Re: [Matplotlib-users] incremental colors for lines
Hi, I like this, too. However, I don't understand why it works at all. Usually, when I apply a colormap, I need to take care about the scaling myself, i.e. divide the range up into the number of elements to plot: import pylab as pl import matplotlib.cm as cm xval = pl.arange(0, 20, 0.2) n = 256 for i in range(n): # pl.plot(xval, pl.sin(xval)+i, c=cm.hot(i), lw=5) pl.plot(xval, pl.sin(xval)+i, c=cm.hot(1.*i/n), lw=5) Can anyone tell me why this is not necessary here but essential for example here: for i,infile in enumerate(infiles): ## title for plot tname = os.path.splitext(infile)[0] ## read data f = FileHelpers.BlockedFile(infile) alldata = scipy.array([[],[]]) for ii in ['+', '2', 'x', '1']: # use for markers, too #for ii in [4,3,2,1]: # use for markers, too try: f.next_block() data = scipy.loadtxt(f).T alldata = scipy.concatenate((alldata, data), axis=1) #ax.plot(data[0],data[1], '%s'%ii, color=cm.hot(1.*i/len(infiles)), mew=1.5 ) ax.plot(data[0],data[1], '%s'%ii, c=cm.hot(i), mew=1.5 ) except Exception, e: print e break Thanks in advance, Daniel I have found a simple and better way. One can chose from colors from a color map: import pylab as pl import matplotlib.cm as cm xval = pl.arange(0, 20, 0.2) for i in range(256): ... pl.plot(xval, pl.sin(xval)+i, c=cm.hot(i), lw=5) This one if, for instance, picking from a color map called hot. If one wants to the colors to fade away, or darken, the alpha option can be utilized or another color map in which colors darken or fade into another color. There is no need for a long sophisticated script. -- Achieve unprecedented app performance and reliability What every C/C++ and Fortran developer should know. Learn how Intel has extended the reach of its next-generation tools to help boost performance applications - inlcuding clusters. http://p.sf.net/sfu/intel-dev2devmay ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] imshow in Axes3D?
Hi, I would like to create a plot with a series of parallel 2-D slices in order to illustrate 3-D data. I got excited when I saw the example of translucent bar plots, which is similiar in some ways to what I had in mind. But it seems that there is no imshow method in Axes3D. How hard would that be to add? (By the way, I do know about mayavi and have used it, but there are things about it that make it somewhat difficult to work with.) Jon -- __ Jonathan D. Slavin Harvard-Smithsonian CfA jsla...@cfa.harvard.edu 60 Garden Street, MS 83 phone: (617) 496-7981 Cambridge, MA 02138-1516 cell: (781) 363-0035 USA __ -- Achieve unprecedented app performance and reliability What every C/C++ and Fortran developer should know. Learn how Intel has extended the reach of its next-generation tools to help boost performance applications - inlcuding clusters. http://p.sf.net/sfu/intel-dev2devmay ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] imshow in Axes3D?
On Tue, May 10, 2011 at 9:25 AM, Jonathan Slavin jsla...@cfa.harvard.eduwrote: Hi, I would like to create a plot with a series of parallel 2-D slices in order to illustrate 3-D data. I got excited when I saw the example of translucent bar plots, which is similiar in some ways to what I had in mind. But it seems that there is no imshow method in Axes3D. How hard would that be to add? (By the way, I do know about mayavi and have used it, but there are things about it that make it somewhat difficult to work with.) Jon imshow() and friends work a little bit differently from the other plotting commands. Unlike the other plotting functions, imshow() does not return any Collection objects, rather it returns an AxesImage object. Most of the other functions are merely wrappers around their 2D equivalent with a few extra keyword arguments and a 2D to 3D converter call for the collection objects returned. In order to support imshow() in Axes3D, a 3D version of the AxesImage object will need to be made and should be able to be created from an existing 2D version. If someone wants to create a 3D version of AxesImage and add it to art3d.py, I would be more than happy to take the patch. But at this time, I am too unfamiliar with AxesImage objects and am more focused on fixing the current feature-set. Ben Root -- Achieve unprecedented app performance and reliability What every C/C++ and Fortran developer should know. Learn how Intel has extended the reach of its next-generation tools to help boost performance applications - inlcuding clusters. http://p.sf.net/sfu/intel-dev2devmay___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Feature request: automatic scaling of subplots, margins, etc
On Fri, May 6, 2011 at 5:20 PM, Daniel Mader danielstefanma...@googlemail.com wrote: From many postings here I have learned that this is the absolute intention, i.e. it is broken by design unless the programmer takes care about this. I think there are pros and cons, and I don't think the current design is simply broken. For example, it will be very distracting if the axes area changes while you're doing some interactive stuff (e.g., panning). Anyhow I admit that the default layout may not be optimal for figures with multiple subplots, and there is a room for improvement. There are a few approach you can take. * If you're only interested in saved outputs, you may use savefig with bbox_inches=tight. Note that this changes the size of figure. * Use Tony's script to adjust the subplot params automatically. * use axes_grid1 toolkit which enables you to change the axes position on the fly. Check http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg18743.html. For current git master branch, check examples/axes_grid/make_room_for_ylabel_using_axesgrid.py Regards, -JJ -- Achieve unprecedented app performance and reliability What every C/C++ and Fortran developer should know. Learn how Intel has extended the reach of its next-generation tools to help boost performance applications - inlcuding clusters. http://p.sf.net/sfu/intel-dev2devmay ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
