hello,for the sake of concreteness, here is an example without any limit issues : the python script is attached and the 2 resulting figures as well. The dirst one is drawn using log directly in the arguments, and correctly transforming the y-errors into y-errors/y-values/log(10). In the second figure, I use the log scaling in x and y. Clearly something goes wrong with plotting the error bars, and the y-scale limits also seem ill chosen....
HTH debugging this. I looked again at the code, but I am decidedly lost as to where the error bar plotting occurs, and where it gets modified by the log scale request.
Johann Cohen-Tanugi Johann wrote:
hello..... Anyone? I would very much love to see this fixed, and I am ready to help out, but I do not know how to browse through the code. Despite the fact that log(errors) should of course not be used, but rathter errors/values/log(10), Michael's point still remains : values- errors in log scale can be negative, so that the artist should just draw a bar until the lower limit of the vertical bar. I would say that this is the standard practice.Sorry for my previous email beside the point. Johann Cohen-Tanugi Johann wrote:I tried to look at the code (axes.py I presume) in order to attempt a patch, but it defeated me, I do not have the instructions to navigate through this code :)Where is the actual transform of the error bars occurring? thanks, Johann Michael Droettboom wrote:I have to say I don't really have a lot of experience with error bars on log plots -- but the root cause here is that the lower bound of the error bar goes negative, and as we all know, the log of a negative number is undefined. If you can suggest where the lower bound should be drawn or provide third-party examples, I'm happy to look into this further and resolve this "surprise".Mike Cohen-Tanugi Johann wrote:yes exactly.... I should have provided a test case, thanks for following up! Johann Matthias Michler wrote:------------------------------------------------------------------------------Hello Johann,is the problem you are reporting the one I observe in the attached picture? Namely some vertical and horizontal lines are missing when using yscale="log". More precisely everything below y=1 seems to be missing.The picture was generated with the code below and matplotlib.__version__ = '0.98.6svn' matplotlib.__revision__ = '$Revision: 6887 $' best regards Matthias ############################### import numpy as np import matplotlib.pyplot as plt plt.subplot(111, xscale="log", yscale="log") x = 10.0**np.linspace(0.0, 2.0, 20) y = x**2.0 plt.errorbar(x, y, xerr=0.1*x, yerr=5.0+0.75*y) plt.show() ################################ On Friday 27 March 2009 16:12:12 Cohen-Tanugi Johann wrote:Hello, what is the best way to get log log plots with error bars? Itried putting log10() everywhere but as I was afraid results look ugly....thanks, johann------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------_______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users_______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users------------------------------------------------------------------------------_______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
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import pyfits import numpy as np import matplotlib.pylab as plt pwl_gamma=2.2482419 lowE=np.array([ 100., 300., 1000., 3000., 10000.], dtype=np.float32) hiE= np.array([ 300., 1000., 3000., 10000., 100000.], dtype=np.float32) cE=np.sqrt(lowE*hiE) #see https://confluence.slac.stanford.edu/display/SCIGRPS/Source+catalog+format corrE= cE**(2-pwl_gamma) * (pwl_gamma-1.) / (lowE**(1.-pwl_gamma) - hiE**(1.-pwl_gamma)) fluxes=np.array([ 8.12756468e-07, 3.01217426e-07, 7.27334069e-08, 1.19868124e-08, 2.56514854e-09], dtype=np.float32) unc_fluxes=np.array([ 1.15193671e-07, 1.32578517e-08, 3.46157170e-09, 1.13887966e-09, 4.41060244e-10], dtype=np.float32) plt.errorbar(np.log10(cE),np.log10(corrE*fluxes), yerr=unc_fluxes/fluxes/np.log(10)) plt.figure() plt.errorbar(cE,corrE*fluxes, yerr=unc_fluxes) a=plt.gca() a.set_xscale('log') a.set_yscale('log')
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