'Experiment10(VGG16): Train the model for diagnosing the heart disease by the ECG.'
)
parser.add_argument(
'-c',
'--config',
type=str,
default='./Config/config.ini',
metavar='str',
help="the path of configure file (default: './Config/config.ini')")
Args = parser.parse_args() # the Arguments
Args = read_config.read(Args) # read configure file
#%% Main Function
if __name__ == '__main__':
#%% ########## Read Data ##########
print('read data')
ECG_data, ECG_label = read_data.extract_data(
read_data.read_data(Args)) # read data
#%% ########## Data Processing ##########
ECG_data = data_process.cut_out(ECG_data,
Args.len) # cut out the ECG signals
ECG_data = data_process.axis_change(ECG_data) # change the axis
ECG_label = data_process.label_from_0(ECG_label) # label from 0
# split data
train_x, test_x, train_y, test_y = data_process.train_test_split(
ECG_data, ECG_label, trainratio=Args.trainratio, random_state=0)
# change to Tensor
train_x, train_y = data_process.to_tensor(train_x, train_y)
test_x, test_y = data_process.to_tensor(test_x, test_y)
#%% ########## Load Data ##########
# change to dataset
train_dataset = Data.TensorDataset(train_x, train_y)
test_dataset = Data.TensorDataset(test_x, test_y)
import read_data as rd
import tensorflow as tf
import numpy as np
BATCH_SIZE = 10
EPOC = 5
import os
dir_path = os.path.dirname(__file__) #<-- absolute dir the script is in
file_path = os.path.join(dir_path, "data.csv")
data_cols = rd.extract_data(file_path)
#place holder for x
X = tf.placeholder(tf.float32, [None, 2])
W = tf.Variable(tf.zeros([2, 1], tf.float32))
B = tf.Variable(tf.zeros([1], tf.float32))
Y_pred = tf.matmul(X, W)
train_x = []
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
for i in range(BATCH_SIZE):
# Retrieve a single instance:
features_result = sess.run(data_cols)
