{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Flybase Learner Notebook" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Install a conda package in the current Jupyter kernel\$n", "import sys\$n", "#!pip install .\n", "\n", "from hyperon import MeTTa\$n", "\n", "from pathlib import Path\$n", "program = '''\n", " (isa red color)\n", " (isa green color)\n", " (isa blue color)\n", " ;(isa comment color)\n", "\n", "!(extend-py! mettalog)\n", "\n", "!(let $space (new-fly-space)\n", " (add-atom &self (= (my-nspace) $space)))\n", "\n", "!(add-atom (my-nspace) (The user name is William))\n", "!(add-atom (my-nspace) (William is 26 years old))\n", "!(add-atom (my-nspace) (William has 2 brothers))\n", "!(add-atom (my-nspace) (Brothers names are Mike and Nick))\n", "!(add-atom (my-nspace) (Nick is 3 years older than William))\n", "!(add-atom (my-nspace) (Mike is 5 years younger than Nick))\n", "\n", "\n", "; !(match (my-nspace) (What is the user name $x) $x)\n", "; !(match (my-nspace) (How old $x is William) $x)\n", "!(match (my-nspace) (How old ($x) is Mike) $x)\n", "; !(match (my-nspace) (What $x is father name) $x)\n", "; !(match (my-nspace) (What $x is Mike age) $x)\n", "\n", " !(match &self (isa $color color) $color)\n", "\n", " (= (f) (+ 2 3))\n", " !(f)\n", "'''\n", "\n", "metta = MeTTa()\n", "[metta.run(program), metta.parse_all('red green blue'), metta.parse_all('5')]\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from __future__ import print_function\$n", "from collections import deque\$n", "\n", "import hyperonpy as hp\$n", "from hyperon.atoms import V, S, E, ValueAtom, GroundedAtom, ExpressionAtom, G, AtomType, MatchableObject, OperationAtom, OperationObject, BindingsSet, Atom\$n", "from hyperon.runner import MeTTa\$n", "from hyperon.ext import register_atoms, register_tokens\$n", "from hyperon.base import AbstractSpace, SpaceRef, GroundingSpace, interpret\$n", "# Avoid conflict for \"Atom\"\n", "from pyswip import Atom as PySwipAtom\$n", "from pyswip import Term\$n", "from hyperon.atoms import Atom as MeTTaAtom\$n", "from pyswip import Functor, registerForeign, PL_PRUNED, PL_retry, PL_FA_NONDETERMINISTIC, PL_foreign_control, PL_foreign_context, PL_FIRST_CALL, PL_REDO, Variable, Prolog as PySwip\$n", "from pyswip.easy import newModule, Query\$n", "from hyperon.atoms import *\n", "import openai\$n", "import hyperon\$n", "\n", "pySwip = PySwip()\n", "for l in pySwip.query(\"working_directory(PWD,PWD)\"):\n", " print(l)\n", "pySwip.consult(\"swi_flybase.pl\")\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": true }, "outputs": [ { "ename": "SyntaxError", "evalue": "invalid syntax (272713009.py, line 5)", "output_type": "error", "traceback": [ "\u001b[0;36m Input \u001b[0;32mIn [3]\u001b[0;36m\u001b[0m\$n\u001b[0;31m pySwip = PySwip()for l in pySwip.query(\"load_flybase\"):\u001b[0m\$n\u001b[0m ^\u001b[0m\$n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\$n" ] } ], "source": [ "from pyswip.pySwip import PySwip\$n", "#from pyswip import getList, registerForeigns\$n", "from pyswip_notebook import IsolatedPySwip\$n", "\n", "pySwip = PySwip()\n", "\n", "for l in pySwip.query(\"load_flybase\"):\n", " print(l)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'N': 'encoding', 'V': 'octet'}\n", "{'N': 'stream_type_check', 'V': 'loose'}\n", "{'N': 'message_context', 'V': ['thread']}\n", "{'N': 'quasi_quotations', 'V': 'true'}\n", "{'N': 'unknown', 'V': 'error'}\n", "{'N': 'allow_variable_name_as_functor', 'V': 'false'}\n", "{'N': 'agc_margin', 'V': 10000}\n", "{'N': 'protect_static_code', 'V': 'false'}\n", "{'N': 'xref', 'V': 'false'}\n", "{'N': 'verbose_load', 'V': 'silent'}\n", "{'N': 'verbose_file_search', 'V': 'false'}\n", "{'N': 'shift_check', 'V': 'false'}\n", "{'N': 'traditional', 'V': 'false'}\n", "{'N': 'toplevel_prompt', 'V': '~m~d~l~! ?- '}\n", "{'N': 'fileerrors', 'V': 'true'}\n", "{'N': 'xpce', 'V': 'true'}\n", "{'N': 'allow_dot_in_atom', 'V': 'false'}\n", "{'N': 'argv', 'V': []}\n", "{'N': 'write_attributes', 'V': 'ignore'}\n", "{'N': 'toplevel_print_anon', 'V': 'true'}\n", "{'N': 'error_ambiguous_stream_pair', 'V': 'false'}\n", "{'N': 'table_space', 'V': 1073741824}\n", "{'N': 'emulated_dialect', 'V': 'swi'}\n", "{'N': 'signals', 'V': 'false'}\n", "{'N': 'system_thread_id', 'V': 49047}\n", "{'N': 'compiled_at', 'V': 'Mar 31 2023, 08:09:42'}\n", "{'N': 'rational_syntax', 'V': 'compatibility'}\n", "{'N': 'var_prefix', 'V': 'false'}\n", "{'N': 'cmake_build_type', 'V': 'DEB'}\n", "{'N': 'table_subsumptive', 'V': 'false'}\n", "{'N': 'cpu_count', 'V': 8}\n", "{'N': 'optimise_debug', 'V': 'default'}\n", "{'N': 'tmp_dir', 'V': '/tmp'}\n", "{'N': 'pid', 'V': 49047}\n", "{'N': 'autoload', 'V': 'true'}\n", "{'N': 'warn_override_implicit_import', 'V': 'true'}\n", "{'N': 'debugger_show_context', 'V': 'false'}\n", "{'N': 'last_call_optimisation', 'V': 'true'}\n", "{'N': 'optimise', 'V': 'false'}\n", "{'N': 'libswipl', 'V': '/lib/x86_64-linux-gnu/libswipl.so.9'}\n", "{'N': 'debug', 'V': 'false'}\n", "{'N': 'shared_home', 'V': '/usr/share/swi-pySwip'}\n", "{'N': 'debug_on_interrupt', 'V': 'false'}\n", "{'N': 'executable', 'V': './'}\n", "{'N': 'file_name_variables', 'V': 'false'}\n", "{'N': 'executable_format', 'V': 'elf'}\n", "{'N': 'float_overflow', 'V': 'error'}\n", "{'N': 'path_max', 'V': 4096}\n", "{'N': 'threads', 'V': 'true'}\n", "{'N': 'arch', 'V': 'x86_64-linux'}\n", "{'N': 'occurs_check', 'V': 'false'}\n", "{'N': 'home', 'V': '/usr/lib/swi-pySwip'}\n", "{'N': 'float_undefined', 'V': 'error'}\n", "{'N': 'dialect', 'V': 'swi'}\n", "{'N': 'toplevel_extra_white_line', 'V': 'true'}\n", "{'N': 'qcompile', 'V': 'false'}\n", "{'N': 'answer_write_options', 'V': ['quoted(true)', 'portray(true)', 'max_depth(10)', 'spacing(next_argument)']}\n", "{'N': 'emacs_inferior_process', 'V': 'false'}\n", "{'N': 'on_warning', 'V': 'print'}\n", "{'N': 'float_zero_div', 'V': 'error'}\n", "{'N': 'compile_meta_arguments', 'V': 'false'}\n", "{'N': 'print_write_options', 'V': ['portray(true)', 'quoted(true)', 'numbervars(true)']}\n", "{'N': 'max_procedure_arity', 'V': 1024}\n", "{'N': 'char_conversion', 'V': 'false'}\n", "{'N': 'float_max_integer', 'V': 9007199254740992.0}\n", "{'N': 'message_language', 'V': 'en_US'}\n", "{'N': 'max_tagged_integer', 'V': 72057594037927935}\n", "{'N': 'gc_thread', 'V': 'false'}\n", "{'N': 'gmp_version', 'V': 6}\n", "{'N': 'toplevel_residue_vars', 'V': 'false'}\n", "{'N': 'bounded', 'V': 'false'}\n", "{'N': 'trace_gc', 'V': 'false'}\n", "{'N': 'shared_table_space', 'V': 1073741824}\n", "{'N': 'c_libs', 'V': ''}\n", "{'N': 'c_cc', 'V': '/usr/bin/cc'}\n", "{'N': 'pipe', 'V': 'true'}\n", "{'N': 'double_quotes', 'V': 'string'}\n", "{'N': 'max_table_subgoal_size_action', 'V': 'error'}\n", "{'N': 'c_ldflags', 'V': ''}\n", "{'N': 'posix_shell', 'V': '/bin/sh'}\n", "{'N': 'agc_close_streams', 'V': 'false'}\n", "{'N': 'float_min', 'V': 2.2250738585072014e-308}\n", "{'N': 'large_files', 'V': 'true'}\n", "{'N': 'max_rational_size_action', 'V': 'error'}\n", "{'N': 'shared_object_search_path', 'V': 'LD_LIBRARY_PATH'}\n", "{'N': 'character_escapes', 'V': 'true'}\n", "{'N': 'shared_object_extension', 'V': 'so'}\n", "{'N': 'max_table_answer_size_action', 'V': 'error'}\n", "{'N': 'heartbeat', 'V': 0}\n", "{'N': 'max_answers_for_subgoal_action', 'V': 'error'}\n", "{'N': 'os_argv', 'V': ['./', '-q', '--nosignals', '--home=/usr/lib/swi-pySwip']}\n", "{'N': 'access_level', 'V': 'user'}\n", "{'N': 'user_flags', 'V': 'silent'}\n", "{'N': 'stack_limit', 'V': 1073741824}\n", "{'N': 'verbose_autoload', 'V': 'false'}\n", "{'N': 'sandboxed_load', 'V': 'false'}\n", "{'N': 'portable_vmi', 'V': 'true'}\n", "{'N': 'verbose', 'V': 'silent'}\n", "{'N': 'query_debug_settings', 'V': 'debug(false, false)'}\n", "{'N': 'unix', 'V': 'true'}\n", "{'N': 'toplevel_var_size', 'V': 1000}\n", "{'N': 'toplevel_name_variables', 'V': 'true'}\n", "{'N': 'iso', 'V': 'false'}\n", "{'N': 'mitigate_spectre', 'V': 'false'}\n", "{'N': 'table_incremental', 'V': 'false'}\n", "{'N': 'table_monotonic', 'V': 'eager'}\n", "{'N': 'packs', 'V': 'true'}\n", "{'N': 'file_search_cache_time', 'V': 10}\n", "{'N': 'table_shared', 'V': 'false'}\n", "{'N': 'version_data', 'V': 'swi(9, 0, 4, [])'}\n", "{'N': 'back_quotes', 'V': 'codes'}\n", "{'N': 'optimise_unify', 'V': 'true'}\n", "{'N': 'timezone', 'V': 28800}\n", "{'N': 'float_underflow', 'V': 'ignore'}\n", "{'N': 'float_rounding', 'V': 'to_nearest'}\n", "{'N': 'vmi_builtin', 'V': 'true'}\n", "{'N': 'generate_debug_info', 'V': 'true'}\n", "{'N': 'debug_on_error', 'V': 'true'}\n", "{'N': 'toplevel_mode', 'V': 'backtracking'}\n", "{'N': 'debugger_write_options', 'V': ['quoted(true)', 'portray(true)', 'max_depth(10)', 'attributes(portray)', 'spacing(next_argument)']}\n", "{'N': 'toplevel_list_wfs_residual_program', 'V': 'true'}\n", "{'N': 'file_name_case_handling', 'V': 'case_preserving'}\n", "{'N': 'report_error', 'V': 'true'}\n", "{'N': 'version', 'V': 90004}\n", "{'N': 'debug_term_position', 'V': 'false'}\n", "{'N': 'on_error', 'V': 'print'}\n", "{'N': 'determinism_error', 'V': 'error'}\n", "{'N': 'max_char_code', 'V': 1114111}\n", "{'N': 'integer_rounding_function', 'V': 'toward_zero'}\n", "{'N': 'gc', 'V': 'true'}\n", "{'N': 'max_arity', 'V': 'unbounded'}\n", "{'N': 'colon_sets_calling_context', 'V': 'true'}\n", "{'N': 'answer_format', 'V': '~p'}\n", "{'N': 'tty_control', 'V': 'false'}\n", "{'N': 'editor', 'V': 'default'}\n", "{'N': 'abi_version', 'V': {'built_in': 2757966453, 'foreign_interface': 2, 'qlf': 68, 'qlf_min_load': 68, 'record': 3, 'vmi': 2678345669}}\n", "{'N': 'address_bits', 'V': 64}\n", "{'N': 'resource_database', 'V': '/usr/lib/swi-pySwip/boot.prc'}\n", "{'N': 'prefer_rationals', 'V': 'false'}\n", "{'N': 'toplevel_goal', 'V': 'default'}\n", "{'N': 'min_tagged_integer', 'V': -72057594037927936}\n", "{'N': 'prompt_alternatives_on', 'V': 'determinism'}\n", "{'N': 'toplevel_print_factorized', 'V': 'false'}\n", "{'N': 'c_cflags', 'V': '-fPIC -pthread'}\n", "{'N': 'c_libplso', 'V': ''}\n", "{'N': 'unload_foreign_libraries', 'V': 'false'}\n", "{'N': 'float_max', 'V': 1.7976931348623157e+308}\n", "{'N': 'malloc', 'V': 'ptmalloc'}\n", "{'N': 'open_shared_object', 'V': 'true'}\n", "{'N': 'character_escapes_unicode', 'V': 'true'}\n", "{}\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "% Started at Tue Aug 22 07:12:37 2023\$n", "% 1.333 seconds cpu time for 444,978 inferences\$n", "% 7,856 atoms, 4,612 functors, 3,215 predicates, 37 modules, 132,243 VM-codes\$n", "% \n", "% Limit Allocated In use\$n", "% Local stack: - 116 Kb 1,384 b\$n", "% Global stack: - 128 Kb 50 Kb\$n", "% Trail stack: - 34 Kb 24 b\$n", "% Total: 1,024 Mb 278 Kb 51 Kb\$n", "% \n", "% 4 garbage collections gained 344,920 bytes in 0.000 seconds.\n", "% 5 clause garbage collections gained 124 clauses in 0.000 seconds.\n", "% Stack shifts: 2 local, 1 global, 0 trail in 0.000 seconds\$n" ] } ], "source": [ " for l in pySwip.query(\"current_pySwip_flag(N,V)\"):\n", " print(l)\n", " \n", "for l in pySwip.query(\"statistics\"):\n", " print(l)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Print all facts in the knowledge base." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "male(cronus).\n", "male(pluto).\n", "male(poseidon).\n", "male(zeus).\n", "male(ares).\n", "male(hephaestus).\n", "\n", "female(rhea).\n", "female(hestia).\n", "female(hera).\n", "female(demeter).\n", "female(athena).\n", "female(hebe).\n", "female(persephone).\n", "\n", "parent(cronus, hestia).\n", "parent(cronus, pluto).\n", "parent(cronus, poseidon).\n", "parent(cronus, zeus).\n", "parent(cronus, hera).\n", "parent(cronus, demeter).\n", "parent(rhea, hestia).\n", "parent(rhea, pluto).\n", "parent(rhea, poseidon).\n", "parent(rhea, zeus).\n", "parent(rhea, hera).\n", "parent(rhea, demeter).\n", "parent(zeus, athena).\n", "parent(zeus, ares).\n", "parent(zeus, hebe).\n", "parent(zeus, hephaestus).\n", "parent(hera, ares).\n", "parent(hera, hebe).\n", "parent(hera, hephaestus).\n", "parent(zeus, persephone).\n", "parent(demeter, persephone).\n", "{}\n" ] } ], "source": [ "# \n", "for l in pySwip.query(\"listing\"):\n", " print(l)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next we add a few more complext rules." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "pySwip.assertz(\"isFather(X, Y) :- male(X), parent(X, Y)\")\n", "\n", "pySwip.assertz(\"isMother(X, Y) :- female(X), parent(X, Y)\")\n", "\n", "pySwip.assertz(\"isDaughter(X, Y) :- female(X), parent(Y, X)\")\n", "\n", "pySwip.assertz(\"isSon(X, Y) :- male(X), parent(Y, X)\")\n", "\n", "pySwip.assertz(\"isAncestor(X, Y) :- parent(X, Y)\")\n", "\n", "pySwip.assertz(\"isAncestor(X, Y) :- parent(X, T), parent(T, Y)\")" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[('TAXRANK:0000001', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000002', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000003', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000004', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000005', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000006', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000007', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000008', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000009', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000010', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000011', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000012', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000013', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000014', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000015', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000016', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000017', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000018', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000019', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000020', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000021', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000022', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000023', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000024', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000025', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000026', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000027', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000028', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000029', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000030', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000031', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000032', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000033', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000034', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000035', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000036', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000037', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000038', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000039', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000040', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000041', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000042', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000043', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000044', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000045', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000046', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000047', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000048', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000049', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000050', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000051', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000052', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000053', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000054', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000055', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000056', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000057', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000058', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000059', 'TAXRANK:0000000', 'is_a'), ('TAXRANK:0000060', 'TAXRANK:0000000', 'is_a')]\n", "['TAXRANK:0000000', 'TAXRANK:0000001', 'TAXRANK:0000002', 'TAXRANK:0000003', 'TAXRANK:0000004', 'TAXRANK:0000005', 'TAXRANK:0000006', 'TAXRANK:0000007', 'TAXRANK:0000008', 'TAXRANK:0000009', 'TAXRANK:0000010', 'TAXRANK:0000011', 'TAXRANK:0000012', 'TAXRANK:0000013', 'TAXRANK:0000014', 'TAXRANK:0000015', 'TAXRANK:0000016', 'TAXRANK:0000017', 'TAXRANK:0000018', 'TAXRANK:0000019', 'TAXRANK:0000020', 'TAXRANK:0000021', 'TAXRANK:0000022', 'TAXRANK:0000023', 'TAXRANK:0000024', 'TAXRANK:0000025', 'TAXRANK:0000026', 'TAXRANK:0000027', 'TAXRANK:0000028', 'TAXRANK:0000029', 'TAXRANK:0000030', 'TAXRANK:0000031', 'TAXRANK:0000032', 'TAXRANK:0000033', 'TAXRANK:0000034', 'TAXRANK:0000035', 'TAXRANK:0000036', 'TAXRANK:0000037', 'TAXRANK:0000038', 'TAXRANK:0000039', 'TAXRANK:0000040', 'TAXRANK:0000041', 'TAXRANK:0000042', 'TAXRANK:0000043', 'TAXRANK:0000044', 'TAXRANK:0000045', 'TAXRANK:0000046', 'TAXRANK:0000047', 'TAXRANK:0000048', 'TAXRANK:0000049', 'TAXRANK:0000050', 'TAXRANK:0000051', 'TAXRANK:0000052', 'TAXRANK:0000053', 'TAXRANK:0000054', 'TAXRANK:0000055', 'TAXRANK:0000056', 'TAXRANK:0000057', 'TAXRANK:0000058', 'TAXRANK:0000059', 'TAXRANK:0000060']\n", "61\$n", "60\$n", "True\$n", "species\$n" ] }, { "data": { "text/plain": [ "{'TAXRANK:0000000'}" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import networkx\$n", "import obonet\$n", "\n", "# Read the taxrank ontology\$n", "url = 'https://github.com/dhimmel/obonet/raw/main/tests/data/taxrank.obo'\n", "graph = obonet.read_obo(url)\n", "\n", "# Or read the xz-compressed taxrank ontology\$n", "url = 'https://github.com/dhimmel/obonet/raw/main/tests/data/taxrank.obo.xz'\n", "graph = obonet.read_obo(url)\n", "\n", "print(graph.edges)\n", "\n", "print(graph.nodes)\n", "\n", "# Number of nodes\$n", "print(len(graph))\n", "\n", "# Number of edges\$n", "print(graph.number_of_edges())\n", "\n", "# Check if the ontology is a DAG\$n", "print(networkx.is_directed_acyclic_graph(graph))\n", "\n", "# Mapping from term ID to name\$n", "id_to_name = {id_: data.get('name') for id_, data in graph.nodes(data=True)}\n", "print(id_to_name['TAXRANK:0000006']) # TAXRANK:0000006 is species\$n", "\n", "# Find all superterms of species. Note that networkx.descendants gets\$n", "# superterms, while networkx.ancestors returns subterms.\n", "networkx.descendants(graph, 'TAXRANK:0000006')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can query the knowledge base." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "true\$n" ] } ], "source": [ "# \n", "res = list(pySwip.query(\"isAncestor(rhea, persephone)\"))\n", "print(\"false\" if len(res) == 0 else \"true\")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Y': 'athena'}\n", "{'Y': 'ares'}\n", "{'Y': 'hebe'}\n", "{'Y': 'hephaestus'}\n", "{'Y': 'persephone'}\n" ] } ], "source": [ "# a more complext query with a variable\$n", "for res in pySwip.query(\"isFather(zeus, Y)\"):\n", " print(res)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Multiple instances of `IsolatedPySwip` do not interfere with each other." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{}\n", "\n", ":- dynamic is_empty/1.\n", "\n", "is_empty(another_pySwip).\n" ] } ], "source": [ "# \n", "\n", "another_pySwip = IsolatedPySwip()\n", "\n", "another_pySwip.assertz(\"is_empty(another_pySwip)\")\n", "\n", "for l in another_pySwip.query(\"listing\"):\n", " print(l)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Foreign functions from `pyswip` work as well" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Hello, john\$n", "Hello, gina\$n", "[{'X': 'john'}, {'X': 'gina'}]\n" ] } ], "source": [ "from pyswip import registerForeign\$n", "\n", "def hello(t):\n", " print(\"Hello,\", t)\n", "hello.arity = 1\$n", "\n", "registerForeign(hello)\n", "\n", "pySwip = IsolatedPySwip()\n", "pySwip.assertz(\"father(michael,john)\")\n", "pySwip.assertz(\"father(michael,gina)\")\n", "print(list(pySwip.query(\"father(michael,X), hello(X)\")))" ] } ], "metadata": { "interpreter": { "hash": "ac3e2752b8d3c7ac594336078a1da4fa888e9a385f6933a16a4c4965994955e7" }, "kernelspec": { "display_name": "MeTTa", "language": "metta", "name": "metta_kernel" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }