matplotlib-users Mailing List for matplotlib

 Hi,
I had a problem with the load function. I have a file with some data in 
two columns. I'm trying to use load:
x,y=load('toto.dat')
with toto something like:
1 3
3 4
5 6
I obtained the error message:
ValueError: too many values to unpack
I understanded why. It's because the array is not use by columns but by 
lines when you unpack the array from load to x and y so I don't have 
enough variable. To solve this problem I add the transpose function:
x,y=transpose(load('toto.dat'))
I don't know if I'm alone with this problem but if yes that will be a 
good idea to update the help of the function.
Thanks,
 Nicolas

>>>>> "Chris" == Chris Barker <Chr...@no...> writes:
 Chris> anyway, to cut my rant short, here is my vote for
 Chris> matplotlib development (not that I get a vote, but
 Chris> hopefully I'll have time to help out someday)
Hey, I live in Chicago -- we pioneered "vote early, vote often". 
 Chris> 2) Improve the OO interface to make it just as easy to use.
Do you have some suggestions which would make the OO interface easier
to use? For concreteness, here is the archetypal OO script
 from matplotlib.backends.backend_svg import FigureCanvasSVG
 from matplotlib.figure import Figure
 fig = Figure()
 ax = fig.add_subplot(211)
 ax.plot([1,2,3])
 ax.set_xlabel('time')
 canvas = FigureCanvasSVG(fig)
 canvas.print_figure('myfile.svg')
Things that leap to my mind:
 * hide the complexity of having both a canvas and the figure from
 the user, allowing them to deal only with figures, or at least
 have the figure store a ref to its canvas and allow you to do
 fig.savefig('myfig')
 
 which can forward the call on to its canvas print_figure method.
 This would bring the OO interface closer to the pylab interface
 and would prevent you from having to remember which methods were
 fig methods and which methods were canvas methods. We could also
 provide a pylab independent factory function that instantiates a
 figure and canvas with the relevant initialization, allowing you to
 do something like
 fig, canvas = figure_factory(*args, **kwargs) # use the current backend
 but I'm not sure how advisable it is to hide this complexity
 because what you ultimately do with the objects depends on whether
 you are using a GUI backend or not. But for pure image backends
 it would be possible to have a single OO interface which works
 across backends.
 * move the (few) remaining pylab only methods (axis, colorbar) into
 the OO framework for full compatibility
 * use properties/traits so you could do
 ax.xlabel = 'hi mom'
 while retaining the setters and getters for backwards
 compatibility
 * provide more pure OO examples in the examples directory
 * significant;y expand the OO section of the user's guide
Do you have additional ideas? Or are these the issues your were thinking of?
JDH

----- Original Message -----
From: John Hunter <jdh...@ac...>
> Eg, if you have set your dpi parameter correctly to reflect your
> monitor 
> 
> from pylab import *
> fig = figure(dpi=96)
> plot([1,2,3])
> text(1,2,'hi mom', fontsize=72)
> show()
> 
> creates text that is an inch high, irrespective of the view port. I
> think this is the behavior most people expect, at least those who are
> used to thinking about fontsizes in points.
Well, I'd rather set the fontsize in Pixels, but I suppose I can do that
by setting DPI to 72. However, you generally don't want to zoom text as
you zoom in and out, you are zooming in on teh DATA, no the PICTURE of
the data.
By the way, if you do want that, check out my FloatCanvas, in the
wxPython lib. You'll have to draw your own Axes, but if you use
ScaledText, you'll get the whole picture to zoom and scroll.
-Chris