[766] | 1 | from dynamico import unstructured as unst |
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| 2 | from dynamico import dyn |
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| 3 | from dynamico import time_step |
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| 4 | from dynamico import DCMIP |
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| 5 | from dynamico import meshes |
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| 6 | from dynamico import xios |
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| 7 | from dynamico import precision as prec |
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| 8 | #from dynamico.meshes import Cartesian_mesh as Mesh |
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| 9 | import math as math |
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| 10 | import matplotlib.pyplot as plt |
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| 11 | import numpy as np |
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| 12 | import time |
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| 13 | import argparse |
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| 14 | |
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| 15 | parser = argparse.ArgumentParser() |
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| 16 | |
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| 17 | parser.add_argument("-mpi_ni", type=int, |
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| 18 | default=64, choices=None, |
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| 19 | help="number of x processors") |
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| 20 | parser.add_argument("-mpi_nj", type=int, |
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| 21 | default=64, choices=None, |
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| 22 | help="number of y processors") |
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| 23 | args = parser.parse_args() |
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| 24 | |
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| 25 | |
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| 26 | def thermal_bubble_3D(Lx,nx,Ly,ny,llm,ztop=1000., zc=350., |
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| 27 | rc=250, thetac=0.5, x0=0., y0=0.): |
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| 28 | Cpd, Rd, g, p0,theta0, T0 = 1004.5, 287.,9.81, 1e5, 300., 300. |
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| 29 | nqdyn = 1 |
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| 30 | |
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| 31 | Phi = lambda eta : g*ztop*eta |
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| 32 | p = lambda Phi : p0*np.exp(-Phi/(Rd*T0)) |
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| 33 | zz = lambda p: -(Rd*T0*np.log(p/p0))/g |
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| 34 | rr = lambda x,y,p: np.sqrt((x-x0)**2 + (y-y0)**2 + (zz(p)-zc)**2) |
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| 35 | sa = lambda x,y,p: rr(x,y,p) < rc |
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| 36 | deform = lambda x,y,p: (0.5*thetac*(1+np.cos(np.pi*rr(x,y,p)/rc)))*sa(x,y,p) |
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| 37 | temp = lambda p: theta0*(p/p0)**(Rd/Cpd) |
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| 38 | T = lambda x,y,p: deform(x,y,p) + temp(p) |
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| 39 | phi0 = 45. # Reference latitude North pi/4 (deg) |
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| 40 | omega = 7.292e-5 # Angular velocity of the Earth (s^-1) |
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| 41 | f0 = 2*omega*np.sin(phi0) |
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| 42 | lap = 0.005 # Lapse rate (K m^-1) |
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| 43 | Rd = 287.0 # Gas constant for dryy air (j kg^-1 K^-1) |
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| 44 | |
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| 45 | def eta(alpha) : return (1-(lap*ztop*alpha/(T0)))**(g/(Rd*lap)) # roughly equispaced levels |
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| 46 | #def eta(alpha) : return alpha/float(llm) |
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| 47 | |
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| 48 | filename = 'cart_%03d_%03d.nc'%(nx,ny) |
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| 49 | print 'Reading Cartesian mesh ...' |
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| 50 | def coriolis(lon,lat): return f0+0.*lon |
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| 51 | meshfile = meshes.DYNAMICO_Format(filename) |
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| 52 | radius = None |
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| 53 | #mesh = Mesh(nx,ny,llm,nqdyn,Lx,Ly,0.) |
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| 54 | print('----read--------') |
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| 55 | pmesh = meshes.Unstructured_PMesh(comm,meshfile) |
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| 56 | pmesh.partition_curvilinear(args.mpi_ni,args.mpi_nj) |
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| 57 | mesh = meshes.Local_Mesh(pmesh, llm, nqdyn, radius, coriolis) |
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| 58 | |
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| 59 | print(mesh.__dict__.keys()) |
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| 60 | |
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| 61 | alpha_k = (np.arange(llm) +.5)/llm |
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| 62 | alpha_l = (np.arange(llm+1)+ 0.)/llm |
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| 63 | x_ik, alpha_ik = np.meshgrid(mesh.lon_i, alpha_k, indexing='ij') |
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| 64 | y_ik, alpha_ik = np.meshgrid(mesh.lat_i, alpha_k, indexing='ij') |
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| 65 | x_il, alpha_il = np.meshgrid(mesh.lon_i, alpha_l, indexing='ij') |
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| 66 | y_il, alpha_il = np.meshgrid(mesh.lat_i, alpha_l, indexing='ij') |
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| 67 | x_ek, alpha_ek = np.meshgrid(mesh.lon_e, alpha_k, indexing='ij') |
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| 68 | y_ek, alpha_ek = np.meshgrid(mesh.lat_e, alpha_k, indexing='ij') |
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| 69 | |
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| 70 | print('alpha_l=',alpha_l) |
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| 71 | |
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| 72 | thermo = dyn.Ideal_perfect(Cpd, Rd, p0, T0) |
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| 73 | |
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| 74 | eta_il = eta(alpha_il) |
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| 75 | eta_ik = eta(alpha_ik) |
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| 76 | eta_ek = eta(alpha_ek) |
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| 77 | |
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| 78 | print('eta_il=',eta_il) |
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| 79 | #Phi_il = Phi(mesh.llp1/float(llm)) #llp is not defined in local mesh |
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| 80 | #Phi_ik = Phi((mesh.ll+.5)/llm) |
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| 81 | Phi_il = Phi(eta_il) |
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| 82 | Phi_ik = Phi(eta_ik) |
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| 83 | p_ik = p(Phi_ik) |
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| 84 | T_ik = T(x_ik, y_ik, p_ik) |
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| 85 | |
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| 86 | gas = thermo.set_pT(p_ik,T_ik) |
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| 87 | mass_ik = mesh.field_mass() |
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| 88 | for l in range(llm): |
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| 89 | mass_ik[:,l]=(Phi_il[:,l+1]-Phi_il[:,l])/(g*gas.v[:,l]) |
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| 90 | Sik, ujk, Wil = gas.s*mass_ik, mesh.field_u(), mesh.field_w() |
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| 91 | |
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| 92 | print 'ztop (m) = ', Phi_il[0,-1]/g, ztop |
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| 93 | ptop = p(g*ztop) |
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| 94 | print 'ptop (Pa) = ', gas.p[0,-1], ptop |
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| 95 | params=dyn.Struct() |
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| 96 | params.ptop=ptop |
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| 97 | params.dx=dx |
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| 98 | params.dx_g0=dx/g |
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| 99 | params.g = g |
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| 100 | #pbot = p(Phi_il[:,:,0]) |
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| 101 | #gas_bot = thermo.set_pT(pbot, temp(pbot)) |
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| 102 | # define parameters for lower BC |
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| 103 | pbot = p(eta_il[0]) |
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| 104 | print 'min p, T :', pbot.min(), temp(pbot/p0) |
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| 105 | gas_bot = thermo.set_pT(pbot, temp(pbot/p0)) |
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| 106 | params.pbot = gas_bot.p |
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| 107 | params.rho_bot = 1e6/gas_bot.v |
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| 108 | |
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| 109 | return thermo, mesh, params, prec.asnum([mass_ik,Sik,ujk,Phi_il,Wil]), gas |
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| 110 | |
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| 111 | with xios.Client() as client: # setup XIOS which creates the DYNAMICO communicator |
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| 112 | comm = client.comm |
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| 113 | mpi_rank, mpi_size = comm.Get_rank(), comm.Get_size() |
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| 114 | print '%d/%d starting'%(mpi_rank,mpi_size) |
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| 115 | |
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| 116 | #Lx, nx, llm, thetac, T, Nslice, courant = 2000., 100, 50, 30., 5., 10, 2.8 |
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| 117 | Lx, nx, llm, thetac = 2000., 200, 79, 30 |
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| 118 | #Lx, nx, llm, thetac, T, Nslice, courant = 3000., 75, 25, -30, 5., 10, 2.8 |
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| 119 | |
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| 120 | nqdyn, dx = 1, Lx/nx |
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| 121 | Ly,ny,dy = Lx,nx,dx |
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| 122 | |
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| 123 | g=9.81 |
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| 124 | unst.setvar('g',g) |
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| 125 | |
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| 126 | print('bubble call-----------') |
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| 127 | thermo, mesh, params, flow0, gas0 = thermal_bubble_3D(Lx,nx,Ly,ny,llm, thetac=thetac) |
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| 128 | print('bubble done-----------') |
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| 129 | |
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| 130 | |
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| 131 | # compute hybrid coefs from initial distribution of mass |
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| 132 | mass_bl,mass_dak,mass_dbk = meshes.compute_hybrid_coefs(flow0[0]) |
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| 133 | print 'Type of mass_bl, mass_dak, mass_dbk : ', [x.dtype for x in mass_bl, mass_dak, mass_dbk] |
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| 134 | unst.ker.dynamico_init_hybrid(mass_bl,mass_dak,mass_dbk) |
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| 135 | |
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| 136 | #dz = flow0[3].max()/(params.g*llm) |
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| 137 | #dt = courant*.5/np.sqrt(gas0.c2.max()*(dx**-2+dy**-2+dz**-2)) |
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| 138 | #dt = courant*.5/np.sqrt(gas0.c2.max()*(dx**-2+dy**-2)) |
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| 139 | #nt = int(math.ceil(T/dt)) |
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| 140 | #dt = T/nt |
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| 141 | #print 'Time step : %d x %g s' % (nt,dt) |
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| 142 | |
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| 143 | |
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| 144 | T, nslice, dt = 3600., 1, 3600. |
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| 145 | #T, nslice = 3600., 4 |
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| 146 | |
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| 147 | with xios.Context_Curvilinear(mesh,1, dt) as context: |
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| 148 | # now XIOS knows about the mesh and we can write to disk |
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| 149 | for i in range(48): # 2 days |
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| 150 | context.update_calendar(i) |
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| 151 | |
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| 152 | print 'send_field', i, gas0.T.shape |
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| 153 | # context.send_field_primal('ps', lat_i) |
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| 154 | context.send_field_primal('temp', gas0.T) |
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| 155 | context.send_field_primal('p', gas0.p) |
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| 156 | print(gas0.__dict__.keys()) |
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| 157 | print('size of T, p',np.shape(gas0.T),np.shape(gas0.p)) |
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| 158 | print('************DONE************') |
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| 159 | |
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| 160 | # #caldyn_thermo, caldyn_eta = unst.thermo_theta, unst.eta_mass |
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| 161 | # caldyn_thermo, caldyn_eta = unst.thermo_entropy, unst.eta_mass |
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| 162 | # #caldyn_thermo, caldyn_eta = unst.thermo_entropy, unst.eta_lag |
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| 163 | # |
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| 164 | # if False: # time stepping in Python |
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| 165 | # caldyn = unst.Caldyn_NH(caldyn_thermo,caldyn_eta, mesh,thermo,params,params.g) |
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| 166 | # scheme = time_step.ARK2(caldyn.bwd_fast_slow, dt) |
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| 167 | # def next_flow(m,S,u,Phi,W): |
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| 168 | # # junk,fast,slow = caldyn.bwd_fast_slow(flow, 0.) |
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| 169 | # return scheme.advance((m,S,u,Phi,W),nt) |
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| 170 | # |
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| 171 | # else: # time stepping in Fortran |
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| 172 | # scheme = time_step.ARK2(None, dt) |
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| 173 | # caldyn_step = unst.caldyn_step_NH(mesh,scheme,nt, caldyn_thermo,caldyn_eta, |
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| 174 | # thermo,params,params.g) |
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| 175 | # def next_flow(m,S,u,Phi,W): |
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| 176 | # # junk,fast,slow = caldyn.bwd_fast_slow(flow, 0.) |
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| 177 | # caldyn_step.mass[:,:], caldyn_step.theta_rhodz[:,:], caldyn_step.u[:,:] = m,S,u |
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| 178 | # caldyn_step.geopot[:,:], caldyn_step.W[:,:] = Phi,W |
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| 179 | # caldyn_step.next() |
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| 180 | # return (caldyn_step.mass.copy(), caldyn_step.theta_rhodz.copy(), caldyn_step.u.copy(), |
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| 181 | # caldyn_step.geopot.copy(), caldyn_step.W.copy()) |
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| 182 | # |
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| 183 | # m,S,u,Phi,W=flow0 |
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| 184 | # if caldyn_thermo == unst.thermo_theta: |
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| 185 | # s=S/m |
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| 186 | # theta = thermo.T0*np.exp(s/thermo.Cpd) |
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| 187 | # S=m*theta |
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| 188 | # title_format = 'Potential temperature at t=%g s (K)' |
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| 189 | # else: |
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| 190 | # title_format = 'Specific entropy at t=%g s (J/K/kg)' |
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| 191 | # |
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| 192 | # w=mesh.field_mass() |
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| 193 | # z=mesh.field_mass() |
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| 194 | # |
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| 195 | # for it in range(Nslice): |
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| 196 | # s=S/m ; s=.5*(s+abs(s)) |
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| 197 | # for l in range(llm): |
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| 198 | # #w[:,:,l]=.5*params.g*(W[:,:,l+1]+W[:,:,l])/m[:,:,l] |
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| 199 | # w[:,l]=.5*params.g*(W[:,l+1]+W[:,l])/m[:,l] |
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| 200 | # #z[:,:,l]=.5*(Phi[:,:,l+1]+Phi[:,:,l])/params.g |
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| 201 | # z[:,l]=.5*(Phi[:,l+1]+Phi[:,l])/params.g |
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| 202 | # |
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| 203 | # print 'ptop, model top (m) :', unst.getvar('ptop'), Phi.max()/unst.getvar('g') |
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| 204 | # jj=ny/2 |
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| 205 | # #xx,zz,ss,ww = mesh.xx[jj,:,:]/1000., z[jj,:,:]/1000., s[jj,:,:], w[jj,:,:] |
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| 206 | # #xx,zz,ss,ww = x_ik[jj,:]/1000., z[jj,:]/1000., s[jj,:], w[jj,:] |
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| 207 | # |
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| 208 | # #f, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize=(12,4)) |
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| 209 | # |
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| 210 | # #c=ax1.contourf(xx,zz,ss,20) |
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| 211 | # #ax1.set_xlim((-.5,.5)), ax1.set_xlabel('x (km)') |
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| 212 | # #ax1.set_ylim((0.,1.)), ax1.set_ylabel('z (km)') |
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| 213 | # #plt.colorbar(c,ax=ax1) |
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| 214 | # #ax1.set_title(title_format % (it*T,)) |
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| 215 | # |
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| 216 | # # plt.show() |
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| 217 | # |
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| 218 | # # plt.figure(figsize=(12,5)) |
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| 219 | # #c=ax2.contourf(xx,zz,ww,20) |
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| 220 | # #ax2.set_xlim((-.5,.5)), ax2.set_xlabel('x (km)') |
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| 221 | # #ax2.set_ylim((0.,1.)), ax2.set_ylabel('z (km)') |
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| 222 | # #plt.colorbar(c,ax=ax2) |
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| 223 | # #ax2.set_title('Vertical velocity at t=%g s (m/s)' % (it*T,)) |
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| 224 | # # plt.tight_layout() |
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| 225 | # # plt.show() |
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| 226 | # #plt.savefig('fig_NH_3D_bubble/%02d.png'%it) |
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| 227 | # |
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| 228 | # time1, elapsed1 =time.time(), unst.getvar('elapsed') |
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| 229 | # m,S,u,Phi,W = next_flow(m,S,u,Phi,W) |
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| 230 | # time2, elapsed2 =time.time(), unst.getvar('elapsed') |
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| 231 | # factor = 1000./nt |
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| 232 | # print 'ms per full time step : ', factor*(time2-time1), factor*(elapsed2-elapsed1) |
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| 233 | # factor = 1e9/(4*nt*nx*ny*llm) |
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| 234 | # print 'nanosec per gridpoint per full time step : ', factor*(time2-time1), factor*(elapsed2-elapsed1) |
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| 235 | # |
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