matplotlib-users Mailing List for matplotlib

Fr, 7 Jun 2013 10:13:26 -0400 Michael Droettboom <md...@st...>:

> Have you tried setting ps.usedistiller to False, or xpdf?  There have 
> been problems using Ghostscript as a distiller with recent versions
> of Ghostscript.

No, I didn't try.  Thanks for the hint, I will test that.

> We'll need a minimal example, or at least a copy of the PS file to 
> investigate this further, however.  Also, what platform, version of 
> matplotlib and Python are you using?

If I keep everything on my system linux with python 2.7.5 and
matplotlib 1.2.1 it works fine.  Problems arise if I move the EPS to an
older system or the printing.  I will have access to these machines on
Tue.  I will try to create a minimal example then.

Best regards, Yoshi

Julien,

See https://github.com/matplotlib/matplotlib/pull/2119 for a proposed fix.

Eric

On Thu, Jun 6, 2013 at 11:39 PM, Sudheer Joseph <sud...@ya...>wrote:

> Dear Experts,
>             I have been experimenting with the plot_dates option of
> matplotlib to plot time series data and have below questions
>
>  I have used
> loc = mdates.AutoDateLocator()
> ax.xaxis.set_major_locator(loc)
> ax.xaxis.set_major_formatter(mpl.dates.DateFormatter('%b\n %Y'))
>
>
> and got the tick labels in attached plot
>
> However I feel the repeatd year labeling is not needed here and it is
> required once in a year only , Also if I need to plot long time seris
> insted of "MAR" "APR" I wanted to get them reduced to "M" "A" etc so that
> the lavel congestion can be avoided.
>
>
> I notice that below options are available, but was wondering how
> commbinatins of these locateors are used ie mark every month and every year
> once each.
>
>
> Is there a way to achive the above or does it need further development?
>
> fmt = mdates.DateFormatter('%Y-%m-%d')
> loc = mdates.WeekdayLocator(byweekday=mdates.MONDAY,interval=4)
> locator = mdates.YearLocator()
>

If I were trying to do this, I'd cobble something together using by the
minor and major formatters.
e.g.,...
import matplotlib.dates as mdates
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

majorLocs = mdates.MonthLocator(bymonth[1,7])
majorFmt = mdates.DateFormatter('%b\n%Y')

minorLocs = mdates.MonthLocator(bymonth[1,7])
minorFmt = mdates.DateFormatter('%b')

ax.xaxis.set_major_locator(majorLocs)
ax.xaxis.set_major_formatter(majorFmt)

ax.xaxis.set_minor_locator(minorLocs)
ax.xaxis.set_minor_formatter(minorFmt)

On 06/07/2013 05:07 AM, Yoshi Rokuko wrote:
> I'm having problems recently with printing EPS figures created by
> matplotlib. To me this is strange because printing postscript should
> just work in my opinion.
>
> My most recent example is a Basemap thing with AxesGrid. Basically the
> idea was to have six maps nicely arranged on a DIN A4 paper for
> printout. The EPS looked nice on my notebook but printing them on our
> freshly leased printers at the institute failed in the middle of the
> fifth map (six maps in total). I have Ghostscript 9.07 and it turned out
> that this EPS stopped working with just one earlier version (a college
> with Ghostscript 9.06 could not open the EPS or more correct Ghostview
> failed in the middle of map number five).
>
> I expect such a Ghostscript version thing to be the problem also with
> the printer. If that is the case don't you think that's ridiculous?
> Isn't at least some legacy support wanted?

Yes -- legacy support is of course intended...  matplotlib has been 
going for over 10 years, after all, and we're very conservative about 
intentionally breaking legacy systems.

Have you tried setting ps.usedistiller to False, or xpdf?  There have 
been problems using Ghostscript as a distiller with recent versions of 
Ghostscript.

We'll need a minimal example, or at least a copy of the PS file to 
investigate this further, however.  Also, what platform, version of 
matplotlib and Python are you using?

Mike

>
> I don't have a minimal example yet, but I could try to create one next
> week if the need is there. The above mentioned thing was something
> along the lines of:
>
> ...
> import matplotlib.pyplot as pl
> from mpl_toolkits.basemap import Basemap
> from mpl_toolkits.axes_grid1 import AxesGrid
>
> # loading data
> ...
>
> fig = pl.figure(1, (16,19))
> grid = AxesGrid(fig, 111,
>              nrows_ncols = (3, 2),
>              axes_pad = 0.3,
>              cbar_location = 'top',
>              cbar_mode = 'each',
>              cbar_size = '3%',
>              cbar_pad = '1%',
>             )
> for i in range(6):
>      bmap = Basemap(projection='aeqd', ..., ax=grid[i])
>      ...
>
> pl.savefig('sixer.eps', bbox_inches='tight')
>
> Best regards, Yoshi
>
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Thans a lot Eric for the fast and detailed answer!


On Thu, Jun 6, 2013 at 9:24 PM, Eric Firing <ef...@ha...> wrote:

> On 2013/06/06 2:08 AM, Julien Cornebise wrote:
> > Dear all
> >
> > I am puzzled: in the following code, when I call clim() *after* having
> > created 3 subplots, only the last subplot takes the new limits into
> > account. All other subplots ignore it. Xlim(), on the countrary, works
> > as intended. Everything works fine when I set the clim()  at creation
> time.
>
> I see what the problem is, so I expect to come up with a PR for it in a
> day or two.
>
> In the meantime, as a workaround, change your clim() line to:
>
>      plt.gca()._gci().set_clim((5,10))
>
> Eric
>
>
>
> ------------------------------------------------------------------------------
> How ServiceNow helps IT people transform IT departments:
> 1. A cloud service to automate IT design, transition and operations
> 2. Dashboards that offer high-level views of enterprise services
> 3. A single system of record for all IT processes
> http://p.sf.net/sfu/servicenow-d2d-j
> _______________________________________________
> Matplotlib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I'm having problems recently with printing EPS figures created by
matplotlib. To me this is strange because printing postscript should
just work in my opinion.

My most recent example is a Basemap thing with AxesGrid. Basically the
idea was to have six maps nicely arranged on a DIN A4 paper for
printout. The EPS looked nice on my notebook but printing them on our
freshly leased printers at the institute failed in the middle of the
fifth map (six maps in total). I have Ghostscript 9.07 and it turned out
that this EPS stopped working with just one earlier version (a college
with Ghostscript 9.06 could not open the EPS or more correct Ghostview
failed in the middle of map number five).

I expect such a Ghostscript version thing to be the problem also with
the printer. If that is the case don't you think that's ridiculous?
Isn't at least some legacy support wanted?

I don't have a minimal example yet, but I could try to create one next
week if the need is there. The above mentioned thing was something
along the lines of:

...
import matplotlib.pyplot as pl
from mpl_toolkits.basemap import Basemap
from mpl_toolkits.axes_grid1 import AxesGrid

# loading data
...

fig = pl.figure(1, (16,19))
grid = AxesGrid(fig, 111,
            nrows_ncols = (3, 2),
            axes_pad = 0.3,
            cbar_location = 'top',
            cbar_mode = 'each',
            cbar_size = '3%',
            cbar_pad = '1%',
           )
for i in range(6):
    bmap = Basemap(projection='aeqd', ..., ax=grid[i])
    ...

pl.savefig('sixer.eps', bbox_inches='tight')

Best regards, Yoshi

Dear Experts,
            I have been experimenting with the plot_dates option of matplotlib to plot time series data and have below questions

 I have used
loc = mdates.AutoDateLocator()
ax.xaxis.set_major_locator(loc)
ax.xaxis.set_major_formatter(mpl.dates.DateFormatter('%b\n %Y'))


and got the tick labels in attached plot

However I feel the repeatd year labeling is not needed here and it is required once in a year only , Also if I need to plot long time seris insted of "MAR" "APR" I wanted to get them reduced to "M" "A" etc so that the lavel congestion can be avoided. 


I notice that below options are available, but was wondering how commbinatins of these locateors are used ie mark every month and every year once each.


Is there a way to achive the above or does it need further development?

fmt = mdates.DateFormatter('%Y-%m-%d')
loc = mdates.WeekdayLocator(byweekday=mdates.MONDAY,interval=4)
locator = mdates.YearLocator()


 with best regards,
Sudheer

***************************************************************
Sudheer Joseph 
Indian National Centre for Ocean Information Services
Ministry of Earth Sciences, Govt. of India
POST BOX NO: 21, IDA Jeedeemetla P.O.
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***************************************************************

Thanks! Using pcolor indeed solved the problem. Now my rows and columns are all nice and even.

Best,
-Michiel.




________________________________
 From: Benjamin Root <ben...@ou...>
To: Michael Droettboom <md...@st...> 
Cc: Matplotlib Users <mat...@li...> 
Sent: Friday, June 7, 2013 1:40 AM
Subject: Re: [Matplotlib-users] matshow unequal element sizes
 




On Thu, Jun 6, 2013 at 10:14 AM, Michael Droettboom <md...@st...> wrote:

By default (when interpolation="nearest") matplotlib is performing nearest neighbor interpolation on the image to the request PDF dpi before storing it in the file.  This results in rows and columns of unequal size because the ratio from the original image to the destination resolution is likely not integral.
>
>You can set interpolation="none", which will pass the original
      image as-is on to the file, but then we can't control the
      interpolation mode (since there's no way to tell the PDF viewer
      what sort of interpolation to perform), so that (usually) will
      result in bicubic interpolation, which is probably not what you
      want.
>
>Mike
>
>

From experience, it seems that pcolor() or pcolormesh() works best for pdf's because it saves the polygons.  You might need some tweaking to get it exactly right, but at least the pdf viewer won't smudge it all out.


Cheers!
Ben Root

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How ServiceNow helps IT people transform IT departments:
1. A cloud service to automate IT design, transition and operations
2. Dashboards that offer high-level views of enterprise services
3. A single system of record for all IT processes
http://p.sf.net/sfu/servicenow-d2d-j
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