With more recent versions of matplotlib I'm getting distorted labels on animated plots. Is anybody else getting this? Am I doing something wrong?
Minimum working example:
from netCDF4 import Dataset
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from IPython import display
print(matplotlib.__version__)
# Make a random array of data to plot
r = np.random.rand(10,100,100)
fig, ax = plt.subplots(1,1,figsize=(10,10))
# Initiate Plot
plot = ax.pcolormesh(range(0,100),
range(0,100),
r[0],
cmap='RdBu')
cb = fig.colorbar(plot)
cb.set_label('Temperature')
def animate(frame):
C = r[frame][:-1,:-1]
plot.set_array(C)
ani = animation.FuncAnimation(fig,
animate,
frames= range(0,r.shape[0]),
)
video = ani.to_html5_video()
html = display.HTML(video)
display.display(html)
plt.close()
My labels seem like they're being placed many times (although this bug persists even when the animation only has two frames), and they appear like this:
This behaviour does not occur if I comment out all the lines below the ax.pcolormesh... which creates static plot that looks fine.
I'm on matplotlib 3.3.2
Related
I am trying to create a real-time colour map. I want to continuously change slightly the RGB values of some elements in the matrix to make up my colour map. I read data from an excel file and a part of my data looks like this
Then I want to show the colour change in my colour map in one figure like a video. I tried this code:
df=pd.read_excel(r"G:\3Y_individualProject\Crop_color_data.xlsx", usecols="C:E")
color_data_2d=np.array(df.iloc[0:101])
color_data_1d=np.reshape(color_data_2d,(300))
color_data=color_data_1d.reshape(5,20,3)
for x in range(5):
fig, ax = plt.subplots()
ax.imshow(color_data)
ax.set_aspect("equal")
plt.pause(0.05)
for i in range(3):
color_data[0,1,i]=color_data[0,1,i]+0.1
color_data[1,1,i]=color_data[1,1,i]+0.2
color_data[2,1,i]=color_data[1,1,i]+0.25
print(color_data)
But it plots many different figures instead of showing them in a figure as I expected. I've also just tried to learn and use matplotlib.animation. I have tried the code below:
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
from matplotlib import cm
from matplotlib.animation import FuncAnimation
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
import itertools
def changeColor(x):
fig, ax = plt.subplots()
ax.imshow(color_data)
ax.set_aspect("equal")
for i in range(3):
color_data[0,1,i]=color_data[0,1,i]+0.1
color_data[1,1,i]=color_data[1,1,i]+0.2
color_data[2,1,i]=color_data[1,1,i]+0.25
results=FuncAnimation(plt.gcf(), changeColor, interval=5)
plt.tight_layout()
plt.show()
But with that code, my figure doesn't even display anything. As said I am quite new to matplotlib.animation so can anyone show me how to use matplotlib.animation or any other way to plot a real-time color map in my case, please? Thank you so much!
I am making a simple animated scatter plot in a Jupyter notebook, and I want it to repeat, but with a delay before it loops. This is supposed to be set with the repeat_delay parameter, but it has no effect when I use it in a Jupyter notebook using HTML(ani.to_html5_video()) to show the animation.
Here is a simple example of repositioning 20 points every 200 ms, but trying to add a 2 second delay before repeating the animation:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
from IPython.display import HTML
frame_interval = 200
vid_repeat = True
repeat_delay = 2000 # set long so it would be obvious
def update_xy(i, scat):
scat.set_offsets(np.random.random((20,2)))
return scat,
fig = plt.figure()
init_data = np.random.random((20,3))
scat = plt.scatter(init_data[:,0], init_data[:,1], c=init_data[:,2], s=50, cmap = "hot")
ani = animation.FuncAnimation(fig,
update_xy,
frames=numframes,
interval = frame_interval,
repeat = vid_repeat,
repeat_delay = repeat_delay,
fargs=(scat,))
plt.close(ani._fig)
HTML(ani.to_html5_video())
At the end, it just loops around at frame_interval no matter what value I put for repeat_delay. I get the same result when I save the animation ani.save('foo.mp4'), or try to play it using HTML(ani.to_jshtml()).
Related Questions
Animation in iPython notebook
How to animate a scatter plot?
What I want to do is create an animation in which the nodes of a graph change color with time. When I search for information on animation in matplotlib, I usually see examples that look something like this:
#!/usr/bin/python
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
fig = plt.figure(figsize=(8,8))
images = []
for i in range(10):
data = np.random.random(100).reshape(10,10)
imgplot = plt.imshow(data)
images.append([imgplot])
anim = ArtistAnimation(fig, images, interval=50, blit=True)
anim.save('this-one-works.mp4')
plt.show()
So I thought I could just do something like this:
#!/usr/bin/python
import numpy as np
import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
G = nx.Graph()
G.add_edges_from([(0,1),(1,2),(2,0)])
fig = plt.figure(figsize=(8,8))
pos=nx.graphviz_layout(G)
images = []
for i in range(10):
nc = np.random.random(3)
imgplot = nx.draw(G,pos,with_labels=False,node_color=nc) # this doesn't work
images.append([imgplot])
anim = ArtistAnimation(fig, images, interval=50, blit=True)
anim.save('not-this-one.mp4')
plt.show()
What I'm stuck on is how, after drawing the graph using nx.draw(), I can get an object of the appropriate type to put in the array being passed to ArtistAnimation. In the first example, plt.imshow() returns an object of type matplot.image.AxesImage, but nx.draw() doesn't actually return anything. Is there a way that I can get my hands on a suitable image object?
Completely different approaches are welcome, of course (it seems like there's always many different ways to do the same thing in matplotlib), as long as I can save my animation as an mp4 when I'm done.
Thanks!
--craig
import numpy as np
import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
G = nx.Graph()
G.add_edges_from([(0,1),(1,2),(2,0)])
fig = plt.figure(figsize=(8,8))
pos=nx.graphviz_layout(G)
nc = np.random.random(3)
nodes = nx.draw_networkx_nodes(G,pos,node_color=nc)
edges = nx.draw_networkx_edges(G,pos)
def update(n):
nc = np.random.random(3)
nodes.set_array(nc)
return nodes,
anim = FuncAnimation(fig, update, interval=50, blit=True)
nx.draw does not return anything, hence why your method didn't work. The easiest way to do this is to draw the nodes and edges using nx.draw_networkx_nodes and nx.draw_networkx_edges which return PatchCollection and LineCollection objects. You can then update the color of the nodes using set_array.
Using the same general frame work you can also move the nodes around (via set_offsets for the PatchCollection and set_verts or set_segments for LineCollection)
best animation tutorial I have seen: http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
What I want to do is create an animation in which the nodes of a graph change color with time. When I search for information on animation in matplotlib, I usually see examples that look something like this:
#!/usr/bin/python
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
fig = plt.figure(figsize=(8,8))
images = []
for i in range(10):
data = np.random.random(100).reshape(10,10)
imgplot = plt.imshow(data)
images.append([imgplot])
anim = ArtistAnimation(fig, images, interval=50, blit=True)
anim.save('this-one-works.mp4')
plt.show()
So I thought I could just do something like this:
#!/usr/bin/python
import numpy as np
import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
G = nx.Graph()
G.add_edges_from([(0,1),(1,2),(2,0)])
fig = plt.figure(figsize=(8,8))
pos=nx.graphviz_layout(G)
images = []
for i in range(10):
nc = np.random.random(3)
imgplot = nx.draw(G,pos,with_labels=False,node_color=nc) # this doesn't work
images.append([imgplot])
anim = ArtistAnimation(fig, images, interval=50, blit=True)
anim.save('not-this-one.mp4')
plt.show()
What I'm stuck on is how, after drawing the graph using nx.draw(), I can get an object of the appropriate type to put in the array being passed to ArtistAnimation. In the first example, plt.imshow() returns an object of type matplot.image.AxesImage, but nx.draw() doesn't actually return anything. Is there a way that I can get my hands on a suitable image object?
Completely different approaches are welcome, of course (it seems like there's always many different ways to do the same thing in matplotlib), as long as I can save my animation as an mp4 when I'm done.
Thanks!
--craig
import numpy as np
import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
G = nx.Graph()
G.add_edges_from([(0,1),(1,2),(2,0)])
fig = plt.figure(figsize=(8,8))
pos=nx.graphviz_layout(G)
nc = np.random.random(3)
nodes = nx.draw_networkx_nodes(G,pos,node_color=nc)
edges = nx.draw_networkx_edges(G,pos)
def update(n):
nc = np.random.random(3)
nodes.set_array(nc)
return nodes,
anim = FuncAnimation(fig, update, interval=50, blit=True)
nx.draw does not return anything, hence why your method didn't work. The easiest way to do this is to draw the nodes and edges using nx.draw_networkx_nodes and nx.draw_networkx_edges which return PatchCollection and LineCollection objects. You can then update the color of the nodes using set_array.
Using the same general frame work you can also move the nodes around (via set_offsets for the PatchCollection and set_verts or set_segments for LineCollection)
best animation tutorial I have seen: http://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
I use matplotlib.animation to animate data in a 3D array named arr. I read data from a h5 file using h5py library and everything is OK. But when using animation, the colormap got stuck in first frame of the data range, and after some steps it shows unnormalized colors while plotting.
Here is my code:
import numpy as np
import h5py
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import matplotlib.cm as cm
f = h5py.File('ez.h5','r')
arr = f["ez"][:,:,:]
f.close()
fig = plt.figure()
i = 0
p = plt.imshow(arr[:,:,0], interpolation='bilinear', cmap=cm.RdYlGn)
def updatefig(*args):
global i
i += 1
if (i==333):
i = 0
p.set_array(arr[:,:,i])
plt.clim()
return p,
ani = animation.FuncAnimation(fig, updatefig, interval=50, blit=True)
plt.show()
I think you want to replace set_clim() with
p.autoscale()
With no arguments, set_clim() is a no-op.
That said, changing your color scale in the middle of an animations seems very misleading.
You should also use set_data instead of set_array (according to the docs).