Hi John,
The image is correct when plotted using i=imread('plot.png') then
imshow(i), but I want to add axes. I generated the image directly using
GTK commands, then saved the pixbuf as png. The pixels in the image
correspond to sample points in both x- and y-directions generated using
exp(linspace(log(low),log(high),num). Why is there no logspace in
matplotlib, btw?
All I basically need is a way to say what the range and distribution of
the pixels is: I don't want the axes to default to integer-numbered
linear-spaced values as they currently do.
I tried to see if I could use the set_xscale command but it seems to be
internal and/or only applicable to polar plots?
There's an ASCII mockup of what I'm wanting below. As I said, the image
doesn't need to be stretched, just stuck straight on the right axes.
Cheers
JP
10 +-----|-----|-----+
| |
| |
1 + + + +
| |
| my image here |
0.1+ + + +
| |
| |
e-3+-----+-----+-----+
0.1 1 10 100
John Hunter wrote:
>>>>>> "John" == John Pye <[EMAIL PROTECTED]> writes:
>>>>>>
>
> John> Hi all, I have a PNG image that I would like to mount on
> John> log-log axes. The points in the image correspond to computed
> John> values on a log-log scale, so no scaling of the image is
> John> required: I just want to stick it on top of suitably-marked
> John> axes. It would be great if I could then overlay some dot
> John> points as well.
>
> John> Is this possible with matplotlib? Can anyone give me some
> John> pointers on how to do it? Or a better tool for this?
>
> I'm not sure from your post if the log scale applies to the implicit
> xy coords of the pixels, or to the intensity of the pixels. I'm
> assuming the former below (if it's the latter you probably want custom
> normalize and colormap objects).
>
> logarithmic xy pixel locations may be possible with a NonuniformImage.
> Take a look at the following for example code
>
> http://article.gmane.org/gmane.comp.python.matplotlib.general/4050
>
> I'm not sure that this will work since I haven't tried it, but it's
> the best bet as far as I can see.
>
> See how far you can get with it and if you get stuck, post a code
> example and CC Nicholas and we'll see if we can progress.
>
> JDH
>
>
>
--
John Pye
School of Mechanical and Manufacturing Engineering
The University of New South Wales
Sydney NSW 2052 Australia
t +61 2 9385 5127
f +61 2 9663 1222
mailto:john.pye_AT_student_DOT_unsw.edu.au
http://pye.dyndns.org/
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