forked from bfijalkowski/KWT-2024
lab 11-14
This commit is contained in:
Patryk
parent
824f7d373d
commit
a3dca39152
@ -52,13 +52,22 @@
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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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"execution_count": 2,
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"id": "german-dispute",
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"metadata": {},
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"outputs": [],
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"source": [
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"def sentence_split(text):\n",
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" return []"
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" def purge(text_l: str) -> str:\n",
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" return text_l.strip('.').strip()\n",
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" index = 0\n",
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" result = []\n",
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" for match in regex.finditer(r'\\. \\p{Lu}|\\n', text):\n",
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" result.append(purge(text[index:match.start(0)]))\n",
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" index = match.start(0)\n",
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" result.append(purge(text[index:len(text)]))\n",
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"\n",
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" return result"
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]
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},
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{
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@ -69,6 +78,14 @@
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"### Ćwiczenie 2: Uruchom powyższy algorytm na treści wybranej przez siebie strony internetowej (do ściągnięcia treści strony wykorzystaj kod z laboratoriów nr 7). Zidentyfikuj co najmniej dwa wyjątki od ogólnej reguły podziału na segmenty i ulepsz algorytm."
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]
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},
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{
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"cell_type": "markdown",
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"id": "20bc0bf7-35b7-44e5-8750-c22e6de9d048",
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"metadata": {},
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"source": [
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"Dwa wyjatki to zdania zakończone wykrzyknikiem i zdania zakończone znakiem zapytania"
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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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@ -76,8 +93,17 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"def sentence_split_enhanced(text):\n",
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" return []"
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"def sentence_split(text):\n",
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" def purge(text_l: str) -> str:\n",
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" return text_l.strip('.').strip('?').strip('!').strip()\n",
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" index = 0\n",
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" result = []\n",
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" for match in regex.finditer(r'(\\.|\\?|\\!) \\p{Lu}|\\n', text):\n",
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" result.append(purge(text[index:match.start(0)]))\n",
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" index = match.start(0)\n",
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" result.append(purge(text[index:len(text)]))\n",
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"\n",
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" return result"
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]
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},
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{
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@ -117,6 +143,14 @@
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"Wyjściem z Hunaligna jest plik w specjalnym formacie Hunaligna. Problem jednak w tym, że niestety nie można go w prosty sposób zaimportować do jakiegokolwiek narzędzia typu CAT. Potrzebna jest konwersja do któregoś z bardziej popularnych formatów, np. XLIFF."
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]
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},
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{
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"cell_type": "markdown",
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"id": "80360005-5110-4f83-bfd6-dbe22a1d5b5b",
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"metadata": {},
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"source": [
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"## *Linki do pobrania tego progamu(ftp://ftp.mokk.bme.hu/Hunglish/src/hunalign/latest/hunalign-1.1-windows.zip), dostępne w README na githubie, nie działają.*"
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]
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},
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{
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"cell_type": "markdown",
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"id": "divided-chain",
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@ -187,15 +221,12 @@
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"metadata": {
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"author": "Rafał Jaworski",
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"email": "rjawor@amu.edu.pl",
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"lang": "pl",
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"subtitle": "11. Urównoleglanie",
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"title": "Komputerowe wspomaganie tłumaczenia",
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"year": "2021",
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3 (ipykernel)",
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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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@ -206,8 +237,11 @@
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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": "3.8.10"
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}
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"version": "3.10.4"
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},
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"subtitle": "11. Urównoleglanie",
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"title": "Komputerowe wspomaganie tłumaczenia",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 5
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109
lab/lab_12.ipynb
109
lab/lab_12.ipynb
@ -96,6 +96,26 @@
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"### Ćwiczenie 1: Wykorzystując powyższy kod napisz keylogger, który zapisuje wszystkie uderzenia w klawisze do pliku. Format pliku jest dowolny, każdy wpis musi zawierać precyzyjną godzinę uderzenia oraz uderzony klawisz. Uruchom program i przepisz paragraf dowolnie wybranego tekstu."
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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": null,
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"id": "8663ef15-88a0-4bb5-aff9-f19cbb3178c1",
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"metadata": {},
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"outputs": [],
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"source": [
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"import keyboard\n",
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"\n",
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"\n",
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"def report_key(event: keyboard.KeyboardEvent):\n",
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" file = open('test.txt', 'a')\n",
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" file.write(f'[{event.time}] {event.name}\\n')\n",
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" file.close()\n",
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"\n",
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"\n",
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"keyboard.on_release(callback=report_key)\n",
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"keyboard.wait()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "valuable-bearing",
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@ -120,7 +140,40 @@
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"outputs": [],
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"source": [
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"def calculate_typing_speed():\n",
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" return 0"
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" import re\n",
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" import numpy\n",
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"\n",
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" def parse(line_l: str) -> (float, str):\n",
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" res = re.findall(r'(\\d+.\\d+)|([a-zA-Z,.]+)', ''.join(line_l.split()))\n",
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" return float(res[0][0]), res[1][1]\n",
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"\n",
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" file = open('test.txt', 'r')\n",
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" time_per_word = []\n",
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" time_per_character = []\n",
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" local_time_per_word = []\n",
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"\n",
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" prev_char_timestamp = None\n",
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" for line in file:\n",
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" time, key = parse(line)\n",
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" if prev_char_timestamp is None or time - prev_char_timestamp > 5:\n",
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" prev_char_timestamp = time\n",
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" local_time_per_word = []\n",
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" continue\n",
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" elapsed = time - prev_char_timestamp\n",
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" time_per_character.append(elapsed)\n",
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" if key == 'space' or key == 'enter' or key == ',' or key == '.':\n",
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" if len(local_time_per_word) > 0:\n",
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" time_per_word.append(numpy.sum(local_time_per_word))\n",
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" local_time_per_word = []\n",
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" time_per_character.append(elapsed)\n",
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" prev_char_timestamp = time\n",
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" continue\n",
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" local_time_per_word.append(elapsed)\n",
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" prev_char_timestamp = time\n",
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" file.close()\n",
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" time_per_word.append(numpy.sum(local_time_per_word))\n",
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" \n",
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" return 60 / numpy.average(time_per_character), 60 / numpy.average(time_per_word)"
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]
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},
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{
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@ -147,22 +200,57 @@
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"outputs": [],
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"source": [
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"def find_pauses():\n",
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" return []"
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" import re\n",
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"\n",
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" def parse(line_l: str) -> (float, str):\n",
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" res = re.findall(r'(\\d+.\\d+)|([a-zA-Z,.]+)', ''.join(line_l.split()))\n",
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" return float(res[0][0]), res[1][1]\n",
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"\n",
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" file = open('test.txt', 'r')\n",
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" stops = []\n",
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" stop_reporting_time = 1\n",
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"\n",
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" prev_char_timestamp = None\n",
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" lines = file.readlines()\n",
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" file.close()\n",
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" for i in range(len(lines)):\n",
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" time, key = parse(lines[i])\n",
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" if prev_char_timestamp is None:\n",
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" prev_char_timestamp = time\n",
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" continue\n",
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" elapsed = time - prev_char_timestamp\n",
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" if elapsed > stop_reporting_time:\n",
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" context_start = max(0, i - 20)\n",
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" context_end = min(len(lines), i + 20)\n",
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" context_before = ''\n",
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" context_after = ''\n",
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" for j in range(context_start, i):\n",
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" time_l, key_l = parse(lines[j])\n",
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" context_before += key_l\n",
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" for j in range(i, context_end):\n",
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" time_l, key_l = parse(lines[j])\n",
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" context_after += key_l\n",
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" stops.append((elapsed, (context_before, context_after)))\n",
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" prev_char_timestamp = time\n",
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"\n",
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" def stop_sort(record: tuple):\n",
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" return record[0]\n",
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"\n",
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" stops.sort(reverse=True, key=stop_sort)\n",
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" \n",
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" return stops"
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]
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}
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],
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"metadata": {
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"author": "Rafał Jaworski",
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"email": "rjawor@amu.edu.pl",
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"lang": "pl",
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"subtitle": "12. Key logging",
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"title": "Komputerowe wspomaganie tłumaczenia",
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"year": "2021",
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3 (ipykernel)",
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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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@ -173,8 +261,11 @@
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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": "3.8.10"
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}
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"version": "3.10.4"
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},
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"subtitle": "12. Key logging",
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"title": "Komputerowe wspomaganie tłumaczenia",
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"year": "2021"
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},
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"nbformat": 4,
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"nbformat_minor": 5
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@ -201,7 +201,7 @@
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"author": "Rafał Jaworski",
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"email": "rjawor@amu.edu.pl",
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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@ -216,7 +216,7 @@
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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": "3.8.10"
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"version": "3.10.4"
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},
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"subtitle": "13,14. Korekta pisowni",
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"title": "Komputerowe wspomaganie tłumaczenia",
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