When I create an animated graph using matplotlib's FuncAnimation, the axis ticks and labels are blurry when I use Jupyter Notebook, as in this screenshot. This is not the case when I use Python from the console.
Here is a minimal working example that has this problem when I run it from a Jupyter notebook:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
x = np.linspace(0, 4*np.pi, 100)
y = np.sin(x)
fig, ax = plt.subplots()
the_plot, = ax.plot([], []) # Empty array for initialisation
ax.set_xlim(np.min(x), np.max(x))
ax.set_ylim(np.min(y), np.max(y))
def update(i):
the_plot.set_data(x[:i+1], y[:i+1])
anim = animation.FuncAnimation(fig, update, range(len(x)), save_count=len(x))
anim.save('Out.mp4', fps=25, writer='ffmpeg')
Related
I am trying a code to plot a live graph but i always land up with an empty plot. Here is my code :
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib import style
import random
style.use('fivethirtyeight')
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
y = random.randint(0,100) # generate random data
x = i # set x as iteration number
ax1.clear()
ax1.plot(x, y, 'ro')
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
I get warning but i am using plt.show() to show animation. Not sure what i am doing wrong :
UserWarning: Animation was deleted without rendering anything. This is most likely not intended. To prevent deletion, assign the Animation to a variable, e.g. `anim`, that exists until you have outputted the Animation using `plt.show()` or `anim.save()`.
warnings.warn(
I have found a code here which is plotting real time data using python matplotlib. I want to watch the same visualization in Kibana. So can anyone please tell me how to modify my code to view the same plot in Kibana instead with matplotlib?
import time
import psutil
import matplotlib.pyplot as plt
%matplotlib notebook
plt.rcParams['animation.html'] = 'jshtml'
fig = plt.figure()
ax = fig.add_subplot(111)
fig.show()
i = 0
x, y = [], []
while True:
x.append(i)
y.append(psutil.cpu_percent())
ax.plot(x, y, color='b')
fig.canvas.draw()
ax.set_xlim(left=max(0, i-50), right=i+50)
time.sleep(0.1)
i += 1
plt.close()
I would essentially like to do the following:
import matplotlib.pyplot as plt
import numpy as np
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
for i in range(10):
ax1.scatter(i, np.sqrt(i))
ax1.show() # something equivalent to this
ax2.scatter(i, i**2)
That is, each time a point is plotted on ax1, it is shown - ax2 being shown once.
You cannot show an axes alone. An axes is always part of a figure. For animations you would want to use an interactive backend. Then the code in a jupyter notebook could look like
%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
frames = 10
x = np.arange(frames)
line1, = ax1.plot([],[], ls="", marker="o")
line2, = ax2.plot(x, x**2, ls="", marker="o")
ax2.set_visible(False)
def animate(i):
line1.set_data(x[:i], np.sqrt(x[:i]))
ax1.set_title(f"{i}")
ax1.relim()
ax1.autoscale_view()
if i==frames-1:
ax2.set_visible(True)
fig2.canvas.draw_idle()
ani = FuncAnimation(fig1, animate, frames=frames, repeat=False)
plt.show()
If you want to change plots dynamically I'd suggest you don't redraw the whole plot every time, this will result in very laggy behavior. Instead you could use Blit to do this. I used it in a previous project. Maybe it can help you too if you just take the parts from this you need:
Python project dynamically updating plot
I trying to make HTML(anim.to_html5_video) animation work in jupyter with seaborn heatmap.
First, I get working working samples from documentation, and make "pure matplotlib" image map animated example, it worked, with small problem ("parasite output" in animation cell)
Then, I tried to make it work with seaborn.heatmap… but failed. Animation looks like "infinite mirror" — obviously something wrong with matplotlib axes/plot composition, but I can't get it.
Common initialization cell:
import pandas as pd
import seaborn as sns
import numpy as np
%matplotlib inline
#%matplotlib notebook # Tried both, not needed for animation.
import matplotlib.pyplot as plt
from matplotlib import animation, rc
from IPython.display import HTML
Animation worked, but "unwanted static output image exists":
fig, ax = plt.subplots()
nx = 50
ny = 50
line2d, = ax.plot([], [], lw=2)
def init():
line2d.set_data([], [])
ax.imshow(np.zeros((nx, ny)))
return (line2d,)
def animate(i):
data = np.random.rand(nx, ny)
ax.set_title('i: ' + str(i))
ax.imshow(data)
return (line2d,)
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=10, interval=1000, blit=False)
HTML(anim.to_html5_video())
So, looks that all OK with my jupyter setup (packages, ffmpeg, etc).
But, I cannot get how to make it with seaborn.heatmap:
fig, ax = plt.subplots()
nx = 50
ny = 50
line2d, = ax.plot([], [], lw=2)
ax_global = ax
def init_heatmap():
line2d.set_data([], [])
sns.heatmap(np.zeros((nx, ny)), ax=ax_global)
return (line2d,)
def animate_heatmap(i):
data = np.random.rand(nx, ny)
sns.heatmap(data, ax=ax_global)
ax.set_title('Frame: ' + str(i))
return (line2d,)
anim = animation.FuncAnimation(fig, animate_heatmap, init_func=init_heatmap,
frames=10, interval=1000, blit=True)
HTML(anim.to_html5_video())
Both samples ready to test on github
Of course, I want to see animation with random map and "stable heat-axes"
but get this
https://vimeo.com/298786185/
You can toggle the "colorbar". From the Seaborn.heatmap documentation, you need to change sns.heatmap(data, ax=ax_global) to sns.heatmap(data, ax=ax_global, cbar=False) and also do the same inside the init_heatmap().
Here's the code that produces an animation using matplotlib. When I run it in Jupyter notebook, I also get another static graph below the animated graph. How do I remove it?
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML
fig, ax = plt.subplots()
x = np.arange(0, 20, 0.1)
ax.scatter(x, x + np.random.normal(0, 3.0, len(x)))
line, = ax.plot(x, x - 5, 'r-', linewidth=2)
def update(i):
label = 'timestep {0}'.format(i)
line.set_ydata(x - 5 + i)
ax.set_xlabel(label)
return line, ax
anim = FuncAnimation(fig, update, frames=np.arange(0, 10), interval=200)
HTML(anim.to_html5_video())
I use a module called JSAnimation (see this example notebook from the Author).
To display the animation, you simply call:
from JSAnimation.IPython_display import display_animation
display_animation(anim)