def nextStep():
data = np.load(
'FallData/D02-S02-E95-RE10-PFAC999-500k.npz') # load in steady state
#acquire data from file
Nice = data['Nice']
Niceoffset = data['Niceoffset']
Diffofx = data['Diffofx']
diffperdtEdgeAdjust = data['diffperdtEdgeAdjust']
Fliq = data['Fliq']
rainperdtTerr = data['rainperdtTerr']
Nbar = data['Nbar']
rainperdtTerrAdjust = data['rainperdtTerrAdjust']
Nstar = data['Nstar']
Nmono = data['Nmono']
phi = data['phi']
x = data['x']
initTime = data['t']
cnt = 0
n = len(x)
while cnt < 1100: #interval to animate
cnt += 1
# find edges
intValues = (Nice - Niceoffset).astype(int)
differences = np.diff(intValues)
stepsUp = mlab.find(differences > 0)
stepsDown = mlab.find(
differences < 0) + 1 #+1 so we are on lower side of edge
steps = np.append(stepsDown, stepsUp)
# adjust diffusion coefficient at edges
Dofx = copy.copy(Diffofx)
Dofx[steps] -= diffperdtEdgeAdjust
#diffuse liquid across surface
Fliq = ds.diffuse(Fliq, Dofx)
#incoming vapor
Fliq = Fliq + rainperdtTerr
Fliq[steps] = Fliq[steps] + rainperdtTerrAdjust[steps]
#equilibrate
for i in range(n):
deltaN = ds.getdeltaN(Nice[i], Fliq[i], Nbar, Nstar, Nmono, phi)
Fliq[i] += deltaN
Nice[i] -= deltaN
if cnt % 1 == 0:
yield x, Fliq, Nice, steps, cnt, initTime # send info for animation before looping again
def nextStep():
data = np.load('FallData/D02-S02-E95-RE10-PFAC999-500k.npz') # load in steady state
#acquire data from file
Nice = data['Nice']
Niceoffset = data['Niceoffset']
Diffofx = data['Diffofx']
diffperdtEdgeAdjust = data['diffperdtEdgeAdjust']
Fliq = data['Fliq']
rainperdtTerr = data['rainperdtTerr']
Nbar = data['Nbar']
rainperdtTerrAdjust = data['rainperdtTerrAdjust']
Nstar = data['Nstar']
Nmono = data['Nmono']
phi = data['phi']
x = data['x']
initTime = data['t']
cnt = 0
n = len(x)
while cnt < 1100: #interval to animate
cnt += 1
# find edges
intValues = (Nice-Niceoffset).astype(int)
differences = np.diff(intValues)
stepsUp = mlab.find(differences > 0)
stepsDown = mlab.find(differences < 0)+1 #+1 so we are on lower side of edge
steps = np.append(stepsDown, stepsUp)
# adjust diffusion coefficient at edges
Dofx = copy.copy(Diffofx)
Dofx[steps] -= diffperdtEdgeAdjust
#diffuse liquid across surface
Fliq = ds.diffuse(Fliq, Dofx)
#incoming vapor
Fliq = Fliq + rainperdtTerr
Fliq[steps] = Fliq[steps] + rainperdtTerrAdjust[steps]
#equilibrate
for i in range(n):
deltaN = ds.getdeltaN(Nice[i], Fliq[i], Nbar, Nstar, Nmono, phi)
Fliq[i] += deltaN
Nice[i] -= deltaN
if cnt%1==0:
yield x, Fliq, Nice, steps, cnt, initTime# send info for animation before looping again
def main():
sec1 = time.time()
# Parameters related to equilibrium
Nbar = 1.0 # new Nbar from VMD, 260K
Nstar = .9 / (2 * np.pi)
phi = 0.0
Nmono = 1.0
Niceoffset = ds.getNiceoffset(Nbar, Nstar, Nmono, phi)
# Want units in terms of micrometers and microseconds
n = 1000 # Number of points in simulation box
t = 10000 #still arbitrary timesteps #Total Simulation Time
deltaT = 2.0 #microseconds
deltaX = 1.0 #micrometers
Fliqstart = 1.5 #monolayers
current_time = 0
D = 2e-2 # micrometers^2/microseconds
#print "Dprime:", Dprime
deprate = .2 # Monolayers per microsecond (Hopefully, depends on how the scale translates in the x direction now that x and deltaX are smaller)
deprate_micronspersecond = deprate * 1e6 * 0.37e-3
#print deprate_micronspersecond
depratePFac = 0.99
#alphaTerr = 1.0 #Not in use yet
# Dependent Parameters
x = np.arange(
0, n, deltaX
) # used arange over linspace because it is more beautiful and easier to manipulate
#print "x:", x
boxpoints = len(x)
Fliq = np.zeros(boxpoints) + Fliqstart
Nice = np.zeros(boxpoints)
Dprime = D * deltaT / deltaX**2 # New diffperdt #Recast into 20 microns
#print "Dprime:", Dprime
xmid = max(x) / 2
depratep = deprate * deltaT * depratePFac
c = (deprate * deltaT - depratep) / xmid**2
depratesurface = (x - xmid)**2 * c + depratep
plt.clf()
sigma0 = 0.1
sigmapfac = 0.983
sigmastepmax = 0.2
sigmastepmin = sigmastepmax * sigmapfac
redux = sigmastepmax - sigmastepmin
sigmastep = redux * (x - xmid)**2 / xmid**2 + sigmastepmin
plt.plot(x, sigmastep)
#Pre equilibration
for i in range(boxpoints):
deltaN = ds.getdeltaN(Nice[i], Fliq[i], Nbar, Nstar, Nmono, phi)
Fliq[i] += deltaN
Nice[i] -= deltaN
#plt.figure(5)
#plt.clf()
#plt.plot(x, Nice, 'k', x, Fliq+Nice, 'b', x, Fliq, 'g')
Dprimesurface = np.zeros(boxpoints) + Dprime
Dprimeedge = 0.99 * Dprime
deprateedge = deprate * 0.1 * deltaT #Additional Deposition at the edge
dtmax = deltaX**2 / D
#print 'max dt is:', dtmax, 'current dt is:', deltaT
deltaN = np.zeros(np.shape(Fliq))
sigavg0 = []
sigavg250 = []
sigavg500 = []
for i in range(int(t / deltaT)):
#intvalues = (Nice-Niceoffset).astype(int)
#differences = np.diff(intvalues)
#stepsUp = mlab.find(differences > 0)
#stepsDown = mlab.find(differences < 0) + 1 # +1 so we are on lower side of the edge
#steps = np.append(stepsDown, stepsUp)
dprimecopy = copy.copy(Dprimesurface)
#dprimecopy[steps] = Dprimeedge
delta = (Fliq - (Nbar - Nstar)) / (2 * Nstar)
sigD = (sigmastep - delta * sigma0) / (1 + delta * sigma0)
depsurf = deprate * sigD * deltaT
sigavg0.append(sigD[0])
sigavg250.append(sigD[250])
sigavg500.append(sigD[500])
Fliq += depsurf
Fliq = ds.diffuse(Fliq, dprimecopy)
#Fliq = Fliq + (sigma - depratesurface * (maxF-Fliq)/maxF) # What is sigma? # Square maxF and Fliq?
for j in range(boxpoints):
deltaN[j] = ds.getdeltaN(Nice[j], Fliq[j], Nbar, Nstar, Nmono, phi)
Fliq += deltaN
Nice -= deltaN
minpoint = min(Nice)
print("Height of Ice", minpoint)
Nice -= minpoint
print("0:", np.mean(sigavg0))
print("250:", np.mean(sigavg250))
print("500:", np.mean(sigavg500))
plt.figure(4)
plt.clf()
plt.plot(x, Nice, 'k', x, Fliq + Nice, 'b', x, Fliq,
'g') #, x[steps], Fliq[steps], 'o')
sec2 = time.time()
print "Time taken:", int(
(sec2 - sec1) / 60), "min", (sec2 - sec1) % 60, "secs"
def main():
sec1 = time.time()
# Parameters related to equilibrium
Nbar = 1.0 # new Nbar from VMD, 260K
Nstar = .9/(2*np.pi)
phi = 0.0
Nmono = 1.0
# Want units in terms of micrometers and microseconds
n = 1000 # Number of points in simulation box
t = 100000 #still arbitrary timesteps #Total Simulation Time
deltaT = 5.0 #microseconds
deltaX = 1.0 #micrometers
Fliqstart = 1.5 #monolayers
D = 10e-2 # micrometers^2/microseconds
#print "Dprime:", Dprime
deprate = .2 # Monolayers per microsecond (Hopefully, depends on how the scale translates in the x direction now that x and deltaX are smaller)
#deprate_micronspersecond = deprate*1e6 * 0.37e-3
#print deprate_micronspersecond
#depratePFac = 0.99
#alphaTerr = 1.0 #Not in use yet
# Dependent Parameters
x = np.arange(0, n, deltaX) # used arange over linspace because it is more beautiful and easier to manipulate
boxpoints = len(x)
Fliq = np.zeros(boxpoints) + Fliqstart
Nice = np.zeros(boxpoints)
# Load them
npzfile = np.load('NeshData/test9.npz')
Fliq = npzfile['Fliq']
Nice = npzfile['Nice']
Dprime = D*deltaT/deltaX**2 # New diffperdt #Recast into 20 microns
xmid = max(x)/2
#depratep = deprate*deltaT * depratePFac
#c = (deprate*deltaT - depratep)/xmid**2
#depratesurface = (x-xmid)**2*c+depratep
plt.clf()
sigma0 = 0.1
sigmapfac = 0.99
sigmastepmax = 0.2
sigmastepmin = sigmastepmax * sigmapfac
redux = sigmastepmax - sigmastepmin
sigmastep = redux*(x-xmid)**2/xmid**2 + sigmastepmin
#plt.plot(x, sigmastep)
#Pre equilibration
for i in range(boxpoints):
deltaN = ds.getdeltaN(Nice[i],Fliq[i],Nbar,Nstar,Nmono,phi)
Fliq[i] += deltaN
Nice[i] -= deltaN
#plt.figure(5)
#plt.clf()
#plt.plot(x, Nice, 'k', x, Fliq+Nice, 'b', x, Fliq, 'g')
Dprimesurface = np.zeros(boxpoints) + Dprime
#Dprimeedge = 0.99 * Dprime
#deprateedge = deprate* 0.1*deltaT #Additional Deposition at the edge
dtmax = deltaX**2/D
print ('max dt is:', dtmax, 'current dt is:', deltaT)
deltaN = np.zeros(np.shape(Fliq))
sigavg0 = []
sigavg250 = []
sigavg500 = []
for i in range(int(t/deltaT)):
#intvalues = (Nice-Niceoffset).astype(int)
#differences = np.diff(intvalues)
#stepsUp = mlab.find(differences > 0)
#stepsDown = mlab.find(differences < 0) + 1 # +1 so we are on lower side of the edge
#steps = np.append(stepsDown, stepsUp)
dprimecopy = copy.copy(Dprimesurface)
#dprimecopy[steps] = Dprimeedge
delta = (Fliq - (Nbar - Nstar))/(2*Nstar)
sigD = (sigmastep - delta * sigma0)/(1+delta*sigma0)
depsurf = deprate * sigD * deltaT
sigavg0.append(sigD[0])
sigavg250.append(sigD[250])
sigavg500.append(sigD[500])
Fliq += depsurf
Fliq = ds.diffuse(Fliq, dprimecopy)
#Fliq = Fliq + (sigma - depratesurface * (maxF-Fliq)/maxF) # What is sigma? # Square maxF and Fliq?
for j in range(boxpoints):
deltaN[j] = ds.getdeltaN(Nice[j], Fliq[j], Nbar, Nstar, Nmono, phi)
Fliq += deltaN
Nice -= deltaN
minpoint = min(Nice)
print("Height of Ice", minpoint)
Nice -= minpoint
print("0:", np.mean(sigavg0))
print("250:", np.mean(sigavg250))
print("500:", np.mean(sigavg500))
print (np.mean(sigavg500)/np.mean(sigavg0))
plt.figure(4)
plt.clf()
plt.plot(x, Nice, 'k', x, Fliq+Nice, 'b', x, Fliq, 'g')#, x[steps], Fliq[steps], 'o')
sec2 = time.time()
print ("Time taken:", int((sec2-sec1)/60), "min", (sec2-sec1)%60, "secs")
saveit = True
if saveit:
np.savez_compressed('NeshData/test10.npz', Nice=Nice,
Fliq=Fliq, Nbar=Nbar, Nstar=Nstar,
x=x, t=t)
def main():
sec1 = time.time()
# Parameters related to equilibrium
Nbar = 1.0 # new Nbar from VMD, 260K
Nstar = .9/(2*np.pi)
phi = 0.0
Nmono = 1.0
Niceoffset = ds.getNiceoffset(Nbar, Nstar, Nmono, phi)
# Want units in terms of micrometers and microseconds
n = 1000 # Number of points in simulation box
t = 3000000 #still arbitrary timesteps #Total Simulation Time
deltaT = 1.0 #microseconds
deltaX = 1.5 #micrometers
Fliqstart = 1.5 #monolayers
current_time = 0
D = 2e-2 # micrometers^2/microseconds
#print "Dprime:", Dprime
deprate = .02 # Monolayers per microsecond (Hopefully, depends on how the scale translates in the x direction now that x and deltaX are smaller)
deprate_micronspersecond = deprate*1e6 * 0.37e-3
print deprate_micronspersecond
depratePFac = 0.999
#alphaTerr = 1.0 #Not in use yet
# Dependent Parameters
x = np.arange(0, n, deltaX) # used arange over linspace because it is more beautiful and easier to manipulate
#print "x:", x
boxpoints = len(x)
Fliq = np.zeros(boxpoints) + Fliqstart
Nice = np.zeros(boxpoints)
Dprime = D*deltaT/deltaX**2 # New diffperdt #Recast into 20 microns
print "Dprime:", Dprime
xmid = max(x)/2
depratep = deprate*deltaT * depratePFac
c = (deprate*deltaT - depratep)/xmid**2
depratesurface = (x-xmid)**2*c+depratep
#Pre equilibration
for i in range(boxpoints):
deltaN = ds.getdeltaN(Nice[i],Fliq[i],Nbar,Nstar,Nmono,phi)
Fliq[i] += deltaN
Nice[i] -= deltaN
#plt.figure(5)
#plt.clf()
#plt.plot(x, Nice, 'k', x, Fliq+Nice, 'b', x, Fliq, 'g')
Dprimesurface = np.zeros(boxpoints) + Dprime
Dprimeedge = 0.99 * Dprime
deprateedge = deprate* 0.1*deltaT #Additional Deposition at the edge
dtmax = deltaX**2/D
print 'max dt is:', dtmax, 'current dt is:', deltaT
deltaN = np.zeros(np.shape(Fliq))
for i in range(int(t/deltaT)):
intvalues = (Nice-Niceoffset).astype(int)
differences = np.diff(intvalues)
stepsUp = mlab.find(differences > 0)
stepsDown = mlab.find(differences < 0) + 1 # +1 so we are on lower side of the edge
steps = np.append(stepsDown, stepsUp)
dprimecopy = copy.copy(Dprimesurface)
dprimecopy[steps] = Dprimeedge
Fliq = ds.diffuse(Fliq, dprimecopy)
Fliq = Fliq + depratesurface
#Fliq[steps] = Fliq[steps] + deprateedge
for j in range(boxpoints):
deltaN[j] = ds.getdeltaN(Nice[j], Fliq[j], Nbar, Nstar, Nmono, phi)
Fliq += deltaN
Nice -= deltaN
minpoint = min(Nice)
Nice -= minpoint
plt.figure(4)
plt.clf()
plt.plot(x, Nice, 'k', x, Fliq+Nice, 'b', x, Fliq, 'g', x[steps], Fliq[steps], 'o')
sec2 = time.time()
print "Time taken:", int((sec2-sec1)/60), "min", (sec2-sec1)%60, "secs"
