",
    "\n",
    "#Predictions on the test subset\n",
    "\n",
    "table(Origen[-trainVi],\n",
    "      predict(propoleo.opls1, X.pqn[-trainVi, ]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Colombian red propolis vs Brazilian red propolis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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E/sWz6/2YurP+MhVudItngFZ+Hnq3Jo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\nDBASYICQAAOEBBggJMDAf8HTMOco5NluAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Data subsetting\n",
    "red_propolis <- subset(X, Metadata_f$Color==\"red\")\n",
    "\n",
    "red_propolis <- red_propolis[c(-1),]\n",
    "\n",
    "Metadata_red <- subset(Metadata_f, Metadata_f$Color==\"red\")\n",
    "\n",
    "Metadata_red <- Metadata_red[c(-1),]\n",
    "\n",
    "matspec(ppm, red_propolis, shift= range(ppm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RCeukXq+ZnXNzJhkNBr6haZab2qnxjL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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Calibration\n",
    "\n",
    "red_propolis.cali = calibration(red_propolis, ppm, type='Urine')\n",
    "\n",
    "Gray <- gray.colors(20, start=0.1, end=0.5, gamma=2.2, alpha=NULL)\n",
    "\n",
    "matplot(t(ppm),t(red_propolis.cali), type=(\"l\"), xlim = c(-0.05,0.05), ylim=c(-1e4, 1e7), xlab=\"ppm\", ylab=\"Intensity\", col=Gray)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Excision of undesired regions\n",
    "\n",
    "red_propolis.cali=red_propolis.cali[,-c(idx.TMS, idx.meoh1, idx.meoh2, idx.meoh3, idx.water, idx.noise)]\n",
    "\n",
    "#Baseline correction\n",
    "\n",
    "red_propolis.bl=bline(red_propolis.cali)\n",
    "\n",
    "#Spectral normalisation\n",
    "\n",
    "red_propolis.pqn= pqn(red_propolis.bl, add.DilF = 'dilF.pqn')\n",
    "red_propolis.ta= totalArea(red_propolis.bl, add.DilF = 'dilF.ta')\n",
    "\n",
    "plot(log10(dilF.pqn), log10(dilF.ta), xlab='PQN Dilution Factor', ylab='Total Area (scaled)')\n",
    "abline(a = c(0,1), col='red')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VgCVEEklYjBEqAKKxtmRj43rP6Gn9Aj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\nrkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualisation\n",
    "\n",
    "matspec(ppm.ex, red_propolis.pqn[1:10,], shift = c(0,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "iterations: 43\n",
      "iterations: 19\n",
      "[1] 19  2\n",
      "[1] 83970     2\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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fMQSSMvXiTP81URKXceImnk5REJMvI79xWAjqR7pM8c/8RY/xeUPZJCnmuhEclO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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#PCA\n",
    "\n",
    "pca.model.red=pca(X=red_propolis.pqn, pc=2, scale='UV', center=TRUE)\n",
    "\n",
    "plotscores(model=pca.model.red, pc=c(1,2), an=list(Tipo=Metadata_red$Origen), title='PCA - Scores plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (grepl(\"stat|recon\", type, ignore.case = T)) {:\n",
      "\"la condición tiene longitud > 1 y sólo el primer elemento será usado\""
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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K+wf40k7fpbrVa3Bl8Nu7euVN1Vx1D9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\nAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotload(pca.model.red, red_propolis.pqn, ppm.ex, pc=2, shift=c(1,9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in if (grepl(\"stat|recon\", type, ignore.case = T)) {:\n",
      "\"la condición tiene longitud > 1 y sólo el primer elemento será usado\""
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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D2qKC+xsT/jaAhJUcwSQMRDMa96zbsN7OYOAMBspt+jfF/ykfv5UVVGm2wP1nGi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p9aGPWl944YUQwqlTp5YvPHPmzMaNG3fs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\nIgQ7AIBECHYAAIkQ7AAAEvH/Aw448OeodDKIAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotload(pca.model.red, red_propolis.pqn, ppm.ex, pc=2, shift=c(6.5,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rQpSvoKMijL7ntFbfXSgA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\nNKmzrSAImzdvbsaayS17DCx2tLi0TrvkcrlKdi0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TAdrZbBZ+RkzASCl1uVzUUWsOmiMdPHhwfHwcjbh5654AACAASURBVDEIIdQ8EA6H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\nI8OB6dG9Tqs6cvZiAu8zrB/VsbqsSKiO1cU7gjBFvNVMiV3iqs0rBvo0b49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zzvXzUJ/NRQXzaLd1RN7zANzWemTyfzEy8cnq2l56K63t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\nKOwAABLxLzi96dP5NhyzAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "specload(pca.model.red, red_propolis.pqn, ppm.ex, shift=c(6.0,7.0), an= list(type='Stat', alp = 0.2, title = 'Overlayed Spectra with Backscaled Loadings'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPLS-DA\n",
      "19 samples x 83970 variables and 1 response\n",
      "standard scaling of predictors and response(s)\n",
      "      R2X(cum) R2Y(cum) Q2(cum)  RMSEE pre ort pR2Y  pQ2\n",
      "Total    0.264    0.995   0.909 0.0351   1   1 0.05 0.05\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"'permI' set to 0 because train/test partition is selected\""
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPLS-DA\n",
      "10 samples x 83970 variables and 1 response\n",
      "standard scaling of predictors and response(s)\n",
      "      R2X(cum) R2Y(cum) Q2(cum)  RMSEE RMSEP pre ort\n",
      "Total    0.324    0.996     0.8 0.0324 0.118   1   1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "     \n",
       "      BRA BST\n",
       "  BRA   3   0\n",
       "  BST   0   7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "     \n",
       "      BRA BST\n",
       "  BRA   2   0\n",
       "  BST   0   7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#OPLS\n",
    "\n",
    "Origen.red= as.character(Metadata_red$Zona)\n",
    "\n",
    "red.prop.opls <- opls(red_propolis.pqn,Origen.red,predI=1,orthoI=NA)\n",
    "\n",
    "#Training\n",
    "\n",
    "red.prop.opls1 <- opls(red_propolis.pqn,Origen.red,predI=1,orthoI=NA, subset=\"odd\")\n",
    "\n",
    "#Predictions on the training subset\n",
    "\n",
    "trainVi2 <- getSubsetVi(red.prop.opls1)\n",
    "table(Origen.red[trainVi2], fitted(red.prop.opls1))\n",
    "\n",
    "#Predictions on the test subset\n",
    "\n",
    "table(Origen.red[-trainVi2],\n",
    "      predict(red.prop.opls1, red_propolis.pqn[-trainVi2, ]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}