def combine_votes(votes_files,
to_prediction,
to_file,
method=0,
prediction_info=NORMAL_FORMAT,
input_data_list=None,
exclude=None):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
u.check_dir(to_file)
with UnicodeWriter(to_file) as output:
number_of_tests = len(votes)
if input_data_list is None or len(input_data_list) != number_of_tests:
input_data_list = None
for index in range(0, number_of_tests):
multivote = votes[index]
input_data = (None if input_data_list is None else
input_data_list[index])
write_prediction(multivote.combine(method, True), output,
prediction_info, input_data, exclude)
def combine_votes(votes_files, to_prediction, to_file, method=0):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
check_dir(to_file)
with open(to_file, 'w', 0) as output:
for multivote in votes:
write_prediction(multivote.combine(method), output)
def combine_votes(votes_files, to_prediction, to_file, method=0,
prediction_info=None):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
check_dir(to_file)
output = csv.writer(open(to_file, 'w', 0),
lineterminator="\n")
for multivote in votes:
write_prediction(multivote.combine(method, True), output,
prediction_info)
def combine_votes(votes_files,
to_prediction,
to_file,
method=0,
prediction_info=None):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
check_dir(to_file)
output = csv.writer(open(to_file, 'w', 0), lineterminator="\n")
for multivote in votes:
write_prediction(multivote.combine(method, True), output,
prediction_info)
def combine_votes(votes_files, to_prediction, to_file, method=0,
prediction_info=None, input_data_list=None):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
u.check_dir(to_file)
output = csv.writer(open(to_file, 'w', 0),
lineterminator="\n")
number_of_tests = len(votes)
if input_data_list is None or len(input_data_list) != number_of_tests:
input_data_list = None
for index in range(0, number_of_tests):
multivote = votes[index]
input_data = (None if input_data_list is None
else input_data_list[index])
write_prediction(multivote.combine(method, True), output,
prediction_info, input_data)
def combine_votes(votes_files, to_prediction, to_file, method=0,
prediction_info=NORMAL_FORMAT, input_data_list=None,
exclude=None):
"""Combines the votes found in the votes' files and stores predictions.
votes_files: should contain the list of file names
to_prediction: is the Model method that casts prediction to numeric
type if needed
to_file: is the name of the final output file.
"""
votes = read_votes(votes_files, to_prediction)
u.check_dir(to_file)
with UnicodeWriter(to_file) as output:
number_of_tests = len(votes)
if input_data_list is None or len(input_data_list) != number_of_tests:
input_data_list = None
for index in range(0, number_of_tests):
multivote = votes[index]
input_data = (None if input_data_list is None
else input_data_list[index])
write_prediction(multivote.combine(method, full=True), output,
prediction_info, input_data, exclude)
