from data import Data

from classifier import Classifier

from score import score

from time import time

from blackbox_preprocess import BlackboxPreprocess

from sklearn import preprocessing

def log(info):

f = file('submission.txt', 'w+')

f.write(str(info))

f.close()

def submission(preds):

log(out)

data, targets = Data.data()

print "training data: ", len(data)

test = Data.test()

print "test data: ", len(test)

data = data + test

print "all data: ", len(data)

# preprocessing

start = time()

matrix = BlackboxPreprocess.to_matrix(data)

print matrix.shape

matrix = BlackboxPreprocess.scale(matrix)

#matrix = BlackboxPreprocess.polynomial(matrix, 2)

matrix = preprocessing.normalize(matrix, norm='l2')

min_max_scaler = preprocessing.MinMaxScaler(feature_range=(-1.,1.))

matrix = min_max_scaler.fit_transform(matrix)

#matrix = BlackboxPreprocess.norm(matrix)

print matrix.shape

data = matrix.tolist()

# split training and test data

test_data = data[1000:]

data, targets = data[:1000], targets[:1000]

# testing

preds = Classifier.preds(data, targets, test_data, [])

print "Duration: ", time() - start

submission(preds)