list(i)
for i in zip(x[:southp, c], y[:southp, c], z[:southp, c])
]
long = c
else:
pos_list = [
list(i) for i in zip(x[(southp - 1):,
c], y[(southp - 1):,
c], z[(southp - 1):, c])
]
pos_list = pos_list[::-1]
long = c + circles - 1
# Get the radians frames (dec, denorm) and the latent interpolants
df_dec_interp, df_z_interp = interp_multi(pos_list, True, nsteps,
check_model, check_epoch,
method, feats_names)
# Add 'time' column based on frequency fr
end = df_dec_interp.shape[0] * fr + 0.02
df_dec_interp['time'] = list(np.arange(0.02, end, fr))
# Prepare the overview
json_file = os.path.join(df_path, '-overview.json')
with open(json_file, 'r') as fd:
files_dict = json.load(fd)
file_id = len(files_dict)
files_dict[file_id] = {
# Postures in radians
pos_list = []
id_anim_list = []
for frame in frames:
if frame == 0:
pos_list.append(standInit_norm) # List of lists
id_anim_list.append('standInit_0')
else:
pos, id_anim = sel_pos_frame(df, frame)
pos_list.append(pos) # List of lists
id_anim_list.append(id_anim + '_f' + str(frame))
# Get the radians frames (dec, denorm) and the latent interpolants
df_dec_interp, df_z_interp = interp_multi(pos_list, latent, nsteps,
check_model, check_epoch, method,
joints_names)
# Add 'time' column based on frequency fr
end = df_dec_interp.shape[0] * fr + 0.02
df_dec_interp['time'] = list(np.arange(0.02, end, fr))
# Save path
df_path = os.path.join(ROOT_PATH, DATA_SAMP, 'interp_multi_pos')
# Prepare the overview
json_file = os.path.join(df_path, '-overview.json')
with open(json_file, 'r') as fd:
files_dict = json.load(fd)