forked from mrlan/EnglishPal
新建了get_difficulty_level_for_words_and_tests函数专门用于给词库单词评级,返回得到一个字典d2({'apple': 4, 'banana': 4, ...});修改get_difficulty_level函数,给用户的单词评级, 分三种情况:1.以原型出现,则无需操作,因为已经出现在d2;2.词根与词库中某单词词根相同,视为一个难度的单词;3.以上两种情况之外的词视为不在词库中的词,按照difficulty_level_from_frequency函数方法评定难度。
目前还未进行测试。SPM2023-PR44-YuGaoxiang
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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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@ -30,26 +37,44 @@ 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 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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"""
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d2 = get_difficulty_level_for_words_and_tests(d2) # 根据标记评级,仅适用于词库中的词
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stem = snowballstemmer.stemmer('english')
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for k in d1: # k是用户不会的词
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for l in d2: # l是已经完成评级的词库的词
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if k == l: # k == l,这个用户也不会的词刚好以原型的形式出现在词库中,因为词库已经评过难度了,所以啥也不用干
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break
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elif stem.stemWord(k) in l: # 这个词的词根与词库中的某个词一样,我们认为是同一难度的词
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d1[k] = d2[l]
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else: # 这个词不在词库中,按频率来评定难度
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d2[k] = difficulty_level_from_frequency(k, d1)
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return d2
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