def postprocess(test_path):
submit_path = 'home/' + function.get_paths()['SUBMISSION_PATH']
os.chdir('post_processing')
cmd = 'sh ./post_processing.sh {0} home/features/Astar_test.f home/scores/final.score {1}'.format(
test_path, submit_path)
print cmd
os.system(cmd)
def predict(test_path):
model_path = 'home/' + function.get_paths()['MODEL_DIR_PATH']
os.chdir('train_and_predict')
train_dir = os.getcwd()
test_file = 'home/features/all_test.f'
os.chdir('Kmeans')
cmd = 'python train_predict.py home/features/Kmeans_train+valid.f home/features/Kmeans_test.f {0} home/scores/K.score'.format(
test_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('BinarySearch')
cmd = './predict.sh {0} {1} {2}BS.model home/scores/BS.score'.format(
test_file, test_path, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('Astar')
cmd = 'python predict.py {0} {1} {2}AS.model home/scores/AS.score'.format(
test_file, test_path, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
def main(): top_dir = os.getcwd() raw_dir = 'home/' + function.get_paths()['TRAIN_DATA_DIR_PATH'] aux_dir = 'home/auxiliary_data/' test_path = 'home/' + function.get_paths()['TEST_DATA_PATH'] function.generate_features(raw_dir, aux_dir+'dummyTrain.csv', test_path, '_null.f', '_test.f') os.chdir(top_dir) concate_features() os.chdir(top_dir) predict(test_path) os.chdir(top_dir) weighted_average() os.chdir(top_dir) postprocess(test_path) os.chdir(top_dir)
def main():
top_dir = os.getcwd()
raw_dir = 'home/' + function.get_paths()['TRAIN_DATA_DIR_PATH']
aux_dir = 'home/auxiliary_data/'
test_path = 'home/' + function.get_paths()['TEST_DATA_PATH']
function.generate_features(raw_dir, aux_dir + 'dummyTrain.csv', test_path,
'_null.f', '_test.f')
os.chdir(top_dir)
concate_features()
os.chdir(top_dir)
predict(test_path)
os.chdir(top_dir)
weighted_average()
os.chdir(top_dir)
postprocess(test_path)
os.chdir(top_dir)
def main():
top_dir = os.getcwd()
raw_dir = 'home/' + function.get_paths()['TRAIN_DATA_DIR_PATH']
cmd = 'python util/gen_Train+Valid.py {0}Train.csv {0}Valid.csv {0}ValidSolution.csv auxiliary_data/Train+Valid.csv'.format(
function.get_paths()['TRAIN_DATA_DIR_PATH'])
print cmd
os.system(cmd)
function.generate_features(raw_dir, raw_dir + 'Train.csv',
raw_dir + 'Valid.csv', '_train.f', '_valid.f')
os.chdir(top_dir)
concate_features()
os.chdir(top_dir)
set_list = ['all', 'Kmeans']
merge_train_and_valid(set_list, raw_dir)
os.chdir(top_dir)
train()
os.chdir(top_dir)
def train():
model_path = 'home/' + function.get_paths()['MODEL_DIR_PATH']
os.chdir('train_and_predict')
train_dir = os.getcwd()
train_file = 'home/features/all_train+valid.f'
ref_file = 'home/auxiliary_data/Train+Valid.csv'
os.chdir('BinarySearch')
cmd = './train.sh {0} {1} {2}BS.model'.format(train_file, ref_file, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('Astar')
cmd = 'python train.py {0} {1} {2}AS.model -m 1'.format(train_file, ref_file, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
def main():
top_dir = os.getcwd()
raw_dir = 'home/' + function.get_paths()['TRAIN_DATA_DIR_PATH']
cmd = 'python util/gen_Train+Valid.py {0}Train.csv {0}Valid.csv {0}ValidSolution.csv auxiliary_data/Train+Valid.csv'.format(function.get_paths()['TRAIN_DATA_DIR_PATH'])
print cmd
os.system(cmd)
function.generate_features(raw_dir, raw_dir+'Train.csv', raw_dir+'Valid.csv', '_train.f', '_valid.f')
os.chdir(top_dir)
concate_features()
os.chdir(top_dir)
set_list = ['all', 'Kmeans']
merge_train_and_valid(set_list, raw_dir)
os.chdir(top_dir)
train()
os.chdir(top_dir)
def train():
model_path = 'home/' + function.get_paths()['MODEL_DIR_PATH']
os.chdir('train_and_predict')
train_dir = os.getcwd()
train_file = 'home/features/all_train+valid.f'
ref_file = 'home/auxiliary_data/Train+Valid.csv'
os.chdir('BinarySearch')
cmd = './train.sh {0} {1} {2}BS.model'.format(train_file, ref_file,
model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('Astar')
cmd = 'python train.py {0} {1} {2}AS.model -m 1'.format(
train_file, ref_file, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
def predict(test_path):
model_path = 'home/' + function.get_paths()['MODEL_DIR_PATH']
os.chdir('train_and_predict')
train_dir = os.getcwd()
test_file = 'home/features/all_test.f'
os.chdir('Kmeans')
cmd = 'python train_predict.py home/features/Kmeans_train+valid.f home/features/Kmeans_test.f {0} home/scores/K.score'.format(test_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('BinarySearch')
cmd = './predict.sh {0} {1} {2}BS.model home/scores/BS.score'.format(test_file, test_path, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
os.chdir('Astar')
cmd = 'python predict.py {0} {1} {2}AS.model home/scores/AS.score'.format(test_file, test_path, model_path)
print cmd
os.system(cmd)
os.chdir(train_dir)
def postprocess(test_path):
submit_path = 'home/' + function.get_paths()['SUBMISSION_PATH']
os.chdir('post_processing')
cmd = 'sh ./post_processing.sh {0} home/features/Astar_test.f home/scores/final.score {1}'.format(test_path, submit_path)
print cmd
os.system(cmd)