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dataset_takedata.py
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dataset_takedata.py
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import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import sys, os, time
import argparse
from pathlib import Path
import shutil
import pickle as pk
import wfdb
import pywt
from collections import Counter
from PIL import Image
from PIL import ImageOps
import itertools
import threading
# parser = argparse.ArgumentParser()
# parser.add_argument('-n','--name', dest='name', required=True, help="session name")
# parser.add_argument('-o','--overwrite', dest='overwrite', action='store_true', help="overwrite the session if it already exists")
#
# args = parser.parse_args()
# session_name = args.name
# session_path = "output/peak_detector/"+session_name+"/"
# if os.path.isdir(session_path):
# if args.overwrite:
# try:
# shutil.rmtree(session_path)
# Path(session_path).mkdir(parents=True, exist_ok=True)
# except OSError:
# print("Error in session creation ("+session_path+").")
# exit()
# else:
# print("Session already exists ("+session_path+"), overwrite the session? (y/n): ", end='')
# force_write = input()
# if force_write == "y":
# print('')
# try:
# shutil.rmtree(session_path)
# Path(session_path).mkdir(parents=True, exist_ok=True)
# except OSError:
# print("Error in session creation ("+session_path+").")
# exit()
# else:
# exit()
# else:
# try:
# Path(session_path).mkdir(parents=True, exist_ok=True)
# except OSError:
# print("Error in session creation ("+session_path+").")
# exit()
def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
"""
Call in a loop to create terminal progress bar
@params:
iteration - Required : current iteration (Int)
total - Required : total iterations (Int)
prefix - Optional : prefix string (Str)
suffix - Optional : suffix string (Str)
decimals - Optional : positive number of decimals in percent complete (Int)
length - Optional : character length of bar (Int)
fill - Optional : bar fill character (Str)
printEnd - Optional : end character (e.g. "\r", "\r\n") (Str)
"""
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filledLength = int(length * iteration // total)
bar = fill * filledLength + '-' * (length - filledLength)
print(f'\r{prefix} |{bar}| {percent}% {suffix}', end = printEnd)
# Print New Line on Complete
if iteration == total:
print(f'\r{prefix} |{bar}| Done! {suffix}')
t_done = False
def animate(prefix = ''):
for c in itertools.cycle(['|', '/', '-', '\\']):
if t_done:
break
print('\r' + prefix + c, end = '\r')
# sys.stdout.write('\r' + prefix + c)
# sys.stdout.flush()
time.sleep(0.1)
print('\r' + prefix + 'Done!')
# sys.stdout.write('\r' + prefix + 'Done!')
# data_names = ['100', '101', '102', '103', '104', '105', '106', '107',
# '108', '109', '111', '112', '113', '114', '115', '116',
# '117', '118', '119', '121', '122', '123', '124', '200',
# '201', '202', '203', '205', '207', '208', '209', '210',
# '212', '213', '214', '215', '217', '219', '220', '221',
# '222', '223', '228', '230', '231', '232', '233', '234']
data_names = [ '100', '101', '103', '105', '106', '107',
'108', '109', '111', '112', '113', '114', '115', '116',
'117', '118', '119', '121', '122', '123', '124', '200',
'201', '202', '203', '205', '207', '208', '209', '210',
'212', '213', '214', '215', '217', '219', '220', '221',
'222', '223', '228', '230', '231', '232', '233', '234']
float2int_mul = 10000;
wid = 99
Y = []
F = []
P = []
Y_NLRAV = []
F_NLRAV = []
P_NLRAV = []
Y_NSVFQ = []
F_NSVFQ = []
P_NSVFQ = []
labels = ['N', 'L', 'R', 'e', 'j', 'A', 'a', 'J', 'S', 'V', 'E', 'F', '/', 'f', 'Q']
NLRAV_labels = ['N', 'L', 'R', 'A', 'V']
NSVFQ_labels = ['N', 'S', 'V', 'F', 'Q']
NSVFQ_sub_labels = {'N':'N', 'L':'N', 'R':'N', 'e':'N', 'j':'N',
'A':'S', 'a':'S', 'J':'S', 'S':'S',
'V':'V', 'E':'V',
'F':'F',
'/':'Q', 'f':'Q', 'Q':'Q'}
allstat_min = 0
allstat_max = 0
session_path = './output/dataset/raw_text/'
if os.path.isdir(session_path):
try:
shutil.rmtree(session_path)
Path(session_path).mkdir(parents=True, exist_ok=True)
except OSError:
print("Error in session creation ("+session_path+").")
exit()
else:
try:
Path(session_path).mkdir(parents=True, exist_ok=True)
except OSError:
print("Error in session creation ("+session_path+").")
exit()
# session_path_text = './output/dataset/raw_peaks/'
# if os.path.isdir(session_path):
# try:
# shutil.rmtree(session_path)
# Path(session_path).mkdir(parents=True, exist_ok=True)
# except OSError:
# print("Error in session creation ("+session_path+").")
# exit()
# else:
# try:
# Path(session_path).mkdir(parents=True, exist_ok=True)
# except OSError:
# print("Error in session creation ("+session_path+").")
# exit()
time.sleep(6)
f_allstat = open('./output/dataset/raw_text/all_stat.txt', "w")
printProgressBar(0, len(data_names), prefix = 'Files analyzed:', suffix = '', length = 60)
for d in data_names:
f_data = open('./output/dataset/raw_text/'+d+'_data.txt', "w")
f_intdata = open('./output/dataset/raw_text/'+d+'_intdata.txt', "w")
f_labels = open('./output/dataset/raw_text/'+d+'_label.txt', "w")
f_labelspos = open('./output/dataset/raw_text/'+d+'_labelpos.txt', "w")
f_labels_NLRAV = open('./output/dataset/raw_text/'+d+'_label_NLRAV.txt', "w")
f_labelspos_NLRAV = open('./output/dataset/raw_text/'+d+'_labelpos_NLRAV.txt', "w")
f_labels_NSVFQ = open('./output/dataset/raw_text/'+d+'_label_NSVFQ.txt', "w")
f_labelspos_NSVFQ = open('./output/dataset/raw_text/'+d+'_labelpos_NSVFQ.txt', "w")
f_stat = open('./output/dataset/raw_text/'+d+'_stat.txt', "w")
r = wfdb.rdrecord('./dataset/raw/'+d)
ann = wfdb.rdann('./dataset/raw/'+d, 'atr', return_label_elements=['label_store', 'symbol'])
# sig = np.array(r.p_signal[:,0])
# intsig = np.array(r.p_signal[:,0])
if d!='114':
sig = np.array(r.p_signal[:,0])
intsig = np.array(r.p_signal[:,0])
else:
sig = np.array(r.p_signal[:,1])
intsig = np.array(r.p_signal[:,1])
sig_len = len(sig)
sym = ann.symbol
pos = ann.sample
beat_len = len(sym)
stat_min = sig[0]
stat_max = sig[0]
for i in range(sig_len):
f_data.write(str(sig[i])+'\n')
intsig[i]=int(sig[i]*float2int_mul)
f_intdata.write(str(intsig[i])+'\n')
if sig[i] < stat_min:
stat_min = sig[i]
if sig[i] > stat_max:
stat_max = sig[i]
for i in range(beat_len):
if pos[i]-wid>=0 and pos[i]+wid<=sig_len and sym[i] in labels:
# if pos[i]-wid>=0 and pos[i]+wid<=sig_len:
f_labels.write(str(sym[i])+'\n')
f_labelspos.write(str(pos[i])+'\n')
# a = sig[pos[i]-wid:pos[i]+wid]
# if len(a) != 2*wid:
# print("Length error")
# continue
# Y.append(labels.index(sym[i]))
# F.append(data_names.index(d))
# P.append(pos[i])
if sym[i] in NLRAV_labels:
f_labels_NLRAV.write(str(sym[i])+'\n')
f_labelspos_NLRAV.write(str(pos[i])+'\n')
# Y_NLRAV.append(NLRAV_labels.index(sym[i]))
# F_NLRAV.append(data_names.index(d))
# P_NLRAV.append(pos[i])
f_labels_NSVFQ.write(str(NSVFQ_sub_labels[sym[i]])+'\n')
f_labelspos_NSVFQ.write(str(pos[i])+'\n')
# Y_NSVFQ.append(NSVFQ_labels.index(NSVFQ_sub_labels[sym[i]]))
# F_NSVFQ.append(data_names.index(d))
# P_NSVFQ.append(pos[i])
if d == data_names[0]:
allstat_min = stat_min
allstat_max = stat_max
else:
if stat_min < allstat_min:
allstat_min = stat_min
if stat_max > allstat_max:
allstat_max = stat_max
f_stat.write(str(stat_min)+'\n'+str(stat_max))
f_data.close()
f_intdata.close()
f_labels.close()
f_labelspos.close()
f_labels_NLRAV.close()
f_labelspos_NLRAV.close()
f_labels_NSVFQ.close()
f_labelspos_NSVFQ.close()
f_stat.close()
printProgressBar(data_names.index(d) + 1, len(data_names), prefix = 'Files analyzed:', suffix = '', length = 60)
f_allstat.write(str(allstat_min)+'\n'+str(allstat_max))
f_allstat.close()
# t_done = False
# t_dict = {'prefix' : 'Exporting dataset peaks: '}
# t = threading.Thread(target=animate, kwargs=t_dict)
# t.start()
#
# Y = np.array(Y)
# F = np.array(F)
# P = np.array(P)
#
# Y_NLRAV = np.array(Y_NLRAV)
# F_NLRAV = np.array(F_NLRAV)
# P_NLRAV = np.array(P_NLRAV)
#
# Y_NSVFQ = np.array(Y_NSVFQ)
# F_NSVFQ = np.array(F_NSVFQ)
# P_NSVFQ = np.array(P_NSVFQ)
#
#
#
# temp_path = './output/dataset/raw_peaks/ordered/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks/ordered/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y, output_file)
# with open("./output/dataset/raw_peaks/ordered/dataset_file.pickle", "wb") as output_file:
# pk.dump(F, output_file)
# with open("./output/dataset/raw_peaks/ordered/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P, output_file)
#
#
#
# temp_path = './output/dataset/raw_peaks/ordered_NLRAV/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks/ordered_NLRAV/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y_NLRAV, output_file)
# with open("./output/dataset/raw_peaks/ordered_NLRAV/dataset_file.pickle", "wb") as output_file:
# pk.dump(F_NLRAV, output_file)
# with open("./output/dataset/raw_peaks/ordered_NLRAV/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P_NLRAV, output_file)
#
#
#
# temp_path = './output/dataset/raw_peaks/ordered_NSVFQ/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks/ordered_NSVFQ/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y_NSVFQ, output_file)
# with open("./output/dataset/raw_peaks/ordered_NSVFQ/dataset_file.pickle", "wb") as output_file:
# pk.dump(F_NSVFQ, output_file)
# with open("./output/dataset/raw_peaks/ordered_NSVFQ/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P_NSVFQ, output_file)
#
#
#
# t_done = True
# time.sleep(0.1)
#
#
#
#
# X = []
# Y = []
# F = []
# P = []
#
# X_NLRAV = []
# Y_NLRAV = []
# F_NLRAV = []
# P_NLRAV = []
#
# X_NSVFQ = []
# Y_NSVFQ = []
# F_NSVFQ = []
# P_NSVFQ = []
#
# labels = ['N', 'L', 'R', 'e', 'j', 'A', 'a', 'J', 'S', 'V', 'E', 'F', '/', 'f', 'Q']
# NLRAV_labels = ['N', 'L', 'R', 'A', 'V']
# NSVFQ_labels = ['N', 'S', 'V', 'F', 'Q']
# NSVFQ_sub_labels = {'N':'N', 'L':'N', 'R':'N', 'e':'N', 'j':'N',
# 'A':'S', 'a':'S', 'J':'S', 'S':'S',
# 'V':'V', 'E':'V',
# 'F':'F',
# '/':'Q', 'f':'Q', 'Q':'Q'}
# X = []
# Y = []
# allstat_min = 0
# allstat_max = 0
#
# temp_path = './output/dataset/raw_text_aug/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# while os.path.exists(temp_path): # check if it exists
# pass
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# while not os.path.exists(temp_path): # check if it exists
# pass
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# time.sleep(6)
#
#
#
# f_allstat = open('./output/dataset/raw_text_aug/all_stat.txt', "w")
#
# printProgressBar(0, len(data_names), prefix = 'Files analyzed:', suffix = '', length = 60)
# for d in data_names:
# f_data = open('./output/dataset/raw_text_aug/'+d+'_data.txt', "w")
# f_intdata = open('./output/dataset/raw_text_aug/'+d+'_intdata.txt', "w")
# f_labels = open('./output/dataset/raw_text_aug/'+d+'_label.txt', "w")
# f_labelspos = open('./output/dataset/raw_text_aug/'+d+'_labelpos.txt', "w")
# f_labels_NLRAV = open('./output/dataset/raw_text_aug/'+d+'_label_NLRAV.txt', "w")
# f_labelspos_NLRAV = open('./output/dataset/raw_text_aug/'+d+'_labelpos_NLRAV.txt', "w")
# f_labels_NSVFQ = open('./output/dataset/raw_text_aug/'+d+'_label_NSVFQ.txt', "w")
# f_labelspos_NSVFQ = open('./output/dataset/raw_text_aug/'+d+'_labelpos_NSVFQ.txt', "w")
# f_stat = open('./output/dataset/raw_text_aug/'+d+'_stat.txt', "w")
# r = wfdb.rdrecord('./dataset/raw/'+d)
# ann = wfdb.rdann('./dataset/raw/'+d, 'atr', return_label_elements=['label_store', 'symbol'])
# sig = np.array(r.p_signal[:,0])
# intsig = np.array(r.p_signal[:,0])
# sig_len = len(sig)
# sym = ann.symbol
# pos = ann.sample
# beat_len = len(sym)
# stat_min = sig[0]
# stat_max = sig[0]
# for i in range(sig_len):
# f_data.write(str(sig[i])+'\n')
# intsig[i]=int(sig[i]*float2int_mul)
# f_intdata.write(str(intsig[i])+'\n')
# if sig[i] < stat_min:
# stat_min = sig[i]
# if sig[i] > stat_max:
# stat_max = sig[i]
# for i in range(beat_len):
# for j in range(-20,21,4):
# if pos[i]-wid+j>=0 and pos[i]+wid+j<=sig_len and sym[i] in labels:
# f_labels.write(str(sym[i])+'\n')
# f_labelspos.write(str(pos[i]+j)+'\n')
#
# a = sig[pos[i]-wid+j:pos[i]+wid+j]
# if len(a) != 2*wid:
# print("Length error")
# continue
# X.append(a)
# Y.append(labels.index(sym[i]))
# F.append(data_names.index(d))
# P.append(pos[i]+j)
#
# if sym[i] in NLRAV_labels:
# f_labels_NLRAV.write(str(sym[i])+'\n')
# f_labelspos_NLRAV.write(str(pos[i]+j)+'\n')
#
# X_NLRAV.append(a)
# Y_NLRAV.append(NLRAV_labels.index(sym[i]))
# F_NLRAV.append(data_names.index(d))
# P_NLRAV.append(pos[i]+j)
#
# f_labels_NSVFQ.write(str(NSVFQ_sub_labels[sym[i]])+'\n')
# # f_labels_NSVFQ.write(f'{NSVFQ_sub_labels[sym[i]]}\n')
# f_labelspos_NSVFQ.write(str(pos[i]+j)+'\n')
#
# X_NSVFQ.append(a)
# Y_NSVFQ.append(NSVFQ_labels.index(NSVFQ_sub_labels[sym[i]]))
# F_NSVFQ.append(data_names.index(d))
# P_NSVFQ.append(pos[i]+j)
# if d == data_names[0]:
# allstat_min = stat_min
# allstat_max = stat_max
# else:
# if stat_min < allstat_min:
# allstat_min = stat_min
# if stat_max > allstat_max:
# allstat_max = stat_max
#
# f_stat.write(str(stat_min)+'\n'+str(stat_max))
# f_data.close()
# f_intdata.close()
# f_labels.close()
# f_labelspos.close()
# f_labels_NLRAV.close()
# f_labelspos_NLRAV.close()
# f_labels_NSVFQ.close()
# f_labelspos_NSVFQ.close()
# f_stat.close()
# printProgressBar(data_names.index(d) + 1, len(data_names), prefix = 'Files analyzed:', suffix = '', length = 60)
#
# f_allstat.write(str(allstat_min)+'\n'+str(allstat_max))
# f_allstat.close()
#
#
#
# t_done = False
# t_dict = {'prefix' : 'Exporting dataset peaks: '}
# t = threading.Thread(target=animate, kwargs=t_dict)
# t.start()
#
# X = np.array(X)
# Y = np.array(Y)
# F = np.array(F)
# P = np.array(P)
#
# X_NLRAV = np.array(X_NLRAV)
# Y_NLRAV = np.array(Y_NLRAV)
# F_NLRAV = np.array(F_NLRAV)
# P_NLRAV = np.array(P_NLRAV)
#
# X_NSVFQ = np.array(X_NSVFQ)
# Y_NSVFQ = np.array(Y_NSVFQ)
# F_NSVFQ = np.array(F_NSVFQ)
# P_NSVFQ = np.array(P_NSVFQ)
#
# temp_path = './output/dataset/raw_peaks_aug/ordered/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks_aug/ordered/dataset_data.pickle", "wb") as output_file:
# pk.dump(X, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered/dataset_file.pickle", "wb") as output_file:
# pk.dump(F, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P, output_file)
#
#
#
# temp_path = './output/dataset/raw_peaks_aug/ordered_NLRAV/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks_aug/ordered_NLRAV/dataset_data.pickle", "wb") as output_file:
# pk.dump(X_NLRAV, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NLRAV/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y_NLRAV, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NLRAV/dataset_file.pickle", "wb") as output_file:
# pk.dump(F_NLRAV, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NLRAV/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P_NLRAV, output_file)
#
#
#
# temp_path = './output/dataset/raw_peaks_aug/ordered_NSVFQ/'
# if os.path.isdir(temp_path):
# shutil.rmtree(temp_path)
# Path(temp_path).mkdir(parents=True, exist_ok=True)
# else:
# Path(temp_path).mkdir(parents=True, exist_ok=True)
#
# with open("./output/dataset/raw_peaks_aug/ordered_NSVFQ/dataset_data.pickle", "wb") as output_file:
# pk.dump(X_NSVFQ, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NSVFQ/dataset_labels.pickle", "wb") as output_file:
# pk.dump(Y_NSVFQ, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NSVFQ/dataset_file.pickle", "wb") as output_file:
# pk.dump(F_NSVFQ, output_file)
# with open("./output/dataset/raw_peaks_aug/ordered_NSVFQ/dataset_position_in_file.pickle", "wb") as output_file:
# pk.dump(P_NSVFQ, output_file)
#
# t_done = True
# time.sleep(0.1)
#
# print('end')
# exit()