使用matplotlib.animate在python中为等高线图设置动画

Question

我有一个3D数据阵列(2个空间维度和1个时间维度),我正在尝试使用matplotlib.animate生成动画轮廓图.我使用此链接作为基础:

http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/

这是我的尝试:

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
from numpy import array, zeros, linspace, meshgrid
from boutdata import collect

# First collect data from files
n = collect("n")   #  This is a routine to collect data
Nx = n.shape[1]
Nz = n.shape[2]
Ny = n.shape[3]
Nt = n.shape[0]

fig = plt.figure()
ax = plt.axes(xlim=(0, 200), ylim=(0, 100))
cont, = ax.contourf([], [], [], 500)

# initialisation function
def init():
    cont.set_data([],[],[])
    return cont,

# animation function
def animate(i): 
    x = linspace(0, 200, Nx)
    y = linspace(0, 100, Ny)
    x,y = meshgrid(x,y)
    z = n[i,:,0,:].T
    cont.set_data(x,y,z)
    return cont, 

anim = animation.FuncAnimation(fig, animate, init_func=init,
                           frames=200, interval=20, blit=True)

plt.show()

但是当我这样做时,我收到以下错误:

Traceback (most recent call last):
  File "showdata.py", line 16, in <module>
    cont, = ax.contourf([], [], [], 500)
  File "/usr/lib/pymodules/python2.7/matplotlib/axes.py", line 7387, in contourf
    return mcontour.QuadContourSet(self, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1112, in __init__
    ContourSet.__init__(self, ax, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 703, in __init__
    self._process_args(*args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1125, in _process_args
    x, y, z = self._contour_args(args, kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1172, in _contour_args
    x,y,z = self._check_xyz(args[:3], kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1204, in _check_xyz
    raise TypeError("Input z must be a 2D array.")
TypeError: Input z must be a 2D array.

所以我尝试用[[],[]]替换所有[],但这会产生:

Traceback (most recent call last):
  File "showdata.py", line 16, in <module>
    cont, = ax.contourf([[],[]], [[],[]], [[],[]],500)
  File "/usr/lib/pymodules/python2.7/matplotlib/axes.py", line 7387, in contourf
    return mcontour.QuadContourSet(self, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1112, in __init__
    ContourSet.__init__(self, ax, *args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 703, in __init__
    self._process_args(*args, **kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1125, in _process_args
    x, y, z = self._contour_args(args, kwargs)
  File "/usr/lib/pymodules/python2.7/matplotlib/contour.py", line 1177, in _contour_args
    self.zmax = ma.maximum(z)
  File "/usr/lib/python2.7/dist-packages/numpy/ma/core.py", line 5806, in __call__
    return self.reduce(a)
  File "/usr/lib/python2.7/dist-packages/numpy/ma/core.py", line 5824, in reduce
    t = self.ufunc.reduce(target, **kargs)
ValueError: zero-size array to maximum.reduce without identity

提前致谢!

Answer 1

这就是我的工作:

# Generate grid for plotting
x = linspace(0, Lx, Nx)
y = linspace(0, Ly, Ny)
x,y = meshgrid(x,y)

fig = plt.figure()
ax = plt.axes(xlim=(0, Lx), ylim=(0, Ly))  
plt.xlabel(r'x')
plt.ylabel(r'y')

# animation function
def animate(i): 
    z = var[i,:,0,:].T
    cont = plt.contourf(x, y, z, 25)
    if (tslice == 0):
        plt.title(r't = %1.2e' % t[i] )
    else:
        plt.title(r't = %i' % i)

    return cont  

anim = animation.FuncAnimation(fig, animate, frames=Nt)

anim.save('animation.mp4')

我发现在FuncAnimation调用中删除blit = 0参数也有帮助......

Answer 2

Felix Schneider对于动画变得非常慢很正确.他的设置解决方案ax.collections = []删除了所有旧的(和被取代的)"艺术家".更外科的方法是只删除参与绘制轮廓的艺术家:

for c in cont.collections:
    c.remove()

这在更复杂的情况下是有用的,而不是重建每个帧的整个图形.这也适用于Rehman Ali的例子; 而不是用clf()返回的值清除整个数字,contourf()而是保存并在下一次迭代中使用.

这是一个类似于2013年6月7日的Luke的示例代码,演示了仅删除轮廓:

import pylab as plt
import numpy
import matplotlib.animation as animation
#plt.rcParams['animation.ffmpeg_path'] = r"C:\some_path\ffmpeg.exe"   # if necessary

# Generate data for plotting
Lx = Ly = 3
Nx = Ny = 11
Nt = 20
x = numpy.linspace(0, Lx, Nx)
y = numpy.linspace(0, Ly, Ny)
x,y = numpy.meshgrid(x,y)
z0 = numpy.exp(-(x-Lx/2)**2-(y-Ly/2)**2)   # 2 dimensional Gaussian

def some_data(i):   # function returns a 2D data array
    return z0 * (i/Nt)

fig = plt.figure()
ax = plt.axes(xlim=(0, Lx), ylim=(0, Ly), xlabel='x', ylabel='y')

cvals = numpy.linspace(0,1,Nt+1)      # set contour values 
cont = plt.contourf(x, y, some_data(0), cvals)    # first image on screen
plt.colorbar()

# animation function
def animate(i):
    global cont
    z = some_data(i)
    for c in cont.collections:
        c.remove()  # removes only the contours, leaves the rest intact
    cont = plt.contourf(x, y, z, cvals)
    plt.title('t = %i:  %.2f' % (i,z[5,5]))
    return cont

anim = animation.FuncAnimation(fig, animate, frames=Nt, repeat=False)
anim.save('animation.mp4', writer=animation.FFMpegWriter())

Answer 3

这是一行：

cont, = ax.contourf([], [], [], 500)

改成：

 x = linspace(0, 200, Nx)
 y = linspace(0, 100, Ny)
 x, y = meshgrid(x, y)
 z = n[i,:,0,:].T
 cont, = ax.contourf(x, y, z, 500)

您需要使用大小合适的数组。