inp = '''!HF RHF 6-31G
* int 0 1
C 0 0 0 0 0 0
C 1 0 0 1.52986 0 0
H 1 2 0 1.08439 111.200 0
H 1 2 3 1.08439 111.200 120
H 1 2 3 1.08439 111.200 -120
H 2 1 3 1.08439 111.200 %i
H 2 1 6 1.08439 111.200 120
H 2 1 6 1.08439 111.200 -120
*
'''
for i in range(-180,181, 12):
#l = 111.2 + i*0.02
name = 'mol'+str(i)+'_tor.inp'
out_file = open (name, 'w')
out_file.write(inp %(i))
out_file.close()
import subprocess
def energy(fineexe):
p = subprocess.Popen("/srv/databases/orca/orca "+fineexe,
shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out=p.communicate()[0]
out.splitlines()
for li in out.splitlines():
data=li.split("FINAL SINGLE POINT ENERGY")
if len(data)==2:
return(data[1].strip())
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
x_o=np.arange(-180,181, 12)
y=[]
for i in range(-180,181, 12):
name = 'mol'+str(i)+'_tor.inp'
en = energy(name)
y.append(float(en))
y_o = np.array(y)
#function is f(x)=k(b-x)^2 + a
fitfunc = lambda p, x: p[0]*pow(p[1]-x,2) + p[2] # Target function
errfunc = lambda p, x, y: fitfunc(p, x) - y # Error function
p0 = [1,1, -79] # Initial guess for the parameters
#p1, success = optimize.leastsq(errfunc, p0[:], args=(x_o, y_o))
#print "Optimized params:", p1
#Plot it
plt.plot(x_o, y_o, "ro",c='blue',alpha=0.5)
plt.xlim(-170,190)
Был получен график зависимости энергии соединения от для торсионного угла CC. Min - (-60°) и (60°) и (180°) и (180°).