# generating the grid is the longest part
start = time.time()
mins = np.array((10, 0.25))
maxs = np.array((50, 0.75))
nums = np.array((10, 10))
try:
cf.load_grid('TASBL_Re0_growth_rates.h5')
except:
cf.grid_generator(mins, maxs, nums)
if comm.rank == 0:
cf.save_grid('TASBL_Re0_growth_rates')
end = time.time()
if comm.rank == 0:
print("grid generation time: {:10.5f} sec".format(end - start))
cf.root_finder()
crit = cf.crit_finder(find_freq=True)
if comm.rank == 0:
print("crit = {}".format(crit))
print("critical wavenumber alpha = {:10.5f}".format(crit[1]))
print("critical Re = {:10.5f}".format(crit[0]))
print("critical omega = {:10.5f}".format(crit[2]))
cf.save_grid('orr_sommerfeld_growth_rates')
cf.plot_crit()
else:
gr, idx, freq = EP.growth_rate({})
print("TASBL growth rate = {0:10.5e}".format(gr))
return val[0]
else:
return val
cf = CriticalFinder(shim, comm)
# generating the grid is the longest part
start = time.time()
gridl = 10
mins = np.array((0.5, 0.001))
maxs = np.array((2.0, 0.1))
num = np.array((gridl, gridl))
logs = np.array((False, True))
cf.grid_generator(mins, maxs, num, logs) # Rm = (0.5, 2.0); k = (0.001, 0.1) is not a bracketing interval for Pm = 1E-4. neither is (0.5, 2.0, 0.0001, 0.001)
end = time.time()
if comm.rank == 0:
print("grid generation time: {:10.5f} sec".format(end-start))
print(cf.grid)
print(cf.grid.shape)
cf.root_finder()
crit = cf.crit_finder()
if comm.rank == 0:
print("critical wavenumber k = {:10.5f}".format(crit[0]))
print("critical Rm = {:10.5f}".format(crit[1]))
cf.plot_crit(title = "growth_rates_Pm"+str(Pm), xlabel = r"$k_z$", ylabel = r"$\mathrm{Rm}$")
cf.save_grid('widegap_growth_rates')
start = time.time()
if no_slip:
mins = np.array((1000, 2))
maxs = np.array((3000, 4))
elif stress_free:
#657.5, 2.221
mins = np.array((400, 1.6))
maxs = np.array((1000, 3))
nums = np.array((20, 20))
try:
cf.load_grid('{}.h5'.format(file_name))
except:
cf.grid_generator(mins, maxs, nums)
if comm.rank == 0:
cf.save_grid(file_name)
end = time.time()
if comm.rank == 0:
print("grid generation time: {:10.5f} sec".format(end - start))
cf.root_finder()
crit = cf.crit_finder(find_freq=True)
if comm.rank == 0:
print("crit = {}".format(crit))
print("critical wavenumber k = {:10.5f}".format(crit[1]))
print("critical Ra = {:10.5f}".format(crit[0]))
print("critical freq = {:10.5f}".format(crit[2]))
cf.plot_crit(title=file_name, transpose=True, xlabel='kx', ylabel='Ra')
nx = 10
ny = 10
xpoints = np.linspace(2, 2.4, ny)
ypoints = np.linspace(550, 700, nx)
try:
cf.load_grid('{}.h5'.format(file_name))
except:
cf.grid_generator((xpoints, ypoints), sparse=True)
cf.save_grid(file_name)
end = time.time()
if comm.rank == 0:
logger.info("grid generation time: {:10.5f} sec".format(end - start))
logger.info("Beginning critical finding with root polishing...")
begin = time.time()
crit = cf.crit_finder(polish_roots=True, tol=1e-5)
end = time.time()
logger.info("critical finding/root polishing time: {:10.5f} sec".format(end -
start))
if comm.rank == 0:
print("crit = {}".format(crit))
print("critical wavenumber k = {:10.5f}".format(crit[0]))
print("critical Ra = {:10.5f}".format(crit[1]))
print("critical freq = {:10.5f}".format(crit[2]))
pax, cax = cf.plot_crit(xlabel=r'$k_x$', ylabel=r'$\mathrm{Ra}$')
pax.figure.savefig("rayleigh_benard_2d_growth_rates.png", dpi=300)
except:
start = time.time()
cf.grid_generator((xpoints, ypoints), sparse=True)
end = time.time()
if comm.rank == 0:
cf.save_grid(file_name)
logger.info("grid generation time: {:10.5f} sec".format(end - start))
crit = cf.crit_finder(polish_roots=False)
if comm.rank == 0:
logger.info("critical Rm = {:10.5f}, Q = {:10.5f}".format(
crit[1], crit[0]))
# create plot of critical parameter space
pax, cax = cf.plot_crit()
fig = pax.figure
# add an interpolated critical line
x_lim = cf.parameter_grids[0][0, np.isfinite(cf.roots)]
x_hires = np.linspace(x_lim[0], x_lim[-1], 100)
pax.plot(x_hires, cf.root_fn(x_hires), color='k')
fig.savefig('{}.png'.format(file_name), dpi=300)
# plot the spectrum for the critical mode
logger.info("solving dense eigenvalue problem for critical parameters")
EP.solve(parameters={"Q": crit[0], "Rm": crit[1]}, sparse=False)
ax = EP.plot_spectrum()
# mark critical mode
eps = 1e-2
mask = np.abs(EP.evalues.real) < eps