Hello, I tried to find a solution now - and I have one: In fact it's really easy: just plot two graphs. For the first one, the text-color and the color of the axes is set to white. This graph is then converted to a jpeg by pipeGS. The second graph gets the axes-sizes (min and max values for each axes, total size of the Graph) from the first graph. Nothing is plotted in this graph, just the jpg-File from the first graph is included. With that, the axes and the text are plotted as vectors, and the surface is plotted as a jpeg. The same should also work for all types of 2d-graphs. For the example "surface.py", the following code works:
from pyx import *
col = color.gray.white
whitetext=text.texrunner()
whitetext.set(mode="latex")
whitetext.preamble(r"\usepackage{color}")
whitetext.preamble(r"\definecolor{COL}{gray}{1}")
axis_texter = graph.axis.texter.decimal(prefix=r"\textcolor{COL}{",suffix=r"}")
paint=graph.axis.painter.regular(
texrunner = whitetext,
basepathattrs = [color.gray.white],
tickattrs = [color.gray.white]
)
g1 = graph.graphxyz(size=4, x2=None, y2=None,
x = graph.axis.linear(painter=paint,texter = axis_texter),
y = graph.axis.linear(painter=paint,texter = axis_texter),
z = graph.axis.linear(painter=paint,texter = axis_texter),
)
g1.plot(graph.data.file("surface.dat", x=1, y=2, z=3), [graph.style.surface()])
g1.pipeGS("surface_tmp.jpg")
c = canvas.canvas()
g2 = graph.graphxyz(size=4, x2=None, y2=None,
x = graph.axis.linear(
min = g1.axes["x"].data.min, max = g1.axes["x"].data.max),
y = graph.axis.linear(
min = g1.axes["y"].data.min, max = g1.axes["y"].data.max),
z = graph.axis.linear(
min = g1.axes["z"].data.min, max = g1.axes["z"].data.max),
)
g2.insert(bitmap.bitmap(g1.bbox().left(), g1.bbox().bottom(),
bitmap.jpegimage("surface_tmp.jpg"),
height=g1.bbox().height(), compressmode=None))
g2.writeEPSfile("surface")
g2.writePDFfile("surface")
HTH,
Axel
On Fri, May 16, 2008 at 10:12:31AM +0200, Axel Freyn wrote:
> Hi all,
>
> may be one possibility would be to write a subroutine which separates text
> and images, and then convert the image-part using pipeGS, and add the
> text-part on top of it?
> I'm thinking of a code like
> text_items=[]
> graph_items=[]
> for item in canvas.items:
> if item.__class__.__name__ == "textbox":
> text_items.append(item)
> else:
> if item.__class__.__name__ == "graphxy":
> item.dolayout()
> # loop over all sub-elements of this graphxy and remove all texts
> ...
> else:
> graph_items.append(item)
> graph_canvas = canvas.canvas()
> graph_canvas.items = graph_items
> text_canvas = canvas.canvas()
> text_canvas = text_items
>
> graph_canvas.insert(text_canvas)
>
> Well, there mightl be some problems to code, as you have to loop recursively
> over all elements (if you include a canvas into another canvas), and you
> have to think about the internals of e.g. graphxy (I don't know how to
> remove there all text - may be changing recursively all texter's of the
> objects? And how to calculate this text and add it to the other list?), or
> what to do with transformations,...
>
> What do you think about it? May be it could be nice to have such a
> subroutine integrated in regular PyX - especially for 3D-Plots, or am I
> missing something?
>
> Axel
>
> On Fri, May 16, 2008 at 8:50 AM, Benedikt Koenig <[EMAIL PROTECTED]> wrote:
>
> > Hi André,
> >
> > like Jörg already pointed out I am indeed looking for a way to convert
> > only the 3d surface to bitmap and keep the scalable fonts and axes. I
> > think such a mix of bitmap and vector parts should be possible in PDF.
> > As I mentioned, I am aware of the pipeGS method but it's not exactly
> > what I mean.
> >
> > Thanks anyway,
> > benedikt
> >
> > Am Donnerstag, den 15.05.2008, 10:00 +0200 schrieb André Wobst:
> > > Hi Benedikt,
> > >
> > > I've used bitmap converted figures before as well. In recent PyX
> > > versions you can quite easily create such bitmaps by the pipeGS method
> > > of a canvas. Note that jpg and png files created this way can be used
> > > in pdfLaTeX directly.
> > >
> > > HTH,
> > >
> > >
> > > André
> > >
> > >
> > > Am 08.05.2008 um 10:35 schrieb Benedikt Koenig:
> > >
> > > > Hi All,
> > > >
> > > > I have a problem concerning the file size of my plots. Producing 3d
> > > > graphs of my data leads to single PDF files of several MB size.
> > > > Including these graphs in my paper gives a nice to print document, but
> > > > it is way to big for easy electronic distribution as PDF. So I was
> > > > thinking if there is a way to produce these high quality vector
> > > > graphics
> > > > for the print version of the paper but to somehow get some smaller
> > > > sized
> > > > graph files for the electronic version.
> > > >
> > > > Currently I am limiting the size by plotting only every x-th point.
> > > > But
> > > > obviously this is a stupid solution if you are lucky enough to have
> > > > high
> > > > resolution data in the first place. Alternatively I could use pipeGS
> > > > to
> > > > produce bitmaps of the complete graph, but I'd rather keep the axes
> > > > and
> > > > text as vectors and only have the actual data as bitmap.
> > > >
> > > > My idea is basically to produce the highly resolved 3d graph, then
> > > > convert the plotted data into a bitmap while keeping axes and text in
> > > > vector format and then write the whole stuff to a PDF. This should
> > > > keep
> > > > file sizes moderate even if the bitmap has printing quality of around
> > > > 300 dpi.
> > > >
> > > > Are there any opinions on whether some thing like this is possible at
> > > > all using PyX and if yes, how to do it? Or is there any other way to
> > > > keep file size small for complexe plots?
> > > >
> > > > Thanks already,
> > > > bene
> > > >
> > > >
> > > >
> > > >
> > > >
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