On 6/8/07, Trevis Crane <[EMAIL PROTECTED]> wrote:
Hi all,
I have a plot of data that I am enabling the user to interact with. That
is, I want them to be able to pick a point, and then have a new plot pop up
in a different figure showing more info about that point.
Here is an example that I just committed to svn as examples/pick_event_demo2.py
It made me realize that despite all my protestations not to repeatedly
call show, we do not have a backend dependent way to raise new figures
created in mpl callbacks. Since we've mostly made show bullet-proof
to repeated calls (because we don't restart the mainloops) this works,
but we do need a backend independent way to raise figures.
One approach would be to have the figure creation function (eg in the
backend) attach a method show() that raises the figure when called, eg
fig.show()
In any case, here is the example code, also attached in case the lines
get wrapped
"""
compute the mean and stddev of 100 data sets and plot mean vs stddev.
When you click on one of the mu, sigma points, plot the raw data from
the dataset that generated the mean and stddev
"""
import numpy
from pylab import figure, show
X = numpy.random.rand(100, 1000)
xs = numpy.mean(X, axis=1)
ys = numpy.std(X, axis=1)
fig = figure()
ax = fig.add_subplot(111)
ax.set_title('click on point to plot time series')
line, = ax.plot(xs, ys, 'o', picker=5) # 5 points tolerance
def onpick1(event):
if event.artist!=line: return True
N = len(event.ind)
if not N: return True
figi = figure()
for subplotnum, dataind in enumerate(event.ind):
ax = figi.add_subplot(N,1,subplotnum+1)
ax.plot(X[dataind])
ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f'%(xs[dataind], ys[dataind]),
transform=ax.transAxes, va='top')
ax.set_ylim(-0.5, 1.5)
ax.figure.canvas.draw()
print 'plotted'
show() # oops, we need a way to raise figures created in callbacks
return True
fig.canvas.mpl_connect('pick_event', onpick1)
show()
"""
compute the mean and stddev of 100 data sets and plot mean vs stddev.
When you click on one of the mu, sigma points, plot the raw data from
the dataset that generated the mean and stddev
"""
import numpy
from pylab import figure, show
X = numpy.random.rand(100, 1000)
xs = numpy.mean(X, axis=1)
ys = numpy.std(X, axis=1)
fig = figure()
ax = fig.add_subplot(111)
ax.set_title('click on point to plot time series')
line, = ax.plot(xs, ys, 'o', picker=5) # 5 points tolerance
def onpick1(event):
if event.artist!=line: return True
N = len(event.ind)
if not N: return True
figi = figure()
for subplotnum, dataind in enumerate(event.ind):
ax = figi.add_subplot(N,1,subplotnum+1)
ax.plot(X[dataind])
ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f'%(xs[dataind], ys[dataind]),
transform=ax.transAxes, va='top')
ax.set_ylim(-0.5, 1.5)
ax.figure.canvas.draw()
print 'plotted'
show() # oops, we need a way to raise figures created in callbacks
return True
fig.canvas.mpl_connect('pick_event', onpick1)
show()
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