Yesterday I started my journey into learning how to animate functions to do some small projects for my work. Right now, I'm trying to code a simple linear equation graph that only shows a dot at a time
from itertools import count
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
plt.style.use('seaborn-paper')
x_vals = []
y_vals = []
index = count()
def animate(i):
x_vals = []
y_vals = []
x_vals*= 0
y_vals*= 0
var=next(index)
x_vals.append(var*0.05 % 10)
y_vals.append(var*0.05 % 10)
plt.cla()
plt.xlim(0,10)
plt.ylim(0,10)
plt.scatter(x_vals,y_vals)
ani = FuncAnimation(plt.gcf(), animate, interval=1)
plt.tight_layout()
plt.show()
Keep in mind that this is a super sketchy solution for what I'm trying to do.
My question is: is there a way to smooth my dot animation so it doesnt look choppy?
I found a way to simplify your code which could help make it faster. Passing index as the function for the frames argument definitely increased the speed.
index = count()
def animate(i):
var = next(index)
v = var*0.05 % 10
plt.cla()
plt.xlim(0,10)
plt.ylim(0,10)
plt.scatter(v,v)
ani = FuncAnimation(plt.gcf(), animate, frames = index, interval = 1)
plt.tight_layout()
plt.show()
If you look at this post you will see (a) smooth animations, and (b) the author's use of optional arguments to FuncAnimation.
Related
I am trying to plot real time data. I managed to plot the data but I would like for the bar graph to go up and down on a single x-value rather than produce new x-values for every new datapoint. I believe I have to replace the function x.append(i) with something like a replace, any ideas? Thank you!!
So far this is what I came up with:
import time
import psutil
import matplotlib.pyplot as plt
%matplotlib notebook
fig = plt.figure()
ax = fig.add_subplot(111)
fig.show()
plt.axis('off')
i = 0
x, y = [], []
while True:
x.append(i)
y.append(psutil.cpu_percent())
ax.bar(x, y, color='b')
fig.canvas.draw()
ax.set_xlim(left=max(0, i-50), right=i+50)
time.sleep(0.1)
i += 1
For the bar graph you can create a list inside the while loop, and instantly update it there. First you need to import a random in order get random value for y axis, or you can use cpu_percent.
import psutil
import random
These two should work.
And then:
while True:
x_axis = [str(_) for _ in range(100, 200)]
y_axis = [8 * random.random() for _ in range(100, 200)]
ax.bar(x, y, color='b')
fig.canvas.draw()
time.sleep(0.1)
However, matplotlib is not convenient for real data plotting, I strongly recommend you to use bokeh. You can find bokeh documentation here. It is really cool for creating any kind of real time plot. And at the same time, you can integrate it with your web browser. Hope this will help you)
If you just want to display the latest value, you can consider doing something like:
plt.ion()
graph = plt.bar(["Now"], [0])[0]
plt.axis('off')
i = 0
data = {}
while True:
cpu_percent = psutil.cpu_percent()
graph.set_ydata(cpu_percent)
plt.draw()
plt.pause(0.1)
data[i] = cpu_percent
i += 1
This way, you still have a record of all the datapoints to play with later (x, y) but you will only display 1 x value at a time on the graph.
Further reading
I am trying to use matplotlib's FuncAnimation to make an animated video. Each frame is just a boolean n x n array visualised as white/black squares. I can do this successfully by defining all the arrays in advance and then going through them one by one. This uses code similar to matplotlib's example.
My items are rather large and I want to run the simulation for a long time. I thus don't want to create the entire list of arrays then go through them one by one. Instead, I want to define the animate function to do each step. Let me explain with a minimal non-working example. My actual example includes far larger arrays!
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def create_video(n):
global X
X = np.random.binomial(1, 0.3, size = (n,n))
fig = plt.figure()
im = plt.imshow(X, cmap = plt.cm.gray)
def animate(t):
global X
X = np.roll(X, +1, axis = 0)
im.set_array(X)
anim = FuncAnimation(
fig,
animate,
frames = 100,
interval = 1000 / 30,
blit = True
)
return anim
anim = create_video(10)
This initialises some random 10 x 10 set of 0/1s then just 'rolls' it at each step. I get an error.
RuntimeError: The animation function must return a sequence of Artist objects.
If I remove the return anim, replacing it with pass, and replacing anim = create_video(10) with create_video(10), then I get a warning.
UserWarning: Animation was deleted without rendering anything. This is most likely unintended. To prevent deletion, assign the Animation to a variable that exists for as long as you need the Animation.
Clearly, I don't understand well enough FuncAnimation. What I want to happen is for the function animate to update the array X, by 'rolling' it one step, as well as doing im.set_array(X).
As explained in this answer:
As the error suggests, and as can be seen e.g. in the
simple_animation example, but also from the FuncAnimation
documentation, the init_func as well as the updating func are
supposed to return an iterable of artists to animate.
The documentation does not say that this is actually only needed when
using blit=True, but since you are using blitting here, it is
definitely needed.
So you have two ways:
add
return im,
to animate function
set blit = False in FuncAnimation
Complete Code
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def create_video(n):
global X
X = np.random.binomial(1, 0.3, size = (n, n))
fig = plt.figure()
im = plt.imshow(X, cmap = plt.cm.gray)
def animate(t):
global X
X = np.roll(X, +1, axis = 0)
im.set_array(X)
return im,
anim = FuncAnimation(
fig,
animate,
frames = 100,
interval = 1000/30,
blit = True
)
plt.show()
return anim
anim = create_video(10)
I have trajectory data where each vehicle has its own time to start. Each vehicle is a point in the animation. So, in the dataset, for each row there is coordinate point (x,y) along with a timestamp. So, fixed time interval would not work for me. I tried with loop and sleep but it not showing the animation but only the first result. But if debug line by line, it seems okay(updating with new points after each iteration). Here is my code (this is to test: loop, sleep and animation):
#sample data
x=[20,23,25,27,29,31]
y=[10,12,14,16,17,19]
t=[2,5,1,4,3,1,]
#code
fig, ax = plt.subplots()
ax.set(xlim=(10, 90), ylim=(0, 60))
for i in range(1,6):
ax.scatter(x[:i+1], y[:i+1])
plt.show()
time.sleep(t[i])
How can get the animation effect?
The already mentioned FuncAnimation has a parameter frame that the animation function can use an index:
import matplotlib.pyplot as plt
import matplotlib.animation as anim
fig = plt.figure()
x=[20,23,25,27,29,31]
y=[10,12,14,16,17,19]
t=[2,9,1,4,3,9]
#create index list for frames, i.e. how many cycles each frame will be displayed
frame_t = []
for i, item in enumerate(t):
frame_t.extend([i] * item)
def init():
fig.clear()
#animation function
def animate(i):
#prevent autoscaling of figure
plt.xlim(15, 35)
plt.ylim( 5, 25)
#set new point
plt.scatter(x[i], y[i], c = "b")
#animate scatter plot
ani = anim.FuncAnimation(fig, animate, init_func = init,
frames = frame_t, interval = 100, repeat = True)
plt.show()
Equivalently, you could store the same frame several time in the ArtistAnimation list. Basically the flipbook approach.
Sample output:
I want to add a legend in a python animation, like the line.set_label() below. It is similar to plt.plot(x,y,label='%d' %*variable*).
However, I find that codes do not work here. The animation only shows lines changing but no label or legend available. How can I fix this problem?
from matplotlib import pyplot as plt
from matplotlib import animation
fig = plt.figure()
ax = plt.axes(xlim=(0, 2), ylim=(0, 100))
N = 3
lines = [plt.plot([], [])[0] for _ in range(N)]
def init():
for line in lines:
line.set_data([], [])
return lines
def animate(i):
for j,line in enumerate(lines):
line.set_data([0, 2], [10*j,i])
line.set_label('line %d, stage %d'%(j,i))
return lines
anim = animation.FuncAnimation(fig, animate, init_func=init,
frames=100, interval=20, blit=True)
plt.show()
you must return the legend in your animation function for it to be rendered.
Try this, instead :
legend = plt.legend()
def animate(i):
for j,line in enumerate(lines):
line.set_data([0, 2], [10*j,i])
line.set_label('line %d, stage %d'%(j,i))
legend.remove()
legend = plt.legend()
return lines + [legend]
You should also include the same code in your init function, init is used when resizing the window, otherwise the legend will disappear when resizing
I'm no expert on matplotlib at all, but in the Double Pendulum animation they display texts which changes, and this leads to some variations which can help you.
To get legends with the actual color of the lines, you can either change the initial setting lines to:
lines = [plt.plot([], [], label = 'line {}'.format(i))[0] for i in range(N)]
or add a line.set_label() to the for loop in the init() function. Both these seem to work as expected. At least if you add plt.legend(loc="upper left") right before plt.show().
However the set_label doesn't work within the animate() function, but according to the linked animation you can use specific text fields added to the animation, and that seems to work nicely. Add the following code after initialisation of lines:
texts = [ax.text(0.80, 0.95-i*0.05, '', transform=ax.transAxes) for i in range(N)]
And change animate() to be:
def animate(i):
for j in range(N):
lines[j].set_data([0, 2], [10*j,i]) #, label="hei {}".format(i))
texts[j].set_text('line %d, stage %d'%(j,i))
return lines
This places the text close to the upper right corner, and is updated for each animation step. Since the lines still have their legend displayed, you possibly simplify into one text only displaying the stage. But I leave the fine tuning of messages to your discretion.
Addendum: Extend Line2D
Another alternative could possibly be to extend lines.Line2D and use these lines in your animation, something similar to this article. Not sure if this would work with animation, but if you can't get the above to work, this might be worth a try.
You can try this minimum working example below. The handle of legend hlegend consist of handles of text htext, so we can update htext content in the hf_frame.
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()
N0 = 20
xdata = np.linspace(0, 2*np.pi, 100)
omega = np.linspace(1, 4, N0)
ydata = np.sin(omega[:,np.newaxis]*xdata)
hline0, = ax.plot(xdata, ydata[0], label=f'omega={omega[0]:.3f}')
hlegend = ax.legend(loc='upper right')
def hf_frame(ind0):
hline0.set_data(xdata, ydata[ind0])
label_i = f'{omega[ind0]:.3f}'
# hline0.set_label(label_i) #doesn't help
htext = hlegend.get_texts()[0]
htext.set_text(label_i)
return hline0,htext
ani = matplotlib.animation.FuncAnimation(fig, hf_frame, frames=N0, interval=200)
plt.show()
I am trying to do the following: Plot points and store a reference in a dictionary. While animating remove points. A minimal example looks as follows:
%matplotlib qt
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.animation as animation
fig = plt.figure()
m = Basemap(projection='aeqd',lat_0=72,lon_0=29, resolution='l',
llcrnrlon=15, llcrnrlat=69,
urcrnrlon=41, urcrnrlat=75.6,area_thresh = 100)
pointDict=dict()
pointDict[1]=m.plot (0, 0,marker='.',label='first')[0]
pointDict[2]=m.plot (0, 0,marker='.',label='second')[0]
def init():
print ("Init")
x,y = m(30, 73)
pointDict[1].set_data(x,y)
x,y = m(31, 73)
pointDict[2].set_data(x,y)
return pointDict.values()
def animate(i):
print ("Frame {0}".format(i))
if i==2:
l=pointDict.pop(1)
print ("Removing {0}".format(l.get_label()))
l.remove()
del l
return pointDict.values()
anim = animation.FuncAnimation(plt.gcf(), animate, init_func=init,
frames=10, interval=1000, blit=True)
plt.show()
Output:
Init
Init
Frame 0
Frame 1
Frame 2
Removing first
Frame 3
Interestingly, if I am plotting just the first point (that is, remove pointDict[2]=m.plot and pointDict[2].set_data in the init function), this works. But if both are plotted, neither removing the first, nor the second point works.
Related questions brought me just as far as I am now:
Matplotlib Basemap animation
How to remove lines in a Matplotlib plot
Matplotlib animating multiple lines and text
Python, Matplotlib, plot multi-lines (array) and animation
I am using Anaconda with Python-2.7 kernel.
I found out what the problem is and want therefore to answer my question by myself:
The problem with this is somewhat unexpected the blit=True.
Obviously, blitting can be only used if the point is set within the animate function. Thus, setting the data in the init routine causes problems.
So there are two options: set blit to False, but this is not very elegant. The other option is to set the points in the first frame.
Then the init and animate functions that work are as follows:
def init():
print ("Init")
pointDict[1].set_data([],[])
pointDict[2].set_data([],[])
return pointDict.values()
def animate(i):
print ("Frame {0}".format(i))
if i==0:
print ("Init")
x,y = m(30, 73)
pointDict[1].set_data(x,y)
x,y = m(31, 73)
pointDict[2].set_data(x,y)
if i==2:
l=pointDict.pop(1)
print ("Removing {0}".format(l.get_label()))
l.remove()
del l
return pointDict.values()
anim = animation.FuncAnimation(plt.gcf(), animate, init_func=init,
frames=10, interval=1000, blit=True)
plt.show()