Bug in eps output of matplotlib

I'm running v0.99.1.2 on Debian Linux, 32 bit Intel.  A colorbar on
the right with negative labels produces postscript-eps output which
displays ok with gv or evince.  But when conversion of the ps/eps file
to pdf is made, the negative labels get replaced by dashes when the
pdf is viewed by xpdf or evince.  A variety of pdf conversion methods
(ps2pdf, pdflatex) were used, all with the same result.  I am
including a simple sample python script which creates a graphic with
the problem:

---------------------------------------------------------------------

#!/usr/bin/python
from numpy import *
import matplotlib.pyplot as plt

# this demos a bug in the eps output

x = linspace(0,6,13)
y = linspace(0,3,7)
(X,Y) = meshgrid(x,y)
a = 3.5*sin(X)*sin(Y)

c = plt.contourf(x,y,a)
b = plt.colorbar(c, orientation = 'vertical')
lx = plt.xlabel('x')
ly = plt.ylabel('y')
ax = plt.axis([0,6,0,3])

plt.show()

Re: Bug in eps output of matplotlib

I can't seem to reproduce this on a 32-bit RHEL4 machine with:

python-2.5.4
matplotlib-0.99.1.2
GNU ghostscript 7.07

and viewed with any of:

Adobe Reader 8.1.7
xpdf 3.00
ggv 2.8.0
(sorry no evince on RHEL4)

What versions of these tools are you running?  Do you have any 
customizations in your matplotlibrc file?  Can you send me (off-list) 
the ps/eps and pdf files in question?

Mike

David J. Raymond wrote:
> I'm running v0.99.1.2 on Debian Linux, 32 bit Intel.  A colorbar on
> the right with negative labels produces postscript-eps output which
> displays ok with gv or evince.  But when conversion of the ps/eps file
> to pdf is made, the negative labels get replaced by dashes when the
> pdf is viewed by xpdf or evince.  A variety of pdf conversion methods
> (ps2pdf, pdflatex) were used, all with the same result.  I am
> including a simple sample python script which creates a graphic with
> the problem:
>
> ---------------------------------------------------------------------

registerable backend and minor refactoring of backend-ps

Dear all,

I just committed a small change that enables a user to register a
custom backend that will be used with "savefig".
For example,

import matplotlib.backend_bases
from matplotlib.backends.backend_ps import FigureCanvasPS, RendererPS

class RendererPSCustom(RendererPS):
    def draw_path(self, gc, path, transform, rgbFace=None):
        print "custom draw path"
        RendererPS.draw_path(self, gc, path, transform, rgbFace)

class FigureCanvasPSCustom(FigureCanvasPS):
    _renderer_class = RendererPSCustom

    def print_eps_custom(self, outfile, *args, **kwargs):
        print "Using Custome backend"
        return self._print_ps(outfile, 'eps', *args, **kwargs)

matplotlib.backend_bases.register_backend("eps_custom", FigureCanvasPSCustom)

plt.plot([1,2,3])
plt.savefig("a.eps", format="eps_custom") # this will save the file
using  backend_ps_cmyk

The api may need some cleanups or modifications, and any suggestion
will be welcomed.

ps backend with images in cmyk

I'm experimenting with a customized ps backend that saves images in
cmyk colorspace.
It simply converts the rgb image to cmyk (using lcms), and nothing
more (i.e., it does not embed the icc profile inside the eps file).
While I don't see practical usefulness of this other than for a
previewing purpose, give it a try if you're interested (the current
svn matplotlib is required).
Any comment of suggestion will be welcomed.

http://github.com/leejjoon/mpl_ps_cmyk

Regards,

-JJ

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Re: registerable backend and minor refactoring of backend-ps

On Wed, Feb 3, 2010 at 2:01 PM, Jae-Joon Lee <lee.j.joon@...> wrote:
> Dear all,
>
> I just committed a small change that enables a user to register a
> custom backend that will be used with "savefig".
> For example,
>
> import matplotlib.backend_bases
> from matplotlib.backends.backend_ps import FigureCanvasPS, RendererPS
>
> class RendererPSCustom(RendererPS):
>    def draw_path(self, gc, path, transform, rgbFace=None):
>        print "custom draw path"
>        RendererPS.draw_path(self, gc, path, transform, rgbFace)
>
> class FigureCanvasPSCustom(FigureCanvasPS):
>    _renderer_class = RendererPSCustom
>
>    def print_eps_custom(self, outfile, *args, **kwargs):
>        print "Using Custome backend"
>        return self._print_ps(outfile, 'eps', *args, **kwargs)
>
>
> matplotlib.backend_bases.register_backend("eps_custom", FigureCanvasPSCustom)
>
> plt.plot([1,2,3])
> plt.savefig("a.eps", format="eps_custom") # this will save the file
> using  backend_ps_cmyk
>
>

Re: registerable backend and minor refactoring of backend-ps

Nothing much in the regards of the functionality.
It only provides a way to use custom backends with "savefig", which I
think is more convenient for interactive use. For example, with the
ps_cmyk backend that I'm playing with, the only thing that I  need to
do is to import the module (ps_cmyk) and call

savefig("test.eps", format="eps_cmyk")

And all other (interactive) work flow is not affected by the use of
the custome backend.
In non-interactive mode where a user explicitly calls
"matplotlib.use", there is no need to register a backend.

Regards,

-JJ

On Wed, Feb 3, 2010 at 4:15 PM, Ryan May <rmay31 <at> gmail.com> wrote:
> On Wed, Feb 3, 2010 at 2:01 PM, Jae-Joon Lee <lee.j.joon <at> gmail.com> wrote:
>> Dear all,
>>
>> I just committed a small change that enables a user to register a
>> custom backend that will be used with "savefig".
>> For example,
>>
>> import matplotlib.backend_bases
>> from matplotlib.backends.backend_ps import FigureCanvasPS, RendererPS
>>
>> class RendererPSCustom(RendererPS):
>>    def draw_path(self, gc, path, transform, rgbFace=None):

Re: A small improvement to plot directive

On Thu, Jan 28, 2010 at 2:51 PM, Fernando Perez <fperez.net@...> wrote:
> Thanks, with your and John's (off-list) approvals, it's committed.
> The patch that went in had more docs than what I posted here, but the
> code is identical.

Oops, somehow my commit had never made it, I just noticed now I was
trying to use it from another machine.

Fixed now, r8110.

Cheers,

f

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Comparison of mlab.csd and Matlab's cpsd

   8.9429666e+00   5.0100717e+00  -2.6816087e+00  -7.1501559e+00  -8.0216237e+00  -8.4308386e+00 
-8.7813313e+00  -7.1541340e+00  -3.1692794e+00  -3.1233587e-02  -8.6932796e-01  -3.2208590e+00 
-2.7708292e+00  -1.1180497e+00  -1.1642218e+00   8.2827157e-01   7.7567196e+00   1.3427191e+01  
1.2297869e+01   7.9463857e+00   4.3650450e+00   7.4513721e-01  -1.8071566e+00  -1.0494220e+00  
2.7099914e-01  -6.0612992e-03   1.0650746e+00   2.7359840e+00  -2.3103312e-01  -5.4394070e+00 
-5.6020012e+00  -2.8549610e+00  -3.9441985e+00  -6.5248611e+00  -5.5182498e+00  -3.5707725e+00 
-3.3029199e+00  -1.4821612e+00   1.9829637e+00   2.9371484e+00   2.4922181e+00   4.6520641e+00  
7.6516172e+00   7.9849900e+00   6.2872303e+00   3.0524810e+00  -2.6249618e+00  -8.4729269e+00 
-1.1423490e+01  -1.1515627e+01  -8.0828989e+00  -6.1605087e-02   7.3546053e+00   7.3762039e+00  
2.7203112e+00   9.7107193e-01   2.3389000e+00   2.3308435e+00   1.0908653e+00   1.3983531e+00  
2.7507814e+00   3.1877024e+00   2.6855553e+00   2.0890036e+00   1.5431800e+00   2.6735579e-01 
-2.8915636e+00  -6.9616787e+00  -7.7022941e+00  -2.6552425e+00   3.6478430e+00   4.5449371e+00  
9.1741479e-01  -1.0349366e-01   3.1044471e+00   3.5481921e+00  -2.7689468e+00  -9.5888143e+00 
-9.2968371e+00  -3.1434409e+00   1.4650620e+00   4.9126975e-02  -4.4859946e+00  -5.1590780e+00  
1.6118592e-01   4.9388060e+00   4.1399337e+00   3.0802173e+00   7.1234314e+00   1.0353879e+01  
6.3260927e+00   5.0624656e-01  -4.3675968e-01  -2.3225964e-01  -2.4186513e+00  -1.9095391e+00  
2.5966116e+00   3.2187007e+00  -1.6422521e+00  -2.9320855e+00   1.4858112e+00   2.1743862e+00 
-3.8657803e+00  -7.4941826e+00  -3.6778977e+00   1.4465903e+00   2.0995855e+00  -3.6925935e-01 
-2.4488424e+00  -2.2657275e+00  -3.0767826e-01  -4.3447784e-02  -3.7835013e+00  -7.7710751e+00 
-6.6156223e+00  -9.8452194e-01   3.6143927e+00   3.3559741e+00  -7.0214935e-01  -4.0464556e+00 
-3.4005198e+00   3.1925151e-01   5.6106943e+00   1.2129909e+01   1.5598452e+01   1.0761346e+01  
2.7808335e+00   1.6264690e+00   4.3371698e+00   6.9655189e-01  -6.4917108e+00  -7.1557533e+00 
-3.2903321e+00  -2.5653037e+00  -2.8456560e+00  -3.8648126e-01  -3.4792857e-01  -5.4706976e+00 
-8.4354584e+00  -4.7666552e+00   1.1698809e-01   1.4126243e+00   5.2560707e-01  -1.2557422e+00 
-4.3464817e+00  -6.0548728e+00  -2.6022608e+00   3.4128104e+00   4.5097622e+00  -6.8046372e-01 
-4.1244079e+00  -2.6499816e-02   6.5978997e+00   8.9300310e+00   8.9028673e+00   1.0882147e+01  
1.1960235e+01   7.5608590e+00   3.1334125e-01  -4.6417949e+00  -6.9282767e+00  -7.4717365e+00 
-4.8990327e+00  -5.8542748e-01  -8.4564434e-02  -4.8146391e+00  -8.9187473e+00  -8.1146069e+00 
-5.1477694e+00  -3.2111192e+00  -7.1163877e-01   3.6409206e+00   6.6594649e+00   5.8487425e+00  
3.7533921e+00   3.2460105e+00   2.9353594e+00   1.0668831e+00  -5.3054098e-01  -4.1149627e-01 
-8.1327290e-01  -3.0706932e+00  -4.5485475e+00  -3.4206624e+00  -1.2170184e+00   9.6882742e-01  
2.7440724e+00   1.8368024e+00  -1.5910131e+00  -2.0317113e+00   2.4423217e+00   5.2609099e+00  
2.5027442e+00  -5.3925455e-01   3.6824003e-01   2.1030815e+00   1.6465455e+00   8.1607062e-02 
-1.1482050e+00  -9.4266580e-01   1.0252083e+00   1.3283382e+00  -2.8992882e+00  -7.2661102e+00 
-6.6027869e+00  -3.7400399e+00  -2.6018526e+00  -2.3601345e-01   5.1733118e+00   7.6959332e+00  
3.2229165e+00  -3.2443397e+00  -5.6303607e+00  -3.8377406e+00   2.4645472e-01   5.0569136e+00  
6.3004349e+00   1.3203384e+00  -3.1151906e+00   1.3232982e+00   9.5677298e+00   9.5030932e+00  
1.5131090e+00  -3.8561271e+00  -4.4258970e+00  -5.7326471e+00  -7.0638856e+00  -4.7194733e+00 
-2.2836642e+00  -3.3429743e+00  -2.5434213e+00   4.5252898e+00   1.1170906e+01   8.4467296e+00 
-1.3827260e+00  -6.9978902e+00  -3.0066829e+00   2.8550972e+00   2.1056966e+00  -1.6739241e+00 
-1.9125812e+00  -1.2343693e+00  -2.3238766e+00   3.4253954e-02   6.2718152e+00   8.3409736e+00  
5.4121519e+00   3.9103398e+00   2.6471453e+00  -2.2564369e+00  -5.9685791e+00  -5.2084251e+00 
-5.5583585e+00  -8.5601348e+00  -9.2173592e+00  -7.7095246e+00  -6.4247195e+00  -2.9195376e+00  
1.3696917e+00   2.3600111e-01  -3.5066462e+00  -1.7906518e+00   3.0267100e+00   4.4608049e+00  
4.9647577e+00   8.1244909e+00   1.0462506e+01   9.6079485e+00   7.7730961e+00   5.8355237e+00  
4.1832824e+00   4.4872281e+00   4.7070481e+00   1.1954062e+00  -3.3703080e+00  -4.2879123e+00 
-3.7852632e+00  -5.9645982e+00  -8.4869057e+00  -7.4016607e+00  -4.3441103e+00  -2.3813524e+00  
1.2418841e-01   4.9183614e+00   7.1076542e+00   1.3607427e+00  -7.3320053e+00  -8.9727762e+00 
-3.2209033e+00   1.4899373e+00   1.0741419e+00  -1.4691569e+00  -2.5938840e+00  -1.2369807e+00  
2.0206986e-01  -1.8303922e+00  -3.9449765e+00   1.4387487e+00   1.0514320e+01   1.0769771e+01
   8.8313817e+00   4.3005055e+00  -4.1649119e+00  -6.3050160e+00  -5.2402152e+00  -7.3721800e+00 
-8.1775693e+00  -3.2534988e+00   1.7048012e+00   1.8813030e+00   1.0824107e-01  -1.1253794e+00 
-2.4968623e+00  -3.3077789e+00  -2.1535871e+00   7.4321205e-01   4.6802272e+00   7.9643259e+00  
7.9943665e+00   5.5547796e+00   4.3951321e+00   4.5254200e+00   2.3442211e+00  -1.8909218e+00 
-3.5125831e+00  -7.2464997e-01   2.7212191e+00   2.5851414e+00  -9.2755899e-01  -3.8951814e+00 
-3.6401440e+00  -1.7854451e+00  -1.5882577e+00  -3.5966400e+00  -5.5301748e+00  -5.3917715e+00 
-3.4710664e+00  -1.6020516e+00  -7.3631744e-01   2.6970500e-01   2.6573457e+00   5.4863161e+00  
6.9121613e+00   6.6655222e+00   5.6622659e+00   4.0389729e+00   9.3885229e-01  -3.9502750e+00 
-8.8257786e+00  -1.0220073e+01  -6.5514972e+00  -7.9560635e-01   2.6491715e+00   3.0176599e+00  
2.3249973e+00   1.3986930e+00   4.0408014e-01   6.3290633e-01   1.6628753e+00   6.5485073e-01 
-1.8717202e+00  -1.4627624e+00   1.9782947e+00   3.2160739e+00   1.1668544e+00  -7.5422833e-02 
-3.0476741e-01  -2.7414493e+00  -5.4076926e+00  -3.5109668e+00   1.5764495e+00   4.3840966e+00  
3.4651353e+00   1.6677022e+00   1.3278134e+00   1.9641438e+00   9.7844787e-01  -2.6541428e+00 
-5.4302555e+00  -3.6952895e+00   3.5658553e-01   1.7762362e+00   3.5450667e-02  -1.0828150e+00  
8.1605611e-01   3.7404261e+00   4.2935454e+00   2.9825690e+00   3.2110963e+00   4.3252139e+00  
2.6993864e+00   2.5772192e-01   1.2371109e+00   2.0607001e+00  -2.2704400e+00  -6.6867329e+00 
-5.4038368e+00  -3.6397915e+00  -6.2586503e+00  -7.3385415e+00  -2.7550983e+00   7.9236928e-01 
-1.8886836e+00  -5.6601482e+00  -3.8104737e+00   2.8583879e+00   7.6702934e+00   5.8872419e+00  
9.0677176e-01  -1.9440434e-01   2.3735551e+00   2.3652435e+00  -7.5500799e-01  -1.8590439e+00  
7.5920807e-03   1.8605444e+00   2.7519176e+00   2.3561563e+00  -2.1737359e-01  -2.8219683e+00 
-2.2463695e+00   7.2443146e-01   3.6353362e+00   5.4375210e+00   4.7116456e+00   1.5334323e+00  
1.3049015e-01   2.1877728e+00   2.5385513e+00  -1.5107798e+00  -4.8889180e+00  -4.1843992e+00 
-2.2828085e+00  -1.0670605e+00   2.3457513e-01   2.0273180e-01  -2.0612892e+00  -3.3606344e+00 
-2.1726779e+00  -1.3180010e+00  -1.4886559e+00  -6.8853732e-01  -3.2777472e-02  -1.2468097e+00 
-2.0177334e+00  -9.4836544e-01  -4.9327480e-01  -9.0372213e-01  -6.2469066e-02   6.9582516e-01 
-2.6679510e-01  -3.0107267e-01   1.5593932e+00   2.2971845e+00   2.3280989e+00   4.3614839e+00  
5.9911319e+00   4.4196684e+00   2.4898740e+00   1.7785859e+00  -1.7747279e-03  -1.4677343e+00 
-7.7654385e-02   6.3896630e-01  -1.8932167e+00  -3.7540125e+00  -3.6034108e+00  -4.3085200e+00 
-4.2368712e+00  -1.2982768e+00   3.4464260e-01  -4.0509169e-01   1.7701181e+00   5.9147567e+00  
5.4544044e+00   1.7826749e+00   4.6335736e-01   2.0463931e-01  -1.3535767e+00  -2.0307774e+00 
-1.9379323e+00  -3.0905695e+00  -3.1283034e+00  -5.8490829e-01   9.5482502e-01   4.8349411e-01  
5.4859920e-01   2.6505302e-01  -1.6738570e+00  -2.1912486e+00   3.2643425e-02   1.8745902e+00  
1.8733346e+00   8.7274346e-01  -6.2320768e-01  -8.6521021e-01   9.8999512e-01   1.7587751e+00  
3.6997317e-01   4.6666216e-01   1.9638847e+00   7.1586139e-01  -2.7192205e+00  -4.8546551e+00 
-5.2275700e+00  -3.6331454e+00  -3.4432594e-01   8.2170170e-01  -7.7122599e-02   2.7567014e+00  
7.0580169e+00   3.6661124e+00  -4.3602951e+00  -5.1712241e+00   9.4062577e-01   4.8370393e+00  
4.8074790e+00   3.6350180e+00   1.7355182e+00   1.1764258e+00   3.3588501e+00   4.1348665e+00  
1.5457105e+00  -8.1362250e-01  -2.4892348e+00  -4.6008297e+00  -3.5153619e+00   1.8112368e-01 
-1.3466809e+00  -7.1410649e+00  -6.9291330e+00  -6.8888605e-01   2.1900116e+00   5.3854746e-01 
-6.6370732e-01  -1.2650612e+00  -1.6732370e+00   2.4574404e-01   2.5040580e+00   1.8156371e+00  
7.8117115e-01   1.9919812e+00   2.8459795e+00   2.4198319e+00   3.0987054e+00   4.2393728e+00  
3.6648485e+00   2.1428796e+00   3.8022045e-01  -2.2021776e+00  -4.1744097e+00  -4.2930744e+00 
-4.3848972e+00  -5.2515582e+00  -5.2594541e+00  -4.4249680e+00  -3.4217885e+00  -1.0180247e+00  
1.8727737e+00   1.4909976e+00  -1.6255664e+00  -2.3798025e+00   6.6177734e-01   4.0583452e+00  
5.4193601e+00   4.7630895e+00   2.7683942e+00   1.1101528e+00   1.2818523e+00   2.5446188e+00  
3.6850506e+00   4.7988971e+00   5.2451330e+00   3.4546722e+00   3.2558037e-01  -1.3030521e+00 
-1.3554915e+00  -2.6284306e+00  -5.3897891e+00  -6.1533489e+00  -3.3546173e+00  -1.5965785e-01  
6.8257969e-01   5.0294837e-01   4.3335249e-01  -1.3020608e+00  -4.4203707e+00  -4.8678613e+00 
-1.5345759e+00   1.3920361e+00   1.2277059e+00  -5.9079942e-02  -6.7115701e-01  -1.3347163e+00 
-2.3535973e+00  -2.2881480e+00   2.0879504e-01   4.4173569e+00   7.1039609e+00   5.4811765e+00

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libpng14 error

This is probably already known, but I'll go ahead and post it.  In trying to build against libpng-1.4.0, I had
to edit src/_png.cpp:

//  png_destroy_read_struct(&png_ptr, &info_ptr, png_infopp_NULL);
   png_destroy_read_struct(&png_ptr, &info_ptr, NULL);

-Randy
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Re: Comparison of mlab.csd and Matlab's cpsd

Hi,

> From: Ariel Rokem <arokem@...>
> However - two elements are off by a factor of approximately 2 - the
> very first element and the very last. ... Does anyone have any idea
> why this would be the case?

>From a quick look at the mlab code, it looks like a bug in
mlab._spectral_helper.

The default spectrum is 'onesided' (same as for Matlab's cpsd). A
single-sided spectrum of a real signal has double the magnitude of a
double-sided spectrum, *except* at the origin (frequency index n = 0)
and Nyquist frequency (n = NFFT / 2), where it is the *same* as the
double-sided one [1]_.

In the mlab code, all the spectral values are simply scaled by a
factor of 2 (among other factors) in this line:

    # Scale the spectrum by the norm of the window to compensate for
    # windowing loss; see Bendat & Piersol Sec 11.5.2.  Also include
    # scaling factors for one-sided densities and dividing by the sampling
    # frequency, if desired.
    Pxy *= scaling_factor / (np.abs(windowVals)**2).sum()

This should be easy to fix (although the function probably needs a
little rework).

Regards,
Ludwig

Quick reference from my bookshelf:
---------------------------------------------------
.. [1] W. L. Briggs, V. E. Henson, "The DFT: An Owner's Manual for the
Discrete Fourier Transform," Section 1.3, Problem 6 (a), p. 13.

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