Example of BioPython #1329 (broken version)

JupyterGenomeDiagram.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.70'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import Bio as biopy\n",
    "biopy.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from Bio.Graphics import GenomeDiagram\n",
    "from Bio.SeqFeature import SeqFeature, FeatureLocation\n",
    "from IPython.display import display, Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bio.Graphics.GenomeDiagram._Feature.Feature at 0x1058d8e10>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_diagram = GenomeDiagram.Diagram(\"Test diagram\")\n",
    "gd_track_for_features = gd_diagram.new_track(1, name=\"Annotated Features\")\n",
    "gd_feature_set = gd_track_for_features.new_set()\n",
    "gd_feature_set.add_feature(SeqFeature(FeatureLocation(5, 10), strand=+1),name=\"gene 1\",sigil=\"BIGARROW\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAFHkHABBF3gEARJF3\nAABR5B0AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAFHkHABBF3gEARJF3\nAABR5B0AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAFHkHABBF3gEARJF3\nAABR5B0AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAFHkHABBF3gEARJF3\nAABR5B0AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAFHkHABBF3gEARJF3\nAABR5B0AQBR5BwAQRd4BAESRdwAAUeQdAEAUeQcAEEXeAQBEkXcAAFHkHQBAlP8D/jCuWpjFCPYA\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_diagram.draw(format=\"linear\", orientation=\"landscape\", pagesize='A4',\n",
    "                fragments=1, start=0, end=100)\n",
    "Image(gd_diagram.write_to_string(\"PNG\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9e7bFwt+yDMqluPLseZpy7U9utKrWsaFjQ0whHlhlfPXr1//Tn/7097//XfQQ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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gd_diagram.draw(format=\"circular\", orientation=\"landscape\", pagesize='A4',\n",
    "                fragments=1, start=0, end=100)\n",
    "Image(gd_diagram.write_to_string(\"PNG\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}