def twosigma(data, window, w):
sp = data[:, 1]
time = data[:, 0]
sp = abs(sp)
index = []
for i in range(len(sp)):
if sp[i] == 50:
index.append(i)
time = np.delete(time, index)
sp = np.delete(sp, index)
speed = sp
for i in range(len(speed)):
if i > window or len(speed) - i > window:
mean = np.mean(speed[i - window:i + window])
elif i < window:
mean = np.mean(speed[0:i + window])
elif len(speed) - i < window:
mean = np.mean(speed[i - window:len(speed)])
if abs((speed[i] - mean) / mean) > 0.1:
speed[i] = mean
speed = signal.medfilt(speed, w)
return (time, speed)
def trace_filter(data, window, w):
sp = data[:, 1]
time = data[:, 0]
sp = abs(sp)
index = []
for i in range(len(sp)):
if sp[i] > 49 and sp[i] < 51 or sp[i] < 10:
index.append(i)
time = np.delete(time, index)
sp = np.delete(sp, index)
speed = sp
for i in range(len(speed)):
if i > window or len(speed) - i > window:
thresh = np.mean(speed[i - window:i + window])
elif i < window:
thresh = np.mean(speed[0:i + window])
elif len(speed) - i < window:
thresh = np.mean(speed[i - window:len(speed)])
if speed[i] < thresh:
speed[i] = thresh
speed = signal.medfilt(speed, w)
return (time, speed)
def medianfilter2(data, w):
sp = data[:, 1]
time = data[:, 0]
index = []
for i in range(len(sp)):
if sp[i] > -55 and sp[i] < 51:
index.append(i)
time = np.delete(time, index)
sp = np.delete(sp, index)
speed = sp
#speed=signal.medfilt(speed,w)
return (time, speed)
def median(data, w):
sp = data[:, 1]
time = data[:, 0]
sp = abs(sp)
index = []
for i in range(len(sp)):
if sp[i] > 49 and sp[i] < 51 or sp[i] < 10:
index.append(i)
time = np.delete(time, index)
sp = np.delete(sp, index)
speed = sp
speed = signal.medfilt(speed, w)
return (time, speed)