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>>>>> "Darius" == Darius Vainius <va...@ib...> writes:

    Darius> Hello, does anybody have an idea how to set the x-axis
    Darius> scale to logarithmic on an errorbar plot? In other words,
    Darius> is there any way to plot data with error bars while having
    Darius> x-axis scale logarithmic?

    Darius> Many thanks in advance for any useful suggestions.

On any type of plot where the data on a given axis is strictly
positive, you should be able to set the scale to 'log'.  Just make
sure that the axis limits are also strictly positive.  Eg

  ax.set_xlim(0.01, 10)
  ax.set_xscale('log')

With errorbars, you have to be careful, because if the error limits on
one of your positive datapoints extend into non-positive territory,
you'll get an error with log scaling.

JDH

Hello,

does anybody have an idea how to set the x-axis scale to logarithmic on 
an errorbar plot? In other words, is there any way to plot data with 
error bars while having x-axis scale logarithmic?

Many thanks in advance for any useful suggestions.

Darius

>>>>> "Michael" == Michael J T O'Kelly <mo...@MI...> writes:

    Michael> I want to be able to specify the size of points in a
    Michael> scatter plot in data coordinates rather than points^2.
    Michael> The points should change in size at different zoom
    Michael> levels.  Is there a built-in way to do this, or a good
    Michael> workaround for now?

You can't do this with the built-in scatter or RegularPolyCollection
(which scatter uses) because these assume a size in points.  But you
can roll your own PolyCollection fairly easily

import matplotlib.cm as cm
import matplotlib.numerix as nx
from matplotlib.collections import PolyCollection
from pylab import figure, show

xs, ys, radii, colors = nx.mlab.rand(4,100)
radii *= 0.1

def poly(x,y,r,numsides):
    theta = 2*nx.pi/numsides*nx.arange(numsides) 
    return zip(x + r*nx.cos(theta), y + r*nx.sin(theta))

verts = [poly(x,y,r,6) for x,y,r in zip(xs, ys, radii)]
col = PolyCollection(verts)
col.set_array(colors)
col.set_cmap(cm.hot)

fig = figure()
ax = fig.add_subplot(111, xlim=(0,1), ylim=(0,1), aspect=1)
ax.add_collection(col)
show()

I want to be able to specify the size of points in a scatter plot in 
data coordinates rather than points^2.  The points should change in size 
at different zoom levels.  Is there a built-in way to do this, or a good 
workaround for now?

Thanks,
Michael