retrieve_steps_variables.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nanopub import Publication, NanopubClient\n",
    "from rdflib import Graph, URIRef, RDF, FOAF, ConjunctiveGraph\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nanopub import NanopubClient\n",
    "client = NanopubClient()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_assertion_to_graph(graph, np_uri):\n",
    "    # Fetch the nanopublication at the specified URI\n",
    "    publication = client.fetch(np_uri)\n",
    "\n",
    "    # Print the RDF contents of the nanopublication\n",
    "    #print(publication)\n",
    "\n",
    "    # Iterate through all triples in the assertion graph\n",
    "    for s, p, o in publication.assertion:\n",
    "        #print(s, p, o)\n",
    "        graph.add((s, p, o))\n",
    "    \n",
    "    return graph\n",
    "\n",
    "def add_np_to_graph(graph, np_uri):\n",
    "    # Fetch the nanopublication at the specified URI\n",
    "    publication = client.fetch(np_uri)\n",
    "\n",
    "    # Print the RDF contents of the nanopublication\n",
    "    #print(publication)\n",
    "\n",
    "    # Iterate through all triples in the assertion graph\n",
    "    quads = publication.rdf.quads()\n",
    "        #print (s, p, o, g)\n",
    "    graph.addN(quads)\n",
    "    #graph = graph + publication.rdf\n",
    "    \n",
    "    return graph\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "g_schema = ConjunctiveGraph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "g_schema.load('data/rdf/whole-user-nanopublications.nq', format=\"nquads\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "qtext= \"\"\" \n",
    "PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>\n",
    "PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>\n",
    "PREFIX p-plan: <http://purl.org/net/p-plan#> \n",
    "select DISTINCT ?s where { \n",
    "?s p-plan:isStepOfPlan  ?o .\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = g_schema.query(qtext)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "g1 = ConjunctiveGraph()\n",
    "complete ={}\n",
    "for r in results:\n",
    "    step_uri = str(r[0])\n",
    "    print (str(r[0]))\n",
    "    results = client.find_nanopubs_with_pattern(subj=step_uri)\n",
    "    for p in results:\n",
    "        np_uri= p['np']\n",
    "        if np_uri not in complete:\n",
    "            complete[np_uri] = True\n",
    "            #print (p)\n",
    "            g1= add_np_to_graph(g1, np_uri) \n",
    "    #g_biolink.add(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "g1.serialize('data/rdf/steps.nq', format=\"nquads\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "qtext= \"\"\" \n",
    "PREFIX p-plan: <http://purl.org/net/p-plan#> \n",
    "PREFIX prov: <http://www.w3.org/ns/prov#>\n",
    "select DISTINCT ?o where { \n",
    "\t?s prov:hasMember  ?o .\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = g_schema.query(qtext)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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    }
   ],
   "source": [
    "g1 = ConjunctiveGraph()\n",
    "complete ={}\n",
    "for r in results:\n",
    "    step_uri = str(r[0])\n",
    "    print (str(r[0]))\n",
    "    results = client.find_nanopubs_with_pattern(subj=step_uri)\n",
    "    for p in results:\n",
    "        np_uri= p['np']\n",
    "        if np_uri not in complete:\n",
    "            complete[np_uri] = True\n",
    "            #print (p)\n",
    "            g1= add_assertion_to_graph(g1, np_uri) \n",
    "    #g_biolink.add(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "g1.serialize('data/rdf/steps_prov.nq', format=\"nquads\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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