Hello.
I'm searching for a method to show a stream of data on a graph. So far
I've only managed to get the stream on a regular graph but the data
bandwidth is very high (100 samples/sec) and the usual graph doesn't
handle redrawing so good.
I was searching for a way to utilize the animation functionality of
matplotlib but found only some Tk examples (with very smooth refresh
rate).
But I couldn't modify the source to create the same effect using the Gtk
+ front-end. The problem is that I don't know how to integrate the graph
into the Glib main loop.
Please help.
This is an example I found o the net:
----------------------------------------------------------
import matplotlib
matplotlib.use('TkAgg') # do this before importing pylab
import matplotlib.pyplot as plt
import random
fig = plt.figure()
ax = fig.add_subplot(111)
x = range(30)
y = [random.random() for i in x]
line, = ax.plot(x,y)
def animate(*args):
n = len(y)
while True:
data = random.random()
y.append(data)
n += 1
line.set_data(range(n-30, n), y[-30:])
ax.set_xlim(n-31, n-1)
fig.canvas.draw()
fig.canvas.manager.window.after(100, animate)
plt.show()
----------------------------------------------------------
------------------------------------------------------------------------------
All the data continuously generated in your IT infrastructure
contains a definitive record of customers, application performance,
security threats, fraudulent activity, and more. Splunk takes this
data and makes sense of it. IT sense. And common sense.
http://p.sf.net/sfu/splunk-novd2d
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
