structure_strings/bp_nichol/alphabet_game.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6975250a-539e-40bd-ac35-4204ff4e3181",
   "metadata": {},
   "outputs": [],
   "source": [
    "# program to counter letter occurances in a string, or a word\n",
    "# methods modified from \n",
    "# https://www.geeksforgeeks.org/python-program-to-find-occurrence-to-each-character-in-given-string/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "365acaac-fc9e-461c-83e4-9235af75bfac",
   "metadata": {},
   "source": [
    "The Alphabet Game: a bpNichol Reader featured a \"Easter Pome\". Easter Pome grows from two words, \"pulpit\" and \"tulip\". <br>\n",
    "pulpit：<br>\n",
    "p 2 <br>\n",
    "u 1 <br>\n",
    "l 1 <br>\n",
    "i 1 <br>\n",
    "t 1 <br>\n",
    "\n",
    "tulip：<br>\n",
    "p 1<br>\n",
    "u 1<br>\n",
    "l 1<br>\n",
    "i 1<br>\n",
    "t 1<br>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "acee5120-ae82-4a9f-bbfb-14148e17d4ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tulip is composed of these letters and occurances :\n",
      "  {'u': 1, 't': 1, 'i': 1, 'p': 1, 'l': 1}\n",
      "pulpit is composed of these letters and occurances :\n",
      "  {'u': 1, 't': 1, 'i': 1, 'p': 2, 'l': 1}\n"
     ]
    }
   ],
   "source": [
    "# 法一\n",
    "def set_counter(inp_str):\n",
    "    # using set() + count() to get count\n",
    "    # of each element in string\n",
    "    out = {x : inp_str.count(x) for x in set(inp_str )}\n",
    "    # printing result\n",
    "    print (\"{} is composed of these letters and occurances :\\n  \".format(inp_str)+ str(out))\n",
    "\n",
    "set_counter(\"tulip\")\n",
    "set_counter(\"pulpit\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0bf4971c-7490-4dbf-910e-0502d9593a17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tulip composed of these letters and occurances : \n",
      "{'t': 1, 'u': 1, 'l': 1, 'i': 1, 'p': 1}\n",
      "pulpit composed of these letters and occurances : \n",
      "{'p': 2, 'u': 1, 'l': 1, 'i': 1, 't': 1}\n"
     ]
    }
   ],
   "source": [
    "# 法二\n",
    "# initializing string\n",
    "def freq_dict(inp_str):\n",
    "    # frequency dictionary\n",
    "    freq = {}\n",
    "    \n",
    "    for ele in inp_str:\n",
    "        if ele in freq:\n",
    "            freq[ele] += 1\n",
    "        else:\n",
    "            freq[ele] = 1\n",
    "    # printing result\n",
    "    print (\"{} composed of these letters and occurances : \\n\".format(inp_str)+ str(freq))\n",
    "\n",
    "freq_dict(\"tulip\")\n",
    "freq_dict(\"pulpit\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a2ce38d4-9407-4e05-a82a-e38667c18367",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tulip is composed of these letters and occurances :\n",
      " Counter({'t': 1, 'u': 1, 'l': 1, 'i': 1, 'p': 1})\n",
      "pulpit is composed of these letters and occurances :\n",
      " Counter({'p': 2, 'u': 1, 'l': 1, 'i': 1, 't': 1})\n"
     ]
    }
   ],
   "source": [
    "# 法三\n",
    "from collections import Counter\n",
    "\n",
    "def collection_counter(inp_str):\n",
    "\n",
    "    # using collections.Counter() to get\n",
    "    # count of each element in string\n",
    "    oup = Counter(inp_str)\n",
    "\n",
    "    # printing result\n",
    "    print (\"{} is composed of these letters and occurances :\\n \".format(inp_str)+ str(oup))\n",
    "\n",
    "collection_counter(\"tulip\")\n",
    "collection_counter(\"pulpit\")\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bf3deb3-467d-4056-8a1b-1df257508356",
   "metadata": {},
   "outputs": [],
   "source": [
    "# this program can take two input words can see if they are anagrams? \n",
    "# isAnagram \n",
    "# hester mofet \n",
    "# are there anagrams in non-alphabetical word arrangements? yes, but in scalable units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4f079374-28d7-4c44-935c-7d26fe9f4691",
   "metadata": {},
   "outputs": [],
   "source": [
    "# method to see if a pair of words are anagrams to each other\n",
    "def set_counter(inp_str):\n",
    "    return {x : inp_str.count(x) for x in set(inp_str )}\n",
    "\n",
    "def areAnagrams(str1, str2):\n",
    "    out1 = {}\n",
    "    out2 = {}\n",
    "    #apply set counter method to each of the words and store the output \n",
    "    out1 = set_counter(str1)\n",
    "    out2 = set_counter(str2)\n",
    "    # compare output \n",
    "    if out1 == out2:\n",
    "        return True\n",
    "    else: \n",
    "        return False "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1f4fab84-aeec-4b6f-af67-a76d2af5e20c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "~~~~~~~~~~~~~~~~~~~~movie still from The Silence of Lamb to for a pair of anagrams ~~~~~~~~~~~~\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f14448dbd00>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Python program to read\n",
    "# image using matplotlib\n",
    "\n",
    "# importing matplotlib modules\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Read Images\n",
    "img = mpimg.imread('therestofme.jpg')\n",
    "\n",
    "# Output Images\n",
    "print(\"~~~~~~~~~~~~~~~~~~~~movie still from The Silence of Lamb to for a pair of anagrams ~~~~~~~~~~~~\")\n",
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3df449e7-93d0-499b-8ea5-84bdba8cd165",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "areAnagrams(\"hestermofet\",\"therestofme\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b517982e-ef53-4424-8a2c-5baf2cdccb1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "areAnagrams(\"hester mofet\",\"the rest of me\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7af1e993-ca08-41eb-924e-d66b44a3480d",
   "metadata": {},
   "source": [
    "in this case the empty strings are also counted. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8970375e-8108-41a8-87cc-e3983c1deb50",
   "metadata": {},
   "source": [
    "    "
   ]
  }
 ],
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