{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "87f95752",
   "metadata": {},
   "source": [
    "# Using MOSES to evolve programs\n",
    "\n",
    "This Jupyter notebook shows how [MOSES](https://github.com/opencog/asmoses) can be used to evolve programs and [mevis](https://pypi.org/project/mevis) can be used to visualize the results. The .ipynb file can be found [here](https://github.com/robert-haas/mevis/tree/master/examples).\n",
    "\n",
    "Sources:\n",
    "\n",
    "- OpenCog Wiki\n",
    "  - Python console: https://wiki.opencog.org/w/Python\n",
    "  - MOSES: [Meta-Optimizing Semantic Evolutionary Search](https://wiki.opencog.org/w/Meta-Optimizing_Semantic_Evolutionary_Search)\n",
    "- GitHub\n",
    "  - [asmoses](https://github.com/opencog/asmoses) with [examples/asmoses.py]((https://github.com/opencog/asmoses/blob/master/examples/asmoses.py))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbf943e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from opencog.asmoses.pyasmoses import moses\n",
    "\n",
    "import mevis as mv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d99d8bb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "moses = moses()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0bff851",
   "metadata": {},
   "source": [
    "## Define training data\n",
    "\n",
    "A list of input-output pairs\n",
    "\n",
    "- Input: first two columns\n",
    "- Output: last column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7022fd3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = [\n",
    "    [0, 0,  0],\n",
    "    [1, 1,  0],\n",
    "    [1, 0,  1],\n",
    "    [0, 1,  1],\n",
    "]\n",
    "\n",
    "print('Training data: {}'.format(input_data))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6abf9c43",
   "metadata": {},
   "source": [
    "## Evolve Python programs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3c25db6",
   "metadata": {},
   "outputs": [],
   "source": [
    "output = moses.run(input=input_data, python=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d418422",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_result = output[0]\n",
    "program_text = best_result.program.decode()\n",
    "\n",
    "print('Score:', best_result.score)\n",
    "print('\\nPython program:\\n', program_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43c83bb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = output[0].eval\n",
    "\n",
    "print('Testing model on data:')\n",
    "print('[0, 0]: {}'.format(model([0, 0])))\n",
    "print('[0, 1]: {}'.format(model([0, 1])))\n",
    "print('[1, 0]: {}'.format(model([1, 0])))\n",
    "print('[1, 1]: {}'.format(model([1, 1])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfe31179",
   "metadata": {},
   "source": [
    "## Evolve Scheme programs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a291fd1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "output = moses.run(input=input_data, scheme=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d77715a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "best_result = output[0]\n",
    "program_text = best_result.program.decode()\n",
    "\n",
    "print('Score:', best_result.score)\n",
    "print('\\nScheme program:\\n', program_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22767aaa",
   "metadata": {},
   "source": [
    "## Evolve a complex Scheme program and put it into an AtomSpace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "421bbf34",
   "metadata": {},
   "outputs": [],
   "source": [
    "from opencog.atomspace import AtomSpace\n",
    "from opencog.scheme import scheme_eval\n",
    "from opencog.utilities import set_default_atomspace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c1054b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = [\n",
    "    [0, 0, 0, 0, 0,  1],\n",
    "    [0, 0, 0, 0, 1,  0],\n",
    "    [0, 0, 0, 1, 0,  0],\n",
    "    [0, 0, 0, 1, 1,  0],\n",
    "    [0, 0, 1, 0, 0,  1],\n",
    "    [0, 0, 1, 0, 1,  0],\n",
    "    [0, 0, 1, 1, 0,  1],\n",
    "    [0, 0, 1, 1, 1,  1],\n",
    "    [0, 1, 0, 0, 0,  0],\n",
    "    [0, 1, 0, 0, 1,  1],\n",
    "    [0, 1, 0, 1, 0,  0],\n",
    "    [0, 1, 0, 1, 1,  1],\n",
    "    [0, 1, 1, 0, 0,  1],\n",
    "    [0, 1, 1, 0, 1,  1],\n",
    "    [0, 1, 1, 1, 0,  0],\n",
    "    [0, 1, 1, 1, 1,  0],\n",
    "    [1, 0, 0, 0, 0,  1],\n",
    "    [1, 0, 0, 0, 1,  1],\n",
    "    [1, 0, 0, 1, 0,  0],\n",
    "    [1, 0, 0, 1, 1,  1],\n",
    "    [1, 0, 1, 0, 0,  0],\n",
    "    [1, 0, 1, 0, 1,  1],\n",
    "    [1, 0, 1, 1, 0,  0],\n",
    "    [1, 0, 1, 1, 1,  0],\n",
    "    [1, 1, 0, 0, 0,  1],\n",
    "    [1, 1, 0, 0, 1,  1],\n",
    "    [1, 1, 0, 1, 0,  0],\n",
    "    [1, 1, 0, 1, 1,  1],\n",
    "    [1, 1, 1, 0, 0,  0],\n",
    "    [1, 1, 1, 0, 1,  1],\n",
    "    [1, 1, 1, 1, 0,  1],\n",
    "    [1, 1, 1, 1, 1,  0],\n",
    "]\n",
    "\n",
    "output = moses.run(input=input_data, scheme=True)\n",
    "best_result = output[0]\n",
    "\n",
    "score = best_result.score\n",
    "program_text = best_result.program.decode()\n",
    "\n",
    "print('Score:', best_result.score)\n",
    "print('\\nPython program:\\n', program_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d44d7019",
   "metadata": {},
   "outputs": [],
   "source": [
    "atomspace = AtomSpace()\n",
    "set_default_atomspace(atomspace)\n",
    "\n",
    "string = scheme_eval(atomspace, program_text)\n",
    "print(string.decode())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da0a5654",
   "metadata": {},
   "outputs": [],
   "source": [
    "mv.plot(atomspace, 'vis', 'dot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3a3c8db",
   "metadata": {},
   "outputs": [],
   "source": [
    "mv.store(atomspace, 'moses_result.scm', overwrite=True)\n",
    "\n",
    "graph = mv.convert(atomspace)\n",
    "mv.export(graph, 'moses_result.gml', overwrite=True)"
   ]
  }
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