else:
# Initialize a simulation form a restart file
[ ss , local_vars] = pyrandaRestart( problem ) # Restore simulation object
locals().update( local_vars ) # Restore local vars saved
time = ss.time # Resume time
dt = ss.deltat # Last deltat
import pdb
pdb.set_trace()
## Make a probe set for diagnostics
xprb = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # X-positions of the probes
yprb = [0.1, 0.2, 0.4, 0.55, 0.7, 0.8] # Y-positions of the probes
probes = pyrandaProbes(ss,x=xprb,y=yprb,z=None) # Create a probe set
## Variables to write to visualization
wvars = ['Yh','rho','u','v','p','beta','kappa','adiff','mu','T','op']
viz_freq = stop_time / float( Nviz )
viz_dump = time + viz_freq
## Frequency of restarts
dump_freq = 3000
## Frequency of probe queries
probe_freq = 10
## Plot the solution of 'rho'
if viz:
plt.figure(2)
plt.clf()
plt.contourf( xx,yy,v ,64 , cmap=cm.jet)
plt.contour( xx,yy,phi,[0.0])
plt.plot(xx, yy, 'k-', lw=0.5, alpha=0.5)
plt.plot(xx.T, yy.T, 'k-', lw=0.5, alpha=0.5)
plt.title(pvar)
plt.pause(.001)
# Make a probe set for diagnostics
x = [5.]*20
y = numpy.linspace(-10,10,20)
probes = pyrandaProbes(ss,x=x,y=y,z=None)
while tt > time:
# Update the EOM and get next dt
time = ss.rk4(time,dt)
dt = min( ss.variables['dt'].data * CFL, dt*1.1)
dt = min(dt, (tt - time) )
# Print some output
ss.iprint("%s -- %s --- %f" % (cnt,time,dt) )
cnt += 1