def f_ext(numdensity):
# Fsolve might need to go outside of our minimum or maximum density that RG was used with, thus this function...
# ... sets the values of the free energy outside those bounds.
if numdensity > 0.0001 and numdensity < max_fillingfraction_handled / (
4 * np.pi / 3):
return finterp(numdensity)
return RG.fiterative(temp, numdensity, 0)
def _create_colors(self, number_of_items):
"""Returning a list of lists with RGB code, where the size of the list
is equals the number_of_items"""
colors = []
for i in range(number_of_items):
value = float(i) / float(number_of_items)
colors.append(RG.rg(value))
return colors
def firstPass():
global f01interp
f01interp=lambda n: RG.fiterative(temp,n,0)
data=[]
t = time.time()
lastprint = t
for i in range(numdata):
n = numdensity[i]
print "%d of %d: "%(i,numdata),
free_energy = RG_first_pass(temp,n,1)
data.append([n,free_energy])
elapsed = time.time() - t
print(elapsed)
np.savetxt(fsave,data)
def RG_dfi(n):
maxn = (max_fillingfraction_handled+0.0001)/sphere_volume
# warning: Forte defines x as a density, we define it
# as a dimensionless quantity that scales the density.
maxx = np.minimum(1,maxn/n-1)
if abs(maxx) < 1e-42:
print 'maxx is zero'
print 'maxx is zero'
print 'maxx is zero'
print 'maxx is zero'
print 'maxx is zero'
T=temp
# eqn (5) from Forte 2011:
IDvalue = ID2(n, maxx)
IDvalueStar = ID2star(n, maxx)
return -k_B*T*(IDvalue-IDvalueStar)/RG.VD(fn) # eqn (7), Forte 2011
def get_data(year, month, var, depth, title_name = 'ESTOCver03'):
import ESTOCver01
import ESTOCver02
import ESTOCver03
import ORAS4
import MOAA_GPV
import GECCO2
import WOA01
import HadISST
import ERSST
import COBESST
import RG
import ERA
if title_name == 'ESTOCver01':
data = ESTOCver01.masuda_data_read(year, month, var, depth)
elif title_name == 'ESTOCver02':
data = ESTOCver02.nc_read(year, month, var, depth)
elif title_name == 'ESTOCver03':
data = ESTOCver03.masuda_data_read(year, month, var, depth)
elif title_name == 'MOAA_GPV':
data = MOAA_GPV.nc_read(year, month, var, depth)
elif title_name == 'ORAS4':
data = ORAS4.nc_read(year, month, var, depth)
elif title_name == 'GECCO2':
data = GECCO2.grib_read(year, month, var, depth)
elif title_name == 'WOA01':
data = WOA01.nc_read(month, var, depth)
elif title_name == 'COBESST':
data = COBESST.nc_read(year, month)
elif title_name == 'HadISST':
data = HadISST.nc_read(year, month)
elif title_name == 'ERSST':
data = ERSST.nc_read(year, month)
elif title_name == 'Roemmich_Gilson':
data = RG.nc_read(year, month, var, depth)
elif title_name == 'ERA':
data = ERA.get_data(year, month, var) # これで得られるデータはインド洋領域のみなので注意。
else:
raise Exception('error! your product_n is not valid!')
return data
def f01_ext(numdensity):
if numdensity > 0.0008 and numdensity < max_fillingfraction_handled/sphere_volume:
return f01interp(numdensity)
return RG.fiterative(temp,numdensity,0)
def integrand_ID2star(n,maxpower,x):
argument = np.exp(-maxpower-RG.VD(fn)/k_B/temp*fbarD(temp,n,x,fn))
return argument
def f0(n):
return RG.fiterative(temp,n,0)
def integrand_ID2(n,maxpower,x):
argument = np.exp(-maxpower-RG.VD(fn)/k_B/temp*(fbarD(temp,n,x,fn) + ubarD(temp,n,x,fn)))
## integrandIDlistn.append(n)
## integrandIDlistx.append(x)
## integrandIDlistarg.append(argument)
return argument
def f_ext(numdensity):
# Fsolve might need to go outside of our minimum or maximum density that RG was used with, thus this function...
# ... sets the values of the free energy outside those bounds.
if numdensity > 0.0001 and numdensity < 0.2:
return finterp(numdensity)
return RG.fiterative(temp,numdensity,0)
def f05_ext(numdensity):
if numdensity > 0.0001 and numdensity < 0.2:
return f05interp(numdensity)
return RG.fiterative(temp, numdensity, 0)
def plotphi(T, n, npart, i):
plt.plot(n * RG.sigma ** 3 * np.pi / 6, RG.phi(T, n, npart, i))
plt.ylabel(r"$\phi$")
plt.xlabel(r"$\eta$")
def plotID_integrand(x):
plt.plot(x, RG.integrand_ID(T, x, 0))
plt.ylabel("integrand of ID")
plt.xlabel("amplitude of wave-packet")
from __future__ import division
import SW
import RG
T = 5
n = 0.02
print ' SW; T = %d; n = %0.2f; f = %0.4f'%(T,n,SW.f(T,n))
print '\n'
for i in range (2):
print ' RG; i = %d; T = %d; n = %0.2f; f = %0.4f'%(i,T,n,RG.ftot(T,n,i))
def f00_tot(n):
return RG.ftot(temp, n, 0)
def f05_ext(numdensity):
if numdensity > 0.0001 and numdensity < 0.2:
return f05interp(numdensity)
return RG.fiterative(temp,numdensity,0)
def f05_tot(n):
return f05_ext(n) + RG.a1SW(n)*n
def f00_tot(n):
return RG.ftot(temp,n,0)
def f05_tot(n):
return f05_ext(n) + RG.a1SW(n) * n
import pylab as plt
import SW
import RG
eta_conv = SW.sigma**3 * plt.pi / 6
n = plt.linspace(1e-8, 0.2, 10000)
### Low temp ###
T = 0.3
npart0 = 0.0462316928818
npart1 = 0.0776670124628
plt.figure()
plt.plot(n * eta_conv, RG.phi(T, n, npart0, 0), label='i=0')
plt.plot(n * eta_conv, RG.phi(T, n, npart1, 1), label='i=1')
plt.title('T = %0.2f' % T)
plt.ylabel(r'$\phi$')
plt.xlabel(r'$\eta$')
plt.ylim(-0.04, 0.1)
plt.xlim(0, 0.7)
plt.legend(loc=0)
plt.savefig('figs/phi-RG-lowT.pdf')
### High Temp ###
T = 1.32
npart0 = 0.0360850913603
def fns_ext(numdensity,i):
if numdensity > 0.0001 and numdensity < 0.2:
return fns[i](numdensity)
return RG.fiterative(temp[i],numdensity,0)
import matplotlib, sys
if 'show' not in sys.argv:
matplotlib.use('Agg')
import pylab
import SW
import RG
eta_conv = SW.sigma**3*pylab.pi/6
n = pylab.linspace(0,0.2,10000)
T = 0.3
npart = 0.0462316928818
pylab.plot(n*eta_conv,SW.phi(T,n,npart),'g-',label='SW')
pylab.plot(n*eta_conv,RG.phi(T,n,npart,0),'r-',label='SW+RG; i=0')
pylab.plot(n*eta_conv,RG.phi(T,n,npart,1),'b--',label='SW+RG; i=1')
# pylab.plot(n*eta_conv,SW.f(T,n),'g-',label='SW')
# pylab.plot(n*eta_conv,RG.ftot(T,n,0),'r--',label='SW+RG; i=0')
# pylab.plot(n*eta_conv,RG.ftot(T,n,1),'b--',label='SW+RG; i=1')
pylab.title('T = %0.2f'%T)
pylab.ylabel(r'$\phi$')
# pylab.ylabel(r'$f$')
pylab.xlabel(r'$\eta$')
pylab.legend(loc=0)
pylab.savefig('figs/SW-RG-compare.pdf')
pylab.show()
def plotID_ref_integrand(x):
plt.plot(x, RG.integrand_ID_ref(x))
plt.ylabel("integrand of ID_ref")
plt.xlabel("amplitude of wave-packet")
def f_tot(n):
# Returns total free energy data with the missing a1SW(n) term that was not used in RG process
return f_ext(n) + RG.a1SW(n)*n
import pylab as plt
import SW
import RG
eta_conv = SW.sigma**3*plt.pi/6
n = plt.linspace(1e-8,0.2,10000)
### Low temp ###
T = 0.3
npart0 = 0.0462316928818
npart1 = 0.0776670124628
plt.figure()
plt.plot(n*eta_conv,RG.phi(T,n,npart0,0),label='i=0')
plt.plot(n*eta_conv,RG.phi(T,n,npart1,1),label='i=1')
plt.title('T = %0.2f'%T)
plt.ylabel(r'$\phi$')
plt.xlabel(r'$\eta$')
plt.ylim(-0.04,0.1)
plt.xlim(0,0.7)
plt.legend(loc=0)
plt.savefig('figs/phi-RG-lowT.pdf')
### High Temp ###
T = 1.32
npart0 = 0.0360850913603
def plotphi_old(T,n,npart,i,label): plt.plot(n*eta_conv,RG1.phi(T,n,npart,i),label=label)
)
exit()
print(" Calculating coplannarity...")
#mod_curv=classifier(25*curvatures)
mod_curv = curvatures
inp = input(
"Do you want to do the region growing? (If this is the first time you are running the code, press y ) (y/n) "
)
if (inp == 'y'):
import RG
RG.main()
"""
plane_normal, plane_seed, grand_nei=region_growing2(normals, indices, mod_curv, total, curvatures, k)
np.savetxt('Pnormal3.out', plane_normal, delimiter=',')
#np.savetxt('Gnei.out', grand_nei, delimiter=',')
try:
os.unlink('Gnei3.txt')
except:
print("could not delete")
try:
os.unlink('Pseed3.txt')
except:
print()
def newphi(T, n, npart, i):
return RG.phi(T, n, npart, i) - delta_mu * n
def f_tot(n):
# Returns total free energy data with the missing a1SW(n) term that was not used in RG process
return f_ext(n) + RG.a1SW(n) * n
def npart(iterations):
# Initial conditions; dependent on you system
T = 0.1
nparticular = 0.08 / (RG.sigma**3 * np.pi / 6
) # using finite differences df_dn
# nparticular = 0.155/(RG.sigma**3*np.pi/6) # using analytic df_nd
# T = 0.68
# nparticular = 0.0414/(RG.sigma**3*np.pi/6)
N = 20 # For publication plots, make this bigger (40? 80? 100? You decide!)
Tc = 1.33
Tlow = T
# Bounds of minimization.
# Use range that works for many temperatures
# Left (vapor)
a_vap = 1e-10 / (RG.sigma**3 * np.pi / 6)
c_vap = nparticular
# Right (liquid)
a_liq = nparticular
c_liq = 0.75 / (RG.sigma**3 * np.pi / 6)
###############################
# Open file for output
fout = open('figs/npart_RG-i%d-out.dat' % iterations, 'w')
# label the columns of the output
fout.write(
'#T nvapor nliquid phi(nvap) phi(nliq) nparticular\n'
) # phi_avg')
sys.stdout.flush()
# Do first temperature before the loop
nvapor, phi_vapor = minmax_RG.minimize(RG.phi, T, a_vap, c_vap,
nparticular, iterations)
print 'initial nvap,phi_vap', nvapor, phi_vapor
nliquid, phi_liquid = minmax_RG.minimize(RG.phi, T, a_liq, c_liq,
nparticular, iterations)
print 'initial nliq,phi_liq', nliquid, phi_liquid
print 'initial npart', nparticular * (RG.sigma**3 * np.pi / 6)
#while T < 1.4:
for j in xrange(0, N + 1):
T = (Tc - Tlow) * (1 - ((N - j) / N)**4) + Tlow
fout.flush()
# Starting point for new nparticular is abscissa of max RG.phi with old nparticular
nparticular = minmax_RG.maximize(RG.phi, T, nvapor, nliquid,
nparticular, iterations)
# I'm looking at the minima of RG.phi
c_vap = nparticular
a_liq = nparticular
nvapor, phi_vapor = minmax_RG.minimize(RG.phi, T, c_vap, a_vap,
nparticular, iterations)
nliquid, phi_liquid = minmax_RG.minimize(RG.phi, T, a_liq, c_liq,
nparticular, iterations)
tol = 1e-5
fnpart = RG.phi(T, nparticular, nparticular, iterations)
# Compare the two minima in RG.phi
while np.fabs(phi_vapor - phi_liquid) / np.fabs(fnpart) > tol:
delta_mu = (phi_liquid - phi_vapor) / (nliquid - nvapor)
def newphi(T, n, npart, i):
return RG.phi(T, n, npart, i) - delta_mu * n
nparticular = minmax_RG.maximize(newphi, T, nvapor, nliquid,
nparticular, iterations)
fnpart = RG.phi(T, nparticular, nparticular, iterations)
nvapor, phi_vapor = minmax_RG.minimize(RG.phi, T, a_vap, c_vap,
nparticular, iterations)
nliquid, phi_liquid = minmax_RG.minimize(RG.phi, T, a_liq, c_liq,
nparticular, iterations)
fout.write(str(T))
fout.write(' ')
fout.write(str(nvapor))
fout.write(' ')
fout.write(str(nliquid))
fout.write(' ')
fout.write(str(phi_vapor))
fout.write(' ')
fout.write(str(phi_liquid))
fout.write(' ')
fout.write(str(nparticular))
fout.write('\n')
sys.stdout.flush()
print ' T, etaVap, etaLiq', T, nvapor / (
RG.sigma**3 * np.pi / 6), nliquid / (RG.sigma**3 * np.pi / 6)
fout.close()
print(" Calculating coplannarity...")
#mod_curv=classifier(25*curvatures)
mod_curv=curvatures
inp=input("Do you want to do the region growing? (If this is the first time you are running the code, press y ) (y/n) ")
if (inp=='y'):
import RG
RG.main()
"""
plane_normal, plane_seed, grand_nei=region_growing2(normals, indices, mod_curv, total, curvatures, k)
np.savetxt('Pnormal3.out', plane_normal, delimiter=',')
#np.savetxt('Gnei.out', grand_nei, delimiter=',')
try:
os.unlink('Gnei3.txt')
except:
print("could not delete")
try:
os.unlink('Pseed3.txt')
except:
print()
def plotphi_old(T, n, npart, i, label):
plt.plot(n * eta_conv, RG1.phi(T, n, npart, i), label=label)
def onlyPower(n,x,i):
return (-RG.VD(i)/k_B/temp*(fbarD(temp,n,x,i) + ubarD(temp,n,x,i)))
def fns_tot(n, i):
return fns_ext(n, i) + RG.a1SW(n) * n
def ubarD(T,n,x,i):
return (RG.u(temp,n*(1+x),0,i) + RG.u(temp,n*(1-x),0,i))/2 - RG.u(temp,n,0,i)
def fns_ext(numdensity, i):
if numdensity > 0.0001 and numdensity < 0.2:
return fns[i](numdensity)
return RG.fiterative(temp[i], numdensity, 0)
def onlyPowerStar(n,x,i):
return (-RG.VD(i)/k_B/temp*fbarD(temp,n,x,i))
for i in xrange(0, N + 1):
T = (Tc - Tlow) * (1 - ((N - i) / N) ** 4) + Tlow
fout.flush()
# Starting point for new nparticular is abscissa of max RG.phi with old nparticular
nparticular = minmax_RG.maximize(RG.phi, T, nvapor, nliquid, nparticular, i)
# I'm looking at the minima of RG.phi
c_vap = nparticular
a_liq = nparticular
nvapor, phi_vapor = minmax_RG.minimize(RG.phi, T, c_vap, a_vap, nparticular, i)
nliquid, phi_liquid = minmax_RG.minimize(RG.phi, T, a_liq, c_liq, nparticular, i)
tol = 1e-5
fnpart = RG.phi(T, nparticular, nparticular, i)
# Compare the two minima in RG.phi
while np.fabs(phi_vapor - phi_liquid) / np.fabs(fnpart) > tol:
delta_mu = (phi_liquid - phi_vapor) / (nliquid - nvapor)
def newphi(T, n, npart, i):
return RG.phi(T, n, npart, i) - delta_mu * n
nparticular = minmax_RG.maximize(newphi, T, nvapor, nliquid, nparticular, i)
fnpart = RG.phi(T, nparticular, nparticular, i)
nvapor, phi_vapor = minmax_RG.minimize(RG.phi, T, a_vap, c_vap, nparticular, i)
nliquid, phi_liquid = minmax_RG.minimize(RG.phi, T, a_liq, c_liq, nparticular, i)
fout.write(str(T))
def RG_first_pass(T,n,i):
fnaught = RG.SWfid(T,n) + RG.SWfhs(T,n) + RG.a2(n)/k_B/T*n # SW (and Hughes) a2/kT is the same as Forte's f2
f = fnaught
return f + RG_dfi(n)
def npart(iterations):
# Initial conditions; dependent on you system
T = 0.1
nparticular = 0.08/(RG.sigma**3*np.pi/6) # using finite differences df_dn
# nparticular = 0.155/(RG.sigma**3*np.pi/6) # using analytic df_nd
# T = 0.68
# nparticular = 0.0414/(RG.sigma**3*np.pi/6)
N = 20 # For publication plots, make this bigger (40? 80? 100? You decide!)
Tc = 1.33
Tlow = T
# Bounds of minimization.
# Use range that works for many temperatures
# Left (vapor)
a_vap = 1e-10/(RG.sigma**3*np.pi/6)
c_vap = nparticular
# Right (liquid)
a_liq = nparticular
c_liq = 0.75/(RG.sigma**3*np.pi/6)
###############################
# Open file for output
fout = open('figs/npart_RG-i%d-out.dat'%iterations,'w')
# label the columns of the output
fout.write('#T nvapor nliquid phi(nvap) phi(nliq) nparticular\n')# phi_avg')
sys.stdout.flush()
# Do first temperature before the loop
nvapor,phi_vapor = minmax_RG.minimize(RG.phi,T,a_vap,c_vap,nparticular,iterations)
print 'initial nvap,phi_vap',nvapor,phi_vapor
nliquid,phi_liquid = minmax_RG.minimize(RG.phi,T,a_liq,c_liq,nparticular,iterations)
print 'initial nliq,phi_liq',nliquid,phi_liquid
print 'initial npart',nparticular*(RG.sigma**3*np.pi/6)
#while T < 1.4:
for j in xrange(0,N+1):
T = (Tc - Tlow)*(1 - ((N-j)/N)**4) + Tlow
fout.flush()
# Starting point for new nparticular is abscissa of max RG.phi with old nparticular
nparticular = minmax_RG.maximize(RG.phi,T,nvapor, nliquid, nparticular,iterations)
# I'm looking at the minima of RG.phi
c_vap = nparticular
a_liq = nparticular
nvapor,phi_vapor = minmax_RG.minimize(RG.phi,T,c_vap,a_vap,nparticular,iterations)
nliquid,phi_liquid = minmax_RG.minimize(RG.phi,T,a_liq,c_liq,nparticular,iterations)
tol = 1e-5
fnpart = RG.phi(T, nparticular, nparticular, iterations)
# Compare the two minima in RG.phi
while np.fabs(phi_vapor - phi_liquid)/np.fabs(fnpart) > tol:
delta_mu = (phi_liquid - phi_vapor)/(nliquid - nvapor)
def newphi(T, n, npart, i):
return RG.phi(T, n, npart, i) - delta_mu*n
nparticular = minmax_RG.maximize(newphi,T,nvapor,nliquid,nparticular,iterations)
fnpart = RG.phi(T, nparticular, nparticular, iterations)
nvapor,phi_vapor = minmax_RG.minimize(RG.phi,T,a_vap,c_vap,nparticular,iterations)
nliquid,phi_liquid = minmax_RG.minimize(RG.phi,T,a_liq,c_liq,nparticular,iterations)
fout.write(str(T))
fout.write(' ')
fout.write(str(nvapor))
fout.write(' ')
fout.write(str(nliquid))
fout.write(' ')
fout.write(str(phi_vapor))
fout.write(' ')
fout.write(str(phi_liquid))
fout.write(' ')
fout.write(str(nparticular))
fout.write('\n')
sys.stdout.flush();
print ' T, etaVap, etaLiq',T,nvapor/(RG.sigma**3*np.pi/6),nliquid/(RG.sigma**3*np.pi/6)
fout.close()
def newphi(T, n, npart, i):
return RG.phi(T, n, npart, i) - delta_mu*n
def fns_tot(n,i):
return fns_ext(n,i) + RG.a1SW(n)*n
