liigitus2.py 23.9 KB
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#/usr/bin/python
# -*- coding: utf-8 -*-


import os
import sys
import re
import  difflib
import  copy

from estnltk import Text
from  difflib import Differ

#proovime mõned lihtsamad vead tuvastada
#Lähtefail ../korpus_tsv

#loeme kõik laused sisse, teeme dict

#item{'senetenceID'}['a'] = {'id': 'sentence'}
#item{'senetenceID'}['p'][0..n] = {'id': 'sentence'}



originals 	= {} 
corrections 	= {} 

script_name = (os.path.realpath(__file__))
script_dir = os.path.dirname(script_name)

def intersection(lst1, lst2):
	if not lst1 or not len(lst1): return []
	if not lst2 or not len(lst2): return []
	return list(set(lst1) & set(lst2))


def get_data_from_ndiff(ndiff_list):
	added = []
	deleted = []
	added_pos = []
	deleted_pos = []
	line_nr_new = -1
	line_nr_old = -1
	for line in ndiff_list:
		token = line.rstrip()[2:]

		if line.startswith('-'):
			line_nr_old += 1
			deleted.append(token)
			deleted_pos.append(line_nr_old)
			continue
				
		if line.startswith('+'):
			line_nr_new += 1
			added.append(token)
			added_pos.append(line_nr_new)
			continue
		
		if line.startswith('?'): continue
		
		line_nr_old += 1
		line_nr_new += 1
	changed = True
	if not len(added_pos) and not len(deleted_pos):
		changed = False
	
		
	return ({'added':added , 'added_pos':added_pos, 'deleted':deleted, 'deleted_pos':deleted_pos, 'changed':changed, 'pos_intersection':sorted(intersection(added_pos,deleted_pos ))})


filename = script_dir +'/../korpus_tsv/korpus.tsv'
#outdir = script_dir +'/korpus_xml'

file_input = open(filename, 'r')



for line in file_input:
	
	line = line.rstrip()
	line_arr = line.split('\t')
	
	if not len(line_arr) == 2:
		print ('ERROR :' , line)
		exit(1)
	
	uid = line_arr[0]
	text = line_arr[1]
	
	uid_arr = uid.split('_')
	uid_ending = uid_arr.pop()
	uid2 = '_'.join(uid_arr)
	el_type = uid_ending[0]
	
	if el_type == 'a':
		originals[uid2] = {'id': uid, 'text':text.strip()}
	
	if el_type == 'p':
		if not uid2 in corrections:
			corrections[uid2] = []
		corrections[uid2].append({'id': uid, 'text':text.strip()})

		
		

collected_flags = {}
#paranduste klassifitseerimine
errorDecriptions = {
	
	'tundmatu' : {'name':'Tundmatu', 'order':'1' } 
	, 'puudub' : {'name':'Parandus puudub', 'order':'1' } 
	, 'tühik' : {'name':'Tühik kirjavahemärgi ees v taga', 'order':'1' } 
	, 'punktuatsioon' : {'name':'Kirjavahemärk lisatud/eemaldatud', 'order':'1' } 
	, 'sõnadejärg' : {'name':'Sõnadejärjekord parandatud', 'order':'1' } 
	, 'sõnalisatud' : {'name':'Lisati puuduv sõna', 'order':'1' } 
	, 'sõnaeemaldatud' : {'name':'Kustutati sõna', 'order':'1' } 
}

# alustame parandustest
d = Differ()
d2 = difflib.HtmlDiff( tabsize=4, wrapcolumn=40 )

stats = {}
stats['total'] = 0
stats['lahendamata1'] = 0
stats['lahendamata2'] = 0
	
filename2 = 'tulemus/tundmatu.html'
file_out = open(filename2, 'w')

file_out.write( """<html> <meta charset="UTF-8"><head></head>
<style>
table   {
	margin-top: 50px;
	width: 1000px;
	border-collapse: collapse;
	}
table, th, td 
{
	border: 1px solid black;
	vertical-align:top;
	padding: 5px;
}
</style>
<body>
""") 

file_out.write( '<h1>%s</h1>' % ('Tuvastamata veaga'))

file_out.write( '<table style="padding:5px">')
linenr = 0
for uid in sorted(corrections.keys()):
	
	linenr +=1
	if linenr > 100: continue
	to_print = 0

	
	correction_sets = []
	

	for (i, correction) in enumerate(corrections[uid]):
			
		stats['total'] += 1
		flags = []
		
		text1 = Text(originals[uid]['text'])
		originals[uid]['tokenized'] = ' '.join(text1.word_texts)

		text2 = Text(correction['text'])
		#text2_words = text2.word_texts
		
		corrections[uid][i]['tokenized'] = ' '.join(text2.word_texts)
		ndiff_result = difflib.ndiff("\n".join(text1.word_texts).splitlines(1), "\n".join(text2.word_texts).splitlines(1))
		ndiff_result_list = list(ndiff_result)
		unified_diff_result = difflib.unified_diff("\n".join(text1.word_texts).splitlines(1), "\n".join(text2.word_texts).splitlines(1))

		html_diff_result = []
		for line in unified_diff_result:
			if line.startswith('-'):
				html_diff_result.append('<span style="color:red">%s</span>' % line)
			elif line.startswith('+'):
				html_diff_result.append('<span style="color:green">%s</span>' % line)
			elif line.startswith('?'):
				html_diff_result.append('<span style="color:gray">%s</span>' % line)
			else:
				html_diff_result.append('%s' % line)
		corrections[uid][i]['unified_diff_result'] = list(unified_diff_result)		
		corrections[uid][i]['html_diff_result'] = html_diff_result
		
		
		#algsed tööks vajalikud massiivid
		#text1
		#text2 
		
		#ndiff_result
		#unified_diff_result
		#et originaal säiliks töötame edasi koopiatega
		
		#finished
		
		finished = 0
		text1_copy  = Text(originals[uid]['text'])
		text2_copy= Text(correction['text'])
		
		text1_lemmas = text1_copy.lemmas
		text2_lemmas = text2_copy.lemmas
		
		
		text1_word_texts = text1_copy.word_texts
		text2_word_texts = text2_copy.word_texts
		
		text1_postags = text1_copy.postags
		text2_postags = text2_copy.postags
	
		text1_forms = text1_copy.forms
		text2_forms = text2_copy.forms
	
	
		
		ndiff_result_list_copy = copy.copy(ndiff_result_list)
		
		added = []
		deleted = []
		
		added_pos = []
		deleted_pos = []
		
		
		
		
		# esiteks lihtne kontroll, et tokeniseerimata originaal ja tokeniseerimata parandus ei erine omavahel
		if originals[uid]['text'] == correction['text']:
			flags.append('puudub')
			finished = 1
		if not finished and originals[uid]['tokenized'] == correction['tokenized']:
			flags.append('tühik')
			finished = 1
		
		#vaatame, kas kirjavahemärkidega tehti midagi
		if not finished:
			ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
			added_pos = [text1_postags[index] for index in ndiff_data['deleted_pos']]
			deleted_pos = [text2_postags[index] for index in ndiff_data['added_pos']]
			
			added_pos_uniq = list(set([text1_postags[index] for index in ndiff_data['deleted_pos']]))
			deleted_pos_uniq = list(set([text2_postags[index] for index in ndiff_data['added_pos']]))
			
			#print ('added_pos_uniq', added_pos_uniq)
			#print ('deleted_pos_uniq', deleted_pos_uniq)
			rowsets = {}
			#muudatused on seatud ainult kirjavahemärkidega
			if ''.join(added_pos_uniq) in ['Z', ''] and ''.join(deleted_pos_uniq) in ['Z', '']:
				flags.append('punktuatsioon')
				#correction_sets.append( {'type':'punktuatsioon', 'added': ndiff_data['added'], 'deleted': ndiff_data['deleted'] })
				
				
				finished = 1
			#muudatused on ka kirjavahemärkidega
			elif 'Z' in added_pos + deleted_pos:
				flags.append('punktuatsioon')
				
				#teeme siin sellise sammu, kus eemaldame kõik kirjavahemärgid ja saame uuesti võrrelda
				for (ind, pos) in reversed(list( enumerate(text1_postags))):
					
					if pos == 'Z':
						text1_lemmas.pop(ind)
						text1_word_texts.pop(ind)
						text1_postags.pop(ind)
						text1_forms.pop(ind)
						
				removed = []
				for (ind, pos) in reversed(list( enumerate(text2_postags))):
					if pos == 'Z':
						text2_lemmas.pop(ind)
						text2_word_texts.pop(ind)
						text2_postags.pop(ind)
						text2_forms.pop(ind)
				
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				#print ("+++++++")
				#print ("".join(ndiff_result_list_copy))
				ndiff_result_list_copy = list(new_ndiff_result)
				if not len(ndiff_result_list_copy):
					finished = 1
				#print ("".join(ndiff_result_list_copy))
				
		if not finished:
			#sõnade järjekorra kontrollimine
			# kui sõna on lause alguses, siis võrdleme seda lowercase
			ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
			
			#keerame esimesed sõnad lowercase
			if 0 in ndiff_data['added_pos']:
				#print (ndiff_data['added'][0])
				ndiff_data['added'][0] = ndiff_data['added'][0].lower()
				#print (ndiff_data['added'][0])
				
			if 0 in ndiff_data['deleted_pos']:
				#print (ndiff_data['deleted'][0])
				ndiff_data['deleted'][0] = ndiff_data['deleted'][0].lower()
				#print (ndiff_data['deleted'][0])
			if (sorted(ndiff_data['added']) == sorted(ndiff_data['deleted'])):
				flags.append('sõnajärg')
				correction_sets.append( {'type':'sõnajärg', 'added': ndiff_data['added'], 'deleted': ndiff_data['deleted'] })
				
				finished = 1
				
			elif intersection(ndiff_data['added'], ndiff_data['deleted']):
				flags.append('sõnajärg')
				
				deleted_elements_ind = []
				added_elements_ind = []
				#kustutame ära need sõnad, mis vahetasid asukohta
				for token in intersection(ndiff_data['added'], ndiff_data['deleted']):
					#kustutame ainult esimese esinemise
					deleted_elements_ind.append(ndiff_data['deleted_pos'][ndiff_data['deleted'].index(token)])
					added_elements_ind.append(ndiff_data['added_pos'][ndiff_data['added'].index(token)])
					correction_sets.append( {'type':'sõnajärg', 'added':  intersection(ndiff_data['added'], ndiff_data['deleted']), 'deleted': intersection(ndiff_data['added'], ndiff_data['deleted']) })
					
				for ind in reversed(sorted(deleted_elements_ind)):
					text1_lemmas.pop(ind)
					text1_word_texts.pop(ind)
					text1_postags.pop(ind)
					text1_forms.pop(ind)

				for ind in reversed(sorted(added_elements_ind)):
					text2_lemmas.pop(ind)
					text2_word_texts.pop(ind)
					text2_postags.pop(ind)
					text2_forms.pop(ind)
			
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				#print ("+++++++")
				#print ("".join(ndiff_result_list_copy))
				ndiff_result_list_copy = list(new_ndiff_result)
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				if not ndiff_data['changed']:
					finished = 1
				#print ("".join(ndiff_result_list_copy))
			
			
		if not finished:
			ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
			if not len(ndiff_data['added']):
				flags.append('sõnaüle')
				finished =1
			elif not len(ndiff_data['deleted']):
				flags.append('sõnapuudu')
				finished =1
		
		if not finished:
			
			if "".join(text1_word_texts) == "".join(text2_word_texts):
				flags.append('kokku-lahku')
				finished =1
			else:
				#otsin lisatud sõnade seas sõnu, mis on järjest positsioonidel ja mille kokkuliitmisel saab mõne kustutatud sõna
				#otsin kustutatud sõnade seas sõnu, mis on järjest positsioonidel ja mille kokkuliitmisel saab mõne lisatud sõna
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				#added_pos = [text1_postags[index] for index in ndiff_data['deleted_pos']]
				#deleted_pos = [text2_postags[index] for index in ndiff_data['added_pos']]
				
				joined = {}
				
				
				text1_word_texts_old  = []
				
				#kokku liidetud sõnad
				while not text1_word_texts == text1_word_texts_old:
					
					new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
					ndiff_result_list_copy = list(new_ndiff_result)
					text1_word_texts_old = copy.copy(text1_word_texts)
					ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
					
					
					remove_added = []
					remove_deleted = []
					
					for pos in reversed(ndiff_data['deleted_pos']):
						ind = ndiff_data['deleted_pos'].index(pos)
						if pos+1 in ndiff_data['deleted_pos']:

							joinedword = ndiff_data['deleted'][ind] + ndiff_data['deleted'][ind+1]
							if joinedword in ndiff_data['added']:
								#print (ndiff_data['deleted'], ndiff_data['added'])
								remove_added.append(ndiff_data['added_pos'][ndiff_data['added'].index(joinedword)])
								remove_deleted.append(pos)
								remove_deleted.append(pos+1)
								#print (remove_deleted, remove_added)
							break
					
					if len(remove_deleted):
						flags.append('kokku-lahku')

						for ind in reversed(sorted(remove_deleted)):
							text1_lemmas.pop(ind)
							text1_word_texts.pop(ind)
							text1_postags.pop(ind)
							text1_forms.pop(ind)
						for ind in reversed(sorted(remove_added)):	
							text2_lemmas.pop(ind)
							text2_word_texts.pop(ind)
							text2_postags.pop(ind)
							text2_forms.pop(ind)
							
					text1_word_texts_old = copy.copy(text1_word_texts)
				
				text1_word_texts_old  = []
				#lahku tõstetud sõnad
				while not text1_word_texts == text1_word_texts_old:
					
					new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
					ndiff_result_list_copy = list(new_ndiff_result)
					text1_word_texts_old = copy.copy(text1_word_texts)
					ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
					
					
					remove_added = []
					remove_deleted = []
					for pos in reversed(ndiff_data['added_pos']):
						ind = ndiff_data['added_pos'].index(pos)
						if pos+1 in ndiff_data['added_pos']:

							joinedword = ndiff_data['added'][ind] + ndiff_data['added'][ind+1]
							if joinedword in ndiff_data['deleted']:
								#print (ndiff_data['added'], ndiff_data['deleted'])
								remove_deleted.append(ndiff_data['deleted_pos'][ndiff_data['deleted'].index(joinedword)])
								remove_added.append(pos)
								remove_added.append(pos+1)
								#print (remove_added, remove_deleted)
							break
					
					if len(remove_deleted):
						flags.append('kokku-lahku')

						for ind in reversed(sorted(remove_deleted)):
							text1_lemmas.pop(ind)
							text1_word_texts.pop(ind)
							text1_postags.pop(ind)
							text1_forms.pop(ind)
						for ind in reversed(sorted(remove_added)):	
							text2_lemmas.pop(ind)
							text2_word_texts.pop(ind)
							text2_postags.pop(ind)
							text2_forms.pop(ind)
							
					text1_word_texts_old = copy.copy(text1_word_texts)
					
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				ndiff_result_list_copy = list(new_ndiff_result)
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				if not ndiff_data['changed']:
					finished = 1
		
				
		if not finished:
			#sama sõna muu vorm
		
			if (text1_lemmas == text2_lemmas and text1_forms == text2_forms and ' '.join(text1_word_texts).lower()==' '.join(text2_word_texts).lower() ):
				flags.append('suurväike')
				finished =1
			elif (text1_lemmas == text2_lemmas and text1_forms == text2_forms and not text1_word_texts==text2_word_texts ):
				flags.append('paralleelvorm')
				finished =1
			
			else:
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				resolved_pos = []
				
				casediff = 0
				worddiff = 0
				for token_pos in intersection(ndiff_data['added_pos'], ndiff_data['deleted_pos']):
					if text1_lemmas[token_pos] == text2_lemmas[token_pos] and text1_forms[token_pos] == text2_forms[token_pos]:
						if text1_word_texts[token_pos].lower() == text2_word_texts[token_pos].lower():
							casediff +=1
						else:
							worddiff +=1
						resolved_pos.append(token_pos)
				
				if len (resolved_pos):
					if casediff:
						flags.append('suurväike')
					if worddiff:
						flags.append('paralleelvorm')
				
				for ind in reversed(sorted(resolved_pos)):
					text1_lemmas.pop(ind)
					text1_word_texts.pop(ind)
					text1_postags.pop(ind)
					text1_forms.pop(ind)
					text2_lemmas.pop(ind)
					text2_word_texts.pop(ind)
					text2_postags.pop(ind)
					text2_forms.pop(ind)
				
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				ndiff_result_list_copy = list(new_ndiff_result)		
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				if not ndiff_data['changed']:
					finished = 1
		if not finished:
			#sama sõna muu vorm
		
			#vaatas kogu teksti
			if (text1_lemmas == text2_lemmas and not text1_word_texts==text2_word_texts ):
	
				flags.append('valevorm')
				finished =1
			#vaatame samal positsioonil asuvaid asendusi
			else:
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				resolved_pos = []
				for token_pos in intersection(ndiff_data['added_pos'], ndiff_data['deleted_pos']):
					if len(intersection(text1_lemmas[token_pos].split('|'), text2_lemmas[token_pos].split('|'))):
					# if text1_lemmas[token_pos] == text2_lemmas[token_pos]:
						resolved_pos.append(token_pos)
						
				
				if len (resolved_pos):
					flags.append('valevorm')
				
				for ind in reversed(sorted(resolved_pos)):
					text1_lemmas.pop(ind)
					text1_word_texts.pop(ind)
					text1_postags.pop(ind)
					text1_forms.pop(ind)
					text2_lemmas.pop(ind)
					text2_word_texts.pop(ind)
					text2_postags.pop(ind)
					text2_forms.pop(ind)
				
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				ndiff_result_list_copy = list(new_ndiff_result)
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				if not ndiff_data['changed']:
					finished = 1
			

		if not finished:
			#sama vorm muu sõna
		
			if (text1_forms == text2_forms and not text1_lemmas==text2_lemmas ):
				flags.append('valelemma')
				finished =1
				
			#vaatame samal positsioonil asuvaid asendusi
			else:
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				resolved_pos = []
				for token_pos in intersection(ndiff_data['added_pos'], ndiff_data['deleted_pos']):
					sub_type = ''
					if text1_forms[token_pos] == text2_forms[token_pos] and not text1_lemmas[token_pos]==text2_lemmas[token_pos]:
						resolved_pos.append(token_pos)
					elif intersection(text1_forms[token_pos].split('|'), text2_forms[token_pos].split('|')) and not text1_lemmas[token_pos]==text2_lemmas[token_pos]:
						sub_type = '2'
						resolved_pos.append(token_pos)
					elif len(intersection(text1_forms[token_pos].split('|'), text2_forms[token_pos].split('|'))) and not len(intersection( text1_lemmas[token_pos].split('|'), text2_lemmas[token_pos].split('|'))):
						sub_type = '3'
						resolved_pos.append(token_pos)
					
				
				if len (resolved_pos):
					flags.append('valelemma'+sub_type)
				
				for ind in reversed(sorted(resolved_pos)):
					text1_lemmas.pop(ind)
					text1_word_texts.pop(ind)
					text1_postags.pop(ind)
					text1_forms.pop(ind)
					text2_lemmas.pop(ind)
					text2_word_texts.pop(ind)
					text2_postags.pop(ind)
					text2_forms.pop(ind)
				
				
				new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
				ndiff_result_list_copy = list(new_ndiff_result)
				ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
				if not ndiff_data['changed']:
					finished = 1
				
		
		if not finished:
			#nud<->nu tud<->tu  nudtud
		
			
			ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
			resolved_pos = []
			for token_pos in intersection(ndiff_data['added_pos'], ndiff_data['deleted_pos']):
				if  ( 'nud' in text1_forms[token_pos].split('|') or  'tud' in text1_forms[token_pos].split('|') ) and  len(intersection(text1_lemmas[token_pos].split('|'), text2_lemmas[token_pos].split('|')) ):
					resolved_pos.append(token_pos)
						
				
			if len (resolved_pos):
				#print('here')
				flags.append('nudtud')
				
			for ind in reversed(sorted(resolved_pos)):
				text1_lemmas.pop(ind)
				text1_word_texts.pop(ind)
				text1_postags.pop(ind)
				text1_forms.pop(ind)
				text2_lemmas.pop(ind)
				text2_word_texts.pop(ind)
				text2_postags.pop(ind)
				text2_forms.pop(ind)
				
			new_ndiff_result = difflib.ndiff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))
			ndiff_result_list_copy = list(new_ndiff_result)
			ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
			if not ndiff_data['changed']:
				finished = 1
	
		
		if not finished:
			
			flags.append('0')
			unified_remained_diff_result = difflib.unified_diff("\n".join(text1_word_texts).splitlines(1), "\n".join(text2_word_texts).splitlines(1))

			html_diff_result = []
			for line in unified_remained_diff_result:
				if line.startswith('-'):
					html_diff_result.append('<span style="color:red">%s</span>' % line)
				elif line.startswith('+'):
					html_diff_result.append('<span style="color:green">%s</span>' % line)
				elif line.startswith('?'):
					html_diff_result.append('<span style="color:gray">%s</span>' % line)
				else:
					html_diff_result.append('%s' % line)
			
			corrections[uid][i]['remained_diff'] = html_diff_result
		
		
		if finished :
			corrections[uid][i]['remained_diff'] = ''
		
		
		
		# tokeniseertud originaal ja tokeniseerimata originaal ei erine omavahel
		# esimene, mida kontrollime on lisatud v eemaldatud kirjavahemärkide olemasolu
		#, kui leiame, et need on olemas, siis võtame diff tulemusest 
		
		ndiff_data = get_data_from_ndiff(ndiff_result_list_copy)
		
		if len(flags)==1 and flags[0] == '0' and ndiff_data['added_pos'] == ndiff_data['deleted_pos']:
			flags=['00']
		
		
		corrections[uid][i]['correction_sets'] = correction_sets
		
		corrections[uid][i]['flags'] = flags	
		corrections[uid][i]['flags_label'] = "_".join(sorted(flags))
		if corrections[uid][i]['flags_label'] == '0' or corrections[uid][i]['flags_label'] == '00':
			corrections[uid][i]['remained_diff'] = ''
		
		
		
		
		
		rows_html  = ''
		rows_html  += '<tr><td colspan="3">&nbsp;</td><td><a href="diff/%s.html" target="_blank">Võrdlus:</a></td>\n' %( correction['id'])

		rows_html  += '<tr><td><b>%s</b></td><td>%s</td><td>%s</td><td rowspan="2">%s</td></tr>\n' %( uid, originals[uid]['text'], originals[uid]['tokenized'], "<br/>".join(correction['html_diff_result']) )
		rows_html  += '<tr><td><b>%s</b></td><td>%s</td><td>%s</td></tr>\n' %(  correction['id'], correction['text'],  correction['tokenized'])

		rows_html  += '<tr><td colspan="4">&nbsp;</td></tr>\n'
		
		
		
		kkey = "_".join(sorted(flags))
		if not kkey in collected_flags:
			collected_flags[kkey] = 0
		collected_flags[kkey] += 1
		#print (flags, correction['text'])
		if '0' in flags and kkey == '0':
			stats['lahendamata1'] +=1
		elif '0' in flags:
			stats['lahendamata2'] +=1
file_out.write('</table>')
file_out.write ('</body></html>') 
file_out.close()	
	
	
	
for label in collected_flags:
	#juba on olemas selline fail
	#if label == 'tundmatu': continue 
	
	print (label)
	filename2 = 'tulemus/%s.html' % label
	file_out = open(filename2, 'w')
	
	file_out.write( '<html> <meta charset="UTF-8"><head></head>') 
	file_out.write( """
	<style>

	table   {
		margin-top: 50px;
		width: 1000px;
		border-collapse: collapse;

		}
	table, th, td 
	{
		border: 1px solid black;
	
		vertical-align:top;
		padding: 5px;
	}
	</style>

	<body>
	""") 
	
	file_out.write( '<h1>%s (%d)</h1>' % (label,collected_flags[label]))
	file_out.write( '<h3>Kontrolliti %d parandust</h3>' % (stats['total']))
	file_out.write( '<h3>Viga tuvastatud: %d</h3>' % (stats['total']- stats['lahendamata1']-stats['lahendamata2']))
	file_out.write( '<h3>Viga tuvastamata: %d</h3>' % (stats['lahendamata1']))
	file_out.write( '<h3>Viga osaliselt tuvastamata: %d</h3>' % (stats['lahendamata2']))
	
	for label2 in sorted(collected_flags):
		file_out.write( '<span>%s <a href="%s.html">(%d)</a></span><br/>' % (label2,label2,collected_flags[label2]))
	
	
	file_out.write( '<table style="padding:5px">')
	for uid in sorted(corrections.keys()):
		for (i, correction) in enumerate(corrections[uid]):
			if not 'flags' in correction : continue
			if not len (correction['flags']): continue
			
			if not label ==  correction['flags_label']: continue
			rows_html  = ''
			
			
			
			rows_html  += '<tr><td>&nbsp;</td><td colspan="2">%s</td><td><a href="../morf/%s.html" target="_blank">Võrdlus:</a></td>\n' %( label, correction['id'])
			
			rows_html  += '<tr><td><b>%s</b></td><td>%s</td><td>%s</td><td rowspan="2">%s</td></tr>\n' %( uid, originals[uid]['text'], originals[uid]['tokenized'], "<br/>".join(correction['html_diff_result']) + '<hr/>' + "<br/>".join(correction['remained_diff']))
			rows_html  += '<tr><td><b>%s</b></td><td>%s</td><td>%s</td></tr>\n' %(  correction['id'], correction['text'],  correction['tokenized'])
			
			for corr_set in corrections[uid][i]['correction_sets']:
				
				rows_html  += '<tr><td>&nbsp;</td><td>%s</td><td><span style="color:red">%s</span> &lt;=== &gt; <span  style="color:green">%s</td><td></td></tr>\n' % (corr_set['type'],  ' '.join(corr_set['deleted']) , ' '.join(corr_set['added'] ) )
			
			rows_html  += '<tr><td colspan="4">&nbsp;</td></tr>\n'
			
			
			file_out.write(rows_html)
		
		
		
	file_out.write('</table>')
	
	
	
	
	file_out.write ('</body></html>') 
	file_out.close()
	
exit()