usage/KB.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "920b3138-bb1e-4792-a306-175fd47a7c63",
   "metadata": {},
   "source": [
    "# Load and render Knowledge Bases\n",
    "Copyright (c) 2022 Siemens AG Oesterreich\n",
    "SPDX-License-Identifier: MIT\n",
    "\n",
    "\n",
    "- How to load a knowledge base from a list of facts with the clorm integration.\n",
    "- How to render a knowledge based with the clingraph integration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e964b3d8-2994-4d9d-8b10-a809a262266c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/susana/Documents/Education/PhD/ExternalProjects/OOASP/asp_interactive_configuration\n"
     ]
    }
   ],
   "source": [
    "%cd .."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46c83134-2ead-4f47-8f93-b6b962f689c3",
   "metadata": {},
   "source": [
    "### Knowledge Base\n",
    "\n",
    "Import the `OOASPKnowledgeBase` classs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "250072bb-f5b1-46a5-b1bd-60e2e4d0f527",
   "metadata": {},
   "outputs": [],
   "source": [
    "from ooasp.kb import OOASPKnowledgeBase"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08285908-c554-49b2-9a9f-e02f006e1bad",
   "metadata": {},
   "source": [
    "Create an `OOASPKnowledgeBase` from a logic program"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49d97d2d-89b3-4c3e-9ac2-6d115f2867ff",
   "metadata": {},
   "source": [
    "#### Racks example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1d1e2028-644f-4769-bcb4-0d450c22242e",
   "metadata": {},
   "outputs": [],
   "source": [
    "racks_kb = OOASPKnowledgeBase.from_file(\"racks_v1\",\"./examples/racks/kb.lp\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d36b8e32-a445-4381-a8ea-e54e890abb13",
   "metadata": {},
   "source": [
    "Print the object (This uses the asp string representation of the factbase)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "51882435-b617-4e54-9d69-ec21f8f1f02c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "%---- OOASPKnowledgeBase (racks_v1) ------\n",
      "ooasp_assoc(rack_frames,rack,1,1,frame,4,8).\n",
      "ooasp_assoc(frame_modules,frame,1,1,module,0,5).\n",
      "ooasp_assoc(element_modules,element,0,1,module,1,4).\n",
      "ooasp_assoc(rack_framesS,rackSingle,0,1,frame,4,4).\n",
      "ooasp_assoc(rack_framesD,rackDouble,0,1,frame,8,8).\n",
      "ooasp_assoc(element_modules1,elementA,1,1,moduleI,1,1).\n",
      "ooasp_assoc(element_modules2,elementB,1,1,moduleII,2,2).\n",
      "ooasp_assoc(element_modules3,elementC,1,1,moduleIII,3,3).\n",
      "ooasp_assoc(element_modules4,elementD,1,1,moduleIV,4,4).\n",
      "ooasp_assoc_specialization(rack_framesS,rack_frames).\n",
      "ooasp_assoc_specialization(rack_framesD,rack_frames).\n",
      "ooasp_assoc_specialization(element_modules1,element_modules).\n",
      "ooasp_assoc_specialization(element_modules2,element_modules).\n",
      "ooasp_assoc_specialization(element_modules3,element_modules).\n",
      "ooasp_assoc_specialization(element_modules4,element_modules).\n",
      "ooasp_attr(frame,frame_position,enumint).\n",
      "ooasp_attr_maxInclusive(frame,frame_position,8).\n",
      "ooasp_attr_minInclusive(frame,frame_position,1).\n",
      "ooasp_class(object).\n",
      "ooasp_class(rack).\n",
      "ooasp_class(rackSingle).\n",
      "ooasp_class(rackDouble).\n",
      "ooasp_class(frame).\n",
      "ooasp_class(element).\n",
      "ooasp_class(elementA).\n",
      "ooasp_class(elementB).\n",
      "ooasp_class(elementC).\n",
      "ooasp_class(elementD).\n",
      "ooasp_class(module).\n",
      "ooasp_class(moduleI).\n",
      "ooasp_class(moduleII).\n",
      "ooasp_class(moduleIII).\n",
      "ooasp_class(moduleIV).\n",
      "ooasp_class(moduleV).\n",
      "ooasp_special_cv(unique,(rack_frames,frame,frame_position)).\n",
      "ooasp_subclass(rack,object).\n",
      "ooasp_subclass(rackSingle,rack).\n",
      "ooasp_subclass(rackDouble,rack).\n",
      "ooasp_subclass(frame,object).\n",
      "ooasp_subclass(element,object).\n",
      "ooasp_subclass(elementA,element).\n",
      "ooasp_subclass(elementB,element).\n",
      "ooasp_subclass(elementC,element).\n",
      "ooasp_subclass(elementD,element).\n",
      "ooasp_subclass(module,object).\n",
      "ooasp_subclass(moduleI,module).\n",
      "ooasp_subclass(moduleII,module).\n",
      "ooasp_subclass(moduleIII,module).\n",
      "ooasp_subclass(moduleIV,module).\n",
      "ooasp_subclass(moduleV,module).\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(racks_kb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "88167f76-5eca-40c4-80cb-d860ce57f78c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('element_modules', 'module', 1, 4)}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "racks_kb.associations('element')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "71ed36f2-6f15-4672-b1f1-a646732106d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "racks_kb.save_png(\"examples/racks\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "699dce56-889e-405c-91a0-b6f9c2e13504",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(\"examples/racks/racks_v1.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06c257aa-dcdf-4f11-ba6d-4376037eb1a8",
   "metadata": {},
   "source": [
    "Query the factbase like a database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "135e8b04-4872-435a-a670-25036f96b9d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "clorm_class = racks_kb.UNIFIERS.Class\n",
    "clorm_subclass = racks_kb.UNIFIERS.SubClass\n",
    "q = racks_kb.fb.query(clorm_class,clorm_subclass).join(clorm_class.name==clorm_subclass.sub_class)\n",
    "q = q.where(clorm_subclass.super_class==\"rack\").select(clorm_class)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b5e8c55a-8304-4682-a67c-90cc9e61ff3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ooasp_class(rackSingle), ooasp_class(rackDouble)]\n"
     ]
    }
   ],
   "source": [
    "print(list(q.all()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "25d6eab0-ec7b-4ea7-8687-51e95fc6a5ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['rackSingle', 'rackDouble']\n"
     ]
    }
   ],
   "source": [
    "print([c.name for c in q.all()])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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