o
    h                     @   s   d dl Z d dlZd dlZd dlZd dlZd dlmZ d dlmZ d dlZd dl	m
Z
 edddgZdZd	d
 Zdd Zdd Zdd Zdd ZdddZdS )    N)
namedtuple)tqdm)SentimentDatumSplitfilenameweight)traindevtestc                 C   s   dd |D }t | d;}|d t|D ]#\}}|d tj||dd |t|d k r4|d	 |d
 q|d W d   dS 1 sJw   Y  dS )z\
    Write a list of items to the given output file

    Expected: list(SentimentDatum)
    c                 S      g | ]}|  qS  )_asdict).0liner   r   h/var/www/html/env_mimamsha/lib/python3.10/site-packages/stanza/utils/datasets/sentiment/process_utils.py
<listcomp>       zwrite_list.<locals>.<listcomp>wz[
z  F)ensure_ascii   ,
z]
N)openwrite	enumeratejsondumplen)out_filenamedatasetformatted_datasetfoutidxr   r   r   r   
write_list   s   


"r#   c                 C   s8   t t| D ]\}}tj|d||f }t|| qdS )zm
    Write train, dev, test as .json files for a given dataset

    dataset: 3 lists of sentiment tuples
    z
%s.%s.jsonN)zipSHARDSospathjoinr#   )r   out_directorydataset_nameshardphrasesoutput_filer   r   r   write_dataset)   s   r.   c           	      C   s   t dd |D }g }d}|D ]}|tt|| |  ||j }q|t| t|D ]*\}}tj| |j	}t
d|| ||d  | t|||| ||d    q/dS )z\
    Write the given list of items to the split files in the specified output directory
    c                 s       | ]}|j V  qd S N)r   )r   splitr   r   r   	<genexpr>7       zwrite_splits.<locals>.<genexpr>g        zWriting {}:{} to {}r   N)sumappendintr   r   r   r&   r'   r(   r   printformatr#   )	r)   snippetssplitstotal_weightdivssubtotalr1   ir   r   r   r   write_splits3   s    r?   c                 C   s   t | } t| dkr%| d dkr%| d d dkr%| d dkr%| dd  } n-t| dkrD| d dkrD| d dkrD| d dkrD| dd  } n| d d dkrR| dd  } tt| D ]}| | d dksj| | d d	krt| | dd  | |< qXd
d | D } | S )N   r   RTr   @   :   #c                 S   s(   g | ]}|r| d s| ds|qS )zhttp:zhttps:)
startswithr   xr   r   r   r   P   s   ( z)clean_tokenized_tweet.<locals>.<listcomp>)listr   range)r   r>   r   r   r   clean_tokenized_tweetE   s   40 rL   c           	   	   C   s  t  ]}tj|d}t|ddd}| D ]
}|d|j  qW d   n1 s+w   Y  tj|d}td||f  t|dd}|	 }W d   n1 sUw   Y  W d   n1 sdw   Y  d	d
 |D }dd
 |D }dd
 t
| |D }|S )a1  
    Use the PTB tokenizer to retokenize the phrases

    Not clear which is better, "Nov." or "Nov ."
    strictAcronym=true makes it do the latter
    tokenizePerLine=true should make it only pay attention to one line at a time

    Phrases will be returned as lists of words rather than one string
    zphrases.txtr   utf-8)encodingz%s


Nztokenized.txtztjava edu.stanford.nlp.process.PTBTokenizer -options "strictAcronym=true,tokenizePerLine=true" -preserveLines %s > %sc                 S   r   r   )striprH   r   r   r   r   j   r   z-get_ptb_tokenized_phrases.<locals>.<listcomp>c                 S   s   g | ]}|r|qS r   r   rH   r   r   r   r   k   r   c                 S   s    g | ]\}}t |j| qS r   )r   	sentimentr1   )r   rI   yr   r   r   r   l   s     )tempfileTemporaryDirectoryr&   r'   r(   r   r   textsystem	readlinesr$   )	r   tempdirphrase_filenamer!   itemtok_filenamefin	tokenizedr,   r   r   r   get_ptb_tokenized_phrasesS   s$   


r]   	FrM   c
                    s^  |du rt j|dd}t| d|	d}
|rt|
 tj|
||d}t|}W d   n1 s/w   Y  g }tt|D ]p\} zt	|t
rM |  }nt fdd|D }W n tyo } z
td	|| |d}~ww  | }|| }||d}|du rtd
||| g }|jD ]}|dd |jD  qt|}|t|| q<|S )zH
    Read in a single CSV file and return a list of SentimentDatums
    Ntokenize)
processors )newlinerN   )	delimiter	quotecharc                    s   g | ]} | qS r   r   rH   r   r   r   r      r   z!read_snippets.<locals>.<listcomp>z'Columns {} did not exist at line {}: {}z(Value {} not in mapping at line {} of {}c                 s   r/   r0   )rT   )r   tokenr   r   r   r2      r3   z read_snippets.<locals>.<genexpr>)stanzaPipeliner   nextcsvreaderrJ   r   r   
isinstancer6   lowertuple
IndexErrorr8   rO   get
ValueError	sentencesextendtokensrL   r5   r   )csv_filenamesentiment_columntext_columntokenizer_languagemappingrc   rd   skip_first_linenlprN   r[   cinlinesr9   r"   rP   erT   docconverted_sentimentsentencer   re   r   read_snippetso   s<   


r   )r^   NFNrM   )rj   globr   r&   rR   collectionsr   r   rg   stanza.models.classifiers.datar   r   r%   r#   r.   r?   rL   r]   r   r   r   r   r   <module>   s"    
