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DataExtractor.py
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#==============================================================================================
# The Jabalín morphological generator for Arabic verbs
#
# Copyright (c) 2012 Susana López Hervás, Alicia González Martínez, Antonio Moreno Sandoval
#
# 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/>
#==============================================================================================
# ________________________________________________________
# | ____________________________________________________ |
# | | | |
# | | EXTRACTS QUANTITATIVE DATA FROM JABALIN LEXICONS | |
# | |____________________________________________________| |
# |________________________________________________________|
# 1 number of roots, verbs and mean pattern per root
# 2 number patterns per root
# 3 freq of patterns
# 4 predicted (expected) freq of pattern co-occurrences
# 5 actual (observed) freq of pattern co-ocurrences
# 6 freq of each radical from a specified list of patterns
# 7 freq of patterns from triliteral roots that meet R2=R3 (biliterals)
# 8 freq each pattern for pat/root=1
# 9 freq of patterns from roots without Form I and QI
# 10 freq of vocalism morphemes
# 11 freq of patterns according to traditional counting of prosody
import util_DataExtractor
import itertools
import re
def quantitativeData():
print("processing input lexicons.....")
util_DataExtractor.preprocess_lexicons() ### prepares the lexicons to extract the data
# dict with each root and its list of codes: {root: [pat, pat, ...]}
RootsPatsTri=util_DataExtractor.saca_root_patterns(3) # triliteral
RootsPatsQua=util_DataExtractor.saca_root_patterns(4) # quadriliteral
TotalRootsTri=len(RootsPatsTri) # number triliteral roots
TotalRootsQua=len(RootsPatsQua) # number quadriliteral roots
# _______________ _______________
# |_______________| 1 |_______________|
Lemas_per_rootTri,Lemas_per_rootQua=[],[] # list with the number of lemmas for each root
TotalVerbsTri=0; TotalVerbsQua=0 # number of verbs
for code_lem in RootsPatsTri.values(): # triliteral
num_verbs_each_root=len(code_lem)
Lemas_per_rootTri.append(num_verbs_each_root)
TotalVerbsTri=TotalVerbsTri+num_verbs_each_root
for code_lem in RootsPatsQua.values(): # quadriliteral
num_verbs_each_root=len(code_lem)
Lemas_per_rootQua.append(num_verbs_each_root)
TotalVerbsQua=TotalVerbsQua+num_verbs_each_root
# _______________ _______________
# |_______________| 3 |_______________|
NumPatTri,NumPatQua={},{}
# {root: [pat, pat, ...]}
for root,codes in RootsPatsTri.items(): # triliteral
for cod in codes:
NumPatTri[cod]=NumPatTri.get(cod,0)+1
## NumPatTri = {'I':32, 'II':120, ...}
for root,codes in RootsPatsQua.items(): # quadriliteral
for cod in codes:
NumPatQua[cod]=NumPatQua.get(cod,0)+1
freqPatTri,freqPatQua={},{} # pattern - freq abs - freq per Total roots
for k,v in util_DataExtractor.freq_dic(NumPatTri,TotalRootsTri).items():
pat,num,perc=k,v[0],v[1]
freqPatTri[pat]=(num,perc)
for k,v in util_DataExtractor.freq_dic(NumPatQua,TotalRootsQua).items():
pat,num,perc=k,v[0],v[1]
freqPatQua[pat]=(num,perc)
# _______________ _______________
# |_______________| 4 |_______________|
## EG. FREQ OF COOCURRENCY PATTERNS II AND III
##
## pattern abs_freq(no. verbs of this pattern) rel_freq(over n. total roots)
## II 1811 56.1
## III 996 30.8
##
## freq relative coocurrence II & III -> (56.1 * 30.8) / 100 = 17.2788
## freq absolute coocurrence II & III -> (17.2788 * 3230{i.e.Total no. Roots}) / 100 = 558
def PredictCoocur(DicFreq,TotalR):
DicKeys=sorted(list(DicFreq.keys()),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
pairs_dic=list(itertools.combinations(sorted(DicKeys,key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare)),2))
# in pairs_dic we include a list of all relevant combinations of pattern pairs [('II','III'), ('II','IV'), ...]
CoocurFreq={}
for pat in pairs_dic:
x,y=pat[0],pat[1]
# we calculate the predicted freq of each pair of patterns
resul_freq=round((float(DicFreq[x][1])*float(DicFreq[y][1]))/100,2)
# we calculate how many roots are expected to have those patterns
resul_abs=int((resul_freq*TotalR)/100)
value={y:(resul_abs,resul_freq)}
CoocurFreq.setdefault(x,value).update(value)
# CoocurFreq -> { X : {'XIII': (1, 0.05), 'XII': (12, 0.39), 'XI': (14, 0.46), 'XV': (0, 0.03)}, ... }
return CoocurFreq
# _______________ _______________
# |_______________| 5 |_______________|
def ActualCoocur(RootsPats, TotalR):
# RootsPats = {r: [p,p,p], ...}
CoocurFreq={}
for root,patterns in RootsPats.items():
PairsPats=list(itertools.combinations(sorted(patterns,key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare)),2))
# !! PairPats -> there are some cases in which a root has two verbs of the same pattern; one of them is archaic
for pair in PairsPats:
x,y=pair[0],pair[1]
if x in CoocurFreq:
if y in CoocurFreq[x]:
CoocurFreq[x][y]+=1
else:
CoocurFreq[x][y]=1
else: CoocurFreq[x]={y:1}
for pat1,listafreq in CoocurFreq.items():
for pat2,fq in listafreq.items():
CoocurFreq[pat1][pat2]=(fq, round((fq*100)/TotalR,2))
return CoocurFreq
###### future work:
###### evaluate statistical significance with chi square-test and G-test
###### Chi-test
###### G-test
# _______________ _______________
# |_______________| 6 |_______________|
def takes_radical_freqs_from_pats(code,lista_pats):
'extracts a list of selected roots and gets the frequency data'
list_target_roots=set()
with open('lexicon_lemas_procesado.txt', encoding='utf8') as f:
for line in f:
try: l,r,c=line.strip().split()
except: print(line)
# ========= we define the variables to filter the roots we want to extract the frequencies from =========== #
# length of root
trilit = (code[0]=='1') and (len(r)==3)
quadrilit = (code[0]=='2') and (len(r)==4)
# filter of geminated root
GeminTri = (trilit) and ((code[1]=='2' and r[1]==r[2]) or (code[1]=='1')) #and r[1]!=r[2]))
GeminQua = (quadrilit) and ((code[1]=='2' and r[0]+r[1]==r[2]+r[3]) or (code[1]=='1' and r[0]+r[1]!=r[2]+r[3]))
# filter of patterns
matching_Pat = (code[2]=='1') or ((code[2]=='2') and (c in lista_pats))
# ========================================================================================================== #
if matching_Pat and (GeminTri or GeminQua):
list_target_roots.add(r) # LIST OF TARGET ROOTS
list_target_roots=list(list_target_roots) # converts the set into a list
total_Roots=len(list_target_roots) # total number of roots
RadicalsFreq=[] # list to insert the frequencies
if len(list_target_roots[0])==3:
length_root=3
Radicals = [{},{},{}] # triliteral roots
else:
length_root=4
Radicals = [{},{},{},{}] # quadriliteral roots
for raiz in list_target_roots: # go through the list of roots
i=0
for r in raiz: # takes each of the char from the root
Radicals[i][r]=Radicals[i].get(r,0)+1
i+=1
Aux=[]
for rad in Radicals:
Aux.append(util_DataExtractor.freq_dic(rad,total_Roots))
RadicalsFreq.append(Aux)
return RadicalsFreq, total_Roots, length_root
def print_freqs(lista_freqR, total_R, length_root): # tri y qua
print('\ttotal: %d\n' % (total_R))
if length_root==3:
print('Char\tR1abs\tR1%\tR2abs\tR2%\tR3abs\tR3%')
for item in lista_freqR:
R1,R2,R3=item[0],item[1],item[2]
for cons,freq in R1.items():
r1abs,r1fq=freq[0],freq[1]
if cons in R2: r2abs,r2fq=R2[cons][0],R2[cons][1]
else: r2abs,r2fq=0,0
if cons in R3: r3abs,r3fq=R3[cons][0],R3[cons][1]
else: r3abs,r3fq=0,0
print(cons,r1abs,r1fq,r2abs,r2fq,r3abs,r3fq,sep='\t')
elif length_root==4:
print('Char\tR1abs\tR1%\tR2abs\tR2%\tR3abs\tR3%\tR4abs\tR4%')
for item in lista_freqR:
R1,R2,R3,R4=item[0],item[1],item[2],item[3]
for cons,freq in R1.items():
r1abs,r1fq=freq[0],freq[1]
if cons in R2: r2abs,r2fq=R2[cons][0],R2[cons][1]
else: r2abs,r2fq=0,0
if cons in R3: r3abs,r3fq=R3[cons][0],R3[cons][1]
else: r3abs,r3fq=0,0
if cons in R4: r4abs,r4fq=R4[cons][0],R4[cons][1]
else: r4abs,r4fq=0,0
print(cons,r1abs,r1fq,r2abs,r2fq,r3abs,r3fq,r4abs,r4fq,sep='\t')
return
# _______________ _______________
# |_______________| 7 |_______________|
def calculateBilitFreq(RootsPats, num_radicals):
BilitFreq={} # just patterns from biliteral root -> {pat: abs}
if num_radicals=='3':
for root,patterns in RootsPats.items():
if root[1]==root[2]:
for pat in patterns:
BilitFreq[pat]=BilitFreq.get(pat,0)+1
return BilitFreq
elif num_radicals=='4':
for root,patterns in RootsPats.items():
if root[0]+root[1]==root[2]+root[3]:
for pat in patterns:
BilitFreq[pat]=BilitFreq.get(pat,0)+1
return BilitFreq
# _______________ _______________
# |_______________| 8, 9 |_______________|
RootsPatsBoth=RootsPatsTri
RootsPatsBoth.update(RootsPatsQua)
def WithoutPatternI_OneRPatPerRoot(RootsPats):
'''it does two things:
extracts freq of patterns with one pattern per root
and extracts freq of patterns without pattern I'''
freqOnePat_per_root={} # pattern per root Ratio = 1
freqMultipleTri,freqTri={},{} # triliteral
freqMultipleQua,freqQua={},{} # quadriliteral
for Root,Patterns in RootsPats.items():
Patterns=sorted(Patterns, key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
Patterns=list(map((lambda p: re.sub('^I[aiu]{2}','I',p)), Patterns))
# freq pattern that meet pat/root=1
if len(Patterns)==1:
for pat in Patterns:
freqOnePat_per_root[pat]=freqOnePat_per_root.get(pat,0)+1
# freq pattern from triliteral root with no form I
if 'I' not in Patterns and len(Root)==3:
# no. patterns from TriRoots without Form I
for pat in Patterns:
freqTri[pat]=freqTri.get(pat,0)+1
# freq pattern combinations from TriRoots without
# Form I and more than one single pattern
if len(Patterns)>1:
pat=' - '.join(Patterns)
freqMultipleTri[pat]=freqMultipleTri.get(pat,0)+1
# freq pattern from quadriliteral root with no form QI
elif 'QI' not in Patterns and len(Root)==4:
# no. patterns from QuaRoots without Form QI
for pat in Patterns:
freqQua[pat]=freqQua.get(pat,0)+1
# no. pattern combinations from QuaRoots without Form QI
# and more than one single pattern
if len(Patterns)>1:
pat=' - '.join(Patterns)
freqMultipleQua[pat]=freqMultipleQua.get(pat,0)+1
return freqOnePat_per_root, freqTri, freqMultipleTri, freqQua, freqMultipleQua
# _______________ _______________
# |_______________| 10 |_______________|
def freqVocalismOneGroup(RootsPats):
'''Patterns Vocalism
Iau aa-au
Iai,VII-XV,QIII,QIV aa-ai
Iuu au-au
Iia ai-aa
II,III,IV,QI aa-ui
Iaa,V,VI,QII aa-aa
Iii ai-ai'''
FreqVoc={}
for patterns in RootsPats.values():
for pat in patterns:
if pat=='Iau':
FreqVoc['aa-au']=FreqVoc.get('aa-au',0)+1
elif pat in ['Iai','VII','VIII','IX','X','XI','XII',\
'XIII','XIV','XV','QIII','QIV']:
FreqVoc['aa-ai']=FreqVoc.get('aa-ai',0)+1
elif pat=='Iuu':
FreqVoc['au-au']=FreqVoc.get('au-au',0)+1
elif pat=='Iia':
FreqVoc['ai-aa']=FreqVoc.get('ai-aa',0)+1
elif pat in ['II','III','IV','QI']:
FreqVoc['aa-ui']=FreqVoc.get('aa-ui',0)+1
elif pat in ['Iaa','V','VI','QII']:
FreqVoc['aa-aa']=FreqVoc.get('aa-aa',0)+1
elif pat=='Iii':
FreqVoc['ai-ai']=FreqVoc.get('ai-ai',0)+1
else:
print('fail in pattern: %s' % pat)
TotalVoc=0
for i in FreqVoc.values(): TotalVoc=TotalVoc+i
return FreqVoc, TotalVoc
def freqVocalismSeparated(RootsPats):
''' Perfective
Patterns Vocalism
Iau,Iai,VII-XV,QIII,QIV,II,III,IV,QI,Iaa,V,VI,QII aa
Iuu au
Iia,Iii ai
Imperfective
Patterns Vocalism
Iau,Iuu au
Iai,VII-XV,QIII,QIV,Iii ai
Iia,Iaa,V,VI,QII aa
II,III,IV,QI ui'''
FreqVocP,FreqVocI={},{}
for patterns in RootsPatsBoth.values():
for pat in patterns:
# perfective vocalism
if pat in ['Iau','Iai','VII','VIII','IX','X','XI','XII','XIII','XIV',\
'XV','QIII','QIV','II','III','IV','QI','Iaa','V','VI','QII']:
FreqVocP['aa']=FreqVocP.get('aa',0)+1
elif pat == 'Iuu':
FreqVocP['au']=FreqVocP.get('au',0)+1
elif pat in ['Iia','Iii']:
FreqVocP['ai']=FreqVocP.get('ai',0)+1
else:
print('fail in pattern (perfective): %s' % pat)
# imperfective vocalism
if pat in ['Iau','Iuu']:
FreqVocI['au']=FreqVocI.get('au',0)+1
elif pat in ['Iai','VII','VIII','IX','X','XI','XII','XIII','XIV','XV','QIII','QIV','Iii']:
FreqVocI['ai']=FreqVocI.get('ai',0)+1
elif pat in ['Iia','Iaa','V','VI','QII']:
FreqVocI['aa']=FreqVocI.get('aa',0)+1
elif pat in ['II','III','IV','QI']:
FreqVocI['ui']=FreqVocI.get('ui',0)+1
else:
print('fail in pattern (imperfective): %s' % pat)
TotalVocP,TotalVocI=0,0
for i in FreqVocP.values(): TotalVocP=TotalVocP+i
for i in FreqVocI.values(): TotalVocI=TotalVocI+i
return FreqVocP, TotalVocP, FreqVocI, TotalVocI
# _______________ _______________
# |_______________| 11 |_______________|
def traditional_counting(VarForm):
PerfectiveForms = util_DataExtractor.saca_perfective_forms(VarForm) # {pat: [form, form, ...], ...}
FreqProsody={}
for pat,forms in PerfectiveForms.items():
for f in forms:
input_f = f # for checking errors in forms
f=f.replace('آ','أَا') # madda normalization
f=re.sub(r'(.)ّ',r'\1ْ\1',f) # shadda normalization
f = re.sub('.ْ','0',f) # Convert SAKIN letter into 0
for s in ['ا','و','ي','ى']: # Convert MAMDOOD letter into 0
f = re.sub(s,'0',f)
f = re.sub('.[َُِ]','1',f) # Convert MUTAHARRIK letter into 1
if not re.search('[^10]',f):
# traditional accumulative counting conversion
f = re.sub('10','2',f)
f = re.sub('12','3',f)
f = re.sub('22','4',f)
# calculate total weight
n=sum(list(map(int,list(f))))
# convert into syllabic weight
f = re.sub('4','HH',f) ## 1010 = 22 = 4 = HH
f = re.sub('3','LH',f) ## 110 = 12 = 3 = LH
f = re.sub('2','H',f) ## 10 = 10 = 2 = H
f = re.sub('1','L',f) ## 1 = 1 = 1 = L
f = re.sub('H0','SH',f) ## [H0 = SH] // SH computa lo mismo que H
else: print('Error in form: %s\tinput form: %s' % (f, input_f))
# pattern total forma_Prosody freq_abs
# {(pat,n,f):freq, ...}
FreqProsody[(pat,n,f)]=FreqProsody.get((pat,n,f),0)+1
return FreqProsody
# ******************************************************************************
salir = False
while salir==False:
option=input('''
________________________________________\n
WRITE NUMBER OF SELECTED OPTION\n\n
1\tnumber of roots, verbs and mean pattern per root\n
2\tnumber patterns per root\n
3\tfreq of patterns\n
4\tpredicted (expected) freq of pattern co-occurrences\n
5\tactual (observed) freq of pattern co-ocurrences\n
6\tfreq of each radical from a specified list of patterns\n
7\tfreq of patterns from triliteral roots that meet R2=R3 (biliterals)\n
8\tfreq of each pattern for pat/root=1\n
9\tfreq of patterns from roots without Form I\n
10\tfreq of vocalism morphemes\n
11\tfreq of patterns according to traditional counting of prosody\n
0\texit\n
________________________________________\n''')
if option == '0': salir=True
elif option == '1':
print('\nNUMBER OF ROOTS, VERBS AND MEAN PATTERNS PER ROOT')
print('\ntriliteral roots: %d' % TotalRootsTri)
print('triliteral verbs: %d' % TotalVerbsTri)
print('pattern/triliteral root: %.2f\n' % round(TotalVerbsTri/TotalRootsTri,2))
print('quadriliteral roots: %d' % TotalRootsQua)
print('quadriliteral verbs: %d' % TotalVerbsQua)
print('pattern/quadriliteral root: %.2f\n' % round(TotalVerbsQua/TotalRootsQua,2))
elif option == '2':
print('\n2. number patterns per root')
pats_per_rootTri,pats_per_rootQua={},{}
for i in Lemas_per_rootTri: pats_per_rootTri[i]=pats_per_rootTri.get(i,0)+1 # triliteral
print('\nPatterns\tNo. TriRoots\t%\n')
for k,v in util_DataExtractor.freq_dic(pats_per_rootTri,TotalRootsTri).items():
print(str(k).ljust(15),str(v[0]).ljust(15),v[1])
for i in Lemas_per_rootQua: pats_per_rootQua[i]=pats_per_rootQua.get(i,0)+1 # quadriliteral
print('\n\nPatterns\tNo. QuaRoots\t%\n')
for k,v in util_DataExtractor.freq_dic(pats_per_rootQua,TotalRootsQua).items():
print(str(k).ljust(15),str(v[0]).ljust(15),v[1])
elif option == '3':
print('\nPat\tFreq\t% TriRoots\n')
DicKeys=sorted(list(freqPatTri.keys()),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
for p in DicKeys:
print(p.ljust(7),str(freqPatTri[p][0]).ljust(7),str(freqPatTri[p][1]))
print('\n\nPat\tFreq\t% QuaRoots\n')
DicKeys=sorted(list(freqPatQua.keys()),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
for p in DicKeys:
print(p.ljust(7),str(freqPatQua[p][0]).ljust(7),str(freqPatQua[p][1]))
elif option == '4':
print('\npredicted freqs for Triliteral pattern co-occurrences\n')
PredCoocurFqTri=PredictCoocur(freqPatTri,TotalRootsTri) # gets predicted freqs
util_DataExtractor.printDic_ordenado(PredCoocurFqTri) # prints predicted freqs
print('\npredicted freqs for Quadriliteral pattern co-occurrences\n')
PredCoocurFqQua=PredictCoocur(freqPatQua,TotalRootsQua) # gets predicted freqs
util_DataExtractor.printDic_ordenado(PredCoocurFqQua) # prints predicted freqs
elif option == '5':
print('\nactual freqs for Triliteral pattern co-occurrences\n')
ActualCoocurFqTri=ActualCoocur(RootsPatsTri,TotalRootsTri) # gets predicted freqs
util_DataExtractor.printDic_ordenado(ActualCoocurFqTri) # prints predicted freqs
print('\nactual freqs for Quadriliteral pattern co-occurrences\n')
ActualCoocurFqQua=ActualCoocur(RootsPatsQua,TotalRootsQua) # gets predicted freqs
util_DataExtractor.printDic_ordenado(ActualCoocurFqQua) # prints predicted freqs
elif option == '6':
# var_length: tri=1 / qua=2
# var_gemin: no_especif=1 / yes=2
# var_pat: all=1 / select=2 -> var_pat_list: [list of patterns]
var_length=input('write 1 for triliteral roots or 2 for quadriliteral:\n')
var_gemin=input('write 1 all times of roots and 2 for geminated roots:\n')
var_pat=input('write 1 for all patterns or 2 if you want to specify the patterns:\n')
if var_pat.strip()=='2': var_list_pat=input('write the pattern(s) separated by spaces:\n').strip().split()
elif var_pat.strip()=='1': var_list_pat=[]
# 3-digit code with info: lenghth of root / filter of patterns / filter of consonants
code_filter=var_length+var_gemin+var_pat
# apply function that extracts the root list and its freq
radic_freqs, radic_total, length_r = takes_radical_freqs_from_pats(code_filter,var_list_pat)
# prints the frequency data
print_freqs(radic_freqs, radic_total, length_r)
elif option == '7':
print('\nPattern freq from triliteral roots that meet R2=R3\n')
BilitFreq=calculateBilitFreq(RootsPatsTri,'3')
DicKeys=sorted(list(BilitFreq.keys()),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
for p in DicKeys:
print(p,BilitFreq[p],sep='\t')
print('\nPattern freq from quadriliteral roots that meet R1+R2=R3+R4\n')
BilitFreq=calculateBilitFreq(RootsPatsQua,'4')
DicKeys=sorted(list(BilitFreq.keys()),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
for p in DicKeys:
print(p,BilitFreq[p],sep='\t')
elif option == '8':
print('\nfreq each pattern for pat/root=1\n')
freqOnePat_per_root = WithoutPatternI_OneRPatPerRoot(RootsPatsBoth)[0]
for k,v in util_DataExtractor.freq_dic(freqOnePat_per_root).items(): print(k.ljust(23),v)
elif option == '9':
freqOnePat_per_root, freqTri, freqMultipleTri, freqQua, freqMultipleQua = WithoutPatternI_OneRPatPerRoot(RootsPatsBoth)
print('\nfreq pats of roots without Form I\n')
for k,v in util_dataEctractor.freq_dic(freqTri).items(): print(k.ljust(23),v)
print('\nfreq multiple patterns of roots without Form I for pat/TriRoot>1\n')
for k,v in util_DataExtractor.freq_dic(freqMultipleTri).items(): print(k.ljust(34),v)
print('\nfreq pats of roots without Form QI\n')
for k,v in util_DataExtractor.freq_dic(freqQua).items(): print(k.ljust(23),v)
print('\nfreq multiple patterns of roots without Form QI for pat/QuaRoot>1\n')
for k,v in util_DataExtractor.freq_dic(freqMultipleQua).items(): print(k.ljust(34),v)
elif option == '10':
VarVocalism = input('write 1 if you want to calculate the frequencies for perfective and imperfective vocalism together, write 2 if separatedly\n')
if VarVocalism == '1':
FreqVoc, TotalVoc = freqVocalismOneGroup(RootsPatsBoth)
print('vocal\tlemas\tfreq\n')
for k,v in FreqVoc.items():
freq=round(v*100/TotalVoc,1)
print(k,v,freq,sep='\t')
print('\ntotal: %d' % TotalVoc)
elif VarVocalism == '2':
FreqVocP, TotalVocP, FreqVocI, TotalVocI = freqVocalismSeparated(RootsPatsBoth)
print('\nPerfective\nvocal\tlemas\tfreq\n')
for k,v in FreqVocP.items():
freq=round(v*100/TotalVocP,1)
print(k,v,freq,sep='\t')
print('\ntotal: %d' % TotalVocP)
print('\n\nImperfective\nvocal\tlemas\tfreq\n')
for k,v in FreqVocI.items():
freq=round(v*100/TotalVocI,1)
print(k,v,freq,sep='\t')
print('\ntotal: %d' % TotalVocI)
elif option == '11':
FormToCount=input('Write 1 if you want to apply counting to perfective form, and 2 for imperfective\n')
FreqProsody = traditional_counting(FormToCount) # {(pat,n,f):freq, ...}
print('\n\nPattern'.ljust(11),'TotalWeight'.ljust(12),'SylStructure'.ljust(15),'freq')
DicKeys=sorted(set([i[0] for i in FreqProsody.keys()]),key=util_DataExtractor.cmp_to_key(util_DataExtractor.numeric_compare))
orden_previous='' ## we store the previous pattern to know when the pattern changes, so we can print a new line (for a clearer visualization)
for orden in DicKeys:
if orden!=orden_previous: print('') # prints a new line
orden_previous=orden
for k,v in FreqProsody.items():
pat,total,syl,freq=k[0],k[1],k[2],v
if pat==orden:
print(pat.ljust(12),str(total).ljust(12),syl.ljust(12),freq)
return
# ============ funciton call ============ #
quantitativeData()
# ======================================= #