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'])])