trim_end = end if (trim_end > end or trim_end is None) else trim_end
# interpolate some NaN values
compute.interpolate3(data, start, end)
if "_side" in ftxt:
data_s = data
elif "_top" in ftxt:
data_t = data
print "TRIM: ", trim_start, trim_end, trim_end-trim_start
data_s = data_s[trim_start:trim_end, :]
data_t = data_t[trim_start:trim_end, :]
# smooth the position data
data_s[:, 1] = compute.smooth(data_s[:, 1], win_size=WIN_SMOOTH_SIZE)
data_s[:, 2] = compute.smooth(data_s[:, 2], win_size=WIN_SMOOTH_SIZE)
# smooth the position data
data_t[:, 1] = compute.smooth(data_t[:, 1], win_size=WIN_SMOOTH_SIZE)
data_t[:, 2] = compute.smooth(data_t[:, 2], win_size=WIN_SMOOTH_SIZE)
# get the time variable to use in the future
T = data_s[:, 0]
# compute speed and acceleration
(veloc_s, accel_s) = compute.velocity(data_s, win_size=WIN_VELOCITY_SIZE)
(veloc_t, accel_t) = compute.velocity(data_t, win_size=WIN_VELOCITY_SIZE)
# dchanges = compute.dir_changesX2(data, win_size=100)
dchanges_s = compute.dir_changesX3(data_s, win_size=WIN_CHANGE_DIR_SIZE)
data = np.array(utils.read_txt(name_txt))
# round the data to clean um some noise
data = np.round(np.array(utils.read_txt(name_txt)), 2)
# trim the initial and final NaN values
data = compute.trim(data, 1)
data = compute.trim(data, 2)
# interpolate some NaN values
compute.interpolate(data, 1)
compute.interpolate(data, 2)
# smooth the position data
data_smooth = data
data_smooth[:, 1] = compute.smooth(data[:, 1], win_size=25)
data_smooth[:, 2] = compute.smooth(data[:, 2], win_size=25)
# get the time variable to use in the future
T = data[:, 0]
# compute speed and acceleration
(veloc, accel) = compute.velocity(data_smooth, win_size=125)
#dchanges = compute.dir_changesX2(data, win_size=100)
dchanges = compute.dir_changesX3(data, win_size=10)
#(fs, es) = compute.decide(data, veloc, accel, dchanges)
(fs, es) = compute.decide2(T, veloc, data[:, 2], accel, dchanges)
intervals = compute.interval_list(fs, es, data, 0)
