if __name__ == '__main__':
inputP = parseInput(sys.argv[1:] )
paraOpt = '-rdf -o -h -d '.split()
helpdoc = \
'''
Usage ./prog.py -rdf ; rdf file
-o ; output cdf ; if no present, sys.stdout
-d ; dimension
'''
print_help( inputP, paraOpt, helpdoc )
rdfdata = xvg( inputP['-rdf'] )
r= rdfdata[:,0]
g= rdfdata[:,1]
if int( inputP['-d'] ) == 2 :
cdf = scipy.integrate.cumtrapz( g * 2 * scipy.pi * r , r )
elif int( inputP['-d'] == 3) :
pass
else:
print >> sys.stderr, "Dimension not supported"
sys.exit(1)
if inputP.has_key('-o'):
import numpy as np
from common.lnx_util import parseInput , print_help, xvg
inputP = parseInput(sys.argv[1:])
paraOpt = ' -fexp -fsim '.split()
helpdoc=\
'''
Usage! ./prog.py
-fexp file1 ; input file for experimental form factor
-fsim file2 ; input file for simulation form factor
'''
print_help(inputP, paraOpt, helpdoc)
fexp = xvg(inputP['-fexp'])
fsim = xvg(inputP['-fsim'])
chi = 0
i=0
j=1
for q, fq, fqdelta in fexp:
# use linear interpolation to find simulated value
while not ( fsim[i,0] < q and fsim[j,0] >= q ):
i+=1
j+=1
#print q, fsim[i,0], fsim[j,0]
fqsim = ((fsim[j,0]-q) * fsim[i,1] + ( q-fsim[i,0]) * fsim[j,1] )/(fsim[j,0] - fsim[i,0])
tmp = ( (np.abs(fq) - np.abs(fqsim) ) / fqdelta )** 2
if __name__ == '__main__':
inputP = parseInput( sys.argv[1:] )
paraOpt = '-f -area -n -mod -h'.split(' ')
helpdoc = 'Usage ./prog.py -f box.xvg ; box information from g_energy \n'\
'-area 68.0 ; find most close area per lipid to 68 a^2 \n'\
'-n 64 ; number of lipids per leaflet \n'\
'-mod 10 ; the frame should also be divided by 10 ps, since we are saving by every 10 ps\n'
print_help(inputP, paraOpt, helpdoc)
fin = xvg(inputP['-f'])
target = float(inputP['-area'])
mod = int(inputP['-mod'])
nlipids = int(inputP['-n'])
apl = []
for i in fin:
apl.append( (i[0], abs(i[1]*i[2]/nlipids*100 - target ) ) )
apl.sort(key=lambda x:x[1] )
for i , data in enumerate(apl):
if data[0] % mod == 0:
print "%d ps, %f" % (data[0] , data[1])
break
import sys
from common.lnx_util import parseInput , print_help , xvg
import numpy as np
inputP = parseInput(sys.argv[1:])
paraOpt = "-f -col -n -h ".split(' ')
helpdoc = 'Usage ./prog.py -f file.xvg ; input \n'\
' -col px py pz lz ; col indx start from 0 \n'\
' -n 2 ; number of surfaces \n'\
print_help(inputP , paraOpt , helpdoc )
data = xvg(inputP['-f'])
colpx, colpy, colpz , collz = map( int, inputP['-col'] )
nsurfs = int( inputP['-n'] )
surfT = ( data[:, colpz] - ( data[:, colpx] + data[:, colpy] ) / 2.0 ) * data[:, collz]
surfT = surfT / nsurfs ;
for i in surfT :
print "%15.5f" % i