Re: [Matplotlib-users] (no subject)
Le 05/09/2014 21:53, Arnaldo Russo a écrit : The following code plots my table, but greek letters are not in Arial. What about adding greek letters directly with a Unicode string and keeping LaTex only for the table? best, Pierre (my greek and math unicode copy-pasting files attached) Table de caractères grecs à copier-coller - α . β . γ Γ δ Δ ε . ζ . η . θ Θ . . κ . λ Λ μ . ν . ξ Ξ . . π Π ρ . ς . σ Σ τ . υ . φ Φ (et aussi ϕ en U+03d5) χ . ψ Ψ ω Ω Pierre H - 8 fév 2012 MàJ septembre 2012 pour le ϕ mathématique Code Python : l = [unichr(a)+u' '+unichr(b) for a,b in zip(range(0x3b1, 0x3ca), range(0x391,0x3aa)) ] print(u'\n'.join(l)) Table de caractères matheux à copier-coller --- Arithmetic -- plus-minus ± multiplication × division÷ power ² ³ root√ ∛ infinity∞ Operators - integrals and sum ∫ ∬ ∑ partial diff. ∂ increment, Laplace ∆ (different from Greek delta : Δ) nabla ∇ expectation 피 ⟨⟩ probability ℙ norm‖ Relationships - equality= ≈ ≠ ≡ inequality≤ ≥ ⩽ ⩾ proportional to ∝ element of ∈ ∉ subset of ⊂ ⊄ quantifiers ∀ ∃ ∄ Sets integersℕ ℤ 퓝 퓩 real numbersℝ 퓡 complex numbers ℂ 퓒 empty set ∅ Arrows -- arrows : → ⟶ ⇒ maps to : ↦ ⟼ -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Plotting large file (NetCDF)
Hi, I'm working with NetCDF format. When I try to make a plot of very large file, I have to wait for a long time for plotting. How can I solve this? Isn't there a solution for this problem? Raffaele -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Plotting large file (NetCDF)
You will need to be more specific... much more specific. What kind of plot are you making? How big is your data? What version of matplotlib are you using? How much RAM do you have available compared to the amount of data (most slowdowns are actually due to swap-thrashing issues). Matplotlib can be used for large data, but there exists some speciality tools for the truly large datasets. The solution depends on the situation. Ben Root On Mon, Sep 8, 2014 at 7:45 AM, Raffaele Quarta raffaele.qua...@linksmt.it wrote: Hi, I'm working with NetCDF format. When I try to make a plot of very large file, I have to wait for a long time for plotting. How can I solve this? Isn't there a solution for this problem? Raffaele -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Plotting large file (NetCDF)
(Keeping this on the mailing list so that others can benefit) What might be happening is that you are keeping around too many numpy arrays in memory than you actually need. Take advantage of memmapping, which most netcdf tools provide by default. This keeps the data on disk rather than in RAM. Second, for very large images, I would suggest either pcolormesh() or just simply imshow() instead of pcolor() as they are more way more efficient than pcolor(). In addition, it sounds like you are dealing with re-sampled data (at different zoom levels). Does this mean that you are re-running contour on re-sampled data? I am not sure what the benefit of doing that is if one could just simply do the contour once at the highest resolution. Without seeing any code, though, I can only provide generic suggestions. Cheers! Ben Root On Mon, Sep 8, 2014 at 10:12 AM, Raffaele Quarta raffaele.qua...@linksmt.it wrote: Hi Ben, sorry for the few details that I gave to you. I'm trying to make a contour plot of a variable at different zoom levels by using high resolution data. The aim is to obtain .PNG output images. Actually, I'm working with big data (NetCDF file, dimension is about 75Mb). The current Matplotlib version on my UBUNTU 14.04 machine is the 1.3.1 one. My system has a RAM capacity of 8Gb. Actually, I'm dealing with memory system problems when I try to make a plot. I got the error message as follow: cs = m.pcolor(xi,yi,np.squeeze(t)) File /usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py, line 521, in with_transform return plotfunc(self,x,y,data,*args,**kwargs) File /usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py, line 3375, in pcolor x = ma.masked_values(np.where(x 1.e20,1.e20,x), 1.e20) File /usr/lib/python2.7/dist-packages/numpy/ma/core.py, line 2195, in masked_values condition = umath.less_equal(mabs(xnew - value), atol + rtol * mabs(value)) MemoryError Otherwise, when I try to make a plot of smaller file (such as 5Mb), it works very well. I believe that it's not something of wrong in the script. It might be a memory system problem. I hope that my message is more clear now. Thanks for the help. Regards, Raffaele - Sent: Mon 9/8/2014 3:19 PM To: Raffaele Quarta Cc: Matplotlib Users Subject: Re: [Matplotlib-users] Plotting large file (NetCDF) You will need to be more specific... much more specific. What kind of plot are you making? How big is your data? What version of matplotlib are you using? How much RAM do you have available compared to the amount of data (most slowdowns are actually due to swap-thrashing issues). Matplotlib can be used for large data, but there exists some speciality tools for the truly large datasets. The solution depends on the situation. Ben Root On Mon, Sep 8, 2014 at 7:45 AM, Raffaele Quarta raffaele.qua...@linksmt.it wrote: Hi, I'm working with NetCDF format. When I try to make a plot of very large file, I have to wait for a long time for plotting. How can I solve this? Isn't there a solution for this problem? Raffaele -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Plotting large file (NetCDF)
It looks like you are calling `pcolor`. Can I suggest you try `pcolormesh`? 75 Mb is not a big file! Cheers, Jody On Sep 8, 2014, at 7:38 AM, Benjamin Root ben.r...@ou.edu wrote: (Keeping this on the mailing list so that others can benefit) What might be happening is that you are keeping around too many numpy arrays in memory than you actually need. Take advantage of memmapping, which most netcdf tools provide by default. This keeps the data on disk rather than in RAM. Second, for very large images, I would suggest either pcolormesh() or just simply imshow() instead of pcolor() as they are more way more efficient than pcolor(). In addition, it sounds like you are dealing with re-sampled data (at different zoom levels). Does this mean that you are re-running contour on re-sampled data? I am not sure what the benefit of doing that is if one could just simply do the contour once at the highest resolution. Without seeing any code, though, I can only provide generic suggestions. Cheers! Ben Root On Mon, Sep 8, 2014 at 10:12 AM, Raffaele Quarta raffaele.qua...@linksmt.it wrote: Hi Ben, sorry for the few details that I gave to you. I'm trying to make a contour plot of a variable at different zoom levels by using high resolution data. The aim is to obtain .PNG output images. Actually, I'm working with big data (NetCDF file, dimension is about 75Mb). The current Matplotlib version on my UBUNTU 14.04 machine is the 1.3.1 one. My system has a RAM capacity of 8Gb. Actually, I'm dealing with memory system problems when I try to make a plot. I got the error message as follow: cs = m.pcolor(xi,yi,np.squeeze(t)) File /usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py, line 521, in with_transform return plotfunc(self,x,y,data,*args,**kwargs) File /usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py, line 3375, in pcolor x = ma.masked_values(np.where(x 1.e20,1.e20,x), 1.e20) File /usr/lib/python2.7/dist-packages/numpy/ma/core.py, line 2195, in masked_values condition = umath.less_equal(mabs(xnew - value), atol + rtol * mabs(value)) MemoryError Otherwise, when I try to make a plot of smaller file (such as 5Mb), it works very well. I believe that it's not something of wrong in the script. It might be a memory system problem. I hope that my message is more clear now. Thanks for the help. Regards, Raffaele - Sent: Mon 9/8/2014 3:19 PM To: Raffaele Quarta Cc: Matplotlib Users Subject: Re: [Matplotlib-users] Plotting large file (NetCDF) You will need to be more specific... much more specific. What kind of plot are you making? How big is your data? What version of matplotlib are you using? How much RAM do you have available compared to the amount of data (most slowdowns are actually due to swap-thrashing issues). Matplotlib can be used for large data, but there exists some speciality tools for the truly large datasets. The solution depends on the situation. Ben Root On Mon, Sep 8, 2014 at 7:45 AM, Raffaele Quarta raffaele.qua...@linksmt.it wrote: Hi, I'm working with NetCDF format. When I try to make a plot of very large file, I have to wait for a long time for plotting. How can I solve this? Isn't there a solution for this problem? Raffaele -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- This email was Virus checked by Astaro Security Gateway. http://www.sophos.com -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191iu=/4140/ostg.clktrk___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Jody Klymak http://web.uvic.ca/~jklymak/ -- Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable.
