Re: [Matplotlib-users] How to close a plot?

[Wayne W. <sie...@sb...>]

Thanks. That could be a very useful observation. I'm doing most of this 
on a win7 machine. When I installed MPL, I had two small dialogs appear 
that said something was missing, but I pressed on. MPL seemed to 
generally work except for the show() problem. I'm in the process of 
bringing programs from my XP to the win7 machine, and on the XP machine 
I decided to start using MPL with a 900 line Py program that I'm 
revising. I had gotten stuck with the very same problem there. However, 
last night I realized someone had added a MPL plot to it years ago, and 
it does not fail on show().

I noticed the msgs mentioned, and though I mad made a mistake in not 
installing numpy first, so tried to figure out a way to do it. Three 
posts on different forums did not provide an answer. I accidentally 
founnd the author of MPL's hidden away in one of MPL files. He said it 
didn't make a difference and asked me not to use his address. I though 
the warning msgs might be of interest to him, so wrote to him. He had 
blocked me. Perhaps I need to file a bug report to get his attention on 
that.

Anyway, I'm now stalled on the development of the big program. It's 
possible this is an IDLE problem, but I ran the big program with a click 
on the file, and the black window showed the same problem. It did show 
some other warnings, which I think I'll capture with Snagit. This is all 
on XP Pro.

I'm going to copy the two code segments here. Maybe you can see a 
difference. I'll also attach the capture of the window too. Two jpg 
files are attached for the same code below, and one for the error 
messages from the console XP.

=================OLD working code============
     def light_curve( self ):
         result = []
         test = 1
         for tup in self.subimages:
             left,top,subimage = tup
             total = 0
             avg_total = 0
             if (test == 1):
                 box = (left, top, left+128, top+128)
                 region = self.reference_image.crop(box)
                 self.reference_image.paste(subimage, box)
                 test = 2
             else:
                 for x in range(left+43,left+82):
                     for y in range(top+43, top+82):
                         avg_total = avg_total + 
self.reference_image.getpixel((x, y))
                 for x in range(43,82): #take the center 40 X 40 pixel block
                     for y in range(43,82):
                         v = subimage.getpixel((x, y))
                         total = total + v
                 #for x in range(left, left+127):
                 #    for y in range(top, top+127):
                 #        avg_total = avg_total + 
self.reference_image.getpixel((x, y))
                 #for x in range(0, 127):
                 #    for y in range(0, 127):
                 #        total = total + subimage.getpixel((x, y))
                 result.append(total - avg_total) #(average - background 
average) gives pixel intensity above the background)
         plotting_x = range(2, len(result)+2)
         plot(plotting_x, result)
         xlabel('Frame #')
         ylabel('Pixel count above background count')
         title('Light curve for selected subplot')
         show()

===========New Code with show problem
     def get_point_trail_stats(self): # Simple track statistics
         xy = array(self.xya)[:,0:2]  # creates a two column array for x,y
         pt2pt_dist = []
         pt_dist = []
         for k in arange(0,len(xy)-1):
             distance = sqrt((xy[k+1,0]-xy[k,0])**2 + 
(xy[k+1,1]-xy[k,1])**2)
             pt_dist.append(distance)
             # wtw print "k ",k, (xy[k,0], xy[k,1]), " distance: ", distance
         # wtwfor k in arange(0, len(xy)-50):
         # wtw    print "k: %3i dist: %6.2f (x,y) (%4.1f,%4.1f)" % (k, 
pt_dist[k], xy[k,0], xy[k,1])
         per_tile25 = stats.scoreatpercentile(pt_dist,25.0)
         per_tile50 = stats.scoreatpercentile(pt_dist,50.0)
         per_tile75 = stats.scoreatpercentile(pt_dist,75.0)
         mean       = stats.mean(pt_dist)
         std        = stats.std(pt_dist)
         #sys.exit()
         amin       = min(pt_dist)
         amax       = max(pt_dist)
         print "   mean: %7.2f std: %7.2f min: %7.2f max: %7.2f" % 
(mean, std, amin, amax)
         print "   quartiles (25-per: %7.2f, 50-per: %7.2f, 75-per: 
%7.2f): " % (per_tile25, per_tile50, per_tile75)
         #print "           Extended stats"
         #print "   min: %7.2f max: %7.2f mean: %7.2f std: %7.2f" % \
         #    (min, max, mean, std)
         #print "   p25: %7.2f p50: %7.2f p75: %7.2f" % (per_tile25, 
per_tile50, per_tile75)
         trk_stats = (amin, amax, mean, std, per_tile25, per_tile50, 
per_tile75)
         fig = figure()
         ax1 = fig.add_subplot(111)
         v = (0, 640, 0, 480)
         print "shapes: ", xy[:,0].shape, xy[:,1].shape
         fig.close()
         ax1.plot(xy[:,0], xy[:,1]) #,100*s, c , picker=True)
         ax1.axis(v)
         #x = (0,1,3,20,20);y=(5,7, 9, 22,90)
         #col = ax1.plot(x,y)
         show()

         print "something for wtw plot"
         print
         return trk_stats

On 2/7/2010 10:53 PM, Philipp Bender wrote:
> I'm pretty sure your problem is not generally related to matplotlib, all the
> examples you mentioned and the one you sent me by e-mail worked for me. Maybe
> you try a different version or a different operating system for your scripts.
>
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