def rdfExtend(rdfX,
rdfY,
ndens,
rmax=50.0,
Niter=5,
T=100.0,
rm=2.5,
eps=-1,
damped=True,
PY=True):
#rm and eps are parameters for the LJ (used as the PY closure)
#T is the temperature for the energy, effects smoothing near the transition point
#PY selects the Percus Yevick Closure for C(r), if false, the HNC criterion are used.
rdfX = list([r for r in rdfX])
rdfY = list(rdfY[:len(rdfX)])
drx = rdfX[1] - rdfX[0]
n = int(np.ceil(rmax / drx))
hrx = np.array([i * drx for i in range(n)])
hry = np.array([j - 1.0 for j in rdfY + [1.0 for i in hrx[len(rdfY):]]])
phi = [
eps * ((rm / r)**12 - 2 * (rm / r)**6) if r > 0 else eps *
((rm / 1E-10)**12 - 2 * (rm / 1E-10)**6) for r in hrx
]
beta = 1.0 / 8.6173324e-05 / T
icut = len(rdfX)
cr = np.array([0.0 for i in hry])
qr = np.array([0.0 for i in hry])
qrp = np.array([0.0 for i in hry])
for k in range(Niter):
qrp = calc_qpr_rltcut(icut, ndens, hrx, hry, cr, qr, qrp)
qrp = calc_qpr_rgtcut(icut, ndens, hrx, hry, cr, qr, qrp)
qrp = superSmooth(hrx, qrp, sigma=0.1)
qr = calc_qr(icut, ndens, hrx, hry, cr, qr, qrp)
hry = calc_hr_rgtcut(icut, ndens, hrx, hry, cr, qr, qrp)
cr = calc_cr_rgtcut(icut, ndens, hrx, hry, cr, qr, qrp, phi, beta, PY)
calc_hr(len(hrx), ndens, hrx, hry, cr, qr, qrp)
grExtended = np.array([i + 1.0 for i in hry])
f = open("/home/acadien/Dropbox/ozsf%d.dat" % rrcut, "w")
a = map(lambda x: "%f %f\n" % (x[0], x[1]), zip(hrx, grExtended))
f.writelines(a)
f.close()
f = open("/home/acadien/Dropbox/qrpsf%d.dat" % rrcut, "w")
a = map(lambda x: "%f %f\n" % (x[0], x[1]), zip(hrx, qrp))
f.writelines(a)
f.close()
return hrx, grExtended
def rdfExtend(rdfX,rdfY,ndens,rmax=50.0,Niter=5,T=100.0,rm=2.5,eps=-1,damped=True,PY=True):
#rm and eps are parameters for the LJ (used as the PY closure)
#T is the temperature for the energy, effects smoothing near the transition point
#PY selects the Percus Yevick Closure for C(r), if false, the HNC criterion are used.
rdfX=list([r for r in rdfX])
rdfY=list(rdfY[:len(rdfX)])
drx = rdfX[1]-rdfX[0]
n = int(np.ceil(rmax/drx))
hrx = np.array([i*drx for i in range(n)])
hry = np.array([j-1.0 for j in rdfY + [1.0 for i in hrx[len(rdfY):]]])
phi=[eps*((rm/r)**12-2*(rm/r)**6) if r>0 else eps*((rm/1E-10)**12-2*(rm/1E-10)**6) for r in hrx]
beta = 1.0/8.6173324e-05/T
icut = len(rdfX)
cr = np.array([0.0 for i in hry])
qr = np.array([0.0 for i in hry])
qrp = np.array([0.0 for i in hry])
for k in range(Niter):
qrp = calc_qpr_rltcut(icut,ndens,hrx,hry,cr,qr,qrp)
qrp = calc_qpr_rgtcut(icut,ndens,hrx,hry,cr,qr,qrp)
qrp = superSmooth(hrx,qrp,sigma=0.1)
qr = calc_qr (icut,ndens,hrx,hry,cr,qr,qrp)
hry = calc_hr_rgtcut (icut,ndens,hrx,hry,cr,qr,qrp)
cr = calc_cr_rgtcut (icut,ndens,hrx,hry,cr,qr,qrp,phi,beta,PY)
calc_hr(len(hrx),ndens,hrx,hry,cr,qr,qrp)
grExtended = np.array([i+1.0 for i in hry])
f= open("/home/acadien/Dropbox/ozsf%d.dat"%rrcut,"w")
a=map(lambda x:"%f %f\n"%(x[0],x[1]),zip(hrx,grExtended))
f.writelines(a)
f.close()
f= open("/home/acadien/Dropbox/qrpsf%d.dat"%rrcut,"w")
a=map(lambda x:"%f %f\n"%(x[0],x[1]),zip(hrx,qrp))
f.writelines(a)
f.close()
return hrx,grExtended
def rdfExtend(rdfX,rdfY,ndens,rmax=50.0,Niter=5,T=300.0,rm=2.5,epsilon=-1E-10,damped=True,PY=True):
#rm and eps are parameters for the LJ (used as the PY closure)
#T is the temperature for the energy, effects smoothing near the transition point
#PY selects the Percus Yevick Closure for C(r), if false, the HNC criterion are used.
rdfX=list(rdfX)[:-10]
rdfY=list(rdfY)[:-10]
drx = rdfX[1]-rdfX[0]
n = int(np.ceil(rmax/drx))
hrx = np.array([i*drx for i in range(n)])
hry = np.array([(j-1.0) for d,j in enumerate(rdfY + [1.0 for i in hrx[len(rdfY):]])])
phi=[ epsilon*((rm/r)**12-2*(rm/r)**6) if r>0 else 0.0 for r in hrx] #else eps*((rm/1E-10)**12-2*(rm/1E-10)**6) for r in hrx]
#import pylab as pl
#pl.plot(hrx,phi)
#pl.ylim(-10,100)
#pl.show()
#exit(0)
beta = 1.0/8.6173324e-05/T
icut = len(rdfX)
cr = np.array([0.0 for i in hry])
qr = np.array([0.0 for i in hry])
qrp = np.array([0.0 for i in hry])
hrlast = np.array(hry)
qrplast = np.zeros(len(hry))
Lmax=10.0
qbins=1024
minq,maxq,dq=0,Lmax,Lmax/qbins
qs=[i*dq+minq for i in range(qbins)]
qs[0]=1E-10
PY=True
eta = 0.2
qs=[i/100.0 for i in range(1,1000)]
import pylab as pl
kbreak=20
for k in range(Niter):
if k==kbreak: break
qrp = calc_qpr_rltcut(icut,ndens,hrx,hry,cr,qr,qrp)
qrp = calc_qpr_rgtcut(icut,ndens,hrx,hry,cr,qr,qrp)
qrp = eta*qrp + (1-eta)*qrplast
qr = calc_qr (icut,ndens,hrx,hry,cr,qr,qrp)
hry = calc_hr_rgtcut (icut,ndens,hrx,hry,cr,qr,qrp)
cr = calc_cr (icut,ndens,hrx,hry,cr,qr,qrp,phi,beta,PY)
#hry2 = calc_hr (icut,ndens,hrx,hry,cr,qr,qrp)
sq = calcSq(ndens,hrx,hry,qs)
#pl.plot(hrx,hry,label=str(k),c=vizSpec(float(k)/kbreak))
pl.plot(qs,sq,label=str(k),c=vizSpec(float(k)/kbreak))
err = np.power((hrlast-hry),2).sum()
print "step %d, error %f"%(k,err)
if err>100: break
hrlast = np.array(hry)
qrplast = np.array(qrp)
pl.legend(loc=0)
pl.show()
exit(0)
qrp = superSmooth(hrx,qrp,sigma=0.1)
calc_hr(len(hrx),ndens,hrx,hry,cr,qr,qrp)
pl.plot(hrx,hry,c="black",lw=2)
grExtended = np.array([i+1.0 for i in hry])
return cr,hrx,grExtended
if xCol == -1:
xdata = range(len(ydata))
else:
xdata = fdata[xCol]
#Smoothing:
xSmoothEnable = xSmoothEnables[i]
ySmoothEnable = ySmoothEnables[i]
xWAN = xWANs[i]
yWAN = yWANs[i]
xdataSmooth = []
ydataSmooth = []
if xSmoothEnable:
if switches["-gauss"]:
xdataSmooth = superSmooth(xdata, ydata, xWAN / 100.0)
else:
xdataSmooth = windowAvg(xdata, xWAN)
if ySmoothEnable:
if switches["-gauss"]:
ydataSmooth = superSmooth(xdata, ydata, yWAN / 100.0)
else:
ydataSmooth = windowAvg(ydata, yWAN)
#Correct for window offset, average introduces extra points that need to be chopped off
if not switches["-gauss"] and xSmoothEnable or ySmoothEnable:
WAN = max(xWAN, yWAN)
xdataSmooth = xdataSmooth[WAN / 2 + 1:WAN / -2]
ydataSmooth = ydataSmooth[WAN / 2 + 1:WAN / -2]
xdata = xdata[WAN / 2 + 1:WAN / -2]
ydata = ydata[WAN / 2 + 1:WAN / -2]
if xCol==-1:
xdata=range(len(ydata))
else:
xdata=fdata[xCol]
#Smoothing:
xSmoothEnable=xSmoothEnables[i]
ySmoothEnable=ySmoothEnables[i]
xWAN=xWANs[i]
yWAN=yWANs[i]
xdataSmooth=[]
ydataSmooth=[]
if xSmoothEnable:
if switches["-gauss"]:
xdataSmooth=superSmooth(xdata,ydata,xWAN/100.0)
else:
xdataSmooth=windowAvg(xdata,xWAN)
if ySmoothEnable:
if switches["-gauss"]:
ydataSmooth=superSmooth(xdata,ydata,yWAN/100.0)
else:
ydataSmooth=windowAvg(ydata,yWAN)
#Correct for window offset, average introduces extra points that need to be chopped off
if not switches["-gauss"] and xSmoothEnable or ySmoothEnable:
WAN=max(xWAN,yWAN)
xdataSmooth=xdataSmooth[WAN/2+1:WAN/-2]
ydataSmooth=ydataSmooth[WAN/2+1:WAN/-2]
xdata=xdata[WAN/2+1:WAN/-2]
ydata=ydata[WAN/2+1:WAN/-2]
