Hello,
The script pasted below plots a square array. The (very small) output
PDF is attached to this posting. For reasons I do not understand,
there's a fine additional border immediately at the top and bottom of
the array.
If the commented-out line of code is removed, the strange border
disapp
Nicolas Rougier writes:
> Would something like this suit your needs ?
>
> (...)
Thanks. Setting figsize is indeed the way to achieve (almost) what I
wanted. My other followup in this thread describes the remaining issue.
Joe, thank you very much for your reply. So the "figsize" of a
matplotlib plot is the physical size of the region between the axes
where the data is shown? If this is indeed the case, as it seems, then
achieving (almost) what I wanted is as easy as setting a figsize with
the proper aspect ratio,
Benjamin Root writes:
> I particularly like using the figaspect() function:
>
> (...)
>
> It isn't perfect, but for its simplicity, it gets it mostly right.
Thanks, Benjamin, for your quick reply.
Unfortunately, figaspect is only an approximate solution, as it simply
uses the aspect ration of th
Hello,
I'm stuck trying to find a solution to the following problem.
I'd like to show an array using imshow preserving the 1:1 aspect ratio
of its pixels. At the same time, I would like the axes to fit around
the image tightly.
Is there some way to, for example, choose a certain figure width, a
Hello,
Is there a way to find out the optimal resolution that an array (of a given
aspect ratio) should have, so that imshow will not re-scale it on a
pixel-based backend?
Some background: I'm preparing an array that has a native resolution, so for
PDF output I use imshow with interpolation='none
Christoph Groth writes:
> show_figures([Figure().add_subplot(1,1,1).plot(range(10)),
> Figure().add_subplot(1,1,1).plot([x*x for x in range(10)])])
This wouldn't work of course, it should be rather
f1 = Figure()
f1.add_subplot(1, 1, 1).plot(range(10))
f2 = Figure()
f2.
Dear matplotlib developers,
I prefer to use matplotlib in my scripts without its state-machine
wrapper and it works mostly nicely. One thing which is missing
currently is a standard way to display a bunch of figures using the
default backend. What I have to do now is:
from matplotlib.pyplot imp
