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dataset2_dataf.py
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dataset2_dataf.py
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import os
import pandas as pd
import random
import numpy as np
import pickle
rng = random
pstri = './'
path = 'pickle_jar/'
assert (os.path.isfile(os.path.join(pstri + path, 'src_data.pickle')))
fs = open(pstri + "pickle_jar/src_data.pickle", "rb")
source_feat_mat, source_label_lis_num_arr = pickle.load(fs)
fs.close()
dum_arr = source_label_lis_num_arr.reshape((source_label_lis_num_arr.shape[0], 1))
clumped_arr = np.concatenate((source_feat_mat, dum_arr), axis=1)
numlis = np.arange(clumped_arr.shape[0])
ann = source_feat_mat.shape[0]
print(clumped_arr[:3])
rng.shuffle(numlis)
clumped_arr = clumped_arr[numlis]
clumped_source = clumped_arr[:]
assert (os.path.isfile(os.path.join(pstri + path, 'tar_data.pickle')))
fs = open(pstri + "pickle_jar/tar_data.pickle", "rb")
target_feat_mat, target_label_lis_num_arr = pickle.load(fs)
bann = target_feat_mat.shape[0]
fs.close()
dum_arr = target_label_lis_num_arr.reshape((target_label_lis_num_arr.shape[0], 1))
clumped_arr = np.concatenate((target_feat_mat, dum_arr), axis=1)
# print(dic)
numlis = np.arange(clumped_arr.shape[0])
rng.shuffle(numlis)
clumped_arr = clumped_arr[numlis]
# clumped_arr = clumped_arr[ numlis ]
clumped_target = clumped_arr[:]
# rng.shuffle(pimadata)
def give_source_data():
'''
returns two tuples each tuple has one array as feature set and other as column arrray of numerical labels
this one is for source
'''
aann = ann
# print(aann)
rest_setx = clumped_source[:aann, :-1] # tuple of two shared variable of array
rest_sety = clumped_source[:aann, -1:]
test_setx = clumped_source[aann:, :-1]
test_sety = clumped_source[aann:, -1:]
'''assert( rest_setx.shape == (150,128))
#print(rest_sety.shape)
assert( rest_sety.shape == (150,1))
assert( test_setx.shape == (50,640))
assert( test_sety.shape == (50,1))'''
return ((rest_setx, rest_sety), (test_setx, test_sety))
def give_target_data():
bbann = (bann * 3) // 4
rest_setx = clumped_target[:bbann, :-1]
rest_sety = clumped_target[:bbann, -1:]
test_setx = clumped_target[bbann:, :-1]
test_sety = clumped_target[bbann:, -1:]
# print(test_setx.shape)
# print(test_sety.shape)
'''assert( rest_setx.shape == (37,640))
assert( rest_sety.shape == (37,1))
assert( test_setx.shape == (13,640))
assert( test_sety.shape == (13,1))'''
return ((rest_setx, rest_sety), (test_setx, test_sety))
def give_source_data_just_src():
'''
returns two tuples each tuple has one array as feature set and other as column arrray of numerical labels
this one is for source
'''
aann = ann * 3 // 4
# print(aann)
rest_setx = clumped_source[:aann, :-1] # tuple of two shared variable of array
rest_sety = clumped_source[:aann, -1:]
test_setx = clumped_source[aann:, :-1]
test_sety = clumped_source[aann:, -1:]
'''assert( rest_setx.shape == (150,128))
#print(rest_sety.shape)
assert( rest_sety.shape == (150,1))
assert( test_setx.shape == (50,640))
assert( test_sety.shape == (50,1))'''
return ((rest_setx, rest_sety), (test_setx, test_sety))
def give_target_data_just_src_just_tar():
bbann = 0
rest_setx = clumped_target[:bbann, :-1]
rest_sety = clumped_target[:bbann, -1:]
test_setx = clumped_target[bbann:, :-1]
test_sety = clumped_target[bbann:, -1:]
# print(test_setx.shape)
# print(test_sety.shape)
'''assert( rest_setx.shape == (37,640))
assert( rest_sety.shape == (37,1))
assert( test_setx.shape == (13,640))
assert( test_sety.shape == (13,1))'''
return ((rest_setx, rest_sety), (test_setx, test_sety))
def main():
print(give_source_data()[0][0][:10])
print(give_target_data()[1][0][:10])
if __name__ == "__main__":
main()