mccoys
commented
3 years ago This is not a question about Smilei but about the visualization software (probably paraview). Please refer to their documentation. Note that this place is not for getting general help, but for reporting bugs or problems with Smilei.
Respected Sir,
I need 3D visualization of my simulation data. I am using paraview with vtk data format. But I can't get proper visual. I am attaching my simulation code and vtk data.
import numpy import math
l0 = 2.0math.pi # laser wavelength [in code units] t0 = l0 # optical cycle Lsimx = 300.l0 # length of the simulation box in x (= 240 mum) Lsimy = 80l0 # length of the simulation box in y (= 64 mum) Lsimz = 80l0 # length of the simulation box in z (= 64 mum) Tsim = 375.*t0 resx = 16. resy = 2. resz = 2. # nb of cells on laser wavelength rest = resx/0.8 # nb of timesteps in one optical cycle dt = t0/rest
nx = 30016 # nb of cells along x-axis ny = 802 # nb of cells along y-axis nz = 80*2 # nb of cells along z-axis npatchx = 32 # nb of patches along x-axis
FWHMinI = 12.5l0 #(= 10 mum) waistinI = FWHMinI/(2.0math.sqrt(math.log(2.0))) waistinE = FWHMinI/math.sqrt(2.0math.log(2.0)) FWHMtinI = 8.0t0 #(= 21.3 fs) FWHMtinE = FWHMtinI*math.sqrt(2.0) #(= 30 fs)
diagEvery = int(37.5*t0/dt) # frequency of outputs(= 100 fs)
Main( geometry = "3Dcartesian", interpolation_order = 4,
timestep = dt, simulation_time = Tsim, cell_length = [l0/resx,l0/resy,l0/resz], grid_length = [Lsimx,Lsimy,Lsimz],
number_of_patches = [32,16,16], reference_angular_frequency_SI = 2.0math.pi3e8/0.8e-6, EM_boundary_conditions = [ ["silver-muller","silver-muller"], ["silver-muller","silver-muller"], ["silver-muller","silver-muller"] ], print_every = 100,
solve_poisson = False, random_seed = smilei_mpi_rank
)
MovingWindow( time_start = 0.9*Main.grid_length[0], velocity_x = 0.9997 )
LoadBalancing( initial_balance = False, every = 20, cell_load = 1.,
Species( name = "electron", position_initialization = "random", momentum_initialization = "cold", particles_per_cell = 4, mass = 1.0, charge = -1.0, number_density = 0.005734, mean_velocity = [0.0,0.0,0.0], pusher = "boris", time_frozen = 0.0, boundary_conditions = [["remove","remove"],["remove","remove"],["remove","remove"]], )
LaserGaussian3D( box_side = "xmin", a0 = 5.2, # intensity 5.8 e+19 omega = 1., focus = [0.,Main.grid_length[1]/2.,Main.grid_length[2]/2.], waist = waistinE,
polarization_phi = math.pi/2,
ellipticity = 1.,
time_envelope = tgaussian(start=0.0,fwhm=FWHMtinE,center=FWHMtinE,duration=2.0*FWHMtinE)
)
list_fields = ['Ex','Ey','Bz','Rho','Jx']
DIAGNOSTICS
DiagFields( every = diagEvery, fields = listfields, subgrid = numpy.s[::2, ::2, ::2] )
probe in x-y plane
DiagProbe( every = diagEvery, origin = [0., 0., Main.grid_length[2]/2.], corners = [ [Main.grid_length[0], 0., Main.grid_length[2]/2.], [0., Main.grid_length[1], Main.grid_length[2]/2.] ], number = [nx, ny], fields = list_fields )
probe in x-z plane
DiagProbe( every = diagEvery, origin = [0., Main.grid_length[1]/2., 0.], corners = [ [Main.grid_length[0], Main.grid_length[1]/2., 0.], [0., Main.grid_length[1]/2., Main.grid_length[2]] ], number = [nx, nz], fields = list_fields )
Image with 2250 timesteps: