#!/usr/bin/env python
if __name__ == '__main__':
import M
import csv
import numpy as np
rows = list(csv.reader(open('../csv/train.csv')))
'''
x, e = M.getColumns(rows, (0, 3, (int, lambda x: 1 if x=='male' else 0)))
print(M.count(x))
'''
x, e = M.getColumns(rows, (0, 1, 3, 4), (int, float, lambda x: 1 if x=='male' else 0, float))
x = np.matrix(x)
y = x[0,:] #class
x = x[1:,:] #attributes
x0, x1 = M.split(x, y, lambda _y: _y==0)
'''
success, failure = M.crossValidation(x0, x1, M.Fisher)
print(success, failure)
'''
d = M.Gauss(x0, x1)
rows = list(csv.reader(open('../csv/test.csv')))[1:]
for row in rows:
try:
x = []
x.append(float(row[0]))
x.append(1 if row[2] == 'male' else 0)
x.append(float(row[3]))
print(d.do(np.matrix(x).T))
except ValueError:
