如何用contourf()制作动画？

Question

我正在尝试动画一些时间相关数据的空间坐标的wigner函数.wigner函数是2维的,所以我使用contourf()来绘制它.我将数据存储在HDF5文件中,可以动态制作Wigner,但我无法弄清楚如何设置动画.我能够找到的所有动画教程和示例(例如这一个和这个)都严格用于线图.具体来说,他们的animate(i)功能使用line.set_data(),我似乎无法找到相应的contourf().

如何使用contourf()？制作的图像动画？

什么是contourf()等效set_data()？

Answer 1

有一种简单的方法FuncAnimation:您必须有一个清除轴的功能,并根据帧编号绘制新的轮廓.不要忘记设置blit为False.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

DATA = np.random.randn(800).reshape(10,10,8)


fig,ax = plt.subplots()

def animate(i):
       ax.clear()
       ax.contourf(DATA[:,:,i])
       ax.set_title('%03d'%(i)) 

interval = 2#in seconds     
ani = animation.FuncAnimation(fig,animate,5,interval=interval*1e+3,blit=False)

plt.show()

Answer 2

这是我用来制作2D等高线图的动画，它是从http://matplotlib.org/examples/animation/dynamic_image2.html改编而来的

import pylab as pl
import numpy as np
import matplotlib.animation as animation
import types


fig = pl.figure()
# Some 2D arrays to plot (time,x,y)
data = np.random.random_sample((20,10,10))

# ims is a list of lists, each row is a list of artists to draw in the
# current frame; here we are just animating one artist, the image, in
# each frame
ims = []
for i in range(len(data[:,0,0])):
    t_step = int(i)
    im = pl.contourf(data[i,:,:])

    #################################################################
    ## Bug fix for Quad Contour set not having attribute 'set_visible'
    def setvisible(self,vis):
        for c in self.collections: c.set_visible(vis)
    im.set_visible = types.MethodType(setvisible,im)
    im.axes = pl.gca()
    im.figure=fig
    ####################################################################

    ims.append([im])

ani = animation.ArtistAnimation(fig, ims, interval=70, blit=False,repeat_delay=1000)

pl.show()

Answer 3

我正在绘制地理数据，因此需要底图。基于captain_M的回答和https://github.com/matplotlib/matplotlib/issues/6139上的讨论/错误报告， 我发布了一个受tacaswell启发的响应，该响应使您可以在二维数据动画中使用contourf并保存如果您有ffmpeg，则将其作为mp4：

from matplotlib import animation
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap


fig, ax = plt.subplots()

# set up map projection
m = Basemap(projection='nsper',lon_0=-0,lat_0=90)
m.drawcoastlines()
m.drawparallels(np.arange(0.,180.,30.))
m.drawmeridians(np.arange(0.,360.,60.))

# some 2D geo arrays to plot (time,lat,lon)
data = np.random.random_sample((20,90,360))
lat = np.arange(len(data[0,:,0]))
lon = np.arange(len(data[0,0,:]))
lons,lats = np.meshgrid(lon,lat)

# ims is a list of lists, each row is a list of artists to draw in the
# current frame; here we are animating three artists, the contour and 2 
# annotatons (title), in each frame
ims = []
for i in range(len(data[:,0,0])):
    im = m.contourf(lons,lats,data[i,:,:],latlon=True)
    add_arts = im.collections
    text = 'title={0!r}'.format(i)
    te = ax.text(90, 90, text)
    an = ax.annotate(text, xy=(0.45, 1.05), xycoords='axes fraction')
    ims.append(add_arts + [te,an])

ani = animation.ArtistAnimation(fig, ims)
## If you have ffmpeg you can save the animation by uncommenting 
## the following 2 lines
# FFwriter = animation.FFMpegWriter()
# ani.save('basic_animation.mp4', writer = FFwriter)
plt.show()