cases = list(set(map(lambda x: x[:3], case_raw.keys())))
numbers = list(set(map(lambda x: x[4:], case_raw.keys())))
else:
cases = case_raw.keys()
if vectors == 'Binary':
# Take log base 2 to figure out how many bits we need for each
human_size = int(ceil(log(len(human), 2))) # 2
dec_size = int(ceil(log(len(declensions), 2))) # 3
gen_size = int(ceil(log(len(genders), 2))) # 2
case_size = int(ceil(log(len(cases), 2))) # 3
if casenum_sep == True:
num_size = int(ceil(log(len(numbers), 2))) # 1
# Now make two way dictionary with bit vectors
human_dict = functions.binaryDict(human)
dec_dict = functions.binaryDict(declensions)
dec_dict.update(functions.invert(dec_dict))
gen_dict = functions.binaryDict(genders)
gen_dict.update(functions.invert(gen_dict))
case_dict = functions.binaryDict(cases)
case_dict.update(functions.invert(case_dict))
if casenum_sep == True:
num_dict = functions.binaryDict(numbers)
num_dict.update(functions.invert(num_dict))
# Identity vectors
else:
human_size = len(human)
dec_size = len(declensions)
gen_size = len(genders)
case_size = len(cases)
return results
########
# MAIN #
########
# Read in corpus
(corpus, suffixes) = objects.readCorpus(constants.corpus_file)
# Determine corpus size from this
corpus_size = len(corpus)
# Create suffix dictionary
if constants.vectors == 'binary':
suffix_size = int(ceil(log(len(suffixes), 2))) # 6
suffix_dict = functions.binaryDict(suffixes)
else:
suffix_size = len(suffixes)
suffix_dict = dict(zip(suffixes, map(tuple, identity(suffix_size))))
suf_to_tup = functions.invert(suffix_dict)
suffix_dict.update(functions.invert(suffix_dict))
##########
# OUTPUT #
##########
# Output layer will be list of potential suffixes, gathered from corpus
output_nodes = suffix_size
# Print information
cases = list(set(map(lambda x: x[:3], case_raw.keys())))
numbers = list(set(map(lambda x: x[4:], case_raw.keys())))
else:
cases = case_raw.keys()
if vectors == 'Binary':
# Take log base 2 to figure out how many bits we need for each
human_size = int(ceil(log(len(human), 2))) # 2
dec_size = int(ceil(log(len(declensions), 2))) # 3
gen_size = int(ceil(log(len(genders), 2))) # 2
case_size = int(ceil(log(len(cases), 2))) # 3
if casenum_sep == True:
num_size = int(ceil(log(len(numbers), 2))) # 1
# Now make two way dictionary with bit vectors
human_dict = functions.binaryDict(human)
dec_dict = functions.binaryDict(declensions)
dec_dict.update(functions.invert(dec_dict))
gen_dict = functions.binaryDict(genders)
gen_dict.update(functions.invert(gen_dict))
case_dict = functions.binaryDict(cases)
case_dict.update(functions.invert(case_dict))
if casenum_sep == True:
num_dict = functions.binaryDict(numbers)
num_dict.update(functions.invert(num_dict))
# Identity vectors
else:
human_size = len(human)
dec_size = len(declensions)
gen_size = len(genders)
case_size = len(cases)
return results
########
# MAIN #
########
# Read in corpus
(corpus, suffixes) = objects.readCorpus(constants.corpus_file)
# Determine corpus size from this
corpus_size = len(corpus)
# Create suffix dictionary
if constants.vectors == 'binary':
suffix_size = int(ceil(log(len(suffixes), 2))) # 6
suffix_dict = functions.binaryDict(suffixes)
else:
suffix_size = len(suffixes)
suffix_dict = dict(zip(suffixes, map(tuple, identity(suffix_size))))
suf_to_tup = functions.invert(suffix_dict)
suffix_dict.update(functions.invert(suffix_dict))
##########
# OUTPUT #
##########
# Output layer will be list of potential suffixes, gathered from corpus
output_nodes = suffix_size
# Print information
