Revert "Fix details"

This reverts commit d863cc1.

Author: aurelberra

2 Import corpora.ipynb

@@ -434,7 +434,7 @@
     }
    ],
    "source": [
-    "!ls -l /home/kyle/cltk_data/originals/  # To be adapted to your file system"
+    "!ls -l /home/kyle/cltk_data/originals/"
    ]
   }
  ],

3 Basic NLP.ipynb

@@ -692,32 +692,27 @@
     "# The easiest way to do this in Python is to use a list comprehension to remove stopwords\n",
     "\n",
     "from cltk.stop.latin.stops import STOPS_LIST\n",
+    "\n",
     "print(STOPS_LIST)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'cato_cltk_word_tokens_no_punt' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-730f01962f9b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcato_no_stops\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mw\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mw\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcato_cltk_word_tokens_no_punt\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mw\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mSTOPS_LIST\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# Note that the stopwords are gone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m#! Consider others you might want to add to the Latin stops list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'cato_cltk_word_tokens_no_punt' is not defined"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['interdum', 'praestare', 'mercaturis', 'rem', 'quaerere', 'periculosum', 'sit', 'item', 'foenerari', 'honestum', 'maiores', 'nostri', 'habuerunt', 'legibus', 'posiverunt', 'furem', 'dupli', 'condemnari', 'foeneratorem', 'quadrupli', 'quanto', 'peiorem', 'civem', 'existimarint', 'foeneratorem', 'furem', 'hinc', 'licet', 'existimare', 'virum', 'bonum', 'quom', 'laudabant', 'laudabant', 'bonum', 'agricolam', 'bonum', '-que', 'colonum', 'amplissime', 'laudari', 'existimabatur', 'laudabatur', 'mercatorem', 'strenuum', 'studiosum', '-que', 'rei', 'quaerendae', 'existimo', 'verum', 'supra', 'dixi', 'periculosum', 'calamitosum', 'agricolis', 'viri', 'fortissimi', 'milites', 'strenuissimi', 'gignuntur', 'maxime', '-que', 'pius', 'quaestus', 'stabilissimus', '-que', 'consequitur', 'minime', '-que', 'invidiosus', 'minime', '-que', 'male', 'cogitantes', 'sunt', 'eo', 'studio', 'occupati', 'sunt', 'nunc', 'rem', 'redeam', 'quod', 'promisi', 'institutum', 'principium', 'hoc', 'erit']\n"
      ]
     }
    ],
    "source": [
     "cato_no_stops = [w for w in cato_cltk_word_tokens_no_punt if not w in STOPS_LIST]\n",
-    "\n",
-    "# Note that the stopwords are gone\n",
-    "#! Consider others you might want to add to the Latin stops list\n",
-    "\n",
+    "# observe no stopwords\n",
+    "#! consider others you might want to add to the Latin stops list\n",
     "print(cato_no_stops)"
    ]
   }

5 Text reuse.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -11,8 +11,15 @@
     "import os\n",
     "\n",
     "div1_fp = os.path.expanduser('~/cltk_data/latin/text/latin_text_latin_library/cicero/divinatione1.txt')\n",
-    "div2_fp = os.path.expanduser('~/cltk_data/latin/text/latin_text_latin_library/cicero/divinatione2.txt')\n",
-    "\n",
+    "div2_fp = os.path.expanduser('~/cltk_data/latin/text/latin_text_latin_library/cicero/divinatione2.txt')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "with open(div1_fp) as fo:\n",
     "    div1 = fo.read()\n",
     "\n",

9 Lexical Dispersion Plot.ipynb

@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -61,8 +61,8 @@
     "                words[i] = words[i].lower()\n",
     "        if lang in [\"bn\",\"hi\",\"sa\"]:\n",
     "            tokens= i_word(text)\n",
-    "\n",
-    "    # Locating the matches of the words in the text\n",
+    "    \n",
+    "    # Locating the matches of the words in the text.    \n",
     "        x_length = len(tokens)\n",
     "        y_length = len(words)\n",
     "        x_list = []\n",
@@ -72,16 +72,17 @@
     "                if tokens[i]==words[j]:\n",
     "                    x_list.append(i+1)\n",
     "                    y_list.append(j)\n",
-    "\n",
-    "    # Creation of Dispersion Plot with Matplotlib's pyplot\n",
+    "    \n",
+    "    #Creation of Dispersion Plot with Matplotlib's pyplot.         \n",
     "        plt.plot(x_list, y_list, \"b|\", scalex=.1)\n",
     "        plt.yticks(list(range(len(words))), words, color=\"b\")\n",
     "        plt.ylim(-1, len(words))\n",
     "        plt.xlabel(\"Lexical Distribution\")\n",
     "        plt.show()\n",
-    "\n",
+    "            \n",
     "    else:\n",
-    "        print(\"Language not presently covered by CLTK or wrong language code\") "
+    "        print(\"Language not presently covered by CLTK or wrong language code\") \n",
+    "        \n"
    ]
   },
   {