I have found a code here which is plotting real time data using python matplotlib. I want to watch the same visualization in Kibana. So can anyone please tell me how to modify my code to view the same plot in Kibana instead with matplotlib?
import time
import psutil
import matplotlib.pyplot as plt
%matplotlib notebook
plt.rcParams['animation.html'] = 'jshtml'
fig = plt.figure()
ax = fig.add_subplot(111)
fig.show()
i = 0
x, y = [], []
while True:
x.append(i)
y.append(psutil.cpu_percent())
ax.plot(x, y, color='b')
fig.canvas.draw()
ax.set_xlim(left=max(0, i-50), right=i+50)
time.sleep(0.1)
i += 1
plt.close()
Related
When I create an animated graph using matplotlib's FuncAnimation, the axis ticks and labels are blurry when I use Jupyter Notebook, as in this screenshot. This is not the case when I use Python from the console.
Here is a minimal working example that has this problem when I run it from a Jupyter notebook:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
x = np.linspace(0, 4*np.pi, 100)
y = np.sin(x)
fig, ax = plt.subplots()
the_plot, = ax.plot([], []) # Empty array for initialisation
ax.set_xlim(np.min(x), np.max(x))
ax.set_ylim(np.min(y), np.max(y))
def update(i):
the_plot.set_data(x[:i+1], y[:i+1])
anim = animation.FuncAnimation(fig, update, range(len(x)), save_count=len(x))
anim.save('Out.mp4', fps=25, writer='ffmpeg')
I am trying a code to plot a live graph but i always land up with an empty plot. Here is my code :
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib import style
import random
style.use('fivethirtyeight')
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
y = random.randint(0,100) # generate random data
x = i # set x as iteration number
ax1.clear()
ax1.plot(x, y, 'ro')
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()
I get warning but i am using plt.show() to show animation. Not sure what i am doing wrong :
UserWarning: Animation was deleted without rendering anything. This is most likely not intended. To prevent deletion, assign the Animation to a variable, e.g. `anim`, that exists until you have outputted the Animation using `plt.show()` or `anim.save()`.
warnings.warn(
community,
I tried to create the 3d scatter by using matplotlib Axes3D on jupyter notebook.
However, it is not showing the image once I execute 'plt.show()'.
#pip install matplotlib
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
%matplotlib inline
fig = plt.figure()
ax =fig.add_subplot(111, projection = '3d')
x = dframe['CTR']
y = dframe['Clicks']
z = dframe['Avg. CPC']
ax.scatter(x, y, z, c='r', marker='o')
plt.show()
Your code works fine like this:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
# dummy data (your actual data should go here)
x = [1, 2, 3, 4]
y = x
z = x
ax.scatter(x, y, z, c="r", marker="o")
plt.show()
This shows:
May be something is wrong with your data. Also, since you are using plt.show() anyway, you can remove the %matplotlib inline line.
I would essentially like to do the following:
import matplotlib.pyplot as plt
import numpy as np
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
for i in range(10):
ax1.scatter(i, np.sqrt(i))
ax1.show() # something equivalent to this
ax2.scatter(i, i**2)
That is, each time a point is plotted on ax1, it is shown - ax2 being shown once.
You cannot show an axes alone. An axes is always part of a figure. For animations you would want to use an interactive backend. Then the code in a jupyter notebook could look like
%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
frames = 10
x = np.arange(frames)
line1, = ax1.plot([],[], ls="", marker="o")
line2, = ax2.plot(x, x**2, ls="", marker="o")
ax2.set_visible(False)
def animate(i):
line1.set_data(x[:i], np.sqrt(x[:i]))
ax1.set_title(f"{i}")
ax1.relim()
ax1.autoscale_view()
if i==frames-1:
ax2.set_visible(True)
fig2.canvas.draw_idle()
ani = FuncAnimation(fig1, animate, frames=frames, repeat=False)
plt.show()
If you want to change plots dynamically I'd suggest you don't redraw the whole plot every time, this will result in very laggy behavior. Instead you could use Blit to do this. I used it in a previous project. Maybe it can help you too if you just take the parts from this you need:
Python project dynamically updating plot
I'm trying to create an animated map plot using smopy and matplotlib in jupyter, but when I run the code I get two figures instead of one. The first figure is shown above the map and empty. Can anyone tell me how to fix this so that only the animation is drawn?
import smopy
import matplotlib.animation as animation
n= 1000
%matplotlib notebook
def update(curr):
if curr == n-100:
a.event_source.stop()
lons = crime_df.X[curr:curr+100]
lats = crime_df.Y[curr:curr+100]
x,y = map.to_pixels(lats,lons)
ax.scatter(x, y, c='r', alpha=0.7, s=200)
plt.title(curr)
fig = plt.figure()
ax = smopy.Map((37.6624,-122.5168,37.8231,-122.3589), z=12)
ax = ax.show_mpl(figsize=(8,8))
a = animation.FuncAnimation(fig, update, interval=100)
You should not create an additional figure, if that is undersired: Leave out plt.figure().
import smopy
import matplotlib.pyplot as plt
import matplotlib.animation as animation
n= 1000
%matplotlib notebook
def update(curr):
if curr == n-100:
a.event_source.stop()
lons = crime_df.X[curr:curr+100]
lats = crime_df.Y[curr:curr+100]
x,y = map.to_pixels(lats,lons)
ax.scatter(x, y, c='r', alpha=0.7, s=200)
plt.title(curr)
m = smopy.Map((37.6624,-122.5168,37.8231,-122.3589), z=12)
ax = m.show_mpl(figsize=(8,8))
a = animation.FuncAnimation(ax.figure, update, interval=100)
Alternatively create the figure beforehands,
fig, ax = plt.subplots(figsize=(8,8))
m = smopy.Map((37.6624,-122.5168,37.8231,-122.3589), z=12)
m.show_mpl(ax = ax)
a = animation.FuncAnimation(fig, update, interval=100)