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Bug476-Zha
Author | SHA1 | Date |
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俞黄焘 | a39b0bb8e5 | |
俞黄焘 | ce9e18e3fe |
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@ -8,6 +8,7 @@
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import pickle
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import math
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from wordfreqCMD import remove_punctuation, freq, sort_in_descending_order, sort_in_ascending_order
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import snowballstemmer
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def load_record(pickle_fname):
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@ -18,6 +19,12 @@ def load_record(pickle_fname):
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def difficulty_level_from_frequency(word, d):
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"""
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根据单词的频率进行难度的评级
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:param word:
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:param d:
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:return:
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"""
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level = 1
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if not word in d:
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return level
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@ -30,27 +37,62 @@ def difficulty_level_from_frequency(word, d):
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return level
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def get_difficulty_level(d1, d2):
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def get_difficulty_level_for_words_and_tests(dic):
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"""
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对原本的单词库中的单词进行难度评级
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:param dic: 存储了单词库pickle文件中的单词的字典
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:return:
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"""
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d = {}
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L = list(d1.keys()) # in d1, we have freuqence for each word
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L2 = list(d2.keys()) # in d2, we have test types (e.g., CET4,CET6,BBC) for each word
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L.extend(L2)
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L3 = list(set(L)) # L3 contains all words
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for k in L3:
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if k in d2:
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if 'CET4' in d2[k]:
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d[k] = 4 # CET4 word has level 4
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elif 'CET6' in d2[k]:
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d[k] = 6
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elif 'BBC' in d2[k]:
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d[k] = 8
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if k in d1: # BBC could contain easy words that are not in CET4 or CET6. So 4 is not reasonable. Recompute difficulty level.
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d[k] = min(difficulty_level_from_frequency(k, d1), d[k])
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elif k in d1:
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d[k] = difficulty_level_from_frequency(k, d1)
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L = list(dic.keys()) # in dic, we have test types (e.g., CET4,CET6,BBC) for each word
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return d
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for k in L:
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if 'CET4' in dic[k]:
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d[k] = 4 # CET4 word has level 4
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elif 'CET6' in dic[k]:
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d[k] = 6
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elif 'BBC' in dic[k]:
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d[k] = 8
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# print(k, d[k])
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return d # {'apple': 4, ...}
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def simplify_the_words_dict(dic):
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"""
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用于把保存了词库中评级后的词新建一个以词根为键、以同词根的最低等级为值
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"""
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stem = snowballstemmer.stemmer('english')
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res = {}
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for j in dic: # j 在字典中
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temp = stem.stemWord(j) # 提取j得词根
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if not temp in res: # 如果这个词根不在结果字典中,则以词根为键、以dic中的等级作为值添加
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res[temp] = dic[j]
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else: # 如果这个词在结果词典中,则比较一下单词的难度等级是否最小
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if res[temp] > dic[j]:
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res[temp] = dic[j]
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return res
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def get_difficulty_level(d1, d2):
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"""
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d2 来自于词库的27000个已标记单词
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d1 你个老六不会的词
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在d2的后面添加单词,没有新建一个新的字典
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"""
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d2 = get_difficulty_level_for_words_and_tests(d2) # 根据d2的标记评级{'apple': 4, 'abandon': 4, ...}
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d2_sim = simplify_the_words_dict(d2) # 提取d2的词根 {'appl': 4, 'abandon': 4, ...}
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stem = snowballstemmer.stemmer('english')
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for k in d1: # 用户的词
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for l in d2_sim: # l是词库的某个单词的词根
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if stem.stemWord(k) == l: # 两者相等则视为同一难度的词
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d2[k] = d2_sim[l] # 给d2定级
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break
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else: # 不相等则表明词库中没这词,按照单词的频率定级
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d2[k] = difficulty_level_from_frequency(k, d1)
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return d2
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def revert_dict(d):
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