Functions — github.com/Seafoodair/Openreview

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Functions139 in github.com/Seafoodair/Openreview

⨍ Functions 139◇ Types & classes 5

↓ 9 callersFunctionget_log

(num)

data/Data analysis/three levels/2017-2019.py:31

↓ 9 callersFunctionget_log

(num)

code/data analysis/three levels/2017-2019MJSDivergence.py:25

↓ 6 callersFunctionTrans

(tt)

code/sentiment analysis/generatecount.py:14

↓ 6 callersFunctionget_log

(num)

data/Data analysis/two levels/2017-2019.py:75

↓ 6 callersFunctionget_log

(num)

code/data analysis/two levels/2017-2019MJSDivergence.py:75

↓ 6 callersFunctionget_review_level_2017_2018_2020

(text)

data/Data analysis/three levels/2017-2019.py:16

↓ 6 callersFunctionget_review_level_2017_2018_2020

(text)

code/data analysis/three levels/2017-2019MJSDivergence.py:10

↓ 6 callersFunctionget_score_2017_2018_2020

(text)

data/Data analysis/three levels/2017-2019.py:9

↓ 6 callersFunctionget_score_2017_2018_2020

(text)

code/data analysis/three levels/2017-2019MJSDivergence.py:3

↓ 5 callersFunctionpdread

(getdd)

code/sentiment analysis/drawsentimentpic.py:118

↓ 4 callersFunctionget_review_level_2017_2018_2020

(text)

data/Data analysis/two levels/2017-2019.py:16

↓ 4 callersFunctionget_review_level_2017_2018_2020

(text)

code/data analysis/two levels/2017-2019MJSDivergence.py:16

↓ 4 callersFunctionget_score_2017_2018_2020

(text)

data/Data analysis/two levels/2017-2019.py:9

↓ 4 callersFunctionget_score_2017_2018_2020

(text)

code/data analysis/two levels/2017-2019MJSDivergence.py:9

↓ 3 callersFunctionevaluate

(data)

code/sentiment analysis/trainmodel.py:85

↓ 3 callersFunctionget_log

(num)

data/Data analysis/three levels/2020.py:64

↓ 3 callersFunctionget_log

(num)

code/data analysis/three levels/2020MJSDivergence.py:59

↓ 3 callersFunctionget_review_level

(text)

data/Data analysis/three levels/2020.py:68

↓ 3 callersFunctionget_review_level

(text)

code/data analysis/three levels/2020MJSDivergence.py:63

↓ 3 callersFunctionget_review_level_2019

(text)

data/Data analysis/three levels/2017-2019.py:25

↓ 3 callersFunctionget_review_level_2019

(text)

code/data analysis/three levels/2017-2019MJSDivergence.py:19

↓ 3 callersFunctionget_score_2017_2018_2020

(text)

data/Data analysis/three levels/2020.py:9

↓ 3 callersFunctionget_score_2017_2018_2020

(text)

code/data analysis/three levels/2020MJSDivergence.py:4

↓ 3 callersFunctionget_score_2019

(text)

data/Data analysis/three levels/2017-2019.py:23

↓ 3 callersFunctionget_score_2019

(text)

code/data analysis/three levels/2017-2019MJSDivergence.py:17

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/bert+lstm+pool.py:72

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/DBERT.py:66

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/attentiononly.py:72

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/DBERTATTENTION.py:66

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/dbertbilstm.py:72

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/main.py:66

↓ 3 callersFunctionreturn_id

(str1, str2, truncation_strategy, length)

Rebuttal/Model/singlebert.py:72

↓ 2 callersFunctionclean_text

(text)

Rebuttal/Model/DLSTM.py:17

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/bert+lstm+pool.py:112

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/DBERT.py:106

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/attentiononly.py:112

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/DBERTATTENTION.py:130

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/dbertbilstm.py:112

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/main.py:106

↓ 2 callersFunctioncompute_input_arrays

(df, columns, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/singlebert.py:112

↓ 2 callersFunctionget_log

(num)

data/Data analysis/two levels/2020.py:53

↓ 2 callersFunctionget_log

(num)

code/data analysis/two levels/2020MJSDivergence.py:53

↓ 2 callersFunctionget_review_level

(text)

data/Data analysis/two levels/2020.py:58

↓ 2 callersFunctionget_review_level

(text)

code/data analysis/two levels/2020MJSDivergence.py:58

↓ 2 callersFunctionget_review_level_2019

(text)

data/Data analysis/two levels/2017-2019.py:25

↓ 2 callersFunctionget_review_level_2019

(text)

code/data analysis/two levels/2017-2019MJSDivergence.py:25

↓ 2 callersFunctionget_score_2017_2018_2020

(text)

data/Data analysis/two levels/2020.py:9

↓ 2 callersFunctionget_score_2017_2018_2020

(text)

code/data analysis/two levels/2020MJSDivergence.py:9

↓ 2 callersFunctionget_score_2019

(text)

data/Data analysis/two levels/2017-2019.py:23

↓ 2 callersFunctionget_score_2019

(text)

code/data analysis/two levels/2017-2019MJSDivergence.py:23

↓ 2 callersFunctiongraphpic5

(w,h,p,q,list66,listgg)

code/sentiment analysis/drawsentimentpic.py:88

↓ 1 callersFunctionGetMultiData

(L)

code/sentiment analysis/generate.py:32

↓ 1 callersFunctionMaxMinNormalization

(x,Max,Min)

code/sentiment analysis/drawsentimentpic.py:10

↓ 1 callersFunctionNormalization

(x)

code/cluster analysis/Clustering.py:173

↓ 1 callersFunctioncolor

(value)

code/cluster analysis/Clustering.py:178

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/bert+lstm+pool.py:71

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/DBERT.py:65

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/attentiononly.py:71

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/DBERTATTENTION.py:65

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/dbertbilstm.py:71

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/main.py:65

↓ 1 callersFunctionconvert_to_transformer_inputs

(str1, str2, tokenizer, max_sequence_length, double=True)

Rebuttal/Model/singlebert.py:71

↓ 1 callersFunctiondual_bert

()

Rebuttal/Model/DBERT.py:173

↓ 1 callersFunctiondual_bert

()

Rebuttal/Model/DBERTATTENTION.py:197

↓ 1 callersFunctiondual_bert

()

Rebuttal/Model/main.py:173

↓ 1 callersFunctionfancy_dendrogram

(*args, **kwargs)

code/cluster analysis/Clustering.py:80

↓ 1 callersFunctiongraphpic

(w,h,p,q,list66,listgg)

code/sentiment analysis/drawsentimentpic.py:13

↓ 1 callersFunctiongraphpic2

(w,h,p,q,list66,listgg)

code/sentiment analysis/drawsentimentpic.py:31

↓ 1 callersFunctiongraphpic3

(w,h,p,q,list66,listgg)

code/sentiment analysis/drawsentimentpic.py:50

↓ 1 callersFunctiongraphpic4

(w,h,p,q,list66,listgg)

code/sentiment analysis/drawsentimentpic.py:69

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/bert+lstm+pool.py:23

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/DBERT.py:22

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/attentiononly.py:23

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/DBERTATTENTION.py:22

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/dbertbilstm.py:23

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/main.py:22

↓ 1 callersFunctionplot_confusion_matrix

(cm, classes, title='Confusion matrix', cmap=plt.cm.Blues)

Rebuttal/Model/singlebert.py:23

↓ 1 callersFunctionpredict

(data)

code/sentiment analysis/predict.py:109

↓ 1 callersFunctionread_message

(path,column_name)

code/sentiment analysis/predict.py:30

↓ 1 callersFunctionread_message

(path)

code/sentiment analysis/trainmodel.py:18

↓ 1 callersFunctionremove_symbols

(sentence)

code/cluster analysis/Clustering.py:16

↓ 1 callersFunctionsegment

(text, userdict_filepath="userdict2.txt", stopwords_filepath='stopwords.txt')

code/cluster analysis/Clustering.py:23

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/bert+lstm+pool.py:64

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/DBERT.py:58

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/attentiononly.py:64

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/DBERTATTENTION.py:58

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/dbertbilstm.py:64

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/main.py:58

↓ 1 callersFunctionset_seed

(seed)

Rebuttal/Model/singlebert.py:64

↓ 1 callersFunctionsimple_bert

()

Rebuttal/Model/bert+lstm+pool.py:165

↓ 1 callersFunctionsimple_bert

()

Rebuttal/Model/attentiononly.py:165

↓ 1 callersFunctionsimple_bert

()

Rebuttal/Model/dbertbilstm.py:165

↓ 1 callersFunctionsimple_bert

()

Rebuttal/Model/singlebert.py:165

FunctionCalcAvg

(pp)

code/sentiment analysis/generatecount.py:11

FunctionDealwith

(i)

ICLR2021-2022/code/CrawlGoogleScholarCite.py:9

FunctionForCicle

()

code/sentiment analysis/generatecount.py:5

FunctionJSD

(prob_distributions, weights, logbase=2)

data/Data analysis/two levels/2017-2019.py:28

FunctionJSD

(prob_distributions, weights, logbase=2)

data/Data analysis/two levels/2020.py:17

FunctionJSD

(prob_distributions, weights, logbase=2)

data/Data analysis/three levels/2017-2019.py:35

FunctionJSD

(prob_distributions, weights, logbase=2)

data/Data analysis/three levels/2020.py:17

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