Cannot save animation in python - python-3.x

Question

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')
This does not save animation. However,
anim.save('animation.mp4', progress_callback=lambda i, n: print(f'Saving frame {i} of {n}'))
Does save the animation but the rendering is not really sharp and quite blurry. How do I change that ?
The other points are:
How do I change all the scatter points to a single color ?eg dark grey or black
How do I change the index finger only to a different color? eg Index finger color red
best wishes,
PS: Attached is the animation

Answer 1

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')
I have managed to answer my questions, however, the saving of the animation still remains a problem, the current version works but the video is blurry and is not particularly sharp. The last line of code which is commented out simply does not work for unknown reasons.
If you have a better way to have save the animation with better resolution please let me know.
Attached is the animation.
best wishes,