__author__ = 'nparslow'
from compareCorrectedCorpus import getFinalTokenFormsAndTreesAndWeight
import calcPLex
print "loading freq info"
lemmacat2freqrank = calcPLex.loadLemmaCat2freqrank()
# testxmls = ["analysed_SpellChecker/entry_81/0/0/0/entry_81.E1.dep.xml"
testxmls = [
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E1.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E5.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E2.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E6.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E3.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E7.dep.xml",
"/home/nparslow/Documents/AutoCorrige/Corpora/analysed_SpellChecker/entry_350/0/0/0/entry_350.E4.dep.xml",
]
wordforms = []
for testxml in testxmls:
print "loading xml", testxml
tok2finalforms, tok2lemmacats, verb2info, trees, (weight, maxweight) = getFinalTokenFormsAndTreesAndWeight(testxml)
# each tok2lemmacat goes to a list to 2-tuples
# print tok2lemmacats.values()
for lemmacats in tok2lemmacats.values():
wordforms.extend([x[0] + u"_" + x[1] for x in lemmacats])
def main(argv):
# todo add a debug variable and optionfilename variable
optionsfilename = "settings/optionsfile.txt"
try:
opts, args = getopt.getopt(argv,"hi:", ["in_options_file="])
except getopt.GetoptError:
print 'textExtractor.py -i <input options file>'
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print 'textExtractor.py -i <input options file>'
sys.exit()
elif opt in ("-i", "--in_options_file"):
optionsfilename = arg
globalparams, variableparams = optionsFileReader.readOptionsFile(optionsfilename)
filenames = allCorpusFiles( globalparams["origtextdir"] )
print filenames
# todo for the moment we just take the first element for these
#meltDir = globalparams["melteddir"][0]
#ddagDir = globalparams["ddageddir"][0]
#frmgDir = globalparams["frmgeddir"][0]
filenameResources = {
"filename": None,
"melteddir" : globalparams["melteddir"][0],
"ddageddir" : globalparams["ddageddir"][0],
"frmgeddir" : globalparams["frmgeddir"][0],
}
print globalparams
outarffdir = globalparams["outdir"][0]
corpusName = globalparams["corpusName"][0]
headerInfo = globalparams["headerInfo"][0]
lexiquefile = globalparams["lexiqueDict"][0]
freq2ranksfile = globalparams["freq2ranks"][0]
gensimModelFile = globalparams["word2vecmodel"][0]
variableTypes = set([x[0] for x in variableparams])
lemmacat2freqrank = {}
if "PLex" in variableTypes or "S" in variableTypes or "altS" in variableTypes or "LFP" in variableTypes:
print "loading freq info"
lemmacat2freqrank = calcPLex.loadLemmaCat2freqrank(freq2ranksfile)
word2vecModel = None
if "w2vct" in variableTypes:
print "loading word2vec model"
word2vecModel = gensim.models.Word2Vec.load(gensimModelFile)
nGramDict, nmoGramDict, totalcounts = {}, {}, 1000000000000000
if "bigramLogProb" in variableTypes:
print "loading bi-gram model"
ngramModelFile = globalparams["bigrammodel"][0]
nGramDict, nmoGramDict, totalcounts = nGramModel.getNgramDicts(ngramModelFile)
lexiqueDict = {}
if "syllablesPerWord" in variableTypes:
loadLexiqueToDict(lexiquefile, lexiqueDict)
# create a list of variables for the arff file:
variables = [ ("filename", "string")] + \
[ (variableAndParamsToString(vname, params), "numeric") for vname,params in variableparams] + \
[ ("level", "numeric")] # note that level must go last!
for x in variables:
print x
#filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/C/Catja.txt"]
#filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/A/Arvid.txt"]
#filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/A/Amie4.txt"]
#filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/B/Bror2.txt"]
filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/C/Caroline.txt"]
filenames = ["/home/nparslow/Documents/AutoCorrige/Corpora/CORPUS_CEFLE/E/Eddy.txt"] # just to test an E
filenames = ["/home/pinot/alpage/nparslow/Documents/Corpora/CEFLE/E/Eddy.txt"] # just to test an E
resources = {
"lemmacat2freqrank": lemmacat2freqrank,
"word2vecModel": word2vecModel,
"nGramDict": nGramDict,
"nmoGramDict": nmoGramDict,
"nGramCounts": totalcounts,
"lexiqueDict": lexiqueDict
}
outputRows =[]
allobservedtrees = set([])
treespertext = []
for filename in filenames:
# we change the resouce filename with each round:
filenameResources["filename"] = filename
baseFileName = os.path.basename(filename)
baseFileName, extension = os.path.splitext(baseFileName)
filenameResources["ddagfile"] = os.path.join(filenameResources["ddageddir"],
os.path.basename(baseFileName) + ".ddag")
print
print filename
#fname = os.path.join(baseDir, filename)
#if "CEFLE" in baseDir:
# fname = os.path.join(baseDir, filename[0], filename)
#text = getDocumentProperties(frmgDir, meltDir, ddagDir, fname, word2vecModel,
# (nGramDict, nmoGramDict, totalcounts), debug=False)
#text = getDocumentProperties(filenameResources, variables, word2vecModel,
# (nGramDict, nmoGramDict, totalcounts), debug=False)
text = getDocumentProperties(filenameResources, variableparams, debug=False)
text.calcVariables( resources )
for i in range(len(variableparams)+1):
#variable, params = variableparams[i]
varlabel = variables[i]
# squeeze the filename in first:
value = filename
if i > 0:
value = text.variablevalues[i-1]
print varlabel, "\t", str(value)
print 'level', "\t", text.level
allobservedtrees.update(text.trees.keys())
treespertext.append( (set(text.trees.keys()), text.level) )
#print "mwpw", text.getMeanWeightPerWord()
outputRows.append( [baseFileName] + text.variablevalues + [text.level] )
savetoArff(outarffdir, corpusName, headerInfo, variables, outputRows )
savetoArff(outarffdir, corpusName + "class", headerInfo, variables, outputRows, levelAsClass=True )
arfftreefile = "testtrees"
#corpusName = "test"
#headerInfo = "a test corpus\n of stuff"
treevariables = list(allobservedtrees)
#print allobservedtrees
#print treespertext
treeoutputRows = [[1 if x in trees else 0 for x in treevariables] + [level] for trees, level in treespertext]
treevariables.append("level")
#print "ntrees", len(treevariables)
#for a,b in zip(treevariables, treeoutputRows):
# print a,len(b), b
savetoTreeArff(outarffdir, arfftreefile, headerInfo, treevariables, treeoutputRows, levelAsClass=True )
