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    "# Filter By Polymer Chain Type Demo\n",
    "\n",
    "Simple exmaple of reading an MMTF Hadoop Sequence file, filtering the entries by polymer chain type, L Protein Chain and D Saccharide Chain, and count the number of entires. This example also show show methods can be chained for a more concise syntax\n",
    "\n",
    "#### Supported polymer chain type includes  (Both string and class variable can be used a input parameter)\n",
    "\n",
    "* containsPolymerChainType.D_PEPTIDE_COOH_CARBOXY_TERMINUS = \"D-PEPTIDE COOH CARBOXY TERMINUS\"\n",
    "* containsPolymerChainType.D_PEPTIDE_NH3_AMINO_TERMINUS = \"D-PEPTIDE NH3 AMINO TERMINUS\"\n",
    "* containsPolymerChainType.D_PEPTIDE_LINKING = \"D-PEPTIDE LINKING\"\n",
    "* containsPolymerChainType.D_SACCHARIDE = \"D-SACCHARIDE\"\n",
    "* containsPolymerChainType.D_SACCHARIDE_14_and_14_LINKING = \"D-SACCHARIDE 1,4 AND 1,4 LINKING\"\n",
    "* containsPolymerChainType.D_SACCHARIDE_14_and_16_LINKING = \"D-SACCHARIDE 1,4 AND 1,6 LINKING\"\n",
    "* containsPolymerChainType.DNA_OH_3_PRIME_TERMINUS = \"DNA OH 3 PRIME TERMINUS\"\n",
    "* containsPolymerChainType.DNA_OH_5_PRIME_TERMINUS = \"DNA OH 5 PRIME TERMINUS\"\n",
    "* containsPolymerChainType.DNA_LINKING = \"DNA LINKING\"\n",
    "* containsPolymerChainType.L_PEPTIDE_COOH_CARBOXY_TERMINUS = \"L-PEPTIDE COOH CARBOXY TERMINUS\"\n",
    "* containsPolymerChainType.L_PEPTIDE_NH3_AMINO_TERMINUS = \"L-PEPTIDE NH3 AMINO TERMINUS\"\n",
    "* containsPolymerChainType.L_PEPTIDE_LINKING = \"L-PEPTIDE LINKING\"\n",
    "* containsPolymerChainType.L_SACCHARIDE = \"L-SACCHARIDE\"\n",
    "* containsPolymerChainType.L_SACCHARIDE_14_AND_14_LINKING = \"L-SACCHARDIE 1,4 AND 1,4 LINKING\"\n",
    "* containsPolymerChainType.L_SACCHARIDE_14_AND_16_LINKING = \"L-SACCHARIDE 1,4 AND 1,6 LINKING\"\n",
    "* containsPolymerChainType.PEPTIDE_LINKING = \"PEPTIDE LINKING\"\n",
    "* containsPolymerChainType.RNA_OH_3_PRIME_TERMINUS = \"RNA OH 3 PRIME TERMINUS\"\n",
    "* containsPolymerChainType.RNA_OH_5_PRIME_TERMINUS = \"RNA OH 5 PRIME TERMINUS\"\n",
    "* containsPolymerChainType.RNA_LINKING = \"RNA LINKING\"\n",
    "* containsPolymerChainType.NON_POLYMER = \"NON-POLYMER\"\n",
    "* containsPolymerChainType.OTHER = \"OTHER\"\n",
    "* containsPolymerChainType.SACCHARIDE = \"SACCHARIDE\"\n",
    "\n",
    "\n",
    "\n",
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "from mmtfPyspark.io import mmtfReader\n",
    "from mmtfPyspark.filters import *\n",
    "from mmtfPyspark.structureViewer import view_structure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configure Spark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "conf = SparkConf().setMaster(\"local[*]\") \\\n",
    "                      .setAppName(\"FilterByPolymerChainType\")\n",
    "sc = SparkContext(conf = conf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read in MMTF Files, filter and count\n",
    "\n",
    "#### * Not filter returns the opposite of a particular filter*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of pure DNA and RNA entires: 227\n"
     ]
    }
   ],
   "source": [
    "path = \"../../resources/mmtf_reduced_sample/\"\n",
    "\n",
    "structures = mmtfReader.read_sequence_file(path, sc) \\\n",
    "                  .filter(ContainsPolymerChainType(\"DNA LINKING\", ContainsPolymerChainType.RNA_LINKING)) \\\n",
    "                  .filter(NotFilter(ContainsLProteinChain())) \\\n",
    "                  .filter(NotFilter(ContainsDSaccharideChain()))\n",
    "\n",
    "print(f\"Number of pure DNA and RNA entires: {structures.count()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View Structures"
   ]
  },
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    "structure_names = structures.keys().collect()\n",
    "view_structure(structure_names, style='sphere')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Terminate Spark "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
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