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From: Christopher Kang <chris.83@gm...>  20050707 12:04:18

Hello everyone and always, thank you for your tremendous help. I was just wondering, I need to get matplotlib to work on a mac but unfortunately I've been running into some problems trying to get it to work on a mac. I tried by installing the unstable version from source using fink and that has some parts of matplotlib working fine, but I can't seem to import pylab. Specifically, when matplotlib tries to import pylab (from pylab import *), it eventually gets to ""from matplotlib._nc_backend_gdk import pixbuf_get_pixels_array" ImportError: No module named _nc_backend_gdk.". It seems like i don't have a _nc_backend_gdk.so file that I need. Could someone please assist me in what I need to do or let me know of a different way to get matplotlib and gtk/gtkagg to work on my mac?=20 I'm running Tiger on the mac. Thank you very much, Chris 
From: Chris Barker <Chris.B<arker@no...>  20050707 17:16:10

Christopher Kang wrote: > Could someone please assist me in what I need to do or let me know of > a different way to get matplotlib and gtk/gtkagg to work on my mac? > I'm running Tiger on the mac. Do you really need GTK? If not, you can use the installer at: http://www.pythonmac.org/packages It should work with TK, wx and Agg. I've heard someone is working on a Cocoa backend which would be great, but it's not available now. If you do need GTK, then you need to go the allfink route: everything fink, including python itself, gtk, pygtk, etc. Maybe whoever is maintaining the fink package can help out with your problems. Chris  Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 5266959 voice 7600 Sand Point Way NE (206) 5266329 fax Seattle, WA 98115 (206) 5266317 main reception Chris.Barker@... 
From: Graeme O'Keefe <gjok@ne...>  20050714 05:31:56

Hi, I know this really belongs on the sourceforge.net:numarray list, but it is a very inactive list. I have noted the following with numarray: >>> x = numarray.zeros([3,3], numarray.Int16) >>> i = [0,1,2,0,1,2] >>> j = [0,1,2,0,1,2] >>> x[i, j] += 1 >>> print x [[1, 0, 0] [0, 1, 0] [0, 0, 1]] I was expecting (hoping) [[2, 0, 0] [0, 2, 0] [0, 0, 2]] which is what you obviously get if you: for n in range(len(i)) : x[i[n], j[n]] += 1 This is the sort of operation one does all the time when histogramming datastreams. Is there a way to achieve this without looping over i/j. cheers, Graeme 
From: Robert Kern <rkern@uc...>  20050714 06:23:48

Graeme O'Keefe wrote: > Hi, > > I know this really belongs on the sourceforge.net:numarray list, but it > is a very inactive list. It's still the right place to ask. Your question would get answered in a timely manner. We're quiet; we're not gone. :) Followupto has been reset. > I have noted the following with numarray: > > >>> x = numarray.zeros([3,3], numarray.Int16) > >>> i = [0,1,2,0,1,2] > >>> j = [0,1,2,0,1,2] > >>> x[i, j] += 1 > >>> print x > [[1, 0, 0] > [0, 1, 0] > [0, 0, 1]] > I was expecting (hoping) > [[2, 0, 0] > [0, 2, 0] > [0, 0, 2]] > > which is what you obviously get if you: > > for n in range(len(i)) : x[i[n], j[n]] += 1 > > This is the sort of operation one does all the time when histogramming > datastreams. Is there a way to achieve this without looping over i/j. This has been discussed recently on the numpydiscussion list (Subject: vectorizing histogramlike computation). The semantics of array indexing aren't anything like that for loop. I doubt that the two kinds of semantics could be merged consistently. x[i,j] += 1 is closer to x[i,j] = x[i,j] + 1 which amounts, in this case, to x[i,j] = array([1, 1, 1, 1, 1, 1]) There's nothing in this last operation to suggest that the numbers ought to be added together (and if the initial values weren't zero, a more complicated operation would have to considered). In short, I consider it cleaner to keep specialized histogram code tucked away in a function which you can eventually optimize to C as required.  Robert Kern rkern@... "In the fields of hell where the grass grows high Are the graves of dreams allowed to die."  Richard Harter 
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