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DataTag_helper.py
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DataTag_helper.py
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#!/usr/bin/env python3
# -*- coding:utf-8 -*-
###
# File: /lib/AIClerk_helper.py
# Project: suidice-text-detection
# Created Date: Monday, May 4th 2020, 3:06:41 pm
# Author: Allenyl(allen7575@gmail.com>)
# -----
# Last Modified: Friday, September 15th 2023, 2:57:01 pm
# Modified By: Allenyl(allen7575@gmail.com)
# -----
# Copyright 2018 - 2020 Allenyl Copyright, Allenyl Company
# -----
# license:
# All shall be well and all shall be well and all manner of things shall be well.
# We're doomed!
# ------------------------------------
# HISTORY:
# Date By Comments
# ---------- --- ---------------------------------------------------------
###
## Non-ASCII output hangs execution in PyInstaller packaged app · Issue #520 · chriskiehl/Gooey
## https://github.com/chriskiehl/Gooey/issues/520
import codecs
import copy
import hashlib
import json
import os
import platform
import re
import sys
from collections import Counter, OrderedDict, defaultdict
from functools import reduce
from pathlib import Path
# from sklearn.utils import shuffle
import emoji
import numpy as np
import pandas as pd
import pdfplumber
from chardet.universaldetector import UniversalDetector
# from lib.AIClerk_helper import to_AI_clerk_batch_upload_json
from docx import Document
# import argparse
from gooey import Gooey, GooeyParser
from natsort import natsorted
from openpyxl.styles import Font
from sklearn.model_selection import StratifiedShuffleSplit
if sys.stdout.encoding != "UTF-8":
sys.stdout = codecs.getwriter("utf-8")(sys.stdout.buffer, "strict")
if sys.stderr.encoding != "UTF-8":
sys.stderr = codecs.getwriter("utf-8")(sys.stderr.buffer, "strict")
# use sqlite db to share data between gui and cli
# because gui will excute this file with cli args to finish its work,
# it needs a way to know what data is change in gui screen.
from sqlitedict import SqliteDict
MY_DB_FILE = "./my_db.sqlite"
# mydict = SqliteDict(MY_DB_FILE, autocommit=True)
# try:
# mydict["global_choies"]
# except KeyError:
# mydict["global_choies"] = []
# share args across different event callbacks
global_args = defaultdict(list)
def patch_gooey_gui_component(mydict):
"""Monkey patch gooey's gui components, like:
Dropdown, FileChooser, GooeyApplication,...etc.
To avoid `ImportError: libXxf86vm.so.1` while import,
we enclose patch code into a function,
and call it when we are going into GUI mode.
Returns:
[type]: [description]
"""
import wx
# from gooey.gui.lang.i18n import _
######
## [Feature request: Allow general callbacks for validation · Issue #293 · chriskiehl/Gooey]
## (https://github.com/chriskiehl/Gooey/issues/293)
# from gooey.gui.components.widgets.bases import TextContainer
# oldGetValue = TextContainer.getValue
#
# def newGetValue(self):
# result = oldGetValue(self)
# userValidator = self._options['validator']['callback']
# message = self._options['validator']['message']
# value = self.getWidgetValue()
# validates = userValidator(value)
# result['test'] = False
# result['error'] = 'test'
# return result
#
# TextContainer.getValue = newGetValue
######
# [Gooey/dropdown.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/dropdown.py)
from gooey.gui.components.widgets.dropdown import Dropdown
Dropdown_oldGetWidget = Dropdown.getWidget
# from gooey.gui import formatters
# def newFormatOutput(self, metadata, value):
# print("debug2")
# print("metadata", metadata)
# print("value", value)
# return formatters.dropdown(metadata, value)
# def newSetValue(self, value):
# ## +1 to offset the default placeholder value
# index = self._meta['choices'].index(value) + 1
# print("debug", self._meta['choices'])
# self.widget.SetSelection(index)
# def newGetWidgetValue(self):
# value = self.widget.GetValue()
# # filter out the extra default option that's
# # appended during creation
# print(value)
# if value == _('select_option'):
# return None
# return value
def Dropdown_newGetWidget(self, parent, *args, **options):
widget = Dropdown_oldGetWidget(self, parent, *args, **options)
# [wxPython ComboBox & Choice类 - WxPython教程™]
# (https://www.yiibai.com/wxpython/wx_combobox_choice_class.html)
# [wx.ComboBox — wxPython Phoenix 4.1.1a1 documentation]
# (https://wxpython.org/Phoenix/docs/html/wx.ComboBox.html)
widget.Bind(wx.EVT_COMBOBOX_DROPDOWN, self.OnCombo)
return widget
def Dropdown_newOnCombo(self, event):
def get_choices(input_file):
try:
# specify engine use 'openpyxl' to avoid not found xlrd error
new_choices = list(
pd.read_excel(
input_file,
sheet_name="document_label",
index_col=0,
nrows=0,
engine="openpyxl",
)
)
message = ""
self.setErrorString(message)
self.showErrorString(False)
# force refresh parent screen
# python - Update/Refresh Dynamically–Created WxPython Widgets - Stack Overflow
# https://stackoverflow.com/questions/10368948/update-refresh-dynamically-created-wxpython-widgets
self.GetParent().Layout()
except Exception as e:
# message = "No sheet named 'document_label'"
# show actual exception message for easier debug
message = repr(e)
# print(message)
self.setErrorString(message)
self.showErrorString(True)
# force refresh parent screen
# python - Update/Refresh Dynamically–Created WxPython Widgets - Stack Overflow
# https://stackoverflow.com/questions/10368948/update-refresh-dynamically-created-wxpython-widgets
self.GetParent().Layout()
new_choices = []
return new_choices
current_input_file = global_args["input_file"]
try:
self.previous_input_file
except Exception:
self.previous_input_file = ""
if self.previous_input_file != current_input_file:
self.new_choices = get_choices(current_input_file)
self.previous_input_file = current_input_file
# save self.new_choices into sqlite db for later access
mydict["global_choies"] = self.new_choices
# [python - Dynamically change the choices in a wx.ComboBox() - Stack Overflow]
# (https://stackoverflow.com/questions/682923/dynamically-change-the-choices-in-a-wx-combobox)
self.setOptions(self.new_choices)
Dropdown.getWidget = Dropdown_newGetWidget
Dropdown.OnCombo = Dropdown_newOnCombo
# Dropdown.setValue = newSetValue
# Dropdown.getWidgetValue = newGetWidgetValue
# Dropdown.formatOutput = newFormatOutput
# [Gooey/choosers.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/choosers.py)
# [Gooey/chooser.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/core/chooser.py#L65)
# [Gooey/chooser.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/core/chooser.py#L13)
# [Gooey/text_input.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/core/text_input.py#L7)
# [Gooey/bases.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/components/widgets/bases.py#L170)
from gooey.gui.components.widgets.core.chooser import FileChooser
FileChooser_old_init = FileChooser.__init__
## monkey patch __init__
def FileChooser_new_init(self, parent, *args, **kwargs):
FileChooser_old_init(self, parent, *args, **kwargs)
# bind event wx.EVT_TEXT to trigger self.OnFileChooser when text change
# [wx.TextCtrl — wxPython Phoenix 4.1.1a1 documentation]
# (https://wxpython.org/Phoenix/docs/html/wx.TextCtrl.html)
# [wxPython - TextCtrl Class - Tutorialspoint]
# (https://www.tutorialspoint.com/wxpython/wx_textctrl_class.htm)
self.widget.Bind(wx.EVT_TEXT, self.OnFileChooser)
## monkey patch OnFileChooser
def FileChooser_newOnFileChooser(self, event):
# read text area value to global_args
global_args["input_file"] = self.widget.getValue()
# print(global_args)
FileChooser.__init__ = FileChooser_new_init
FileChooser.OnFileChooser = FileChooser_newOnFileChooser
# [Gooey/application.py at 8c88980e12a968430df5cfd0779fab37db287680 · chriskiehl/Gooey]
# (https://github.com/chriskiehl/Gooey/blob/8c88980e12a968430df5cfd0779fab37db287680/gooey/gui/containers/application.py#L29)
from gooey.gui.containers.application import GooeyApplication
## monkey patch onClose
def newOnClose(self, *args, **kwargs):
"""Cleanup the top level WxFrame and shutdown the process"""
self.Destroy()
# print("onClose")
# remove db file when close
# [sqlite - Python PermissionError: [WinError 32] The process cannot access the file..... but my file is closed - Stack Overflow]
# (https://stackoverflow.com/questions/59482990/python-permissionerror-winerror-32-the-process-cannot-access-the-file-bu)
mydict.close()
os.remove(MY_DB_FILE)
sys.exit()
GooeyApplication.onClose = newOnClose
# navigation option must be upper cased 'TABBED', instead of 'Tabbed'
@Gooey(
program_name="DataTag Helper (標註轉檔小幫手) v0.9.0",
navigation="TABBED",
tabbed_groups=False,
default_size=(525, 670),
)
def parse_args(mydict, args=None):
if args is None:
args = sys.argv[1:]
# parser = argparse.ArgumentParser()
parser = GooeyParser()
subs = parser.add_subparsers(help="commands", dest="command")
### for original file
sub_parser1 = subs.add_parser("original", prog="未標註原始檔案", help="未標註原始檔案")
sub_parser1_1 = sub_parser1.add_argument_group(
"input file(s)",
"choose unlabeled file(s)",
gooey_options={"show_border": True, "show_underline": True, "columns": 1},
)
# add default selection option
# https://github.com/chriskiehl/Gooey/issues/590#issue-650474511
mutex_sub_parser1 = sub_parser1_1.add_mutually_exclusive_group(
required=True,
gooey_options={
"show_border": True,
"show_underline": True,
"columns": 1,
"initial_selection": 0,
},
)
#### input txt files
mutex_sub_parser1.add_argument(
"-d",
"--input-dir",
help="dir that contains input files(.txt)",
dest="input_dir",
default=None,
widget="DirChooser",
)
#### input excel files
mutex_sub_parser1.add_argument(
"-i",
"--input_file",
help="input filename (excel)",
dest="input_file",
default=None,
widget="FileChooser",
)
sub_parser1_2 = sub_parser1.add_argument_group(
"options",
"only works for input excel file",
gooey_options={"show_border": True, "show_underline": True, "columns": 2},
)
sub_parser1_2.add_argument(
"--emojilize",
help="turn text to emoji (uncheck to reverse)",
dest="emojilize",
action="store_true",
)
sub_parser1_2.set_defaults(emojilize=False)
sub_parser1_2.add_argument(
"--to-excel",
help="output excel file (uncheck to output json)",
dest="to_excel",
action="store_true",
)
sub_parser1_2.set_defaults(to_excel=False)
### for labeled file
sub_parser2 = subs.add_parser("labeled", prog="已標註檔案", help="已標註檔案")
sub_parser2 = sub_parser2.add_argument_group(
"labeled file to excel",
"choose the labeled file which want to be convert to Excel file(s)",
gooey_options={"show_border": True, "show_underline": True, "columns": 1},
)
sub_parser2.add_argument(
"-i",
"--input_file",
help="input filename (json)",
dest="input_file",
default=None,
widget="FileChooser",
)
### for labeled file want to second upload
sub_parser2_1 = subs.add_parser("second_upload", prog="標註二次上傳", help="已標註檔案二次上傳")
sub_parser2_1 = sub_parser2_1.add_argument_group(
"second upload",
"choose the labeled file which want to be second upload (for double check purpose)",
gooey_options={"show_border": True, "show_underline": True, "columns": 1},
)
sub_parser2_1.add_argument(
"-i",
"--input_file",
help="input filename (json)",
dest="input_file",
default=None,
widget="FileChooser",
)
### for second labeled file convert
sub_parser2_2 = subs.add_parser("second_labeled", prog="二次標註轉換", help="二次標註轉換")
sub_parser2_2 = sub_parser2_2.add_argument_group(
"second labeled convertion",
"choose the first and second labeled files which wants to be converted to final json",
gooey_options={"show_border": True, "show_underline": True, "columns": 1},
)
sub_parser2_2.add_argument(
"-i1",
"--input_file_1",
nargs="*",
help="choose multiple files (first labeled json)",
dest="input_file_1",
default=None,
widget="MultiFileChooser",
)
sub_parser2_2.add_argument(
"-i2",
"--input_file_2",
help="input filename (second labeled json)",
dest="input_file_2",
default=None,
widget="FileChooser",
)
### concat files
sub_parser3 = subs.add_parser("concat", prog="合併檔案", help="合併檔案")
sub_parser3 = sub_parser3.add_argument_group("")
sub_parser3.add_argument(
"-i",
"--input_file",
help="input filenames (excel)",
dest="input_files",
default=None,
widget="MultiFileChooser",
)
### for random tran/test split
sub_parser4 = subs.add_parser("split", prog="分割檔案", help="分割檔案")
sub_parser4 = sub_parser4.add_argument_group("")
sub_parser4.add_argument(
"-i",
"--input_file",
help="input filename (excel)",
dest="input_file",
default=None,
widget="FileChooser",
)
sub_parser4.add_argument(
"-y",
"--y_column",
help="y column",
dest="y_col",
default=None,
widget="Dropdown",
choices=mydict["global_choies"],
)
# parser.add_argument('--type', '-t', choices=getLob())
# args, unknown = parser.parse_known_args()
args = parser.parse_args(args)
return args
def to_AI_clerk_batch_upload_json(dataframe, save_path):
def to_article_dict(x):
return {
"Title": x.Title.tolist()[0],
"Content": x.Content.tolist()[0],
"Author": x.Author.tolist()[0],
"Time": x.Time.tolist()[0],
}
print("number of entries: {}".format(len(dataframe)))
dup_id = dataframe.duplicated(["TextID"], keep=False)
print("duplicated entries: {}".format(len(dataframe[dup_id])))
print(dataframe[dup_id])
samples_dict = dataframe.groupby(["TextID"]).apply(to_article_dict).to_dict()
print("keep first, drop duplicated!")
content_length_lower_threshold = 100
long_id = dataframe["Content"].apply(
lambda x: True if len(x) < content_length_lower_threshold else False
)
print(
"number of entries which Content shorter then {} words: {}".format(
content_length_lower_threshold, len(dataframe[long_id])
)
)
print("no drop, just show information.")
sample_articles = defaultdict(defaultdict)
sample_articles["Articles"].update(samples_dict)
print("number of remaining entries: {}".format(len(sample_articles["Articles"])))
# output articles.json
with open(save_path, "w", encoding="utf-8") as outfile:
json.dump(sample_articles, outfile, ensure_ascii=False, indent=4)
# read ouputed samples to test
# with open('./suicide_text_sample.json', 'r') as outfile:
# temp_dict = json.load(outfile)
# try:
# display(temp_dict)
# except:
# pass
def get_TextID(df):
title_hsah = hashlib.md5(df["Title"].encode("utf-8")).hexdigest()[:10]
content_hash = hashlib.md5(df["Content"].encode("utf-8")).hexdigest()[:10]
return title_hsah + "-" + content_hash
# ### 清理資料格式
def clean_data(df):
empty_entries = df["Content"].isnull()
print("number of empty content entries: {}".format(len(df[empty_entries])))
df_cleaned = df[~empty_entries].copy()
if len(df[empty_entries]):
print("drop empty!")
drop_columns = df_cleaned.columns.str.contains("Unnamed")
# print(any(df_cleaned.columns.str.contains("^ID$")))
# if not any(df_cleaned.columns.str.contains("^TextID$")):
leave_columns = df_cleaned.columns[~drop_columns].tolist()
# df_cleaned['ID'] = df_cleaned[["Content"]].apply(lambda x: hashlib.md5(x[0].encode('utf-8')).hexdigest()[:10],axis=1)
df_cleaned = df_cleaned[leave_columns]
# print(df_cleaned.head())
df_cleaned = df_cleaned.sort_values("TextID").reset_index(drop=True)
try:
df_cleaned["Author"] = df_cleaned.apply(
lambda x: x.Poster + "/" + x.Gender, axis=1
)
except:
try:
df_cleaned["Author"] = df_cleaned["Poster"]
except:
df_cleaned["Author"] = None
try:
df_cleaned["Date"] = df_cleaned["Date"].apply(lambda x: x.strftime("%Y-%m-%d"))
df_cleaned["Time"] = df_cleaned["Time"].apply(lambda x: x.strftime("%H:%M:%S"))
except:
pass
try:
df_cleaned["Time"] = df_cleaned.apply(
lambda x: str(x.Date) + "/" + str(x.Time), axis=1
)
except:
try:
df_cleaned["Time"] = df_cleaned.apply(lambda x: str(x.Date), axis=1)
except:
df_cleaned["Time"] = None
return df_cleaned
def emoji_to_text(df):
df_deemojilized = df.copy()
## 轉換 emoji 格式成 :emoji:
## python - How to replace emoji to word in a text? - Stack Overflow
## https://stackoverflow.com/questions/57580288/how-to-replace-emoji-to-word-in-a-text
df_deemojilized["Content"] = df[["Content"]].apply(
lambda x: emoji.demojize(x[0]), axis=1
)
df_deemojilized["Title"] = df[["Title"]].apply(
lambda x: emoji.demojize(x[0]), axis=1
)
return df_deemojilized
def text_to_emoji(df):
df_emojilized = df.copy()
## 將:emoji: 換回 unicode character
df_emojilized["Content"] = df[["Content"]].apply(
lambda x: emoji.emojize(x[0]), axis=1
)
df_emojilized["Title"] = df[["Title"]].apply(lambda x: emoji.emojize(x[0]), axis=1)
return df_emojilized
def reorder_column(columns_list, selected_column_name, insert_before_column_name=None):
"""
columns_list: the list of columns to be reordered
selected_column_name: the column name which wants to be inserted to the point before column `insert_before_column_name`
insert_before_column_name: the column name which act as fix point relative to the `selected_column_name`
"""
columns_list = copy.copy(columns_list)
selected_index = columns_list.index(selected_column_name)
selected_item = columns_list.pop(selected_index)
# drop selected column when insert_before_column_name is infinity
if insert_before_column_name is np.inf:
return columns_list
# print(insert_before_column_name is float('inf'))
# insert to the end of column list when insert_before_column_name is None
if insert_before_column_name is None:
insert_point_index = len(columns_list)
else:
insert_point_index = columns_list.index(insert_before_column_name)
columns_list.insert(insert_point_index, selected_item)
return columns_list
def extract_dict(df, id_column_list, dict_column):
df_tmp = df[id_column_list + [dict_column]].set_index(id_column_list)
df_tmp = pd.DataFrame(
df_tmp.apply(lambda x: {"empty": "nan"} if len(x[0]) == 0 else x[0], axis=1)
)
df_tmp = df_tmp.apply(
lambda x: pd.DataFrame.from_dict(x[0], orient="index").stack(), axis=1
)
df_tmp = df_tmp.reset_index(level=id_column_list)
return df_tmp
# these illegal characters is represented by octal escape
# [Regular Expressions Reference: Special and Non-Printable Characters]
# (https://www.regular-expressions.info/refcharacters.html)
# [(1条消息)openpyxl.utils.exceptions.IllegalCharacterError 错误原因分析及解决办法_村中少年的专栏-CSDN博客]
# (https://blog.csdn.net/javajiawei/article/details/97147219)
ILLEGAL_CHARACTERS_RE = re.compile(r"[\000-\010]|[\013-\014]|[\016-\037]")
# [openpyxl.utils.escape — openpyxl 3.0.5 documentation]
# (https://openpyxl.readthedocs.io/en/stable/_modules/openpyxl/utils/escape.html)
ESCAPED_REGEX = re.compile("_x([0-9A-Fa-f]{4})_")
def unescape_OOXML(string):
def remove_character(char):
print("removed illegal char!")
return r""
def _sub(match):
"""
Callback to unescape chars
"""
char = chr(int(match.group(1), 16))
# [Convert regular Python string to raw string - Stack Overflow]
# (https://stackoverflow.com/questions/4415259/convert-regular-python-string-to-raw-string)
# [python - Pythonic way to do base conversion - Stack Overflow]
# (https://stackoverflow.com/questions/28824874/pythonic-way-to-do-base-conversion)
print(
"found char {}, which int in octal number is: {}".format(
char.encode("unicode_escape"), oct(ord(char))
)
)
# remove carriage return
if char == "\r":
print("removed!")
char = ""
else:
# remove illegal characters
char = ILLEGAL_CHARACTERS_RE.sub(remove_character, char)
return char
string = ESCAPED_REGEX.sub(_sub, string)
return string
## [pandas - How to remove illegal characters so a dataframe can write to Excel - Stack Overflow]
## (https://stackoverflow.com/questions/42306755/how-to-remove-illegal-characters-so-a-dataframe-can-write-to-excel)
def remove_illegal_characters(dataframe):
# dataframe = dataframe.applymap(lambda x: x.encode('unicode_escape').decode('utf-8') if isinstance(x, str) else x)
dataframe = dataframe.applymap(
lambda x: ILLEGAL_CHARACTERS_RE.sub(r"", x) if isinstance(x, str) else x
)
return dataframe
def to_excel_AI_clerk_labeled_data(dataframe, save_path):
## unescape OOXML string
dataframe = dataframe.applymap(
lambda x: unescape_OOXML(x) if isinstance(x, str) else x
)
## remove illegal characters
dataframe = remove_illegal_characters(dataframe)
df1 = (
dataframe.T.sort_values(["TextID", "Annotator"])
.rename_axis("SerialID")
.reset_index()
)
df1 = df1[sorted(df1.columns)]
columns_list = list(df1.columns)
print(columns_list)
columns_list = reorder_column(columns_list, "TextID", "Annotator")
columns_list = reorder_column(columns_list, "SerialID", "TextID")
columns_list = reorder_column(columns_list, "Title", "Content")
columns_list = reorder_column(columns_list, "Author", "Title")
columns_list = reorder_column(columns_list, "TextTime", "Comment")
print(columns_list)
df2 = df1[columns_list]
def extract_dict_of_list(dataframe, column_name):
df_dict_of_list = extract_dict(dataframe, ["TextID", "Annotator"], column_name)
## reduce multi-selection option into string
def multi_selection_to_string(option_columns):
# print(option_columns)
option_columns_list = list(filter(lambda y: pd.notnull(y), option_columns))
# check if option_columns_list is empty or ['']
if len(option_columns_list) == 0:
result = np.nan
elif len(option_columns_list) == 1 and option_columns_list[0] == "":
result = np.nan
else:
result = reduce(lambda a, b: a + ", " + b, option_columns_list)
if result == "":
# print(list(option_columns))
# print(len(option_columns_list))
result = np.nan
return result
### use ordered set to keep columns order
od = OrderedDict(df_dict_of_list.columns.to_flat_index())
option_columns_list = list(od.keys())
df_dict_of_list_tmp = pd.DataFrame(columns=option_columns_list)
df_dict_of_list_tmp["TextID"] = df_dict_of_list["TextID"]
df_dict_of_list_tmp["Annotator"] = df_dict_of_list["Annotator"]
option_columns_list.remove("TextID")
option_columns_list.remove("Annotator")
### flatten all option columns
for option_column in option_columns_list:
df_dict_of_list_tmp[option_column] = df_dict_of_list[option_column].apply(
lambda x: multi_selection_to_string(x), axis=1
)
df_dict_of_list = pd.merge(
dataframe[["TextID", "Annotator"]],
df_dict_of_list_tmp,
how="left",
on=["TextID", "Annotator"],
)
return df_dict_of_list, option_columns_list
########### extract document label #############
df_document_label, document_label_option_columns_list = extract_dict_of_list(
df2, "Summary"
)
########### extract ArticleTag #############
df_article_tag = None
try:
df_article_tag, _ = extract_dict_of_list(df2, "ArticleTag")
# print(df_article_tag)
except Exception as e:
print(str(e))
pass
########## create doc label compare view ##########
df_doc_label_cmp = pd.pivot_table(
df_document_label,
values=document_label_option_columns_list,
index=["TextID"],
columns=["Annotator"],
aggfunc=lambda x: x.iloc[0],
)
df_doc_label_cmp = df_doc_label_cmp.reset_index()
########## extract sentence label ############
df_sentence_label_tmp = extract_dict(df2, ["TextID", "Annotator"], "TermTab")
sentence_label_index_dict = OrderedDict(
df_sentence_label_tmp.columns.to_flat_index()
)
sent_label_column_list = list(sentence_label_index_dict.keys())
# print(sent_label_column_list)
sent_label_column_list.remove("TextID")
sent_label_column_list.remove("Annotator")
## drop unused level of multi index to avoid KeyError
df_sentence_label_tmp = df_sentence_label_tmp.droplevel(1, axis=1)
df_sentence_label_tmp = df_sentence_label_tmp.melt(
id_vars=["TextID", "Annotator"],
value_vars=sent_label_column_list,
var_name="Sent_Label",
value_name="Sentence",
)
df_sentence_label_tmp = df_sentence_label_tmp.dropna()
df_sentence_label_tmp["Sent_Label"] = df_sentence_label_tmp["Sent_Label"].apply(
lambda x: x.split("_")[0]
)
df_sentence_label_tmp.reset_index(drop=True, inplace=True)
df_sentence_label = pd.merge(
df_document_label, df_sentence_label_tmp, how="left", on=["TextID", "Annotator"]
)
df_sentence_label = df_sentence_label.sort_values(
["TextID", "Annotator", "Sent_Label"]
)
######### create sent label cmp long view ########
# this will group sentence by 'TextID', 'Annotator' and 'Sent_Label'
df_sentence_sector = df_sentence_label_tmp.groupby(
["TextID", "Annotator", "Sent_Label"]
)
# because there may be many sentences belong to one Sent_Label,
# when arragate, save these sentence into a list
df_sent_label_cmp_long_tmp = df_sentence_sector.agg(lambda x: [y for y in x])
# this will separate each sentence into columns,
# so if there are 21 sentence, column's name will be a list of 0-20
df_sent_label_cmp_long_tmp = df_sent_label_cmp_long_tmp["Sentence"].apply(
lambda x: pd.Series(x)
)
# add new column level: Sentence
column_level_list = [["Sentence"], df_sent_label_cmp_long_tmp.columns]
df_sent_label_cmp_long_tmp.columns = pd.MultiIndex.from_product(
column_level_list, names=["", "Sent_num"]
)
# stack 'Sent_num' column as row index
df_sent_label_cmp_long_tmp = df_sent_label_cmp_long_tmp.stack()
# reset_index will turn all row index into columns
df_sent_label_cmp_long_tmp = df_sent_label_cmp_long_tmp.reset_index()
# set multilevel index with this order: 'TextID', 'Annotator', 'Sent_Label', 'Sent_num'
df_sent_label_cmp_long_tmp = df_sent_label_cmp_long_tmp.set_index(
["TextID", "Annotator", "Sent_Label", "Sent_num"]
)
def merge(x, y):
if isinstance(x, list):
new_x = x + y
else:
new_x = "error"
return new_x
# use 'TextID', 'Sent_Label', 'Sent_num' as index,
# and turn 'Annotator''s value into columns, eg.
# if there were four possible values of Annotator: A,B,C,D
# then use A,B,C,B as new column names, pivot under value column 'Sentence'
# in case there are multiple items with same index, aggfunc will be used.
# it will pass a pd.Series object into aggfunc,
# we cae use reduce to return sum over the series,
# if each item in series is a list object,
# we can define a merge function to sum these list up into one list.
df_sent_label_cmp_long = pd.pivot_table(
df_sent_label_cmp_long_tmp,
values=["Sentence"],
index=["TextID", "Sent_Label", "Sent_num"],
columns=["Annotator"],
aggfunc=lambda x: reduce(merge, x),
)
# add additional level in the multiindex: 'Sent'
# for sent_doc_cmp use
col_index_names = list(df_sent_label_cmp_long.columns.names)
df_sent_label_cmp_long.columns = pd.MultiIndex.from_tuples(
map(lambda x: (x[0], "Sent", x[1]), df_sent_label_cmp_long.columns),
names=[col_index_names[0], "", col_index_names[1]],
)
######### create sentence label wide view ##########
df_sentence_label_wide = df_sent_label_cmp_long.unstack().unstack()
df_sentence_label_wide.columns = df_sentence_label_wide.columns.swaplevel(3, 4)
df_sentence_label_wide.sort_index(axis=1, level=3, inplace=True)
df_sentence_label_wide.columns = pd.MultiIndex.from_tuples(
map(
lambda x: (x[2], str(x[3]) + "_" + "{:0>2d}".format(x[4])),
df_sentence_label_wide.columns,
)
)
df_sentence_label_wide = df_sentence_label_wide.stack(level=0)
df_sentence_label_wide.index = df_sentence_label_wide.index.rename(
["TextID", "Annotator"]
)
df_sentence_label_wide = df_sentence_label_wide.reset_index()
df_sentence_label_wide = pd.merge(
df_document_label,
df_sentence_label_wide,
how="left",
on=["TextID", "Annotator"],
)
empty_cols_exclude_first = df_sentence_label_wide.columns[
df_sentence_label_wide.columns.str.contains("empty_(?:[0][1-9]|[1-9][0-9])")
]
df_sentence_label_wide = df_sentence_label_wide.drop(
empty_cols_exclude_first, axis=1
)
######### create sent label cmp wide views ##########
df_sent_label_cmp_wide = df_sent_label_cmp_long.unstack()
df_sent_label_cmp_wide.columns = df_sent_label_cmp_wide.columns.swaplevel(2, 3)
df_sent_label_cmp_wide.sort_index(axis=1, level=2, inplace=True)
######## create sent_doc_cmp views #########
df_doc_tmp = df_doc_label_cmp.set_index("TextID")
df_doc_tmp = pd.concat({"Doc_Label": df_doc_tmp}, names=["label_kind"], axis=1)
df_sent_tmp = df_sent_label_cmp_long.reset_index()
# to prevent warning: PerformanceWarning: dropping on a non-lexsorted multi-index without a level parameter may impact performance.
# need to sort multi-index
# see: [python - What exactly is the lexsort_depth of a multi-index Dataframe? - Stack Overflow](https://stackoverflow.com/questions/27116739/what-exactly-is-the-lexsort-depth-of-a-multi-index-dataframe)
df_sent_tmp.sort_index(axis=1, level=0, inplace=True)
df_sent_doc_cmp_tmp = pd.merge(df_doc_tmp, df_sent_tmp, how="left", on=["TextID"])
df_sent_doc_cmp_tmp.columns = df_sent_doc_cmp_tmp.columns.swaplevel(1, 2)
df_sent_doc_cmp_tmp.columns = df_sent_doc_cmp_tmp.columns.swaplevel(0, 1)
df_sent_doc_cmp_tmp.sort_index(axis=1, level=0, inplace=True)
sent_doc_cols = list(df_sent_doc_cmp_tmp.columns)
new_sent_doc_cols = reorder_column(
sent_doc_cols, ("", "TextID", ""), ("", "Sent_Label", "")
)
df_sent_doc_cmp = df_sent_doc_cmp_tmp[new_sent_doc_cols]
df_sent_doc_cmp = df_sent_doc_cmp.set_index(
[("", "TextID", ""), ("", "Sent_Label", ""), ("", "Sent_num", "")]
)
df_sent_doc_cmp.index = df_sent_doc_cmp.index.rename(
["TextID", "Sent_Label", "Sent_num"]
)
########## extract content ##########
drop_columns_list = reorder_column(columns_list, "Summary", np.inf)
drop_columns_list = reorder_column(drop_columns_list, "TermTab", np.inf)
if df_article_tag is not None:
drop_columns_list = reorder_column(drop_columns_list, "ArticleTag", np.inf)
print(drop_columns_list)
## explicit copy to avoid SettingWithCopyWarning warning
df_content = df2[drop_columns_list].copy()
## remove tags in content
df_content["Content(remove_tag)"] = df_content["Content"].apply(
lambda x: re.sub(r"(＜(／)?＊(.+?)_\d{1,2}＊＞)", "", x)
)
# write to excel
with pd.ExcelWriter(
save_path, options={"strings_to_urls": False}, engine="openpyxl"
) as writer:
df_sent_doc_cmp.to_excel(writer, sheet_name="sent_doc_cmp", index=True)
df_doc_label_cmp.to_excel(writer, sheet_name="doc_label_cmp", index=True)
df_sent_label_cmp_long.to_excel(
writer, sheet_name="sent_label_cmp(long)", index=True
)
df_sent_label_cmp_wide.to_excel(
writer, sheet_name="sent_label_cmp(wide)", index=True
)
df_sentence_label_wide.to_excel(
writer, sheet_name="sentence_label(wide)", index=False
)
df_content.to_excel(writer, sheet_name="contents", index=False)
df_document_label.to_excel(writer, sheet_name="document_label", index=False)
df_sentence_label.to_excel(writer, sheet_name="sentence_label", index=False)
if df_article_tag is not None:
df_article_tag.to_excel(writer, sheet_name="article_tag", index=False)
for ws in writer.sheets.values():
"""
fix column headers and row headers no font name issue
need to use engine='openpyxl'
"""
# row_level = df_sent_doc_cmp.index.nlevels
# print(row_level)
for row in ws.iter_rows(min_row=1, max_row=1):
"""
walk through each cell of first row to assign font name
"""
for cell in row:
# print(cell)
font_params = cell.font.__dict__
if font_params["name"] is None:
font_params["name"] = "Calibri"
cell.font = Font(**font_params)
return (
df_content,
df_document_label,
df_sentence_label,
df_sentence_label_wide,
df_doc_label_cmp,
df_sent_label_cmp_long,
df_sent_label_cmp_wide,
df_sent_doc_cmp,
df_article_tag,
)
def split_train_test_to_target(X, y, target):
sss = StratifiedShuffleSplit(n_splits=5, test_size=0.2, random_state=1234)
for index, (train_index, test_index) in enumerate(sss.split(X, y)):
# print("TRAIN:", train_index, "TEST:", test_index)
X_train, X_test = X.iloc[train_index], X.iloc[test_index]
y_train, y_test = y.iloc[train_index], y.iloc[test_index]
print("split {}".format(index))
print("train:", Counter(y_train))
print("test:", Counter(y_test))
df_train = pd.DataFrame({"TextID": X_train}).reset_index(drop=True)
df_test = pd.DataFrame({"TextID": X_test}).reset_index(drop=True)
df_target_train = pd.merge(df_train, target, how="left", on=["TextID"])
df_target_test = pd.merge(df_test, target, how="left", on=["TextID"])