I am trying to make an animation in 3D using Matplotlib and mpl_toolkits. For starter, I am trying to make an animation of a shifting cos wave. But when I run the program, the plot is completely empty. I have just started learning matplotlib animations, so I don't have in-depth knowledge of it. Here is my code:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import math
import matplotlib.animation as animation
fig = plt.figure()
ax = Axes3D(fig)
line, = ax.plot([],[])
print(line)
X = np.linspace(0, 6*math.pi, 100)
def animate(frame):
line.set_data(X-frame, np.cos(X-frame))
return line
anim = animation.FuncAnimation(fig, animate, frames = 100, interval = 50)
plt.show()
Here is the output:
What is wrong with my code? Why am I not getting any output?
There are two issues with your code:
use set_data_3d to update the data of a Line3D object instead of set_data
initialize the Axes3D scales before starting the animation
This should work:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import math
import matplotlib.animation as animation
fig = plt.figure()
ax = Axes3D(fig)
# initialize scales
ax.set_xlim3d(0, 6 * math.pi)
ax.set_ylim3d(-1, 1)
ax.set_zlim3d(0, 100)
X = np.linspace(0, 6 * math.pi, 100)
line, = ax.plot([], [], [])
def animate(frame):
# update Line3D data
line.set_data_3d(X, np.cos(X - frame), frame)
return line,
anim = animation.FuncAnimation(fig, animate, frames = 20, interval = 50)
plt.show()
and yield an animation like this (I have truncated the number of frames to reduce image file size).
Related
I want to make 3D animation with matplotlib, but I don't know how to. Here is my non-working code.
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import animation
from math import *
fig = plt.figure()
ax = fig.add_subplot(111) #, projection='3d'
#setting
ax.set_xlim(-5,5)
ax.set_ylim(-5,5)
#ax.set_zlim(-5,5)
ax.set_xlabel('x')
ax.set_ylabel('y')
#ax.set_zlabel('z')
ax.grid()
f1, = ax.plot([], [], "r-", lw=1) #plot1
def gen():
for phi in np.linspace(0,2*pi,100):
yield np.cos(phi), np.sin(phi), phi
def update(data):
p1, q1, psi = data
f1.set_data(p1,q1)
#f1.set_3d_properties(psi)
ani = animation.FuncAnimation(fig, update, gen, blit=False, interval=100, repeat=True)
#ani.save('matplot003.gif', writer='imagemagick')
plt.show()
I used this example http://matplotlib.org/1.4.1/examples/animation/simple_3danim.html
and modified your code:
from matplotlib import pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import animation
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
def gen(n):
phi = 0
while phi < 2*np.pi:
yield np.array([np.cos(phi), np.sin(phi), phi])
phi += 2*np.pi/n
def update(num, data, line):
line.set_data(data[:2, :num])
line.set_3d_properties(data[2, :num])
N = 100
data = np.array(list(gen(N))).T
line, = ax.plot(data[0, 0:1], data[1, 0:1], data[2, 0:1])
# Setting the axes properties
ax.set_xlim3d([-1.0, 1.0])
ax.set_xlabel('X')
ax.set_ylim3d([-1.0, 1.0])
ax.set_ylabel('Y')
ax.set_zlim3d([0.0, 10.0])
ax.set_zlabel('Z')
ani = animation.FuncAnimation(fig, update, N, fargs=(data, line), interval=10000/N, blit=False)
#ani.save('matplot003.gif', writer='imagemagick')
plt.show()
Here is the following code for a sphere moving to the right and off the screen.
You will have to run this code in a folder for tidiness, as it generates 26 .png images (and a .gif image):
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from numpy import sin, cos, pi, outer, ones, size, linspace
# Define x, y, z lists for sphere
a = linspace(0, 2 * pi)
b = linspace(0, pi)
x = 10 * outer(cos(a), sin(b))
y = 10 * outer(sin(a), sin(b))
z = 10 * outer(ones(size(a)), cos(b))
# The amount of frames in the animation
frames = 26
# Generate each frame
for n in range(frames):
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(x, y, z, color=('b'))
ax.set_xticks([])
ax.set_yticks([])
ax.set_zticks([])
ax.set_xlim(-8,8)
ax.set_xlim(-8,8)
ax.set_xlim(-8,8)
plt.savefig(f"{n}.png")
plt.close()
# Add 1 to the x so the sphere moves right by 1
x += 1
# Use pillow to save all frames as an animation in a gif file
from PIL import Image
images = [Image.open(f"{n}.png") for n in range(frames)]
images[0].save('ball.gif', save_all=True, append_images=images[1:], duration=100, loop=0)
Output:
I have written the following code with the help of online search. My intention here is to get a real time graph with time on x axis and some randomly generated value on y axis
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import time
import numpy as np
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
xar = []
yar = []
x,y = time.time(), np.random.rand()
xar.append(x)
yar.append(y)
ax1.clear()
ax1.plot(xar,yar)
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
With the above code I just see the range of y axis changing continuously and the graph will not appear in the figure.
The problem is that you never update xvar and yvar. You can do that by moving the definitions of the lists outside the definition of animate.
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import time
import numpy as np
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
xar = []
yar = []
def animate(i):
x,y = time.time(), np.random.rand()
xar.append(x)
yar.append(y)
ax1.clear()
ax1.plot(xar,yar)
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
I wonder if there is some way to plot a waveform point to point at a certain rate through the matplotlib so that the graph appears slowly in the window. Or another method to graph appears at a certain speed in the window and not all the points simultaneously. I've been tried this but I can only plot a section of points at a time
import numpy as np
import matplotlib.pyplot as plt
import time
x = np.arange(0,5,0.001)
y = np.sin(2*np.pi*x)
ind_i = 0
ind_f = 300
while ind_f <= len(x):
xtemp = x[ind_i:ind_f]
ytemp = y[ind_i:ind_f]
plt.hold(True)
plt.plot(xtemp,ytemp)
plt.show()
time.sleep(1)
ind_i = ind_f
ind_f = ind_f + 300
You can also do this with Matplotlib's FuncAnimation function. Adapting one of the matplotlib examples:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
x = np.arange(0,5,0.001)
y = np.sin(2*np.pi*x)
def update_line(num, data, line):
line.set_data(data[..., :num])
return line,
fig = plt.figure()
data = np.vstack((x,y))
l, = plt.plot([], [], 'r-')
plt.xlim(0, 5)
plt.ylim(-1, 1)
line_ani = animation.FuncAnimation(fig, update_line, frames=1000,
fargs=(data, l), interval=20, blit=False)
plt.show()
I'd like to update a matrix text in dynamic by using animation function of matplotlib. But I found that if the data array is too large , the animation will become very very slow. Is there any way to improve it ?
from matplotlib import animation
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots(figsize=(10,20))
def updatefig(i):
plt.cla()
ax.grid()
data = np.random.rand(50,50)
ax.set_xticks(np.arange(data.shape[1]+1))
ax.set_yticks(np.arange(data.shape[0]+1))
for y in range(data.shape[0]):
for x in range(data.shape[1]):
plt.text(x + 0.5 , y + 0.5, '%.1f' % data[y, x],horizontalalignment='center',verticalalignment='center',color='b',size = 6)
plt.draw()
anim = animation.FuncAnimation(fig, updatefig,interval=50)
plt.show()
Actually, I wants to create a heatmmap plot with data values like below link. But use annotations is the only way i could figure out.
Heamap with values
Find a workaround by import seaborn module.
But how to avoid the graph keep flashing
from matplotlib import animation
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
fig, ax = plt.subplots(figsize=(10,20))
sns.set()
def updatefig(i):
plt.clf()
data = np.random.rand(10,10)
sns.heatmap(data, annot=True, linewidths=.5,cbar=False)
anim = animation.FuncAnimation(fig, updatefig,interval=50)
plt.show()
I am trying to do an animation using the FuncAnimation module, but my code only produces one frame and then stops. It seems like it doesn't realize what it needs to update. Can you help me what went wrong?
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
x = np.linspace(0,2*np.pi,100)
def animate(i):
PLOT.set_data(x[i], np.sin(x[i]))
print("test")
return PLOT,
fig = plt.figure()
sub = fig.add_subplot(111, xlim=(x[0], x[-1]), ylim=(-1, 1))
PLOT, = sub.plot([],[])
animation.FuncAnimation(fig, animate, frames=len(x), interval=10, blit=True)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
x = np.linspace(0,2*np.pi,100)
fig = plt.figure()
sub = fig.add_subplot(111, xlim=(x[0], x[-1]), ylim=(-1, 1))
PLOT, = sub.plot([],[])
def animate(i):
PLOT.set_data(x[:i], np.sin(x[:i]))
# print("test")
return PLOT,
ani = animation.FuncAnimation(fig, animate, frames=len(x), interval=10, blit=True)
plt.show()
You need to keep a reference to the animation object around, otherwise it gets garbage collected and it's timer goes away.
There is an open issue to attach a hard-ref to the animation to the underlying Figure object.
As written, your code well only plot a single point which won't be visible, I changed it a bit to draw up to current index