Hey,
the plots in the paper were generated using this little python script
which is attached. It uses matplotlib for drawin, you can also write out
data to visualize in gnuplot or any other tool.
for details: histogram2d.py --help
Cheers,
Victor
On 05/31/2011 03:07 PM, Patrick Kiley wrote:
> Dear all,
>
> I have what I hope is a very simple question.
>
> I am interested in making 2-d histograms of my bonded interactions in
> the same way described on page 21 of the votca manual.
>
> I issue the command
>
> vals vals.txt 1:bond:1 1:angle:1
>
> and get three columns of data for timestep, bond and angle.
>
> My question: does VOTCA provide a simple tool to convert columns 2 and
> 3 to gnuplot pm3d input or other 2-d plotting tools, or do I need to
> write my own script?
>
> cheers,
> Patrick Kiley
>
--
You received this message because you are subscribed to the Google Groups
"votca" group.
To post to this group, send email to [email protected].
To unsubscribe from this group, send email to
[email protected].
For more options, visit this group at
http://groups.google.com/group/votca?hl=en.
#!/usr/bin/python
# -*- coding: utf-8 -*-
# To change this template, choose Tools | Templates
# and open the template in the editor.
from pylab import *;
from numpy import *;
from optparse import OptionParser;
__author__="ruehle"
__date__ ="$Jun 9, 2010 6:03:05 PM$"
# some options parsing
usage = "usage: %prog [options] filename"
parser = OptionParser(usage)
parser.add_option("--nx", dest="nx", type="int", help="x bins", default=100)
parser.add_option("--ny", dest="ny", type="int", help="y bins", default=100)
parser.add_option("--xlabel", dest="xlbl", type="string", help="label for x axis", default="x")
parser.add_option("--ylabel", dest="ylbl", type="string", help="label for y axis", default="y")
parser.add_option("--cols", dest="cols", type="string", help="use columns e.g. 1:2", default="1:2")
parser.add_option("--gpout", dest="gpout", type="string", help="save data to use in gnuplot")
parser.add_option("--noshow", action="store_false", dest="show", default=True, help="don't show the histogram")
parser.add_option("--normalize", action="store_true", dest="normalize", default=False, help="Normalize the histogram")
(options, args) = parser.parse_args()
cols=options.cols.split(":")
if(size(cols)!=2):
parser.error("wrong format in cols, use 1:2")
if len(args) == 0:
parser.error("filename missing")
# load the data, change this!
data=loadtxt(args[0], usecols=(int(cols[0])-1, int(cols[1])-1));
# number of points for 2d histogram
nx=options.nx; ny=options.ny
# bounds of histogram - do not touch
xmin=min(data[:,0])
xmax=max(data[:,0])
ymin=min(data[:,1])
ymax=max(data[:,1])
ix = (xmax - xmin)
iy = (ymax - ymin)
dx = (xmax - xmin)/nx
dy = (ymax - ymin)/ny
# create histogram array - do not touch
hist2d=ndarray(shape=(ny, nx))
hist2d[:,:]=0;
increment=1.0
if(options.normalize == True):
increment = 1. / float(size(data, 0)) / float(dx*dy)
# loop over all points - do not change
for v in data:
hist2d[min((v[1]-ymin)/iy*ny, ny-1), min((v[0]-xmin)/ix*nx, nx-1)]+=increment
print(ymin,ymax,xmin,xmax)
if(options.gpout != None):
file = open(options.gpout, 'w')
for iiy in range(0,size(hist2d, 1)):
for iix in range(0,size(hist2d, 0)):
file.write(str(iix*dx + xmin) + " " + str(iiy*dy + ymin) + " " + str(hist2d[iiy,iix]) + "\n")
file.write("\n")
file.close()
if(options.show):
# you can output the histogram if needed
# savetxt('/people/thnfs/homes/ruehle/hist2d.txt', hist2d)
# create color table for nicer output - might be changed if needed
cdict = {'red': [(0.0, 1.0, 1.0),
(0.2/3., 1.0, 1.0),
(1.0/3., 1.0, 1.0),
(1.0, 0.0, 0.0)],
'green': [(0.0, 1.0, 1.0),
(0.2/3., 1.0, 1.0),
(1.0/3., 0.0, 0.0),
(1.0, 0.0, 0.0)],
'blue': [(0.0, 1.0, 1.0),
(0.2/3., 0.0, 0.0),
(1.0/3., 0.0, 0.0),
(1.0, 0.0, 0.0)]}
mymap = matplotlib.colors.LinearSegmentedColormap('my_colormap',cdict)
# display histogram - do not change
im=imshow(hist2d, origin='lower', aspect='auto', interpolation='bicubic',
cmap=mymap, extent=[xmin, xmax, ymin, ymax])
colorbar(im)
# axis labels - adjust to your values, you can use latex code
xlabel(options.xlbl);
ylabel(options.ylbl);
# show the image
show()
