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From: Ken McIvor <mcivor@ii...>  20090221 21:19:47

I've finally been able to update the WxMpl library so it's compatible with MPL 0.98: http://agni.phys.iit.edu/~kmcivor/wxmpl/downloads/wxmpl1.3.0.tar.gz It's been tested on Debian Lenny (Python 2.5.2, MPL 0.98.1, wxPython 2.6.3.2) and Mac OS 10.5.5 (MacPython 2.5.4, MPL 0.98.1 and 0.98.6svn, wxPython 2.8.9.1). Please let me know if you encounter any problems. My thanks to everyone for the patches and feedback, and for being so patient. Ken 
From: Eric Firing <efiring@ha...>  20090221 19:34:22

Thomas Robitaille wrote: > Hello, > > I am using matplotlib to show an image using: > > fig = figure() > ax = fig.add_subplot(111) > ax.imshow(image) > > After doing this, I want to find the contours for a different image > (with different dimensions), but I do not want to interact with the > current figure or axes, I just want to retrieve the set of > LineCollection objects for the contours. The issue is that if I do > > c = contour(image2) > > the contours are stored inside c, but at the same time they are plotted > in the current figure. If I use > > ax.contour(image2) > > then the contours are not plotted immediately, but the view interval has > already been changed inside ax. The workaround for now may be to call ax.set_autoscale_on(False) before your call to ax.contour. You could also save the datalim before and restore them afterwards. This sort of request has come up before, though, and the longerterm solution might be some refactoring in contour.py. As it is, everything is done when the ContourSet is instantiated; one does not have the option of simply calculating the contours, for example. Eric > > So essentially, I am wondering if it is possible to retrieve a set of > LineCollection objects without acting in any way on the current figure/axes. > > Thanks for any help, > > Thomas > >  > Open Source Business Conference (OSBC), March 2425, 2009, San Francisco, CA > OSBC tackles the biggest issue in open source: Open Sourcing the Enterprise > Strategies to boost innovation and cut costs with open source participation > Receive a $600 discount off the registration fee with the source code: SFAD > http://p.sf.net/sfu/XcvMzF8H > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers 
From: Thomas Robitaille <thomas.robitaille@gm...>  20090221 14:00:47

Hello, I am using matplotlib to show an image using: fig = figure() ax = fig.add_subplot(111) ax.imshow(image) After doing this, I want to find the contours for a different image (with different dimensions), but I do not want to interact with the current figure or axes, I just want to retrieve the set of LineCollection objects for the contours. The issue is that if I do c = contour(image2) the contours are stored inside c, but at the same time they are plotted in the current figure. If I use ax.contour(image2) then the contours are not plotted immediately, but the view interval has already been changed inside ax. So essentially, I am wondering if it is possible to retrieve a set of LineCollection objects without acting in any way on the current figure/axes. Thanks for any help, Thomas 
From: Nils Wagner <nwagner@ia...>  20090221 10:22:04

Hi all, I have written a small program for optimization of truss structures. The design variables are the cross sectional areas of the truss elements (attached figure). One way to visualize the results is to use the linewidth as a parameter. Is it also possible to use different ("continuous") colors corresponding to the values of the design variables ? Any pointer would be appreciated. Thanks in advance. Nils Postprocessing from scipy import io, set_printoptions from numpy import zeros, arange, outer, identity, loadtxt, ones, shape, dot, r_, where, min, max set_printoptions(precision=4,linewidth=150) from pylab import spy, show, plot, subplot, figure, imshow, scatter, title, text, annotate, xlabel, ylabel, savefig from scipy.linalg import eigh, norm, solve # # Visualization of the # results of a sizing optimization problem # N = 45 # Number of nodes nele = 136 # Number of elements coord = loadtxt('coord.inp',comments='#',usecols=(1,2)).astype(float) inz = loadtxt('connect.inp',comments='#',usecols=(1,2)).astype(int) cross = loadtxt('crossopt.dat') cross_max = max(cross) cross_min = min(cross) a = 1.9/(cross_maxcross_min) b = 2.a*cross_max def model(cross): """ Model plot """ scatter(coord[:,0],coord[:,1]) title('Plane truss structure') for iele in arange(0,nele): p_j = coord[inz[iele,1]1] p_i = coord[inz[iele,0]1] linewidth = a*cross[iele]+b print iele, linewidth plot (r_[p_i[0],p_j[0]],r_[p_i[1],p_j[1]],'r',lw=linewidth) xlabel('$x$') ylabel('$y$') model(cross) savefig('truss') show() 
From: C M <cmpython@gm...>  20090221 09:15:12

Hi, I have two picking questions. First, If I do this inside a pick handler function: def OnPick(self, event): if isinstance(event.artist, Line2D): thisline = event.artist xdata = thisline.get_xdata() ydata = thisline.get_ydata() I can grab the data from a line. Fine. Now I'd like to do two things: 1) WIthin this same pick handler function, have another if conditional, but for the case when the user is picking the legend. In other words, I want to pick the legend artist, not a Line2D artist. 2) Modify the above so the user can pick only the actual points on a line, but not the connecting line if I have plotted it like 'o' style (connected points). I hope this is clear. Any help is appreciated. Thanks. Che 
From: Eric Firing <efiring@ha...>  20090221 01:07:16

Jeff Whitaker wrote: > Armin Moser wrote: >> Jeff Whitaker wrote: >> >>> Armin Moser wrote: >>> >>>> Hi, >>>> >>>> I would like to interpolate an array of shape (801,676) to regularily >>>> spaced datapoints using griddata. This interpolation is quick if the >>>> (x,y) supporting points are computed as X,Y = meshgrid(x,y). If this >>>> condition is not fullfilled the delaunay triangulation is extremely >>>> slow, i.e. not useable. Is this a known property of the used >>>> triangulation? The triangulation can be performed with matlab without >>>> any problems. >>>> >>>> Armin >>>> >>>> >>> Armin: You could try installing the natgrid toolkit and see if that >>> speeds up griddata at all. If not, please post a test script with data >>> and maybe we can figure out what is going on. >>> >> I have already tried natgrid and it didn't improve the situation. As >> suggested I append a script demonstrating the problem. Reducing the original grid from 676x801 to 100x120, I get benchmarks of about 6 seconds with natgrid and 0.15 s with Robert's delaunay. This seems quite repeatable. I also tried randomizing x and y in the first benchmark with natgrid, and it made only a slight difference. Eric >> >> Thanks >> Armin >> > > Armin: On my mac, your two benchmarks take 15 and 14 seconds. Do you > consider that too slow? > > Perhaps this is just a toy example to test griddata, but I assume you > realize that you wouldn't normally use griddata to interpolate data on > one regular grid to another regular grid. griddata is strictly for > interpolating scatter data (not on a regular mesh) to a regular mesh. > > Jeff >> 8< >> from numpy import * >> from pylab import * >> import time >> >> deg2rad = pi/180.0 >> ai = 0.12*deg2rad >> x = linspace(13,40,676) >> y = linspace(10,22,801) >> >> x = x*deg2rad >> y = y*deg2rad >> [x,y] = meshgrid(x,y) >> z = (x**2+y**2) >> >> xi = linspace(x.min(),x.max(),x.shape[1]) >> yi = linspace(y.min(),y.max(),y.shape[0]) >> tic= time.time() >> zi = griddata(x.flatten(),y.flatten(),z.flatten(),xi,yi) >> toc = time.time() >> print toctic >> >> fac = 2*pi/1.2681 >> nx = fac * (cos(y)*cos(x)  cos(ai)) >> ny = fac * (cos(y)*sin(x)) >> nz = fac * (sin(y) + sin(ai)) >> np = sqrt(nx**2 + ny**2) >> >> z = (np**2+nz**2)*exp(0.001*nz) >> >> xi = linspace(np.min(),np.max(),x.shape[1]) >> yi = linspace(nz.min(),nz.max(),y.shape[0]) >> tic = time.time() >> zi = griddata(np.flatten(),nz.flatten(),z.flatten(),xi,yi) >> toc = time.time() >> print toctic >> > > 