def create_spng(spngname, grdname, str):
dimy, dimx, units = setstr(str)
grid = NF(grdname, 'r')
lon = grid.variables[dimx][:]
lat = grid.variables[dimy][:]
grid.close()
ff = NF(spngname, 'w', format='NETCDF3_CLASSIC')
ff.createDimension(dimy, np.size(lat))
ff.createDimension(dimx, np.size(lon))
ff.createVariable(dimy, 'd', (dimy, ))
ff.createVariable(dimx, 'd', (dimx, ))
ff.createVariable('Idamp', 'd', (
dimy,
dimx,
))
ff.close()
ff = NF(spngname, 'a')
ff.variables[dimx][:] = lon
ff.variables[dimy][:] = lat
ff.close()
def volume_flux(sname,gname,tind,lonind):
print lonind
ff=NF(sname,'r')
u=ff.variables['u'][-tind:,:,:,lonind:lonind+2]
thick=ff.variables['h'][-tind:,:,:,lonind]
time=ff.variables['Time'][-tind:]
ff.close()
ff=NF(gname,'r')
dyh=ff.variables['dyh'][:,lonind].flatten()
ff.close()
u=u[:,:,:,:-1]+0.5*np.diff(u,axis=3) #regrid
u=u[...,0]
thick=thick[...,0]
dyh=np.tile(dyh,(u.shape[0],u.shape[1],1))
U=thick*u*dyh
U=np.sum(U,axis=2)
U=U[:,:]/1e6
U1m=np.mean(U[:,0])
U2m=np.mean(U[:,1])
U1std=np.std(U[:,0])
U2std=np.std(U[:,1])
return U1m, U2m, U1std, U2std
def create_grd(grdname, lat, lon, str):
dimy, dimx, units = setstr(str)
ff = NF(grdname, 'w', format='NETCDF3_CLASSIC')
ff.createDimension(dimy, np.size(lat))
ff.createDimension(dimx, np.size(lon))
ff.createVariable(dimy, 'd', (dimy, ))
tmp = ff.variables[dimy]
if str == 'l':
setattr(tmp, "long_name", "Latitude")
elif str == 'x':
setattr(tmp, "long_name", "y dist")
setattr(tmp, "units", units)
ff.createVariable(dimx, 'd', (dimx, ))
tmp = ff.variables[dimx]
if str == 'l':
setattr(tmp, "long_name", "Longitude")
elif str == 'x':
setattr(tmp, "long_name", "x dist")
setattr(tmp, "units", units)
ff.createVariable('D', 'd', (
dimy,
dimx,
))
tmp = ff.variables['D']
setattr(tmp, "long_name", "Depth")
setattr(tmp, "units", "meter")
ff.close()
def create_bdy(bdyname, grdname, str):
dimy, dimx, units = setstr(str)
grid = NF(grdname, 'r')
lon = grid.variables[dimx][:]
lat = grid.variables[dimy][:]
grid.close()
ff = NF(bdyname, 'w', format='NETCDF3_CLASSIC')
ff.createDimension(dimy, np.size(lat))
ff.createDimension(dimx, np.size(lon))
ff.createDimension('interface', 3)
ff.createDimension('LAYER', 2)
ff.createVariable(dimy, 'd', (dimy, ))
ff.createVariable(dimx, 'd', (dimx, ))
ff.createVariable('interface', 'd', ('interface', ))
ff.createVariable('LAYER', 'd', ('LAYER', ))
ff.createVariable('ETA', 'd', (
'interface',
dimy,
dimx,
))
ff.createVariable('u', 'd', (
'LAYER',
dimy,
dimx,
))
ff.createVariable('v', 'd', (
'LAYER',
dimy,
dimx,
))
ff.close()
# copy lon/lat from grid
ff = NF(bdyname, 'a')
ff.variables[dimx][:] = lon
ff.variables[dimy][:] = lat
ff.close()
xs = 160.
xh = xh[xs:]
bot = bot[:, xs:]
if 1: #Alboran run90+
xs = 140.
xh = xh[xs:]
bot = bot[:, xs:]
bot[bot == 0.] = 0.1
bot[0, :] = 0.1
bot[-1, :] = 0.1 # dirty
md.create_grd(grdname, yh, xh, 'x')
grid = NF(grdname, 'a')
grid.variables['xh'][:] = xh
grid.variables['yh'][:] = yh
grid.variables['D'][:] = bot
grid.close()
#
print ""
print "lenlat: " + str(np.diff(yh)[0] * yh.shape[0])
print "lenlon: " + str(np.diff(xh)[0] * xh.shape[0])
print ""
print "lowlat: " + str(min(yh))
print "westlon: " + str(min(xh))
#
print "size: " + str(bot.shape)
plt.figure()
# -*- coding: utf-8 -*- #from Scientific.IO.NetCDF import NetCDFFile as NF from netCDF4 import Dataset as NF import matplotlib.pyplot as plt import numpy as np import mod_data as md import os as os import inspect as inspect rundir = os.path.dirname(inspect.getfile(inspect.currentframe())) grdname = rundir + '/../data/grd.nc' initname = rundir + '/../data/init.nc' bdyname = rundir + '/../data/bdy.nc' grid = NF(grdname, 'r') h = grid.variables['D'][:] lon = grid.variables['xh'][:] lat = grid.variables['yh'][:] grid.close() #fac=np.linspace(0.,-0.5,h.shape[1]) #eta1=-np.ones(h.shape)*np.tile(fac,(h.shape[0],1)) eta1 = np.zeros(h.shape) e2east = 80. eta2a = eta1 + e2east eta2b = h - 1e-9 #eta2b[eta2b<eta2a]=eta2a[eta2b<eta2a]+1e-9 fac = np.linspace(1, 0, 10) mat = np.ones(h.shape) [x1, x2] = np.meshgrid(fac, np.arange(mat.shape[0])) #mat[:,22:34]= x1;
line = file.readline()
ll = np.fromstring(line.rstrip(),
dtype=float,
count=-1,
sep=' ')
lon[:, jj, offs + ii] = lo
lat[:, jj, offs + ii] = la
file.close()
offs = offs + 120
oo = np.ones((1, 341, 720)) # make pressure (depth)
p = p_[:, None, None] * oo
ds = NF('wghc.nc', 'w', format='NETCDF4')
ds.createDimension('z', 45)
ds.createDimension('y', 341)
ds.createDimension('x', 720)
ds.createVariable('lat', 'd', ('z', 'y', 'x'))
ds.createVariable('lon', 'd', ('z', 'y', 'x'))
ds.createVariable('p', 'd', ('z', 'y', 'x'))
ds.createVariable('s', 'd', ('z', 'y', 'x')) # single precision!
ds.createVariable('tis', 'd', ('z', 'y', 'x'))
ds.variables['lat'][:] = lat
ds.variables['lon'][:] = lon
ds.variables['p'][:] = p
ds.variables['s'][:] = s
#vec=range(215,219)
#vec=range(219,223)
stats=[[] for i in range(len(vec))]
for jj in range(len(vec)):
ddir='../run'+str(vec[jj])+'/';
sname=ddir+'saves/save0.00e00.517.085.nc';
statsname=ddir+'saves/timestats.nc';
aname=ddir+'saves/avfld0.00e00.517.085.nc';
dname=ddir+'saves/D.517.85.2.nc';
gname=ddir+'saves/grid.517.85.nc';
grdname=ddir+'data/grd.nc';
spngname=ddir+'data/sponge.nc';
ininame=ddir+'data/init.nc';
ff=NF(dname,'r')
D=ff.variables['D'][:]
ff.close()
jmid=np.argmax(D[:,0])
isill=np.argwhere(D[jmid,:]==Ds)[0]
inarrow=np.argwhere(D[jmid,:]==Dn)[0]
iexit=np.argwhere(D[10,inarrow:]>1)[0]+inarrow-1 #index of strait exit
ff=NF(ininame,'r')
e_ini=ff.variables['ETA'][1,10,-1]
yh=ff.variables['yh'][:]*1e-3
ff.close()
ff=NF(sname,'r')
e=ff.variables['e'][-tind:,1,jmid,:]
fig = plt.figure(figsize=(fac * 9.2, fac * 3.2))
g = []
cblevs = []
for jj in range(len(vec)):
print 'processing ' + str(jj) + ' of ' + str(len(vec))
ddir = '../run' + str(vec[jj]) + '/'
sname = ddir + 'saves/save0.00e00.517.085.nc'
aname = ddir + 'saves/avfld0.00e00.517.085.nc'
gname = ddir + 'saves/grid.517.85.nc'
gname1 = ddir + 'data/grd.nc'
ininame = ddir + 'data/init.nc'
dname = ddir + 'saves/D.517.85.2.nc'
ff = NF(ininame, 'r')
xh = ff.variables['xh'][:] * 1e-3
yh = ff.variables['yh'][:] * 1e-3
ff.close()
ff = NF(aname, 'r')
e = ff.variables['etm'][-tind:, ifc, :, :]
ff.close()
ff = NF(gname1, 'r')
D = ff.variables['D'][:]
ff.close()
ff = NF(dname, 'r')
r2 = ff.variables['R'][1]
ff.close()
handles = []
col = ['b', 'g', 'r']
for dr, icol in zip([light, basic, dense], range(3)):
print dr
q = []
qstd = []
eta_exit = []
for ii in range(4):
ddir = '../run' + str(dr[ii]) + '/'
sname = ddir + 'saves/save0.00e00.517.085.nc'
aname = ddir + 'saves/avfld0.00e00.517.085.nc'
dname = ddir + 'saves/D.517.85.2.nc'
gname = ddir + 'saves/grid.517.85.nc'
ff = NF(dname, 'r')
D = ff.variables['D'][:]
ff.close()
jmid = np.argmax(D[:, 0])
inarrow = np.argwhere(D[jmid, :] == Dn)[0]
iexit = np.argwhere(
D[10, inarrow:] > 1)[0] + inarrow - 1 #index of strait exit
ff = NF(aname, 'r')
etm = ff.variables['etm'][-tind:, 1, jmid, :]
ff.close()
em_exit = np.mean(etm[:, iexit], axis=0)
U1m, U2m, U1std, U2std = volume_flux(sname, gname, tind, inarrow)
q.append(U1m)
#from Scientific.IO.NetCDF import NetCDFFile as NF from netCDF4 import Dataset as NF import matplotlib.pyplot as plt import numpy as np import mod_data as md import os as os import inspect as inspect rundir = os.path.dirname(inspect.getfile(inspect.currentframe())) grdname = rundir + '/../data/grd.nc' spngname = rundir + '/../data/sponge.nc' grid = NF(grdname, 'r') h = grid.variables['D'][:] grid.close() idamp = np.zeros(h.shape) #dmp=1./77. dmp = 1e-4 #dmp=0.; #dmp=1./20; n = 15 nv = dmp * np.linspace(1, 0, n) [x1, x2] = np.meshgrid(nv, np.arange(h.shape[0])) idamp[:, :n] = x1 dmp = 2.5e-5 n = 150 nv = dmp * np.linspace(1, 0, n) [x1, x2] = np.meshgrid(nv, np.arange(h.shape[0]))
# Isotropic grid
gibRadEarth=6371e3;
#gibDx=4e3;
gibDx=2e3;
dl = ((gibDx/gibRadEarth)/np.cos(36*np.pi/180))*180/np.pi;
lon=np.arange(lonmin,lonmax,dl);
i=0;
lat=[latmin];
while lat[-1]<=latmax:
i=i+1;
b=[lat[i-1]+dl*np.cos(lat[i-1]*np.pi/180)]
lat=np.r_[lat,b];
ff = NF('./ETOPO1_Ice_g_gdal.grd', 'r')
x=np.linspace(-180.,180.,360*60+1);
y=np.linspace(-90.,90.,180*60+1);
xi=np.where((x>lonmin) & (x < lonmax))[0];
xi=np.arange(xi[0]-4,xi[-1]+4)
yi=np.where((y>latmin) & (y < latmax))[0];
yi=np.arange(yi[0]-4,yi[-1]+4)
x1=np.arange(np.size(yi))
x2=np.arange(np.size(yi))
for j in np.arange(0,np.size(yi)):
x1[j]=np.size(x)*(np.size(y)-yi[j])+xi[0];
x2[j]=np.size(x)*(np.size(y)-yi[j])+xi[-1];
