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extract_all.py
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import csv,sys
import queue
from statistics import mean, median, variance, stdev
from scipy.stats import skew, kurtosis
from functools import reduce
from math import sqrt,floor,ceil
import numpy as np
def rms(xs):
return sqrt(reduce(lambda a, x: a + x * x, xs, 0) / len(xs))
def en(xs):
return reduce(lambda a, x: a + x * x, xs, 0) / len(xs)
idx = 0
posedge_term = 0
threshold = 2.97
can_dom_bit_idx = 0 # 0 to 2000
can_res_bit_idx = 0 # 0 to 2000
can_signal = []
SOF = False
POSEDGE = False
posedge_q = queue.Queue()
dominant_list = []
prev_can_signal_len = -1
sampling_rate = int(sys.argv[2])
skip_duration = floor(float(1/sampling_rate)*1000/2)
queue_length = ceil(sampling_rate/2.0)+1
buffering_term = floor((sampling_rate/2.0+1)/2)
dominant_buffering_term = 0 if sampling_rate==1 else ceil((sampling_rate/2.0+1)*1.5)
with open(sys.argv[1]) as f:
while True:
idx += 1
row = f.readline()
if idx == 1 or idx == 2 or idx == 3:
continue
#print(row, end='')
try :
v_value = float(row.split(',')[1])
except IndexError:
break
# estimate can bit signal
if v_value >= threshold :
#print(v_value)
SOF = True
can_dom_bit_idx += 2
elif SOF == True and v_value < threshold :
can_res_bit_idx += 2
if can_dom_bit_idx == 1000:
can_signal.append('0')
elif can_res_bit_idx == 1000:
can_signal.append('1')
elif can_res_bit_idx >= 2000:
can_res_bit_idx = 0
elif can_dom_bit_idx >= 2000:
can_dom_bit_idx = 0
if idx % skip_duration != 0:
continue
posedge_q.put(v_value)
if posedge_q.qsize() > queue_length:
posedge_q.get()
# extract posedge edge
try :
if posedge_q.queue[-1] - posedge_q.queue[0] >= 0.5 and prev_can_signal_len != len(can_signal) :
POSEDGE = True
#print(len(can_signal), posedge_q.queue[0], posedge_q.queue[-1])
prev_can_signal_len = len(can_signal)
if POSEDGE == True:
posedge_term += 1
if posedge_term >= dominant_buffering_term and POSEDGE == True:
if sampling_rate==1:
dominant_list.append(posedge_q.queue[-1])
#print("Dominant signals: ", q_item, len(can_signal))
else:
for q_item in posedge_q.queue:
dominant_list.append(q_item)
#print("Dominant signals: ", q_item, len(can_signal))
POSEDGE = False
posedge_term = 0
posedge_q.empty()
#print("=================================")
except IndexError :
continue
# label
#print('mean,stdev,variance,skew,kurtosis,max,min,rms,en,mean_fft,stdev_fft,variance_fft,skew_fft,kurtosis_fft,max_fft,min_fft,rms_fft,en_fft')
# feature extraction
fft_dominant_list = abs(np.fft.fft(dominant_list))
idx = 0
posedge_term = 0
threshold = 2.97
can_dom_bit_idx = 0 # 0 to 2000
can_res_bit_idx = 0 # 0 to 2000
can_signal = []
SOF = False
POSEDGE = False
posedge_q = queue.Queue()
posedge_list = []
prev_can_signal_len = -1
with open(sys.argv[1]) as f:
while True:
idx += 1
row = f.readline()
if idx == 1 or idx == 2 or idx == 3:
continue
#print(row, end='')
try :
v_value = float(row.split(',')[1])
except IndexError:
break
# estimate can bit signal
if v_value >= threshold :
#print(v_value)
SOF = True
can_dom_bit_idx += 2
elif SOF == True and v_value < threshold :
can_res_bit_idx += 2
if can_dom_bit_idx == 1000:
can_signal.append('0')
elif can_res_bit_idx == 1000:
can_signal.append('1')
elif can_res_bit_idx >= 2000:
can_res_bit_idx = 0
elif can_dom_bit_idx >= 2000:
can_dom_bit_idx = 0
if idx % skip_duration != 0:
continue
posedge_q.put(v_value)
if posedge_q.qsize() > queue_length:
posedge_q.get()
# extract posedge edge
try :
if posedge_q.queue[-1] - posedge_q.queue[0] >= 0.5 and prev_can_signal_len != len(can_signal) :
POSEDGE = True
#print(len(can_signal), posedge_q.queue[0], posedge_q.queue[-1])
prev_can_signal_len = len(can_signal)
if POSEDGE == True:
posedge_term += 1
if posedge_term >= buffering_term and POSEDGE == True:
for q_item in posedge_q.queue:
posedge_list.append(q_item)
#print("Posedge Edge: ", q_item, len(can_signal))
POSEDGE = False
posedge_term = 0
posedge_q.empty()
#print("=================================")
except IndexError :
continue
# feature extraction
fft_posedge_list = abs(np.fft.fft(posedge_list))
idx = 0
negedge_term = 0
threshold = 2.97
can_dom_bit_idx = 0 # 0 to 2000
can_res_bit_idx = 0 # 0 to 2000
can_signal = []
SOF = False
NEGEDGE = False
negedge_q = queue.Queue()
negedge_list = []
prev_can_signal_len = -1
with open(sys.argv[1]) as f:
while True:
idx += 1
row = f.readline()
if idx == 1 or idx == 2 or idx == 3:
continue
#print(row, end='')
try :
v_value = float(row.split(',')[1])
except IndexError:
break
# estimate can bit signal
if v_value >= threshold :
#print(v_value)
SOF = True
can_dom_bit_idx += 2
elif SOF == True and v_value < threshold :
can_res_bit_idx += 2
if can_dom_bit_idx == 1000:
can_signal.append('0')
elif can_res_bit_idx == 1000:
can_signal.append('1')
elif can_res_bit_idx >= 2000:
can_res_bit_idx = 0
elif can_dom_bit_idx >= 2000:
can_dom_bit_idx = 0
if idx % skip_duration != 0:
continue
negedge_q.put(v_value)
if negedge_q.qsize() > queue_length:
negedge_q.get()
# extract negedge edge
try :
if negedge_q.queue[0] - negedge_q.queue[-1] >= 0.5 and prev_can_signal_len != len(can_signal) :
NEGEDGE = True
#print(len(can_signal), negedge_q.queue[0], negedge_q.queue[-1])
prev_can_signal_len = len(can_signal)
if NEGEDGE == True:
negedge_term += 1
if negedge_term >= buffering_term and NEGEDGE == True:
for q_item in negedge_q.queue:
negedge_list.append(q_item)
#print("Negedge Edge: ", q_item, len(can_signal))
NEGEDGE = False
negedge_term = 0
negedge_q.empty()
#print("=================================")
except IndexError :
continue
# feature extraction
fft_negedge_list = abs(np.fft.fft(negedge_list))
print('{:.4f}'.format(mean(dominant_list)),\
'{:.4f}'.format(stdev(dominant_list)),\
'{:.4f}'.format(variance(dominant_list)),\
'{:.4f}'.format(skew(dominant_list)),\
'{:.4f}'.format(kurtosis(dominant_list)),\
'{:.4f}'.format(max(dominant_list)),\
'{:.4f}'.format(min(dominant_list)),\
'{:.4f}'.format(rms(dominant_list)),\
'{:.4f}'.format(en(dominant_list)),\
'{:.4f}'.format(mean(fft_dominant_list)),\
'{:.4f}'.format(stdev(fft_dominant_list)),\
'{:.4f}'.format(variance(fft_dominant_list)),\
'{:.4f}'.format(skew(fft_dominant_list)),\
'{:.4f}'.format(kurtosis(fft_dominant_list)),\
'{:.4f}'.format(max(fft_dominant_list)),\
'{:.4f}'.format(min(fft_dominant_list)),\
'{:.4f}'.format(rms(fft_dominant_list)),\
'{:.4f}'.format(en(fft_dominant_list)),\
'{:.4f}'.format(mean(negedge_list)),\
'{:.4f}'.format(stdev(negedge_list)),\
'{:.4f}'.format(variance(negedge_list)),\
'{:.4f}'.format(skew(negedge_list)),\
'{:.4f}'.format(kurtosis(negedge_list)),\
'{:.4f}'.format(max(negedge_list)),\
'{:.4f}'.format(min(negedge_list)),\
'{:.4f}'.format(rms(negedge_list)),\
'{:.4f}'.format(en(negedge_list)),\
'{:.4f}'.format(mean(fft_negedge_list)),\
'{:.4f}'.format(stdev(fft_negedge_list)),\
'{:.4f}'.format(variance(fft_negedge_list)),\
'{:.4f}'.format(skew(fft_negedge_list)),\
'{:.4f}'.format(kurtosis(fft_negedge_list)),\
'{:.4f}'.format(max(fft_negedge_list)),\
'{:.4f}'.format(min(fft_negedge_list)),\
'{:.4f}'.format(rms(fft_negedge_list)),\
'{:.4f}'.format(en(fft_negedge_list)),\
'{:.4f}'.format(mean(posedge_list)),\
'{:.4f}'.format(stdev(posedge_list)),\
'{:.4f}'.format(variance(posedge_list)),\
'{:.4f}'.format(skew(posedge_list)),\
'{:.4f}'.format(kurtosis(posedge_list)),\
'{:.4f}'.format(max(posedge_list)),\
'{:.4f}'.format(min(posedge_list)),\
'{:.4f}'.format(rms(posedge_list)),\
'{:.4f}'.format(en(posedge_list)),\
'{:.4f}'.format(mean(fft_posedge_list)),\
'{:.4f}'.format(stdev(fft_posedge_list)),\
'{:.4f}'.format(variance(fft_posedge_list)),\
'{:.4f}'.format(skew(fft_posedge_list)),\
'{:.4f}'.format(kurtosis(fft_posedge_list)),\
'{:.4f}'.format(max(fft_posedge_list)),\
'{:.4f}'.format(min(fft_posedge_list)),\
'{:.4f}'.format(rms(fft_posedge_list)),\
'{:.4f}'.format(en(fft_posedge_list)),\
sys.argv[3],sep=','
)