I've got an animation with lines and now I want to label the points.
I tried plt.annotate()
and I tried plt.text()
but the labes don't move.
This is my example code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def update_line(num, data, line):
newData = np.array([[1+num,2+num/2,3,4-num/4,5+num],[7,4,9+num/3,2,3]])
line.set_data(newData)
plt.annotate('A0', xy=(newData[0][0],newData[1][0]))
return line,
fig1 = plt.figure()
data = np.array([[1,2,3,4,5],[7,4,9,2,3]])
l, = plt.plot([], [], 'r-')
plt.xlim(0, 20)
plt.ylim(0, 20)
plt.annotate('A0', xy=(data[0][0], data[1][0]))
# plt.text( data[0][0], data[1][0], 'A0')
line_ani = animation.FuncAnimation(fig1, update_line, 25, fargs=(data, l),
interval=200, blit=True)
plt.show()
Can you help me please?
My next step is:
I have vectors with origin in these Points. These vectors change their length and their direction in each animation step.
How can I animate these?
Without animation this works:
soa =np.array( [ [data[0][0],data[1][0],F_A0[i][0][0],F_A0[i][1][0]],
[data[0][1],data[1][1],F_B0[i][0][0],F_B0[i][1][0]],
[data[0][2],data[1][2],F_D[i][0][0],F_D[i][1][0]] ])
X,Y,U,V = zip(*soa)
ax = plt.gca()
ax.quiver(X,Y,U,V,angles='xy',scale_units='xy',scale=1)
First thanks a lot for your fast and very helpful answer!
My Vector animation problem I have solved with this:
annotation = ax.annotate("C0", xy=(data[0][2], data[1][2]), xycoords='data',
xytext=(data[0][2]+1, data[1][2]+1), textcoords='data',
arrowprops=dict(arrowstyle="->"))
and in the 'update-function' I write:
annotation.xytext = (newData[0][2], newData[1][2])
annotation.xy = (data[0][2]+num, data[1][2]+num)
to change the start and end position of the vectors (arrows).
But what is, wehn I have 100 vectors or more? It is not practicable to write:
annotation1 = ...
annotation2 = ...
.
:
annotation100 = ...
I tried with a list:
...
annotation = [annotation1, annotation2, ... , annotation100]
...
def update(num):
...
return line, annotation
and got this error:
AttributeError: 'list' object has no attribute 'axes'
What can I do? Have you any idea?
You have the return all objects that changed from your update function. So since your annotation changed it's position you should return it also:
line.set_data(newData)
annotation = plt.annotate('A0', xy=(newData[0][0],newData[1][0]))
return line, annotation
You can read more about matplotlib
animations in this tutorial
You should also specify the init
function so that the FuncAnimation
knows which elements to remove from the plot when redrawing on the first update. So the full example would be:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
# Create initial data
data = np.array([[1,2,3,4,5], [7,4,9,2,3]])
# Create figure and axes
fig = plt.figure()
ax = plt.axes(xlim=(0, 20), ylim=(0, 20))
# Create initial objects
line, = ax.plot([], [], 'r-')
annotation = ax.annotate('A0', xy=(data[0][0], data[1][0]))
annotation.set_animated(True)
# Create the init function that returns the objects
# that will change during the animation process
def init():
return line, annotation
# Create the update function that returns all the
# objects that have changed
def update(num):
newData = np.array([[1 + num, 2 + num / 2, 3, 4 - num / 4, 5 + num],
[7, 4, 9 + num / 3, 2, 3]])
line.set_data(newData)
# This is not working i 1.2.1
# annotation.set_position((newData[0][0], newData[1][0]))
annotation.xytext = (newData[0][0], newData[1][0])
return line, annotation
anim = animation.FuncAnimation(fig, update, frames=25, init_func=init,
interval=200, blit=True)
plt.show()
I'm coming here from this question, where an annotation should be updated that uses both xy
and xytext
. It appears that, in order to update the annotation correctly, one needs to set the attribute .xy
of the annotation to set the position of the annotated point and to use the .set_position()
method of the annotation to set the position of the annotation. Setting the .xytext
attribute has no effect -- somewhat confusing in my opinion. Below a complete example:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.animation as animation
fig, ax = plt.subplots()
ax.set_xlim([-1,1])
ax.set_ylim([-1,1])
L = 50
theta = np.linspace(0,2*np.pi,L)
r = np.ones_like(theta)
x = r*np.cos(theta)
y = r*np.sin(theta)
line, = ax.plot(1,0, 'ro')
annotation = ax.annotate(
'annotation', xy=(1,0), xytext=(-1,0),
arrowprops = {'arrowstyle': "->"}
)
def update(i):
new_x = x[i%L]
new_y = y[i%L]
line.set_data(new_x,new_y)
##annotation.xytext = (-new_x,-new_y) <-- does not work
annotation.set_position((-new_x,-new_y))
annotation.xy = (new_x,new_y)
return line, annotation
ani = animation.FuncAnimation(
fig, update, interval = 500, blit = False
)
plt.show()
The result looks something like this:
In case that versions matter, this code has been tested on Python 2.7 and 3.6 with matplotlib version 2.1.1, and in both cases setting .xytext
had no effect, while .set_position()
and .xy
worked as expected.
I think I figured out how to animate multiple annotations through a list. First you just create your annotations list:
for i in range(0,len(someMatrix)):
annotations.append(ax.annotate(str(i), xy=(someMatrix.item(0,i), someMatrix.item(1,i))))
Then in your "animate" function you do as you have already written:
for num, annot in enumerate(annotations):
annot.set_position((someMatrix.item((time,num)), someMatrix.item((time,num))))
(You can write it as a traditional for loop as well if you don't like the enumerate way). Don't forget to return the whole annotations list in your return statement.
Then the important thing is to set "blit=False" in your FuncAnimation:
animation.FuncAnimation(fig, animate, frames="yourframecount",
interval="yourpreferredinterval", blit=False, init_func=init)
It is good to point out that blit=False might slow things down. But its unfortunately the only way I could get animation of annotations in lists to work...