build training data label.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from lib import text_searcher as searcher"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f = open(\"training_terms.tsv\", \"r\", encoding=\"utf-8\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'生活費', '食物', '交通', '衣物', '醫療', '大賣場', '飲料'}\n"
     ]
    }
   ],
   "source": [
    "labels = set()\n",
    "for row in f:\n",
    "    r = row.strip(\"\\n\").split(\"\\t\")\n",
    "    \n",
    "    l = r[1].split(\" \")\n",
    "    for lab in l:\n",
    "        labels.add(lab)\n",
    "    \n",
    "print(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "labelFile = open(\"label.txt\", \"w\", encoding=\"utf-8\")\n",
    "for label in labels:\n",
    "    labelFile.write(label + \"\\n\")\n",
    "    \n",
    "labelFile.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "labelF = open(\"label.txt\", \"r\", encoding=\"utf-8\")\n",
    "dic = dict()\n",
    "for i, term in enumerate(labels):\n",
    "    dic[term] = i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'生活費': 0, '衣物': 3, '交通': 2, '醫療': 4, '食物': 1, '大賣場': 5, '飲料': 6}\n"
     ]
    }
   ],
   "source": [
    "print(dic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " len(dic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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