Here's one way to do it in Python using matplotlib and data downloaded from the cytoBandIdeo table from UCSC's Table Browser saved as ideogram.txt:

"""
Rough script to plot chromosome ideograms using data from UCSC
"""
from matplotlib import pyplot as plt
from matplotlib.collections import BrokenBarHCollection

color_lookup = {
                  'gneg': (1., 1., 1.),
                'gpos25': (.6, .6, .6),
                'gpos50': (.4, .4, .4),
                'gpos75': (.2, .2, .2),
               'gpos100': (0., 0., 0.),
                  'acen': (.8, .4, .4),
                  'gvar': (.8, .8, .8),
                 'stalk': (.9, .9, .9),
               }

height = 0.9
spacing = 0.9

def ideograms(fn):
    last_chrom = None
    fin = open(fn)
    fin.readline()
    xranges, colors = [], []
    ymin = 0

    for line in fin:
        chrom, start, stop, label, stain = line.strip().split('\t')
        start = int(start)
        stop = int(stop)
        width = stop - start
        if chrom == last_chrom or (last_chrom is None):
            xranges.append((start, width))
            colors.append(color_lookup[stain])
            last_chrom = chrom
            continue

        ymin += height + spacing
        yrange = (ymin, height)
        yield xranges, yrange, colors, last_chrom
        xranges, colors = [], []
        xranges.append((start, width))
        colors.append(color_lookup[stain])
        last_chrom = chrom

    # last one
    ymin += height + spacing
    yrange = (ymin, height)
    yield xranges, yrange, colors, last_chrom

fig = plt.figure()
ax = fig.add_subplot(111)
d = {}
yticks = []
yticklabels = []

# ideogram.txt downloaded from UCSC's table browser
for xranges, yrange, colors, label in ideograms('ideogram.txt'):
    coll = BrokenBarHCollection(xranges, yrange, facecolors=colors)
    ax.add_collection(coll)
    center = yrange[0] + yrange[1]/2.
    yticks.append(center)
    yticklabels.append(label)
    d[label] = xranges

ax.axis('tight')
ax.set_yticks(yticks)
ax.set_yticklabels(yticklabels)
ax.set_xticks([])
plt.show()

I don't know details about the staining (so my colors are probably off), but this should hopefully get you started. Since it's off-the-shelf matplotlib and the x-axis is in bp, you can easily add lines/annotations for your own data.

Edit, 4 yrs later... see an improved version over at A: Matplotlib comprehensive chromosome drawing

There is Easyfig which is basically a GUI for genome annotation and comparison. You might be able to reuse some of it's code.

And there's AnnotationSketch (part of genometools), which has Python bindings according to the website.

Andreas

If you want to code your python scripts to fix this,I know two ways : 1 use the 3rd lib to plot, like matplotlib, pysvg , ... ; 2 generate svg (xml) script directly (need to know SVG grammar).

I like the latter .