I am updating the graph, but can't join to it the scatter, could someone help me, please? I don't understand, how to realize it.
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
fig = plt.figure()
ax = fig.add_subplot()
line = ax.plot([],[])[0]
x = []
y = []
scat = ax.scatter(x,y,c='Red')
def animate(i):
x.append(i)
y.append((-1)**i)
line.set_data(x, y)
ax.relim()
ax.autoscale_view()
return [line]
anim = FuncAnimation(fig, animate, frames=200, interval=100, blit=True)
plt.show()
I want to add dotes and their coordinates change only in X, Y should be 0.
Several problems have to be addressed here. You have to update the scatter plot, which is a PathCollection that is updated via .set_offsets(). This is in turn requires the x-y data to be in an array of the form (N, 2). We could combine the two lists x, y in every animation loop to such an array but this would be time-consuming. Instead, we declare the numpy array in advance and update it in the loop.
As for axes labels, you might have noticed that they are not updated in your animation. The reason for this is that you use blitting, which suppresses redrawing all artists that are considered unchanged. So, if you don't want to take care manually of the axis limits, you have to turn off blitting.
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
import numpy as np
fig, ax = plt.subplots()
line, = ax.plot([],[])
scat = ax.scatter([], [], c='Red')
n=200
#prepare array for data storage
pos = np.zeros((n, 2))
def animate(i):
#calculate new x- and y-values
pos[i, 0] = i
pos[i, 1] = (-1)**i
#update line data
line.set_data(pos[:i, 0], pos[:i, 1])
#update scatter plot data
scat.set_offsets(pos[:i, :])
#update axis view - works only if blit is False
ax.relim()
ax.autoscale_view()
return scat, line
anim = FuncAnimation(fig, animate, frames=n, interval=100, blit=False)
plt.show()
Sample output:
Related
I have 5 txt files which contain data give me the effect of increasing heat on my samples and I want plot them in a vertical stacked graph, Where the final figure is 5 vertical stacked chart sharing the same X-axis and each line in a separate one to reveal the difference between them.
I wrote this code:
import glob
import pandas as pd
import matplotlib.axes._axes as axes
import matplotlib.pyplot as plt
input_files = glob.glob('01-input/RR_*.txt')
for file in input_files:
data = pd.read_csv(file, header=None, delimiter="\t").values
x = data[:,0]
y = data[:,1]
plt.subplot(2, 1, 1)
plt.plot(x, y, linewidth=2, linestyle=':')
plt.tight_layout()
plt.xlabel('x-axis')
plt.ylabel('y-axis')
But the result is only one graph containing all the lines:
I want to get the following chart:
import matplotlib.pyplot as plt
import numpy as np
# just a dummy data
x = np.linspace(0, 2700, 50)
all_data = [np.sin(x), np.cos(x), x**0.3, x**0.4, x**0.5]
n = len(all_data)
n_rows = n
n_cols = 1
fig, ax = plt.subplots(n_rows, n_cols) # each element in "ax" is a axes
for i, y in enumerate(all_data):
ax[i].plot(x, y, linewidth=2, linestyle=':')
ax[i].set_ylabel('y-axis')
# You can to use a list of y-labels. Example:
# my_labels = ['y1', 'y2', 'y3', 'y4', 'y5']
# ax[i].set_ylabel(my_labels[i])
# The "my_labels" lenght must be "n" too
plt.xlabel('x-axis') # add xlabel at last axes
plt.tight_layout()
I am trying to make an animation using ArtistAnimation like this:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
ims = []
for i in range(60):
x = np.linspace(0,i,1000)
y = np.sin(x)
im = ax.plot(x,y, color='black')
ims.append(im)
ani = animation.ArtistAnimation(fig, ims, interval=50, blit=True,
repeat_delay=1000)
plt.show()
This animates a sine wave growing across the figure. Currently I'm just adding the Lines2D object returned by ax.plot() to ims. However, I would like to potentially draw multiple overlapping plots on the Axes and adjust the title, legend and x-axis range for each frame. How do I get an object that I can add to ims after plotting and making all the changes I want for each frame?
The list you supply to ArtistAnimation should be a list of lists of artists, one list per frame.
artist_list = [[line1a, line1b, title1], [line2a, line2b, title2], ...]
where the first list is shown in the first frame, the second list in the second frame etc.
The reason your code works is that ax.plot returns a list of lines (in your case only a list of a single line).
In any case, the following might be a more understandable version of your code where an additional text is animated.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
artist_list = []
for i in range(60):
x = np.linspace(0,i,1000)
y = np.sin(x)
line, = ax.plot(x,y, color='black')
text = ax.text(i,0,i)
artist_list.append([line, text])
ani = animation.ArtistAnimation(fig, artist_list, interval=50, blit=True,
repeat_delay=1000)
plt.show()
In general, it will be hard to animate changing axes limits with ArtistAnimation, so if that is an ultimate goal consider using a FuncAnimation instead.
I can generate an error-bar plot using the code below. The graph produced by the code shows vertical lines that represent the errors in y. I would like to have horizontal lines at the tips of these errors ("error bars") and am not sure how to do so.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1, 10, 10, dtype=int)
y = 2**x
yerr = np.sqrt(y)*10
fig, ax = plt.subplots()
ax.errorbar(x, y, yerr, solid_capstyle='projecting')
ax.grid(alpha=0.5, linestyle=':')
plt.show()
plt.close(fig)
The code generates the figure below. I've played with the solid_capstyle kwarg. Is there a specific kwarg that does what I am trying to do?
And as an example of what I'd like, the figure below:
In case it's relevant, I am using matplotlib 2.2.2
The argument you are looking for is capsize= in ax.errorbar(). The default is None so the length of the cap will default to the value of matplotlib.rcParams["errorbar.capsize"]. The number you give will be the length of the cap in points:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1, 10, 10, dtype=int)
y = 2**x
yerr = np.sqrt(y)*10
fig, ax = plt.subplots()
ax.errorbar(x, y, yerr, solid_capstyle='projecting', capsize=5)
ax.grid(alpha=0.5, linestyle=':')
plt.show()
I have a series to plot at y-axis.
y = [3,4,5,1,4,7,4,7,1,9]
However, I want to plot it by recent time by second. I've done it like this,
import time
def xtime():
t = time.strftime("%H%M%S")
t = int(t)
xtime = [t]
while xtime:
t = time.strftime("%H%M%S")
t = int(t)
xtime.extend([t])
time.sleep(1)
I'm having problem when I want to plot each one of the number at y by each second. Please correct my code here,
import time
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig = plt.figure()
def animate(i):
x = xtime()
y = [3,4,5,1,4,7,4,7,1,9]
plt.plot(x,y)
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
xtime function is referred as code at first.
Thanks!
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
# Y data
ydata = [3,4,5,1,4,7,4,7,1,9]
# how many points
N = len(ydata)
# make x data
xdata = np.arange(N)
def animate(i):
# update the date in our Line2D artist
# note that when run this will look at the global namespace for
# an object called `ln` which we will define later
ln.set_data(xdata[:i], ydata[:i])
# return the updated artist for the blitting
return ln,
# make our figure and axes
fig, ax = plt.subplots()
# make the artist we will be using. Note this was used in `animate`
ln, = ax.plot([], [], animated=True)
# set the axes limits
ax.set_xlim(0, N)
ax.set_ylim(0, 10)
# run the animation. Keeping a ref to the animation object is important
# as if it gets garbage collected it takes you timer and callbacks with it
ani = animation.FuncAnimation(fig, animate, frames=N, interval=1000, blit=True)
I have two random vectors which are used to create a line plot. Using the same vectors, I would like to animate the line but the animation is static - it just plot the original graph. Any suggestions on how to animate such a line plot?
import numpy as np
import matplotlib.pyplot as py
from matplotlib import animation
# random line plot example
x = np.random.rand(10)
y = np.random.rand(10)
py.figure(3)
py.plot(x, y, lw=2)
py.show()
# animation line plot example
fig = py.figure(4)
ax = py.axes(xlim=(0, 1), ylim=(0, 1))
line, = ax.plot([], [], lw=2)
def init():
line.set_data([], [])
return line,
def animate(i):
line.set_data(x, y)
return line,
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=200, interval=20, blit=False)
The final frame of the animation should look something like the plot below. Keep in mind that this is a random plot so the actual figure will change with each run.
Okay, I think what you want is to only plot up to the i-th index for frame i of the animation. In that case, you can just use the frame number to limit the data displayed:
import numpy as np
import matplotlib.pyplot as py
from matplotlib import animation
x = np.random.rand(10)
y = np.random.rand(10)
# animation line plot example
fig = py.figure(4)
ax = py.axes(xlim=(0, 1), ylim=(0, 1))
line, = ax.plot([], [], lw=2)
def init():
line.set_data([], [])
return line,
def animate(i):
line.set_data(x[:i], y[:i])
return line,
anim = animation.FuncAnimation(fig, animate, init_func=init, frames=len(x)+1,
interval=200, blit=False)
Notice I changed the number of frames to len(x)+1 and increased the interval so it's slow enough to see.