def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
parser.add_argument('--infile', help="conllu file")
parser.add_argument('--lang', help="")
args = parser.parse_args()
#try:
header = ["proj_pred", "proj_gold", "leaf_viol_pred", "leaf_viol_gold", "posAcc", "UAS"]
if True:
vals = []
rdr = CoNLLReader()
predicted_sentences = []
gold_sentences = []
if args.infile:
gold_sentences = rdr.read_conll_u_8cols(args.infile)
numwords = sum([len(s.nodes()[1:]) for s in predicted_sentences])
#print([int(s.is_fully_projective()) for s in predicted_sentences])
for idx,s in enumerate(gold_sentences):
print(idx,s.is_fully_projective())
def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
parser.add_argument('input', help="conllu file")
parser.add_argument('output', help="target file", type=Path)
parser.add_argument('--replace_subtokens_with_fused_forms', help="By default removes fused tokens", default=False, action="store_true")
parser.add_argument('--remove_deprel_suffixes', help="Restrict deprels to the common universal subset, e.g. nmod:tmod becomes nmod", default=False, action="store_true")
parser.add_argument('--remove_node_properties', help="space-separated list of node properties to remove: form, lemma, cpostag, postag, feats", choices=['form', 'lemma', 'cpostag','postag','feats'], metavar='prop', type=str, nargs='+')
parser.add_argument('--lang', help="specify a language 2-letter code", default="default")
parser.add_argument('--output_format', choices=['conll2006', 'conll2009', 'conllu'], default="conll2006")
parser.add_argument('--remove_arabic_diacritics', help="remove Arabic short vowels", default=False, action="store_true")
parser.add_argument('--print_comments',default=False,action="store_true")
parser.add_argument('--print_fused_forms',default=False,action="store_true")
args = parser.parse_args()
if sys.version_info < (3,0):
print("Sorry, requires Python 3.x.") #suggestion: install anaconda python
sys.exit(1)
POSRANKPRECEDENCEDICT = defaultdict(list)
POSRANKPRECEDENCEDICT["default"] = "VERB NOUN PROPN PRON ADJ NUM ADV INTJ AUX ADP DET PART CCONJ SCONJ X PUNCT ".split(" ")
# POSRANKPRECEDENCEDICT["de"] = "PROPN ADP DET ".split(" ")
POSRANKPRECEDENCEDICT["es"] = "VERB AUX PRON ADP DET".split(" ")
POSRANKPRECEDENCEDICT["fr"] = "VERB AUX PRON NOUN ADJ ADV ADP DET PART SCONJ CONJ".split(" ")
POSRANKPRECEDENCEDICT["it"] = "VERB AUX ADV PRON ADP DET INTJ".split(" ")
if args.lang in POSRANKPRECEDENCEDICT:
current_pos_precedence_list = POSRANKPRECEDENCEDICT[args.lang]
else:
current_pos_precedence_list = POSRANKPRECEDENCEDICT["default"]
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(args.input)#, args.keep_fused_forms, args.lang, POSRANKPRECEDENCEDICT)
modif_treebank = copy.copy(orig_treebank)
# As per Dec 2015 the args.lang variable is redundant once you have current_pos_precedence_list
# We keep it for future modifications, i.e. any language-specific modules
for s in modif_treebank:
# print('sentence', s.get_sentence_as_string(printid=True))
s.filter_sentence_content(args.replace_subtokens_with_fused_forms, args.lang, current_pos_precedence_list,args.remove_node_properties,args.remove_deprel_suffixes,args.remove_arabic_diacritics)
cio.write_conll(modif_treebank,args.output, args.output_format,print_fused_forms=args.print_fused_forms, print_comments=args.print_comments)
def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
parser.add_argument('input', help="conllu file")
parser.add_argument('output', help="target file", type=Path)
parser.add_argument('--replace_subtokens_with_fused_forms', help="By default removes fused tokens", default=False, action="store_true")
parser.add_argument('--remove_deprel_suffixes', help="Restrict deprels to the common universal subset, e.g. nmod:tmod becomes nmod", default=False, action="store_true")
parser.add_argument('--remove_node_properties', help="space-separated list of node properties to remove: form, lemma, cpostag, postag, feats", choices=['form', 'lemma', 'cpostag','postag','feats'], metavar='prop', type=str, nargs='+')
parser.add_argument('--lang', help="specify a language 2-letter code", default="default")
parser.add_argument('--output_format', choices=['conll2006', 'conll2009', 'conllu'], default="conll2006")
parser.add_argument('--remove_arabic_diacritics', help="remove Arabic short vowels", default=False, action="store_true")
parser.add_argument('--print_comments',default=False,action="store_true")
parser.add_argument('--print_fused_forms',default=False,action="store_true")
args = parser.parse_args()
if sys.version_info < (3,0):
print("Sorry, requires Python 3.x.") #suggestion: install anaconda python
sys.exit(1)
POSRANKPRECEDENCEDICT = defaultdict(list)
POSRANKPRECEDENCEDICT["default"] = "VERB NOUN PROPN PRON ADJ NUM ADV INTJ AUX ADP DET PART CONJ SCONJ X PUNCT ".split(" ")
POSRANKPRECEDENCEDICT["de"] = "PROPN ADP DET ".split(" ")
POSRANKPRECEDENCEDICT["es"] = "VERB AUX PRON ADP DET".split(" ")
POSRANKPRECEDENCEDICT["fr"] = "VERB AUX PRON NOUN ADJ ADV ADP DET PART SCONJ CONJ".split(" ")
POSRANKPRECEDENCEDICT["it"] = "VERB AUX ADV PRON ADP DET".split(" ")
if args.lang in POSRANKPRECEDENCEDICT:
current_pos_precedence_list = POSRANKPRECEDENCEDICT[args.lang]
else:
current_pos_precedence_list = POSRANKPRECEDENCEDICT["default"]
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(args.input)#, args.keep_fused_forms, args.lang, POSRANKPRECEDENCEDICT)
modif_treebank = copy.copy(orig_treebank)
# As per Dec 2015 the args.lang variable is redundant once you have current_pos_precedence_list
# We keep it for future modifications, i.e. any language-specific modules
for s in modif_treebank:
s.filter_sentence_content(args.replace_subtokens_with_fused_forms, args.lang, current_pos_precedence_list,args.remove_node_properties,args.remove_deprel_suffixes,args.remove_arabic_diacritics)
cio.write_conll(modif_treebank,args.output, args.output_format,print_fused_forms=args.print_fused_forms, print_comments=args.print_comments)
def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
#parser.add_argument('--input', help="conllu file", default='../..//UD_Spanish-AnCora/es_ancora-all.conllu')
parser.add_argument('--input', help="conllu file", default='../..//UD_Catalan/ca-all.conllu')
parser.add_argument('--output', help="target file", type=Path,default="catout.conllu")
parser.add_argument('--lang', help="specify a language 2-letter code", default="default")
args = parser.parse_args()
if sys.version_info < (3,0):
print("Sorry, requires Python 3.x.") #suggestion: install anaconda python
sys.exit(1)
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(args.input)#, args.keep_fused_forms, args.lang, POSRANKPRECEDENCEDICT)
modif_treebank = []
for s in orig_treebank:
s = copy.copy(apply_transform(s,args.lang))
#if not 'multi_tokens' in s.graph.keys():
# print(s.get_sentence_as_string())
modif_treebank.append(s)
cio.write_conll(modif_treebank,args.output,conllformat='conllu', print_fused_forms=True,print_comments=True)
def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
parser.add_argument('--infile', help="conllu file", default="/Users/hmartine/proj/eval_multisource/data/2project/watchtower/en.2proj.conll.head1000")
args = parser.parse_args()
#try:
DEPCHILDCOUNTER=Counter()
GAPDEGREECOUNTER=Counter()
PROJCOUNTER=Counter()
header = ["proj_pred", "proj_gold", "leaf_viol_pred", "leaf_viol_gold", "posAcc", "UAS"]
vals = []
rdr = CoNLLReader()
predicted_sentences = []
gold_sentences = []
if args.infile:
gold_sentences = rdr.read_conll_2006_dense(args.infile)
numwords = sum([len(s.nodes()[1:]) for s in predicted_sentences])
#print([int(s.is_fully_projective()) for s in predicted_sentences])
for idx,s in enumerate(gold_sentences):
local_isproj = s.is_fully_projective()
localdependentcounter,gapdegreecounter = s.non_projectivity_edge_info()
PROJCOUNTER.update([local_isproj])
DEPCHILDCOUNTER+=localdependentcounter
GAPDEGREECOUNTER+=gapdegreecounter
projpercent=round(PROJCOUNTER[True]/sum(PROJCOUNTER.values()),2)
deppercent=[round(DEPCHILDCOUNTER[posname]/sum(DEPCHILDCOUNTER.values()),2) for posname in POSLIST]
edgelenths = [round(GAPDEGREECOUNTER[l]/sum(GAPDEGREECOUNTER.values()),2) for l in EDGELENGTHS]
otherlength = round(sum([GAPDEGREECOUNTER[l]/sum(GAPDEGREECOUNTER.values()) for l in GAPDEGREECOUNTER.keys() if l not in EDGELENGTHS]),2)
#print(Counter(PROJLIST),DEPCHILDCOUNTER.most_common(),GAPDEGREECOUNTER.most_common())
print("\t".join([str(x) for x in ["",projpercent]+deppercent+edgelenths+[otherlength]]))
def main():
parser = argparse.ArgumentParser(
description="""Convert conllu to conll format""")
#parser.add_argument('--input', help="conllu file", default='../..//UD_Spanish-AnCora/es_ancora-all.conllu')
parser.add_argument(
'--input',
help="conllu file",
default='../data/v2/UD_Spanish-Ancora/es_ancora-ud-train.conllu')
parser.add_argument('--output',
help="target file",
type=Path,
default="es_train_out.conllu")
parser.add_argument('--lang',
help="specify a language 2-letter code",
default="es")
args = parser.parse_args()
if sys.version_info < (3, 0):
print("Sorry, requires Python 3.x."
) #suggestion: install anaconda python
sys.exit(1)
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(
args.input
) #, args.keep_fused_forms, args.lang, POSRANKPRECEDENCEDICT)
modif_treebank = []
for s in orig_treebank:
s = copy.copy(apply_transform(s, args.lang))
#if not 'multi_tokens' in s.graph.keys():
# print(s.get_sentence_as_string())
modif_treebank.append(s)
cio.write_conll(modif_treebank,
args.output,
conllformat='conllu',
print_fused_forms=True,
print_comments=True)
def main():
parser = argparse.ArgumentParser(
description="""Extract data based on comments info""")
parser.add_argument('input', help="conllu file")
parser.add_argument('output', help="target file", type=Path)
parser.add_argument('--input-format',
choices=['conll2006', 'conll2006dense', 'conllu'],
default="conllu")
parser.add_argument('--mapping', help="mapping file", required=True)
args = parser.parse_args()
lines = [line.strip() for line in open(args.mapping)]
mapping = {}
for line in lines:
commentpart, target = line.split()
mapping[commentpart] = target
print("loaded mapping:", mapping, file=sys.stderr)
cio = CoNLLReader()
if args.input_format == "conllu":
orig_treebank = cio.read_conll_u(args.input)
elif args.input_format == "conll2006":
orig_treebank = cio.read_conll_2006(args.input)
elif args.input_format == "conll2006dense":
orig_treebank = cio.read_conll_2006_dense(args.input)
num_trees = len(orig_treebank)
print("Loaded treebank {} with {} sentences".format(args.input, num_trees),
file=sys.stderr)
split = {mapping[k]: [] for k in mapping.keys()}
default = "various"
split[default] = []
for tree in orig_treebank:
found_mapping = False
for token in " ".join(tree.graph['comment']).strip().split():
if token in mapping:
split[mapping[token]].append(tree)
found_mapping = True
continue
if not found_mapping:
split[default].append(tree)
for key in split:
print(key, len(split[key]), file=sys.stderr)
cio.write_conll(split[key], Path(args.output.name + "_" + key),
"conll2006")
def main():
parser = argparse.ArgumentParser(description="""Sample k trees from a dependency tree file (w/o replacement)""")
parser.add_argument('input', help="conllu file")
parser.add_argument('output', help="target file", type=Path)
parser.add_argument('--input-format', choices=['conll2006', 'conll2006dense', 'conllu'], default="conllu")
parser.add_argument('--k',default=None,help="randomly sample k instances from file", type=int, required=True)
parser.add_argument('--ignore-first-n',default=0,help="ignore first n sentences in the file", type=int, required=False)
parser.add_argument('--seed',default=None,help="seed to use")
parser.add_argument('--ignore-warning', help="if k > size, ignore warning and select all", default=False, action="store_true")
args = parser.parse_args()
cio = CoNLLReader()
if args.input_format == "conllu":
orig_treebank = cio.read_conll_u(args.input)
elif args.input_format == "conll2006":
orig_treebank = cio.read_conll_2006(args.input)
elif args.input_format == "conll2006dense":
orig_treebank = cio.read_conll_2006_dense(args.input)
num_trees = len(orig_treebank)
if args.seed:
random.seed(args.seed)
print("Loaded treebank {} with {} sentences".format(args.input,num_trees), file=sys.stderr)
if args.k > num_trees:
if args.ignore_warning:
print("ignore-warning={}".format(args.ignore_warning),file=sys.stderr)
else:
print("k cannot be larger than {} trees. abort. ".format(num_trees))
exit()
if args.ignore_first_n >= max(num_trees-args.k,num_trees):
print("--ignore-first-n cannot be larger than {} trees. abort. ".format(max(num_trees-args.k,num_trees)))
exit()
if args.ignore_first_n:
print("ignoring first {} trees in file".format(args.ignore_first_n), file=sys.stderr)
orig_treebank = orig_treebank[args.ignore_first_n+1:]
random.shuffle(orig_treebank)
sample = orig_treebank[0:args.k]
print("sampled {} trees. seed: {}".format(len(sample), args.seed))
cio.write_conll(sample, args.output, "conll2006")
def main():
parser = argparse.ArgumentParser(description="""Extract data based on comments info""")
parser.add_argument('input', help="conllu file")
parser.add_argument('output', help="target file", type=Path)
parser.add_argument('--input-format', choices=['conll2006', 'conll2006dense', 'conllu'], default="conllu")
parser.add_argument('--mapping', help="mapping file", required=True)
args = parser.parse_args()
lines=[line.strip() for line in open(args.mapping)]
mapping={}
for line in lines:
commentpart, target = line.split()
mapping[commentpart] = target
print("loaded mapping:", mapping, file=sys.stderr)
cio = CoNLLReader()
if args.input_format == "conllu":
orig_treebank = cio.read_conll_u(args.input)
elif args.input_format == "conll2006":
orig_treebank = cio.read_conll_2006(args.input)
elif args.input_format == "conll2006dense":
orig_treebank = cio.read_conll_2006_dense(args.input)
num_trees = len(orig_treebank)
print("Loaded treebank {} with {} sentences".format(args.input,num_trees), file=sys.stderr)
split = {mapping[k] : [] for k in mapping.keys()}
default = "various"
split[default] = []
for tree in orig_treebank:
found_mapping=False
for token in " ".join(tree.graph['comment']).strip().split():
if token in mapping:
split[mapping[token]].append(tree)
found_mapping=True
continue
if not found_mapping:
split[default].append(tree)
for key in split:
print(key, len(split[key]), file=sys.stderr)
cio.write_conll(split[key], Path(args.output.name + "_" + key), "conll2006")
def main():
parser = argparse.ArgumentParser(description="""Convert conllu to conll format""")
parser.add_argument("--input", help="conllu file", default="../data/en-ud-dev.conllu")
parser.add_argument("--lang")
parser.add_argument("--posrules", help="head POS rules file", default="../data/posrules.tsv")
parser.add_argument("--output", help="target file", default="testout.conllu")
parser.add_argument("--parsing_strategy", choices=["rules", "pagerank", "adjacent"], default="pagerank")
parser.add_argument(
"--steps",
choices=["twotags", "complete", "neighbors", "verbs", "function", "content", "headrule"],
nargs="+",
default=[""],
)
parser.add_argument("--reverse", action="store_true", default=True)
parser.add_argument("--rule_backoff", choices=["cycle", "left", "right"], default="left")
parser.add_argument("--ablation", choices=["pagerank", "2stepdecoding"], default="pagerank")
args = parser.parse_args()
if sys.version_info < (3, 0):
print("Sorry, requires Python 3.x.") # suggestion: install anaconda python
sys.exit(1)
headrules = pd.read_csv(args.posrules, "\t")
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(args.input)
ref_treebank = cio.read_conll_u(args.input)
modif_treebank = []
posbigramcounter, wordcounter = count_pos_bigrams(orig_treebank)
functionlist = [x for x, y in wordcounter.most_common(100)]
print(functionlist)
fill_out_left_and_right_attach(posbigramcounter)
if args.parsing_strategy == "pagerank":
for o, ref in zip(orig_treebank, ref_treebank):
s = copy.copy(o)
s.remove_edges_from(s.edges())
s.remove_node(
0
) # From here and until tree reconstruction there is no symbolic root node, makes our life a bit easier
if "twotags" in args.steps:
s = map_to_two_tags(s, functionlist)
if "complete" in args.steps:
s = add_all_edges(s)
if "neighbors" in args.steps:
s = add_short_edges(s)
if "verbs" in args.steps:
s = add_verb_edges(s)
if "function" in args.steps:
s = manage_function_words(s)
if "content" in args.steps:
s = relate_content_words(s)
if "headrule" in args.steps:
s = add_head_rule_edges(s, headrules)
tree_decoding_algorithm_content_and_function(s, headrules, args.reverse, args.ablation)
modif_treebank.append(s)
if args.reverse:
r = ".rev"
else:
r = ".norev"
outfile = Path(args.lang + "_" + args.output + "_" + "_".join(args.steps) + r + ".conllu")
cio.write_conll(
modif_treebank, outfile, conllformat="conllu", print_fused_forms=False, print_comments=False
)
outfile = Path(args.lang + "_" + args.output)
cio.write_conll(
modif_treebank, outfile, conllformat="conllu", print_fused_forms=False, print_comments=False
)
elif args.parsing_strategy == "adjacent":
for s in orig_treebank:
s.remove_edges_from(s.edges())
s = attach_adjacent(s, args.rule_backoff)
modif_treebank.append(s)
outfile = Path(args.output + "." + args.rule_backoff)
cio.write_conll(modif_treebank, outfile, conllformat="conllu", print_fused_forms=False, print_comments=False)
else:
for s in orig_treebank:
s = add_high_confidence_edges(s, posbigramcounter, args.rule_backoff)
modif_treebank.append(s)
for k in sorted(scorerdict.keys()):
prec = sum([p for p, r in scorerdict[k]]) / len(scorerdict[k])
reca = sum([r for p, r in scorerdict[k]]) / len(scorerdict[k])
print("{0}, {1:.2f}, {2:.2f}".format(k, prec, reca))
outfile = Path(args.output + ".rules")
cio.write_conll(modif_treebank, outfile, conllformat="conllu", print_fused_forms=False, print_comments=False)
from lib.conll import CoNLLReader
from collections import Counter
def getPosDist(sents):
C = Counter()
for s in sents:
for n in s.nodes()[1:]:
C[s.node[n]["cpostag"]] += 1
total = sum(C.values())
for k in C.keys():
C[k] /= total
return C
rdr = CoNLLReader()
Acc = Counter()
langs = "ar bg cs da de en es eu fa fi fr he hi hr id it nl pl pt sl sv".split(
)
langs = langs[:3]
for lang in langs:
filepattern = "/Users/hector/data/parse-holy-data/parse/goldpos/" + lang + "-ud-train.conllu.delex"
current_sentences = rdr.read_conll_u(filepattern)
posdist = getPosDist(current_sentences)
Acc = Acc + posdist
total = len(langs)
for k in Acc.keys():
Acc[k] /= total
print(Acc)
def main():
parser = argparse.ArgumentParser(
description="""Convert conllu to conll format""")
parser.add_argument('--input',
help="conllu file",
default='../data/en-ud-dev.conllu')
parser.add_argument('--lang')
parser.add_argument('--posrules',
help="head POS rules file",
default='../data/posrules.tsv')
parser.add_argument('--output',
help="target file",
default="testout.conllu")
parser.add_argument('--parsing_strategy',
choices=['rules', 'pagerank', 'adjacent'],
default='pagerank')
parser.add_argument('--steps',
choices=[
'twotags', 'complete', 'neighbors', 'verbs',
'function', 'content', 'headrule'
],
nargs='+',
default=[""])
parser.add_argument('--reverse', action='store_true', default=True)
parser.add_argument('--rule_backoff',
choices=['cycle', 'left', 'right'],
default="left")
parser.add_argument('--ablation',
choices=['pagerank', '2stepdecoding'],
default="pagerank")
args = parser.parse_args()
if sys.version_info < (3, 0):
print("Sorry, requires Python 3.x."
) #suggestion: install anaconda python
sys.exit(1)
headrules = pd.read_csv(args.posrules, '\t')
cio = CoNLLReader()
orig_treebank = cio.read_conll_u(args.input)
ref_treebank = cio.read_conll_u(args.input)
modif_treebank = []
posbigramcounter, wordcounter = count_pos_bigrams(orig_treebank)
functionlist = [x for x, y in wordcounter.most_common(100)]
print(functionlist)
fill_out_left_and_right_attach(posbigramcounter)
if args.parsing_strategy == 'pagerank':
for o, ref in zip(orig_treebank, ref_treebank):
s = copy.copy(o)
s.remove_edges_from(s.edges())
s.remove_node(
0
) # From here and until tree reconstruction there is no symbolic root node, makes our life a bit easier
if "twotags" in args.steps:
s = map_to_two_tags(s, functionlist)
if "complete" in args.steps:
s = add_all_edges(s)
if "neighbors" in args.steps:
s = add_short_edges(s)
if "verbs" in args.steps:
s = add_verb_edges(s)
if "function" in args.steps:
s = manage_function_words(s)
if "content" in args.steps:
s = relate_content_words(s)
if "headrule" in args.steps:
s = add_head_rule_edges(s, headrules)
tree_decoding_algorithm_content_and_function(
s, headrules, args.reverse, args.ablation)
modif_treebank.append(s)
if args.reverse:
r = ".rev"
else:
r = ".norev"
outfile = Path(args.lang + "_" + args.output + "_" +
"_".join(args.steps) + r + ".conllu")
cio.write_conll(modif_treebank,
outfile,
conllformat='conllu',
print_fused_forms=False,
print_comments=False)
outfile = Path(args.lang + "_" + args.output)
cio.write_conll(modif_treebank,
outfile,
conllformat='conllu',
print_fused_forms=False,
print_comments=False)
elif args.parsing_strategy == 'adjacent':
for s in orig_treebank:
s.remove_edges_from(s.edges())
s = attach_adjacent(s, args.rule_backoff)
modif_treebank.append(s)
outfile = Path(args.output + "." + args.rule_backoff)
cio.write_conll(modif_treebank,
outfile,
conllformat='conllu',
print_fused_forms=False,
print_comments=False)
else:
for s in orig_treebank:
s = add_high_confidence_edges(s, posbigramcounter,
args.rule_backoff)
modif_treebank.append(s)
for k in sorted(scorerdict.keys()):
prec = sum([p for p, r in scorerdict[k]]) / len(scorerdict[k])
reca = sum([r for p, r in scorerdict[k]]) / len(scorerdict[k])
print('{0}, {1:.2f}, {2:.2f}'.format(k, prec, reca))
outfile = Path(args.output + ".rules")
cio.write_conll(modif_treebank,
outfile,
conllformat='conllu',
print_fused_forms=False,
print_comments=False)
def main():
parser = argparse.ArgumentParser(
description="""Convert conllu to conll format""")
parser.add_argument('--predicted', help="conllu file")
parser.add_argument('--gold', help="conllu file")
parser.add_argument('--lang', help="")
args = parser.parse_args()
#try:
header = [
"proj_pred", "proj_gold", "leaf_viol_pred", "leaf_viol_gold", "posAcc",
"UAS"
]
if True:
vals = []
rdr = CoNLLReader()
predicted_sentences = []
gold_sentences = []
if args.predicted:
predicted_sentences = rdr.read_conll_u_8cols(args.predicted)
if args.gold:
gold_sentences = rdr.read_conll_u(args.gold)
numwords = sum([len(s.nodes()[1:]) for s in predicted_sentences])
#print([int(s.is_fully_projective()) for s in predicted_sentences])
proj_pred = sum(
[int(s.is_fully_projective()) for s in predicted_sentences])
proj_gold = sum([int(s.is_fully_projective()) for s in gold_sentences])
punct_non__proj_pred = sum(
[int(s.punct_proj_violations()) for s in predicted_sentences])
punct_non__proj_gold = sum(
[int(s.punct_proj_violations()) for s in gold_sentences])
leaf_violations_pred = sum(
[s.leaf_violations()[0] for s in predicted_sentences])
leaf_violations_gold = sum(
[s.leaf_violations()[0] for s in gold_sentences])
wrongPOSgoodHeadscore = wrongPOSgoodHead(predicted_sentences,
gold_sentences)
posAcc_accum = sum([
POSAcc(p, g) for p, g in zip(predicted_sentences, gold_sentences)
]) / numwords
UAS_accum = sum(
[UAS(p, g)
for p, g in zip(predicted_sentences, gold_sentences)]) / numwords
prelength = edgelengths(predicted_sentences)
goldlength = edgelengths(gold_sentences)
avgprelength = np.std(prelength)
avggoldlength = np.std(goldlength)
vals.append(wrongPOSgoodHeadscore)
vals.append(avgprelength)
vals.append(avggoldlength)
vals.append(proj_pred / len(predicted_sentences))
vals.append(proj_pred / len(predicted_sentences))
vals.append(proj_gold / len(gold_sentences))
vals.append(punct_non__proj_pred / numwords)
vals.append(punct_non__proj_gold / numwords)
vals.append(leaf_violations_pred / numwords)
vals.append(leaf_violations_gold / numwords)
vals.append(KLdivFromMACRO_POS_from_Training(predicted_sentences))
vals.append(KLdivFromMACRO_POS_from_Training(gold_sentences))
vals.append(posAcc_accum)
vals.append(UAS_accum)
lineout = " ".join([args.lang] + ["{0:.2f}".format(x) for x in vals])
#except:
# lineout = "_\t_"
print(lineout)
parser.add_argument('--input', help="conllu file", default='../data/UD_Spanish-AnCora_frozen/es_ancora-ud-')
args = parser.parse_args()
underscore_counter = Counter()
treebank = []
wordcounter=defaultdict(dict)
for ext in "dev.conllu test.conllu train.conllu".split():
infile = args.input+ext
cio = CoNLLReader()
treebank = treebank + cio.read_conll_u(infile)#, args.keep_fused_forms, args.lang, POSRANKPRECEDENCEDICT)
for s in treebank:
for n in s.nodes()[1:]:
lemma = s.node[n]['lemma']
form = s.node[n]['form']
cpostag = s.node[n]['cpostag']
feats = s.node[n]['feats']
if len(lemma) > 2 and "_" in lemma:
if cpostag == "DET":
action = 'shared'
else:
action = 'leftmost'