param.cax = np.array([-1, 1]) * .25
param.colorscheme = 'imposed'
param.generate_mp4 = True
# physics
param.forcing = False
param.noslip = False
param.diffusion = False
#
# add a passive tracer
param.additional_tracer = ['tracer']
grid = Grid(param)
param.Kdiff = 5e-4 * grid.dx
f2d = Fluid2d(param, grid)
model = f2d.model
xr, yr = grid.xr, grid.yr
vor = model.var.get('vorticity')
trac = model.var.get('tracer')
# set an initial small scale random vorticity field (white noise)
np.random.seed(42)
def set_x_and_k(n, L):
k = ((n // 2 + np.arange(n)) % n) - n // 2
return (np.arange(n) + 0.5) * L / n, 2 * np.pi * k / L
grid = Grid(param) # define the grid coordinates grid.xr, grid.yr and
# the mask, grid.msk. You may modify the mask just below
param.Kdiff=0.5e-4*grid.dx # diffusion coefficient (same for all
# tracers), there is a possibility to
# assign a different value for each tracer,
# see the experiment rayleigh_benard.py
# watch out, Kdiff should be adjusted when
# the resolution is changed
f2d = Fluid2d(param,grid) # define everything
model = f2d.model
xr,yr = grid.xr,grid.yr
vor = model.var.get('pv') # way to access the 2D array of a variable,
# vor is 2 array
# set an initial tracer field
vor[:] = 1e-2*random.normal(size=shape(vor))*grid.msk
y=vor[:]*1.
model.ope.fill_halo(y) # each variable is surrounded with a halo. Halo
# width is param.nh=3 grid points. The halo is
# used in the periodic case (xchannel,
# ychannel, perio) and when the model is used with MPI
vor[:]=y
