I am generating a live plot using matplotlib's funcAnimation function such as in the example below. To be clear I am plotting data that is dynamically updating in real-time and I want to view these updates in the browser rather than in its own local plotting window.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
import mpld3
def animate(i):
plt.clf()
#generate random data
x = np.array([i for i in range(100)])
y = np.random.normal(loc=0,scale=1, size = 100)
plt.scatter(x,y)
def main():
fig = plt.figure()
ani = animation.FuncAnimation(fig, animate, interval=1000)
ani.save('animation.gif', fps=10)
plt.show()
#mpld3.show()
if __name__ == '__main__':
main()
It opens the plot in its own little window.
I was wondering what is the best/quickest way to open this in browser instead? I tried using mpld3 as recommended in some places (see the commented bits of code in my code snippet), but all I get is a static page that does not update. I would like the plot to be redrawn in the browser during each redraw done by the animate fuction as it does when the plot is generated in it's own window instead as in the first image.
Thanks in advance for any help anyone has to offer!
Related
I have an animation created with plt.pause as below...
import matplotlib.pyplot as plt
for i in range(10):
plt.scatter(0, i)
plt.pause(0.01)
plt.show()
How can I save this as a video file, e.g. a .mp4 file?
First, I have to redefine the plotting as a function with the plotted point given by a frame i. plt.pause() can be replaced by matplotlib.animate. Finally, I used a package suggested here to get the conversion to .mp4 format. You will need to install MoviePy:
pip install MoviePy
and then I just animate the function with matplotlib.animate into a .gif format before sending it to MoviePy. You'll need to figure out what directory you want this all to happen in. I'm just using the current working directory.
Here is the code:
import matplotlib.pyplot as plt
import matplotlib.animation as ani
import os
import moviepy.editor as mp
frames=20
fig = plt.figure()
ax = plt.gca()
def scatter_ani(i=int):
plt.scatter(0, i)
name = r"\test.gif"
path = str(os.getcwd())
anim = ani.FuncAnimation(fig, scatter_ani, frames = frames, interval=50)
anim.save(path+name)
clip = mp.VideoFileClip(path+name)
clip.write_videofile(path+r"\test.mp4")
The gif is then
To tweak the length of the animation, check out the docs for matplotlib.animate. For example, if you want to clear all of the previous data-points and show only the dot moving up, then you need to clear the axes in the function, and bound the y-axis so you see the motion ie
def scatter_ani(i=int):
ax.clear()
ax.set_ylim(0, frames+1)
plt.scatter(0, i)
to get:
I am working on a project that involves generating a matplotlib animation using pyplot.imshow for the frames. I am doing this in a jupyter notebook. I have managed to get it working, but there is one annoying bug (or feature?) left. After the animation is created, Jupyter shows the last frame of the animation in the output cell. I would like the output to include the animation, captured as html, but not this final frame. Here is a simple example:
import numpy as np
from matplotlib import animation
from IPython.display import HTML
grid = np.zeros((10,10),dtype=int)
fig1 = plt.figure(figsize=(8,8))
ax1 = fig1.add_subplot(1,1,1)
def animate(i):
grid[i,i]=1
ax1.imshow(grid)
return
ani = animation.FuncAnimation(fig1, animate,frames=10);
html = HTML(ani.to_jshtml())
display(html)
I can use the capture magic, but that suppresses everything. This would be OK, but my final goal is to make this public, via binder, and make it as simple as possible for students to use.
I have seen matplotlib animations on the web that don't seem to have this problems, but those used plot, rather than imshow, which might be an issue.
Any suggestions would be greatly appreciated.
Thanks,
David
That's the answer I got from the same thing I was looking for in 'jupyter lab'. Just add plt.close().
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from IPython.display import HTML
grid = np.zeros((10,10),dtype=int)
fig1 = plt.figure(figsize=(8,8))
ax1 = fig1.add_subplot(1,1,1)
def animate(i):
grid[i,i]=1
ax1.imshow(grid)
return
ani = animation.FuncAnimation(fig1, animate,frames=10);
html = HTML(ani.to_jshtml())
display(html)
plt.close() # update
I want to implement some live plotting in Jupyter lab using Jupyter-Matplotlib. Unfortunately the plot is scaled awkwardly during live plotting. You can see the result in the GIF below. Only the upper left corner of the plot is visible.
The code I used is as follows:
%matplotlib notebook
from matplotlib import pyplot as plt
import time
fig = plt.figure()
ax = fig.gca()
canvas = fig.canvas
a = []
for i in range(10):
a.append(i)
ax.clear()
ax.plot(a)
canvas.draw()
time.sleep(0.5)
Does anyone have experience with this kind of issue and knows how to fix it?
I'm trying to control the display of a scatter plot with a checkbox. When I built it using the interact function it worked as expected. The plot was shown or hidden based on the value in the checkbox.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
def on_change(Display):
if Display == True:
plt.scatter(x,y)
plt.show()
return Display
interact(on_change, Display=False);
When I tried to do the same thing using the observe function every time I clicked on the checkbox I get an additional plot displayed below. What do I need to do to get it to redraw the same plot so it works like the example above?
I suppose something in the interact example is clearing the display but it's not clear how to do this manually.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
x = [1,2,3,4,5,6,7,8]
y = [5,2,4,2,1,4,5,2]
def on_change(change):
if change['new'] == True:
scat = plt.scatter(x,y)
plt.show()
cb = widgets.Checkbox(False, description = "Display")
cb.observe(on_change, names='value')
display(cb)
A couple of alterations I made to your example to hopefully demonstrate what you want. I have taken a more object-oriented route, not sure if you specifically wanted to avoid it but it helps achieve your desired outcome, it seems like you are moving towards a simple GUI here.
1) Include an Output widget (out) - basically a cell output which you can display like a normal widget. You can use a context manager block (with out:) when you want to print to that specific output widget. You can also clear the widget with out.clear_output()
2) Use the object oriented interface in matplotlib rather than using plt. I find this easier to control which plots are displayed and in which location at the right times.
temporarily suspend the interactive matplotlib with plt.ioff()
Create your figure and axis with fig, ax = plt.subplots(). NB figures can have multiple axes/subplots but we only need one.
'plot' the scatter data to your axis using ax.scatter(x,y), but this won't cause it to appear.
Explicitly display the figure with display(fig).
I'm assuming you want your figure to be replotted each time you check the box, so I have included it in the observe function. If your figure doesn't change, it would make sense to move it outside of the loop.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
out = widgets.Output()
x = [1,2,3,4,5,6,7,8]
y = [5,2,4,2,1,4,5,2]
def on_change(change):
if change['new'] == True:
with out:
plt.ioff()
fig,ax = plt.subplots()
ax.scatter(x,y)
display(fig)
else:
out.clear_output()
cb = widgets.Checkbox(False, description = "Display")
cb.observe(on_change, names='value')
display(cb)
display(out)
I'm trying to create an animated histogram for work, using matplotlib.animation, but animation.FuncAnimation is not functioning properly : when using this code, that i found on the official documentation,
"""
A simple example of an animated plot
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
x = np.arange(0, 2*np.pi, 0.01)
line, = ax.plot(x, np.sin(x))
def animate(i):
print(i)
line.set_ydata(np.sin(x + i/10.0)) # update the data
return line,
# Init only required for blitting to give a clean slate.
def init():
line.set_ydata(np.ma.array(x, mask=True))
return line,
ani = animation.FuncAnimation(fig, animate, np.arange(1, 200),init_func=init,interval=25, blit=True)
plt.show()
I get as final result the graph created by init() function (an empty graph also), but no animate iterations. Furthermore, I tested other codes, which practically gave me the same result : i get the initialization, or the first frame, but not more. matplotlib and matplotlib.animation are installed, everything seems to be ok, except it doesn't work. Have someone an idea how to fix it ? (Thank you in advance :) !)
I had the same issue working with Jupyter notebook and I solved it by inserting the line
%matplotlib notebook
in the code.
It may be that IPython inside your Spyder is configured to automatically use the inline backend. This would show your plots inside the console as png images. Of course png images cannot be animated.
I would suggest not to use IPython but execute the script in a dedicated Python console. In Spyder, go to Run/Configure.. and set the option to new dedicated Python console.