__author__ = 'Andrew'
import numpy as np
from random import random, randrange
from pylab import *
import matplotlib
import numpy as np
import Basic_IO_functions as io
#get the csv file and convert into an array
train_array = io.read_csv_into_array("train.csv")
#Create a 2d array of just survive and some other element
survive_array = np.array([train_array[:,0]])
gender_array = np.array([train_array[:,3]])
#concatenate the two arrays to be two columns with many rows
survive_gender_array = ([])
#survive_gender_array = [survive_array[0,2],gender_array[0,2]]
i = 0
ii = survive_array.size
while i < ii:
survive_gender_array.append((survive_array[0,i],gender_array[0,i]))
print i
#print 'printing survive gender array'
#print survive_gender_array
i = i+1
#print out that result in a table
while iiii < (rules_array.__len__()-1):
rules_array_list_a = rules_array[iiii]
rules_array_list_b = rules_array[iiii+1]
if rules_array_list_b[3] > rules_array_list_a[3]:
print "Switch took place "+iiii.__str__()
rules_array[iiii]= rules_array_list_b
rules_array[iiii+1] = rules_array_list_a
swapped = True
print swapped
iiii = iiii + 1
if swapped == True:
iiii = 0
print "rules_array"
print rules_array
return rules_array
#scripting lines for test purposes
train_array = io.read_csv_into_array("train.B.csv")
io.convert_into_csv(find_high_value_comparison_pairs(train_array), "prioritized rules")
#io.convert_into_csv(compare_all_columns_in_array(train_array, 0), "comparison values")
# print extract_comparison_values_from_array(train_array[:,1])#how do I do default values?
#sample_array= ([34,65,32,76,2])
#io.plot_histogram_of_comparison(sample_array)
#io.plot_histogram_of_comparison(compare_columns_in_array(train_array))
#print np.array(compare_columns_in_array(train_array, 0))
#print train_array[0]
#convert_into_csv(train_array, "test_csv_file")
