443 lines
11 KiB
Plaintext
443 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"![Logo 1](https://git.wmi.amu.edu.pl/AITech/Szablon/raw/branch/master/Logotyp_AITech1.jpg)\n",
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"<div class=\"alert alert-block alert-info\">\n",
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"<h1> Ekstrakcja informacji </h1>\n",
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"<h2> 3. <i>Entropia</i> [ćwiczenia]</h2> \n",
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"<h3> Jakub Pokrywka (2022)</h3>\n",
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"</div>\n",
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"\n",
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"![Logo 2](https://git.wmi.amu.edu.pl/AITech/Szablon/raw/branch/master/Logotyp_AITech2.jpg)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: dahuffman in /home/kuba/anaconda3/lib/python3.8/site-packages (0.4.1)\r\n"
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]
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}
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],
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"source": [
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"!pip install dahuffman"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"from collections import Counter\n",
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"from dahuffman import HuffmanCodec"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Wprowadzenie"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"tekst = 'Ala ma kota. Jarek ma psa'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"codec = HuffmanCodec.from_data(tekst)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Counter({'A': 1,\n",
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" 'l': 1,\n",
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" 'a': 6,\n",
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" ' ': 5,\n",
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" 'm': 2,\n",
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" 'k': 2,\n",
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" 'o': 1,\n",
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" 't': 1,\n",
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" '.': 1,\n",
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" 'J': 1,\n",
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" 'r': 1,\n",
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" 'e': 1,\n",
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" 'p': 1,\n",
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" 's': 1})"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Counter(tekst)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Bits Code Value Symbol\n",
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" 2 00 0 ' '\n",
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" 2 01 1 'a'\n",
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" 4 1000 8 't'\n",
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" 5 10010 18 _EOF\n",
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" 5 10011 19 '.'\n",
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" 5 10100 20 'A'\n",
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" 5 10101 21 'J'\n",
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" 5 10110 22 'e'\n",
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" 5 10111 23 'l'\n",
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" 4 1100 12 'k'\n",
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" 4 1101 13 'm'\n",
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" 5 11100 28 'o'\n",
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" 5 11101 29 'p'\n",
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" 5 11110 30 'r'\n",
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" 5 11111 31 's'\n"
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]
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}
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],
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"source": [
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"codec.print_code_table()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{' ': (2, 0),\n",
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" 'a': (2, 1),\n",
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" 't': (4, 8),\n",
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" _EOF: (5, 18),\n",
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" '.': (5, 19),\n",
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" 'A': (5, 20),\n",
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" 'J': (5, 21),\n",
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" 'e': (5, 22),\n",
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" 'l': (5, 23),\n",
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" 'k': (4, 12),\n",
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" 'm': (4, 13),\n",
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" 'o': (5, 28),\n",
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" 'p': (5, 29),\n",
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" 'r': (5, 30),\n",
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" 's': (5, 31)}"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"codec.get_code_table()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"encoded = codec.encode(tekst)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'1010010111010011010100110011100100001100110010101011111010110110000110101001110111111011'"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"\"{:08b}\".format(int(encoded.hex(),16))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"A l a"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"101001 10111 01"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'Ala ma kota. Jarek ma psa'"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"codec.decode(encoded)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"25"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(tekst)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"11"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(encoded)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Zadanie 1 ( 30 punktów)\n",
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"\n",
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"Weź teksty:\n",
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"- z poprzednich zajęć (lub dowolny inny) w języku naturalnym i obetnij do długości 100_000 znaków\n",
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"- wygenerowany losowo zgodnie z rozkładem jednostajnym dyskretnym z klasy [a-zA-Z0-9 ] o długości 100_000 znaków\n",
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"- wygenerowany losowo zgodnie z rozkładem geometrycznym (wybierz p między 0.2 a 0.8) z klasy [a-zA-Z0-9 ] o długości 100_000 znaków\n",
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"- wygenerowany losowo zgodnie z rozkładem jednostajnym dwupunktowym p=0.5 z klasy [01] o długości 100_000 znaków\n",
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"- wygenerowany losowo zgodnie z rozkładem jednostajnym dwupunktowym p=0.9 z klasy [01] o długości 100_000 znaków\n",
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"\n",
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"Następnie dla każdego z tekstów trakując je po znakach:\n",
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"- skompresuj plik za pomocą dowolnego progrmu (zip, tar lub inny)\n",
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"- policz entropię\n",
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"- wytrenuj kodek huffmana i zakoduj cały tekst\n",
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"- zdekoduj pierwsze 3 znaki (jako zera i jedynki) wypisz je (z oddzieleniem na znaki)\n",
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"- zakodowany tekst zapisz do pliku binarnego, zapisz również tablicę kodową\n",
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"- porównaj wielkość pliku tekstowego, skompresowanego pliku tekstowego (zip, ...) oraz pliku skompresowanego hofmmanem (wraz z kodekiem)\n",
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"\n",
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"Uzupełnij poniższe tabelki oraz wnioski (conajmniej 5 zdań).\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### START ZADANIA"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Entropia\n",
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" \n",
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"| | Entropia |\n",
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"| ----------- | ----------- |\n",
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"| tekst w jęz. naturalnym | |\n",
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"| losowy tekst (jednostajny) | |\n",
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"| losowy tekst (geometryczny)| |\n",
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"| losowy tekst (dwupunktowy 0.5) | |\n",
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"| losowy tekst (dwupunktowy 0.9) | |\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Wielkości w bitach:\n",
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" \n",
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"| | Plik nieskompresowany | Plik skompresowany (zip, tar,.. ) | Plik skompresowany + tablica kodowa) |\n",
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"| ----------- | ----------- |-----------|----------- |\n",
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"| tekst w jęz. naturalnym | | | |\n",
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"| losowy tekst (jednostajny) | | | |\n",
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"| losowy tekst (geometryczny)| | | |\n",
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"| losowy tekst (dwupunktowy 0.5)| | | |\n",
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"| losowy tekst (dwupunktowy 0.9)| | | |"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Wnioski:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### KONIEC ZADANIA"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Zadanie 2 \n",
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"\n",
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"Powtórz kroki z zadania 1, tylko potraktuje wiadomości jako słowa (oddzielone spacją). Jeżeli występują więcej niż jedna spacja równocześnie- usuń je.\n",
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" \n",
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"Do wniosków dopisz koniecznie porównanie między kodowaniem hoffmana znaków i słów.\n",
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"\n",
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"### START ZADANIA"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Entropia\n",
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" \n",
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"| | Entropia |\n",
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"| ----------- | ----------- |\n",
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"| tekst w jęz. naturalnym | |\n",
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"| losowy tekst (dyskretny) | |\n",
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"| losowy tekst (geometryczny)| |\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Wielkości w bitach:\n",
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" \n",
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"| | Plik nieskompresowany | Plik skompresowany (zip, tar,.. ) | Plik skompresowany + tablica kodowa) |\n",
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"| ----------- | ----------- |-----------|----------- |\n",
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"| tekst w jęz. naturalnym | | | |\n",
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"| losowy tekst (jednostajny) | | | |\n",
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"| losowy tekst (geometryczny)| | | |\n",
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"| losowy tekst (dwupunktowy 0.5)| | | |\n",
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"| losowy tekst (dwupunktowy 0.9)| | | |"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Wnioski:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### KONIEC ZADANIA"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## WYKONANIE ZADAŃ\n",
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"Zgodnie z instrukcją 01_Kodowanie_tekstu.ipynb"
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]
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}
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],
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"metadata": {
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"author": "Jakub Pokrywka",
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"email": "kubapok@wmi.amu.edu.pl",
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"lang": "pl",
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.3"
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},
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"subtitle": "0.Informacje na temat przedmiotu[ćwiczenia]",
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"title": "Ekstrakcja informacji",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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