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问题:
I have a 3D array of data (2 spatial dimensions and 1 time dimension) and I'm trying to produce an animated contour plot using matplotlib.animate. I'm using this link as a basis:
http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
And here's my attempt:
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()
But when I do this, I get the following error:
Traceback (most recent call last): File "showdata.py", line 16, in 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.
So I've tried replacing all the [] by [[],[]] but this then produces:
Traceback (most recent call last): File "showdata.py", line 16, in 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
Thanks in advance!
回答1:
This is what I got to work:
# 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')
I found that removing the blit=0 argument in the FuncAnimation call also helped...
回答2:
This is the line:
cont, = ax.contourf([], [], [], 500)
change to:
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)
You need to intilize with sized arrays.
回答3:
Here is another way of doing the same thing if matplotlib.animation don't work for you. If you want to continuously update the colorbar and everything else in the figure, use plt.ion() at the very beginning to enable interactive plotting and use a combo of plt.draw() and plt.clf() to continuously update the plot.
import matplotlib.pyplot as plt import numpy as np plt.ion(); plt.figure(1); for k in range(10): plt.clf(); plt.subplot(121); plt.contourf(np.random.randn(10,10)); plt.colorbar(); plt.subplot(122,polar=True) plt.contourf(np.random.randn(10,10)); plt.colorbar(); plt.draw();
Note that this works with figures containing different subplots and various types of plots (i.e. polar or cartesian)
回答4:
Removing the blit=0 or blit = True argument in the FuncAnimation call also helped is important!!!
回答5:
I used Lukes approach (from Jun 7 '13 at 8:08 ), but added
ax.collections = []
right before
cont = plt.contourf(x, y, z, 25).
Otherwise I experienced that creating the animation will become very slow for large frame numbers.
回答6:
Felix Schneider is correct about the animation becoming very slow. His solution of setting ax.collections = [] removes all old (and superseded) "artist"s. A more surgical approach is to only remove the artists involved in the drawing the contours:
for c in cont.collections: c.remove()
which is useful in more complicated cases, in lieu of reconstructing the entire figure for each frame. This also works in Rehman Ali's example; instead of clearing the entire figure with clf() the value returned by contourf() is saved and used in the next iteration.
Here is an example code similar to Luke's from Jun 7 '13, demonstrating removing the contours only:
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())
回答7:
I have been looking at this a while ago. I my situation I had a few subplots with contours which I wanted to animate. I did not want to use the plt.clf() solution as Rehman ali suggest as I used some special setup of my axis (with pi symbols etc) which would be cleaned as well, so I preferred the 'remove()' approach suggest be Felix. The thing is that only using 'remove' does not clean up memory and will clog your computer eventually, so you need to explicitly delete of the contours by setting it to an empty list as well.
In order to have a generic remove routine which is able to take away contours as well as text, I wrote the routine 'clean_up_artists' which you should use on every time step on all the axis.
This routine cleans up the artists which are passed in a list called 'artist_list' in a given axis 'axis'. This means that for animating multiple subplots, we need to store the lists of artists for each axis which we need to clean every time step.
Below the full code to animate a number of subplots of random data. It is pretty self-explanatory, so hopefully it becomes clear what happens. Anyhow, I just thought to post it, as it combines several ideas I found on stack overflow which I just to come up with this working example.
Anybody with suggestions to improve the code, please shoot-)
import matplotlib.pyplot as plt from matplotlib import cm import matplotlib.animation as animation import string import numpy as np def clean_up_artists(axis, artist_list): """ try to remove the artists stored in the artist list belonging to the 'axis'. :param axis: clean artists belonging to these axis :param artist_list: list of artist to remove :return: nothing """ for artist in artist_list: try: # fist attempt: try to remove collection of contours for instance while artist.collections: for col in artist.collections: artist.collections.remove(col) try: axis.collections.remove(col) except ValueError: pass artist.collections = [] axis.collections = [] except AttributeError: pass # second attempt, try to remove the text try: artist.remove() except (AttributeError, ValueError): pass def update_plot(frame_index, data_list, fig, axis, n_cols, n_rows, number_of_contour_levels, v_min, v_max, changed_artists): """ Update the the contour plots of the time step 'frame_index' :param frame_index: integer required by animation running from 0 to n_frames -1. For initialisation of the plot, call 'update_plot' with frame_index = -1 :param data_list: list with the 3D data (time x 2D data) per subplot :param fig: reference to the figure :param axis: reference to the list of axis with the axes per subplot :param n_cols: number of subplot in horizontal direction :param n_rows: number of subplot in vertical direction :param number_of_contour_levels: number of contour levels :param v_min: minimum global data value. If None, take the smallest data value in the 2d data set :param v_max: maximum global data value. If None, take the largest value in the 2d data set :param changed_artists: list of lists of artists which need to be updated between the time steps :return: the changed_artists list """ nr_subplot = 0 # keep the index of the current subplot (nr_subplot = 0,1, n_cols x n_rows -1) # loop over the subplots for j_col in range(n_cols): for i_row in range(n_rows): # set a short reference to the current axis ax = axis[i_row][j_col] # for the first setup call, add and empty list which can hold the artists belonging to the current axis if frame_index
