labs

'labs3'
'labs2'
2024-06-23 23:57:31 +02:00 · 2024-04-20 19:56:41 +02:00 · 2024-04-20 16:54:31 +02:00 · 2024-04-20 16:00:10 +02:00
9 changed files with 2336 additions and 65 deletions
--- a/lab/lab_01.ipynb
+++ b/lab/lab_01.ipynb
@ -251,10 +251,40 @@
    "tm_lookup('Wciśnij przycisk [ENTER]')"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "36510584-d363-444d-bfdb-2f0260d197cd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Press the ENTER button']"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "translation_memory = [('Wciśnij przycisk Enter', 'Press the ENTER button'), \n",
+    "                      ('Sprawdź ustawienia sieciowe', 'Check the network settings')]\n",
+    "\n",
+    "def tm_lookup(sentence):\n",
+    "    return [entry[1] for entry in translation_memory if entry[0].lower() == sentence.lower()]\n",
+    "\n",
+    "#tm_lookup('Wciśnij przycisk Enter') # -> ['Press the ENTER button'] OK\n",
+    "tm_lookup('Wciśnij przycisk ENTER') # -> ['Press the ENTER button'] OK"
+   ]
+  },
  {
   "cell_type": "markdown",
   "id": "choice-committee",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
   "source": [
    "### Ćwiczenie 2: zmodyfikuj funkcję tm_lookup w taki sposób, aby nie brała pod uwagę znaków interpunkcyjnych. Rada - zdefiniuj funkcję sentence_similar."
   ]
@ -299,6 +329,66 @@
    "tm_lookup('Wymagane ponowne uruchomienie maszyny')"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "25af95de-30e0-468c-8c0c-2478ce0d8856",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "wciśnijprzyciskenter\n",
+      "wciśnijprzyciskenter\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'Press the ENTER button'"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import re\n",
+    "translation_memory = [('Wciśnij przycisk Enter', 'Press the ENTER button'), \n",
+    "                      ('Sprawdź ustawienia sieciowe', 'Check the network settings')]\n",
+    "\n",
+    "def sentence_cleanup(sentence):\n",
+    "    x = sentence.replace(\" \", \"\")\n",
+    "    x = x.replace(\"\\s\", \"\")\n",
+    "    x = x.replace(\"\\t\", \"\")\n",
+    "    x = x.replace(\"\\v\", \"\")\n",
+    "    x = x.replace(\"\\n\", \"\")\n",
+    "    x = x.replace(\"\\r\", \"\")\n",
+    "    x = x.replace(\"\\f\", \"\")\n",
+    "    x = x.replace(\".\", \"\")\n",
+    "    x = x.replace(\"!\", \"\")\n",
+    "    x = x.replace(\":\", \"\")\n",
+    "    x = x.replace('?', \"\")\n",
+    "    x = x.replace(\";\", \"\")\n",
+    "    x = x.replace('\"', \"\")\n",
+    "    x = x.lower()\n",
+    "    print(x)\n",
+    "    return x\n",
+    "\n",
+    "def tm_lookup(sentence):\n",
+    "    for entry in translation_memory:\n",
+    "        part1 = entry[0]\n",
+    "        part2 = entry[1]\n",
+    "        better_sentence = sentence_cleanup(sentence)\n",
+    "        better_entry = sentence_cleanup(part1)\n",
+    "        if better_entry == better_sentence:\n",
+    "            return part2\n",
+    "\n",
+    "tm_lookup('Wciśnij przycisk:ENTER!') # -> ['Press the ENTER button'] OK"
+   ]
+  },
  {
   "cell_type": "markdown",
   "id": "guided-tutorial",
@ -409,6 +499,34 @@
    "Odpowiedź:"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "6347bc85-194d-45c4-a30d-5e5e06033821",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('przycisk', 'button'), ('drukarka', 'printer')]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "glossary = [('komputer', 'computer'), ('przycisk', 'button'), ('drukarka', 'printer')]\n",
+    "\n",
+    "def glossary_lookup(sentence):\n",
+    "    better_sentence = sentence.lower()\n",
+    "    sentence_words = better_sentence.split()\n",
+    "    return [entry for entry in glossary if entry[0] in sentence_words]\n",
+    "\n",
+    "glossary_lookup('Każda DRUKARKA posiada PrzycisK wznowienia drukowania')"
+   ]
+  },
  {
   "cell_type": "markdown",
   "id": "objective-matthew",
@ -424,8 +542,14 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "glossary = [('komputer', 'computer'), ('przycisk', 'button'), ('drukarka', 'printer')]\n",
+    "\n",
    "def glossary_lookup(sentence):\n",
-    "    return ''"
+    "    better_sentence = sentence.lower()\n",
+    "    sentence_words = better_sentence.split()\n",
+    "    return [entry for entry in glossary if entry[0] in sentence_words]\n",
+    "\n",
+    "glossary_lookup('Każda DRUKARKA posiada PrzycisK wznowienia drukowania')"
   ]
  },
  {
@ -452,7 +576,7 @@
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@ -467,7 +591,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.2"
  },
  "subtitle": "1. Podstawowe techniki wspomagania tłumaczenia",
  "title": "Komputerowe wspomaganie tłumaczenia",
--- a/lab/lab_02.ipynb
+++ b/lab/lab_02.ipynb
@ -223,17 +223,17 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
   "id": "secondary-wrist",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
-       "2"
+       "3"
      ]
     },
-     "execution_count": 5,
+     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
@ -344,21 +344,70 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 19,
   "id": "genetic-cradle",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wciśnij przycisk Enter -> Wciśnij przycisk Enter [ SCORE = 1.0 ]\n",
+      "Wciśnij przycisk Enter -> Wciśnij przycisk ENTER [ SCORE = 0.8181818181818181 ]\n",
+      "Wciśnij przycisk Enter -> Wciśnij przycisk Enter! [ SCORE = 0.9565217391304348 ]\n"
+     ]
+    }
+   ],
   "source": [
+    "#!pip3 install python-Levenshtein\n",
+    "from Levenshtein import distance as levenshtein_distance\n",
+    "\n",
+    "translation_memory = [\n",
+    "                      ('Wciśnij przycisk Enter', 'Press the ENTER button'),\n",
+    "                      ('Wciśnij przycisk ENTER', 'Press the ENTER button'), \n",
+    "                      ('Wciśnij przycisk Enter!', 'Press the ENTER button!'), \n",
+    "                      ('Wciśnij przycisk', 'Press the button'), \n",
+    "                      ('Wciśnij Enter', 'Press the ENTER'), \n",
+    "                      ('Sprawdź ustawienia sieciowe', 'Check the network settings'),\n",
+    "                      ('Drukarka jest wyłączona', 'The printer is switched off'),\n",
+    "                      ('Wymagane ponowne uruchomienie komputera', 'System restart required')\n",
+    "                     ]\n",
+    "\n",
+    "def levenshtein_similarity(x,y):\n",
+    "    return 1 - levenshtein_distance(x,y) / max(len(x), len(y))\n",
+    "\n",
    "def fuzzy_lookup(sentence, threshold):\n",
-    "    return []"
+    "    for entry in translation_memory:\n",
+    "        part1 = entry[0]\n",
+    "        score = levenshtein_similarity(sentence, part1)\n",
+    "        if score >= threshold:\n",
+    "            print(sentence + ' -> ' + part1 + ' [ SCORE = ' + str(score) + ' ]')\n",
+    "\n",
+    "fuzzy_lookup('Wciśnij przycisk Enter', 0.8)"
   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8b7bb6aa-5aaf-4f49-84ab-edbe6797d568",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3b095fff-71a8-44a9-b809-d872ee9a7b62",
+   "metadata": {},
+   "outputs": [],
+   "source": []
  }
 ],
 "metadata": {
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@ -373,7 +422,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.2"
  },
  "subtitle": "2. Zaawansowane użycie pamięci tłumaczeń",
  "title": "Komputerowe wspomaganie tłumaczenia",
--- a/lab/lab_03.ipynb
+++ b/lab/lab_03.ipynb
@ -63,7 +63,14 @@
   "id": "diverse-sunglasses",
   "metadata": {},
   "source": [
-    "Odpowiedź:"
+    "Odpowiedź:\n",
+    "\n",
+    "slides of metal cabinet\n",
+    "\n",
+    "Źródła - tłumaczono z PL -> ENG oraz ENG -> PL\n",
+    "https://translate.google.pl/?hl=pl&sl=en&tl=pl&text=metal%20cabinet%20slides&op=translate\n",
+    "\n",
+    "https://www.deepl.com/pl/translator#en/pl/slides%20of%20metal%20cabinet"
   ]
  },
  {
@ -128,13 +135,50 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 97,
   "id": "cognitive-cedar",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "program(14, 21)\n",
+      "program(291, 298)\n",
+      "program(468, 475)\n",
+      "program(516, 523)\n",
+      "program(533, 540)\n",
+      "application(80, 91)\n",
+      "application(164, 175)\n",
+      "application(322, 333)\n",
+      "applet(302, 308)\n",
+      "compile(56, 63)\n"
+     ]
+    }
+   ],
   "source": [
-    "def terminology_lookup():\n",
-    "    return []"
+    "import re\n",
+    "\n",
+    "text = \" For all Java programmers:\"\n",
+    "text += \" This section explains how to compile and run a Swing application from the command line.\"\n",
+    "text += \" For information on compiling and running a Swing application using NetBeans IDE,\"\n",
+    "text += \" see Running Tutorial Examples in NetBeans IDE. The compilation instructions work for all Swing programs\"\n",
+    "text += \" — applets, as well as applications. Here are the steps you need to follow:\"\n",
+    "text += \" Install the latest release of the Java SE platform, if you haven't already done so.\"\n",
+    "text += \" Create a program that uses Swing components. Compile the program. Run the program.\"\n",
+    "\n",
+    "dictionary = ['program', 'application', 'applet', 'compile']\n",
+    "\n",
+    "def terminology_lookup():    \n",
+    "    for entry in dictionary:\n",
+    "        p = r\"\\b\" + entry + \"\\w+\" \n",
+    "        p1 = r\"\\b\" + entry\n",
+    "        re_pattern = re.compile(p1)\n",
+    "        match = re_pattern.finditer(text)\n",
+    "        for x in match:\n",
+    "            print(entry + str(x.span()))\n",
+    "            \n",
+    "terminology_lookup()"
   ]
  },
  {
@ -407,7 +451,7 @@
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@ -422,7 +466,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.2"
  },
  "subtitle": "3. Terminologia",
  "title": "Komputerowe wspomaganie tłumaczenia",
--- a/lab/lab_08.ipynb
+++ b/lab/lab_08.ipynb
@ -57,13 +57,62 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
   "id": "moving-clothing",
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "Fraction.__new__() got an unexpected keyword argument '_normalize'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[6], line 35\u001b[0m\n\u001b[0;32m     32\u001b[0m predictions \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthe\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpicture\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mthe\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpicture\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mby\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mme\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m     34\u001b[0m \u001b[38;5;66;03m# Calculate BLEU score with weights\u001b[39;00m\n\u001b[1;32m---> 35\u001b[0m score \u001b[38;5;241m=\u001b[39m \u001b[43msentence_bleu\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreference\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpredictions\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     36\u001b[0m \u001b[38;5;28mprint\u001b[39m(score)\n",
+      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\nltk\\translate\\bleu_score.py:107\u001b[0m, in \u001b[0;36msentence_bleu\u001b[1;34m(references, hypothesis, weights, smoothing_function, auto_reweigh)\u001b[0m\n\u001b[0;32m     20\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msentence_bleu\u001b[39m(\n\u001b[0;32m     21\u001b[0m     references,\n\u001b[0;32m     22\u001b[0m     hypothesis,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     25\u001b[0m     auto_reweigh\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m     26\u001b[0m ):\n\u001b[0;32m     27\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m     28\u001b[0m \u001b[38;5;124;03m    Calculate BLEU score (Bilingual Evaluation Understudy) from\u001b[39;00m\n\u001b[0;32m     29\u001b[0m \u001b[38;5;124;03m    Papineni, Kishore, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002.\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    105\u001b[0m \u001b[38;5;124;03m    :rtype: float / list(float)\u001b[39;00m\n\u001b[0;32m    106\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 107\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcorpus_bleu\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    108\u001b[0m \u001b[43m        \u001b[49m\u001b[43m[\u001b[49m\u001b[43mreferences\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mhypothesis\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweights\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msmoothing_function\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mauto_reweigh\u001b[49m\n\u001b[0;32m    109\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\nltk\\translate\\bleu_score.py:210\u001b[0m, in \u001b[0;36mcorpus_bleu\u001b[1;34m(list_of_references, hypotheses, weights, smoothing_function, auto_reweigh)\u001b[0m\n\u001b[0;32m    206\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m references, hypothesis \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(list_of_references, hypotheses):\n\u001b[0;32m    207\u001b[0m     \u001b[38;5;66;03m# For each order of ngram, calculate the numerator and\u001b[39;00m\n\u001b[0;32m    208\u001b[0m     \u001b[38;5;66;03m# denominator for the corpus-level modified precision.\u001b[39;00m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, max_weight_length \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m):\n\u001b[1;32m--> 210\u001b[0m         p_i \u001b[38;5;241m=\u001b[39m \u001b[43mmodified_precision\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreferences\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhypothesis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    211\u001b[0m         p_numerators[i] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m p_i\u001b[38;5;241m.\u001b[39mnumerator\n\u001b[0;32m    212\u001b[0m         p_denominators[i] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m p_i\u001b[38;5;241m.\u001b[39mdenominator\n",
+      "File \u001b[1;32m~\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\nltk\\translate\\bleu_score.py:368\u001b[0m, in \u001b[0;36mmodified_precision\u001b[1;34m(references, hypothesis, n)\u001b[0m\n\u001b[0;32m    364\u001b[0m \u001b[38;5;66;03m# Ensures that denominator is minimum 1 to avoid ZeroDivisionError.\u001b[39;00m\n\u001b[0;32m    365\u001b[0m \u001b[38;5;66;03m# Usually this happens when the ngram order is > len(reference).\u001b[39;00m\n\u001b[0;32m    366\u001b[0m denominator \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28msum\u001b[39m(counts\u001b[38;5;241m.\u001b[39mvalues()))\n\u001b[1;32m--> 368\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mFraction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnumerator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdenominator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_normalize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;31mTypeError\u001b[0m: Fraction.__new__() got an unexpected keyword argument '_normalize'"
+     ]
+    }
+   ],
   "source": [
-    "def calculate_bleu():\n",
-    "    return 0"
+    "#!pip install nltk\n",
+    "#from nltk.translate.bleu_score import sentence_bleu, corpus_bleu\n",
+    "#import zipfile\n",
+    "#archive = zipfile.ZipFile('./data/corpus_corrected.zip', 'r')\n",
+    "#reference1 = archive.read('corpus_the_human.txt')\n",
+    "#reference2 = archive.read('corpus_the_nmt.txt')\n",
+    "#translation = archive.read('corpus_en.txt')\n",
+    "\n",
+    "# Prepare the reference sentences\n",
+    "#reference1 = ['I', 'love', 'eating', 'ice', 'cream']\n",
+    "#reference2 = ['I', 'enjoy', 'eating', 'ice', 'cream']\n",
+    "#translation = ['I', 'love', 'eating', 'ice', 'cream']\n",
+    "\n",
+    "#bleu_score = sentence_bleu([reference1, reference2], translation)\n",
+    "#print(\"BLEU Score: \", bleu_score)\n",
+    "# Calculate the BLEU score for a single sentence\n",
+    "\n",
+    "#def calculate_bleu(reference1,reference2,translation):\n",
+    "#    bleu_score = sentence_bleu([reference1, reference2], translation)\n",
+    "#    print(\"BLEU Score: \", bleu_score)\n",
+    "#    return bleu_score\n",
+    "#\n",
+    "#calculate_bleu(reference1,reference2,translation)\n",
+    "\n",
+    "# V2\n",
+    "from nltk.translate.bleu_score import sentence_bleu, corpus_bleu \n",
+    "# Define your desired weights (example: higher weight for bi-grams)\n",
+    "weights = (0.25, 0.25, 0, 0)  # Weights for uni-gram, bi-gram, tri-gram, and 4-gram \n",
+    "# Reference and predicted texts (same as before)\n",
+    "reference = [[\"the\", \"picture\", \"is\", \"clicked\", \"by\", \"me\"],\n",
+    "             [\"this\", \"picture\", \"was\", \"clicked\", \"by\", \"me\"]]\n",
+    "predictions = [\"the\", \"picture\", \"the\", \"picture\", \"by\", \"me\"]\n",
+    " \n",
+    "# Calculate BLEU score with weights\n",
+    "score = sentence_bleu(reference, predictions, weights=weights)\n",
+    "print(score)"
   ]
  },
  {
@ -190,15 +239,12 @@
 "metadata": {
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
-  "lang": "pl",
-  "subtitle": "8. Wykorzystanie tłumaczenia automatycznego we wspomaganiu tłumaczenia",
-  "title": "Komputerowe wspomaganie tłumaczenia",
-  "year": "2021",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
+  "lang": "pl",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
@ -209,8 +255,11 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  }
+   "version": "3.12.2"
+  },
+  "subtitle": "8. Wykorzystanie tłumaczenia automatycznego we wspomaganiu tłumaczenia",
+  "title": "Komputerowe wspomaganie tłumaczenia",
+  "year": "2021"
 },
 "nbformat": 4,
 "nbformat_minor": 5
--- a/lab/lab_09-10.ipynb
+++ b/lab/lab_09-10.ipynb
--- a/lab/lab_11.ipynb
+++ b/lab/lab_11.ipynb
@ -187,15 +187,12 @@
 "metadata": {
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
-  "lang": "pl",
-  "subtitle": "11. Urównoleglanie",
-  "title": "Komputerowe wspomaganie tłumaczenia",
-  "year": "2021",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
+  "lang": "pl",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
@ -206,8 +203,11 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  }
+   "version": "3.12.2"
+  },
+  "subtitle": "11. Urównoleglanie",
+  "title": "Komputerowe wspomaganie tłumaczenia",
+  "year": "2021"
 },
 "nbformat": 4,
 "nbformat_minor": 5
--- a/lab/lab_12.ipynb
+++ b/lab/lab_12.ipynb
@ -154,15 +154,12 @@
 "metadata": {
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
-  "lang": "pl",
-  "subtitle": "12. Key logging",
-  "title": "Komputerowe wspomaganie tłumaczenia",
-  "year": "2021",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
+  "lang": "pl",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
@ -173,8 +170,11 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  }
+   "version": "3.12.2"
+  },
+  "subtitle": "12. Key logging",
+  "title": "Komputerowe wspomaganie tłumaczenia",
+  "year": "2021"
 },
 "nbformat": 4,
 "nbformat_minor": 5
--- a/lab/lab_13-14.ipynb
+++ b/lab/lab_13-14.ipynb
@ -201,7 +201,7 @@
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@ -216,7 +216,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.12.2"
  },
  "subtitle": "13,14. Korekta pisowni",
  "title": "Komputerowe wspomaganie tłumaczenia",
--- a/lab/lab_15.ipynb
+++ b/lab/lab_15.ipynb
@ -155,7 +155,7 @@
  "author": "Rafał Jaworski",
  "email": "rjawor@amu.edu.pl",
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@ -170,7 +170,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.12.2"
  },
  "subtitle": "15. Korekta gramatyczna",
  "title": "Komputerowe wspomaganie tłumaczenia",
Author	SHA1	Message	Date
kamil kubiak	bd8ec052b5	labs	2024-06-23 23:57:31 +02:00
Kamil Kubiak	959cf021a0	'labs3'	2024-04-20 19:56:41 +02:00
Kamil Kubiak	9a3d25dac1	'labs2'	2024-04-20 16:54:31 +02:00
Kamil Kubiak	1f7c4d72ad	'labs1'	2024-04-20 16:00:10 +02:00