def step_id(df_f, df_t, forcepla=[2], R='RCAL', L='LCAL', show_msg=True):
"""Identification of step side based on .forces and .trc files.
"""
if show_msg:
print('Step identification ... ', end='')
if not isinstance(forcepla, list):
forcepla = [forcepla]
if not forcepla:
forcepla = list(set([int(fp[-1]) for fp in df_f.columns.values]))
forces = [
force + str(fp) for fp in forcepla
for force in ['FX', 'FY', 'FZ', 'MZ']
]
time = df_f.index.values
freq = np.round(np.mean(1 / np.diff(time)), 0)
# resample trc data to the forces frequency
R = np.interp(time, df_t.index.values, df_t[R].Y.values[:, 0])
L = np.interp(time, df_t.index.values, df_t[L].Y.values[:, 0])
# detect onsets in Fy data
threshold = 50
n_above = int(0.1 * freq)
n_below = int(0.01 * freq)
threshold2 = 10 * threshold # N
n_above2 = int(0.02 * freq)
idx = detect_onset(df_f[forces[1]].values, threshold, n_above, n_below,
threshold2, n_above2)
# column names of the .mot dataframe
cols = [
'R_ground_force_vx', 'R_ground_force_vy', 'R_ground_force_vz',
'R_ground_force_px', 'R_ground_force_py', 'R_ground_force_pz',
'L_ground_force_vx', 'L_ground_force_vy', 'L_ground_force_vz',
'L_ground_force_px', 'L_ground_force_py', 'L_ground_force_pz',
'R_ground_torque_x', 'R_ground_torque_y', 'R_ground_torque_z',
'L_ground_torque_x', 'L_ground_torque_y', 'L_ground_torque_z'
]
data = np.zeros((df_f.shape[0], len(cols)))
# step side identification
for ini, end in idx:
if R[ini:int((ini + end) / 2)].sum() < L[ini:int((ini + end) /
2)].sum():
data[ini:end + 1,
[0, 1, 2, 3, 4, 5, 14]] = df_f.values[ini:end + 1, :]
else:
data[ini:end + 1,
[6, 7, 8, 9, 10, 11, 17]] = df_f.values[ini:end + 1, :]
df = pd.DataFrame(data=data, columns=cols, index=time)
df.index.name = 'time'
if show_msg:
print('done.')
return df
def detect_onset_aux(dfData, **args_func_cortes):
#Si se pasa como argumento corte_ini=1, coge el corte del final de cada ventana
try:
from detecta import detect_onset
except:
from detect_onset import detect_onset
try: #si no se ha indicado el núm corte, coge el primero
corte_ini = args_func_cortes['corte_ini']
args_func_cortes.pop('corte_ini', None)
except:
corte_ini = 0
cortes = detect_onset(dfData, **args_func_cortes)
if corte_ini == 1:
cortes = cortes[:,
corte_ini] + 1 #si se elije el final de la ventana, se añade 1 para que empiece cuando ya ha superado el umbral
cortes = cortes[:-1] #quita el último porque suele quedar cortado
else:
cortes = cortes[:,
corte_ini] #se queda con el primer o segundo dato de cada par de datos.
cortes = cortes[1:] #quita el primero porque suele quedar cortado
return cortes
def filter_forces(df,
h,
forcepla=[2],
fc_forces=20,
fc_cop=6,
threshold=50,
show_msg=True):
"""Filter force data from the treadmill.
"""
if not isinstance(forcepla, list):
forcepla = [forcepla]
if not forcepla:
forcepla = list(set([int(fp[-1]) for fp in df.columns.values]))
forces = [
force + str(fp) for fp in forcepla
for force in ['FX', 'FY', 'FZ', 'MZ']
]
cops = [cop + str(fp) for fp in forcepla for cop in ['X', 'Z']]
df2 = df.copy()
F = df2[forces[1]].values
freq = h['SampleRate']
npad = int(freq / 4)
npad2 = 2
# filter parameters for COP
b_cd, a_cd, fc_cd = critic_damp(fcut=fc_cop,
freq=freq,
npass=2,
fcorr=True,
filt='critic')
if show_msg:
print('Filtering: COP Fc: {:.2f} Hz'.format(fc_cd), end=', ')
n_above = int(0.1 * freq)
n_below = int(0.01 * freq)
threshold2 = 10 * threshold # N
n_above2 = int(0.02 * freq)
# detect onsets in Fy data
idx1 = detect_onset(F, threshold, n_above, n_below, threshold2, n_above2)
for cop in cops:
COP = df2[cop].values
# for each foot strike
for ini, end in idx1:
# reliable COP portion
idx2 = detect_onset(F[ini:end + 1],
4 * threshold,
n_above,
n_below,
None,
1,
del_ini_end=False)
if idx2.shape[0]:
# fit polynomiun
y = COP[ini + idx2[0, 0]:ini + idx2[0, 1] + 1]
t = ini + idx2[0, 0] + np.linspace(0, y.shape[0] - 1,
y.shape[0])
p = np.polyfit(t, y, 2)
# values at the extremities for using to pad data
z = np.polyval(p, [ini, end])
q = np.hstack((z[0] * np.ones(npad), COP[ini:end + 1],
z[1] * np.ones(npad)))
# filter data
q2 = signal.filtfilt(b_cd, a_cd, q)
COP[ini - npad2:end + 1 + npad2] = q2[npad - npad2:-npad +
npad2]
df2[cop] = COP
b_cd, a_cd, fc_cd = critic_damp(fcut=fc_forces,
freq=freq,
npass=2,
fcorr=True,
filt='critic')
if show_msg:
print('Forces Fc: {:.2f} Hz'.format(fc_cd))
for force in forces:
df2[force] = signal.filtfilt(b_cd, a_cd, df2[force])
return df2