无法在 python 中保存动画
Cannot save animation in python
import numpy as np
import pandas as pd
import matplotlib
# matplotlib.use("Agg")
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation
t_start = 2 #start frame
t_end = 1711 #end frame
data = pd.read_csv('Sub6_cylinder0009_index_flex_processed.csv')
df = data.loc[t_start:t_end,'FT1X':'CMC5Z']
df_minmax = pd.DataFrame(index=list('xyz'),columns=range(2))
for i in list('xyz'):
c_max = df.max().max()
c_min = df.min().min()
df_minmax.loc[i] = np.array([c_min,c_max])
df_minmax = 3.3*df_minmax
df.columns = np.repeat(range(22),3)
N_tag = int(df.shape[1]/3) # nr of tags used (all)
N_trajectories = N_tag
t = np.linspace(0,data.Time[t_end],df.shape[0])
x_t = np.zeros(shape=(N_tag,df.shape[0],3))
for tag in range(22):
x_t[tag,:,:] = df[tag]
x_t = x_t[:, :, [0, 2, 1]]
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('on')
#choose a different color for each trajectory
colors = plt.cm.jet(np.linspace(0, 1, N_trajectories))
# set up trajectory lines
lines = sum([ax.plot([], [], [], '-', c=c) for c in colors], [])
# set up points
pts = sum([ax.plot([], [], [], 'o', c=c) for c in colors], [])
#set up lines which create the stick figures
stick_defines = [
(0, 13),
(13, 14),
(14, 19),
(1, 5),
(2, 6),
(3, 7),
(4, 8),
(5, 9),
(6, 10),
(7, 11),
(8, 12),
(9, 15),
(10, 16),
(11, 17),
(12, 18),
(18, 21),
(15, 20)
]
stick_lines = [ax.plot([], [], [], 'k-')[0] for _ in stick_defines]
print(stick_lines)
ax.set_xlim3d([np.nanmin(x_t[:, :, 0]), np.nanmax(x_t[:, :, 0])])
ax.set_ylim3d([np.nanmin(x_t[:, :, 1])-400, np.nanmax(x_t[:, :, 1])+400])
ax.set_zlim3d([np.nanmin(x_t[:, :, 2]), np.nanmax(x_t[:, :, 2])])
ax.set_xlabel('X [mm]')
ax.set_ylabel('Y [mm]')
ax.set_zlabel('Z [mm]')
# set point-of-view: specified by (altitude degrees, azimuth degrees)
#ax.view_init(30, 25)
# initialization function: plot the background of each frame
def init():
for line, pt in zip(lines, pts):
line.set_data(np.array([]), np.array([]))
line.set_3d_properties(np.array([]))
pt.set_data(np.array([]),np.array([]))
pt.set_3d_properties(np.array([]))
return lines + pts
# animation function. This will be called sequentially with the frame number
def animate(i):
i = (5 * i) % x_t.shape[1]
for pt, xi in zip(pts, x_t):
x, y, z = xi[:i].T
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
for stick_line, (sp, ep) in zip(stick_lines, stick_defines):
stick_line._verts3d = x_t[[sp,ep], i, :].T.tolist()
#ax.view_init(30, 0.3 * i)
fig.canvas.draw()
return lines + pts + stick_lines
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=500, interval=30, blit=True, repeat=False)
# Save as mp4. This requires mplayer or ffmpeg to be installed
#anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
plt.show()
anim.save('test.mp4', writer='ffmpeg')
这不会保存动画。然而，
anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
确实保存了动画，但渲染不是很清晰而且很模糊。我该如何更改？
其他要点是：
- 如何将所有散点更改为单一颜色？例如深灰色或黑色
- 如何只将食指换成不同的颜色？例如食指颜色红色
祝福，
PS: 附上动画
import numpy as np
import pandas as pd
import matplotlib
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation
#=============================================================================================
t_start = 2# start frame
t_end = 1711# end frame
data = pd.read_csv('Sub6_cylinder0009_index_flex_processed.csv') # only coordinate data
df = data.loc[t_start:t_end,'FT1X':'CMC5Z']
# Find max and min values for animation ranges
df_minmax = pd.DataFrame(index=list('xyz'),columns=range(2))
for i in list('xyz'):
c_max = df.max().max()
c_min = df.min().min()
df_minmax.loc[i] = np.array([c_min,c_max])
df_minmax = 3.3*df_minmax # increase by 30% to make animation look better
df.columns = np.repeat(range(22),3) # store cols like this for simplicity
print(df.columns)
N_tag = int(df.shape[1]/3) # nr of tags used (all)
N_trajectories = N_tag
t = np.linspace(0,data.Time[t_end],df.shape[0]) # pseudo time-vector for first walking activity
x_t = np.zeros(shape=(N_tag,df.shape[0],3)) # empty animation array (3D)
for tag in range(22):
# # store data in numpy 3D array: (tag,time-stamp,xyz-coordinates)
x_t[tag,:,:] = df[tag]
x_t = x_t[:, :, [0, 2, 1]]
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('on')
#choose a different color for each trajectory
#colors1 = plt.cm.Reds(np.linspace(0, 1, N_trajectories))
#colors2 = plt.cm.gray(np.linspace(0, 1, N_trajectories))
# set up trajectory lines
#lines = sum([ax.plot([], [], [], '-', c=c) for c in colors1], [])
# set up points
#pts = sum([ax.plot([], [], [], 'o--', c=c) for c in colors2], [])
#pts = ax.plot([], [], [], 'o', c=colors2[0])
#pts = ax.plot([], [], [], 'o-', c=colors2[8])
#set up lines which create the stick figures
stick_defines = [
(0, 13), # Thumb Tip
(13, 14),
(14, 19),
(1, 5), #Index Tip
(2, 6), # Middle Tip
(3, 7), # Ring Tip
(4, 8), # Pinky Tip
(5, 9),
(6, 10),
(7, 11),
(8, 12),
(9, 15),
(10, 16),
(11, 17),
(12, 18),
(18, 21),
(15, 20)
# (22, 23),
# (23, 24),
# (22, 26),
# (25,26)
]
stick_defines1 = [
# (0, 13), # Thumb Tip
# (13, 14),
# (14, 19),
(1, 5), #Index Tip
# (2, 6), # Middle Tip
# (3, 7), # Ring Tip
# (4, 8), # Pinky Tip
(5, 9),
# (6, 10),
# (7, 11),
# (8, 12),
(9, 15),
# (10, 16),
# (11, 17),
# (12, 18),
# (18, 21),
(15, 20)
# (22, 23),
# (23, 24),
# (22, 26),
# (25,26)
]
stick_lines = [ax.plot([], [], [], 'ko--', alpha=0.5)[0] for _ in stick_defines]
stick_lines1 = [ax.plot([], [], [], 'ro-')[0] for _ in stick_defines1]
print(stick_lines)
ax.set_xlim3d([np.nanmin(x_t[:, :, 0]), np.nanmax(x_t[:, :, 0])])
ax.set_ylim3d([np.nanmin(x_t[:, :, 1])-400, np.nanmax(x_t[:, :, 1])+400])
ax.set_zlim3d([np.nanmin(x_t[:, :, 2]), np.nanmax(x_t[:, :, 2])])
ax.set_xlabel('X [mm]')
ax.set_ylabel('Y [mm]')
ax.set_zlabel('Z [mm]')
# set point-of-view: specified by (altitude degrees, azimuth degrees)
#ax.view_init(30, 25)
# initialization function: plot the background of each frame
# def init():
# for pt in pts:#zip(pts):
# # line.set_data(np.array([]), np.array([]))
# # line.set_3d_properties(np.array([]))
# pt.set_data(np.array([]), np.array([]))
# pt.set_3d_properties(np.array([]))
# return pts
# animation function. This will be called sequentially with the frame number
def animate(i):
# we'll step two time-steps per frame. This leads to nice results.
i = (5 * i) % x_t.shape[1]
pts = []
for pt, xi in zip(pts, x_t):
x, y, z = xi[:i].T # note ordering of points to line up with true exogenous registration (x,z,y)
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
for stick_line, (sp, ep) in zip(stick_lines, stick_defines):
stick_line._verts3d = x_t[[sp,ep], i, :].T.tolist()
for stick_line1, (sp, ep) in zip(stick_lines1, stick_defines1):
stick_line1._verts3d = x_t[[sp,ep], i, :].T.tolist()
#ax.view_init(30, 0.3 * i)
fig.canvas.draw()
return pts + stick_lines+stick_lines1
# instantiate the animator.
anim = animation.FuncAnimation(fig, animate, frames=500, interval=30, blit=True, repeat=False)
plt.show()
# Save as mp4. This requires mplayer or ffmpeg to be installed
anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
#anim.save('test.mp4', writer='ffmpeg')
我已经回答了我的问题，但是，动画的保存仍然是一个问题，当前版本可以，但是视频模糊并且不是特别清晰。由于未知原因，被注释掉的最后一行代码根本不起作用。
如果您有更好的方法以更好的分辨率保存动画，请告诉我。
附上动画
最良好的祝愿，
import numpy as np
import pandas as pd
import matplotlib
# matplotlib.use("Agg")
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation
t_start = 2 #start frame
t_end = 1711 #end frame
data = pd.read_csv('Sub6_cylinder0009_index_flex_processed.csv')
df = data.loc[t_start:t_end,'FT1X':'CMC5Z']
df_minmax = pd.DataFrame(index=list('xyz'),columns=range(2))
for i in list('xyz'):
c_max = df.max().max()
c_min = df.min().min()
df_minmax.loc[i] = np.array([c_min,c_max])
df_minmax = 3.3*df_minmax
df.columns = np.repeat(range(22),3)
N_tag = int(df.shape[1]/3) # nr of tags used (all)
N_trajectories = N_tag
t = np.linspace(0,data.Time[t_end],df.shape[0])
x_t = np.zeros(shape=(N_tag,df.shape[0],3))
for tag in range(22):
x_t[tag,:,:] = df[tag]
x_t = x_t[:, :, [0, 2, 1]]
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('on')
#choose a different color for each trajectory
colors = plt.cm.jet(np.linspace(0, 1, N_trajectories))
# set up trajectory lines
lines = sum([ax.plot([], [], [], '-', c=c) for c in colors], [])
# set up points
pts = sum([ax.plot([], [], [], 'o', c=c) for c in colors], [])
#set up lines which create the stick figures
stick_defines = [
(0, 13),
(13, 14),
(14, 19),
(1, 5),
(2, 6),
(3, 7),
(4, 8),
(5, 9),
(6, 10),
(7, 11),
(8, 12),
(9, 15),
(10, 16),
(11, 17),
(12, 18),
(18, 21),
(15, 20)
]
stick_lines = [ax.plot([], [], [], 'k-')[0] for _ in stick_defines]
print(stick_lines)
ax.set_xlim3d([np.nanmin(x_t[:, :, 0]), np.nanmax(x_t[:, :, 0])])
ax.set_ylim3d([np.nanmin(x_t[:, :, 1])-400, np.nanmax(x_t[:, :, 1])+400])
ax.set_zlim3d([np.nanmin(x_t[:, :, 2]), np.nanmax(x_t[:, :, 2])])
ax.set_xlabel('X [mm]')
ax.set_ylabel('Y [mm]')
ax.set_zlabel('Z [mm]')
# set point-of-view: specified by (altitude degrees, azimuth degrees)
#ax.view_init(30, 25)
# initialization function: plot the background of each frame
def init():
for line, pt in zip(lines, pts):
line.set_data(np.array([]), np.array([]))
line.set_3d_properties(np.array([]))
pt.set_data(np.array([]),np.array([]))
pt.set_3d_properties(np.array([]))
return lines + pts
# animation function. This will be called sequentially with the frame number
def animate(i):
i = (5 * i) % x_t.shape[1]
for pt, xi in zip(pts, x_t):
x, y, z = xi[:i].T
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
for stick_line, (sp, ep) in zip(stick_lines, stick_defines):
stick_line._verts3d = x_t[[sp,ep], i, :].T.tolist()
#ax.view_init(30, 0.3 * i)
fig.canvas.draw()
return lines + pts + stick_lines
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=500, interval=30, blit=True, repeat=False)
# Save as mp4. This requires mplayer or ffmpeg to be installed
#anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
plt.show()
anim.save('test.mp4', writer='ffmpeg')
这不会保存动画。然而，
anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
确实保存了动画，但渲染不是很清晰而且很模糊。我该如何更改？
其他要点是：
- 如何将所有散点更改为单一颜色？例如深灰色或黑色
- 如何只将食指换成不同的颜色？例如食指颜色红色
祝福，
PS: 附上动画
import numpy as np
import pandas as pd
import matplotlib
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from matplotlib import animation
#=============================================================================================
t_start = 2# start frame
t_end = 1711# end frame
data = pd.read_csv('Sub6_cylinder0009_index_flex_processed.csv') # only coordinate data
df = data.loc[t_start:t_end,'FT1X':'CMC5Z']
# Find max and min values for animation ranges
df_minmax = pd.DataFrame(index=list('xyz'),columns=range(2))
for i in list('xyz'):
c_max = df.max().max()
c_min = df.min().min()
df_minmax.loc[i] = np.array([c_min,c_max])
df_minmax = 3.3*df_minmax # increase by 30% to make animation look better
df.columns = np.repeat(range(22),3) # store cols like this for simplicity
print(df.columns)
N_tag = int(df.shape[1]/3) # nr of tags used (all)
N_trajectories = N_tag
t = np.linspace(0,data.Time[t_end],df.shape[0]) # pseudo time-vector for first walking activity
x_t = np.zeros(shape=(N_tag,df.shape[0],3)) # empty animation array (3D)
for tag in range(22):
# # store data in numpy 3D array: (tag,time-stamp,xyz-coordinates)
x_t[tag,:,:] = df[tag]
x_t = x_t[:, :, [0, 2, 1]]
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection='3d')
ax.axis('on')
#choose a different color for each trajectory
#colors1 = plt.cm.Reds(np.linspace(0, 1, N_trajectories))
#colors2 = plt.cm.gray(np.linspace(0, 1, N_trajectories))
# set up trajectory lines
#lines = sum([ax.plot([], [], [], '-', c=c) for c in colors1], [])
# set up points
#pts = sum([ax.plot([], [], [], 'o--', c=c) for c in colors2], [])
#pts = ax.plot([], [], [], 'o', c=colors2[0])
#pts = ax.plot([], [], [], 'o-', c=colors2[8])
#set up lines which create the stick figures
stick_defines = [
(0, 13), # Thumb Tip
(13, 14),
(14, 19),
(1, 5), #Index Tip
(2, 6), # Middle Tip
(3, 7), # Ring Tip
(4, 8), # Pinky Tip
(5, 9),
(6, 10),
(7, 11),
(8, 12),
(9, 15),
(10, 16),
(11, 17),
(12, 18),
(18, 21),
(15, 20)
# (22, 23),
# (23, 24),
# (22, 26),
# (25,26)
]
stick_defines1 = [
# (0, 13), # Thumb Tip
# (13, 14),
# (14, 19),
(1, 5), #Index Tip
# (2, 6), # Middle Tip
# (3, 7), # Ring Tip
# (4, 8), # Pinky Tip
(5, 9),
# (6, 10),
# (7, 11),
# (8, 12),
(9, 15),
# (10, 16),
# (11, 17),
# (12, 18),
# (18, 21),
(15, 20)
# (22, 23),
# (23, 24),
# (22, 26),
# (25,26)
]
stick_lines = [ax.plot([], [], [], 'ko--', alpha=0.5)[0] for _ in stick_defines]
stick_lines1 = [ax.plot([], [], [], 'ro-')[0] for _ in stick_defines1]
print(stick_lines)
ax.set_xlim3d([np.nanmin(x_t[:, :, 0]), np.nanmax(x_t[:, :, 0])])
ax.set_ylim3d([np.nanmin(x_t[:, :, 1])-400, np.nanmax(x_t[:, :, 1])+400])
ax.set_zlim3d([np.nanmin(x_t[:, :, 2]), np.nanmax(x_t[:, :, 2])])
ax.set_xlabel('X [mm]')
ax.set_ylabel('Y [mm]')
ax.set_zlabel('Z [mm]')
# set point-of-view: specified by (altitude degrees, azimuth degrees)
#ax.view_init(30, 25)
# initialization function: plot the background of each frame
# def init():
# for pt in pts:#zip(pts):
# # line.set_data(np.array([]), np.array([]))
# # line.set_3d_properties(np.array([]))
# pt.set_data(np.array([]), np.array([]))
# pt.set_3d_properties(np.array([]))
# return pts
# animation function. This will be called sequentially with the frame number
def animate(i):
# we'll step two time-steps per frame. This leads to nice results.
i = (5 * i) % x_t.shape[1]
pts = []
for pt, xi in zip(pts, x_t):
x, y, z = xi[:i].T # note ordering of points to line up with true exogenous registration (x,z,y)
pt.set_data(x[-1:], y[-1:])
pt.set_3d_properties(z[-1:])
for stick_line, (sp, ep) in zip(stick_lines, stick_defines):
stick_line._verts3d = x_t[[sp,ep], i, :].T.tolist()
for stick_line1, (sp, ep) in zip(stick_lines1, stick_defines1):
stick_line1._verts3d = x_t[[sp,ep], i, :].T.tolist()
#ax.view_init(30, 0.3 * i)
fig.canvas.draw()
return pts + stick_lines+stick_lines1
# instantiate the animator.
anim = animation.FuncAnimation(fig, animate, frames=500, interval=30, blit=True, repeat=False)
plt.show()
# Save as mp4. This requires mplayer or ffmpeg to be installed
anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
#anim.save('test.mp4', writer='ffmpeg')
我已经回答了我的问题，但是，动画的保存仍然是一个问题，当前版本可以，但是视频模糊并且不是特别清晰。由于未知原因，被注释掉的最后一行代码根本不起作用。
如果您有更好的方法以更好的分辨率保存动画，请告诉我。
附上动画
最良好的祝愿，