def animation_for_char(fig, ax, sample_data, rate=30):
if ax is None:
return None
# process the data, rescale time length...
timelen_array = sample_data[:, -1]
nframes_array = timelen_array * rate * 3
motion_data = []
motionframenum_array = []
for strk_idx in range(len(nframes_array)):
strk_data = np.reshape(sample_data[strk_idx][0:-1], (2, -1)).T
# print len(strk_data), int(nframes_array[strk_idx])
resample_strk_data = utils.interp_traj(strk_data, int(nframes_array[strk_idx]))
motion_data.append(resample_strk_data)
motionframenum_array.append(len(resample_strk_data))
motionframenum_array = np.cumsum(motionframenum_array)
motion_data_stacked = np.vstack(motion_data)
# print sample_data
# print timelen_array
# print motion_data
tol_nframes = motionframenum_array[-1]
frame_data_array = []
last_frame_data = [[]]
for frame_idx in range(tol_nframes):
new_start_pnt = np.any(motionframenum_array == frame_idx)
if new_start_pnt:
last_frame_data.append([])
# insert to the active stroke from the last frame data
last_frame_data[len(last_frame_data) - 1].append(motion_data_stacked[frame_idx, :])
frame_data_array.append(copy.deepcopy(last_frame_data))
def init_animation():
global line
for strk_data in frame_data_array[0]:
strk_data_array = np.array(strk_data)
line, = ax.plot(strk_data_array[:, 0], -strk_data_array[:, 1], "b", linewidth=4.0)
ax.hold(True)
ax.set_xlim([-1.5, 1.5])
ax.set_ylim([-1.5, 1.5])
def animate(nframe):
for strk_data in frame_data_array[nframe]:
strk_data_array = np.array(strk_data)
line, = ax.plot(strk_data_array[:, 0], -strk_data_array[:, 1], "b", linewidth=4.0)
ax.hold(True)
ax.set_xlim([-1.5, 1.5])
ax.set_ylim([-1.5, 1.5])
ax.hold(False)
anim = animation.FuncAnimation(fig, animate, init_func=init_animation, frames=tol_nframes)
return anim
def resample_data_to_2d_array_list(sample_data, rate=30):
"""
resample the data to a 2d array list...
"""
timelen_array = sample_data[:, -1]
nframes_array = timelen_array * rate * 3
motion_data = []
for strk_idx in range(len(nframes_array)):
strk_data = np.reshape(sample_data[strk_idx][0:-1], (2, -1)).T
# print len(strk_data), int(nframes_array[strk_idx])
resample_strk_data = utils.interp_traj(strk_data, int(nframes_array[strk_idx]))
motion_data.append(resample_strk_data)
return motion_data
def resample_data_to_2d_array_list(sample_data, rate=30):
'''
resample the data to a 2d array list...
'''
timelen_array = sample_data[:, -1]
nframes_array = timelen_array * rate * 3
motion_data = []
for strk_idx in range(len(nframes_array)):
strk_data = np.reshape(sample_data[strk_idx][0:-1], (2, -1)).T
# print len(strk_data), int(nframes_array[strk_idx])
resample_strk_data = utils.interp_traj(strk_data,
int(nframes_array[strk_idx]))
motion_data.append(resample_strk_data)
return motion_data
def animation_for_char(fig, ax, sample_data, rate=30):
if ax is None:
return None
#process the data, rescale time length...
timelen_array = sample_data[:, -1]
nframes_array = timelen_array * rate * 3
motion_data = []
motionframenum_array = []
for strk_idx in range(len(nframes_array)):
strk_data = np.reshape(sample_data[strk_idx][0:-1], (2, -1)).T
# print len(strk_data), int(nframes_array[strk_idx])
resample_strk_data = utils.interp_traj(strk_data,
int(nframes_array[strk_idx]))
motion_data.append(resample_strk_data)
motionframenum_array.append(len(resample_strk_data))
motionframenum_array = np.cumsum(motionframenum_array)
motion_data_stacked = np.vstack(motion_data)
# print sample_data
# print timelen_array
# print motion_data
tol_nframes = motionframenum_array[-1]
frame_data_array = []
last_frame_data = [[]]
for frame_idx in range(tol_nframes):
new_start_pnt = np.any(motionframenum_array == frame_idx)
if new_start_pnt:
last_frame_data.append([])
#insert to the active stroke from the last frame data
last_frame_data[len(last_frame_data) - 1].append(
motion_data_stacked[frame_idx, :])
frame_data_array.append(copy.deepcopy(last_frame_data))
def init_animation():
global line
for strk_data in frame_data_array[0]:
strk_data_array = np.array(strk_data)
line, = ax.plot(strk_data_array[:, 0],
-strk_data_array[:, 1],
'b',
linewidth=4.0)
ax.hold(True)
ax.set_xlim([-1.5, 1.5])
ax.set_ylim([-1.5, 1.5])
def animate(nframe):
for strk_data in frame_data_array[nframe]:
strk_data_array = np.array(strk_data)
line, = ax.plot(strk_data_array[:, 0],
-strk_data_array[:, 1],
'b',
linewidth=4.0)
ax.hold(True)
ax.set_xlim([-1.5, 1.5])
ax.set_ylim([-1.5, 1.5])
ax.hold(False)
anim = animation.FuncAnimation(fig,
animate,
init_func=init_animation,
frames=tol_nframes)
return anim
