matplotlib-users Mailing List for matplotlib

On 2007年4月22日, Hans Strotzer apparently wrote: 
> One thing that really annoys me is that generally python 
> code is quite visually appealing
Tastes must vary!
What is your point of comparison??
Controlling may graph properties is never going to be 
beautiful. But why not define a class that can build
a figure with your desired defaults?
> # change color of important bars... 
> for i in p.info: 
> if type(i)==datetime: 
> index = p.dates.index(i) 
> if index: 
> p1[index].set_facecolor('r') 
Apparently p.dates is NOT a list?
(You seem to assume None is returned if a ValueError would be raised.)
Anyway, maybe something like:
colorindices = (p.dates.index(d) for d in p.info if d in p.dates)
for index in colorindices:
 p1[index].set_facecolor('r')
Cheers,
Alan Isaac

Hi
I'm using matplotlib for producing a bar-chart displaying my
electricity consumption. One thing that really annoys me is
that generally python code is quite visually appealing, the
same goes for the code in the matplotlib-examples.
The code I have produced here is frankly quite ugly
when it comes to setting all the properties I want.
Is there a smarter way of doing this, perhaps using dictionaries etc?
(I have attached the genereated png-file)
cheers
//Fredrik
--
from parser_el import *
from pylab import *
# Override some matplotlibrc defaults
# to get some nicer plots
rc('figure', figsize=3D(18,8))
rc('figure.subplot', bottom=3D0.14)
rc('figure.subplot', left=3D0.04)
rc('figure.subplot', right=3D0.98)
p =3D parser_el()
N =3D len(p.dates)
ind =3D arange(N)
p1 =3D bar(ind, p.kwh_avg, color=3D'b', align=3D'center')
# change color of important bars...
for i in p.info:
 if type(i)=3D=3Ddatetime:
 index =3D p.dates.index(i)
 if index:
 p1[index].set_facecolor('r')
# Set axis, grid properties & use dates as xticks
title('kWh/Dygn')
ylabel('kWh')
axis([-1,N,0,110])
locs, labels =3D xticks(ind, p.dates_string)
setp(labels, 'rotation', '270', 'ha', 'center', fontsize=3D10,
family=3D'monospace')
xgridlines =3D getp(gca(), 'xgridlines')
ygridlines =3D getp(gca(), 'ygridlines')
setp(ygridlines, 'linestyle', '-')
setp(xgridlines, 'linestyle', 'None')
ax =3D subplot(111)
ax.yaxis.set_major_locator(MultipleLocator(10)) # Set y-gridlines=20
multiples of 10
grid(True)
text(0,85, p.info_string, bbox=3Ddict(facecolor=3D'darkturquoise', alpha=3D=
0.9))
# Store graph as image
savefig('el', dpi=3D80, orientation=3D'landscape', format=3D'png')
show()
=3D
--=20
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