def est_smooth_ideal(moves, ts, stype='sparc'):
"""Estimates the smoothness of the ideal movements.
"""
sys.stdout.write('.')
if stype == 'sparc':
return np.array(
[sparc(_m, fs=1/ts, padlevel=4, fc=10., amp_th=0.05)[0]
for _m in moves])
else:
return np.array([ldlj(_m, fs=1/ts) for _m in moves])
def estimate_smoothness(moves, ts, param, stype="sparc"):
"""Estimates the smoothness of the movements of two different scales.
"""
if stype == 'sparc':
return np.array([[
sparc(moves[i, j], fs=1 / ts, padlevel=4, fc=10., amp_th=0.05)[0]
for j in xrange(param['N_m'])
] for i in xrange(len(param['scales']))])
else:
return np.array([[ldlj(moves[i, j], ts) for j in xrange(param['N_m'])]
for i in xrange(len(param['scales']))])
def est_smooth_ideal(moves, ts, stype='sparc'):
"""Estimates the smoothness of the ideal movements.
"""
sys.stdout.write('.')
if stype == 'sparc':
return np.array([
sparc(_m, fs=1 / ts, padlevel=4, fc=10., amp_th=0.05)[0]
for _m in moves
])
else:
return np.array([ldlj(_m, fs=1 / ts) for _m in moves])
def estimate_smoothness(moves, ts, param, stype="sparc"):
"""Estimates the smoothness of the movements of two different scales.
"""
if stype == 'sparc':
return np.array(
[[sparc(moves[i, j], fs=1/ts, padlevel=4, fc=10., amp_th=0.05)[0]
for j in xrange(param['N_m'])]
for i in xrange(len(param['scales']))])
else:
return np.array(
[[ldlj(moves[i, j], ts)
for j in xrange(param['N_m'])]
for i in xrange(len(param['scales']))])
def est_smooth_noisy(moves, ts, param, stype='sparc'):
"""Estimates the smoothness of noisy movements.
"""
sys.stdout.write('.')
if stype == 'sparc':
return np.array([[[
sparc(moves[i, j, k], fs=1 / ts, padlevel=4, fc=10.,
amp_th=0.05)[0] for k in xrange(param['N_n'])
] for j in xrange(len(param['snr']))] for i in xrange(param['N_m'])])
else:
return np.array(
[[[ldlj(moves[i, j, k], ts) for k in xrange(param['N_n'])]
for j in xrange(len(param['snr']))]
for i in xrange(param['N_m'])])
def est_smooth_noisy(moves, ts, param, stype='sparc'):
"""Estimates the smoothness of noisy movements.
"""
sys.stdout.write('.')
if stype == 'sparc':
return np.array(
[[[sparc(moves[i, j, k], fs=1/ts,
padlevel=4, fc=10., amp_th=0.05)[0]
for k in xrange(param['N_n'])]
for j in xrange(len(param['snr']))]
for i in xrange(param['N_m'])])
else:
return np.array(
[[[ldlj(moves[i, j, k], ts)
for k in xrange(param['N_n'])]
for j in xrange(len(param['snr']))]
for i in xrange(param['N_m'])])