如何在Matplotlib中为3D plot_surface设置动画 [英] How to animate 3d plot_surface in matplotlib

问题描述

我已经从文件创建了3D绘图表面，并且正在尝试对绘图进行动画处理. 我已经阅读了matplotlib网页中的示例以及SO中的其他示例，并注意到我需要创建一个更新函数来遍历文件中的值，然后创建一个matplotlib.animation对象，但是我不知道该怎么做.它.

I have created a 3D plot surface from a file and I'm trying to animate the plot. I have read the examples in the matplotlib webpage and other examples in SO, and notice that I need to create an update function to loop through the values in the file and then create a matplotlib.animation object but I don't understand how to do it.

如果有人可以向我解释更新函数的语法以及如何在matplotlib.animation对象中使用它，我将不胜感激.

I would appreciate very much if someone could explain me the syntax of the update function and how to use it in the matplotlib.animation object.

我的数据是一个有498行的多维数组，对于每一行，我都有一个具有64x128值的数组.数据的组织方式如下:

My data is a multidimensional array with 498 lines and for each line i have an array with 64x128 values. Data is organized in the following way:

数据是来自测力板的时间序列，每500条线中的每一条都是一帧，这意味着该试验持续10秒.对于每一帧，我都有另一个具有64x128值的数组.

Data is a time series from a force plate and each one of the 500 lines is a frame, wich means that this trial lasts 10 seconds. For each frame i have another array with 64x128 values.

这是我到目前为止的代码:

This is my code until now:

from mpl_toolkits.mplot3d import *
import matplotlib.pyplot as plt
import numpy as np
from random import random, seed
from matplotlib import cm
from mpl_toolkits.mplot3d import axes3d
import matplotlib.animation as animation

source_path = "c:\\Projecto\\"
destination_path = "c:\\Projecto\\EntirePlate\\"
#fid = np.loadtxt(source_path + "rolloff_xls.txt",dtype=str)

fid_MP = open(source_path + "101mp - Entire plate roll off.xls","Ur")
lines_MP = fid_MP.readlines()
fid_MP.close()

values_MP = []

for i in lines_MP:
      if i[0].isdigit():
          values_MP.append(i)

values = np.loadtxt(values_MP,dtype=float)

new_values_MP =[]

for i in range(0,(len(values_MP)/64)):
    for j in range(0,64):
        new_values_MP.append([[i],[j],values[j]])

new_values_MP = np.asarray(new_values_MP)

fig = plt.figure()
ax = fig.gca(projection='3d')               # to work in 3d
plt.hold(True)

x_surf = np.arange(0,128)                # generate a mesh
y_surf = np.arange(0,64)
x_surf, y_surf = np.meshgrid(x_surf, y_surf)
z_surf = []

for i in range(0,64):
     # print(new_values[i])
     z_surf.append(np.asarray(new_values_MP[i][2])) # ex. function, which depends on x and y

z_surf = np.asarray(z_surf).reshape([64,128])

ax.plot_surface(x_surf, y_surf, z_surf, rstride=2, cstride=2 ,cmap=cm.jet)    # plot a 3d surface plot

ax.set_xlabel('Medio Lateral - Axis')
ax.set_ylabel('Anterior Posterior - Axis')
ax.set_zlabel('Pressure (P)')

def update(x_values, y_values, z_values):
     for i in range(0,len(values_MP)/64):
         x_surf = x_values
         y_surf = y_values
         z_surf.set_data(new_values_MP[i,2])
     return z_surf

ani = animation.FuncAnimation(fig, update, frames=xrange(len(values_MP)/64),
                               interval=50, blit=False)
plt.show()

推荐答案

这可能不是最佳方法，但是我发现文档/示例也不够.

This is possibly not the optimal way, but I found the documentation/examples not sufficient too.

我采用的是以下解决方案:使用animation.FuncAnimation调用函数.在该函数中清除并重新绘制，如下所示:

What I resorted to is the following solution: use animation.FuncAnimation to call a function. In that function clear and redraw, like so:

from __future__ import division
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as p3
import matplotlib.animation as animation
import numpy as np

plot_args = {'rstride': 1, 'cstride': 1, 'cmap':
             cm.bwr, 'linewidth': 0.01, 'antialiased': True, 'color': 'w',
             'shade': True}

soln = np.zeros((size, size))
midpoint = size // 2
soln[midpoint, midpoint] = 1

#first frame
X = range(size)
Y = range(size)
X, Y = np.meshgrid(X, Y)
plot = ax.plot_surface(X, Y, soln, **plot_args)
pam_ani = animation.FuncAnimation(fig, data_gen, fargs=(soln, plot),
                              interval=30, blit=False)

def data_gen(framenumber, soln, plot):
    #change soln variable for the next frame
    ...
    ax.clear()
    plot = ax.plot_surface(X, Y, soln, **plot_args)
    return plot,

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