From 4f305cc3a0739fa435360c82eed3b7a8c9f7b76e Mon Sep 17 00:00:00 2001 From: DaDeng Date: Thu, 9 Mar 2023 14:57:22 +0800 Subject: [PATCH] 1.8.4 --- .DS_Store | Bin 6148 -> 8196 bytes build/lib/cntext/__init__.py | 2 +- build/lib/cntext/dictionary.py | 6 +++--- build/lib/cntext/mind.py | 2 -- cntext.egg-info/PKG-INFO | 2 +- cntext/.DS_Store | Bin 0 -> 6148 bytes cntext/__init__.py | 2 +- cntext/dictionary.py | 6 +++--- cntext/mind.py | 2 -- ...-any.whl => cntext-1.8.4-py3-none-any.whl} | Bin 960994 -> 961020 bytes setup.py | 2 +- 11 files changed, 10 insertions(+), 14 deletions(-) create mode 100644 cntext/.DS_Store rename dist/{cntext-1.8.3-py3-none-any.whl => cntext-1.8.4-py3-none-any.whl} (98%) diff --git a/.DS_Store b/.DS_Store index a9aaeffe7befa02d012d0626f688d89cdb5e33a1..4f2f96daaa2ad8f8f5dc0bc1e4238d5370d56228 100644 GIT binary patch delta 287 zcmZoMXmOBWU|?W$DortDU;r^WfEYvza8E20o2aMAD7Z0TH}hr%jz7$c**Q2SHn1=X zPUc}*Ik}UCck&;W1`$IeOC1Fx6VqB9g=$L^6CDLpQ}f9aSdAsw7?K(C7)lsY87de` 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min_count=5, ngram=False): + def train(self, input_txt_file, model_name='w2v.model', vector_size=100, window_size=6, min_count=5, ngram=False): """ train word2vec model for corpus :param input_txt_file: corpus file path :param model_name: used as model name(save) :param vector_size: dimensionality of the word vectors. + :param window_size: window size for word2vec :param min_count: Set the word to appear at least min_count times in the model :param ngram: whether to take the ngram case into account,default False :return: @@ -298,7 +299,7 @@ def train(self, input_txt_file, model_name='w2v.model', vector_size=100, min_cou sentences = sents print('Step 2/4:...Train word2vec model\n used {} s'.format(duration)) - self.model = word2vec.Word2Vec(sentences, vector_size=vector_size, min_count=min_count, workers=multiprocessing.cpu_count()) + self.model = word2vec.Word2Vec(sentences, vector_size=vector_size, window=window_size, min_count=min_count, workers=multiprocessing.cpu_count()) modeldir = Path(self.cwd).joinpath('output', 'w2v_candi_words') Path(self.cwd).joinpath('output').mkdir(exist_ok=True) Path(self.cwd).joinpath('output', 'w2v_candi_words').mkdir(exist_ok=True) @@ -373,7 +374,6 @@ def find(self, seedword_txt_file, topn=50): - def co_occurrence_matrix(documents, window_size=2, lang='chinese'): """ Build a co-word matrix diff --git a/build/lib/cntext/mind.py b/build/lib/cntext/mind.py index 20a4123..94aa284 100644 --- a/build/lib/cntext/mind.py +++ b/build/lib/cntext/mind.py @@ -134,8 +134,6 @@ def divergent_association_task(words, minimum=7): - - # class Alignment(object): # def __init__(self): # pass diff --git a/cntext.egg-info/PKG-INFO b/cntext.egg-info/PKG-INFO index 02d9ddc..cd3c9e0 100644 --- a/cntext.egg-info/PKG-INFO +++ b/cntext.egg-info/PKG-INFO @@ -1,6 +1,6 @@ Metadata-Version: 2.1 Name: cntext -Version: 1.8.3 +Version: 1.8.4 Summary: Chinese text analysis library, which can perform word frequency statistics, dictionary expansion, sentiment analysis, 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@@ -3,7 +3,7 @@ setup( name='cntext', # 包名字 - version='1.8.3', # 包版本 + version='1.8.4', # 包版本 description='Chinese text analysis library, which can perform word frequency statistics, dictionary expansion, sentiment analysis, similarity, readability, co-occurrence analysis, social calculation (attitude, prejudice, culture) on texts', # 简单描述 author='大邓', # 作者 author_email='thunderhit@qq.com', # 邮箱