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Rocío López Anguita - rlanguit@ujaen.es
Arturo Montejo Ráez - amontejo@ujaen.es
Jaime Collado Montañez - jcollado@ujaen.es
SINAI Research Group 2019
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# INSTALLATION INSTRUCTIONS
## REQUIREMENTS
(Freeling version, Python, NumPy, etc.)
## INSTALLATION PROCEDURE
1.
2.
3.
...
## TESTING
(talk about the notebook to test it)
LICENSE.md 0 → 100644
# GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 [Free Software Foundation, Inc.](http://fsf.org/)
Everyone is permitted to copy and distribute verbatim copies of this license
document, but changing it is not allowed.
## Preamble
The GNU General Public License is a free, copyleft license for software and
other kinds of works.
The licenses for most software and other practical works are designed to take
away your freedom to share and change the works. By contrast, the GNU General
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versions of a program--to make sure it remains free software for all its users.
We, the Free Software Foundation, use the GNU General Public License for most
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### 12. No Surrender of Others' Freedom.
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pertinent obligations, then as a consequence you may not convey it at all. For
example, if you agree to terms that obligate you to collect a royalty for
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could satisfy both those terms and this License would be to refrain entirely
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### 13. Use with the GNU Affero General Public License.
Notwithstanding any other provision of this License, you have permission to
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### 14. Revised Versions of this License.
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If the Program specifies that a proxy can decide which future versions of the
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### 15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE
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CORRECTION.
### 16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY
COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS
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### 17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided above cannot
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liability in connection with the Program, unless a warranty or assumption of
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## END OF TERMS AND CONDITIONS ###
### How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest possible
use to the public, the best way to achieve this is to make it free software
which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest to attach
them to the start of each source file to most effectively state the exclusion
of warranty; and each file should have at least the *copyright* line and a
pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short notice like
this when it starts in an interactive mode:
<program> Copyright (C) <year> <name of author>
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w` and `show c` should show the appropriate
parts of the General Public License. Of course, your program's commands might
be different; for a GUI interface, you would use an *about box*.
You should also get your employer (if you work as a programmer) or school, if
any, to sign a *copyright disclaimer* for the program, if necessary. For more
information on this, and how to apply and follow the GNU GPL, see
[http://www.gnu.org/licenses/](http://www.gnu.org/licenses/).
The GNU General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may consider
it more useful to permit linking proprietary applications with the library. If
this is what you want to do, use the GNU Lesser General Public License instead
of this License. But first, please read
[http://www.gnu.org/philosophy/why-not-lgpl.html](http://www.gnu.org/philosophy/why-not-lgpl.html).
README.md 0 → 100644
# TextComplexity class
This class provides methods for the calculation of different complexity metrics on text.
# Files
(put here a description of files)
TextComplexityFreeling.py 0 → 100644
# -*- coding: utf-8 -*-
import freeling
import os
import re
from functools import reduce
import numpy as np
import scipy.stats
import math
class TextComplexityFreeling():
def __init__(self, lang='es'):
## Modify this line to be your FreeLing installation directory
FREELINGDIR = "/usr/local"
DATA = FREELINGDIR+"/share/freeling/"
self.lang = lang
freeling.util_init_locale("default")
# create language analyzer
self.la=freeling.lang_ident(DATA+"common/lang_ident/ident.dat")
# create options set for maco analyzer. Default values are Ok, except for data files.
op= freeling.maco_options(lang)
op.set_data_files( "",
DATA + "common/punct.dat",
DATA + lang + "/dicc.src",
DATA + lang + "/afixos.dat",
"",
DATA + lang + "/locucions.dat",
DATA + lang + "/np.dat",
DATA + lang + "/quantities.dat",
DATA + lang + "/probabilitats.dat")
# create analyzers
self.tk=freeling.tokenizer(DATA+lang+"/tokenizer.dat")
self.sp=freeling.splitter(DATA+lang+"/splitter.dat")
self.mf=freeling.maco(op)
# activate mmorpho modules to be used in next call
self.mf.set_active_options(False, True, True, True, # select which among created
True, True, False, True, # submodules are to be used.
True, True, True, True ) # default: all created submodules are used
# create tagger, sense anotator, and parsers
self.tg=freeling.hmm_tagger(DATA+lang+"/tagger.dat",True,2)
self.sen=freeling.senses(DATA+lang+"/senses.dat")
self.parser= freeling.chart_parser(DATA+lang+"/chunker/grammar-chunk.dat")
self.dep=freeling.dep_txala(DATA+lang+"/dep_txala/dependences.dat", self.parser.get_start_symbol())
# Para leer el texto que introducimos
f = open('./CREA_total.txt')
lines = f.readlines()
f.close()
crea = {}
for l in lines[1:1000]: # those words not in the 1000 most frequent words in CREA are low frequency words
data = l.strip().split()
crea[data[1]] = float(data[2].replace(',', ''))
self.crea = crea
pass
def textProcessing(self, text):
# meter todas las funciones en una patron de los tokens válidos
#ls = sen.analyze(ls)
sid=self.sp.open_session()
tokens = self.tk.tokenize(text)
#print("Tokens:", [w.get_form() for w in tokens])
#print("hay Tokens:", len(tokens))
ls = self.sp.split(sid,tokens,True)
#print("After split", len(ls))
ls = self.mf.analyze(ls)
#print("After morpho", len(ls))
ls = self.tg.analyze(ls)
#print("After tagger", len(ls))
ls = self.parser.analyze(ls)
#print("After parser", len(ls))
ls = self.dep.analyze(ls)
#print("After dependencies", len(ls))
self.sentences = ls
self.nsentences = len(ls)
self.sp.close_session(sid)
print('Las oraciones: ', self.sentences)
'''
Filtra aquellos tokens que no sean adjetivos, verbos o sustantivos
'''
pos_content_sentences = []
for sentence in self.sentences:
ws = sentence.get_words();
pos_content_sentences.append([w for w in ws if re.match('N.*|V.*|A.*', w.get_tag())])
self.pos_content_sentences = pos_content_sentences
return self.pos_content_sentences
def punctuationMarks(self):
#Solo nos interesa contar los tokens que sean signo de puntuación.
#Number of words.
punctuation = []
N_words = []
for words in self.sentences:
for w in words:
if re.match('F.*', w.get_tag()):
punctuation.append(w.get_form())
else:
N_words.append(w.get_form())
print('Las palabras del texto son : ', N_words)
self.N_words = len(N_words)
print('Number of words (N_w): ', self.N_words, '\n' )
self.npunctuation = len(punctuation)
self.punctuation = punctuation
print("PUNCTUATION MARKS = ", self.npunctuation,'\n')
return self.npunctuation, self.punctuation, self.N_words
def lexicalComplexity(self):
#Number of low frequency words
count = 0
for sentence in self.pos_content_sentences:
for w in sentence:
if w.get_form() not in self.crea:
count+=1
N_lfw = count
self.N_lfw = N_lfw
print("Number of low frequency words (N_lfw): ", self.N_lfw, "\n")
#Number of distinct content words
N_dcw = len(set([w.get_form().lower() for s in self.pos_content_sentences for w in s]))
self.N_dcw =N_dcw
print('Number of distinct content words (N_dcw) = ', self.N_dcw, '\n')
#Number of sentences
N_s = len(self.pos_content_sentences)
self.N_s = N_s
print("Number os sentences (N_s): ", self.N_s, "\n")
#Number of total content words
N_cw = reduce((lambda x, y: x + y), [len(s) for s in self.pos_content_sentences])
self.N_cw = N_cw
print("Number of total content words (N_cw): ", self.N_cw, "\n")
#Lexical Distribution Index
LDI = N_dcw / float(N_s)
self.LDI = LDI
print("Lexical Distribution Index (LDI) = ", self.LDI, '\n')
#Index of Low Frequency Words
ILFW = N_lfw / float(N_cw)
self.ILFW =ILFW
print("Index Low Frequency Words (ILFW) = ", self.ILFW, '\n')
#Lexical Complexity
LC = (LDI + ILFW) / 2
self.LC = LC
print ("LEXICAL COMPLEXITY INDEX (LC) =", LC, "\n")
return self.N_lfw, self.N_cw, self.N_dcw, self.N_s, self.LDI, self.ILFW, self.LC
def ssReadability(self):
#Number of rare words
byfreq = sorted(self.crea, key=self.crea.__getitem__, reverse=True)
byfreq = byfreq[:1500]
count = 0
for sentence in self.pos_content_sentences:
for w in sentence:
if w.get_form().lower() not in byfreq:
count +=1
N_rw = count
self.N_rw = N_rw
print("Number of rare words (N_rw): ", self.N_rw, "\n")
SSR = 1.609*(self.N_words / self.N_s) + 331.8* (self.N_rw /self.N_words) + 22.0
self.SSR= SSR
print ("SPAULDING SPANISH READABILITY (SSR) ", self.SSR, "\n")
return self.N_rw, self.SSR
def sentenceComplexity(self):
#Number of complex sentences
N_cs = 0
for sentence in self.sentences:
previous_is_verb = False
count = 0
for words in sentence:
for w in words:
if re.match('V.*', w.get_tag()):
if (previous_is_verb):
count += 1
previous_is_verb = False
else:
previous_is_verb = True
else:
previous_is_verb = False
if count>0:
N_cs += 1
self.N_cs = N_cs
#print("Number of complex sentences: ", self.N_cs, "\n")
ASL = self.N_words / self.N_s
self.ASL = ASL
print("Average Sentence Length (ASL) = ", self.ASL, '\n')
CS = self.N_cs / self.N_s
self.CS = CS
print("Complex Sentences (CS) = ", self.CS, '\n')
SCI = (ASL + CS)/ 2
self.SCI = SCI
print("SENTENCE COMPLEXITY INDEX:(SCI) = ", self.SCI, "\n")
return self.N_cs, self.ASL, self.CS, self.SCI
def autoReadability(self):
#Number of characters
count = 0
listwords = []
for words in self.sentences:
for w in words:
if re.match('\r\n.*', w.get_tag()):
count +=1
else:
listwords.append(w.get_form())
self.listwords = listwords
N_charac = 0
for characters in self.listwords:
N_charac += len(characters)
self.N_charac = N_charac
#print("Number of characters: ", self.N_charac, "\n")
ARI = 4.71 * self.N_charac / self.N_words + 0.5 * self.N_words/ self.N_s - 21.43
self.ARI = ARI
print("AUTOMATED READABILITY INDEX (ARI) = ", self.ARI, '\n')
return self.N_charac, self.ARI, self.listwords
def getDepth(self, ptree, depth=0):
node = ptree.begin()
info = node.get_info()
nch = node.num_children()
if (nch == 0) :
return depth
else :
child_depth = []
for i in range(nch) :
child = node.nth_child_ref(i)
child_depth.append(self.getDepth(child, depth+1))
return max(child_depth)
def embeddingDepth(self):
##output results
max_list = []
for s in self.sentences:
tr = s.get_parse_tree()
max_list.append(self.getDepth(tr,0))
#print('Longitud mi lista es:', len(max_list))
#print('Mi lista es:', max_list)
mean_max_list = sum(max_list)/float(len(max_list))
max_max_list = max(max_list)
min_max_list = min(max_list)
print('MAXIMUN EMBEDDING DEPTH OF SENTENCE (MaxDEPTH): ', max_max_list, '\n')
print('MINIMUN EMBEDDING DEPTH OF SENTENCE (MinDEPTH): ', min_max_list, '\n')
print('AVERAGE EMBEDDING DEPTH OF SENTENCE (MeanDEPTH): ', mean_max_list, '\n')
#lin=sys.stdin.readline()
self.max_max_list = max_max_list
self.min_max_list = min_max_list
self.mean_max_list = mean_max_list
return self.max_max_list, self.min_max_list, self.mean_max_list
def readability(self):
#Number of syllables and Number of words with 3 or more syllables:tagger
n_syllables = 0
n_syllables3 = 0
for words in self.listwords:
count=0
for character in words:
if re.match('a|e|i|o|u|y', character):
n_syllables +=1
count+=1
if count>=3:
n_syllables3 += 1
self.n_syllables = n_syllables
self.n_syllables3 = n_syllables3
#Number of letters
nletters= 0
letters = []
vecletters =[]
for word in self.listwords:
if re.match('[a-zA-Z]|á|ó|í|ú|é', word):
letters.append(word)
nletters+=len(word)
vecletters.append(len(word))
self.letters = letters
self.nletters = nletters
self.vecletters= vecletters
huertareadability = 206.835 - 60 * (self.n_syllables / self.N_words) - 102 * (self.nsentences / self.N_words)
print("THE READABILITY OF HUERTA: ", huertareadability, "\n")
self.huertareadability = huertareadability
ifszreadability = 206.835 - 62.3 * (self.n_syllables / self.N_words) - (self.N_words / self.nsentences)
print("THE READABILITY IFSZ: ", ifszreadability, "\n")
self.ifszreadability = ifszreadability
self.syll_words = self.n_syllables / self.N_words
polinicompressibility = 95.2 - 9.7 * (self.nletters / self.N_words) - 0.35 * (self.N_words / self.nsentences)
print("THE COMPRESSIBILITY OF GUTIÉRREZ POLINI: ", polinicompressibility, "\n")
self.polinicompressibility = polinicompressibility
self.words_sen = self.N_words / self.nsentences
x=self.nletters / self.N_words
varianza=np.var(self.vecletters)
mureadability= (self.N_words /(self.N_words-1))*(x/varianza)*100
print("READABILITY MU: ", mureadability, "\n")
self.mureadability = mureadability
return self.n_syllables, self.n_syllables3, self.nletters, self.huertareadability, self.ifszreadability, self.polinicompressibility, self.mureadability, self.syll_words, self.words_sen
def ageReadability(self):
minimumage = 0.2495 *(self.N_words/self.nsentences) + 6.4763 * (self.n_syllables /self.N_words) - 7.1395
print("MINIMUM AGE TO UNDERSTAND A TEXT: ", minimumage, "\n")
self.minimumage = minimumage
solreadability= -2.51+0.74*(3.1291+1.0430*math.sqrt(self.n_syllables3*(30/self.nsentences)))
print("THE READABILITY SOL: ", solreadability, "\n")
self.solreadability = solreadability
return self.minimumage, self.solreadability
def yearsCrawford(self):
years = -20.5 *(self.nsentences/self.N_words) + 4.9 * (self.n_syllables /self.N_words) - 3.407
print("YEARS NEEDED: ", years, "\n")
self.years = years
return self.years
\ No newline at end of file
examples.ipynb 0 → 100644
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