structure_graphs/yong_brainsim_randomization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9b41cf26-d1c2-4e20-97fa-9e51df98b7b9",
   "metadata": {},
   "source": [
    "# Yong (永) Brainsim \n",
    "Tribute to BRAINSIM, a neural network on the Commodore 64 \n",
    "\n",
    "My discussion (with @nickm) on BRAINSIM can be found in the archive of the Critical Code Studies Working Group 2022: https://wg.criticalcodestudies.com/index.php?p=/discussion/117/brainsim-neural-network-on-a-commodore-64-2022-code-critique#latest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "70db2505-37c4-45a0-aca6-94da2f5e310f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "28cb06d8-6efe-47c5-932b-7ceeeaa2849f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# a representation of \"永\" in matrix notation\n",
    "yong_grid = [[0,0,0,0,1,1,0,0,0,0],\n",
    "             [0,0,1,1,1,1,0,0,1,0],\n",
    "             [0,0,0,0,0,1,0,1,0,0],\n",
    "             [0,0,0,0,0,1,1,0,0,0],\n",
    "             [0,1,1,1,1,1,1,0,0,0],\n",
    "             [0,0,0,1,0,1,1,0,0,0],\n",
    "             [0,0,1,0,0,1,0,1,0,0],\n",
    "             [0,1,0,0,0,1,0,0,1,0],\n",
    "             [0,0,0,1,0,1,0,0,0,0],\n",
    "             [0,0,0,0,1,1,0,0,0,0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "4fabcbef-6471-46b3-b2d2-a40d175ea5d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 0 0 0 1 1 0 0 0 0]\n",
      " [0 0 1 1 1 1 0 0 1 0]\n",
      " [0 0 0 0 0 1 0 1 0 0]\n",
      " [0 0 0 0 0 1 1 0 0 0]\n",
      " [0 1 1 1 1 1 1 0 0 0]\n",
      " [0 0 0 1 0 1 1 0 0 0]\n",
      " [0 0 1 0 0 1 0 1 0 0]\n",
      " [0 1 0 0 0 1 0 0 1 0]\n",
      " [0 0 0 1 0 1 0 0 0 0]\n",
      " [0 0 0 0 1 1 0 0 0 0]]\n"
     ]
    }
   ],
   "source": [
    "print(np.matrix(yong_grid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "2c97a665-f732-4e6a-a65d-15230f4c4b34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "im = plt.imshow(yong_grid, cmap=\"copper_r\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "88b311f4-e2cc-494d-9e24-714816303460",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns; sns.set()\n",
    "ax = sns.heatmap(yong_grid, annot=True, fmt=\"d\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "9f113e8b-b4f3-4633-ae25-0c8f52cd9131",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "# access item in matrix\n",
    "# notation is [column][row]\n",
    "print(yong_grid[0][4])\n",
    "print(yong_grid[0][5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "432f0ba2-6e6f-4e75-92b0-60edfa334e91",
   "metadata": {},
   "outputs": [],
   "source": [
    "twenty_p_one = [1,1,0,0,0,0,0,0,0,0]\n",
    "twenty_p_zero = [0,0,1,1,1,1,1,1,1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "b8de1127-f19b-4c9b-a8e2-f199af0cc965",
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import math\n",
    "z_count = 0\n",
    "one_count = 0\n",
    "import math\n",
    "for i in range(10):\n",
    "    for j in range(10):\n",
    "        if yong_grid[i][j] == 0:\n",
    "            # reassign\n",
    "            yong_grid[i][j] = random.choice(twenty_p_one)  \n",
    "        else:\n",
    "            yong_grid[i][j] = random.choice(twenty_p_zero)         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "a650e08a-9a56-45ca-b230-e3c15308d4e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.heatmap(yong_grid, annot=True, fmt=\"d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "539a820f-d146-441f-add1-329c76b73e4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lists for 5%, 10% and 15% randomization\n",
    "five_p_one = [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]\n",
    "five_p_zero = [0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]\n",
    "ten_p_one = [1,0,0,0,0,0,0,0,0,0]\n",
    "ten_p_zero = [0,1,1,1,1,1,1,1,1,1]\n",
    "fifteen_p_one = [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0]\n",
    "fifteen_p_zero = [0,1,1,1,1,1,1,1,1,1,1,1,1,1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "0bcb9ea5-8cca-429b-8c23-65ff435d7592",
   "metadata": {},
   "outputs": [],
   "source": [
    "# random image generator\n",
    "# generate heatmap and save in folder \n",
    "def randImg(list_zero, list_one):\n",
    "    z_count = 0\n",
    "    one_count = 0\n",
    "    for i in range(10):\n",
    "        for j in range(10):\n",
    "            if yong_grid[i][j] == 0:\n",
    "                yong_grid[i][j] = random.choice(list_zero)  \n",
    "            else:\n",
    "                yong_grid[i][j] = random.choice(list_one) \n",
    "    ax = sns.heatmap(yong_grid, annot=True, fmt=\"d\")\n",
    "    # clear randomization; reassign var yong_grid hold values of original text input matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "95d3568c-082a-4343-80b9-9004521817bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# call function with 5%\n",
    "# clear randomization; reassign var yong_grid hold values of original text input matrix\n",
    "yong_grid = [[0,0,0,0,1,1,0,0,0,0],\n",
    "             [0,0,1,1,1,1,0,0,1,0],\n",
    "             [0,0,0,0,0,1,0,1,0,0],\n",
    "             [0,0,0,0,0,1,1,0,0,0],\n",
    "             [0,1,1,1,1,1,1,0,0,0],\n",
    "             [0,0,0,1,0,1,1,0,0,0],\n",
    "             [0,0,1,0,0,1,0,1,0,0],\n",
    "             [0,1,0,0,0,1,0,0,1,0],\n",
    "             [0,0,0,1,0,1,0,0,0,0],\n",
    "             [0,0,0,0,1,1,0,0,0,0]]\n",
    "randImg(five_p_zero, five_p_one)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "506f97b0-e44d-401c-81b5-6d43d9933944",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# call function with 10%\n",
    "yong_grid = [[0,0,0,0,1,1,0,0,0,0],\n",
    "             [0,0,1,1,1,1,0,0,1,0],\n",
    "             [0,0,0,0,0,1,0,1,0,0],\n",
    "             [0,0,0,0,0,1,1,0,0,0],\n",
    "             [0,1,1,1,1,1,1,0,0,0],\n",
    "             [0,0,0,1,0,1,1,0,0,0],\n",
    "             [0,0,1,0,0,1,0,1,0,0],\n",
    "             [0,1,0,0,0,1,0,0,1,0],\n",
    "             [0,0,0,1,0,1,0,0,0,0],\n",
    "             [0,0,0,0,1,1,0,0,0,0]]\n",
    "randImg(ten_p_zero, ten_p_one)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "bf3dd55e-6614-4b9d-9e99-8e81f957bfa9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWQAAAD/CAYAAADGzawUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAl1klEQVR4nO3de1RVZf4/8DccosQ8ICgIWnmbDJvUURunmzoI4ioUaSobtOVvLGiNQo1d1NC4CGX0ncYcUcsuDg5mfv1WJuRXraF+/nDKWt3UwEaRvB5Abh4FFThn//5wSRJw2Nt99j7PeXy/WnstOeyzP8+zz/bT43P2sz8+iqIoICIij/P1dAOIiOgiJmQiIkEwIRMRCYIJmYhIEEzIRESCYEImIhIEEzIRkQa5ubmIiorCsGHD8J///KfTfRwOB7KyshAdHY2YmBhs3rxZ1bGZkImINJg0aRI2bNiA/v37d7lPYWEhjh49ip07d2LTpk1YuXIljh8/3u2xmZCJiDQYO3YswsPDXe6zbds2PPjgg/D19UVwcDCio6Oxffv2bo/t565GEhF5K7vdDrvd3uF1q9UKq9Wq+Xg2mw0RERFtP4eHh6OysrLb95makFtqDpsZzhQ9Iu4xLda5k//PtFhm9ssssp4/M/tlpmv6DNb1fi35Jn/jR8jLy+vwekpKClJTU3W1QwuOkIlITk6H6l1nz56NhISEDq9fyegYuDgiPnnyJEaMGAGg44i5K0zIRCQnR6vqXa90aqIrU6ZMwebNmzF58mQ0NDTgk08+wYYNG7p9H7/UIyIpKYpT9aZFTk4Oxo8fj8rKSvzpT3/CfffdBwBISkrCvn37AADx8fEYMGAAJk+ejIceegjz5s3DDTfc0O2xfcx8/CbnkPWRdQ7ULLKeP84hd675+D7V+/oPuE1XLHfhlAURyUnjyFcEwk5ZvPM/W/HQnCfwm4lTsTjnFa+Pc0nv3kH4n81v4nT9QZQf3IOHH55uSBwz+2VWn8yMxevCu2J1yulQvwlC2BFy3z4hePz/PIzde77GhQvNXh/nkpV/fwHNzS2IGDASo0beiq0frsfevaUoLe18CeaVMrNfZvXJzFi8LrwrVqc4QnafmIl3YdL4OxEU6L5vPj0ZBwACAnrg/oR7kZH5X2hsbMLuf3+FwqKPMWvmH9wey6x+mdknGc8fIG+/zIzVGcXRqnoThaqEXF9fj7KyMpSVlaG+vt7oNknr5psHw+Fw4ODBn7/c3Lv3BwwfPsyDrdLHzD7JeP4AefvlcU6n+k0QLqcsjh49iueffx6lpaUIDQ0FAFRXV2P48OHIysrCwIEDzWijNK7v2ROnT59p99rp02fQ6/qeHmqRfmb2ScbzB8jbL4/zwikLlwl5wYIFSExMxLp16+Dre3Ew7XQ6UVhYiIULF2LTpk2mNFIWZxsbYbX2avea1doLZ842eqhF+pnZJxnPHyBvvzxOoC/r1HI5ZdHQ0IBp06a1JWMA8PX1RXx8PE6fPm1442Tzn/8chp+fBUOHDmp7bcSI4Sgt/dGDrdLHzD7JeP4AefvlcYpT/SYIlwk5KCgIRUVFuHztiKIo2Lp1q1uXGXamtdWBCxea4XA44XA6ceFCM1pb3f9/PLPiAEBT0zl8sOV/kZnxDAICeuDOO8Zi2tTJKNjwnttjmdUvM/sk4/kD5O2XmbE65WhVvwnC5Uq9n376CRkZGSgrK0NYWBgAoKqqCrfccgsyMzMxeLC2lTRaVuqteqsAa95uv/b7z3NmYt6jszTFNDqO1hVZvXsH4c03XkH0pPGora1H2pIX8e67W1S9V8uKLDP7padPWsl4/gDv6ZcWemPpXal3Ye8O1fteOyJWVyx3UbV0uq6uDjabDcDFpxgFBwdfUTAundZH1qW/ZpH1/HHpdOfOf79N9b7XjbxXVyx3UbUwJDg4+IqTMBGRRwg0N6yWsCv1iIh0Eej+YrWYkIlIThwhExEJwtHi6RZoxoRMRHLilAURkSA4ZUFGkvFWNNKPt9h1gSNkIiJBMCETEYlB4Zd6RESC4BwyEZEgvHDKQtgSTixy6h1xZI3F60I/jxc59cLHbwo7QmaRU++II2ssXhf6ebzIKUfI7sMip+LHkTkWrwv9PF3k1BtHyMImZBmZVcxS1sKjshYDlfG6EEJrq/pNEMJOWcjIrGKWshYelbUYqIzXhRAEGvmqdcUj5KlTp7qzHVcFs4pZylp4VNZioDJeF0JwOtVvgnA5Qj506FCXv6uvr3d7Y2R3eTHLQ4cqABhTzNKsODLHMpOM14UQvHCE7DIhx8XFoX///uisylNDQ4NRbQJwsUCiw+FoVyDRYrHAz8/ilXGA9sUskx9/BqNG3oppUyfjngnxXhlH5li8LvQz8xx2SqCRr1ouE3L//v3xzjvvtBU4vdyECRMMaxQAvJ6/sV2BxKIdxYYUYzQrziUpqWl4841XYDuxF7W19ZiX+pwhtxyZFUfWWLwu9DP7HHbghSNkl0VOc3NzERMTg9GjR3f4XU5ODpYsWaIpGIuckifJWuTUTGaeQ71FTs/991LV+/Z4KF1XLHdxOUJeuHBhl7/TmoyJiEzV9VhTWLztjYjkJNscMhGR12JCJiIShEFf6lVUVGDRokVoaGhAUFAQcnNzMXDgwHb71NbW4rnnnoPNZkNLSwt+97vfYcmSJfDzc51yuXSaiOTkcKjfNMjIyEBiYiJ27NiBxMREpKd3/ELwtddew5AhQ1BYWIjCwkL88MMP2LlzZ7fH5giZiOSkYcrCbrfDbrd3eN1qtcJq/fnhSLW1tSgtLcW6desAXFyrkZ2djbq6OgQHB7ft5+Pjg8bGRjidTjQ3N6OlpaXT24d/iQlZJ68q+igoWW8RMwuvwS5oSMj5+fnIy8vr8HpKSgpSU1PbfrbZbAgLC4PFcnFxi8ViQWhoKGw2W7uEPHfuXKSmpuLuu+/GuXPnMHPmTIwZM6bbdjAhE5GcNMwhz549GwkJCR1ev3x0rMX27dsxbNgw5Ofno7GxEUlJSdi+fTumTJni8n1MyEQkJcWp/j7kX05NdCU8PBxVVVVwOBywWCxwOByorq5GeHh4u/0KCgrw4osvwtfXF7169UJUVBT27NnTbULml3pEJCcDnvYWEhKCyMhIFBUVAQCKiooQGRnZbroCAAYMGIBdu3YBAJqbm/H555/jV7/6VbfHZ0ImIjkZdJdFZmYmCgoKEBsbi4KCAmRlZQEAkpKSsG/fPgBAWloavv76a0ydOhXTp0/HwIED8dBDD3V7bJfPsnA3GZ9lQfqZ9aWerM+ykPVLPb3PsmhaOVf1vgGpq3XFchdhR8gyVp1mLP1YdVofWa+LTsn2gHpPkrHqNGPpx6rT+sh6XXSKDxdyn5iJdwEAfjhwEFXVNV4fh7H0u1Q1eeRvJnWompy2eJlbY5l5/mTtl5mxOiXQyFctYacsiH5J1qrJsvbL45yK+k0QLhNyfX09Fi9ejDlz5mDDhg3tfnf56hUiM8haNVnWfnmcQXdZGMllQs7IyEBgYCAefvhhfPLJJ0hJSUFraysA4NixY6Y0kOgSWasmy9ovT1OcTtWbKFwm5CNHjmDBggWYPHky3n77bfTt2xePP/44Lly4YFb7iNpcXjX5EhmqJsvaL4+Tbcqiufnnb0Z9fHyQkZGBm2++GcnJyYYn5dZWBy5caG5Xsba11f3/tDArDmPpd3nV5ICAHrjzjrGYNnUyCja85/ZYZp4/WftlZqxOKU71myBcLgxJTk5GUlISbr/99navL1++HGvXrkVZWZmmYFoWhqx6q6BdxVoAhlSsNSsOY3VNyyKK3r2D8OYbryB60njU1tYjbcmLePfdLareq2UBhZl9ArynX1rojaV3YUjj0pmq9+2ZvqH7nUzgMiE3NDTAx8cHgYGBHX536NAhDB06VFMwrtSjznClnj5cqde5xvSHVe/bc+m7umK5i8v7kIOCgrr8ndZkTERkKoGmItQSdmEIEZEuAn1ZpxYTMhFJSaTb2dRiQiYiOXGETEQkCCZkIiJBCLQkWi0mZOqUjJWgeSva1UVLTT1RMCETkZyYkImIBMG7LIiIBMERMhG
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fifteen percent\n",
    "yong_grid = [[0,0,0,0,1,1,0,0,0,0],\n",
    "             [0,0,1,1,1,1,0,0,1,0],\n",
    "             [0,0,0,0,0,1,0,1,0,0],\n",
    "             [0,0,0,0,0,1,1,0,0,0],\n",
    "             [0,1,1,1,1,1,1,0,0,0],\n",
    "             [0,0,0,1,0,1,1,0,0,0],\n",
    "             [0,0,1,0,0,1,0,1,0,0],\n",
    "             [0,1,0,0,0,1,0,0,1,0],\n",
    "             [0,0,0,1,0,1,0,0,0,0],\n",
    "             [0,0,0,0,1,1,0,0,0,0]]\n",
    "randImg(fifteen_p_zero, fifteen_p_one)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c9a8f88b-6b44-4587-a4b8-46ed9fd26b14",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO\n",
    "# clear randomization; reassign var yong_grid hold values of original text input matrix\n",
    "# add annotation to specify level of randomization \n",
    "# run 100 times and save pictures"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}