03-minimal.ipynb

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   "source": [
    "### Notebook index\n",
    "\n",
    "[3 Minimal examples](03-minimal.ipynb)  \n",
    "[4 Plotting chromosomes](04-plotting.ipynb)   \n",
    "[5 Multiple OTUs](05-multiple.ipynb)    \n",
    "[6 Changing units](06-units.ipynb)  \n",
    "[7 GISH](07-gish.ipynb)  \n",
    "[8 Groups](08-groups.ipynb)  \n",
    "[9 Circular Plots](09-circular.ipynb)  \n",
    "[10 Plotting alongside phylogeny](10-phylogeny.ipynb)  \n",
    "[11 Citrus](11-citrushelp.ipynb)  \n",
    "[12 Human Karyotype](12-human.ipynb)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1c43233",
   "metadata": {},
   "source": [
    "# Minimal examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3729a054-36df-4968-8b4b-20ecc34b3e4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# General jupyter instructions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "54627046-3d2d-40f7-a51e-c66d6e431701",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# press Ctrl + Enter to RUN active cell\n",
    "\n",
    "# SHOW keyboard shortcuts Ctrl + M then H (only jupyter notebooks and colab)\n",
    "\n",
    "# Ctrl + D (or X) DELETE a line of code\n",
    "\n",
    "# press Ctrl + M to escape from cell (opposite to ENTER)\n",
    "\n",
    "# then !\n",
    "# B to ADD cell below or A above\n",
    "# M to turn code cell into MARKDOWN\n",
    "# Y turn markdown to CODE\n",
    "# O to toggle OUTPUT\n",
    "# D D to DELETE cell\n",
    "\n",
    "# If in jupyter-lab:\n",
    "# collapse cell clicking in the blue left bar\n",
    "# use the settings menu to use the dark theme\n",
    "\n",
    "# if in colab:\n",
    "# remove bar at 80 in tools, preferences, 80 -> 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86d10cf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# to run 1 time in a common R session (not here)\n",
    "install.packages(\"IRkernel\")\n",
    "IRkernel::installspec()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2d52ffe4-d948-4671-98b9-05647521e63f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "version 2.0.6 See help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# install if missing\n",
    "if (system.file(package = \"idiogramFISH\") == '') {\n",
    "  install.packages(\"idiogramFISH\")\n",
    "}\n",
    "library(idiogramFISH)"
   ]
  },
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   "cell_type": "markdown",
   "id": "ecfc3afb-00a2-410d-8e6a-c884ec9e4e05",
   "metadata": {},
   "source": [
    "## Monocentrics\n",
    "\n",
    "Define your plotting window size with something like `par(pin=c(10,6))`, or with `svg()`, `png()`, etc.\n",
    "Add chromosome morphology according to [Guerra](https://ferroao.gitlab.io/guerra1986/Guerra1986.pdf) [-@Guerra1986d] or [@Levan1964]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7621a6c7",
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   "outputs": [
    {
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YW9Fy500GjaUgQAQHAHAFkK+/zzFjO3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\nDPx/nfKNYNNeYfUAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 300,
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data(dfOfChrSize) # chromosome data\n",
    "data(dfMarkColor) # mark general data\n",
    "data(dfOfMarks2)  # mark position data (inc. cen.)\n",
    "\n",
    "# column Mbp not for plotting purposes\n",
    "dfOfChrSize$Mbp<-(dfOfChrSize$shortArmSize+dfOfChrSize$longArmSize)*100\n",
    "\n",
    "# svg(\"dfOfChrSize.svg\", width=10, height=6 )\n",
    "# png(\"dfOfChrSize.png\", width=500, height=400)\n",
    "options(repr.plot.width = 10, repr.plot.height = 6, repr.plot.res = 100)\n",
    "\n",
    "suppressMessages(\n",
    "plotIdiograms(dfChrSize  =dfOfChrSize,  # data.frame of chr. size\n",
    "              dfMarkColor=dfMarkColor,  # d.f of mark style <- Optional\n",
    "              dfMarkPos=dfOfMarks2,     # df of mark positions (includes cen. marks)\n",
    "              \n",
    "              karHeight=5,              # kar. height\n",
    "              chrWidth = 1.2,           # chr. width\n",
    "              chrSpacing = 1,           # space among chr.\n",
    "              \n",
    "              morpho=\"Guerra\",          # chr. morpho. classif. (Guerra, Levan, both, \"\" ) ver. >= 1.12 only\n",
    "              chrIndex=\"CI\",            # cen. pos. (CI, AR, both, \"\" ) ver. >= 1.12 only\n",
    "              chrSize = TRUE,           # add chr. sizes under chr.\n",
    "              chrSizeMbp = TRUE,        # add Mbp sizes under chr. (see above)\n",
    "              \n",
    "              rulerPos= 0,              # position of ruler\n",
    "              ruler.tck=-0.01,          # size and orientation of ruler ticks\n",
    "              rulerNumberSize=.8        # font size of rulers\n",
    "              ,xPosRulerTitle = 3             # pos of ruler title\n",
    "              \n",
    "              ,legendWidth=1            # width of legend items\n",
    "              ,fixCenBorder = TRUE      # use chrColor as border color of cen. or cen. marks\n",
    "              ,distTextChr = 1.2        # chr. text separation\n",
    "              \n",
    "              ,xlimLeftMod = 2          # xlim left param.\n",
    "              ,ylimBotMod = 0           # modify ylim bottom argument\n",
    "              ,ylimTopMod = 0           # modify ylim top argument\n",
    ")\n",
    ")\n",
    "# dev.off() # close svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3909908d",
   "metadata": {},
   "source": [
    "###  Let's explore the data.frames for monocentrics: {-}\n",
    "\n",
    "If only one species, column OTU is optional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dfa46794",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>chrName</th><th scope=col>shortArmSize</th><th scope=col>longArmSize</th><th scope=col>Mbp</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1</td><td>3</td><td>4</td><td>700</td></tr>\n",
       "\t<tr><td>2</td><td>4</td><td>5</td><td>900</td></tr>\n",
       "\t<tr><td>3</td><td>2</td><td>3</td><td>500</td></tr>\n",
       "\t<tr><td>X</td><td>1</td><td>2</td><td>300</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 4\n",
       "\\begin{tabular}{llll}\n",
       " chrName & shortArmSize & longArmSize & Mbp\\\\\n",
       " <chr> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 1 & 3 & 4 & 700\\\\\n",
       "\t 2 & 4 & 5 & 900\\\\\n",
       "\t 3 & 2 & 3 & 500\\\\\n",
       "\t X & 1 & 2 & 300\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 4\n",
       "\n",
       "| chrName &lt;chr&gt; | shortArmSize &lt;dbl&gt; | longArmSize &lt;dbl&gt; | Mbp &lt;dbl&gt; |\n",
       "|---|---|---|---|\n",
       "| 1 | 3 | 4 | 700 |\n",
       "| 2 | 4 | 5 | 900 |\n",
       "| 3 | 2 | 3 | 500 |\n",
       "| X | 1 | 2 | 300 |\n",
       "\n"
      ],
      "text/plain": [
       "  chrName shortArmSize longArmSize Mbp\n",
       "1 1       3            4           700\n",
       "2 2       4            5           900\n",
       "3 3       2            3           500\n",
       "4 X       1            2           300"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# chromosome data, if only 1 species, column OTU is optional\n",
    "dfOfChrSize\n",
    "# mark general data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1c8dbb97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>markName</th><th scope=col>markColor</th><th scope=col>style</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>5S  </td><td>red           </td><td>dots  </td></tr>\n",
       "\t<tr><td>45S </td><td>chartreuse3   </td><td>square</td></tr>\n",
       "\t<tr><td>DAPI</td><td>blue          </td><td>square</td></tr>\n",
       "\t<tr><td>CMA </td><td>darkgoldenrod1</td><td>square</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 3\n",
       "\\begin{tabular}{lll}\n",
       " markName & markColor & style\\\\\n",
       " <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t 5S   & red            & dots  \\\\\n",
       "\t 45S  & chartreuse3    & square\\\\\n",
       "\t DAPI & blue           & square\\\\\n",
       "\t CMA  & darkgoldenrod1 & square\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 3\n",
       "\n",
       "| markName &lt;chr&gt; | markColor &lt;chr&gt; | style &lt;chr&gt; |\n",
       "|---|---|---|\n",
       "| 5S   | red            | dots   |\n",
       "| 45S  | chartreuse3    | square |\n",
       "| DAPI | blue           | square |\n",
       "| CMA  | darkgoldenrod1 | square |\n",
       "\n"
      ],
      "text/plain": [
       "  markName markColor      style \n",
       "1 5S       red            dots  \n",
       "2 45S      chartreuse3    square\n",
       "3 DAPI     blue           square\n",
       "4 CMA      darkgoldenrod1 square"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mark general data\n",
    "dfMarkColor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "852b879d",
   "metadata": {},
   "source": [
    "`p, q` and `w` marks can have empty columns `markDistCen` and `markSize` since v. 1.9.1 to plot whole arms (`p`, `q`) and whole chr. `w`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "374b41cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 5</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>chrName</th><th scope=col>markName</th><th scope=col>chrRegion</th><th scope=col>markSize</th><th scope=col>markDistCen</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>5S  </td><td>p  </td><td> 1</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>45S </td><td>q  </td><td> 1</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>X</td><td>45S </td><td>p  </td><td>NA</td><td> NA</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>3</td><td>DAPI</td><td>q  </td><td> 1</td><td>1.0</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>1</td><td>DAPI</td><td>cen</td><td>NA</td><td> NA</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>X</td><td>CMA </td><td>cen</td><td>NA</td><td> NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 5\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & chrName & markName & chrRegion & markSize & markDistCen\\\\\n",
       "  & <chr> & <chr> & <chr> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 5S   & p   &  1 & 0.5\\\\\n",
       "\t2 & 1 & 45S  & q   &  1 & 0.5\\\\\n",
       "\t3 & X & 45S  & p   & NA &  NA\\\\\n",
       "\t4 & 3 & DAPI & q   &  1 & 1.0\\\\\n",
       "\t5 & 1 & DAPI & cen & NA &  NA\\\\\n",
       "\t6 & X & CMA  & cen & NA &  NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 5\n",
       "\n",
       "| <!--/--> | chrName &lt;chr&gt; | markName &lt;chr&gt; | chrRegion &lt;chr&gt; | markSize &lt;dbl&gt; | markDistCen &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|\n",
       "| 1 | 1 | 5S   | p   |  1 | 0.5 |\n",
       "| 2 | 1 | 45S  | q   |  1 | 0.5 |\n",
       "| 3 | X | 45S  | p   | NA |  NA |\n",
       "| 4 | 3 | DAPI | q   |  1 | 1.0 |\n",
       "| 5 | 1 | DAPI | cen | NA |  NA |\n",
       "| 6 | X | CMA  | cen | NA |  NA |\n",
       "\n"
      ],
      "text/plain": [
       "  chrName markName chrRegion markSize markDistCen\n",
       "1 1       5S       p          1       0.5        \n",
       "2 1       45S      q          1       0.5        \n",
       "3 X       45S      p         NA        NA        \n",
       "4 3       DAPI     q          1       1.0        \n",
       "5 1       DAPI     cen       NA        NA        \n",
       "6 X       CMA      cen       NA        NA        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mark position data (inc. cen.) \n",
    "dfOfMarks2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6cee561",
   "metadata": {},
   "source": [
    "## Holocentrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b8d4068",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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k1OTr5169apU6fCwsJKrDp27Njt27d/\n//330D/s27evhnfLENwBAABQC3Xr1m3Tpk1paWklxrdv356Xl+fn51d8sHv37g0aNNi6dWts\nbGyzZs06duxYYtWmTZssLS3T09OlP6hUKkdHx5rcLUNwBwAAQC20YMECtVo9ZsyY3NzcosHo\n6OitW7cOHTrUwuKpGGxlZRUaGrply5bY2NiwsDCFQlH8qHafTI8ePZycnIov6dev3759+0q/\nNqgmBHcAAADUQj4+PvPnz9+2bVvHjh2nT5/+1VdfDRs2bNiwYR4eHp9//nnp+QMHDty3b9/+\n/fvL2yfz+uuvlxgPCwtTq9Vbt26trufwNII7AAAAaqdJkyYdOnTIx8fnhx9+mD59+oULFz78\n8MMzZ84888wzpSf36dPH0tKyfv36L7/8colDUVFRFhYWpQN9nz59bG1ta2y3DFeVgRlRqVSf\nf/75999/f+vWLQ8Pj7fffnvy5MnF73YGAABQJZ07d96xY0d5R4suESOEsLOze/LkSfGjcXFx\n2i+WLFmyZMmS0svr169ffB9OdSO4w4xMmzbtyy+/nDhxYlBQ0MmTJ2fNmpWWllbmvxMAAIC6\nhuAOc6FSqVasWPHpp59+8sknQoihQ4dmZmauXr2a4A4AACDY4w7zkZyc3LFjx969exeNeHh4\n5Ofnq1QqE3YFAABgJjjjDnPh6elZtJNMCHH16tUNGzb07duXPe4AAACC4A4ztGPHjjfffDM7\nO/u5555bt25d6QkpKSmRkZEVF7l169arr75aPQ0CkIHHjx8/fvxYpVJJklTBNIVCYWNj06BB\ng/r16+tSVpKkx48fZ2Vl6VjZ0dHR3t6+aq0D0JE629Qd1DSCO8xOUFDQxo0bL1++vGTJkj59\n+uzfv7/ETRDc3NwWLlxYcZG9e/cWFhZWZ5sAzNTDhw9Pnz6tx8KOHTuWeYW4Iunp6WfPnq1q\nWXd396ZNm+r4wgCoIY7B4i+Zpm4CVcYed5gdV1fX0NDQiIiItWvXHjx4MD4+3tQdAZCNe/fu\n6ZfahRAnT55MTU0t7+idO3f0SO1CiLt37544caLGbqwIoBYjuMNcbN26tVu3bllZWUUjgYGB\nQogzZ86YrikAcpKRkXHlyhVDKly4cKH4b6EiDx48SEhIMKTyuXPncnJyDKkAAAR3mItGjRod\nOnRo165dRSP79u0Tf8R3AKiYJElGeZ2fkpJSuvL58+cNr3zv3j3DiwCoy9jjDnPRtWvX0NDQ\nMWPGXLlypUWLFufPn1+6dOmrr77aqVMnU7cGQAYePXpklDp37txxd3e3s7MrGsnIyDBW5Wef\nfdbW1tYo1QDUQQR3mAuFQhEdHT19+vSoqKiEhAQvL6+IiIipU6eaui8A8mCs4K4tVTy4P378\n2FiVHz9+THAHoDeCO8yItbU190kFoB+1Wm2sUgUFBcUfVnzZxyrhjnIADMEedwAAnmLEpA4A\nRkRwBwAAAGSA4A4AAADIAMEdAAAAkAGCOwAAACADBHcAAABABgjuAAAAgAwQ3AEAAAAZILgD\nRjZp0iSFQvHiiy+auhEAAFCrENwBY5IkKTo62tLSMi4u7u7duyWObtq0KSQkxNHR0cvL6733\n3ktPTy+vTlxcXI8ePRwdHTt16rRp06bypqlUqjlz5gQEBNjb2wcEBCxYsEB7X8bDhw8ryjJ4\n8GBjPVMAAFDDLE3dAFCrHD169Pbt2x9//PH8+fNjYmImTJhQdGjlypXjxo0bMGDAV199lZSU\ntHjx4lOnTh06dMjSsuQ/w99//71Hjx7du3dfunTp3r17hw4dKoQYMmRI6W83bdq0L7/8cuLE\niUFBQSdPnpw1a1ZaWtqSJUu8vLwWL15cfOaTJ08+++yzDh06VMOTBgAANYHgDhhTVFRUvXr1\npk+f/uOPP0ZFRRUFd0mSZs2aFRoaGhMTo1AohBDt27fv37//zz//3L9//xJFPv/88+bNm2/b\nts3a2nrUqFGZmZnz5s0rHdxVKtWKFSs+/fTTTz75RAgxdOjQzMzM1atXL1myxN3dffLkycUn\nT5s2rW3btlOmTKmuZw4AAKoZW2UAo5EkafPmzf369atfv/7AgQMPHz6cnJysPZSSkpKamvr6\n669rU7sQonv37kKICxculCiSm5u7ZcuWN954w9raWjvy9ttvnz17Nj4+vsTM5OTkjh079u7d\nu2jEw8MjPz9fu1umuPj4+K+//nrt2rWlz+4DAAC5ILgDRqPdJ6M9NT5w4ECNRrNlyxbtIScn\np/Pnz7/22mtFkw8dOiSE8PHxKVHk3r17arW6bdu2RSNt2rQRQly8eLHETE9Pz7i4uBdeeEH7\n8OrVqxs2bOjbt29R4i8yduzY0aNHa+sAAACZ4vQbYDRRUVH29vb9+vUTQgQHB7u5uUVFRb33\n3ntCCBsbm8DAwKKZ8fHxo0aNatWq1cCBA0sU0X6ktVGjRkUj2q8zMzPL+747dux48803s7Oz\nn3vuuXXr1pU4Gh0dffHixe3btxv69CpjKXKdNUfqSclCCIVCqniyJClUCsdUxYsqRUMdKj9x\n0RyylR4IofnjHYuKKzulWryoEg107t2MZGVZ7tvnmppqo9FU9lSFUCikxo3ze/RIbdCgoNLJ\njx5Z7d3rkpFho1brVNnVNb979/sODoU69W1m8hSZt6335SkyNEJd6WSFUNhr3J4t6G4t1deh\nckaS1V6VxSNdKgshHDTNnlW9bCXsdJkM1Jj7+Vd3319WTynL35NFHK2ahrh8YOouahTBHTAO\n7T6ZgICAvXv3akf8/f0PHDiQmprq4uJSNO3Jkyfz5s1bvHhxu3btYmJirKysStTRaDRl1rew\nKPf9saCgoI0bN16+fHnJkiV9+vTZv39/0YYcjUYzc+bM9957z9XV1aCnVxk3zb4A9fKqrvIT\nq68p375tMUAq/92/Jppf/dX/rHJl9apE5ajbFqFCVB5Szcf27e7LlrWo6qovv2wxYUJCWNid\n8l7VSJLYsqXZ11/7VbXysmUtJk260r//vaouNCFJSFdtouNtq/wzc6Le0qAnk30L+pVfWXPZ\nZtMZ25VVrXy83qLg3OleqlequhCoPtkFDw6kfWvqLgz1V7ePTd1CTSO4A8Zx7Nix27dv3759\nOzQ0tPj4li1bxo4dq/364MGDI0eOfPTo0eLFi8ePH1/mjvMmTZoIIR4+fFg0kpGRIYRo2rRp\ned/a1dU1NDQ0NDS0bdu2vXv3jo+PL7p6zM6dOy9fvhwbG2vw86uIhybWV/0f/db6qv+ftZRx\nTTmqzKOe6igfzff6VW6uXmMtZVxTvq3f8pq3dq3X2rXe+q396iu/9HTr0aOvl3n03//22bjR\nU7/Ky5a1zMiwCQ+/od/yGiYJ6Yztyss2P+q3/ITdkvz8h63yRpRxTCHF23xz1SZav8pH6y3I\nUzz0zy/j2lAAoDv2uAPGsWnTJktLy/T0dOkPKpXK0dExKipKO2HPnj29evUKCgpKSEiYMGFC\neZ8TdXd3VyqVxXe0X758WQjh6VkyeG3durVbt25ZWVlFI9rdOGfOnCkaWb16dZcuXVq0qPJJ\nXN05aU7pndq1ntXscNf8t/S4s+ao3qldy0OztanmV0Mq1JjffnPRO7Vrff+95y+/NCk9/ssv\nTfRO7Vpr13rt3etS+TwzcN36v3qndq2zNmvuWB0qPX7FKkbv1K512vbbZMsThlQAAII7YATa\nfTI9evRwcnIqGrSysurXr9++ffvS0tI0Gs3o0aN79eq1ceNGR0fHCkrVr18/NDR08+bNRXtm\nNm3a5O/v3759+xIzGzVqdOjQoV27dhWN7Nu3T/wR34UQWVlZ27ZtGzRokDGeYrnaqecYXsRP\nvdpCk/PUkKRprf7c8Mot1d8opHzD61QrtVrMnRtY+bzKfPGFv0r11HaZggLFF1/4G155zpxA\ntU47uk2pUMo7UW+p4XUO2X0iiad2rKmk7Ph6KwyvvN9+muFFAOhHpVLduXNHx8mJiYnh4eF+\nfn62trbu7u7Dhw8vfYkIk2CrDGAE2n0yM2bMKDEeFha2YcOGrVu3BgQE3Lx5MyQkZMWKp/77\n79q1a7t27Uqsmjp1akhIyKhRo4YPH75nz56NGzeuX79ee+ibb76JiYlZtWqVl5dX165dQ0ND\nx4wZc+XKlRYtWpw/f37p0qWvvvpqp06dtJP37dtXUFDQrVu36nnSQghhlZ9orFJ2OQeE+PO6\nNzb5541Vud6To0IEGKtadTh50tZYpY4eredfLKgfOVLPWJVPnbL19TVWsWpxo7CMM+X6SS48\n6yX+fAMkseA3Y1V+UHilmWhmrGoAdDd+/Piffvqp6DLNBw4cePnll4tPcHR01O5TvXbtWseO\nHV1cXMaOHdusWbObN2+uWrUqKCgoLi6u+DXfTILgDhhBVFSUhYVFWFhYifE+ffrY2tpGRUUN\nGzZMCLFmzZo1a9YUnxAZGVk6uHfp0uWnn36aPXv24MGDW7ZsuX79eu1yIcTVq1d3796dk5Mj\nhFAoFNHR0dOnT4+KikpISPDy8oqIiJg6dWpRnd27d9vZ2ZU+VW9EVrlGOwNhXfDULmrrvMvG\nqmyTb7RS1eTChZJX8NTb+fNPlTJu5cGDjVWsWqSqjfbTmFJ4XogBRQ/TNUZ7gZpceP450dNY\n1QDoKDo6es2aNW5ubkUj165dUyqVCxcuLLqcg42NjfaLefPmWVlZHT16tOgKb+PGjWvTps2U\nKVN27txZw52XQHAHjGDJkiVLliwpPV6/fv3c3Fzt1+Hh4boXDAkJCQkJKT2+bNmyZcuWFT20\ntrYu8/tqLV++fPnyKl/ppUosNNlGqyU9tTnBiJUVUuWXSjStrCyj7Vp88uSpUrm5RqtsxCar\niVoY7S86X8oq/lASlVzeVO/KAGrA3bt33333XV9fX+1pL63ExETtCa/S88+dO9e6devi12V2\ndHQMDw/fv39/TbRbIXP/RQzAvBkt0JS6bmP1VTY7kvGea6XXudebEZs0f0ZM6mXUBlCDJEkK\nDw8PCQkp8a54YmJi8+bNy1zi6up6/Pjx3357ao/c3LlzDx48WI2N6obgDgAAgNpp6dKlly5d\n+te//qV4+sRGYmJiTk5O9+7dHRwc/Pz8Jk+eXHQ+fubMmUqlsmfPnu3bt585c+b+/ftVKpUp\nei8DwR0AAAC10OnTp2fMmLFmzZri13zTunbt2vHjx1944YVvvvlmwIABX3/9dWhoqCRJQojg\n4OBz587NmDHDwsJi/vz53bt3b9So0Xvvvffo0SNTPImnsMcdAAAAtU1ubu7w4cPHjBnTu3fv\nEofUavXy5cvbtGmjvV/hiBEjAgMDR40atXPnzj59+gghvLy85s6dO3fu3LS0tF27dq1du/ab\nb76Jj48/cuSIovq2JOqAM+4AAACobSIjI5OSkrp06RIbGxsbG5uQkJCXlxcbG3vixAmlUhke\nHl50l3EhxJAhQxQKxalTpx4/fhwbG5uamqodb9y48bBhw3bu3Dl9+vSjR48eO3bMRM/mfwju\nAAAAqG0yMjJycnKGDRsWFhYWFhYWGxubmZkZFhb2xRdfPHjw4NixY8V3rltYWCgUCgcHh5yc\nnLCwsO3bt5eo1rNnTyFE8buVmwTBHQAAALXNokWLpGIiIiLc3NwkSYqKikpMTAwODi5+eeVt\n27ZpNJrOnTu7ubn5+/svW7YsPT29eLWoqChLS8ugoKAafx5PYY87AEMYcavfU5fJk6TqqmyG\nLIx3CqX6Ltpo0l2dNU1RjZcQrUt/joC56ty5c//+/WfPnp2UlNS1a9eLFy8uW7Zs5MiRzz//\nvBBi5cqVr732Wps2bUaMGNG8efPc3Nzdu3fv2LFj0aJFjo6Opu2c4A5AfxpLo/0KkxRP/Toy\nYmWNRT1jlaomjo5qY5Vq0OCp+1g984ymvJlV1bCh0ZqsJlbCaH/R9RQNiz9UGO/daTuLkpe2\nAGASW7ZsmT9//tatW9etW+fr6ztnzpyJEydqD3Xr1u3kyZOfffbZnj17VqxY0bBhQ39//5iY\nmIEDB5q2Z0Fwh7nZtGnTt99+e+rUKUdHx759+86ZM6f4rctgblT12hqtlE1A8Yf5tm2MVTnf\nprWxSlWT9u3zjVWqXbu8Ch4awohNVpMmlu2MVcrd8rmnKxvtp9Hdsr2xSgGokk4Z8EgAACAA\nSURBVEWLFi1atKjooVKpnDVr1qxZs8qc7OHhsXr16ppqrQrY4w4zsnLlyqFDhzZo0OCrr74a\nPXr0999/369fv8LCQlP3hXIVWjW7Y9HPKKWe2HUu/rDAxs8oZYUQeXbPG6tUNWnd2mi39nj+\n+bwKHhqiTRtzuf9IeTwtg41VytmyZfGH3pYvGaVsC9VrjkoPo5QCUDcR3GEuJEmaNWtWaGho\nTEzMW2+9NXPmzPXr1x87duznn382dWuoSIpFD8OLXFROlBTWJQZPWc43vPJ5y48koTS8TrVS\nKMTSpacNrzN//tkS2+UtLMT8+WcNr2yU9qqbQii75sw2vE7P7OUlRpTCuvOTGYZX9lL9xfAi\nAOoygjvMRUpKSmpq6uuvv150a4Pu3bsLIS5cuGDKtlCZLIXvReUkQypcVw6/b/Fy6fFHioDL\nyr8bUjlROfKB4gVDKtSY9u0f/uMfVwyp8Pe/JwQHp5ceDw5O//vfEwyp/I9/XGnf/qEhFWpM\ns8Kuz+WNN6RCp9wpzuoyNsZ4FvRskzfKkMqdn8xwUrcwpAIAsMcd5sLJyen8+fMeHn++j3zo\n0CEhhI+Pj+magk7uW7yUr3B+rvBjPdZetPzHfUW38o4mW/TME43bq/9Pj8rnldMeWBht70QN\nCA295+KS99FH+mzUnjv3XJcuaeUdfe21O25ueTNn6rNR+/PPzwQFZeix0FRa5g+217gdsvtU\nj7Xdcxa5FXYs72hg/ggHqemRenP1qNwzZ7lzodE2ygOoswjuMBc2NjaBgYFFD+Pj40eNGtWq\nVavSH+JOSUmJjIysuNqtW7deffVV43eJcmQqAvZaxThKlxtIF5RSvkJRycVM1JJ1lsL3oUV7\nTWW/hR5atNtnEdNAc8FRXLKQVBVXliShEdaPFX4PLdpKMvz91qlTxp49+06fdrxwoUF+voVG\nU/GlAyVbW01AwOPnnnuoVFZyGcguXdJ279536lTDS5eeyc+3qPhqmwqFZGOjCQx81L59poWF\nuV9Ms7RmBd3eePRriuWpdOUljUIlVXg9UIVQWArbxoWtXdTtRGUXIfVQhTQreOm+8mS68opa\nUcmndRVCoZRsXdTtnNWtK61snn78MWvPHvWqVbpe4mn8+MwRI6y7dLGreJokifXrHx88qNG9\n8vvvZ4aH2wQFmfsVomTkGSu3Xi7/UCqsTN2IQZrYtjJ1CzVNIVXfVX8BvTx58mTevHmLFy9u\n165dTExMs2bN9Ciyd+/ewsLCV155xejtobg7d+4kJBi0DaOIp6dn8XdXkpKSrl+/Xh2VzdDN\nmzdv3LhhlFIlnuz169eTkpKMUtnb29vLy8sopaqJEZ+sj4+Pp6dndVT28/PT73daDUtOLoiI\nyPn+e32uyvrBB5mLFzewsir7tcqtWwUffZSzcaM+lSdPzly4sIGlpSxfBQFGIb8zUqjdDh48\nOHLkyEePHi1evHj8+PGWlvyIAkCNysgobNrUSgg976Xw5ZeOWVmZq1c7lr5pV0pKgaen/pWX\nLHHMysr8179MfAccwIT4cCrMyJ49e3r16hUUFJSQkDBhwgRSOwDUvI8/zjawwnffOS5f/qj0\n+MyZOQZWXrnScdWqxwYWAeSL4A5zodFoRo8e3atXr40bN5r8lsIAUDddvZpvlFPakyY1UKuf\n2osbH5+3erURKr/77jOGFwFkijOaMBdxcXE3b94MCQlZsWJF8fGuXbu2a2e0GyICACrw44+5\nQtgYpdThw7kvvfTnB1U3bcoTwtYolU+fzmvf3jilAHkhuMNcJCYmCiHWrFmzZs2a4uORkZEE\ndwCoGcnJRit19mzBS8XuOfuojL0zejp9WkVwR91EcIe5CA8PDw8PN3UXAFCnlf5Eqd5ycp7a\nKlN9lYG6gz3uAAAAgAwQ3AEAAAAZILgDAAAAMkBwBwAAAGSA4A4AAADIAMEdAAAAkAGCOwAA\nACADBHcAAGB8SqX8KgNmjuAOAAD+x9LSaPc2cnPTFH9oxBswNWmiqXwSUBsR3AEAwP88/3ye\nsUp17Kgq/rBt23xjVW7XrsBYpQB5IbgDAID/6dw51yh13nzzVoMGT50X7979iVEqjxiRVK+e\n0d4WAOSF4A4AAP7HwkIsWxZveJ3XX79dYsTSUlq48KzhlQcNKlkZqDsI7gAA4E/t2mXOnHnB\nkAr/+tcJJydV6fFOndKnTbtkSOXvvjv+zDPsk0HdZWnqBgAAgHkJCUn18nry889NoqObFR9v\nKa4EiguNRZpGWNwTTU+L9vdE0+IT3nwzadCgOw0blpHatXr3TvH2ztm1yy0m5s/KCiEFiEsB\n4lIjka4Wynuiabx4LkW4FV84fHjS4MG3Se3GUlAgbsv/rYsGDUSjRqZuomYR3AEAQEk+Ptnv\nv5/w5ptJV686aO5mBp/Y0PHSdses5BLT7jn7H2/9enzH1x1cFa1aPa5XT11p5RYtslq0yHrz\nzVtXrzoo7qZ1Pr6+w+Udz2Snlph2xzXwWOtBZzoMcHRTBAQ8trWtvDJ0d+KEePFFUzdhsAkT\nxJdfmrqJmkVwBwAAZXNqmD/41nqv9ests7PLnND0weWwvfP+en7llYkT0+t11r1y44a5Ha6v\n8fjhB8ucnDInNLt/odn9C/0u/OvK5MkZth316R7lk2rF53sdHEzdQY1jjzsAACiDhUrV+tNP\nm3/7bXmpvYjNgwdtZ8zwWrdOx8rKvLw2H3/ss3p1eam9iG1KSrspU57dtEnHykDtRnAHAAAl\nKSQpcPZs50OHdF/i/d13nhs2VF65sLD1rFmNjh/XvXLzb79tFhOj+3xAa/r06YpiGjdu3Ldv\n3+jo6NIzJ02apFAoXiy1f2jevHnFK1hZWbVs2XL69OlPnjwRQvz4448KheLw4cM18WSEEGyV\nAQAApXlu2ND4yJGqrvJZvfqxv//DjhXtbPH+7junkyerWtnv66+zWrZ8FBhY1YXAqlWrrKys\nJEm6efPmzz//PGjQoE8++eSzzz4rmiBJUnR0tKWlZVxc3N27d93d3UtU+Oc//2lnZyeEyMnJ\n2b1798KFC+/cubNO57eYjIgz7gAA4Cm2ycnea9bot7ZlZKSisLC8o3ZJSZ4bN+pZedkyRe3Y\nmo2a9dZbb4WHh7/zzjv/93//d+TIkb/97W9z5sw5f/580YSjR4/evn176tSpkiTFlPXezrBh\nw8LDw8PDw997772YmJihQ4euX7/+wYMHNfgk/ofgDgAAnuLxww96r613967rb7+Vd9Tz++/1\nrmx//Xrjgwf1Xg4IIZRK5eLFi+3s7L744ouiwaioqHr16k2fPt3X1zcqKqrSIr179xZCJCQk\nVGOj5SC4AwCAP1kUFFSQvHXh9ssvZY4rc3OrtGm+tCY7dxqyHBBCODo69u3bNy4uTvtQkqTN\nmzf369evfv36AwcOPHz4cHJyycuelnDr1i0hRMOGDau911II7gAA4E/PXLpU6cVeKtbgwgWL\n/PzS447nzilzcw2p7Bgfr1BzQXcYysPD49atWxqNRvyxT2bIkCFCiIEDB2o0mi1btpS3MDc3\nd8eOHcuWLfP29m7evHnNdfwHgjsAAPiT/fXrBlawKCiwu3WrjMrXrhlYWZmXV6+ys6FApZyd\nnVUq1cOHD4UQUVFR9vb2/fr1E0IEBwe7ubmV3i3j6OiovaqMnZ1d//79bW1t169fb2VlVfOd\nc1UZAADwJ+uHD6upiHVmpuGVrYzRHuq4tLQ0a2vrhg0bavfJBAQE7N27V3vI39//wIEDqamp\nLi4uRfOLriojhGjatGlwcLCDiW7+RHAHAACyoTB1A6gFbt265eHhYWFhod0nc/v27dDQ0OIT\ntmzZMnbs2KKHw4YNa9CgQY23WQa2ygAAgD+pjPGRuzKLVF9lQHePHz/+6aefOnfuLITYtGmT\npaVlenq69AeVSuXo6KjLtWVMguAOAAD+lOPjY2AFjbV1rodHdVRW29rmNmliYBHUZRqNZurU\nqTk5Odqrtm/evLlHjx5OTk5FE6ysrPr167dv3760tDQT9lketsoAAIA/PQ4IKLS3N+TCMo8C\nA9U2NqXHM9u0UdvaKvPy9K6c+dxzklKp93LUTd9//721tbUkSUlJST///PPhw4c/+eST1q1b\na/fJzJgxo8T8sLCwDRs2bN26dfTo0SZpuAIEd5gjjUaTn59fr149UzcCAHWOxsrqfkiI+/bt\neldI6d27zHF1vXoPunVz+/VXvSsn9+mj91rUWaNGjdJ+4eTkFBQUFBUVNWjQICFEVFSUhYVF\nWFhYifl9+vSxtbWNiooyw+DOVhmYo7Vr14aEhJi6CwCoo24NHar32lx39/vl/wK/NWyY3pVz\nvL3TXnxR7+WogxYsWCAVk56e/ssvv2hTuxBiyZIlarXa1dW1xKr69evn5ubu3LlTCDFjxgxJ\nksr7ZOobb7whSdKLNfhjSXCH2blz586CBQtM3QUA1F15TZrc+OMkZVVdmThRsiz3/fwcT8+k\nN9/Us/KkSZIFuQV1Gv8AYEaOHz8eFBTk7e2dkJBg6l4AoE5LGjYsrXPnqq66/re/PezYseI5\nN0aOzKhsTmkJf//7o9atq7oKqGUI7jAjzs7O77zzTmRkZNu2bU3dCwDUaZKFxYVPP33Qtavu\nS26MHJk0fHjllS0tz8+Zk9Gpk+6VE8eNu/Paa7rPB2orPpwKM+Lt7f3+++8LIXbv3p2SkmLq\ndgCgTtNYW5//7LNnN2/2WrfOMju7gpn5zs5XJk1KDw7WsbLa1vbs/PkeGzd6/PBDxZevyXNz\nuzx5cqVn8YE6guAO+cnIyNi8eXPFc65cudKlS5ea6QdlsszObhgfXz8xUXvn80IHhxwvr4cd\nOuQ3amRgZavHjxvGx9tfu6a9fXqBg0OOt/fDDh1UxS7EC8A4FIrbgwff79mzWXS02+7dNg8e\nlDie7eOT3Ldvcr9+ZV7/sQKShUXS8OEpf/lLs+ho1z17bNLTS0zI8vNL7tcvuU8fjbW1QU8B\ntVdWlqk7qHEEd8iPg4NDr169Kp5Tv359Ozu7mukHJdjfvOm1bl2juLgyr9b8sGPHpOHDH7Zv\nr0fl+omJXuvWOR88WObR9E6dkoYPf9SmjR6VAVRA5eR0fcyY62PG2N26ZZ+UZPXokaRQqBo3\nzm7e3MCX4vnOztfGjbs2dqz9rVt2SUlWjx9LCoXK2TmreXNeilerjh3FtWumbsJg5VzrpTYj\nuEN+rKysfCq7/V5SUlJhYWHN9IMiCrXa+7vvPL//voI5DU+ebHjy5P1eva5OnFio84sri8JC\nn1Wrnq3wHtSNjh9vdPx4cp8+CR98oLa1rULfAHTzxMPjSVm3RDWUQpHj6Znj6Wn8yiiHra0w\n+D62MAE+nArAOCzy89vMmFFxai/iunt3hwkTrDMydJmszM1tO3Vqxam9SJNffnlu4kSrR490\nmQwAgIwQ3AEYgyS1mjev0fHjuq+wv3Gj3bRpld78XKHRtP7ss4anT+te2eHq1bbTp1uoVLov\nAQDA/BHcARhBs61bnQ8dquqq+teuNV+xouI5Hj/+6FSV1wNaz1y+7LNqVVVXAQBgzgjuAAxl\n9fix93/+o9/apv/9r8PVq+UdtU5P99i4Ub/Kz0ZH2ycl6bcWAAAzRHCHOdqyZUtcXJypu4Cu\nmm7fbmnARbk8fvyxvEPNtm6t+OrRFXt20ya91wIAYG4I7gAM5bp7tyHLy7twpBDCdc8eQyo7\n799vwcWFAAC1BcEdgEGsMzMN3JGizMt75sKF0uO2ycm2ht1A1/LJkwr24QAAIC8EdwAGsTPG\nPnL727fLGLx1y/DKdsYoAgCAOSC4AzCIIbvbKy5SfZUBAJAjgjsAg0iWRrgBc5lFjFNZqTS8\nCAAA5oDgDsAg+c7ORijSuLGOg1WubIz2AAAwBwR3AAZ54uGhtrExsEiWn1/pwWwfHwPLllcZ\nAAA5IrgDMIjGyuphx46GVMhr0iTH07P0uNrO7mGHDoZUzvHyynNzM6QCAADmg+AOwFD3+vUz\ndLlCUV2VAQCoLQjuAAyVHhz8qFUr/daqGjW6GxZW3tEH3btnN2+uX+U8F5d7oaH6rQUAwAwR\n3AEYTKG4EhFR6OCgx9IrH35YaGdX3lFJobgcEaFfU1ciIjQGb74HAMB8ENwBGEGOl9flyZOr\nuurGyJFpXbtWPCerRYtL06dXtXLi+PEZzz9f1VUAAJgzgjsA43jw0kvnZs8u0Pm8+7Vx426+\n9ZYuM1NeeeXCzJm6n9G/+sEHtwcP1nEyAAByYYT7mwCAVlrXrie9vVtGRjY8ebKCadk+Plcn\nTXoUGKh75dSQkGxf35aRkY5nzlQwLatFi6uTJj1u2VL3ygAAyAXBHYAx5bq7n160qMGFC01+\n+snpxAmbtLSiQwUODpkdOqS88kp6585SOZeRqcATT8/4Zcscz5xp8ssvTidOWGdk/Fm5QYOH\nHTqk9O6dHhRU3gVqAABVdumSiI0Vx4+LW7dEVpZo1Ej4+opu3URYmHBxMUJ9tVrs3St++UWc\nOSPu3xcajXBxEa1bi1deEb17C2trI3yL2oXgDsD4HgUGak+oW2Vm2mRkCLW6wMkpv1Ejwytn\ntmuX2a6dEMI6M9M6PV1IkqphQ5UxKgMA/nTsmJg+XezdW3I8Lk6sXy8mTxaDB4s5c4S7u571\nNRqxerWYN08kJT01fuGC2LtXfPWVcHUVU6aICROI78Wxxx1ANSpwdMz28cn28zNKai9O5eiY\n7eub3bw5qR0AjEmtFh99JIKDy0jtRbKzxXffibZtRVSUPt8iOVn06CHefbdkai/u/n0RESFe\neEEkJurzLWopgjsAAACEEEIUFoo33hCff67T5IwMMWSI+PLLqn2LGzdE587iwAGdJp8+LV58\nUVT46aY6heAOAAAAIYQQEyeK6OiqLfnwQxETo+vkrCzx179WdKK9tNRU0bevSE6uWlc6SExM\nDA8P9/Pzs7W1dXd3Hz58+MWLF43+XYyL4A4AAAAhfv5ZrFihz8KxY0VKik4z//EPceVKlevf\nuyfGjKnyKiEOHDigeFrDhg21h65du9axY8cjR46MHTv2P//5z4QJE44ePRoUFHT27Fk9vlGN\n4cOpAAAAdZ5GI6p+H73/SUsTn30mvvmmkmnnzol//1vPb/Hf/4pffxWvvFKlRdeuXVMqlQsX\nLlT8ccExmz/uqD1v3jwrK6ujR482+uODUuPGjWvTps2UKVN27typZ5PVj+AOAABQ5+3cKS5d\n0n/5+vViwQLh6FjRnKruhi9h+fKqBvfExEQvL6+IiIjSh86dO9e6detGxS5v4OjoGB4evn//\nfoOarGZslQEAAKjz9Ls+TJHsbPHf/1Y0Qa2uwlb4Mu3dKx4/rtKKxMTE5s2bl3nI1dX1+PHj\nv/32W/HBuXPnHjx4UP8Oqx/BHQAAoM47fNjQCocOVXT08mVR7MZ5+njyRBw7VqUViYmJOTk5\n3bt3d3Bw8PPzmzx5ck5OjvbQzJkzlUplz54927dvP3PmzP3796tUKoPaqxEEdwAAgLpNoxE3\nbhha5Nq1io4a5XLsFX+LMqZfO378+AsvvPDNN98MGDDg66+/Dg0NlSRJCBEcHHzu3LkZM2ZY\nWFjMnz+/e/fujRo1eu+99x49emSEPqsNe9wBAADqtrw8UVBgaJHsbP2P6igrS/e5arV6+fLl\nbdq06dChgxBixIgRgYGBo0aN2rlzZ58+fYQQXl5ec+fOnTt3blpa2q5du9auXfvNN9/Ex8cf\nOXKk6MOs5oYz7gAAAHWbjY1QKg0tUq+e/kd1ZGen+1ylUhkeHq5N7VpDhgxRKBSnTp16/Phx\nbGxsamqqdrxx48bDhg3buXPn9OnTjx49eqyKG3JqEsEdAACgblMqxbPPGlrEy0v/o0b5Fk97\n8ODBsWPHiu9ct7CwUCgUDg4OOTk5YWFh27dvL7GkZ8+eQoisqpzXr2EEdwAAgDrvhRcMrRAc\nXNHR1q1F/fqGfotOnXSfm5iYGBwcvGzZsqKRbdu2aTSazp07u7m5+fv7L1u2LD09vfiSqKgo\nS0vLoKAgQ/usNuxxBwAAqPMGDhQ//mhQhf79KzpqbS369hWbNulfv1s34eys+/TOnTv3799/\n9uzZSUlJXbt2vXjx4rJly0aOHPn8888LIVauXPnaa6+1adNmxIgRzZs3z83N3b17944dOxYt\nWuRY8dXoTYoz7gD0Z2lZXS/+jVjZwsLcf9EZ8ckqn96lqjR80+ofqu/v2liM+Bctix9s81d9\nT9aIP9j4U1iYcHfXf/kbbwg3t0rm/P3v+tcXQrz/flVXbNmy5aOPPjp27NjYsWN37NgxZ86c\nf/9x69Zu3bqdPHnyr3/96549eyZNmrRo0aLc3NyYmJgy79ZkPurQbxDIQlxc3McffxwfH9+i\nRYuIiIghQ4aYuiNUxMHBwVil7O3tq6lyfcPfnK1mRuywRKnqq2yGjNhhiR+/Ej+cRqxshuyq\n8uG/ipX4Gym61bzhzP+PUZZsbMTcuWLkSD2Xz5lT+Zxu3UT//qLUznKdBAWJwYOrukipVM6a\nNWvWrFllHvXw8Fi9erU+zZiOuZ+IQp3y+++/9+jRw8bGZunSpS1bthw6dOgmQ95TQ/UzYqAp\nft9pYdT/mJ2cnIxVqpo0aNDAWKUaNmxYwUNDGLHJamLEv+gSP34lfjgNYcR/MtWkcePGxipV\n4jWAc1U2OVSgWbNmRnwNgKeEh4sBA/RZGBkp/Px0mvntt5WfmC/NyUmsXSvM/u3TGsAfAczI\n559/3rx5823bto0aNWrdunX9+vWbN2+eqZtCJdq1a2d4ET8/vxLvqisUitatWxteuWXLlua/\nVUahUAQGBhpex9/fv8STtbCw8Pf3N7xyYGCg2V7VuIiFhUXLli0Nr9O6desST9bS0tJPx1BS\nIaP8Y6lulpaWvr6+htdp3759iRFra2sfHx/DK7u4uBheBGVTKMS6dZV8xrS0Dz4QH36o6+Sm\nTUVsrKjqi+HvvxcBAVVbUkuZ+/9nqDtyc3O3bNnyxhtvWFtba0fefvvts2fPxsfHm7YxVMzJ\nycnA/+afffZZ97I2Vjo7O3t7extS2cPDo2nTpoZUqDEuLi5ehl0rzdPTs0mTJqXHmzRp4unp\naUhlLy8vuUSlpk2benh4GFLB29u7zBPD7u7uzxp2sTxfX1/zf/NH69lnn23WrJkhFfz8/Mp8\nt8fDw6PMf+y6a9Gihfm/+SNvDg7i11/Fa6/pOn/ePLF8edW+RadO4rffhI7/cTRpIg4cEL17\nV+1b1F4Ed5iLe/fuqdXqtm3bFo20adNGCHHx4kXTNQWdeHh4BOh7LsTX19fX17e8s7leXl56\nnzBu3ry5UU4c1hhvb+8WLVrot9bPz6+Cc5k+Pj56nzBu0aKFgS+fapivr2/z5s31W+vv71/e\nyyeFQqH9WdWvckBAgIGvKGqSQqFo3ry53mfHW7VqVV7u11bW+yeqdevWBuZ+6KR+fREdLTZs\nqOSi6V27iuPHxccf6/Mt2rYVp0+LKVPEM89UNG3cOHH2rOjWTZ9vUUspJEkydQ+AEEIcOHDg\n5ZdfPnjwYNeuXbUjDx48cHFx+frrr99/+oPkKSkpkZGRFVdLS0sbNmxYSEhIdbWLUtRqdWpq\nam5urhCi0l8sCoXCysrK1dW16A2WChQWFqampubl5eny+0qhUFhbW7u4uOhS2QwVFhbev38/\nPz9f9yfr6upqZWVV6eSCgoLU1FTdK9vY2Li6usr0KigqlSo1NVWlUun4ZG1tbV1cXHR5siqV\n6v79+wUFBbr8kAsh6tWr5+LiItOroOTn56emplbHk83Ly0tNTS0sLNSlsiRJ9vb2zs7OMv1j\nlLHCQvHTTyI2Vpw4IW7cENnZwtlZ+PqKrl3FkCHCKBc7z8gQP/wgdu4UZ8+K5GSh0QhXV9Gm\njejZU7z5ppDJW6Y1ieAOc7Fv374ePXqUDu7//Oc/x48fb9reAAAATI6tMjAX2u25Dx8+LBrJ\nyMgQQshljzIAAEC1IrjDXLi7uyuVyuI72i9fviyEMPBzdQAAALUDW2VgRsLCwu7evXvs2DHt\nJe2GDx9+6tSpS5cumbovAAAA05Plp45QW02dOjUkJGTUqFHDhw/fs2fPxo0b169fb+qmAAAA\nzAJn3GFefvvtt9mzZ58+fbply5YffvjhsGHDTN0RAACAWSC4AwAAADLAh1MBAAAAGSC4AwAA\nADJAcAcAAABkgOAOAAAAyADBHQAAAJABgjsAAAAgAwR3AAAAQAYI7gAAAIAMENwBAAAAGSC4\nAwAAADJAcAcAAABkgOAOAAAAyADBHQAAAJABgjsAAAAgAwR3AAAAQAYI7gAAAIAMENwBAAAA\nGSC4AwAAADJAcAcAAABkgOAOAAAAyADBHQAAAJABgjsAAAAgAwR3wDTOnDkzZMgQf39/e3v7\nwMDAKVOmPHz4sOhoQEDAlClTTNieaalUqjt37pi6C9R1Go0mNzfX1F0AwJ8I7oAJrFmzplOn\nTpcvX37ttdcWLFjQqVOn5cuXv/jiizk5OaZuzSyMHz8+KCjI1F3I1aZNm0JCQhwdHb28vN57\n77309HRTdyRXa9euDQkJMXUXcqVSqebMmRMQEGBvbx8QELBgwQKVSmXqpgDZszR1A0Cdk5yc\n/OGHH4aFha1bt87a2lo7+O6777700kvz5s2bP3++adszuejo6DVr1ri5uZm6EVlauXLluHHj\nBgwY8NVXXyUlJS1evPjUqVOHDh2ytOS3fdXcuXNnwYIFjRo1MnUjcjVt2rQvv/xy4sSJQUFB\nJ0+enDVrVlpa2pIlS0zdFyBvCkmSTN0DULeMHj36xx9/vHXrVsOGDYuP//Wvf01MTExISBBC\nBAQEhIaGLlq0qII6kiTl5uba2dlVb7s16+7du23btm3YsGFOTk5ycrKp25EZSZLc3NxeeOGF\n2NhYhUIhhNixY0f//v23bdvWv39/U3cnG8ePH3///fdPnz5dWFgYHBwcQilXGwAAHkFJREFU\nFxdn6o7kR6VS1a9ff+bMmZ988ol2ZMyYMVFRUZmZmaZtDJA7tsoANW3Xrl2DBw8ukdqFELGx\nsadPny4+smrVqnbt2tWvX79Lly6///67dtDPz2/FihVff/21p6fn9u3ba6jpGiFJUnh4eEhI\nSFhYmKl7kaWUlJTU1NTXX39dm9qFEN27dxdCXLhwwZRtyY2zs/M777wTGRnZtm1bU/ciV8nJ\nyR07duzdu3fRiIeHR35+PrtlAAPx5ilQo3Jycu7cudOyZcvSh6ytrYt2zgghfvjhBy8vr9mz\nZycnJy9YsGDQoEE3b97UHtq8eXNubu78+fNffvnlmmm7ZixduvTSpUvnzp1bsGCBqXuRJScn\np/Pnz3t4eBSNHDp0SAjh4+Njuqbkx9vb+/333xdC7N69OyUlxdTtyJKnp2fxdyquXr26YcOG\nvn37Fv8VB0APBHegRiUlJWn3M1Q6U6VS7dy5U7sTxt7e/u23305LS2vcuLEQ4tKlS9evX69l\nm2ROnz49Y8aM2NhYJycnU/ciVzY2NoGBgUUP4+PjR40a1apVq4EDB5qwK9RlO3bsePPNN7Oz\ns5977rl169aZuh1A9tgqA9SoZs2aCSF0OY33l7/8pSiau7i4CCHUarX2Yc+ePWtZas/NzR0+\nfPiYMWOKv7cOvT158mTGjBnBwcHNmjXbuXOnlZWVqTtCHRUUFLRx48ZFixYlJyf36dOHj9UB\nBiK4AzXqmWeeadKkyZUrV0ofWrt2bfFDrq6u5RWpfVdciYyMTEpK6tKlS2xsbGxsbEJCQl5e\nXmxs7IkTJ0zdmvwcPHiwbdu2K1euXLx48ZEjR7SvFQGTcHV1DQ0NjYiIWLt27cGDB+Pj403d\nESBvBHegpnXr1m3Tpk1paWklxrdv356Xl+fn56d9WPT5wtIsLGrbv9yMjIycnJxhw4aFhYWF\nhYXFxsZmZmaGhYV98cUXpm5NZvbs2dOrV6+goKCEhIQJEyZwFUiYxNatW7t165aVlVU0ot3E\ndebMGdM1BdQGte2/f8D8LViwQK1WjxkzpvhNGaOjo7du3Tp06NDaF8p1sWjRIqmYiIgINzc3\nSZKioqJM3ZqcaDSa0aNH9+rVa+PGjY6OjqZuB3VXo0aNDh06tGvXrqKRffv2iT/iOwC9cTIG\nqGk+Pj7z58+PiIjo2LHjgAEDmjZtGhcXFx0d7eHh8fnnn1ep1DfffBMTE7Nq1SovL6/qaRZy\nEhcXd/PmzZCQkBUrVhQf79q1a7t27UzVFeqgrl27hoaGjhkz5sqVKy1atDh//vzSpUtfffXV\nTp06mbo1QN4I7oAJTJo0KTg4eN68eT/88MODBw98fX0//PDDWbNmOTg4VKnO1atXd+/enZOT\nU019Ql4SExOFEGvWrFmzZk3x8cjISII7apJCoYiOjp4+fXpUVFRCQoKXl1dERMTUqVNN3Rcg\ne9w5FQAAAJCBuribFgAAAJAdgjsAAAAgAwR3AAAAQAYI7gAAAIAMENwBAAAAGSC4AwAAADJA\ncAcAAABkgOAOAAAAyADBHQAAAJABgjsAAAAgAwR3AAAAQAYI7gAAAIAMENwBAAAAGSC4AwAA\nADJAcAcAAABkgOAOAAAAyADBHQAAAJABgjsAAAAgAwR3AAAAQAYI7gAAAIAMENwBAAAAGSC4\nA9UiMTExPDzcz8/P1tbW3d19+P9v796DojrvP46fZcWNIAGRKAIJeCGiRKQQZOs0DQgdElgF\nE8cwSESpMdUpExsRNcTxSqxKEMeMCkZjJMQEvLDGmmJCQ72Bl4AXKl6AhIwXinctIAjs74/z\nyxm64LqGDfLY9+uvPc/zPQ/PPnNgP3v27GHSpDNnzpjeZePGjQkJCZaaQFVVla+vb1NTk6UG\nBAAAj5fKYDA87jkAT5rKyko/P79+/fq9/fbbbm5uP/7448aNG2tqaoqKinx8fDrcpba21s/P\n7/jx487Ozpaaxp/+9CdXV9cFCxZYakAAAPAYccYdsLyUlBRra+vi4uLExMTo6Oh58+Z9//33\njo6Oc+bMedAua9euDQkJsWBqlyQpISEhLS2trq7OgmNaxP79+1X/rU+fPg8qLioqCg4OdnBw\nGDVqVE5OTlfOUyBNTU0XL1583LMQT1NT09KlS4cNG2Zrazts2LDly5eb+JCKQ9GEnJycMWPG\nODg4eHh4zJw58/r16w+qZBmBziC4A5Z3+vTpF154oW/fvkqLg4NDXFxcfX19h/VNTU0ZGRmx\nsbGP9FMaGxtNF3h7ew8cOHDr1q2PNGwXqKysVKvVq1atSv3Z0qVLO6w8fvx4cHCwRqNJS0sb\nOnRodHQ0r/QdmjFjRkBAgIkC0lKH5s6du2jRovDw8E2bNul0ugULFsyfP7/DS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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 300,
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(idiogramFISH)\n",
    "\n",
    "# load some package data.frames - optional\n",
    "data(dfChrSizeHolo, dfMarkColor, dfMarkPosHolo)\n",
    "\n",
    "# column Mbp not for plotting purposes\n",
    "dfChrSizeHolo$Mbp<-dfChrSizeHolo$chrSize*100\n",
    "\n",
    "# svg(\"testing.svg\",width=14,height=8 )\n",
    "par(mar = c(0, 0, 0, 0), omi=rep(0,4) )\n",
    "\n",
    "# png(\"dfOfChrSize.png\", width=500, height=400)\n",
    "options(repr.plot.width = 10, repr.plot.height = 6, repr.plot.res = 100)\n",
    "\n",
    "suppressMessages(\n",
    "\n",
    "plotIdiograms(dfChrSize  =dfChrSizeHolo, # data.frame of chr. size\n",
    "              dfMarkColor=dfMarkColor,   # df of mark style\n",
    "              dfMarkPos  =dfMarkPosHolo, # df of mark positions\n",
    "              \n",
    "              addOTUName=FALSE,        # do not add OTU names\n",
    "              distTextChr = 1,         # chr. name distance to chr.\n",
    "              chrSize = TRUE,          # show chr. size under chr.\n",
    "              chrSizeMbp = TRUE,       # show chr. size in Mbp under chr. requires Mbp column\n",
    "              \n",
    "              rulerPos=-0.1,           # position of ruler\n",
    "              rulerNumberPos=.9        # position of numbers of rulers\n",
    "              ,xPosRulerTitle = 3            # pos. of ruler title (units)\n",
    "              \n",
    "              ,xlimLeftMod=2           # modify xlim left argument of plot\n",
    "              ,ylimBotMod=.2           # modify ylim bottom argument of plot\n",
    "              ,legendHeight=.5         # height of legend labels\n",
    "              ,legendWidth = 1.2       # width of legend labels\n",
    "              ,xModifier = 20        # separ. among chromatids\n",
    "              )\n",
    "    )\n",
    "    #dev.off() # close svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ec95c4c",
   "metadata": {},
   "source": [
    "### Let's explore the data.frames for holocentrics:\n",
    "\n",
    "* chromosome data, if only 1 species, column OTU is optional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dc9f711b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>chrName</th><th scope=col>chrSize</th><th scope=col>Mbp</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1</td><td>3</td><td>300</td></tr>\n",
       "\t<tr><td>2</td><td>4</td><td>400</td></tr>\n",
       "\t<tr><td>3</td><td>2</td><td>200</td></tr>\n",
       "\t<tr><td>4</td><td>5</td><td>500</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 3\n",
       "\\begin{tabular}{lll}\n",
       " chrName & chrSize & Mbp\\\\\n",
       " <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 1 & 3 & 300\\\\\n",
       "\t 2 & 4 & 400\\\\\n",
       "\t 3 & 2 & 200\\\\\n",
       "\t 4 & 5 & 500\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 3\n",
       "\n",
       "| chrName &lt;dbl&gt; | chrSize &lt;dbl&gt; | Mbp &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| 1 | 3 | 300 |\n",
       "| 2 | 4 | 400 |\n",
       "| 3 | 2 | 200 |\n",
       "| 4 | 5 | 500 |\n",
       "\n"
      ],
      "text/plain": [
       "  chrName chrSize Mbp\n",
       "1 1       3       300\n",
       "2 2       4       400\n",
       "3 3       2       200\n",
       "4 4       5       500"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfChrSizeHolo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6af561ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>markName</th><th scope=col>markColor</th><th scope=col>style</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>5S  </td><td>red           </td><td>dots  </td></tr>\n",
       "\t<tr><td>45S </td><td>chartreuse3   </td><td>square</td></tr>\n",
       "\t<tr><td>DAPI</td><td>blue          </td><td>square</td></tr>\n",
       "\t<tr><td>CMA </td><td>darkgoldenrod1</td><td>square</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 3\n",
       "\\begin{tabular}{lll}\n",
       " markName & markColor & style\\\\\n",
       " <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t 5S   & red            & dots  \\\\\n",
       "\t 45S  & chartreuse3    & square\\\\\n",
       "\t DAPI & blue           & square\\\\\n",
       "\t CMA  & darkgoldenrod1 & square\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 3\n",
       "\n",
       "| markName &lt;chr&gt; | markColor &lt;chr&gt; | style &lt;chr&gt; |\n",
       "|---|---|---|\n",
       "| 5S   | red            | dots   |\n",
       "| 45S  | chartreuse3    | square |\n",
       "| DAPI | blue           | square |\n",
       "| CMA  | darkgoldenrod1 | square |\n",
       "\n"
      ],
      "text/plain": [
       "  markName markColor      style \n",
       "1 5S       red            dots  \n",
       "2 45S      chartreuse3    square\n",
       "3 DAPI     blue           square\n",
       "4 CMA      darkgoldenrod1 square"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mark general data\n",
    "\n",
    "dfMarkColor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "79d0f82e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>chrName</th><th scope=col>markName</th><th scope=col>markPos</th><th scope=col>markSize</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>3</td><td>5S  </td><td>1.0</td><td>0.5</td></tr>\n",
       "\t<tr><td>3</td><td>DAPI</td><td>1.5</td><td>0.5</td></tr>\n",
       "\t<tr><td>1</td><td>45S </td><td>2.0</td><td>0.5</td></tr>\n",
       "\t<tr><td>2</td><td>DAPI</td><td>2.0</td><td>0.5</td></tr>\n",
       "\t<tr><td>4</td><td>CMA </td><td>2.0</td><td>0.5</td></tr>\n",
       "\t<tr><td>4</td><td>5S  </td><td>0.5</td><td>0.5</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 4\n",
       "\\begin{tabular}{llll}\n",
       " chrName & markName & markPos & markSize\\\\\n",
       " <dbl> & <chr> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t 3 & 5S   & 1.0 & 0.5\\\\\n",
       "\t 3 & DAPI & 1.5 & 0.5\\\\\n",
       "\t 1 & 45S  & 2.0 & 0.5\\\\\n",
       "\t 2 & DAPI & 2.0 & 0.5\\\\\n",
       "\t 4 & CMA  & 2.0 & 0.5\\\\\n",
       "\t 4 & 5S   & 0.5 & 0.5\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 4\n",
       "\n",
       "| chrName &lt;dbl&gt; | markName &lt;chr&gt; | markPos &lt;dbl&gt; | markSize &lt;dbl&gt; |\n",
       "|---|---|---|---|\n",
       "| 3 | 5S   | 1.0 | 0.5 |\n",
       "| 3 | DAPI | 1.5 | 0.5 |\n",
       "| 1 | 45S  | 2.0 | 0.5 |\n",
       "| 2 | DAPI | 2.0 | 0.5 |\n",
       "| 4 | CMA  | 2.0 | 0.5 |\n",
       "| 4 | 5S   | 0.5 | 0.5 |\n",
       "\n"
      ],
      "text/plain": [
       "  chrName markName markPos markSize\n",
       "1 3       5S       1.0     0.5     \n",
       "2 3       DAPI     1.5     0.5     \n",
       "3 1       45S      2.0     0.5     \n",
       "4 2       DAPI     2.0     0.5     \n",
       "5 4       CMA      2.0     0.5     \n",
       "6 4       5S       0.5     0.5     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mark position data, if only 1 species, column OTU is optional (mandatory if in d.f of Chr. Size)\n",
    "\n",
    "dfMarkPosHolo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66fbbdfb",
   "metadata": {},
   "source": [
    "## Plotting both mono. and holo.\n",
    "\n",
    "Merge data.frames with `plyr` [@plyr2011]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "86dc9426",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: plyr\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# chromosome data, if only 1 species, column OTU is optional\n",
    "require(plyr)\n",
    "dfOfChrSize$OTU   <- \"Species mono\"\n",
    "dfChrSizeHolo$OTU <- \"Species holo\"\n",
    " \n",
    "monoholoCS <- plyr::rbind.fill(dfOfChrSize,dfChrSizeHolo)\n",
    "\n",
    "dfOfMarks2$OTU     <-\"Species mono\"\n",
    "dfOfMarks2[which(dfOfMarks2$markName==\"5S\"),]$markSize<-.7\n",
    "dfMarkPosHolo$OTU <-\"Species holo\"\n",
    "\n",
    "monoholoMarks <- plyr::rbind.fill(dfOfMarks2,dfMarkPosHolo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ac50d645",
   "metadata": {},
   "outputs": [
    {
     "data": {
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29K9J9Vgq92AOgyniEEgO5yLS42/dqO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UN2HChP3797do0WLTpk3BwcGnT5/+5JNP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\nMvX/ATAwnaMWh3rBAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 500,
       "width": 600
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(idiogramFISH)\n",
    "\n",
    "#svg(\"testing.svg\",width=14,height=10 )\n",
    "#png(\"monoholoCS.png\", width=700, height=600)\n",
    "options(repr.plot.width = 12, repr.plot.height = 10, repr.plot.res = 100)\n",
    "\n",
    "par(mar=rep(0,4))\n",
    "\n",
    "suppressMessages(\n",
    "\n",
    "plotIdiograms(dfChrSize  = monoholoCS,   # data.frame of chr. size\n",
    "              dfMarkColor= dfMarkColor,  # df of mark style\n",
    "              dfMarkPos  = monoholoMarks,# df of mark positions, includes cen. marks\n",
    "              \n",
    "              chrSize = TRUE,            # show chr. size under chr.\n",
    "              \n",
    "              squareness = 4,            # vertices squareness\n",
    "              cenFormat = \"triangle\",        # triangular cen.\n",
    "              addOTUName = TRUE,         # add OTU names\n",
    "              OTUTextSize = .7,          # font size of OTU\n",
    "              distTextChr = .5,          # separ. among chr. and text and among chr. name and indices\n",
    "              \n",
    "              karHeiSpace = 4,           # karyotype height inc. spacing\n",
    "              karIndexPos = .2,          # move karyotype index\n",
    "              \n",
    "              legendHeight= 1,           # height of legend labels\n",
    "              legendWidth = 1,           # width of legend labels\n",
    "              fixCenBorder = TRUE,       # use chrColor as border color of cen. or cen. marks\n",
    "              \n",
    "              rulerPos= 0,               # position of ruler\n",
    "              ruler.tck=-0.02,           # size and orientation of ruler ticks\n",
    "              rulerNumberPos=.9,         # position of numbers of rulers\n",
    "              xPosRulerTitle = 3.5,      # ruler title (units) position\n",
    "              \n",
    "              xlimLeftMod=1,             # modify xlim left argument of plot\n",
    "              xlimRightMod=3,            # modify xlim right argument of plot\n",
    "              ylimBotMod= .2             # modify ylim bottom argument of plot\n",
    "              \n",
    "              ,chromatids=FALSE          # do not show separ. chromatids\n",
    "              \n",
    "              # ,useOneDot=TRUE\n",
    "              \n",
    "              # ,circularPlot = TRUE       # circularPlot\n",
    "              # ,shrinkFactor = .9         # percentage 1 = 100% of circle with chr.\n",
    "              # ,circleCenter = 3          # X coordinate of circleCenter (affects legend pos.)\n",
    "              # ,chrLabelSpacing = .9      # chr. names spacing\n",
    "              \n",
    "              # ,OTUsrt = 0                # angle for OTU name (or number)\n",
    "              # ,OTUplacing = \"number\"     # Use number and legend instead of name\n",
    "              # ,OTULabelSpacerx = -0.6    # modify position of OTU label, when OTUplacing=\"number\" or \"simple\"\n",
    "              # ,OTUlegendHeight = 1.5     # space among OTU names when in legend - OTUplacing\n",
    "              # ,separFactor = 0.75        # alter separ. of kar.\n",
    ")\n",
    ")\n",
    "#dev.off() # close png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9abcf20b-5540-4fe9-a833-e2648459cc74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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51fxXDz5s3PPvtMr9cvWLBg+vTpNMmCZWVlFRUVA15WzZ7FxxvEmFNncTkjHvu+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DQ0O0R0EIIe3t7QUFBbRHIRnxeHwqcGPM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\nyNr/B4g/jK/cpR+MAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 300,
       "width": 300
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(idiogramFISH)\n",
    "\n",
    "#svg(\"testing.svg\",width=14,height=10 )\n",
    "#png(\"monoholoCS.png\", width=700, height=600)\n",
    "options(repr.plot.width = 6, repr.plot.height = 6, repr.plot.res = 100)\n",
    "\n",
    "par(mar=rep(0,4))\n",
    "\n",
    "suppressMessages(\n",
    "\n",
    "plotIdiograms(dfChrSize  = monoholoCS,   # data.frame of chr. size\n",
    "              dfMarkColor= dfMarkColor,  # df of mark style\n",
    "              dfMarkPos  = monoholoMarks,# df of mark positions, includes cen. marks\n",
    "              \n",
    "              chrSize = TRUE,            # show chr. size under chr.\n",
    "              \n",
    "              squareness = 4,            # vertices squareness\n",
    "              addOTUName = TRUE,         # add OTU names\n",
    "              OTUTextSize = .7,          # font size of OTU\n",
    "              distTextChr = .5,          # separ. among chr. and text and among chr. name and indices\n",
    "              \n",
    "              legendHeight= 1,           # height of legend labels\n",
    "              legendWidth = 1,           # width of legend labels\n",
    "              fixCenBorder = TRUE,       # use chrColor as border color of cen. or cen. marks\n",
    "              \n",
    "              xlimLeftMod=-2,             # modify xlim left argument of plot\n",
    "              xlimRightMod=2,            # modify xlim right argument of plot\n",
    "              ylimBotMod= .2,            # modify ylim bottom argument of plot\n",
    "              ylimTopMod=-2\n",
    "              \n",
    "              ,chromatids=FALSE          # do not show separ. chromatids\n",
    "              \n",
    "              ,useOneDot=TRUE\n",
    "              \n",
    "              ,circularPlot = TRUE       # circularPlot\n",
    "              ,shrinkFactor = .9         # percentage 1 = 100% of circle with chr.\n",
    "              ,circleCenter = 3          # X coordinate of circleCenter (affects legend pos.)\n",
    "              ,chrLabelSpacing = .9      # chr. names spacing\n",
    "              \n",
    "              ,OTUsrt = 0                # angle for OTU name (or number)\n",
    "              ,OTUplacing = \"number\"     # Use number and legend instead of name\n",
    "              ,OTULabelSpacerx = -0.6    # modify position of OTU label, when OTUplacing=\"number\" or \"simple\"\n",
    "              ,OTUlegendHeight = 1.5     # space among OTU names when in legend - OTUplacing\n",
    "              ,separFactor = 0.75        # alter separ. of kar.\n",
    ")\n",
    ")\n",
    "#dev.off() # close png"
   ]
  }
 ],
 "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": "4.1.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}